Search results for: oriented object database (db4o)

Authors: Kunchit Pirapake

Abstract:

Application of Geo-Informatic technology in land tenure and land use on the economic crop area, to create sustainable land, access to the area, and produce sustainable food for the demand of its people in the community. The research objectives are to 1) apply Geo-Informatic Technology on land ownership and agricultural land use (cash crops) in the research area, 2) create GIS database on land ownership and land use, 3) create database of an online Geoinformation system on land tenure and land use. The results of this study reveal that, first; the study area is on high slope, mountains and valleys. The land is mainly in the forest zone which was included in the Forest Act 1941 and National Conserved Forest 1964. Residents gained the rights to exploit the land passed down from their ancestors. The practice was recognized by communities. The land was suitable for cultivating a wide variety of economic crops that was the main income of the family. At present the local residents keep expanding the land to grow cash crops. Second; creating a database of the geographic information system consisted of the area range, announcement from the Interior Ministry, interpretation of satellite images, transportation routes, waterways, plots of land with a title deed available at the provincial land office. Most pieces of land without a title deed are located in the forest and national reserve areas. Data were created from a field study and a land zone determined by a GPS. Last; an online Geo-Informatic System can show the information of land tenure and land use of each economic crop. Satellite data with high resolution which could be updated and checked on the online Geo-Informatic System simultaneously.

Keywords: Geo-Informatic Technology, Land Tenure, Online Geo-Informatic System, Land Use of cash crops.

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Authors: P. Joyce Beryl Princess, Y. Harold Robinson

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Image Processing is a structure of Signal Processing for which the input is the image and the output is also an image or parameter of the image. Image Resolution has been frequently referred as an important aspect of an image. In Image Resolution Enhancement, images are being processed in order to obtain more enhanced resolution. To generate highly resoluted image for a low resoluted input image with high PSNR value. Stationary Wavelet Transform is used for Edge Detection and minimize the loss occurs during Downsampling. Inverse Discrete Wavelet Transform is to get highly resoluted image. Highly resoluted output is generated from the Low resolution input with high quality. Noisy input will generate output with low PSNR value. So Noisy resolution enhancement technique has been used for adaptive sub-band thresholding is used. Downsampling in each of the DWT subbands causes information loss in the respective subbands. SWT is employed to minimize this loss. Inverse Discrete wavelet transform (IDWT) is to convert the object which is downsampled using DWT into a highly resoluted object. Used Image denoising and resolution enhancement techniques will generate image with high PSNR value. Our Proposed method will improve Image Resolution and reached the optimized threshold.

Keywords: Image Processing, Inverse Discrete wavelet transform, PSNR.

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Authors: Z. Ezzouine, A. Nakheli

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This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: Electromagnetic sensor, data acquisition, accurately, position measurement.

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Authors: Vishal Awasthi, Atul Kumar Agnihotri

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Face is a non-intrusive strong biometrics for identification of original and dummy facial by different artificial means. Face recognition is extremely important in the contexts of computer vision, psychology, surveillance, pattern recognition, neural network, content based video processing. The availability of a widespread face database is crucial to test the performance of these face recognition algorithms. The openly available face databases include face images with a wide range of poses, illumination, gestures and face occlusions but there is no dummy face database accessible in public domain. This paper presents a face detection algorithm based on the image segmentation in terms of distance from a fixed point and template matching methods. This proposed work is having the most appropriate number of nodal points resulting in most appropriate outcomes in terms of face recognition and detection. The time taken to identify and extract distinctive facial features is improved in the range of 90 to 110 sec. with the increment of efficiency by 3%.

Keywords: Face recognition, Principal Component Analysis, PCA, Linear Discriminant Analysis, LDA, Improved Support Vector Machine, iSVM, elastic bunch mapping technique.

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Authors: Atef. A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

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Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronic color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to act as the main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam fixed at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works accurately under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: Robotics manipulator, 5-DOF manipulator, image processing, Color sorting, Pick-and-place.

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Authors: LC Chong , A Yaacob, MH Rosli, Y Adam, A Yusuf , MS Omar-Fauzee, N Sutresna, Berliana, HH Pramono, M Nazrul-Hakim

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Currently, there is no database or local norms for the physical performance of Malaysian rugby players. This database or norms are vital for Malaysian-s sports development as programs can be setup to improve the current status. This pilot study was conducted to evaluate the status of our semi professional rugby players. The rugby players were randomly selected from the Malaysian National team and several clubs in the Klang valley, Kuala Lumpur Malaysia. 54 male rugby players (Age: 24.41 ± 4.06 years) were selected for this pilot study. Height, bodyweight, percentage body fat and body mass index (BMI) and several other physical tests were performed. Results from the BLEEP test revealed an average of level 9, shuttle 2 for the players. Interestingly, forwards were taller, heavier, and had lower maximal aerobic power than backs in the same team. In conclusion, the physical characteristics of the rugby players were much lower when compared to international players from other countries. From this pilot study, the physical performance of the Malaysian team must be improved in order to further develop the sports.

Keywords: Rugby, Malaysia, Fitness, Collision sports

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Authors: Mustafa S. Fawad, Wang Wencheng, Wu Enhua

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Shadows add great amount of realism to a scene and many algorithms exists to generate shadows. Recently, Shadow volumes (SVs) have made great achievements to place a valuable position in the gaming industries. Looking at this, we concentrate on simple but valuable initial partial steps for further optimization in SV generation, i.e.; model simplification and silhouette edge detection and tracking. Shadow volumes (SVs) usually takes time in generating boundary silhouettes of the object and if the object is complex then the generation of edges become much harder and slower in process. The challenge gets stiffer when real time shadow generation and rendering is demanded. We investigated a way to use the real time silhouette edge detection method, which takes the advantage of spatial and temporal coherence, and exploit the level-of-details (LOD) technique for reducing silhouette edges of the model to use the simplified version of the model for shadow generation speeding up the running time. These steps highly reduce the execution time of shadow volume generations in real-time and are easily flexible to any of the recently proposed SV techniques. Our main focus is to exploit the LOD and silhouette edge detection technique, adopting them to further enhance the shadow volume generations for real time rendering.

Keywords: LOD, perception, Shadow Volumes, SilhouetteEdge, Spatial and Temporal coherence.

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Authors: Yung-Chien Sun, O. Grant Clark

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In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

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Authors: Hossein Heidari Tabrizi, Azizeh Chalak

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The present study examined how translation teachers develop final tests as measures for checking on the quality of students’ academic translation in Iranian context. To achieve this goal, thirty experienced male and female translation teachers from the four types of the universities offering the program were invited to an in-depth 30-minute one-session semi-structured interview. The responses provided showed how much discrepancy exists among the Iranian translation teachers (as developers of final translation tests), who are least informed with the current translation evaluation methods. It was also revealed that the criteria they use for developing such tests and scoring student translations are not theory-driven but are highly subjective, mainly based on their personal experience and intuition. Hence, the quality and accountability of such tests are under serious question. The results also confirmed that the dominant method commonly and currently practiced is the purely essay-type format. To remedy the situation, some suggestions are in order. As part of the solution, to improve the reliability and validity of such tests, the present summative, product-oriented evaluation should be accompanied with some formative, process-oriented methods of evaluation. Training the teachers and helping them get acquainted with modern principles of translation evaluation as well as the existing models, and rating scales does improve the quality of academic translation evaluation.

Keywords: Iranian universities, students’ academic translations, translation final tests, undergraduate translation programs.

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Authors: Tzu-Hsin Liu

Abstract:

This study adopts a qualitative approach, which engages in the dialectical discussion on two levels of dyad opposite views. The first level of the dyad opposite views is the Western strategic perspective and the Eastern Tai-Chi thinking. The second level of the dyad opposite views is resource-based view and resource dependence theory. This study concludes the resource-oriented actions for competitive advantage as the metaphor of Tai-Chi consisted of yin and yang. This study argues that the focal firm should adopt bridging strategy during the core competence development period because its core competence development is likely to meet its competitor’s needs of exploring strategy during the competitor’s external resource development stage. In addition, the focal firm should adopt buffering strategy during the external resource development period to prevent its competitor’s the exploiting strategy from attack during the competitor’s core competence development stage. Consequently, this study takes a significant first step toward a novel contextualize understanding of resource development based on strategic perspective and Tai-Chi thinking providing more fully sustainable strategy for competitive advantage.

Keywords: Competitive advantage, resource-based view, resource dependence theory, strategic perspective, Tai-Chi thinking.

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Authors: Jaydip M. Desai, Antonio Valdevit, Arthur Ritter

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Robotic surgery is used to enhance minimally invasive surgical procedure. It provides greater degree of freedom for surgical tools but lacks of haptic feedback system to provide sense of touch to the surgeon. Surgical robots work on master-slave operation, where user is a master and robotic arms are the slaves. Current, surgical robots provide precise control of the surgical tools, but heavily rely on visual feedback, which sometimes cause damage to the inner organs. The goal of this research was to design and develop a realtime Simulink based robotic system to study force feedback mechanism during instrument-object interaction. Setup includes three VelmexXSlide assembly (XYZ Stage) for three dimensional movement, an end effector assembly for forceps, electronic circuit for four strain gages, two Novint Falcon 3D gaming controllers, microcontroller board with linear actuators, MATLAB and Simulink toolboxes. Strain gages were calibrated using Imada Digital Force Gauge device and tested with a hard-core wire to measure instrument-object interaction in the range of 0-35N. Designed Simulink model successfully acquires 3D coordinates from two Novint Falcon controllers and transfer coordinates to the XYZ stage and forceps. Simulink model also reads strain gages signal through 10-bit analog to digital converter resolution of a microcontroller assembly in real time, converts voltage into force and feedback the output signals to the Novint Falcon controller for force feedback mechanism. Experimental setup allows user to change forward kinematics algorithms to achieve the best-desired movement of the XYZ stage and forceps. This project combines haptic technology with surgical robot to provide sense of touch to the user controlling forceps through machine-computer interface.

Keywords: Haptic feedback, MATLAB, Simulink, Strain Gage, Surgical Robot.

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Authors: I. Sarenkova, I. Ciprovica, I. Cinkmanis

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Lactobionic acid is a disaccharide formed from gluconic acid and galactose, and produced by oxidation of lactose. Productivity of lactobionic acid by microbial synthesis can be affected by various factors, and one of them is a presence of potassium, magnesium and manganese ions. In order to extend lactobionic acid production efficiency, it is necessary to increase the yield of lactobionic acid by optimising the fermentation conditions and available substrates for Pseudomonas taetrolens growth. The object of the research was to determinate the application of K₂HPO₄, MnSO₄, MgSO₄ × 7H₂O salts in different concentration for effective lactose oxidation to lactobionic acid by Pseudomonas taetrolens. Pseudomonas taetrolens NCIB 9396 (NCTC, England) and Pseudomonas taetrolens DSM 21104 (DSMZ, Germany) were used for the study. The acid whey was used as the study object. The content of lactose in whey samples was determined using MilcoScan^TM Mars (Foss, Denmark) and high performance liquid chromatography (Shimadzu LC 20 Prominence, Japan). The content of lactobionic acid in whey samples was determined using the high performance liquid chromatography. The impact of studied salts differs, Mn²⁺ and Mg²⁺ ions enhanced fermentation instead of K⁺ ions. Results approved that Mn²⁺ and Mg²⁺ ions are necessary for Pseudomonas taetrolens growth. The study results will help to improve the effectiveness of lactobionic acid production with Pseudomonas taetrolens NCIB 9396 and DSM 21104.

Keywords: lactobionic acid, lactose oxidation, Pseudomonas taetrolens, whey.

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Authors: Jiaqi Yan, Sherry Sun, Huaiqing Wang, Zhongsheng Hua

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In the highly competitive and rapidly changing global marketplace, independent organizations and enterprises often come together and form a temporary alignment of virtual enterprise in a supply chain to better provide products or service. As firms adopt the systems approach implicit in supply chain management, they must manage the quality from both internal process control and external control of supplier quality and customer requirements. How to incorporate quality management of upstream and downstream supply chain partners into their own quality management system has recently received a great deal of attention from both academic and practice. This paper investigate the collaborative feature and the entities- relationship in a supply chain, and presents an ontology of collaborative supply chain from an approach of aligning service-oriented framework with service-dominant logic. This perspective facilitates the segregation of material flow management from manufacturing capability management, which provides a foundation for the coordination and integration of the business process to measure, analyze, and continually improve the quality of products, services, and process. Further, this approach characterizes the different interests of supply chain partners, providing an innovative approach to analyze the collaborative features of supply chain. Furthermore, this ontology is the foundation to develop quality management system which internalizes the quality management in upstream and downstream supply chain partners and manages the quality in supply chain systematically.

Keywords: Ontology, supply chain quality management, service-oriented architecture, service-dominant logic.

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Authors: Charles D. Otine, Samuel B. Kucel, Lena Trojer

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Selecting the data modeling technique for an information system is determined by the objective of the resultant data model. Dimensional modeling is the preferred modeling technique for data destined for data warehouses and data mining, presenting data models that ease analysis and queries which are in contrast with entity relationship modeling. The establishment of data warehouses as components of information system landscapes in many organizations has subsequently led to the development of dimensional modeling. This has been significantly more developed and reported for the commercial database management systems as compared to the open sources thereby making it less affordable for those in resource constrained settings. This paper presents dimensional modeling of HIV patient information using open source modeling tools. It aims to take advantage of the fact that the most affected regions by the HIV virus are also heavily resource constrained (sub-Saharan Africa) whereas having large quantities of HIV data. Two HIV data source systems were studied to identify appropriate dimensions and facts these were then modeled using two open source dimensional modeling tools. Use of open source would reduce the software costs for dimensional modeling and in turn make data warehousing and data mining more feasible even for those in resource constrained settings but with data available.

Keywords: About Database, Data Mining, Data warehouse, Dimensional Modeling, Open Source.

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Authors: Mohamed Moheyeldin Mahmoud

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Egypt suffers from a severe shortage of data and charts concerning the physical dimensions, measurements, qualities and consumer behavior. The shortage of needed information and appropriate methods has forced the Egyptian designer to use any other foreign standard when designing a product for the Egyptian consumer which has led to many problems. The urgently needed database concerning the physical specifications, measurements of the Egyptian consumers, as well as the need to support the Ergonomics given courses in many colleges and institutes with the latest technologies, is stated as the research problem. Descriptive analytical method relying on the compiling, comparing and analyzing of information and facts in order to get acceptable perceptions, ideas and considerations is the used methodology by the researcher. The research concludes that: 1. Good interaction relationship between users and products shows the success of that product. 2. An integration linkage between the most prominent fields of science specially Ergonomics, Interaction Design and Ethnography should be encouraged to provide an ultimately updated database concerning the nature, specifications and environment of the Egyptian consumer, in order to achieve a higher benefit for both user and product. 3. Chinese economic policy based on the study of market requirements long before any market activities should be emulated. 4. Using Ethnography supports the design activities creating new products or updating existent ones through measuring the compatibility of products with their environment and user expectations, While contracting a joint cooperation between military colleges, sports education institutes from one side, and design institutes from the other side to provide an ultimately updated (annually updated) database concerning some specifications about students of both sexes applying in those institutes (height, weight, etc.) to provide the Industrial designer with the needed information when creating a new product or updating an existing one concerning that category is recommended by the researcher.

Keywords: Adapt ergonomics, ethnography, interaction design.

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Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida

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This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatiotemporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.

Keywords: WSN, database spatio-temporal, GIS, web-mapping, indicator of drought.

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: Big data, k-NN, machine learning, traffic speed prediction.

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Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

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In this paper, we propose an improved fast search algorithm using combined histogram features and temporal division method for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal feature which is robust to color distortion. Combined with active search [4], a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by 6 hours of video to search for given 200 MPEG video clips which each length is 30 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 120ms, and Equal Error Rate (ERR) of 1% is achieved, which is more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, Adjacent pixel intensity differencequantization (APIDQ), DC image, Histogram feature.

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Authors: V. Charaia

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From the strategic point of view, not all Foreign Direct Investments (FDIs) are always positively benefiting the host economy, i.e. not all Multinational Enterprises (MNEs) are promoting local/host economies. FDI could have different impact on different sectors of the economy, based not only on annual investment amount, but MNE motivations and peculiarities of the host economy in particular. FDI analysis based only on its amount can lead to incorrect decisions, it is much more important to understand the essence of investment. Consequently, our research is oriented on MNE’s motivations, answering which sectors are most popular among international investors and why, what motivated them to invest into one or another business. Georgian economy for the last period of time is attracting more and more efficiency seeking investments, which could be translated as - concentrating production in a limited number of locations to supply various markets, while benefiting local economy with: new technologies, employment, exports diversification, increased income for the local economy and so on. Foreign investors and MNEs in particular are no longer and not so much interested in the resource seeking investments, which was the case for Georgia in the last decade of XX century. Despite the fact of huge progress for the Georgian economy, still there is a room for foreign investors to make a local market oriented investments. The local market is still rich in imported products, which should be replaced by local ones. And the last but not the least important issue is that approximately 30% of all FDIs in Georgia according to this research are “efficiency seeking” investments, which is an enormous progress and a hope for future Georgian success.

Keywords: Investments, MNE, FDI motivations, Georgian economy.

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Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

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Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: Clusters of Microcalcifications, Ductal Carcinoma in Situ, Least-Square Support Vector Machine, Particle Swarm Optimization.

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Authors: Agus Harjoko, Sri Hartati, Henry Dwiyasa

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There have been numerous implementations of security system using biometric, especially for identification and verification cases. An example of pattern used in biometric is the iris pattern in human eye. The iris pattern is considered unique for each person. The use of iris pattern poses problems in encoding the human iris. In this research, an efficient iris recognition method is proposed. In the proposed method the iris segmentation is based on the observation that the pupil has lower intensity than the iris, and the iris has lower intensity than the sclera. By detecting the boundary between the pupil and the iris and the boundary between the iris and the sclera, the iris area can be separated from pupil and sclera. A step is taken to reduce the effect of eyelashes and specular reflection of pupil. Then the four levels Coiflet wavelet transform is applied to the extracted iris image. The modified Hamming distance is employed to measure the similarity between two irises. This research yields the identification success rate of 84.25% for the CASIA version 1.0 database. The method gives an accuracy of 77.78% for the left eyes of MMU 1 database and 86.67% for the right eyes. The time required for the encoding process, from the segmentation until the iris code is generated, is 0.7096 seconds. These results show that the accuracy and speed of the method is better than many other methods.

Keywords: Biometric, iris recognition, wavelet transform.

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Authors: B. Soleimani

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Paleoclimate was reconstructed by the clay mineral assemblages of shale units of Pabdeh (Paleocene- Oligocene), Gurpi (Upper Cretaceous), Kazhdumi (Albian-Cenomanian) and Gadvan (Aptian-Neocomian) formations in the Bangestan anticline. To compare with clay minerals assemblages in these formations, selected samples also taken from available formations in drilled wells in Ahvaz, Marun, Karanj, and Parsi oil fields. Collected samples prepared using standard clay mineral methodology. They were treated as normal, glycolated and heated oriented glass slides. Their identification was made on X-Ray diffractographs. Illite % varies from 8 to 36. Illite quantity increased from Pabdeh to Gurpi Formation. This may be due to dominant dry climate. Kaolinite is in range of 12-49%. Its variation style in different formations could be a marker of climate changes from wet to dry which is supported by the lithological changes. Chlorite (4-28%) can also be detected in those samples without any kaolinite. Mixed layer minerals as the mixture of illite-chlorite and illite-vermiculite-montmorillonite are varied from 6 to 36%, decreased during Kazhdumi deposition from the base to the top. This result may be according to decreasing of illite leaching process. Vermiculite was also determined in very less quantity and found in those units without kaolinite. Montmorillonite varies from 8 to 43%, and its presence is due to terrestrial depositional condition. Stratigraphical documents is also supported this idea that clay mineral distribution is a function of the climate changes. It seems, thus, the present results can be indicated a possible procedure for ancient climate changes evaluation.

Keywords: Clay Minerals, Paleoclimate, XRD, oriented slide

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Authors: Deepti Tamrakar, Pritee Khanna

Abstract:

This manuscript presents, palmprint recognition by combining different texture extraction approaches with high accuracy. The Region of Interest (ROI) is decomposed into different frequencytime sub-bands by wavelet transform up-to two levels and only the approximate image of two levels is selected, which is known as Approximate Image ROI (AIROI). This AIROI has information of principal lines of the palm. The Competitive Index is used as the features of the palmprint, in which six Gabor filters of different orientations convolve with the palmprint image to extract the orientation information from the image. The winner-take-all strategy is used to select dominant orientation for each pixel, which is known as Competitive Index. Further, PCA is applied to select highly uncorrelated Competitive Index features, to reduce the dimensions of the feature vector, and to project the features on Eigen space. The similarity of two palmprints is measured by the Euclidean distance metrics. The algorithm is tested on Hong Kong PolyU palmprint database. Different AIROI of different wavelet filter families are also tested with the Competitive Index and PCA. AIROI of db7 wavelet filter achievs Equal Error Rate (EER) of 0.0152% and Genuine Acceptance Rate (GAR) of 99.67% on the palm database of Hong Kong PolyU.

Keywords: DWT, EER, Euclidean Distance, Gabor filter, PCA, ROI.

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Authors: Shih-Wen Hsiao, Yi-Cheng Tsao

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In the field of reverse engineering and creative industries, applying 3D scanning process to obtain geometric forms of the objects is a mature and common technique. For instance, organic objects such as faces and nonorganic objects such as products could be scanned to acquire the geometric information for further application. However, although the data resolution of 3D scanning device is increasing and there are more and more abundant complementary applications, the penetration rate of 3D scanning for the public is still limited by the relative high price of the devices. On the other hand, Kinect, released by Microsoft, is known for its powerful functions, considerably low price, and complete technology and database support. Therefore, related studies can be done with the applying of Kinect under acceptable cost and data precision. Due to the fact that Kinect utilizes optical mechanism to extracting depth information, limitations are found due to the reason of the straight path of the light. Thus, various angles are required sequentially to obtain the complete 3D information of the object when applying a single Kinect for 3D scanning. The integration process which combines the 3D data from different angles by certain algorithms is also required. This sequential scanning process costs much time and the complex integration process often encounter some technical problems. Therefore, this paper aimed to apply multiple Kinects simultaneously on the field of developing a rapid 3D mannequin scan platform and proposed suggestions on the number and angles of Kinects. In the content, a method of establishing the coordination based on the relation between mannequin and the specifications of Kinect is proposed, and a suggestion of angles and number of Kinects is also described. An experiment of applying multiple Kinect on the scanning of 3D mannequin is constructed by Microsoft API, and the results show that the time required for scanning and technical threshold can be reduced in the industries of fashion and garment design.

Keywords: 3D scan, depth sensor, fashion and garment design, mannequin, multiple kinect sensor.

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Authors: Mohamed Gouskir, Belaid Bouikhalene, Hicham Aissaoui, Benachir Elhadadi

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In this paper, we present an application of Riemannian geometry for processing non-Euclidean image data. We consider the image as residing in a Riemannian manifold, for developing a new method to brain edge detection and brain extraction. Automating this process is a challenge due to the high diversity in appearance brain tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based anisotropic diffusion tensor for the segmentation task by integrating both image edge geometry and Riemannian manifold (geodesic, metric tensor) to regularize the convergence contour and extract complex anatomical structures. We check the accuracy of the segmentation results on simulated brain MRI scans of single T1-weighted, T2-weighted and Proton Density sequences. We validate our approach using two different databases: BrainWeb database, and MRI Multiple sclerosis Database (MRI MS DB). We have compared, qualitatively and quantitatively, our approach with the well-known brain extraction algorithms. We show that using a Riemannian manifolds to medical image analysis improves the efficient results to brain extraction, in real time, outperforming the results of the standard techniques.

Keywords: Riemannian manifolds, Riemannian Tensor, Brain Segmentation, Non-Euclidean data, Brain Extraction.

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Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

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The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: Autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS.

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Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data of the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as «signaling parameters» (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of COTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources, but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as rule. This report contains describing of the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems.

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Authors: Bello Abdullahi, Yahaya M. Ibrahim, Ahmed D. Ibrahim, Kabir Bala

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Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Keywords: e-Tendering, e-Procurement, public tendering, tender evaluation, tender evaluation committee, web-based group decision support system.

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Authors: Fernando C. Monteiro, Vasco Cadavez

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This paper presents a method for the detection of OD in the retina which takes advantage of the powerful preprocessing techniques such as the contrast enhancement, Gabor wavelet transform for vessel segmentation, mathematical morphology and Earth Mover-s distance (EMD) as the matching process. The OD detection algorithm is based on matching the expected directional pattern of the retinal blood vessels. Vessel segmentation method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel-s feature vector. Feature vectors are composed of the pixel-s intensity and 2D Gabor wavelet transform responses taken at multiple scales. A simple matched filter is proposed to roughly match the direction of the vessels at the OD vicinity using the EMD. The minimum distance provides an estimate of the OD center coordinates. The method-s performance is evaluated on publicly available DRIVE and STARE databases. On the DRIVE database the OD center was detected correctly in all of the 40 images (100%) and on the STARE database the OD was detected correctly in 76 out of the 81 images, even in rather difficult pathological situations.

Keywords: Diabetic retinopathy, Earth Mover's distance, Gabor wavelets, optic disc detection, retinal images

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Authors: Abhimanyu Pati, Prabir K. Bandyopadhyay

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The paper intends to highlight the significance of Digital Manufacturing (DM) strategy in support and achievement of business strategy and goals of any manufacturing organization. Towards this end, DM initiatives have been given a process perspective, while not undermining its technological significance, with a view to link its benefits directly with fulfilment of customer needs and expectations in a responsive and cost-effective manner. A digital process model has been proposed to categorize digitally enabled organizational processes with a view to create synergistic groups, which adopt and use digital tools having similar characteristics and functionalities. This will throw future opportunities for researchers and developers to create a unified technology environment for integration and orchestration of processes. Secondly, an effort has been made to apply “what” and “how” features of Quality Function Deployment (QFD) framework to establish the relationship between customers’ needs – both for external and internal customers, and the features of various digital processes, which support for the achievement of these customer expectations. The paper finally concludes that in the present highly competitive environment, business organizations cannot thrive to sustain unless they understand the significance of digital strategy and integrate it with their business strategy with a clearly defined implementation roadmap. A process-oriented approach to DM strategy will help business executives and leaders to appreciate its value propositions and its direct link to organization’s competitiveness.

Keywords: Digital manufacturing, digital process model, quality function deployment, business strategy.

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