Search results for: clinical application.

Authors: Mohamed Gouskir, Belaid Bouikhalene, Hicham Aissaoui, Benachir Elhadadi

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In this paper, we present an application of Riemannian geometry for processing non-Euclidean image data. We consider the image as residing in a Riemannian manifold, for developing a new method to brain edge detection and brain extraction. Automating this process is a challenge due to the high diversity in appearance brain tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based anisotropic diffusion tensor for the segmentation task by integrating both image edge geometry and Riemannian manifold (geodesic, metric tensor) to regularize the convergence contour and extract complex anatomical structures. We check the accuracy of the segmentation results on simulated brain MRI scans of single T1-weighted, T2-weighted and Proton Density sequences. We validate our approach using two different databases: BrainWeb database, and MRI Multiple sclerosis Database (MRI MS DB). We have compared, qualitatively and quantitatively, our approach with the well-known brain extraction algorithms. We show that using a Riemannian manifolds to medical image analysis improves the efficient results to brain extraction, in real time, outperforming the results of the standard techniques.

Keywords: Riemannian manifolds, Riemannian Tensor, Brain Segmentation, Non-Euclidean data, Brain Extraction.

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Authors: Mohammad Songolzadeh, Maryam Takht Ravanchi, Mansooreh Soleimani

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CO2 is the primary anthropogenic greenhouse gas, accounting for 77% of the human contribution to the greenhouse effect in 2004. In the recent years, global concentration of CO2 in the atmosphere is increasing rapidly. CO2 emissions have an impact on global climate change. Anthropogenic CO2 is emitted primarily from fossil fuel combustion. Carbon capture and storage (CCS) is one option for reducing CO2 emissions. There are three major approaches for CCS: post-combustion capture, pre-combustion capture and oxyfuel process. Post-combustion capture offers some advantages as existing combustion technologies can still be used without radical changes on them. There are several post combustion gas separation and capture technologies being investigated, namely; (a) absorption, (b) cryogenic separation, (c) membrane separation (d) micro algal biofixation and (e) adsorption. Apart from establishing new techniques, the exploration of capture materials with high separation performance and low capital cost are paramount importance. However, the application of adsorption from either technology, require easily regenerable and durable adsorbents with a high CO2 adsorption capacity. It has recently been reported that the cost of the CO2 capture can be reduced by using this technology. In this paper, the research progress (from experimental results) in adsorbents for CO2 adsorption, storage, and separations were reviewed and future research directions were suggested as well.

Keywords: Carbon capture and storage, pre-combustion, postcombustion, adsorption

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Authors: Eu Tteum Ha, Kwang Ryel Ryu

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As smartphones are equipped with various sensors, there have been many studies focused on using these sensors to create valuable applications. Human activity recognition is one such application motivated by various welfare applications, such as the support for the elderly, measurement of calorie consumption, lifestyle and exercise patterns analyses, and so on. One of the challenges one faces when using smartphone sensors for activity recognition is that the number of sensors should be minimized to save battery power. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we adopt to deal with this twelve-class problem uses various methods. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point, but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window. The experiments compared the performance of four kinds of basic multi-class classifiers and the performance of four kinds of ensemble learning methods based on three kinds of basic multi-class classifiers. The results show that while the method with the highest accuracy is ECOC based on Random forest.

Keywords: Ensemble learning, activity recognition, smartphone accelerometer.

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Authors: M. Mojaddam, M. Araei, T. Saki Nejad, M. Soltani Howyzeh

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In order to study the effect of different levels of triple super phosphate chemical fertilizer and biological phosphate fertilizer (fertile 2) on some morphological traits of corn this research was carried out in Ahvaz in 2002 as a factorial experiment in randomized complete block design with 4 replications). The experiment included two factors: first, biological phosphate fertilizer (fertile 2) at three levels of 0, 100, 200 g/ha; second, triple super phosphate chemical fertilizer at three levels of 0, 60, 90 kg/ha of pure phosphorus (P2O5). The obtained results indicated that fertilizer treatments had a significant effect on some morphological traits at 1% probability level. In this regard, P2B2 treatment (100 g/ha biological phosphate fertilizer (fertile 2) and 60 kg/ha triple super phosphate fertilizer) had the greatest plant height, stem diameter, number of leaves and ear length. It seems that in Ahvaz weather conditions, decrease of consumption of triple superphosphate chemical fertilizer to less than a half along with the consumption of biological phosphate fertilizer (fertile 2) is highly important in order to achieve optimal results. Therefore, it can be concluded that biological fertilizers can be used as a suitable substitute for some of the chemical fertilizers in sustainable agricultural systems.

Keywords: Biological phosphate fertilizer, corn (SC704), morphological, triple super phosphate.

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Authors: H. C. O. Reis, A. S. Cossolin, B. A. P. Santos, K. C. Castro, G. M. Pereira, V. C. Silva, P. T. Sousa Jr, E. L. Dall’Oglio, L. G. Vasconcelos, E. B. Morais

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In this study, malt bagasse, a low-cost waste biomass, was tested as a biosorbent to remove the cationic dye Malachite green (MG) from aqueous solution. Batch biosorption experiments were investigated as functions of different experimental parameters such as initial pH, salt (NaCl) concentration, contact time, temperature and initial dye concentration. Higher removal rates of MG were obtained at pH 8 and 10. The equilibrium and kinetic studies suggest that the biosorption follows Langmuir isotherm and the pseudo-second-order model. The maximum monolayer adsorption capacity was estimated at 117.65 mg/g (at 45 °C). According to Dubinin–Radushkevich (D-R) isotherm model, biosorption of MG onto malt bagasse occurs physically. The thermodynamic parameters such as Gibbs free energy, enthalpy and entropy indicated that the MG biosorption onto malt bagasse is spontaneous and endothermic. The results of the ionic strength effect indicated that the biosorption process under study had a strong tolerance under high salt concentrations. It can be concluded that malt bagasse waste has potential for application as biosorbent for removal of MG from aqueous solution.

Keywords: Color removal, kinetic and isotherm studies, thermodynamic parameters, FTIR.

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Authors: Frank C. Pan, Chih-Hao Chen

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The purpose of this study is to discuss the effect of the intervention of exercise behavior change plan for high school students on study subjects- social and psychological factors and exercise stages. This research uses the transtheoretical model as the research framework. One experiment group and one control group were used in a quasi-experimental design research. The experimental group accepted health-related physical fitness course and the traditional course; the control group accepted traditional physical education course. There is a significant difference before and after the intervention in the experimental group. Karl-s test shows the experimental group gained a better improvement than that in the control group. The Analysis of Covariance had shown the exercise stages (F=7.62, p<0.05), and the perceived exercise benefit (F=16.91, p<0.05) of the experimental group were obviously larger than those of the control group. There was no major effect on the perceived exercise barrier (F=0.61, p>0.05) after the intervention of exercise behavior change plan. However, the rate of high school students the practical implementation of the exercise is not high, obviously influenced by the exercise barrier. The academic and examination pressure may be the major causes of the exercise barrier in the high school.

Keywords: Transtheoretical model (TTM), High school students, exercise behavior

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Authors: Fatemeh Cheraghali, Saeedeh Shojaee-Aliabadi, Seyede Marzieh Hosseini, Leila Mirmoghtadaie

Abstract:

In recent years, the field of natural antimicrobial and antioxidant compounds is one of the main research topics in the food industry. Application of agricultural residues is mainly cheap, and available resources are receiving increased attention. Walnut green husk is one of the agricultural residues that is considered as natural compounds with biological properties because of phenolic compounds. In this study, maltodextrin 10% was used for microencapsulation of walnut green husk extract. At first, the extract was examined to consider extraction yield, total phenolic compounds, and antioxidant activation. The results showed the extraction yield of 81.43%, total phenolic compounds of 3997 [mg GAE/100 g], antioxidant activity [DPPH] of 84.85% for walnut green husk extract. Antioxidant activity is about 75%-81% and by DPPH. At the next stage, microencapsulation was done by spry-drying method. The microencapsulation efficiency was 72%-79%. The results of SEM tests confirmed this microencapsulation process. In addition, microencapsulated and free extract was more effective on gram-positive bacteria’s rather than the gram-negative ones. According to the study, walnut green husk can be used as a cheap antioxidant and antimicrobial compounds due to sufficient value of phenolic compounds.

Keywords: Biopolymer, microencapsulation, Spray-drying, Walnut green husk.

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Authors: Rana Th. A. Al-Rubaye, Burcin Atilgan, Richard J. Holmes, Arthur A. Garforth

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Structured catalysts formed from the growth of zeolites on substrates is an area of increasing interest due to the increased efficiency of the catalytic process, and the ability to provide superior heat transfer and thermal conductivity for both exothermic and endothermic processes. However, the generation of structured catalysts represents a significant challenge when balancing the relationship variables between materials properties and catalytic performance, with the Na2O, H2O and Al2O3 gel composition paying a significant role in this dynamic, thereby affecting the both the type and range of application. The structured catalyst films generated as part of this investigation have been characterised using a range of techniques, including X-ray diffraction (XRD), Electron microscopy (SEM), Energy Dispersive X-ray analysis (EDX) and Thermogravimetric Analysis (TGA), with the transition from oxide-on-alloy wires to hydrothermally synthesised uniformly zeolite coated surfaces being demonstrated using both SEM and XRD. The robustness of the coatings has been ascertained by subjecting these to thermal cycling (ambient to 550oC), with the results indicating that the synthesis time and gel compositions have a crucial effect on the quality of zeolite growth on the FeCrAlloy wires. Finally, the activity of the structured catalyst was verified by a series of comparison experiments with standard zeolite Y catalysts in powdered pelleted forms.

Keywords: FeCrAlloy, Structured catalyst, and Zeolite Y.

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Authors: Wadea Ameen, Abdulrahman Al-Ahmari, Osama Abdulhameed

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Electron beam melting (EBM) is one of the modern additive manufacturing (AM) technologies. In EBM, the electron beam melts metal powder into a fully solid part layer by layer. Since EBM is a new technology, most designers are unaware of the capabilities and the limitations of EBM technology. Also, many engineers are facing many challenges to utilize the technology because of a lack of design rules for the technology. The aim of this study is to identify the capabilities and the limitations of EBM technology in fabrication of small features and overhang structures and develop a design rules that need to be considered by designers and engineers. In order to achieve this objective, a series of experiments are conducted. Several features having varying sizes were designed, fabricated, and evaluated to determine their manufacturability limits. In general, the results showed the capabilities and limitations of the EBM technology in fabrication of the small size features and the overhang structures. In the end, the results of these investigation experiments are used to develop design rules. Also, the results showed the importance of developing design rules for AM technologies in increasing the utilization of these technologies.

Keywords: Additive manufacturing, design for additive manufacturing, electron beam melting, self-supporting overhang.

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Authors: G. Kloudova, M. Stehlik

Abstract:

Optimal human performance is a key goal in the professional setting of military pilots, which is a highly challenging atmosphere. The aviation environment requires substantial cognitive effort and is rich in potential stressors. Therefore, it is important to analyze variables such as mental workload to ensure safe conditions. Pilot mental workload could be measured using several tools, but most of them are very subjective. This paper details research conducted with military pilots using psychophysiological methods such as electroencephalography (EEG) and heart rate (HR) monitoring. The data were measured in a simulator as well as under real flight conditions. All of the pilots were exposed to highly demanding flight tasks and showed big individual response differences. On that basis, the individual pattern for each pilot was created counting different EEG features and heart rate variations. Later on, it was possible to distinguish the most difficult flight tasks for each pilot that should be more extensively trained. For training purposes, an application was developed for the instructors to decide which of the specific tasks to focus on during follow-up training. This complex system can help instructors detect the mentally demanding parts of the flight and enhance the training of military pilots to achieve optimal performance.

Keywords: Cognitive effort, human performance, military pilots, psychophysiological methods.

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Authors: Raksha Sharma, Vishnu Kant Soni, Manoj Kumar Mishra, Prachet Bhuyan, Utpal Chandra Dey

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Grid computing is a group of clusters connected over high-speed networks that involves coordinating and sharing computational power, data storage and network resources operating across dynamic and geographically dispersed locations. Resource management and job scheduling are critical tasks in grid computing. Resource selection becomes challenging due to heterogeneity and dynamic availability of resources. Job scheduling is a NP-complete problem and different heuristics may be used to reach an optimal or near optimal solution. This paper proposes a model for resource and job scheduling in dynamic grid environment. The main focus is to maximize the resource utilization and minimize processing time of jobs. Grid resource selection strategy is based on Max Heap Tree (MHT) that best suits for large scale application and root node of MHT is selected for job submission. Job grouping concept is used to maximize resource utilization for scheduling of jobs in grid computing. Proposed resource selection model and job grouping concept are used to enhance scalability, robustness, efficiency and load balancing ability of the grid.

Keywords: Agent, Grid Computing, Job Grouping, Max Heap Tree (MHT), Resource Scheduling.

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Authors: Siqing S. Chen

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Landscape connectivity combines a description of the physical structure of the landscape with special species- response to that structure, which forms the theoretical background of applying landscape connectivity principles in the practices of landscape planning and design. In this study, a residential development project in the southern United States was used to explore the meaning of landscape connectivity and its application in town planning. The vast rural landscape in the southern United States is conspicuously characterized by the hedgerow trees or groves. The patchwork landscape of fields surrounded by high hedgerows is a traditional and familiar feature of the American countryside. Hedgerows are in effect linear strips of trees, groves, or woodlands, which are often critical habitats for wildlife and important for the visual quality of the landscape. Based on geographic information system (GIS) and statistical analysis (FRAGSTAT), this study attempts to quantify the landscape connectivity characterized by hedgerows in south Alabama where substantial areas of authentic hedgerow landscape are being urbanized due to the ever expanding real estate industry and high demand for new residential development. The results of this study shed lights on how to balance the needs of new urban development and biodiversity conservation by maintaining a higher level of landscape connectivity, thus will inform the design intervention.

Keywords: Biodiversity, Connectivity, Landscape planning, GIS

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Authors: Sulaiman Al Amro

Abstract:

There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies, and therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and thus the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.

Keywords: Cyberattacks, detection, first-order logic, Metaverse, privacy, security.

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Authors: Mohsen Pirdashti, Masoomeh Omidi, Hemmatollah Pidashti

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Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.

Keywords: Analytical Hierarchy Process, ARP, Delphi, Multi- criteria decision making, Citrogypsum

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: Channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, Lévy flight distribution, optimization, improved multi–objective Firefly algorithms, Pareto optimal.

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Authors: A. Pashkevich, A. Klimchik, D. Chablat

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The paper focuses on the enhanced stiffness modeling of robotic manipulators by taking into account influence of the external force/torque acting upon the end point. It implements the virtual joint technique that describes the compliance of manipulator elements by a set of localized six-dimensional springs separated by rigid links and perfect joints. In contrast to the conventional formulation, which is valid for the unloaded mode and small displacements, the proposed approach implicitly assumes that the loading leads to the non-negligible changes of the manipulator posture and corresponding amendment of the Jacobian. The developed numerical technique allows computing the static equilibrium and relevant force/torque reaction of the manipulator for any given displacement of the end-effector. This enables designer detecting essentially nonlinear effects in elastic behavior of manipulator, similar to the buckling of beam elements. It is also proposed the linearization procedure that is based on the inversion of the dedicated matrix composed of the stiffness parameters of the virtual springs and the Jacobians/Hessians of the active and passive joints. The developed technique is illustrated by an application example that deals with the stiffness analysis of a parallel manipulator of the Orthoglide family

Keywords: Robotic manipulators, Stiffness model, Loaded mode, Nonlinear effects, Buckling, Orthoglide manipulator

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Authors: Sabina Baraković, Dragan Jevtić, Jasmina Baraković Husić

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Wireless mobile communications have experienced the phenomenal growth through last decades. The advances in wireless mobile technologies have brought about a demand for high quality multimedia applications and services. For such applications and services to work, signaling protocol is required for establishing, maintaining and tearing down multimedia sessions. The Session Initiation Protocol (SIP) is an application layer signaling protocols, based on request/response transaction model. This paper considers SIP INVITE transaction over an unreliable medium, since it has been recently modified in Request for Comments (RFC) 6026. In order to help in assuring that the functional correctness of this modification is achieved, the SIP INVITE transaction is modeled and analyzed using Colored Petri Nets (CPNs). Based on the model analysis, it is concluded that the SIP INVITE transaction is free of livelocks and dead codes, and in the same time it has both desirable and undesirable deadlocks. Therefore, SIP INVITE transaction should be subjected for additional updates in order to eliminate undesirable deadlocks. In order to reduce the cost of implementation and maintenance of SIP, additional remodeling of the SIP INVITE transaction is recommended.

Keywords: Colored Petri Nets, SIP INVITE, state space, dead marking

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Authors: Hani Shafeek, Muhammed Marsudi

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The purpose of this work is examining the multiproduct multi-stage in a battery production line. To improve the performances of an assembly production line by determine the efficiency of each workstation. Data collected from every workstation. The data are throughput rate, number of operator, and number of parts that arrive and leaves during part processing. Data for the number of parts that arrives and leaves are collected at least at the amount of ten samples to make the data is possible to be analyzed by Chi-Squared Goodness Test and queuing theory. Measures of this model served as the comparison with the standard data available in the company. Validation of the task time value resulted by comparing it with the task time value based on the company database. Some performance factors for the multi-product multi-stage in a battery production line in this work are shown. The efficiency in each workstation was also shown. Total production time to produce each part can be determined by adding the total task time in each workstation. To reduce the queuing time and increase the efficiency based on the analysis any probably improvement should be done. One probably action is by increasing the number of operators how manually operate this workstation.

Keywords: Production line, manufacturing, performance measurement, queuing theory.

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Authors: Fabian Horn, Reinhard Guthke

Abstract:

In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.

Keywords: bottom-up approach, gene clusters, melting temperature, metabolic pathway, microarray probe design, probe selection

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Authors: Sadi Vural, Hiromi Tomii, Hironori Yamauchi

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With the advent of digital cinema and digital broadcasting, copyright protection of video data has been one of the most important issues. We present a novel method of watermarking for video image data based on the hardware and digital wavelet transform techniques and name it as “traceable watermarking" because the watermarked data is constructed before the transmission process and traced after it has been received by an authorized user. In our method, we embed the watermark to the lowest part of each image frame in decoded video by using a hardware LSI. Digital Cinema is an important application for traceable watermarking since digital cinema system makes use of watermarking technology during content encoding, encryption, transmission, decoding and all the intermediate process to be done in digital cinema systems. The watermark is embedded into the randomly selected movie frames using hash functions. Embedded watermark information can be extracted from the decoded video data. For that, there is no need to access original movie data. Our experimental results show that proposed traceable watermarking method for digital cinema system is much better than the convenient watermarking techniques in terms of robustness, image quality, speed, simplicity and robust structure.

Keywords: Decoder, Digital content, JPEG2000 Frame, System-On-Chip, traceable watermark, Hash Function, CRC-32.

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Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng

Abstract:

The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.

 

Keywords: Electro-Rheological Fluid, Semi-active vibration control, shock absorber, type 2 fuzzy control.

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Authors: M. Mohebbi, K. Shakeri

Abstract:

Since the actuator capacity is limited, in the real application of active control systems under sever earthquakes it is conceivable that the actuators saturate, hence the actuator saturation should be considered as a constraint in design of optimal controllers. In this paper optimal design of active controllers for nonlinear structures by considering actuator saturation, has been studied. The proposed method for designing optimal controllers is based on defining an optimization problem which the objective has been to minimize the maximum displacement of structure when a limited capacity for actuator has been used. To this end a single degree of freedom (SDF) structure with a bilinear hysteretic behavior has been simulated under a white noise ground acceleration of different amplitudes. Active tendon control mechanism, comprised of prestressed tendons and an actuator, and extended nonlinear Newmark method based instantaneous optimal control algorithm have been used. To achieve the best results, the weights corresponding to displacement, velocity, acceleration and control force in the performance index have been optimized by the Distributed Genetic Algorithm (DGA). Results show the effectiveness of the proposed method in considering actuator saturation. Also based on the numerical simulations it can be concluded that the actuator capacity and the average value of required control force are two important factors in designing nonlinear controllers which consider the actuator saturation.

Keywords: Active control, Actuator Saturation, Distributedgeneticalgorithms, Nonlinear.

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Authors: Surya Prakash, Sunil Kumar Sinha

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This paper deals with the application of artificial neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy Inference System(ANFIS) approach to Load Frequency Control (LFC) of multi unequal area hydro-thermal interconnected power system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Area-1 and area-2 consists of thermal reheat power plant whereas area-3 and area-4 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent controller like ANFIS, ANN and Fuzzy controllers and conventional PI and PID control approaches. To enhance the performance of intelligent and conventional controller sliding surface is included. The performances of the controllers are simulated using MATLAB/SIMULINK package. A comparison of ANFIS, ANN, Fuzzy, PI and PID based approaches shows the superiority of proposed ANFIS over ANN & fuzzy, PI and PID controller for 1% step load variation.

Keywords: Load Frequency Control (LFC), ANFIS, ANN & Fuzzy, PI, PID Controllers, Area Control Error (ACE), Tie-line, MATLAB / SIMULINK.

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Authors: Elham Jelodari Mamaghani, Christian Prins, Haoxun Chen

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In this paper, there is concentration on collaborative transportation planning (CTP) among multiple carriers with pickup and delivery requests and time windows. This problem is a vehicle routing problem with constraints from standard vehicle routing problems and new constraints from a real-world application. In the problem, each carrier has a finite number of vehicles, and each request is a pickup and delivery request with time window. Moreover, each carrier has reserved requests, which must be served by itself, whereas its exchangeable requests can be outsourced to and served by other carriers. This collaboration among carriers can help them to reduce total transportation costs. A mixed integer programming model is proposed to the problem. To solve the model, a hybrid algorithm that combines Genetic Algorithm and Simulated Annealing (GASA) is proposed. This algorithm takes advantages of GASA at the same time. After tuning the parameters of the algorithm with the Taguchi method, the experiments are conducted and experimental results are provided for the hybrid algorithm. The results are compared with those obtained by a commercial solver. The comparison indicates that the GASA significantly outperforms the commercial solver.

Keywords: Centralized collaborative transportation, collaborative transportation with pickup and delivery, collaborative transportation with time windows, hybrid algorithm of GA and SA.

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Authors: Estevan B. Costa, Armando M. Toda, Marcell A. A. Mesquita, Jacques D. Brancher

Abstract:

The advances in technology in the last five years allowed an improvement in the educational area, as the increasing in the development of educational software. One of the techniques that emerged in this lapse is called Gamification, which is the utilization of video game mechanics outside its bounds. Recent studies involving this technique provided positive results in the application of these concepts in many areas as marketing, health and education. In the last area there are studies that covers from elementary to higher education, with many variations to adequate to the educators methodologies. Among higher education, focusing on IT courses, data structures are an important subject taught in many of these courses, as they are base for many systems. Based on the exposed this paper exposes the development of an interactive web learning environment, called DSLEP (Data Structure Learning Platform), to aid students in higher education IT courses. The system includes basic concepts seen on this subject such as stacks, queues, lists, arrays, trees and was implemented to ease the insertion of new structures. It was also implemented with gamification concepts, such as points, levels, and leader boards, to engage students in the search for knowledge and stimulate self-learning.

Keywords: Gamification, Interactive learning environment, Data structures, e-learning.

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: Stochastic models, ARIMA, extreme streamflow, Karkheh River.

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Authors: Veronika Solilová, Danuše Nerudová

Abstract:

The paper examines the interaction between the environmental taxation, size of government spending on environmental protection and greenhouse gas emissions and gross inland energy consumption. The aim is to analyze the effects of environmental taxation and government spending on environmental protection as an environmental policy instruments on greenhouse gas emissions and gross inland energy consumption in the EU15. The empirical study is performed using a VAR approach with the application of aggregated data of EU15 over the period 1995 to 2012. The results provide the evidence that the reactions of greenhouse gas emission and gross inland energy consumption to the shocks of environmental policy instruments are strong, mainly in the short term and decay to zero after about 8 years. Further, the reactions of the environmental policy instruments to the shocks of greenhouse gas emission and gross inland energy consumption are also strong in the short term, however with the deferred effects. In addition, the results show that government spending on environmental protection together with gross inland energy consumption has stronger effect on greenhouse gas emissions than environmental taxes in EU15 over the examined period.

Keywords: VAR analysis, greenhouse gas emissions, environmental taxation, government spending.

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Authors: Ganesan V.

Abstract:

Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.

Keywords: Diagnostic, inference engine, knowledge base and user interface.

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Authors: P. Chultheera, T. Rirksomboon, S. Kulprathipanja, C. Liu, W. Chinsirikul, N. Kerddonfag

Abstract:

Gas separation by selective transport through polymeric membranes is one of the rapid growing branches of membrane technology. However, the tradeoff between the permeability and selectivity is one of the critical challenges encountered by pure polymer membranes, which in turn limits their large-scale application. To enhance gas separation performances, mixed matrix membranes (MMMs) have been developed. In this study, MMMs were prepared by a solution-coating method and tested for CO₂/CH₄ separation through permeability and selectivity using a membrane testing unit at room temperature and a pressure of 100 psig. The fabricated MMMs were composed of silicone rubber dispersed with the activated carbon individually absorbed with polyethylene glycol (PEG) as a liquid additive. PEG emulsified silicone rubber MMMs showed superior gas separation on cellulose acetate membrane with both high permeability and selectivity compared with silicone rubber membrane and alone support membrane. However, the MMMs performed limited stability resulting from the undesirable PEG leakage. To stabilize the MMMs, PEG was then incorporated into activated carbon by adsorption. It was found that the incorporation of solid and liquid was effective to improve the separation performance of MMMs.

Keywords: Mixed matrix membrane, membrane, CO2/CH4 separation, activated carbon.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

Abstract:

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

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

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