Search results for: learning efficiency

Authors: Abraham Undu, Stephen Akuma

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Websites are becoming a major component of an organization’s success in our ever globalizing competitive world. The website symbolizes an organization, interacting or projecting an organization’s principles, culture, values, vision, and perspectives. It is an interface connecting organizations and their clients. The university, as an academic institution, makes use of a website to communicate and offer computing services to its stakeholders (students, staff, host community, university management etc). Unfortunately, website designers often give more consideration to the technology, organizational structure and business objectives of the university than to the usability of the site. Website designers end up designing university websites which do not meet the needs of the primary users. This empirical study investigated the Benue State University website from the point view of students. This research was realized by using a standardized website usability questionnaire based on the five factors of usability defined by WAMMI (Website Analysis and Measurement Inventory): attractiveness, controllability, efficiency, learnability and helpfulness. The result of the investigation showed that the university website (https://portal.bsum.edu.ng/) has neutral usability level because of the usability issues associated with the website. The research recommended feasible solutions to improve the usability of the website from the users’ perspective and also provided a modified usability model that will be used for better evaluation of the Benue State University website.

Keywords: Usability, usability factors, university websites, user’s perspective, WAMMI, modified usability model, Benue State University.

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Authors: Wanghongshu Zhou

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This study aims to explore the relationship between the second language motivational self-system (L2MSS) and the willingness to communicate (WTC) among Chinese non-English major students in order to provide pedagogical implications for English as a Foreign Language (EFL) classrooms in Chinese universities. By employing a mixed methods approach, we involved 103 Chinese non-English major students from a typical university in China, conducted questionnaire survey to measure their levels of L2WTC and L2MSS level, and then analyzed the correlation between the two above mentioned variables. Semi-structured interviews were conducted with eight participants to provide a deeper understanding and explanation of the questionnaire data. Findings show that 1) Chinese non-English major students’ ideal L2 self and L2 learning experience could positively predict their L2 WTC in EFL class; 2) Chinese non-English major students’ ought-to L2 self might have no significant impact on their L2 WTC in EFL class; and 3) self-confidence might be another main factor that will influence Chinese non-English major students’ L2 WTC in EFL class. These findings might shed light on the second language acquisition field and provide pedagogical recommendations for pre-service as well as in-service EFL teachers.

Keywords: Chinese non-English major students, L2 Motivation, L2 willingness to communicate, self-confidence.

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Authors: Mitchell J. McHugh, John J. Case

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Systems engineering is a holistic discipline that seeks to organize and optimize complex, interdisciplinary systems. With the growth of artificial intelligence, systems engineers must face the challenge of leveraging artificial intelligence systems to solve complex problems. This paper analyzes the integration of systems engineering and artificial intelligence and discusses how artificial intelligence systems embody the systems decision process (SDP). The SDP is a four-stage problem-solving framework that outlines how systems engineers can design and implement solutions using value-focused thinking. This paper argues that artificial intelligence models can replicate the SDP, thus validating its flexible, value-focused foundation. The authors demonstrate this by developing a machine vision mobile application that can classify weapons to augment the decision-making role of an Army subject matter expert. This practical application was an end-to-end design challenge that highlights how artificial intelligence systems embody systems engineering principles. The impact of this research demonstrates that the SDP is a dynamic tool that systems engineers should leverage when incorporating artificial intelligence within the systems that they develop.

Keywords: Computer vision, machine learning, mobile application, systems engineering, systems decision process.

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Authors: Nuawi M. Z., Lamin F., Ismail A. R., Abdullah S., Wahid Z.

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A filter is used to remove undesirable frequency information from a dynamic signal. This paper shows that the Znotch filter filtering technique can be applied to remove the noise nuisance from a machining signal. In machining, the noise components were identified from the sound produced by the operation of machine components itself such as hydraulic system, motor, machine environment and etc. By correlating the noise components with the measured machining signal, the interested components of the measured machining signal which was less interfered by the noise, can be extracted. Thus, the filtered signal is more reliable to be analysed in terms of noise content compared to the unfiltered signal. Significantly, the I-kaz method i.e. comprises of three dimensional graphical representation and I-kaz coefficient, Z∞ could differentiate between the filtered and the unfiltered signal. The bigger space of scattering and the higher value of Z∞ demonstrated that the signal was highly interrupted by noise. This method can be utilised as a proactive tool in evaluating the noise content in a signal. The evaluation of noise content is very important as well as the elimination especially for machining operation fault diagnosis purpose. The Z-notch filtering technique was reliable in extracting noise component from the measured machining signal with high efficiency. Even though the measured signal was exposed to high noise disruption, the signal generated from the interaction between cutting tool and work piece still can be acquired. Therefore, the interruption of noise that could change the original signal feature and consequently can deteriorate the useful sensory information can be eliminated.

Keywords: Digital signal filtering, I-kaz method, Machiningmonitoring, Noise Cancelling, Sound

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Authors: Eftah Bte. Moh Hj Abdullah, Izazol Binti Idris, Abd Aziz Bin Abd Shukor

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This study aims to identify the understanding expectations of school administrators concerning school assessment. The researcher utilized a qualitative descriptive study on 19 administrators from three secondary schools in the North Kinta district. The respondents had been interviewed on their understanding expectations of school assessment using the focus group discussion method. Overall findings showed that the administrators’ understanding expectations of school assessment was weak; especially in terms of content focus, articulation across age and grade, transparency and fairness, as well as the pedagogical implications. Findings from interviews indicated that administrators explained their understanding expectations of school assessment from the aspect of school management, and not from the aspect of instructional leadership or specifically as assessment leaders. The study implications from the administrators’ understanding expectations may hint at the difficulty of the administrators to function as assessment leaders, in order to reduce their focus as manager, and move towards their primary role in the process of teaching and learning. The administrator, as assessment leaders, would be able to reach assessment goals via collaboration in identifying and listing teacher assessment competencies, how to construct assessment capacity, how to interpret assessment correctly, the use of assessment and how to use assessment information to communicate confidently and effectively to the public.

Keywords: Assessment leaders, assessment goals, instructional leadership, understanding expectation of assessment.

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Authors: Andra Blumberga, Armands Gravelsins, Haralds Vigants, Dagnija Blumberga

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The paper discovers biotechonomy development analysis by use of system dynamics modelling. The research is connected with investigations of biomass application for production of bioproducts with higher added value. The most popular bioresource is wood, and therefore, the main question today is about future development and eco-design of products. The paper emphasizes and evaluates energy sector which is open for use of wood logs, wood chips, wood pellets and so on. The main aim for this research study was to build a framework to analyse development perspectives for wood pellet production. To reach the goal, a system dynamics model of energy wood supplies, processing, and consumption is built. Production capacity, energy consumption, changes in energy and technology efficiency, required labour source, prices of wood, energy and labour are taken into account. Validation and verification tests with available data and information have been carried out and indicate that the model constitutes the dynamic hypothesis. It is found that the more is invested into pellets production, the higher the specific profit per production unit compared to wood logs and wood chips. As a result, wood chips production is decreasing dramatically and is replaced by wood pellets. The limiting factor for pellet industry growth is availability of wood sources. This is governed by felling limit set by the government based on sustainable forestry principles.

Keywords: Bioenergy, biotechonomy, system dynamics modelling, wood pellets.

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Authors: S. M. Kamruzzaman, Md. Monirul Islam

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Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users to gain a better understanding of how the networks solve the problems. A new rule extraction algorithm, called rule extraction from artificial neural networks (REANN) is proposed and implemented to extract symbolic rules from ANNs. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Explicitness of the extracted rules is supported by comparing them to the symbolic rules generated by other methods. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification problems, such as breast cancer, iris, diabetes, and season classification problems, demonstrate the effectiveness of the proposed approach with good generalization ability.

Keywords: Backpropagation, clustering algorithm, constructivealgorithm, continuous activation function, pruning algorithm, ruleextraction algorithm, symbolic rules.

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Authors: Nicolae Bold, Daniel Nijloveanu

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The idea of cropping-system is a method used by farmers. It is an environmentally-friendly method, protecting the natural resources (soil, water, air, nutritive substances) and increase the production at the same time, taking into account some crop particularities. The combination of this powerful method with the concepts of genetic algorithms results into a possibility of generating sequences of crops in order to form a rotation. The usage of this type of algorithms has been efficient in solving problems related to optimization and their polynomial complexity allows them to be used at solving more difficult and various problems. In our case, the optimization consists in finding the most profitable rotation of cultures. One of the expected results is to optimize the usage of the resources, in order to minimize the costs and maximize the profit. In order to achieve these goals, a genetic algorithm was designed. This algorithm ensures the finding of several optimized solutions of cropping-systems possibilities which have the highest profit and, thus, which minimize the costs. The algorithm uses genetic-based methods (mutation, crossover) and structures (genes, chromosomes). A cropping-system possibility will be considered a chromosome and a crop within the rotation is a gene within a chromosome. Results about the efficiency of this method will be presented in a special section. The implementation of this method would bring benefits into the activity of the farmers by giving them hints and helping them to use the resources efficiently.

Keywords: Genetic algorithm, chromosomes, genes, cropping, agriculture.

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Authors: M. R. Mustafa, M. H. Isa, R. B. Rezaur

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The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Keywords: ANN, discharge, modeling, prediction, sediment,

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Authors: Thiang, Handry Khoswanto, Rendy Pangaldus

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Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.

Keywords: Artificial neural network, back propagation, inverse kinematics, manipulator, robot.

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Authors: Mohammed T. Hayajneh

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Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: Composite, fuzzy, tool life, wear.

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Authors: Jheng-Long Wu, Pei-Chann Chang, Shih-Ling Chang, Liang-Chih Yu, Jui-Feng Yeh, Chin-Sheng Yang

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The Major Depressive Disorder has been a burden of medical expense in Taiwan as well as the situation around the world. Major Depressive Disorder can be defined into different categories by previous human activities. According to machine learning, we can classify emotion in correct textual language in advance. It can help medical diagnosis to recognize the variance in Major Depressive Disorder automatically. Association language incremental is the characteristic and relationship that can discovery words in sentence. There is an overlapping-category problem for classification. In this paper, we would like to improve the performance in classification in principle of no overlapping-category problems. We present an approach that to discovery words in sentence and it can find in high frequency in the same time and can-t overlap in each category, called Association Language Features by its Category (ALFC). Experimental results show that ALFC distinguish well in Major Depressive Disorder and have better performance. We also compare the approach with baseline and mutual information that use single words alone or correlation measure.

Keywords: Association language features, Emotion Classification, Overlap-Category Feature, Nature Language Processing.

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Authors: S. Chahba, R. Sehab, A. Akrad, C. Morel

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Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: Electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit fault diagnosis, artificial neural network.

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Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the least square support vector machine (LSSVM) optimized by an improved sparrow search algorithm combined with the variational mode decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of intrinsic mode functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the LSSVM. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: Load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine.

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Authors: Pierre Kancir, Jean-Philippe Diguet, Marc Sevaux

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One of the main difficulties in developing multi-robot systems (MRS) is related to the simulation and testing tools available. Indeed, if the differences between simulations and real robots are too significant, the transition from the simulation to the robot won’t be possible without another long development phase and won’t permit to validate the simulation. Moreover, the testing of different algorithmic solutions or modifications of robots requires a strong knowledge of current tools and a significant development time. Therefore, the availability of tools for MRS, mainly with flying drones, is crucial to enable the industrial emergence of these systems. This research aims to present the most commonly used tools for MRS simulations and their main shortcomings and presents complementary tools to improve the productivity of designers in the development of multi-vehicle solutions focused on a fast learning curve and rapid transition from simulations to real usage. The proposed contributions are based on existing open source tools as Gazebo simulator combined with ROS (Robot Operating System) and the open-source multi-platform autopilot ArduPilot to bring them to a broad audience.

Keywords: ROS, ArduPilot, MRS, simulation, drones, Gazebo.

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Authors: Pornchai Suriya-Amrit, Suratsawadee Kungsanant, Boonyarach Kitiyanan

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There has been a growing interest in utilizing surfactants in remediation processes to separate the hydrophobic volatile organic compounds (HVOCs) from aqueous solution. One attractive process is cloud point extraction (CPE), which utilizes nonionic surfactants as a separating agent. Since the surfactant cost is a key determination of the economic viability of the process, it is important that the surfactants are recycled and reused. This work aims to study the performance of the co-current vacuum stripping using a packed column for HVOCs removal from contaminated surfactant solution. Six types HVOCs are selected as contaminants. The studied surfactant is the branched secondary alcohol ethoxylates (AEs), Tergitol TMN-6 (C14H30O2). The volatility and the solubility of HVOCs in surfactant system are determined in terms of an apparent Henry’s law constant and a solubilization constant, respectively. Moreover, the HVOCs removal efficiency of vacuum stripping column is assessed in terms of percentage of HVOCs removal and the overall liquid phase volumetric mass transfer coefficient. The apparent Henry’s law constant of benzenz , toluene, and ethyl benzene were 7.00×10-5, 5.38×10-5, 3.35× 10-5 respectively. The solubilization constant of benzene, toluene, and ethyl benzene were 1.71, 2.68, 7.54 respectively. The HVOCs removal for all solute were around 90 percent.

Keywords: Apparent Henry’s law constant, Branched secondary alcohol ethoxylates, Vacuum Stripping.

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Authors: Sufian Ashraf Mazhari, Surendra Kumar

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In this paper performance of Puma 560 manipulator is being compared for hybrid gradient descent and least square method learning based ANFIS controller with hybrid Genetic Algorithm and Generalized Pattern Search tuned radial basis function based Neuro-Fuzzy controller. ANFIS which is based on Takagi Sugeno type Fuzzy controller needs prior knowledge of rule base while in radial basis function based Neuro-Fuzzy rule base knowledge is not required. Hybrid Genetic Algorithm with generalized Pattern Search is used for tuning weights of radial basis function based Neuro- fuzzy controller. All the controllers are checked for butterfly trajectory tracking and results in the form of Cartesian and joint space errors are being compared. ANFIS based controller is showing better performance compared to Radial Basis Function based Neuro-Fuzzy Controller but rule base independency of RBF based Neuro-Fuzzy gives it an edge over ANFIS

Keywords: Neuro-Fuzzy, Robotic Control, RBFNF, ANFIS, Hybrid GA.

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Authors: Anita Kéri

Abstract:

Recent developments in the field of education have led to a renewed interest in teaching methodologies and practices. Gamification is fast becoming a key instrument in the education of new generations and besides other methods, serious games have become the center of attention. Ready-built serious games are available for most higher education institutions to buy and implement. However, monetary restraints and the unalterable nature of the games might deter most higher education institutions from the application of these serious games. Therefore, there is a continuously growing need for a customizable serious game that has been developed based on a concrete need analysis and experts’ opinion. There has been little evidence so far of serious games that have been created based on relevant and current need analysis from higher education institution teachers, professional practitioners and students themselves. Therefore, the aim of this current paper is to analyze the needs of higher education institution educators with special emphasis on their needs, the applicability of serious games in their classrooms, and exploring options for the development of a customizable serious game framework. The paper undertakes to analyze workshop discussions on implementing serious games in education and propose a customizable serious game framework applicable in the education of the new generation. Research results show that the most important feature of a serious game is its customizability. The fact that practitioners are able to manage different scenarios and upload their own content to a game seems to be a key to the increasingly widespread application of serious games in the classroom.

Keywords: Education, gamification, game-based learning, serious games.

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Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

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This study employs a method based on image analyses and structure information to detect accumulated ice on known structures. The icing of marine vessels and offshore structures causes significant reductions in their efficiency and creates unsafe working conditions. Image processing methods are used to measure ice loads automatically. Most image processing methods are developed based on captured image analyses. In this method, ice loads on structures are calculated by defining structure coordinates and processing captured images. A pyramidal structure is designed with nine cylindrical bars as the known structure of experimental setup. Unsymmetrical ice accumulated on the structure in a cold room represents the actual case of experiments. Camera intrinsic and extrinsic parameters are used to define structure coordinates in the image coordinate system according to the camera location and angle. The thresholding method is applied to capture images and detect iced structures in a binary image. The ice thickness of each element is calculated by combining the information from the binary image and the structure coordinate. Averaging ice diameters from different camera views obtains ice thicknesses of structure elements. Comparison between ice load measurements using this method and the actual ice loads shows positive correlations with an acceptable range of error. The method can be applied to complex structures defining structure and camera coordinates.

Keywords: Camera calibration, Ice detection, ice load measurements, image processing.

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Authors: Djelloul Nedjai

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The issue of cultural awareness triggers many controversies, especially in a context where individuals do not share the same cultural backgrounds and characteristics. The Algerian context is no exception. It is extensively important to highlight how culture remains essential in many areas. In higher education, for instance, culture plays a pivotal role in shaping individuals’ perceptions and attitudes. Henceforth, the current paper attempts to look at the perceptions of the British culture held by students engaged in learning English as a Foreign Language (EFL) at the department of English at Banta 2 University, Algeria. It also inquiries into EFL students’ perceptions of British culture. To address the aforementioned research queries, a descriptive study has been carried out wherein a questionnaire of 15 items has been deployed to collect students’ attitudes and perceptions toward British culture. Results showcase that, indeed, EFL students of the department of English at Banta 2 University hold both positive and negative perceptions towards British culture at different levels. The explanation could relate to the student's lack of acquaintance with and awareness of British culture. Consequently, this paper is an attempt to address the issue of cultural awareness from the perspective of EFL students.

Keywords: British culture, cultural awareness, EFL students’ perceptions, higher education.

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Authors: M. Aminu Sanda, K. Ewontumah

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This paper explored the challenges faced by the management of a Ghanaian state enterprise in managing conflicts and disturbances associated with its attempt to implement new work practices to enhance its capability to operate as a commercial entity. The purpose was to understand the extent to which organizational involvement, consistency and adaptability influence employees’ consumption of new work practices in transforming the organization’s organizational activity system. Using selfadministered questionnaires, data were collected from one hundred and eighty (180) employees and analyzed using both descriptive and inferential statistics. The results showed that constraints in organizational involvement and adaptability prevented the positive consumption of new work practices by employees in the organization. It is also found that the organization’s employees failed to consume the new practices being implemented, because they perceived the process as non-involving, and as such, did not encourage the development of employee capability, empowerment, and teamwork. The study concluded that the failure of the organization’s management to create opportunities for organizational learning constrained its ability to get employees consume the new work practices, which situation could have facilitated the organization’s capabilities of operating as a commercial entity.

Keywords: Organizational transformation, new work practices, work practice consumption, organizational involvement, state-owned enterprise, Ghana.

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Authors: V. Sandeep Kumar, S. Anuradha

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The high Peak to Average Power Ratio (PAR) in Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) can significantly reduce power efficiency and performance. In this paper, we address the problem of PAPR reduction for FBMC-OQAM systems using Tone Reservation (TR) technique. Due to the overlapping structure of FBMCOQAM signals, directly applying TR schemes of OFDM systems to FBMC-OQAM systems is not effective. We improve the tone reservation (TR) technique by employing sliding window with Active Constellation Extension for the PAPR reduction of FBMC-OQAM signals, called sliding window tone reservation Active Constellation Extension (SW-TRACE) technique. The proposed SW-TRACE technique uses the peak reduction tones (PRTs) of several consecutive data blocks to cancel the peaks of the FBMC-OQAM signal inside a window, with dynamically extending outer constellation points in active(data-carrying) channels, within margin-preserving constraints, in order to minimize the peak magnitude. Analysis and simulation results compared to the existing Tone Reservation (TR) technique for FBMC/OQAM system. The proposed method SW-TRACE has better PAPR performance and lower computational complexity.

Keywords: FBMC-OQAM, peak-to-average power ratio, sliding window, tone reservation Active Constellation Extension.

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Authors: G. Sevilla, S. Zapata, F. Giraldo, E. Torres, C. Collazos

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This work describes a framework for teaching of global software engineering (GSE) in university undergraduate programs. This framework proposes a method of teaching that incorporates adequate techniques of software requirements elicitation and validated tools of communication, critical aspects to global software development scenarios. The use of proposed framework allows teachers to simulate small software development companies formed by Latin American students, which build information systems. Students from three Latin American universities played the roles of engineers by applying an iterative development of a requirements specification in a global software project. The proposed framework involves the use of a specific purpose Wiki for asynchronous communication between the participants of the process. It is also a practice to improve the quality of software requirements that are formulated by the students. The additional motivation of students to participate in these practices, in conjunction with peers from other countries, is a significant additional factor that positively contributes to the learning process. The framework promotes skills for communication, negotiation, and other complementary competencies that are useful for working on GSE scenarios.

Keywords: Requirements analysis, distributed requirements engineering, practical experiences, collaborative support.

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Authors: Shoujia Fang, Guoqing Ding, Xin Chen

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The quality of press-fit assembly is closely related to reliability and safety of product. The paper proposed a keypoint detection method based on convolutional neural network to improve the accuracy of keypoint detection in press-fit curve. It would provide an auxiliary basis for judging quality of press-fit assembly. The press-fit curve is a curve of press-fit force and displacement. Both force data and distance data are time-series data. Therefore, one-dimensional convolutional neural network is used to process the press-fit curve. After the obtained press-fit data is filtered, the multi-layer one-dimensional convolutional neural network is used to perform the automatic learning of press-fit curve features, and then sent to the multi-layer perceptron to finally output keypoint of the curve. We used the data of press-fit assembly equipment in the actual production process to train CNN model, and we used different data from the same equipment to evaluate the performance of detection. Compared with the existing research result, the performance of detection was significantly improved. This method can provide a reliable basis for the judgment of press-fit quality.

Keywords: Keypoint detection, curve feature, convolutional neural network, press-fit assembly.

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Authors: Duangkamol Thitivesa, Abigail Melad Essien

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This paper explores the use of project work in a content-based instruction in a Rajabhat University, a teacher college, where student teachers are instructed to perform teaching roles mainly in basic education level. Its aim is to link theory to practice, and to help language teachers maximize the full potential of project work for genuine communication and give real meaning to writing activity. Two research questions are formulated to guide this study: a) What is the academic achievement of the students- writing skill against the 70% attainment target after the use of project to enhance the skill? and b) To what degree is the development of the students- writing skills during the course of project to enhance the skill? The sample of the study comprised of 38 fourth-year English major students. The data was collected by means of achievement test, student writing works, and project diary. The scores in the summative achievement test were analyzed by mean score, standard deviation, and t-test. Project diary serves as students- record of the language acquired during the project. List of structures and vocabulary noted in the diary has shown students- ability to attend to, recognize, and focus on meaningful patterns of language forms.

Keywords: EFL classroom, Project-Based Learning, project work, writing skill.

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Authors: Gulnaziya Issabayeva, Mohamed Kheireddine Aroua

Abstract:

commercially produced in Malaysia granular palm shell activated carbon (PSAC) was biomodified with bacterial biomass (Bacillus subtilis) to produce a hybrid biosorbent of higher efficiency. The obtained biosorbent was evaluated in terms of adsorption capacity to remove copper and zinc metal ions from aqueous solutions. The adsorption capacity was evaluated in batch adsorption experiments where concentrations of metal ions varied from 20 to 350 mg/L. A range of pH from 3 to 6 of aqueous solutions containing metal ions was tested. Langmuir adsorption model was used to interpret the experimental data. Comparison of the adsorption data of the biomodified and original palm shell activated carbon showed higher uptake of metal ions by the hybrid biosorbent. A trend in metal ions uptake increase with the increase in the solution-s pH was observed. The surface characterization data indicated a decrease in the total surface area for the hybrid biosorbent; however the uptake of copper and zinc by it was at least equal to the original PSAC at pH 4 and 5. The highest capacity of the hybrid biosorbent was observed at pH 5 and comprised 22 mg/g and 19 mg/g for copper and zinc, respectively. The adsorption capacity at the lowest pH of 3 was significantly low. The experimental results facilitated identification of potential factors influencing the adsorption of copper and zinc onto biomodified and original palm shell activated carbon.

Keywords: Adsorption, biomodification, copper, zinc, palm shell carbon.

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Authors: Ren-Junn Hwang, Chung-Chien Lu, Jain-Shing Wu

Abstract:

Cloud outsource storage is one of important services in cloud computing. Cloud users upload data to cloud servers to reduce the cost of managing data and maintaining hardware and software. To ensure data confidentiality, users can encrypt their files before uploading them to a cloud system. However, retrieving the target file from the encrypted files exactly is difficult for cloud server. This study proposes a protocol for performing multikeyword searches for encrypted cloud data by applying k-nearest neighbor technology. The protocol ranks the relevance scores of encrypted files and keywords, and prevents cloud servers from learning search keywords submitted by a cloud user. To reduce the costs of file transfer communication, the cloud server returns encrypted files in order of relevance. Moreover, when a cloud user inputs an incorrect keyword and the number of wrong alphabet does not exceed a given threshold; the user still can retrieve the target files from cloud server. In addition, the proposed scheme satisfies security requirements for outsourced data storage.

Keywords: Fault-tolerance search, multi-keywords search, outsource storage, ranked search, searchable encryption.

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Authors: Byounghyun Kim, Youngjoon Han, Hernsoo Hahn

Abstract:

The purpose of this study is to find natural gait of biped robot such as human being by analyzing the COG (Center Of Gravity) trajectory of human being's gait. It is discovered that human beings gait naturally maintain the stability and use the minimum energy. This paper intends to find the natural gait pattern of biped robot using the minimum energy as well as maintaining the stability by analyzing the human's gait pattern that is measured from gait image on the sagittal plane and COG trajectory on the frontal plane. It is not possible to apply the torques of human's articulation to those of biped robot's because they have different degrees of freedom. Nonetheless, human and 5-link biped robots are similar in kinematics. For this, we generate gait pattern of the 5-link biped robot by using the GA algorithm of adaptation gait pattern which utilize the human's ZMP (Zero Moment Point) and torque of all articulation that are measured from human's gait pattern. The algorithm proposed creates biped robot's fluent gait pattern as that of human being's and to minimize energy consumption because the gait pattern of the 5-link biped robot model is modeled after consideration about the torque of human's each articulation on the sagittal plane and ZMP trajectory on the frontal plane. This paper demonstrate that the algorithm proposed is superior by evaluating 2 kinds of the 5-link biped robot applied to each gait patterns generated both in the general way using inverse kinematics and in the special way in which by considering visuality and efficiency.

Keywords: 5-link biped robot, gait pattern, COG (Center OfGravity), ZMP (Zero Moment Point).

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Authors: André C. Silva, Débora N. Sousa, Elenice M. S. Silva, Thales P. Fontes, Raphael S. Tomaz

Abstract:

Starches are widely used as depressant in froth flotation operations in Brazil due to their efficiency, increasing the selectivity in the inverse flotation of quartz depressing iron ore. Starches market have been growing and improving in recent years, leading to better products attending the requirements of the mineral industry. The major source of starch used for iron ore is corn starch, which needs to be gelatinized with sodium hydroxide (NaOH) prior to use. This stage has a direct impact on industrials costs, once the lowest consumption of NaOH in gelatinization provides better control of the pH in the froth flotation and reduces the amount of electrolytes present in the pulp. In order to evaluate the gelatinization degree of different starches and flour were subjected to the addiction of NaOH and temperature variation experiments. Samples of starch (corn, cassava, HIPIX 100, HIPIX 101 and HIPIX 102 commercialized by Ingredion) and flour (cassava and potato) were tested. The starch samples were characterized through Scanning Electronic Microscopy and the amylose content were determined through spectrometry, swelling and solubility tests. The gelatinization was carried out through titration with NaOH, keeping the solution temperature constant at 40 ^oC. At the end of the tests, the optimal amount of NaOH consumed to gelatinize the starch or flour from different botanical sources was established and a correlation between the content of amylopectin in the starch and the starch/NaOH ratio needed for its gelatinization.

Keywords: Froth flotation, gelatinization, sodium hydroxide, starches and flours.

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Authors: C. lo Storto

Abstract:

This paper presents an approach based on the adoption of a distributed cognition framework and a non parametric multicriteria evaluation methodology (DEA) designed specifically to compare e-commerce websites from the consumer/user viewpoint. In particular, the framework considers a website relative efficiency as a measure of its quality and usability. A website is modelled as a black box capable to provide the consumer/user with a set of functionalities. When the consumer/user interacts with the website to perform a task, he/she is involved in a cognitive activity, sustaining a cognitive cost to search, interpret and process information, and experiencing a sense of satisfaction. The degree of ambiguity and uncertainty he/she perceives and the needed search time determine the effort size – and, henceforth, the cognitive cost amount – he/she has to sustain to perform his/her task. On the contrary, task performing and result achievement induce a sense of gratification, satisfaction and usefulness. In total, 9 variables are measured, classified in a set of 3 website macro-dimensions (user experience, site navigability and structure). The framework is implemented to compare 40 websites of businesses performing electronic commerce in the information technology market. A questionnaire to collect subjective judgements for the websites in the sample was purposely designed and administered to 85 university students enrolled in computer science and information systems engineering undergraduate courses.

Keywords: Website, e-commerce, DEA, distributed cognition, evaluation, comparison.

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