Search results for: Leadership Approach

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: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: Autonomous mobile robots, obstacle avoidance, path planning, and processing time.

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Authors: Kazeem A. Adebiyi

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Despite many success stories of manufacturing safety, many organizations are still reluctant, perceiving it as cost increasing and time consuming. The clear contributor may be due to the use of lagging indicators rather than leading indicator measures. The study therefore proposes a combinatorial model for determining the best safety strategy. A combination theory and cost benefit analysis was employed to develop a monetary saving / loss function in terms value of preventions and cost of prevention strategy. Documentations, interviews and structured questionnaire were employed to collect information on Before-And-After safety programme records from a Tobacco company between periods of 1993-2001(for pre-safety) and 2002-2008 (safety period) for the model application. Three combinatorial alternatives A, B, C were obtained resulting into 4, 6 and 4 strategies respectively with PPE and Training being predominant. A total of 728 accidents were recorded for a 9 year period of pre-safety programme and 163 accidents were recorded for 7 years period of safety programme. Six preventions activities (alternative B) yielded the best results. However, all the years of operation experienced except year 2004. The study provides a leading resources for planning successful safety programme

Keywords: Combination, Manufacturing Safety, Monetary Savings, Prevention Strategies.

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Authors: A. Khosravi, S. Ghadirian, J. S. McCartney

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Evaluation of the seismic-induced settlement of an unsaturated soil layer depends on several variables, among which the small strain shear modulus, G_max, and soil’s state of stress have been demonstrated to be of particular significance. Recent interpretation of trends in G_max revealed considerable effects of the degree of saturation and hydraulic hysteresis on the shear stiffness of soils in unsaturated states. Accordingly, the soil layer is expected to experience different settlement behaviors depending on the soil saturation and seasonal weathering conditions. In this study, a semi-empirical formulation was adapted to extend an existing G_max model to infer hysteretic effects along different paths of the SWRC including scanning curves. The suitability of the proposed approach is validated against experimental results from a suction-controlled resonant column test and from data reported in literature. The model was observed to follow the experimental data along different paths of the SWRC, and showed a slight hysteresis in shear modulus along the scanning curves.

Keywords: Hydraulic hysteresis, Scanning path, Small strain shear modulus, Unsaturated soil.

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Authors: Ja'far Alqatawna, Jawed Siddiqi, Babak Akhgar, Mohammad Hjouj Btoush

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A great deal of research works in the field information systems security has been based on a positivist paradigm. Applying the reductionism concept of the positivist paradigm for information security means missing the bigger picture and thus, the lack of holism which could be one of the reasons why security is still overlooked, comes as an afterthought or perceived from a purely technical dimension. We need to reshape our thinking and attitudes towards security especially in a complex and dynamic environment such as e- Business to develop a holistic understanding of e-Business security in relation to its context as well as considering all the stakeholders in the problem area. In this paper we argue the suitability and need for more inductive interpretive approach and qualitative research method to investigate e-Business security. Our discussion is based on a holistic framework of enquiry, nature of the research problem, the underling theoretical lens and the complexity of e-Business environment. At the end we present a research strategy for developing a holistic framework for understanding of e-Business security problems in the context of developing countries based on an interdisciplinary inquiry which considers their needs and requirements.

Keywords: e-Business Security, Complexity, Methodological considerations, interpretive qualitative research and Case study method.

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Authors: Md. Zahangir Alom, Mei-Lan Piao, Md. Ashraful Alam, Nam Kim, Jae-Hyeung Park

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A new approach for facial expressions recognition based on face context and adaptively weighted sub-pattern PCA (Aw-SpPCA) has been presented in this paper. The facial region and others part of the body have been segmented from the complex environment based on skin color model. An algorithm has been proposed to accurate detection of face region from the segmented image based on constant ratio of height and width of face (δ= 1.618). The paper also discusses on new concept to detect the eye and mouth position. The desired part of the face has been cropped to analysis the expression of a person. Unlike PCA based on a whole image pattern, Aw-SpPCA operates directly on its sub patterns partitioned from an original whole pattern and separately extracts features from them. Aw-SpPCA can adaptively compute the contributions of each part and a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on single standard face with five types of facial expression database shows that the proposed method is competitive.

Keywords: Aw-SpPC, Expressoin Recognition, Face context, Face Detection, PCA

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Authors: Carole A. El Raheb, Hassan K. Abdel-Salam, Ingi Elcherif

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An architect carrying the design process alone is the main reason for the deterioration of the quality of the architectural product as the complexity of the projects makes it a multi-disciplinary work; then, the Integrative Design Process (IDP) must be applied in the architectural firm especially from the early design phases to improve the product’s quality and to eliminate the ignorance of the principles of design causing the occurrence of low-grade buildings. The research explores the Integrative Design (ID) principles that fit in the architectural practice. Constraints facing this application are presented with strategies and solutions to overcome them. A survey questionnaire was conducted to collect data from a number of recognized Egyptian Architecture, Engineering and Construction (AEC) firms that explores their opinions on using the IDP. This survey emphasizes the importance of the IDP in firms and presents the reasons preventing the firms from applying the IDP. The aim here is to investigate the potentials of integrating this approach into architectural firms emphasizing the importance of this application which ensures the realization of the project’s goal and eliminates the reduction in the project’s quality.

Keywords: Application, architectural firms, integrative design principles, integrative design process, the project quality.

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Authors: Aleksandar Zhelyazkov, Daniele Zonta, Helmut Wenzel, Peter Furtner

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In the current research structural health monitoring is considered for addressing the critical issue of post-earthquake damage detection. A non-standard approach for damage detection via acoustic emission is presented - acoustic emissions are monitored in the low frequency range (up to 120 Hz). Such emissions are termed high-frequency transients. Further a damage indicator defined as the Time-Ratio Damage Indicator is introduced. The indicator relies on time-instance measurements of damage initiation and deformation peaks. Based on the time-instance measurements a procedure for estimation of the maximum drift ratio is proposed. Monitoring data is used from a shaking-table test of a full-scale reinforced concrete bridge pier. Damage of the experimental column is successfully detected and the proposed damage indicator is calculated.

Keywords: Acoustic emission, Damage detection, Shaking table test, Structural health monitoring, High-frequency transients.

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Authors: Angela Unna Chukwu, Samuel Oluwafemi Oyamakin

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We proposed a Hyperbolic Gompertz Growth Model (HGGM), which was developed by introducing a shape parameter (allometric). This was achieved by convoluting hyperbolic sine function on the intrinsic rate of growth in the classical gompertz growth equation. The resulting integral solution obtained deterministically was reprogrammed into a statistical model and used in modeling the height and diameter of Pines (Pinus caribaea). Its ability in model prediction was compared with the classical gompertz growth model, an approach which mimicked the natural variability of height/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using goodness of fit tests and model selection criteria. The Kolmogorov Smirnov test and Shapiro-Wilk test was also used to test the compliance of the error term to normality assumptions while the independence of the error term was confirmed using the runs test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic gompertz growth models better than the source model (classical gompertz growth model) while the results of R2, Adj. R2, MSE and AIC confirmed the predictive power of the Hyperbolic Gompertz growth models over its source model.

Keywords: Height, Dbh, forest, Pinus caribaea, hyperbolic, gompertz.

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Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

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The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain and how various stakeholders will interact with the system.

Keywords: Internet of Things, IoT, blockchain, data integrity, authentication, data privacy.

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Authors: Sajad Farokhi, Siti Mariyam Shamsuddin, Jan Flusser, Usman Ullah Sheikh

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Although face recognition seems as an easy task for human, automatic face recognition is a much more challenging task due to variations in time, illumination and pose. In this paper, the influence of time-lapse on visible and thermal images is examined. Orthogonal moment invariants are used as a feature extractor to analyze the effect of time-lapse on thermal and visible images and the results are compared with conventional Principal Component Analysis (PCA). A new triangle square ratio criterion is employed instead of Euclidean distance to enhance the performance of nearest neighbor classifier. The results of this study indicate that the ideal feature vectors can be represented with high discrimination power due to the global characteristic of orthogonal moment invariants. Moreover, the effect of time-lapse has been decreasing and enhancing the accuracy of face recognition considerably in comparison with PCA. Furthermore, our experimental results based on moment invariant and triangle square ratio criterion show that the proposed approach achieves on average 13.6% higher in recognition rate than PCA.

Keywords: Infrared Face recognition, Time-lapse, Zernike moment invariants

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Thus, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Edge detection is one of the basic building blocks of video and image processing applications. It is a common block in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: High Level Synthesis, Canny edge detection, Hardware accelerators, and Computer Vision.

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Authors: S. Shanthi, V. Muralibhaskaran

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Mammography has been one of the most reliable methods for early detection of breast cancer. There are different lesions which are breast cancer characteristic such as microcalcifications, masses, architectural distortions and bilateral asymmetry. One of the major challenges of analysing digital mammogram is how to extract efficient features from it for accurate cancer classification. In this paper we proposed a hybrid feature extraction method to detect and classify all four signs of breast cancer. The proposed method is based on multiscale surrounding region dependence method, Gabor filters, multi fractal analysis, directional and morphological analysis. The extracted features are input to self adaptive resource allocation network (SRAN) classifier for classification. The validity of our approach is extensively demonstrated using the two benchmark data sets Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammograph (DDSM) and the results have been proved to be progressive.

Keywords: Feature extraction, fractal analysis, Gabor filters, multiscale surrounding region dependence method, SRAN.

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Authors: Sawsan J. Al-husseini, Talib A. Dosa

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Educational institutions are today facing increasing pressures due to economic, political and social upheaval. This is only exacerbated by the nature of education as an intangible good which relies upon the intellectual assets of the organisation, its staff. Top management support has been acknowledged as having a positive general influence on knowledge management and creativity. However, there is a lack of models linking top management support, knowledge sharing, and innovation within higher education institutions, in general within developing countries, and particularly in Iraq. This research sought to investigate the impact of top management support on innovation through the mediating role of knowledge sharing in Iraqi private HEIs. A quantitative approach was taken and 262 valid responses were collected to test the causal relationships between top management support, knowledge sharing, and innovation. Employing structural equation modelling with AMOS v.25, the research demonstrated that knowledge sharing plays a pivotal role in the relationship between top management support and innovation. The research has produced some guidelines for researchers as well as leaders, and provided evidence to support the use of knowledge sharing to increase innovation within the higher education environment in developing countries, particularly Iraq.

Keywords: Top management support, knowledge sharing, innovation, structural equation modelling.

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an ‘optimal’ value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: Cross Validation, Parameter Averaging, Parameter Selection, Regularization Parameter Search.

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Authors: Liliana M. Marinelli, Cristina T. Varanese

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In the last few years, students from higher education have difficulties in grasping mathematical concepts which support physical matters, especially those in the first years of this education. Classical Physics teaching turns to be complex when students are not able to make use of mathematical tools which lead to the conceptual structure of Physics. When derivation and integration rules are not used or developed in parallel with other disciplines, the physical meaning that we attempt to convey turns to be complicated. Due to this fact, it could be of great use to see the Classical Mechanics from an axiomatic approach, where the correspondence rules give physical meaning, if we expect students to understand concepts clearly and accurately. Using the Minkowski point of view adapted to a two-dimensional space and time where vectors, matrices, and straight lines (worked from an affine space) give mathematical and physical rigorosity even when it is more abstract. An interesting option would be to develop the disciplinary contents from an axiomatic version which embraces the Classical Mechanics as a particular case of Relativistic Mechanics. The observation about the increase in the difficulties stated by students in the first years of education allows this idea to grow as a possible option to improve performance and understanding of the concepts of this subject.

Keywords: Axiom, classical physics, physical concepts, relativity.

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Authors: A. Krishna Veni, R.Geetha

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Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.

Keywords: Aggregation, lifetime, network security, wireless sensor network.

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Authors: Rossitza M. Setchi, Nikolaos Lagos

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Problem solving has traditionally been one of the principal research areas for artificial intelligence. Yet, although artificial intelligence reasoning techniques have been employed in several product support systems, the benefit of integrating product support, knowledge engineering, and problem solving, is still unclear. This paper studies the synergy of these areas and proposes a knowledge engineering framework that integrates product support systems and artificial intelligence techniques. The framework includes four spaces; the data, problem, hypothesis, and solution ones. The data space incorporates the knowledge needed for structured reasoning to take place, the problem space contains representations of problems, and the hypothesis space utilizes a multimodal reasoning approach to produce appropriate solutions in the form of virtual documents. The solution space is used as the gateway between the system and the user. The proposed framework enables the development of product support systems in terms of smaller, more manageable steps while the combination of different reasoning techniques provides a way to overcome the lack of documentation resources.

Keywords: Knowledge engineering framework, product support, case-based reasoning, model-based reasoning, multimodal reasoning.

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Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: Process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis.

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Authors: Ping He

Abstract:

This paper addresses the problem of the partial state feedback stabilization of a class of nonlinear systems. In order to stabilization this class systems, the especial place of this paper is to reverse designing the state feedback control law from the method of judging system stability with the center manifold theory. First of all, the center manifold theory is applied to discuss the stabilization sufficient condition and design the stabilizing state control laws for a class of nonlinear. Secondly, the problem of partial stabilization for a class of plane nonlinear system is discuss using the lyapunov second method and the center manifold theory. Thirdly, we investigate specially the problem of the stabilization for a class of homogenous plane nonlinear systems, a class of nonlinear with dual-zero eigenvalues and a class of nonlinear with zero-center using the method of lyapunov function with homogenous derivative, specifically. At the end of this paper, some examples and simulation results are given show that the approach of this paper to this class of nonlinear system is effective and convenient.

Keywords: Partial stabilization, Nonlinear critical systems, Centermanifold theory, Lyapunov function, System reduction.

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Authors: N. H. Adenan, M. S. M. Noorani

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River flow prediction is an essential to ensure proper management of water resources can be optimally distribute water to consumers. This study presents an analysis and prediction by using nonlinear prediction method involving monthly river flow data in Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The phase space reconstruction involves the reconstruction of one-dimensional (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. Revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) have been employed to compare prediction performance for nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show the prediction results using nonlinear prediction method is better than ARIMA and SVM. Therefore, the result of this study could be used to develop an efficient water management system to optimize the allocation water resources.

Keywords: River flow, nonlinear prediction method, phase space, local linear approximation.

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Authors: Kamalendu Pal

Abstract:

This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision-making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a fuzzy linguistic term. The finding suggests that fuzzy linguistic evaluation is practical and meaningful in knowledge-based system development purpose. 

Keywords: Case-based reasoning, decision-support system, fuzzy linguistic term, rule-based reasoning, system evaluation.

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Authors: Banashree N. P., Andhe Dharani, R. Vasanta, P. S. Satyanarayana

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The applications on numbers are across-the-board that there is much scope for study. The chic of writing numbers is diverse and comes in a variety of form, size and fonts. Identification of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], machine printed or handwritten characters/numerals are recognized. There are plentiful approaches that deal with problem of detection of numerals/character depending on the sort of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent our work focused on a technique in feature extraction i.e. Local-based approach, a method using 16-segment display concept, which is extracted from halftoned images & Binary images of isolated numerals. These feature vectors are fed to neural classifier model that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. Experimentation result shows that recognition rate of halftoned images is 98 % compared to binary images (95%).

Keywords: OCR, Halftoning, Neural classifier, 16-segmentdisplay concept.

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Authors: E.J. Cilliers

Abstract:

Green- spaces might be very attractive, but where are the economic benefits? What value do nature and landscape have for us? What difference will it make to jobs, health and the economic strength of areas struggling with deprivation and social problems? [1].There is a need to consider green spaces from a different perspective. Green planning is not just about flora and fauna, but also about planning for economic benefits [2]. It is worth trying to quantify the value of green spaces since nature and landscape are crucially important to our quality of life and sustainable development. The reality, however, is that urban development often takes place at the expense of green spaces. Urbanization is an ongoing process throughout the world; however, hyper-urbanization without environmental planning is destructive, not constructive [3]. Urban spaces are believed to be more valuable than other land uses, particular green areas, simply because of the market value connected to urban spaces. However, attractive landscapes can help raise the quality and value of the urban market even more. In order to reach these objectives of integrated planning, the Green-Value-Gap needs to be bridged. Economists have to understand the concept of Green-Planning and the spinoffs, and Environmentalists have to understand the importance of urban economic development and the benefits thereof to green planning. An interface between Environmental Management, Economic Development and sustainable Spatial Planning are needed to bridge the Green-Value-Gap.

Keywords: Spatial Planning, Environmental Management, Green-Value-Gap, Compensation, Participation.

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Authors: Norbik Bashah, Idris Bharanidharan Shanmugam, Abdul Manan Ahmed

Abstract:

Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection. The techniques that are being investigated includes neural networks and fuzzy logic with network profiling, that uses simple data mining techniques to process the network data. The proposed system is a hybrid system that combines anomaly, misuse and host based detection. Simple Fuzzy rules allow us to construct if-then rules that reflect common ways of describing security attacks. For host based intrusion detection we use neural-networks along with self organizing maps. Suspicious intrusions can be traced back to its original source path and any traffic from that particular source will be redirected back to them in future. Both network traffic and system audit data are used as inputs for both.

Keywords: Intrusion Detection, Network Security, Data mining, Fuzzy Logic.

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Authors: A. Shukla, A. Tarsauliya, R. Tiwari, S. Sharma

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Cancer classification to their corresponding cohorts has been key area of research in bioinformatics aiming better prognosis of the disease. High dimensionality of gene data has been makes it a complex task and requires significance data identification technique in order to reducing the dimensionality and identification of significant information. In this paper, we have proposed a novel approach for classification of oral cancer into metastasis positive and negative patients. We have used significance analysis of microarrays (SAM) for identifying significant genes which constitutes gene signature. 3 different gene signatures were identified using SAM from 3 different combination of training datasets and their classification accuracy was calculated on corresponding testing datasets using k-Nearest Neighbour (kNN), Fuzzy C-Means Clustering (FCM), Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN). A final gene signature of only 9 genes was obtained from above 3 individual gene signatures. 9 gene signature-s classification capability was compared using same classifiers on same testing datasets. Results obtained from experimentation shows that 9 gene signature classified all samples in testing dataset accurately while individual genes could not classify all accurately.

Keywords: Cancer, Gene Signature, SAM, Classification.

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Authors: Prawal Sinha, Getachew Adamu

Abstract:

Heating is inevitable in any bearing operation. This leads to not only the thinning of the lubricant but also could lead to a thermal deformation of the bearing. The present work is an attempt to analyze the influence of thermal deformation on the thermohydrodynamic lubrication of infinitely long tilted pad slider rough bearings. As a consequence of heating the slider is deformed and is assumed to take a parabolic shape. Also the asperities expand leading to smaller effective film thickness. Two different types of surface roughness are considered: longitudinal roughness and transverse roughness. Christensen-s stochastic approach is used to derive the Reynolds-type equations. Density and viscosity are considered to be temperature dependent. The modified Reynolds equation, momentum equation, continuity equation and energy equation are decoupled and solved using finite difference method to yield various bearing characteristics. From the numerical simulations it is observed that the performance of the bearing is significantly affected by the thermal distortion of the slider and asperities and even the parallel sliders seem to carry some load.

Keywords: Thermal Deformation, Tilted pad slider bearing, longitudinal roughness, transverse roughness, load capacity

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Authors: Chie Urawa

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Cautionary statements or disclaimers in corporate annual reports need to be carefully designed because clear cautionary statements may protect a company in the case of legal disputes and may undermine positive impressions. This study compares the language of cautionary statements using two corpora, Sony’s cautionary statement corpus (S-corpus) and Panasonic’s cautionary statement corpus (P-corpus), illustrating the differences and similarities in relation to the use of meaningful cautionary statements and critically analyzing why practitioners use the way. The findings describe the distinct differences between the two companies in the presentation of the risk factors and the way how they make the statements. The word ability is used more for legal protection in S-corpus whereas the word possibility is used more to convey a better impression in P-corpus. The main similarities are identified in the use of lexical words and pronouns, and almost the same wordings for eight years. The findings show how they make the statements unique to the company in the presentation of risk factors, and the characteristics of specific genre of professional communication. Important implications of this study are that more comprehensive approach can be applied in other contexts, and be used by companies to reflect upon their cautionary statements.

Keywords: Cautionary statements, corporate annual reports, corpus, risk factors.

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Authors: Ali Mirmohammadi, Arash Taheri, Meysam Mohammadi-Amin

Abstract:

One of the major parts of a jet engine is air intake, which provides proper and required amount of air for the engine to operate. There are several aerodynamic parameters which should be considered in design, such as distortion, pressure recovery, etc. In this research, the effects of lip ice accretion on pitot intake performance are investigated. For ice accretion phenomenon, two supervised multilayer neural networks (ANN) are designed, one for ice shape prediction and another one for ice roughness estimation based on experimental data. The Fourier coefficients of transformed ice shape and parameters include velocity, liquid water content (LWC), median volumetric diameter (MVD), spray time and temperature are used in neural network training. Then, the subsonic intake flow field is simulated numerically using 2D Navier-Stokes equations and Finite Volume approach with Hybrid mesh includes structured and unstructured meshes. The results are obtained in different angles of attack and the variations of intake aerodynamic parameters due to icing phenomenon are discussed. The results show noticeable effects of ice accretion phenomenon on intake behavior.

Keywords: Artificial Neural Network, Ice Accretion, IntakeAerodynamics, Design Parameters, Finite Volume Method.

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Authors: Slavka Zeković

Abstract:

A preliminary evaluation of the urban land system is presented in the article together with the instruments of land policy in Serbia. The main reason for the analysis is demand for definition of reform framework for urban land management in Serbia in the period of transition towards market-led system. It is concluded that due to the limitations of the current regulation it will be impossible in the future to apply market principles in the urban land policy (supply and demand of land, land capitalization, investment efficiency, et al.). Based on the estimation that the urban land system and land policy are key factors of competitiveness between regions and towns in Serbia, it is necessary to initiate changes in this field. There are indicated on an option of privatization of urban public land and possible establishment of leasehold land. A comparative analysis of the possibilities of the reform urban land system in Serbia has been carried out in relation to two approaches of market systems: (a) with dominant private ownership of urban land (neo/liberal approach) and (b) with dominant public ownership of urban land (system of leasehold)whose findings can be a basis for further study of the new system in Serbia.. The attanied results are part of studies matter for the making of Strategy of territorial development of Serbia.

Keywords: Urban Land System, Urban Land Management, Instruments of Land Policy, Evaluation, Market.

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