Search results for: Geographic information system.

Authors: Zohreh Soltani, Seyedmohammadhossein Hosseinian

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Reduction of energy consumption in built infrastructure, through the installation of energy-efficient technologies, is a major approach to achieving sustainability. In practice, the viability of energy efficiency projects strongly depends on the cost reimbursement and profitability. These projects are subject to failure if the actual cost savings do not reimburse the project cost promptly. In such cases, refinancing could be a solution to benefit from the long-term returns of the project, if implemented wisely. However, very little is still known about the effect of refinancing options on financial performance of energy efficiency projects. In order to fill this gap, the present study investigates the financial behavior of energy efficiency projects with focus on refinancing options, such as Leveraged Loans. A System Dynamics (SD) model is introduced, and the model application is presented using an actual case-study data. The case study results indicate that while high-interest start-ups make using Leveraged Loan inevitable, refinancing can rescue the project and bring about profitability. This paper also presents some managerial implications of refinancing energy efficiency projects based on the case-study analysis. Results of this study help to implement financially viable energy efficiency projects so that the community could benefit from their environmental advantages widely.

Keywords: Energy efficiency projects, leveraged loan, refinancing, sustainability.

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Authors: Jihad S. Daba, J. P. Dubois, Yvette Antar

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With the exponential growth of cellular users, a new generation of cellular networks is needed to enhance the required peak data rates. The co-channel interference between neighboring base stations inhibits peak data rate increase. To overcome this interference, multi-cell cooperation known as coordinated multipoint transmission is proposed. Such a solution makes use of multiple-input-multiple-output (MIMO) systems under two different structures: Micro- and macro-diversity. In this paper, we study the capacity and bit error rate in cellular networks using MIMO technology. We analyse both micro- and macro-diversity schemes and develop a hybrid model that switches between macro- and micro-diversity in the case of hard handoff based on a cut-off range of signal-to-noise ratio values. We conclude that our hybrid switched micro-macro MIMO system outperforms classical MIMO systems at the cost of increased hardware and software complexity.

Keywords: Cooperative multipoint transmission, ergodic capacity, hard handoff, macro-diversity, micro-diversity, multiple-input-multiple-output systems, MIMO, orthogonal frequency division multiplexing, OFDM.

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Authors: Jakyoung Kim, Sungwook Jang

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The purpose of this study is to examine the research trends of life-long education for people with disabilities using a keyword network analysis. For this purpose, 151 papers were selected from 594 papers retrieved using keywords such as 'people with disabilities' and 'life-long education' in the Korean Education and Research Information Service. The Keyword network analysis was constructed by extracting and coding the keyword used in the title of the selected papers. The frequency of the extracted keywords, the centrality of degree, and betweenness was analyzed by the keyword network. The results of the keyword network analysis are as follows. First, the main keywords that appeared frequently in the study of life-long education for people with disabilities were 'people with disabilities', 'life-long education', 'developmental disabilities', 'current situations', 'development'. The research trends of life-long education for people with disabilities are focused on the current status of the life-long education and the program development. Second, the keyword network analysis and visualization showed that the keywords with high frequency of occurrences also generally have high degree centrality and betweenness centrality. In terms of the keyword network diagram, it was confirmed that research trends of life-long education for people with disabilities are centered on six prominent keywords. Based on these results, it was discussed that life-long education for people with disabilities in the future needs to expand the subjects and the supporting areas of the life-long education, and the research needs to be further expanded into more detailed and specific areas. 

Keywords: Life-long education, people with disabilities, research trends, keyword network analysis.

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Authors: Samir J. Deshmukh, Lalit B. Bhuyar, Shashank B. Thakre

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Partial combustion of biomass in the gasifier generates producer gas that can be used for heating purposes and as supplementary or sole fuel in internal combustion engines. In this study, the virgin biomass obtained from hingan shell is used as the feedstock for gasifier to generate producer gas. The gasifier-engine system is operated on diesel and on esters of vegetable oil of hingan in liquid fuel mode operation and then on liquid fuel and producer gas combination in dual fuel mode operation. The performance and emission characteristics of the CI engine is analyzed by running the engine in liquid fuel mode operation and in dual fuel mode operation at different load conditions with respect to maximum diesel savings in the dual fuel mode operation. It was observed that specific energy consumption in the dual fuel mode of operation is found to be in the higher side at all load conditions. The brake thermal efficiency of the engine using diesel or hingan oil methyl ester (HOME) is higher than that of dual fuel mode operation. A diesel replacement in the tune of 60% in dual fuel mode is possible with the use of hingan shell producer gas. The emissions parameters such CO, HC, NOx, CO2 and smoke are higher in the case of dual fuel mode of operation as compared to that of liquid fuel mode.

Keywords: Esters, performance, producer gas, vegetable oil.

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Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: Structural health monitoring, bridge health monitoring, sensor-based methods, machine-learning algorithms, model-based techniques, sensor placement, data acquisition, data analysis.

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Authors: Elyas Akbari, Jafar Hasani, Newsha Dehestani, Mohammad Khaleghi, Alireza Moradi

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The aim of the present study was to assess the effect of emotional experience induction in the mirror neurons systems (MNS) activity with regard to the spectrum of depressive symptoms. For this purpose, at first stage, 449 students of Kharazmi University of Tehran were selected randomly and completed the second version of the Beck Depression Inventory (BDI-II). Then, 36 students with standard Z-score equal or above +1.5 and equal or equal or below -1.5 were selected to construct two groups of high and low spectrum of depressive symptoms. In the next stage, the basic activity of MNS was recorded (mu wave) before presenting the positive and negative emotional video clips by Electroencephalography (EEG) technique. The findings related to emotion induction (neutral, negative and positive emotion) demonstrated that the activity of recorded mirror neuron areas had a significant difference between the depressive and non-depressive groups. These findings suggest that probably processing of negative emotions in depressive individuals is due to the idea that the mirror neurons in motor cortex matched up the activity of cognitive regions with the person’s schema. Considering the results of the present study, it could be said that the MNS provides a substrate where emotional disorders can be studied and evaluated.

Keywords: Emotional experiences, mirror neurons, depressive symptoms.

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Authors: M. Moslehpour, S. Khorsandi

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Due to shortage in IPv4 addresses, transition to IPv6 has gained significant momentum in recent years. Like Address Resolution Protocol (ARP) in IPv4, Neighbor Discovery Protocol (NDP) provides some functions like address resolution in IPv6. Besides functionality of NDP, it is vulnerable to some attacks. To mitigate these attacks, Internet Protocol Security (IPsec) was introduced, but it was not efficient due to its limitation. Therefore, SEND protocol is proposed to automatic protection of auto-configuration process. It is secure neighbor discovery and address resolution process. To defend against threats on NDP’s integrity and identity, Cryptographically Generated Address (CGA) and asymmetric cryptography are used by SEND. Besides advantages of SEND, its disadvantages like the computation process of CGA algorithm and sequentially of CGA generation algorithm are considerable. In this paper, we parallel this process between network resources in order to improve it. In addition, we compare the CGA generation time in self-computing and distributed-computing process. We focus on the impact of the malicious nodes on the CGA generation time in the network. According to the result, although malicious nodes participate in the generation process, CGA generation time is less than when it is computed in a one-way. By Trust Management System, detecting and insulating malicious nodes is easier.

Keywords: NDP, IPsec, SEND, CGA, Modifier, Malicious node, Self-Computing, Distributed-Computing.

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Authors: K. Kouzi

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In order to have stable and high performance of direct torque and flux control (DTFC) of double star induction motor drive (DSIM), proper on-line adaptation of the stator resistance is very important. This is inevitably due to the variation of the stator resistance during operating conditions, which introduces error in estimated flux position and the magnitude of the stator flux. Error in the estimated stator flux deteriorates the performance of the DTFC drive. Also, the effect of error in estimation is very important especially at low speed. Due to this, our aim is to overcome the sensitivity of the DTFC to the stator resistance variation by proposing on-line fuzzy estimation stator resistance. The fuzzy estimation method is based on an on-line stator resistance correction through the variations of the stator current estimation error and its variations. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of the suggested algorithm control is to avoid the drive instability that may occur in certain situations and ensure the tracking of the actual stator resistance. The validity of the technique and the improvement of the whole system performance are proved by the results.

Keywords: Direct torque control, dual stator induction motor, fuzzy logic estimation, stator resistance adaptation.

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Authors: Abdelhamid Louliej, Younes Jabrane

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Satellites are becoming indispensable assets to fifth-generation (5G) new radio architecture, complementing wireless and terrestrial communication links. The combination of satellites and 5G architecture allows consumers to access all next-generation services anytime, anywhere, including scenarios, like traveling to remote areas (without coverage). Nevertheless, this solution faces several challenges, such as a significant propagation delay, Doppler frequency shift, and high Peak-to-Average Power Ratio (PAPR), causing signal distortion due to the non-linear saturation of the High-Power Amplifier (HPA). To compensate for HPA non-linearity in 5G satellite transmission, an efficient pre-distorter scheme using Neural Networks (NN) is proposed. To assess the proposed NN pre-distorter, two types of HPA were investigated: Travelling Wave Tube Amplifier (TWTA) and Solid-State Power Amplifier (SSPA). The results show that the NN pre-distorter design presents an Error Vector Magnitude (EVM) improvement by 95.26%. Normalized Mean Square Error (NMSE) and Adjacent Channel Power Ratio (ACPR) were reduced by -43,66 dB and 24.56 dBm, respectively. Moreover, the system suffers no degradation of the Bit Error Rate (BER) for TWTA and SSPA amplifiers.

Keywords: Satellites, 5G, Neural Networks, High-Power Amplifier, Travelling Wave Tube Amplifier, Solid-State Power Amplifier, EVM, NMSE, ACPR.

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Authors: Rehab F. Abdel-Kader, Rabab M. Ramadan, Rawya Y. Rizk

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The recognition of human faces, especially those with different orientations is a challenging and important problem in image analysis and classification. This paper proposes an effective scheme for rotation invariant face recognition using Log-Polar Transform and Discrete Cosine Transform combined features. The rotation invariant feature extraction for a given face image involves applying the logpolar transform to eliminate the rotation effect and to produce a row shifted log-polar image. The discrete cosine transform is then applied to eliminate the row shift effect and to generate the low-dimensional feature vector. A PSO-based feature selection algorithm is utilized to search the feature vector space for the optimal feature subset. Evolution is driven by a fitness function defined in terms of maximizing the between-class separation (scatter index). Experimental results, based on the ORL face database using testing data sets for images with different orientations; show that the proposed system outperforms other face recognition methods. The overall recognition rate for the rotated test images being 97%, demonstrating that the extracted feature vector is an effective rotation invariant feature set with minimal set of selected features.

Keywords: Discrete Cosine Transform, Face Recognition, Feature Extraction, Log Polar Transform, Particle SwarmOptimization.

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Authors: Hadi Gholizadeh, Ali Tajdin

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: Goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression.

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Authors: Konstanca Nikolajevic, Nicolas Belanger, David Duvivier, Rabie Ben Atitallah, Abdelhakim Artiba

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Finding the optimal 3D path of an aerial vehicle under flight mechanics constraints is a major challenge, especially when the algorithm has to produce real time results in flight. Kinematics models and Pythagorian Hodograph curves have been widely used in mobile robotics to solve this problematic. The level of difficulty is mainly driven by the number of constraints to be saturated at the same time while minimizing the total length of the path. In this paper, we suggest a pragmatic algorithm capable of saturating at the same time most of dimensioning helicopter 3D trajectories’ constraints like: curvature, curvature derivative, torsion, torsion derivative, climb angle, climb angle derivative, positions. The trajectories generation algorithm is able to generate versatile complex 3D motion primitives feasible by a helicopter with parameterization of the curvature and the climb angle. An upper ”motion primitives’ concatenation” algorithm is presented based. In this article we introduce a new way of designing three-dimensional trajectories based on what we call the ”Dubins gliding symmetry conjecture”. This extremely performing algorithm will be soon integrated to a real-time decisional system dealing with inflight safety issues.

Keywords: Aerial robots, Motion primitives, Robotics.

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Authors: Budiyono, I N. Widiasa, S. Johari, Sunarso

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In this study, the kinetic of biogas production was studied by performing a series laboratory experiment using rumen fluid of animal ruminant as inoculums. Cattle manure as substrate was inoculated by rumen fluid to the anaerobic biodigester. Laboratory experiments using 400 ml biodigester were performed in batch operation mode. Given 100 grams of fresh cattle manure was fed to each biodigester and mixed with rumen fluid by manure : rumen weight ratio of 1:1 (MR11). The operating temperatures were varied at room temperature and 38.5 oC. The cumulative volume of biogas produced was used to measure the biodigester performance. The research showed that the rumen fluid inoculated to biodigester gave significant effect to biogas production (P<0.05). Rumen fluid inoculums caused biogas production rate and efficiency increase two to three times in compare to manure substrate without rumen fluid. With the rumen fluid inoculums, gave the kinetic parameters of biogas production i.e biogas production rate constants (U), maximum biogas production (A), and minimum time to produce biogas (λ) are 3.89 ml/(gVS.day); 172.51 (ml/gVS); dan 7.25 days, respectively. While the substrate without rumen fluid gave the kinetic parameters U, A, and λ are 1.74 ml/(gVS.day); 73.81 (ml/gVS); dan 14.75 days, respectively. The future work will be carried out to study the dynamics of biogas production if both the rumen inoculums and manure are fed in the continuous system.

Keywords: rumen fluid, inoculums, anaerobic digestion, biogasproduction.

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Authors: Munazza A. Mirza, Khawar Khurshid

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Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.

Keywords: Learning style, VARK, sensory preferences, identification model, didactic practices.

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Authors: Prakash G L, Chaitra K Meti, Poojitha K, Divya R.K.

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Wireless Sensor Network is Multi hop Self-configuring Wireless Network consisting of sensor nodes. The deployment of wireless sensor networks in many application areas, e.g., aggregation services, requires self-organization of the network nodes into clusters. Efficient way to enhance the lifetime of the system is to partition the network into distinct clusters with a high energy node as cluster head. The different methods of node clustering techniques have appeared in the literature, and roughly fall into two families; those based on the construction of a dominating set and those which are based solely on energy considerations. Energy optimized cluster formation for a set of randomly scattered wireless sensors is presented. Sensors within a cluster are expected to be communicating with cluster head only. The energy constraint and limited computing resources of the sensor nodes present the major challenges in gathering the data. In this paper we propose a framework to study how partially correlated data affect the performance of clustering algorithms. The total energy consumption and network lifetime can be analyzed by combining random geometry techniques and rate distortion theory. We also present the relation between compression distortion and data correlation.

Keywords: Clusters, multi hop, random geometry, rate distortion.

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Authors: Vahid R. Asghari, Mehrdad Ardebilipour

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In the context of spectrum surveillance, a new method to recover the code of spread spectrum signal is presented, while the receiver has no knowledge of the transmitter-s spreading sequence. In our previous paper, we used Genetic algorithm (GA), to recover spreading code. Although genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems, but nonetheless, by increasing the length of the code, we will often lead to an unacceptable slow convergence speed. To solve this problem we introduce Particle Swarm Optimization (PSO) into code estimation in spread spectrum communication system. In searching process for code estimation, the PSO algorithm has the merits of rapid convergence to the global optimum, without being trapped in local suboptimum, and good robustness to noise. In this paper we describe how to implement PSO as a component of a searching algorithm in code estimation. Swarm intelligence boasts a number of advantages due to the use of mobile agents. Some of them are: Scalability, Fault tolerance, Adaptation, Speed, Modularity, Autonomy, and Parallelism. These properties make swarm intelligence very attractive for spread spectrum code estimation. They also make swarm intelligence suitable for a variety of other kinds of channels. Our results compare between swarm-based algorithms and Genetic algorithms, and also show PSO algorithm performance in code estimation process.

Keywords: Code estimation, Particle Swarm Optimization(PSO), Spread spectrum.

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Authors: Ezequiel Garcia-Rodriguez, Luis A. Ochoa-Franco, Adrian I. Cervantes-Servin

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In this work, the Ictalurus punctatus species estimated available physical habitat is compared with the estimated physical habitat for the same but modified river reach, with the aim of creating a linear park, along a length of 5 500 m. To determine the effect of ecological park construction, on physical habitat of the Lerma river stretch of study, first, the available habitat for the Ictalurus punctatus species was estimated through the simulation of the physical habitat, by using surveying, hydraulics, and habitat information gotten at the river reach in its actual situation. Second, it was estimated the available habitat for the above species, upon the simulation of the physical habitat through the proposed modification for the ecological park creation. Third, it is presented a comparison between both scenarios in terms of available habitat estimated for Ictalurus punctatus species, concluding that in cases of adult and spawning life stages, changes in the channel to create an ecological park would produce a considerable loss of potentially usable habitat (PUH), while in the case of the juvenile life stage PUH remains virtually unchanged, and in the case of life stage fry the PUH would increase due to the presence of velocities and depths of lesser magnitude, due to the presence of minor flow rates and lower volume of the wet channel. It is expected that habitat modification for linear park construction may produce the lack of Ictalurus punktatus species conservation at the river reach of the study.

Keywords: Habitat modification, Ictalurus punctatus, Lerma, river, linear park.

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Authors: Marek Halenár, Eva Tvrdá, Tomáš Slanina, Ľubomír Ondruška, Eduard Kolesár, Peter Massányi, Adriana Kolesárová

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The present in vitro study was designed to reveal whether amygdalin (AMG) is able to cause changes to the motility, viability and mitochondrial activity of rabbit spermatozoa. New Zealand White rabbits (n = 10) aged four months were used in the study. Semen samples were collected from each animal and used for the in vitro incubation. The samples were divided into five equal parts and diluted with saline supplemented with 0, 0.5, 1, 2.5 and 5 mg/mL AMG. At times 0h, 3h and 5h spermatozoa motion parameters were assessed using the SpermVision™ computer-aided sperm analysis (CASA) system, cell viability was examined with the metabolic activity (MTT) assay, and the eosin-nigrosin staining technique was used to evaluate the viability of rabbit spermatozoa. All AMG concentrations exhibited stimulating effects on the spermatozoa activity, as shown by a significant preservation of the motility (P<0.05 with respect to 0.5 mg/mL and 1 mg/mL AMG; Time 5 h) and mitochondrial activity (P< 0.05 in case of 0.5 mg/mL AMG; P< 0.01 in case of 1 mg/mL AMG; P < 0.001 with respect to 2.5 mg/mL and 5 mg/mL AMG; Time 5 h). None of the AMG doses supplemented had any significant impact of the spermatozoa viability. In conclusion, the data revealed that short-term co-incubation of spermatozoa with AMG may result in a higher preservation of the sperm structural integrity and functional activity.

Keywords: Amygdalin, CASA, mitochondrial activity, motility, rabbits, spermatozoa, viability.

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Authors: Yessine Hadj Kacem, Adel Mahfoudhi, Hedi Tmar, Mohamed Abid

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Unified Modeling Language (UML) extensions for real time embedded systems (RTES) co-design, are taking a growing interest by a great number of industrial and research communities. The extension mechanism is provided by UML profiles for RTES. It aims at improving an easily-understood method of system design for non-experts. On the other hand, one of the key items of the co- design methods is the Hardware/Software partitioning and scheduling tasks. Indeed, it is mandatory to define where and when tasks are implemented and run. Unfortunately the main goals of co-design are not included in the usual practice of UML profiles. So, there exists a need for mapping used models to an execution platform for both schedulability test and HW/SW partitioning. In the present work, test schedulability and design space exploration are performed at an early stage. The proposed approach adopts Model Driven Engineering MDE. It starts from UML specification annotated with the recent profile for the Modeling and Analysis of Real Time Embedded systems MARTE. Following refinement strategy, transformation rules allow to find a feasible schedule that satisfies timing constraints and to define where tasks will be implemented. The overall approach is experimented for the design of a football player robot application.

Keywords: MDE, UML profile, scheduling analysis, HW/SW partitioning.

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Authors: L. A. Muhammad, M. S. Argungu

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Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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Authors: M. Cañada-Soriano, C. Aparicio-Fernández, P. Sebastián Ferrer Gisbert, M. Val Field, J.-L. Vivancos-Bono

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The lack of insulation along with the existence of air leakages constitute a meaningful impact on the energy performance of buildings. Both of them lead to increases in the energy demand through additional heating and/or cooling loads. Additionally, they cause thermal discomfort. In order to quantify these uncontrolled air currents, the Blower Door test can be used. It is a standardized procedure that determines the airtightness of a space by characterizing the rate of air leakages through the envelope surface. In this sense, the low-energy buildings complying with the Passive House design criteria are required to achieve high levels of airtightness. Due to the invisible nature of air leakages, additional tools are often considered to identify where the infiltrations take place such as the infrared thermography. The aim of this study is to assess the airtightness of a typical Mediterranean dwelling house, refurbished under the Passive House standard, using the Blower Door test. Moreover, the building energy performance modelling tools TRNSYS (TRaNsient System Simulation program) and TRNFlow (TRaNsient Flow) have been used to estimate the energy demand in different scenarios. In this sense, a sequential implementation of three different energy improvement measures (insulation thickness, glazing type and infiltrations) have been analyzed.

Keywords: Airtightness, blower door, TRNSYS, infrared thermography, energy demand.

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Authors: Carolijn Van Noort

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The aim of this research is to understand how the emerging power bloc BRICS employs infrastructure development narratives to construct a new world order. BRICS is an international body consisting of five emerging countries that collaborate on economic and political issues: Brazil, Russia, India, China, and South Africa. This study explores the projection of infrastructure development narratives through an analysis of BRICS’ attention to infrastructure investment and financing, its support of the New Partnership on African Development and the establishment of the New Development Bank in Shanghai. The theory of Strategic Narratives is used to explore BRICS’ commitment to infrastructure development and to distinguish three layers: system narratives (BRICS as a global actor to propose development reform), identity narratives (BRICS as a collective identity joining efforts to act upon development aspirations) and issue narratives (BRICS committed to a range of issues of which infrastructure development is prominent). The methodology that is employed is a narrative analysis of BRICS’ official documents, media statements, and website imagery. A comparison of these narratives illuminates tensions at the three layers and among the five member states. Identifying tensions among development infrastructure narratives provides an indication of how policymaking for infrastructure development could be improved. Subsequently, it advances BRICS’ ability to act as a global actor to construct a new world order.

Keywords: BRICS, emerging powers, infrastructural development, strategic narratives.

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Authors: S. R. Shamili, C. Natarajan, J. Karthikeyan

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Rapid growth of world population and widespread urbanization has remarkably increased the development of the construction industry which caused a huge demand for sand and gravels. Environmental problems occur when the rate of extraction of sand, gravels, and other materials exceeds the rate of generation of natural resources; therefore, an alternative source is essential to replace the materials used in concrete. Now-a-days, electronic products have become an integral part of daily life which provides more comfort, security, and ease of exchange of information. These electronic waste (E-Waste) materials have serious human health concerns and require extreme care in its disposal to avoid any adverse impacts. Disposal or dumping of these E-Wastes also causes major issues because it is highly complex to handle and often contains highly toxic chemicals such as lead, cadmium, mercury, beryllium, brominates flame retardants (BFRs), polyvinyl chloride (PVC), and phosphorus compounds. Hence, E-Waste can be incorporated in concrete to make a sustainable environment. This paper deals with the composition, preparation, properties, classification of E-Waste. All these processes avoid dumping to landfills whilst conserving natural aggregate resources, and providing a better environmental option. This paper also provides a detailed literature review on the behaviour of concrete with incorporation of E-Wastes. Many research shows the strong possibility of using E-Waste as a substitute of aggregates eventually it reduces the use of natural aggregates in concrete.

Keywords: Disposal, electronic waste, landfill, toxic chemicals.

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Authors: Emmanouel Koumoulas, Aikaterini Rokkou, Marios Moschakis

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Theagenio" in Thessaloniki exists and works for three centuries now as a hospital. Since 1975, it has been operating as an Integrated Special Cancer Hospital and since 1985 it has been integrated into the National Health System. "Theagenio" Cancer Hospital is located at the central web of Thessaloniki residential complex and consists of two buildings, the "Symeonidio Research Center", which was completed in 1962 and the Nursing Ward, a project that was later completed in 1975. This paper examines the design of the Hospital Unit according to the requirements of the energy design of buildings. Initially, the energy characteristics of the Hospital are recorded, followed by a detailed presentation of the electromechanical installations. After the existing situation has been captured and with the help of the software TEE-KENAK, different scenarios for the energy upgrading of the buildings have been studied. Proposals for upgrading concern both the shell, e.g. installation of external thermal insulation, replacement of frames, addition of shading systems, etc. as well as electromechanical installations, e.g. use of ceiling fans, improvements in heating and cooling systems, interventions in lighting, etc. The simulation calculates the future energy status of the buildings and presents the economic benefits of the proposed interventions with reference to the environmental profits that arise.

Keywords: Energy consumption in hospitals, energy saving interventions, energy upgrading, hospital facilities.

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Authors: Qing Dai, Zhengkui Lin, Jiajia Zhang, Yi Qu

Abstract:

Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving.

Keywords: Autonomous cars, bottleneck model, activity utility, user equilibrium.

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Authors: Sudip Kumar Kundu, Charu Singh

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The climatic condition over Indian region is highly dependent on monsoon. India receives maximum amount of rainfall during southwest monsoon. Indian economy is highly dependent on agriculture. The presence of flood and drought years influenced the total cultivation system as well as the economy of the country as Indian agricultural systems is still highly dependent on the monsoon rainfall. The present study has been planned to investigate the flood and drought years for the north-west Himalayan region from 1951 to 2014 by using area average Indian Meteorological Department (IMD) rainfall data. For this investigation the Normalized index (NI) has been utilized to find out whether the particular year is drought or flood. The data have been extracted for the north-west Himalayan (NWH) region states namely Uttarakhand (UK), Himachal Pradesh (HP) and Jammu and Kashmir (J&K) to find out the rainy season average rainfall for each year, climatological mean and the standard deviation. After calculation it has been plotted by the diagrams (or graphs) to show the results- some of the years associated with drought years, some are flood years and rest are neutral. The flood and drought years can also relate with the large-scale phenomena El-Nino and La-Lina.

Keywords: Indian Meteorological Department, Rainfall, Normalized index, Flood, Drought, NWH.

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Authors: Youngsub Oh, Youngsoon Kim

Abstract:

As the second largest group among international marriages in Korea, Vietnamese married immigrant women have been exposed to psychological crisis like divorce and family violence. The purpose of this study is to understand how to counsel those women from the perspective of indigenous healing as their own psychological problem-solving way. To this end, this study reviewed Vietnamese cultural literatures on their mentality as well as Vietnamese medical literatures on indigenous healing. The research results are as follows: First, cultural foundations that have formed Vietnamese mentality are Confucian value system, reserved communication, and religious pluralism. These cultural backgrounds play an important role in understanding their own therapeutic tradition. Second, Vietnamese indigenous healing considers cause of mental disease as a collapse of balance between mind and body and environment. Thus, indigenous treatment deals with psychological problems through a recovery of the balance from the holistic perspective. In fact, indigenous healing has been actively practiced in everyday place as well as hospital until today. The implications of Vietnamese indigenous healing for multicultural counseling in Korea are as follows: First, Korean counselors need to interactively understand their own assumptions on indigenous healing as well as counselees’ own assumptions. Second, a variety of psychological intervention strategies can be drawn from Vietnamese indigenous healing. Third, indigenous healing needs to be integrated with modern techniques of counseling and psychotherapy, as both treatments are not mutually exclusive but complementary.

Keywords: Indigenous healing, Vietnamese married immigrant women in Korea, multicultural counseling.

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Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini

Abstract:

Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.

Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.

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Authors: Sangeeta Tripathi, Muna Al Shahri

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This research article presents the changing role and status of women in Oman. Transformation of women’s status started with the regime of His Majesty Sultan Qaboos Bin Said in 1970. It is always desired by the Sultan to enable women in all the ways for the balance growth of the country. Forbidding full face veil for women in public offices is one of the best efforts for their empowerment. Women education is also increasing rapidly. They are getting friendly with new information communication technology and using different social media applications such as WhatsApp, Instagram and Facebook for interaction and economic growth. Though there are some traditional and tribal boundaries, women are infused with courage and enjoying fair treatment and equal opportunities in different career positions. The study will try to explore changing mindset of young Omani women towards these traditional tribal boundaries, cultural heritage, business and career: ‘How are young Omani women making balance between work and social prestige?’, ‘How are they preserving their cultural values, embracing new technologies and approaching social network to enhance their economic power.’ This paper will discover their hurdles while using internet for their new entrepreneur. It will also examine the prospects of online business in Oman. The mixed research methodology is applied to find out the result.

Keywords: Advertising, business, entrepreneurship, Social Media, tribal barrier, traditional barriers.

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Authors: Mansoor Ahsan, Khalid Rafique, Farrukh Mazhar

Abstract:

Unmanned Aerial Vehicles (UAVs) have gained tremendous importance, in both Military and Civil, during first decade of this century. In a UAV, onboard computer (autopilot) autonomously controls the flight and navigation of the aircraft. Based on the aircraft role and flight envelope, basic to complex and sophisticated controllers are used to stabilize the aircraft flight parameters. These controllers constitute the autopilot system for UAVs. The autopilot systems, most commonly, provide lateral and longitudinal control through Proportional-Integral-Derivative (PID) controllers or Phase-lead or Lag Compensators. Various techniques are commonly used to ‘tune’ gains of these controllers. Some techniques used are, in-flight step-by-step tuning, software-in-loop or hardware-in-loop tuning methods. Subsequently, numerous in-flight tests are required to actually ‘fine-tune’ these gains. However, an optimization-based tuning of these PID controllers or compensators, as presented in this paper, can greatly minimize the requirement of in-flight ‘tuning’ and substantially reduce the risks and cost involved in flight-testing.

Keywords: Unmanned aerial vehicle (UAV), autopilot, autonomous controls, PID controler gains tuning, optimization.

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