Search results for: Analytical approach

Authors: MohammadReza EffatParvar, Akbar Bemana, Mehdi EffatParvar

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Scheduling algorithms are used in operating systems to optimize the usage of processors. One of the most efficient algorithms for scheduling is Multi-Layer Feedback Queue (MLFQ) algorithm which uses several queues with different quanta. The most important weakness of this method is the inability to define the optimized the number of the queues and quantum of each queue. This weakness has been improved in IMLFQ scheduling algorithm. Number of the queues and quantum of each queue affect the response time directly. In this paper, we review the IMLFQ algorithm for solving these problems and minimizing the response time. In this algorithm Recurrent Neural Network has been utilized to find both the number of queues and the optimized quantum of each queue. Also in order to prevent any probable faults in processes' response time computation, a new fault tolerant approach has been presented. In this approach we use combinational software redundancy to prevent the any probable faults. The experimental results show that using the IMLFQ algorithm results in better response time in comparison with other scheduling algorithms also by using fault tolerant mechanism we improve IMLFQ performance.

Keywords: IMLFQ, Fault Tolerant, Scheduling, Queue, Recurrent Neural Network.

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Authors: Hui-Yu Huang, Shih-Hang Hsu

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In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.

Keywords: Gabor filter, improved active shape model (IASM), principal component analysis (PCA), face alignment, face recognition, support vector machine (SVM)

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Authors: Fahri Benli, Sitalakshmi Venkatraman, Ye Wei, Fiona Wahr

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A flipped classroom which is a form of blended learning shifts the focus from a teacher-centered approach to a learner-centered approach. However, not all learners are ready to take the active role of knowledge and skill acquisition through a flipped classroom and they continue to delve in a passive mode of learning. This challenges educators in designing, scaffolding and facilitating in-class activities for students to have active learning experiences in a flipped classroom environment. Experiential learning theories have been employed by educators in the past in physical classrooms based on the principle that knowledge could be actively developed through direct experience. However, with more of online teaching witnessed recently, there are inherent limitations in designing and simulating an experiential learning activity for an online environment. In this paper, we explore enhancing experiential learning using smart digital tools that could be employed in a flipped classroom within a higher education setting. We present the use of smart collaborative tools online to enhance the experiential learning activity to teach higher-order cognitive concepts of business process modeling as a case study.

Keywords: Experiential learning, flipped classroom, smart software tools, online learning higher-order learning attributes.

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

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Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: Binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform.

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Authors: Héctor Rivera-Gómez, Eva Selene Hernández-Gress, Oscar Montaño-Arango, Jose Ramon Corona-Armenta

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This research studies the joint production, maintenance and subcontracting control policy for an unreliable deteriorating manufacturing system. Production activities are controlled by a derivation of the Hedging Point Policy, and given that the system is subject to deterioration, it reduces progressively its capacity to satisfy product demand. Multiple deterioration effects are considered, reflected mainly in the quality of the parts produced and the reliability of the machine. Subcontracting is available as support to satisfy product demand; also, overhaul maintenance can be conducted to reduce the effects of deterioration. The main objective of the research is to determine simultaneously the production, maintenance and subcontracting rate, which minimize the total, incurred cost. A stochastic dynamic programming model is developed and solved through a simulation-based approach composed of statistical analysis and optimization with the response surface methodology. The obtained results highlight the strong interactions between production, deterioration and quality, which justify the development of an integrated model. A numerical example and a sensitivity analysis are presented to validate our results.

Keywords: Deterioration, simulation, subcontracting, production planning.

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Authors: Sara Najiazarpour, Mahsa Najiazarpour

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There are many problems in contracting projects and their performance. At each project stage and due to different reasons, these problems affect cost, time, and quality. Hence, in order to increase the efficiency and performance in all levels of the chain and with supply chain management approach, there will be a coordination from the beginning of a project to the end of project (handover of project). Contractor selection is the foremost part of construction projects which in this multi-criteria decision-making, the best contractor is determined by expert judgment, different variables, and their priorities. In this paper for selecting the best contractor, numerous criteria were collected by asking from adept experts and then among them, 16 criteria with highest frequency were considered for questionnaire. This questionnaire was distributed between experts. Cronbach's alpha coefficient was used and then based on Borda function important criteria were selected which was categorized in four main criteria as follows: Environmental factors and physical equipment, past performance and technical expertise, affordability and standards. Then with PROMTHEE method, the criteria were normalized and monitored, finally the best alternative was selected. A case study had been done, and the best contractor was selected based on all criteria and their priorities.

Keywords: Evaluation and selecting contractors, project development, supply chain management, multi-criteria decision-making.

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Authors: Eberechi Weli, Michael Todinov

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The gap between the selection of risk-reduction options in the railway industry and the task of their effective implementation results in compromised safety and substantial losses. An effective risk management must necessarily integrate the evaluation phases with the implementation phase. This paper proposes an essential categorisation of risk reduction measures that best addresses a standard railway industry portfolio. By categorising the risk reduction options into design, operational, procedural and technical options, it is guaranteed that the efforts of the implementation facilitators (people, processes and supporting systems) are systematically harmonised. The classification is based on an integration of fundamental principles of risk reduction in the railway industry with the systems engineering approach.

This paper argues that the use of a similar classification approach is an attribute of organisations possessing a superior level of risk-reduction readiness. The integration of the proposed rational classification structure provides a solid ground for effective risk reduction.

Keywords: Cost effectiveness, organisational readiness, risk reduction, railway, system engineering.

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Authors: Rogayah A. Majid, Nor Laila Md. Noor, Wan Adilah Wan Adnan

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User-Centered Design (UCD), Usability Engineering (UE) and Participatory Design (PD) are the common Human- Computer Interaction (HCI) approaches that are practiced in the software development process, focusing towards issues and matters concerning user involvement. It overlooks the organizational perspective of HCI integration within the software development organization. The Management Information Systems (MIS) perspective of HCI takes a managerial and organizational context to view the effectiveness of integrating HCI in the software development process. The Human-Centered Design (HCD) which encompasses all of the human aspects including aesthetic and ergonomic, is claimed as to provide a better approach in strengthening the HCI approaches to strengthen the software development process. In determining the effectiveness of HCD in the software development process, this paper presents the findings of a content analysis of HCI approaches by viewing those approaches as a technology which integrates user requirements, ranging from the top management to other stake holder in the software development process. The findings obtained show that HCD approach is a technology that emphasizes on human, tools and knowledge in strengthening the HCI approaches to strengthen the software development process in the quest to produce a sustainable, usable and useful software product.

Keywords: Human-Centered Design (HCD), Management Information Systems (MIS), Participatory Design (PD), User- Centered Design (UCD), Usability Engineering (UE)

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Authors: Dyi-Cheng Chen, Wen-Hsuan Ku, Ming-Ren Chen

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The current of professional bicycle pedal-s manufacturing model mostly used casting, forging, die-casting processing methods, so the paper used 7075 aluminum alloy which is to produce the bicycle parts most commonly, and employs the rigid-plastic finite element (FE) DEFORMTM 3D software to simulate and to analyze the professional bicycle pedal design. First we use Solid works 2010 3D graphics software to design the professional bicycle pedal of the mold and appearance, then import finite element (FE) DEFORMTM 3D software for analysis. The paper used rigid-plastic model analytical methods, and assuming mode to be rigid body. A series of simulation analyses in which the variables depend on different temperature of forging billet, friction factors, forging speed, mold temperature are reveal to effective stress, effective strain, damage and die radial load distribution for forging bicycle pedal. The analysis results hope to provide professional bicycle pedal forming mold references to identified whether suit with the finite element results for high-strength design suitability of aluminum alloy.

Keywords: Bicycle pedal, finite element analysis, 7075 aluminum alloy, Taguchi method

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Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

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Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: Automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA.

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Authors: Radomir Perzina, Jaroslav Ramik

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The Analytic Hierarchy Process is frequently used approach for solving decision making problems. There exists wide range of software programs utilizing that approach. Their main disadvantage is that they are relatively expensive and missing intermediate calculations. This work introduces a Microsoft Excel add-in called DAME – Decision Analysis Module for Excel. Comparing to other computer programs DAME is free, can work with scenarios or multiple decision makers and displays intermediate calculations. Users can structure their decision models into three levels – scenarios/users, criteria and variants. Items on all levels can be evaluated either by weights or pair-wise comparisons. There are provided three different methods for the evaluation of the weights of criteria, the variants as well as the scenarios – Saaty’s Method, Geometric Mean Method and Fuller’s Triangle Method. Multiplicative and additive syntheses are supported. The proposed software package is demonstrated on couple of illustrating examples of real life decision problems.

Keywords: Analytic hierarchy process, multi-criteria decision making, pair-wise comparisons, Microsoft Excel, Scenarios.

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Authors: S. Bader, N. Essoukri Ben Amara

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With the technological development and rise of virtual worlds, these spaces are becoming more and more attractive for cybercriminals, hidden behind avatars and fictitious identities. Since access to these spaces is not restricted or controlled, some impostors take advantage of gaining unauthorized access and practicing cyber criminality. This paper proposes an identity management approach for securing access to virtual worlds. The major purpose of the suggested solution is to install a strong security mechanism to protect virtual identities represented by avatars. Thus, only legitimate users, through their corresponding avatars, are allowed to access the platform resources. Access is controlled by integrating an authentication process based on biometrics. In the request process for registration, a user fingerprint is enrolled and then encrypted into a watermark utilizing a cancelable and non-invertible algorithm for its protection. After a user personalizes their representative character, the biometric mark is embedded into the avatar through a watermarking procedure. The authenticity of the avatar identity is verified when it requests authorization for access. We have evaluated the proposed approach on a dataset of avatars from various virtual worlds, and we have registered promising performance results in terms of authentication accuracy, acceptation and rejection rates.

Keywords: Identity management, security, biometrics authentication and authorization, avatar, virtual world.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

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In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: Khaled S. Ragab

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This paper deals with behavior and capacity of punching shear force for flat slabs produced from steel fiber reinforced self compacting concrete (SFRSCC) by application nonlinear finite element method. Nonlinear finite element analysis on nine slab specimens was achieved by using ANSYS software. A general description of the finite element method, theoretical modeling of concrete and reinforcement are presented. The nonlinear finite element analysis program ANSYS is utilized owing to its capabilities to predict either the response of reinforced concrete slabs in the post elastic range or the ultimate strength of a flat slabs produced from steel fiber reinforced self compacting concrete (SFRSCC). In order to verify the analytical model used in this research using test results of the experimental data, the finite element analysis were performed then a parametric study of the effect ratio of flexural reinforcement, ratio of the upper reinforcement, and volume fraction of steel fibers were investigated. A comparison between the experimental results and those predicted by the existing models are presented. Results and conclusions may be useful for designers, have been raised, and represented.

Keywords: Nonlinear FEM, Punching shear behavior, Flat slabs and Steel fiber reinforced self compacting concrete (SFRSCC).

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Authors: Markus Kaiser, Johannes Buchmann

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In this article, a formal specification and verification of the Rabin public-key scheme in a formal proof system is presented. The idea is to use the two views of cryptographic verification: the computational approach relying on the vocabulary of probability theory and complexity theory and the formal approach based on ideas and techniques from logic and programming languages. A major objective of this article is the presentation of the first computer-proved implementation of the Rabin public-key scheme in Isabelle/HOL. Moreover, we explicate a (computer-proven) formalization of correctness as well as a computer verification of security properties using a straight-forward computation model in Isabelle/HOL. The analysis uses a given database to prove formal properties of our implemented functions with computer support. The main task in designing a practical formalization of correctness as well as efficient computer proofs of security properties is to cope with the complexity of cryptographic proving. We reduce this complexity by exploring a light-weight formalization that enables both appropriate formal definitions as well as efficient formal proofs. Consequently, we get reliable proofs with a minimal error rate augmenting the used database, what provides a formal basis for more computer proof constructions in this area.

Keywords: public-key encryption, Rabin public-key scheme, formalproof system, higher-order logic, formal verification.

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Authors: A. Zaidi, F. Khelifi, R. Masmoudi, M. Bouhicha

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5

In order to eradicate the degradation of reinforced concrete structures due to the steel corrosion, professionals in constructions suggest using fiber reinforced polymers (FRP) for their excellent properties. Nevertheless, high temperatures may affect the bond between FRP bar and concrete, and consequently the serviceability of FRP-reinforced concrete structures. This paper presents a nonlinear numerical investigation using ADINA software to investigate the effect of the spacing between glass FRP (GFRP) bars embedded in concrete on circumferential thermal deformations and the distribution of radial thermal cracks in reinforced concrete beams submitted to high temperature variations up to 60 °C for asymmetrical problems. The thermal deformations predicted from nonlinear finite elements model, at the FRP bar/concrete interface and at the external surface of concrete cover, were established as a function of the ratio of concrete cover thickness to FRP bar diameter (c/d_b) and the ratio of spacing between FRP bars in concrete to FRP bar diameter (e/d_b). Numerical results show that the circumferential thermal deformations at the external surface of concrete cover are linear until cracking thermal load varied from 32 to 55 °C corresponding to the ratio of e/d_b varied from 1.3 to 2.3, respectively. However, for ratios e/d_b >2.3 and c/d_b >1.6, the thermal deformations at the external surface of concrete cover exhibit linear behavior without any cracks observed on the specified surface. The numerical results are compared to those obtained from analytical models validated by experimental tests.

Keywords: Concrete beam, FRP bars, spacing effect, thermal deformation.

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Authors: Izaz Ahmad, Farhatullah, Shahbaz Ali, Farhad Ali, Faiza, Hazrat Junaid, Farhan Zaid

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Current trends in remote health monitoring to monetize on the Internet of Things applications have been raised in efficient and interference free communications in Wireless Body Area Network (WBAN) scenario. Co-existence interference in WBANs have aggravates the over-congested radio bands, thereby requiring efficient Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) strategies and improve interference management. Existing solutions utilize simplistic heuristics to approach interference problems. The scope of this research article is to investigate reinforcement learning for efficient interference management under co-existing scenarios with an emphasis on homogenous interferences. The aim of this paper is to suggest a smart CSMA/CA mechanism based on reinforcement learning called QIM-MAC that effectively uses sense slots with minimal interference. Simulation results are analyzed based on scenarios which show that the proposed approach maximized Average Network Throughput and Packet Delivery Ratio and minimized Packet Loss Ratio, Energy Consumption and Average Delay.

Keywords: WBAN, IEEE 802.15.4 Standard, CAP Super-frame, Q-Learning.

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Authors: A. Zahedi Yeganeh, A. Khademolhosseini, R. Mokhtari Malekabadi

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Undoubtedly one of the most far-reaching and controversial topics considered in the past few decades, has been globalization. Globalization lies in the essence of the modern culture. It is a complex and rapidly expanding network of links and mutual interdependence that is an aspect of modern life; though some argue that this link existed since the beginning of human history. If we consider globalization as a dynamic social process in which the geographical constraints governing the political, economic, social and cultural relationships have been undermined, it might not be possible to simply describe its impact on the urban fabric. But since in this phenomenon the increase in communications of societies (while preserving the main cultural - regional characteristics) with one another and the increase in the possibility of influencing other societies are discussed, the need for more studies will be felt. The main objective of this study is to grade based on some globalization factors on urban fabric applying the TOPSIS model. The research method is descriptive - analytical and survey. For data analysis, the TOPSIS model and SPSS software were used and the results of GIS software with fourteen cities are shown on the map. The results show that the process of being influenced by the globalization of the urban fabric of fourteen zones of Isfahan was not similar and there have been large differences in this respect between city zones; the most affected areas are zones 5, 6 and 9 of the municipality and the least impact has been on the zones 4 and 3 and 2.

Keywords: Grading, Globalization, Urban fabric, 14 zones of Isfahan, TOPSIS model.

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Authors: Iau-Teh Wang, Chin-Yu Lee

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Rockfall is a kind of irregular geological disaster. Its destruction time, space and movements are highly random. The impact force is determined by the way and velocity rocks move. The movement velocity of a rockfall depends on slope gradient of its moving paths, height, slope surface roughness and rock shapes. For effectively mitigate and prevent disasters brought by rockfalls, it is required to precisely calculate the moving paths of a rockfall so as to provide the best protective design. This paper applies Colorado Rockfall Simulation Program (CRSP) as our study tool to discuss the impact of slope shape and surface roughness on the moving paths of a single rockfall. The analytical results showed that the slope, m=1:1, acted as the threshold for rockfall bounce height on a monoclinal slight slope. When JRC ´╝£ 1.2, movement velocity reduced and bounce height increased as JCR increased. If slope fixed and JRC increased, the bounce height of rocks increased gradually with reducing movement velocity. Therefore, the analysis on the moving paths of rockfalls with CRSP could simulate bouncing of falling rocks. By analyzing moving paths, velocity, and bounce height of falling rocks, we could effectively locate impact points of falling rocks on a slope. Such analysis can be served as a reference for future disaster prevention and control.

Keywords: Rockfall, Slope Shape, Moving Path, SurfaceRoughness.

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Authors: T. Teo, S. W. Lye, Y. F. Li, Z. Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that using a developed channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available brain computer interface (BCI) 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring, ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: Neurophysiology, monitoring, EEG, outliers, electroencephalography.

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Authors: Lin Yang, Zhian Mi, Jiacheng Xiao, Rong Li

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Swimming with the tide of deep learning, the field of music information retrieval (MIR) experiences parallel development and a sheer variety of feature-learning models has been applied to music classification and tagging tasks. Among those learning techniques, the deep convolutional neural networks (CNNs) have been widespreadly used with better performance than the traditional approach especially in music genre classification and prediction. However, regarding the music recommendation, there is a large semantic gap between the corresponding audio genres and the various aspects of a song that influence user preference. In our study, aiming to bridge the gap, we strive to construct an automatic music aesthetic annotation model with MIDI format for better comparison and measurement of the similarity between music pieces in the way of harmonic analysis. We use the matrix of qualification converted from MIDI files as input to train two different classifiers, support vector machine (SVM) and Decision Tree (DT). Experimental results in performance of a tag prediction task have shown that both learning algorithms are capable of extracting high-level properties in an end-to end manner from music information. The proposed model is helpful to learn the audience taste and then the resulting recommendations are likely to appeal to a niche consumer.

Keywords: Harmonic analysis, machine learning, music classification and tagging, MIDI.

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Authors: Emad E Abdallah, A.F. Otoom, ArwaSaqer, Ola Abu-Aisheh, Diana Omari, Ghadeer Salem

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As emails communications have no consistent authentication procedure to ensure the authenticity, we present an investigation analysis approach for detecting forged emails based on Random Forests and Naïve Bays classifiers. Instead of investigating the email headers, we use the body content to extract a unique writing style for all the possible suspects. Our approach consists of four main steps: (1) The cybercrime investigator extract different effective features including structural, lexical, linguistic, and syntactic evidence from previous emails for all the possible suspects, (2) The extracted features vectors are normalized to increase the accuracy rate. (3) The normalized features are then used to train the learning engine, (4) upon receiving the anonymous email (M); we apply the feature extraction process to produce a feature vector. Finally, using the machine learning classifiers the email is assigned to one of the suspects- whose writing style closely matches M. Experimental results on real data sets show the improved performance of the proposed method and the ability of identifying the authors with a very limited number of features.

Keywords: Digital investigation, cybercrimes, emails forensics, anonymous emails, writing style, and authorship analysis

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Authors: A. F. Ali, D. M. Shawky

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Discovering new biological knowledge from the highthroughput biological data is a major challenge to bioinformatics today. To address this challenge, we developed a new approach for protein classification. Proteins that are evolutionarily- and thereby functionally- related are said to belong to the same classification. Identifying protein classification is of fundamental importance to document the diversity of the known protein universe. It also provides a means to determine the functional roles of newly discovered protein sequences. Our goal is to predict the functional classification of novel protein sequences based on a set of features extracted from each protein sequence. The proposed technique used datasets extracted from the Structural Classification of Proteins (SCOP) database. A set of spectral domain features based on Fast Fourier Transform (FFT) is used. The proposed classifier uses multilayer back propagation (MLBP) neural network for protein classification. The maximum classification accuracy is about 91% when applying the classifier to the full four levels of the SCOP database. However, it reaches a maximum of 96% when limiting the classification to the family level. The classification results reveal that spectral domain contains information that can be used for classification with high accuracy. In addition, the results emphasize that sequence similarity measures are of great importance especially at the family level.

Keywords: Bioinformatics, Artificial Neural Networks, Protein Sequence Analysis, Feature Extraction.

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Authors: Manpreet Singh, V. P. Agrawal, Gurmanjot Singh Bhatti

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From the last decades, there is a significant technological advancement in the field of robotics, and a number of modular self-reconfigurable robots were introduced that can help in space exploration, bucket to stuff, search, and rescue operation during earthquake, etc. As there are numbers of self-reconfigurable robots, choosing the optimum one is always a concern for robot user since there is an increase in available features, facilities, complexity, etc. The objective of this research work is to present a multiple attribute decision making based methodology for coding, evaluation, comparison ranking and selection of modular self-reconfigurable robots using a technique for order preferences by similarity to ideal solution approach. However, 86 attributes that affect the structure and performance are identified. A database for modular self-reconfigurable robot on the basis of different pertinent attribute is generated. This database is very useful for the user, for selecting a robot that suits their operational needs. Two visual methods namely linear graph and spider chart are proposed for ranking of modular self-reconfigurable robots. Using five robots (Atron, Smores, Polybot, M-Tran 3, Superbot), an example is illustrated, and raking of the robots is successfully done, which shows that Smores is the best robot for the operational need illustrated, and this methodology is found to be very effective and simple to use.

Keywords: Self-reconfigurable robots, MADM, TOPSIS, morphogenesis, scalability.

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Authors: Hassan Haleh, Amin Ghaffari, Parisa Farahpour

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Need for an appropriate system of evaluating students- educational developments is a key problem to achieve the predefined educational goals. Intensity of the related papers in the last years; that tries to proof or disproof the necessity and adequacy of the students assessment; is the corroborator of this matter. Some of these studies tried to increase the precision of determining question weights in scientific examinations. But in all of them there has been an attempt to adjust the initial question weights while the accuracy and precision of those initial question weights are still under question. Thus In order to increase the precision of the assessment process of students- educational development, the present study tries to propose a new method for determining the initial question weights by considering the factors of questions like: difficulty, importance and complexity; and implementing a combined method of PROMETHEE and fuzzy analytic network process using a data mining approach to improve the model-s inputs. The result of the implemented case study proves the development of performance and precision of the proposed model.

Keywords: Assessing students, Analytic network process, Clustering, Data mining, Fuzzy sets, Multi-criteria decision making, and Preference function.

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Authors: Matthias Kirmse, Uwe Petersohn, Elief Paffrath

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As in today's semiconductor industries test costs can make up to 50 percent of the total production costs, an efficient test error detection becomes more and more important. In this paper, we present a new machine learning approach to test error detection that should provide a faster recognition of test system faults as well as an improved test error recall. The key idea is to learn a classifier ensemble, detecting typical test error patterns in wafer test results immediately after finishing these tests. Since test error detection has not yet been discussed in the machine learning community, we define central problem-relevant terms and provide an analysis of important domain properties. Finally, we present comparative studies reflecting the failure detection performance of three individual classifiers and three ensemble methods based upon them. As base classifiers we chose a decision tree learner, a support vector machine and a Bayesian network, while the compared ensemble methods were simple and weighted majority vote as well as stacking. For the evaluation, we used cross validation and a specially designed practical simulation. By implementing our approach in a semiconductor test department for the observation of two products, we proofed its practical applicability.

Keywords: Ensemble methods, fault detection, machine learning, semiconductor test.

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Authors: M. Orefice, V. Di Vito

Abstract:

This paper provides a description of a Collision Avoidance algorithm that has been developed starting from the mathematical modeling of the flight of insects, in terms of spirals and conchospirals geometric paths. It is able to calculate a proper avoidance manoeuver aimed to prevent the infringement of a predefined distance threshold between ownship and the considered intruder, while minimizing the ownship trajectory deviation from the original path and in compliance with the aircraft performance limitations and dynamic constraints. The algorithm is designed in order to be suitable for real-time applications, so that it can be considered for the implementation in the most recent airborne automatic collision avoidance systems using the traffic data received through an ADS-B IN device. The presented approach is able to take into account the rules-of-the-air, due to the possibility to select, through specifically designed decision making logic based on the consideration of the encounter geometry, the direction of the calculated collision avoidance manoeuver that allows complying with the rules-of-the-air, as for instance the fundamental right of way rule. In the paper, the proposed collision avoidance algorithm is presented and its preliminary design and software implementation is described. The applicability of this method has been proved through preliminary simulation tests performed in a 2D environment considering single intruder encounter geometries, as reported and discussed in the paper.

Keywords: collision avoidance, RPAS, spiral geometry, ADS-B based application

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Authors: Ali N. Suri, Ahmad A. Al-Makhlufi

Abstract:

In this paper the problem of buckling of plates on foundation of finite length and with different side support is studied.

The Finite Strip Method is used as tool for the analysis. This method uses finite strip elastic, foundation, and geometric matrices to build the assembly matrices for the whole structure, then after introducing boundary conditions at supports, the resulting reduced matrices is transformed into a standard Eigenvalue-Eigenvector problem. The solution of this problem will enable the determination of the buckling load, the associated buckling modes and the buckling wave length.

To carry out the buckling analysis starting from the elastic, foundation, and geometric stiffness matrices for each strip a computer program FORTRAN list is developed.

Since stiffness matrices are function of wave length of buckling, the computer program used an iteration procedure to find the critical buckling stress for each value of foundation modulus and for each boundary condition.

The results showed the use of elastic medium to support plates subject to axial load increase a great deal the buckling load, the results found are very close with those obtained by other analytical methods and experimental work.

The results also showed that foundation compensates the effect of the weakness of some types of constraint of side support and maximum benefit found for plate with one side simply supported the other free.

Keywords: Buckling, Finite Strip, Different Sides Support, Plates on Foundation.

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Authors: Lahcene Boukelkoul

Abstract:

The influence of finite ground conductivity is of great importance in calculating the induced voltages from the radiated electromagnetic fields due to lightning. In this paper, we try to give a comprehensive approach to calculate the impact of the ground on the radiated electromagnetic fields to lightning. The vertical component of lightning electric field is calculated with a reasonable approximation assuming a perfectly conducting ground in case the observation point does not exceed a few kilometers from the lightning channel. However, for distant observation points the radiated vertical component of lightning electric field is attenuated due finitely conducting ground. The attenuation is calculated using the expression elaborated for both low and high frequencies. The horizontal component of the electric field, however, is more affected by a finite conductivity of a ground. Besides, the contribution of the horizontal component of the electric field, to induced voltages on an overhead transmission line, is greater than that of the vertical component. Therefore, the calculation of the horizontal electric field is great concern for the simulation of lightning-induced voltages. For field to transmission lines coupling the ground impedance is calculated for early time behavior and for low frequency range.

Keywords: Ground impedance, horizontal electric field, lightning, transient propagation, vertical electric field.

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Authors: Brahmjit Singh

Abstract:

Mobile IP has been developed to provide the continuous information network access to mobile users. In IP-based mobile networks, location management is an important component of mobility management. This management enables the system to track the location of mobile node between consecutive communications. It includes two important tasks- location update and call delivery. Location update is associated with signaling load. Frequent updates lead to degradation in the overall performance of the network and the underutilization of the resources. It is, therefore, required to devise the mechanism to minimize the update rate. Mobile IPv6 (MIPv6) and Hierarchical MIPv6 (HMIPv6) have been the potential candidates for deployments in mobile IP networks for mobility management. HMIPv6 through studies has been shown with better performance as compared to MIPv6. It reduces the signaling overhead traffic by making registration process local. In this paper, we present performance analysis of MIPv6 and HMIPv6 using an analytical model. Location update cost function is formulated based on fluid flow mobility model. The impact of cell residence time, cell residence probability and user-s mobility is investigated. Numerical results are obtained and presented in graphical form. It is shown that HMIPv6 outperforms MIPv6 for high mobility users only and for low mobility users; performance of both the schemes is almost equivalent to each other.

Keywords: Wireless networks, Mobile IP networks, Mobility management, performance analysis, Handover.

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