Search results for: Frequent Feature

Authors: Zarita Zainuddin, Mohammed Mahmod Shuaib, Ibtesam M. Abu-Sulyman

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The social force model which belongs to the microscopic pedestrian studies has been considered as the supremacy by many researchers and due to the main feature of reproducing the self-organized phenomena resulted from pedestrian dynamic. The Preferred Force which is a measurement of pedestrian-s motivation to adapt his actual velocity to his desired velocity is an essential term on which the model was set up. This Force has gone through stages of development: first of all, Helbing and Molnar (1995) have modeled the original force for the normal situation. Second, Helbing and his co-workers (2000) have incorporated the panic situation into this force by incorporating the panic parameter to account for the panic situations. Third, Lakoba and Kaup (2005) have provided the pedestrians some kind of intelligence by incorporating aspects of the decision-making capability. In this paper, the authors analyze the most important incorporations into the model regarding the preferred force. They make comparisons between the different factors of these incorporations. Furthermore, to enhance the decision-making ability of the pedestrians, they introduce additional features such as the familiarity factor to the preferred force to let it appear more representative of what actually happens in reality.

Keywords: Pedestrian movement, social force model, preferredforce, familiarity.

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Authors: Rajamani Doraiswami, Lahouari Cheded

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Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: Keywords—Identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: Chaiwat Tantarangsee

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The purposes of this study are 1) to study the effects of participatory error correction process and 2) to find out the students’ satisfaction of such error correction process. This study is a Quasi Experimental Research with single group, in which data is collected 5 times preceding and following 4 experimental studies of participatory error correction process including providing coded indirect corrective feedback in the students’ texts with error treatment activities. Samples include 52 2nd year English Major students, Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat University. Tool for experimental study includes the lesson plan of the course; Reading and Writing English for Academic Purposes II, and tools for data collection include 5 writing tests of short texts and a questionnaire. Based on formative evaluation of the students’ writing ability prior to and after each of the 4 experiments, the research findings disclose the students’ higher scores with statistical difference at 0.00. Moreover, in terms of the effect size of such process, it is found that for mean of the students’ scores prior to and after the 4 experiments; d equals 0.6801, 0.5093, 0.5071, and 0.5296 respectively. It can be concluded that participatory error correction process enables all of the students to learn equally well and there is improvement in their ability to write short texts. Finally the students’ overall satisfaction of the participatory error correction process is in high level (Mean = 4.39, S.D. = 0.76).

Keywords: Coded indirect corrective feedback, participatory error correction process, error treatment.

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Authors: Sanjay Kanade, Danielle Camara, Dijana Petrovska-Delacretaz, Bernadette Dorizzi

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In this paper, a two factor scheme is proposed to generate cryptographic keys directly from biometric data, which unlike passwords, are strongly bound to the user. Hash value of the reference iris code is used as a cryptographic key and its length depends only on the hash function, being independent of any other parameter. The entropy of such keys is 94 bits, which is much higher than any other comparable system. The most important and distinct feature of this scheme is that it regenerates the reference iris code by providing a genuine iris sample and the correct user password. Since iris codes obtained from two images of the same eye are not exactly the same, error correcting codes (Hadamard code and Reed-Solomon code) are used to deal with the variability. The scheme proposed here can be used to provide keys for a cryptographic system and/or for user authentication. The performance of this system is evaluated on two publicly available databases for iris biometrics namely CBS and ICE databases. The operating point of the system (values of False Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set by properly selecting the error correction capacity (ts) of the Reed- Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096% and FRR is 0.76%.

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Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: Data fusion, Dempster-Shafer theory, data mining, event detection.

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Authors: Javed Khan, Aamir Saeed Malik, Nidal Kamel, Sarat Chandra Dass, Azura Mohd Affandi

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Low contrast images can result from the wrong setting of image acquisition or poor illumination conditions. Such images may not be visually appealing and can be difficult for feature extraction. Contrast enhancement of color images can be useful in medical area for visual inspection. In this paper, a new technique is proposed to improve the contrast of color images. The RGB (red, green, blue) color image is transformed into normalized RGB color space. Adaptive histogram equalization technique is applied to each of the three channels of normalized RGB color space. The corresponding channels in the original image (low contrast) and that of contrast enhanced image with adaptive histogram equalization (AHE) are morphed together in proper proportions. The proposed technique is tested on seventy color images of acne patients. The results of the proposed technique are analyzed using cumulative variance and contrast improvement factor measures. The results are also compared with decorrelation stretch. Both subjective and quantitative analysis demonstrates that the proposed techniques outperform the other techniques.

Keywords: Contrast enhancement, normalized RGB, adaptive histogram equalization, cumulative variance.

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Authors: Omer Nebil Yaveroglu, Tolga Can

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In this study, a high accuracy protein-protein interaction prediction method is developed. The importance of the proposed method is that it only uses sequence information of proteins while predicting interaction. The method extracts phylogenetic profiles of proteins by using their sequence information. Combining the phylogenetic profiles of two proteins by checking existence of homologs in different species and fitting this combined profile into a statistical model, it is possible to make predictions about the interaction status of two proteins. For this purpose, we apply a collection of pattern recognition techniques on the dataset of combined phylogenetic profiles of protein pairs. Support Vector Machines, Feature Extraction using ReliefF, Naive Bayes Classification, K-Nearest Neighborhood Classification, Decision Trees, and Random Forest Classification are the methods we applied for finding the classification method that best predicts the interaction status of protein pairs. Random Forest Classification outperformed all other methods with a prediction accuracy of 76.93%

Keywords: Protein Interaction Prediction, Phylogenetic Profile, SVM , ReliefF, Decision Trees, Random Forest Classification

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Authors: Jatin Kumar Choudhary, Naren Rayala, Abbas Eslami Kiasari, Fahimeh Jafari

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Great Britain has one of the safest road networks in the world. However, the consequences of any death or serious injury are devastating for loved ones, as well as for those who help the severely injured. This paper aims to analyse Great Britain's road safety situation and show the response measures for areas where the total damage caused by accidents can be significantly and quickly reduced. For the past 30 years, the UK has had a good record in reducing fatalities over the past 30 years, there is still a considerable number of road deaths. The government continues to scale back road deaths empowering responsible road users by identifying and prosecuting the parameters that make the roads less safe. This study represents an exploratory analysis with deep insights which could provide policy makers with invaluable insights into how accidents happen and how they can be mitigated. We use STATS19 data published by the UK government. Since we need more information about locations which is not provided in STATA19, we first expand the features of the dataset using OpenStreetMap and Visual Crossing. This paper also provides a discussion regarding new road safety methods.

Keywords: Road safety, data analysis, OpenStreetMap, feature expanding.

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Authors: Jukka Heinonen

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Higher density reduces distances, private car dependency and thus reduces greenhouse gas emissions (GHGs). As a result, increased density has been given a central role among urban development targets. However, it is not just travel behavior that changes along with density. Rather, the consumption patterns, or overall lifestyles, change along with changing urban structure, particularly with changing housing types and consumption opportunities. Furthermore, elevated consumption of services, more frequent flying and less intra-household sharing have been shown to potentially outweigh the gains from reduced driving in more dense urban settlements. In this study, the geography of carbon footprints (CFs) in California is analyzed paying close attention to the household size differences and the resulting economies-of-scale advantages and disadvantages. A hybrid life cycle assessment (LCA) framework is employed together with consumer expenditure data to assess the CFs. According to the study, small urban households have the highest CFs in California. Their transport related emissions are significantly lower than those of the residents of less urbanized areas, but higher emissions from other consumption categories, together with the low degree of sharing of goods, overweigh the gains. Two functional units, per capita and per household, are used to analyze the CFs and to demonstrate the importance of household size. The lifestyle impacts visible through the consumption data are also discussed. The study suggests that there are still significant gaps in our understanding of the premises of low-carbon human settlements.

Keywords: Carbon footprint, life cycle assessment, consumption, lifestyle, household size, economies-of-scale.

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Authors: Parvinder S. Sandhu, Hardeep Singh

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Automatic reusability appraisal could be helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable components from existing legacy systems; that can save cost of developing the software from scratch. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this paper, we have mentioned two-tier approach by studying the structural attributes as well as usability or relevancy of the component to a particular domain. Latent semantic analysis is used for the feature vector representation of various software domains. It exploits the fact that FeatureVector codes can be seen as documents containing terms -the idenifiers present in the components- and so text modeling methods that capture co-occurrence information in low-dimensional spaces can be used. Further, we devised Neuro- Fuzzy hybrid Inference System, which takes structural metric values as input and calculates the reusability of the software component. Decision tree algorithm is used to decide initial set of fuzzy rules for the Neuro-fuzzy system. The results obtained are convincing enough to propose the system for economical identification and retrieval of reusable software components.

Keywords: Clustering, ID3, LSA, Neuro-fuzzy System, SVD

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Authors: Haoyu Ma, Bin Hu, Mike Jackson, Jingzhi Yan, Wen Zhao

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In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.

Keywords: Sleep, Sleep stage, Automatic sleep scoring, Electroencephalography, Decision tree, Artificial neural network

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Authors: Fuyang Peng, Donghong Li

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The aim of information systems integration is to make all the data sources, applications and business flows integrated into the new environment so that unwanted redundancies are reduced and bottlenecks and mismatches are eliminated. Two issues have to be dealt with to meet such requirements: the software architecture that supports resource integration, and the adaptor development tool that help integration and migration of legacy applications. In this paper, a service-enabled dependable integration environment (SDIE), is presented, which has two key components, i.e., a dependable service integration platform and a legacy application integration tool. For the dependable platform for service integration, the service integration bus, the service management framework, the dependable engine for service composition, and the service registry and discovery components are described. For the legacy application integration tool, its basic organization, functionalities and dependable measures taken are presented. Due to its service-oriented integration model, the light-weight extensible container, the service component combination-oriented p-lattice structure, and other features, SDIE has advantages in openness, flexibility, performance-price ratio and feature support over commercial products, is better than most of the open source integration software in functionality, performance and dependability support.

Keywords: Application integration, dependability, legacy, SOA.

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Authors: Jun Seok Kim, Cheong-Sool Park, Jun-Geol Baek, Sung-Shick Kim

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Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.

Keywords: Control chart pattern recognition, Multi-resolution wavelet analysis, Bi-directional Kohonen network, Back-propagation network, Feature extraction.

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Authors: Atefeh Heydari, Mohammadali Tavakoli, Zuriati Ismail, Naomie Salim

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Seeking and sharing knowledge on online forums have made them popular in recent years. Although online forums are valuable sources of information, due to variety of sources of messages, retrieving reliable threads with high quality content is an issue. Majority of the existing information retrieval systems ignore the quality of retrieved documents, particularly, in the field of thread retrieval. In this research, we present an approach that employs various quality features in order to investigate the quality of retrieved threads. Different aspects of content quality, including completeness, comprehensiveness, and politeness, are assessed using these features, which lead to finding not only textual, but also conceptual relevant threads for a user query within a forum. To analyse the influence of the features, we used an adopted version of voting model thread search as a retrieval system. We equipped it with each feature solely and also various combinations of features in turn during multiple runs. The results show that incorporating the quality features enhances the effectiveness of the utilised retrieval system significantly.

Keywords: Content quality, Forum search, Thread retrieval, Voting techniques.

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Authors: Elena Krelja Kurelović, Jasminka Tomljanović, Vlatka Davidović

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The development of web technologies and mobile devices makes creating, accessing, using and sharing information or communicating with each other simpler every day. However, while the amount of information constantly increasing it is becoming harder to effectively organize and find quality information despite the availability of web search engines, filtering and indexing tools. Although digital technologies have overall positive impact on students’ lives, frequent use of these technologies and digital media enriched with dynamic hypertext and hypermedia content, as well as multitasking, distractions caused by notifications, calls or messages; can decrease the attention span, make thinking, memorizing and learning more difficult, which can lead to stress and mental exhaustion. This is referred to as “information overload”, “information glut” or “information anxiety”. Objective of this study is to determine whether students show signs of information overload and to identify the possible predictors. Research was conducted using a questionnaire developed for the purpose of this study. The results show that students frequently use technology (computers, gadgets and digital media), while they show moderate level of information literacy. They have sometimes experienced symptoms of information overload. According to the statistical analysis, higher frequency of technology use and lower level of information literacy are correlated with larger information overload. The multiple regression analysis has confirmed that the combination of these two independent variables has statistically significant predictive capacity for information overload. Therefore, the information science teachers should pay attention to improving the level of students’ information literacy and educate them about the risks of excessive technology use.

Keywords: Information overload, technology use, digital media, information literacy, students.

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Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Jörg Appenrodt, Bernd Michaelis

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Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.

Keywords: Computer Vision & Image Processing, Gesture Recognition, Pattern Recognition, Application

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Authors: Manas Ranjan Kabat, Manoj Kumar Patel, Chita Ranjan Tripathy

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Many multimedia communication applications require a source to transmit messages to multiple destinations subject to quality of service (QoS) delay constraint. To support delay constrained multicast communications, computer networks need to guarantee an upper bound end-to-end delay from the source node to each of the destination nodes. This is known as multicast delay problem. On the other hand, if the same message fails to arrive at each destination node at the same time, there may arise inconsistency and unfairness problem among users. This is related to multicast delayvariation problem. The problem to find a minimum cost multicast tree with delay and delay-variation constraints has been proven to be NP-Complete. In this paper, we propose an efficient heuristic algorithm, namely, Economic Delay and Delay-Variation Bounded Multicast (EDVBM) algorithm, based on a novel heuristic function, to construct an economic delay and delay-variation bounded multicast tree. A noteworthy feature of this algorithm is that it has very high probability of finding the optimal solution in polynomial time with low computational complexity.

Keywords: EDVBM, Heuristic algorithm, Multicast tree, QoS routing, Shortest path.

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Authors: Pisit Boonsrimuang, Arjin Numsomran, Tawil Paungma, Hideo Kobayashi

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One of the disadvantages of using OFDM is the larger peak to averaged power ratio (PAPR) in its time domain signal. The larger PAPR signal would course the fatal degradation of bit error rate performance (BER) due to the inter-modulation noise in the nonlinear channel. This paper proposes an improved DSI (Dummy Sequence Insertion) method, which can achieve the better PAPR and BER performances. The feature of proposed method is to optimize the phase of each dummy sub-carrier so as to reduce the PAPR performance by changing all predetermined phase coefficients in the time domain signal, which is calculated for data sub-carriers and dummy sub-carriers separately. To achieve the better PAPR performance, this paper also proposes to employ the time-frequency domain swapping algorithm for fine adjustment of phase coefficient of the dummy subcarriers, which can achieve the less complexity of processing and achieves the better PAPR and BER performances than those for the conventional DSI method. This paper presents various computer simulation results to verify the effectiveness of proposed method as comparing with the conventional methods in the non-linear channel.

Keywords: OFDM, PAPR, dummy sub-carriers, non-linear

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Authors: Mesut Gündüz, Ferruh Yildiz, Ayşe Onat

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In Geographic Information System, one of the sources of obtaining needed geographic data is digitizing analog maps and evaluation of aerial and satellite photos. In this study, a method will be discussed which can be used to extract vectorial features and creating vectorized drawing files for aerial photos. At the same time a software developed for these purpose. Converting from raster to vector is also known as vectorization and it is the most important step when creating vectorized drawing files. In the developed algorithm, first of all preprocessing on the aerial photo is done. These are; converting to grayscale if necessary, reducing noise, applying some filters and determining the edge of the objects etc. After these steps, every pixel which constitutes the photo are followed from upper left to right bottom by examining its neighborhood relationship and one pixel wide lines or polylines obtained. The obtained lines have to be erased for preventing confusion while continuing vectorization because if not erased they can be perceived as new line, but if erased it can cause discontinuity in vector drawing so the image converted from 2 bit to 8 bit and the detected pixels are expressed as a different bit. In conclusion, the aerial photo can be converted to vector form which includes lines and polylines and can be opened in any CAD application.

Keywords: Vectorization, Aerial Photos, Vectorized DrawingFile.

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Authors: Laimona Sliburyte

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The ever increasing product diversity and competition on the market of goods and services has dictated the pace of growth in the number of advertisements. Despite their admittedly diminished effectiveness over the recent years, advertisements remain the favored method of sales promotion. Consequently, the challenge for an advertiser is to explore every possible avenue of making an advertisement more noticeable, attractive and impellent for consumers. One way to achieve this is through invoking celebrity endorsements. On the one hand, the use of a celebrity to endorse a product involves substantial costs, however, on the other hand, it does not immediately guarantee the success of an advertisement. The question of how celebrities can be used in advertising to the best advantage is therefore of utmost importance. Celebrity endorsements have become commonplace: empirical evidence indicates that approximately 20 to 25 per cent of advertisements feature some famous person as a product endorser. The popularity of celebrity endorsements demonstrates the relevance of the topic, especially in the context of the current global economic downturn, when companies are forced to save in order to survive, yet simultaneously to heavily invest in advertising and sales promotion. The issue of the effective use of celebrity endorsements also figures prominently in the academic discourse. The study presented below is thus aimed at exploring what qualities (characteristics) of a celebrity endorser have an impact on the ffectiveness of the advertisement in which he/she appears and how.

Keywords: Advertising, celebrity, celebrity endorsements, effectiveness of celebrity.

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: Pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction.

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Authors: Luo Jin, Jin Fang

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Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it is failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits.

Keywords: The rural, sustainable renovation, restoration, psychology, memory.

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Authors: M. G. Papoutsidakis, G. Chamilothoris, F. Dailami, N. Larsen, A Pipe

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Due to their high power-to-weight ratio and low cost, pneumatic actuators are attractive for robotics and automation applications; however, achieving fast and accurate control of their position have been known as a complex control problem. A methodology for obtaining high position accuracy with a linear pneumatic actuator is presented. During experimentation with a number of PID classical control approaches over many operations of the pneumatic system, the need for frequent manual re-tuning of the controller could not be eliminated. The reason for this problem is thermal and energy losses inside the cylinder body due to the complex friction forces developed by the piston displacements. Although PD controllers performed very well over short periods, it was necessary in our research project to introduce some form of automatic gain-scheduling to achieve good long-term performance. We chose a fuzzy logic system to do this, which proved to be an easily designed and robust approach. Since the PD approach showed very good behaviour in terms of position accuracy and settling time, it was incorporated into a modified form of the 1st order Tagaki- Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler uses an input variable which automatically changes the PD gain values of the controller according to the frequency of repeated system operations. Performance of the new controller was significantly improved and the need for manual re-tuning was eliminated without a decrease in performance. The performance of the controller operating with the above method is going to be tested through a high-speed web network (GRID) for research purposes.

Keywords: Fuzzy logic, gain scheduling, leaky integrator, pneumatic actuator.

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Authors: Fei Long Wei, Hua Yang, Hai Tao Zhang, Zhou Ping Yin

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In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.

Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment.

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Authors: Changyi Liu, Gui Wang, Matthew Dargusch

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Helical milling operations are used to generate or enlarge boreholes by means of a milling tool. The bore diameter can be adjusted through the diameter of the helical path. The kinematics of helical milling on a three axis machine tool is analysed firstly. The relationships between processing parameters, cutting tool geometry characters with machined hole feature are formulated. The feed motion of the cutting tool has been decomposed to plane circular feed and axial linear motion. In this paper, the time varying cutting forces acted on the side cutting edges and end cutting edges of the flat end cylinder miller is analysed using a discrete method separately. These two components then are combined to produce the cutting force model considering the complicated interaction between the cutters and workpiece. The time varying cutting force model describes the instantaneous cutting force during processing. This model could be used to predict cutting force, calculate statics deflection of cutter and workpiece, and also could be the foundation of dynamics model and predicting chatter limitation of the helical milling operations.

Keywords: Helical milling, Hole machining, Cutting force, Analytical model, Time domain

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Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

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In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building. Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that no more than 7% prediction error of annual cooling/heating load will be caused by the geometric simplification for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which means this method is applicable for building performance simulation.

Keywords: building energy model, simulation, geometric simplification, design, regression

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Authors: Yemisi Rufina Alli Smith, Isaac Gbadura Adanlawo

Abstract:

Liver disorders are one of the major problems of the world. Despite its frequent occurrence, high morbidity and high mortality, its medical management is currently inadequate. This study was designed to evaluate the hepatoprotective effect of saponin extract of the root of Garcinia kola on the integrity of the liver of paracetamol induced wistar albino rats. Twenty five (25) male adult wistar albino rats were divided into five (5) groups. Group I was the Control group that received distilled water only, group II was the negative control that received 2 g/kg of paracetamol on the 13th day, and group III, IV and V were pre-treated with 100, 200 and 400mg/kg of the saponin extract before inducing the liver damage on the 13th day with 2 g/kg of paracetamol. Twenty four (24) h after administration, the rats were sacrificed and blood samples were collected. The serum Alanine Transaminase (ALT), Aspartate Transaminase (AST), Alkaline Phosphatase (ALP) activities, Bilirubin and conjugated bilirubin, glucose and protein concentrations were evaluated. The liver was fixed immediately in Formalin and was processed and stained in Haematoxylin and Eosin (H&E). Administration of saponin extract from the root of Garcinia kola significantly decreased paracetamol induced elevated enzymes in the test group. Also histological observations showed that saponin extract of the root of Garcinia kola exhibited a significant liver protection against the toxicant as evident by the cells trying to return to normal. Saponin extract from the root of Garcinia kola indicated a protection of structural integrity of the hepatocytic cell membrane and regeneration of the damaged liver.

Keywords: Garcinia kola, Hepatoprotective, paracetamol, Saponin.

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Authors: Obeidat I., Bsoul M., Khasawneh A., Kilani Y.

Abstract:

This paper simulates the ad-hoc mesh network in rural areas, where such networks receive great attention due to their cost, since installing the infrastructure for regular networks in these areas is not possible due to the high cost. The distance between the communicating nodes is the most obstacles that the ad-hoc mesh network will face. For example, in Terranet technology, two nodes can communicate if they are only one kilometer far from each other. However, if the distance between them is more than one kilometer, then each node in the ad-hoc mesh networks has to act as a router that forwards the data it receives to other nodes. In this paper, we try to find the critical number of nodes which makes the network fully connected in a particular area, and then propose a method to enhance the intermediate node to accept to be a router to forward the data from the sender to the receiver. Much work was done on technological changes on peer to peer networks, but the focus of this paper will be on another feature which is to find the minimum number of nodes needed for a particular area to be fully connected and then to enhance the users to switch on their phones and accept to work as a router for other nodes. Our method raises the successful calls to 81.5% out of 100% attempt calls.

Keywords: Adjacency matrix, Ad-hoc mesh network, Connectedness, Terranet technology

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Authors: Reza Gheisari, Paulo J. Bartolo, Nicholas Goddard

Abstract:

Polymeric micro-cantilevers (Cs) are rapidly becoming popular for MEMS applications such as chemo- and biosensing as well as purely electromechanical applications such as microrelays. Polymer materials present suitable physical and chemical properties combined with low-cost mass production. Hence, micro-cantilevers made of polymers indicate much more biocompatibility and adaptability of rapid prototyping along with mechanical properties. This research studies the effects of three process and one size factors on the filling behaviour in micro cavity, and the role of each in the replication of micro parts using different polymer materials i.e. polypropylene (PP) SABIC 56M10 and acrylonitrile butadiene styrene (ABS) Magnum 8434 . In particular, the following factors are considered: barrel temperature, mould temperature, injection speed and the thickness of micro features. The study revealed that the barrel temperature and the injection speed are the key factors affecting the flow length of micro features replicated in PP and ABS. For both materials, an increase of feature sizes improves the melt flow. However, the melt fill of micro features does not increase linearly with the increase of their thickness.

Keywords: Flow length, micro-cantilevers, micro injection moulding, microfabrication.

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Authors: I. Yakubu, D. Mireku-Gyimah, D. Asafo-Adjei

Abstract:

The challenge for everyone involved in preserving the ecosystem is to find creative ways to protect and restore the remaining ecosystems while accommodating and enhancing the country social and economic well-being. Frequent fires of anthropogenic origin have been affecting the ecosystems in many countries adversely. Hence adopting ways of decision making such as Multicriteria Decision Making (MCDM) is appropriate since it will enhance the evaluation and analysis of fire risk and hazard of the ecosystem. In this paper, fire risk and hazard data from the West Gonja area of Ghana were used in some of the methods (Analytical Hierarchy Process, Compromise Programming, and Grey Relational Analysis (GRA) for MCDM evaluation and analysis to determine the optimal weight method for fire risk and hazard. Ranking of the land cover types was carried out using; Fire Hazard, Fire Fighting Capacity and Response Risk Criteria. Pairwise comparison under Analytic Hierarchy Process (AHP) was used to determine the weight of the various criteria. Weights for sub-criteria were also obtained by the pairwise comparison method. The results were optimised using GRA and Compromise Programming (CP). The results from each method, hybrid GRA and CP, were compared and it was established that all methods were satisfactory in terms of optimisation of weight. The most optimal method for spatial multicriteria evaluation was the hybrid GRA method. Thus, a hybrid AHP and GRA method is more effective method for ranking alternatives in MCDM than the hybrid AHP and CP method.

Keywords: Compromise programming, grey relational analysis, spatial multi-criteria, weight optimisation.

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