Abstract: In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network.
The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters.
Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output.
This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc.
From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.
Abstract: The characteristics of fluid flow and heat transfer over a permeable shrinking sheet is studied. The governing partial differential equations are transformed into a set of ordinary differential equations, which are then solved numerically using MATLAB routine boundary value problem solver bvp4c. Numerical results show that dual solutions are possible for a certain range of the suction parameter. A stability analysis is performed to determine which solution is linearly stable and physically realizable.
Abstract: In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.
As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.
Abstract: Traditional software engineering allows engineers to propose to their clients multiple specialized software distributions assembled from a shared set of software assets. The management of these assets however requires a trade-off between client satisfaction and software engineering process. Clients have more and more difficult to find a distribution or components based on their needs from all of distributed repositories.
This paper proposes a software engineering for a user-driven software product line in which engineers define a Feature Model but users drive the actual software distribution on demand. This approach makes the user become final actor as a release manager in software engineering process, increasing user product satisfaction and simplifying user operations to find required components. In addition, it provides a way for engineers to manage and assembly large software families.
As a proof of concept, a user-driven software product line is implemented for Eclipse, an integrated development environment. An Eclipse feature model is defined, which is exposed to users on a cloud-based built platform from which clients can download individualized Eclipse distributions.
Abstract: Autonomous mobile robots can be found in a wide
field of applications. Their types range from household robots over
workshop robots to autonomous cars and many more. All of them
undergo a number of testing steps during development, production
and maintenance. This paper describes an approach to improve
testing of robot behavior. It was inspired by the RoboCup @work
competition that itself reflects a robotics benchmark for industrial
robotics. There, scaled down versions of mobile industrial robots
have to navigate through a workshop-like environment or operation
area and have to perform tasks of manipulating and transporting
work pieces. This paper will introduce an approach of automated
vision-based testing of the behavior of the so called youBot robot,
which is the most widely used robot platform in the RoboCup
@work competition. The proposed system allows automated testing
of multiple tries of the robot to perform a specific missions and
it allows for the flexibility of the robot, e.g. selecting different
paths between two tasks within a mission. The approach is based
on a multi-camera setup using, off the shelf cameras and optical
markers. It has been applied for test-driven development (TDD) and
maintenance-like verification of the robot behavior and performance.
Abstract: A bubbly flow in a vertical miniature tube is analyzed theoretically. The liquid and gas phase are co-current flowing upward. The gas phase is injected via a nozzle whose inner diameter is 0.11mm and it is placed on the axis of the tube. A force balance is applied on the bubble at its detachment. The set of governing equations are solved by use of Mathematica software. The bubble diameter and the bubble generation frequency are determined for various inlet phase velocities represented by the inlet mass quality. The results show different behavior of bubble growth and detachment depending on the tube size.
Abstract: 12.7-mm thick plates of 6061-T6511 aluminum alloy and high hardness steel (528 HV) were successfully joined by a friction stir bonding process using a tungsten-rhenium stir tool. Process parameter variation experiments, which included tool design geometry, plunge and traverse rates, tool offset, spindle tilt, and rotation speed, were conducted to develop a parameter set which yielded a defect free joint. Laboratory tensile tests exhibited yield stresses which exceed the strengths of comparable AA6061-to-AA6061 fusion and friction stir weld joints. Scanning electron microscopy and energy dispersive X-ray spectroscopy analysis also show atomic diffusion at the material interface region.
Abstract: This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in VerilogHDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.
Abstract: Universities have different offices such as educational, research, student, administrative, and financial offices. This paper considers universities as groups of decision making units (DMUs) in which DMUs are their offices. This approach gives us with a more just evaluation of universities instead of separate evaluation of the offices of universities. The proposed approach to evaluate group performance of universities is based on common set of weights method in DEA. The suggested method not only can compare groups and measure their efficiencies, but also can calculate the efficiency of units within group and efficiency spread of groups. At last, the suggested method is applied for the analysis of the performance of universities in 14th district of Islamic Azad University as groups under evaluation.
Abstract: Recently, distributed generation technologies have received much attention for the potential energy savings and reliability assurances that might be achieved as a result of their widespread adoption. The distribution feeder reconfiguration (DFR) is one of the most important control schemes in the distribution networks, which can be affected by DGs. This paper presents a new approach to DFR at the distribution networks considering wind turbines. The main objective of the DFR is to minimize the deviation of the bus voltage. Since the DFR is a nonlinear optimization problem, we apply the Adaptive Modified Firefly Optimization (AMFO) approach to solve it. As a result of the conflicting behavior of the single- objective function, a fuzzy based clustering technique is employed to reach the set of optimal solutions called Pareto solutions. The approach is tested on the IEEE 32-bus standard test system.
Abstract: Non-invasive Brain Computer Interface like Electroencephalography (EEG) which directly taps neurological signals, is being widely explored these days to connect paralytic patients/elderly with the external environment. However, in India the research is confined to laboratory settings and is not reaching the mass for rehabilitation purposes. An attempt has been made in this paper to analyze real time acquired EEG signal using cost effective and portable headset unit EMOTIV. Signal processing of real time acquired EEG is done using EEGLAB in MATLAB and EDF Browser application software platforms. Independent Component Analysis algorithm of EEGLAB is explored to identify deliberate eye blink in the attained neural signal. Time Frequency transforms and Data statistics obtained using EEGLAB along with component activation results of EDF browser clearly indicate voluntary eye blink in AF3 channel. The spectral analysis indicates dominant frequency component at 1.536000Hz representing the delta wave component of EEG during voluntary eye blink action. An algorithm is further designed to generate an active high signal based on thoughtful eye blink that can be used for plethora of control applications for rehabilitation.
Abstract: In this era of competitiveness, there is a growing need for supply chains also to become competitive enough to handle pressures like varying customer’s expectations, low cost high quality products to be delivered at the minimum time and the most important is throat cutting competition at world wide scale. In the recent years, supply chain competitiveness has been, therefore, accepted as one of the most important philosophies in the supply chain literature and researchers have tried to identify variables of supply chain competitiveness. This paper highlights some of the concepts of supply chain competitiveness and tries to identify select variables on the basis of literature review. Further, the paper tries to highlight the importance of the identified variables in the achievement of supply chain competitiveness. The aim is to explore the concept and to motivate researchers to further investigate the unexplored areas of this important subject domain.
Abstract: In the study presented institutional context is discussed in terms of companies’ entry mode choice. In contrary to many previous analyses, instead of using one or two aggregated variables, a set of eleven determinants is used to establish equity and non-equity internationalization friendly conditions. Based on secondary data, 140 countries are analyzed and grouped into clusters revealing similar framework. The range of the economies explored is wide as it covers all regions distinguished by The World Bank. The results can prove a useful alternative for operationalization of institutional variables in further research concerning entry modes or strategic management in international markets.
Abstract: Kandy district in Sri Lanka, has small scale and rain-fed paddy farming, and highly vulnerable to climate change. In this study, the status of climate change was assessed using meteorological data and compared with the perceptions of paddy farming community. Factors affecting the adaptation to the climate smart farming were also assessed.
Meteorological data for 33 years were collected and the changes over time compared with the perceptions of farmers. The temperature, rainfall and number of rainy days have increased in both locations. The onset of rains also has shifted. The perceptions of the majority of the farmers were in line with the actual changes. The knowledge and attitudes about the causes of climate change and adaptation were medium and related to level of adoption. Formulating effective communication strategies, and a collaborative approach involving state, private sector, civil society to make Sri Lankan agriculture ‘climate-smart’ is urgently needed.
Abstract: The association between sensory problems and cognitive abilities has been studied in individuals with Autism Spectrum Disorders (ASDs). In this study, we used a Neuropsychological Test to evaluate memory and attention in ASDs children with sensory problems compared to the ASDs children without sensory problems. Four visual memory tests of Cambridge Neuropsychological Test Automated Battery (CANTAB) including Big/little circle (BLC), Simple Reaction Time (SRT) Intra /Extra dimensional set shift (IED), Spatial recognition memory (SRM), were administered to 14 ASDs children with sensory problems compared to 13 ASDs without sensory problems aged 3 to 12 with IQ of above 70. ASDs individuals with sensory problems performed worse than the ASDs group without sensory problems on comprehension, learning, reversal and simple reaction time tasks, and no significant difference between the two groups was recorded in terms of the visual memory and visual comprehension tasks. The findings of this study suggest that ASDs children with sensory problems are facing deficits in learning, comprehension, reversal, and speed of response to a stimulus.
Abstract: This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have became popular and considerable interest by researcher are given on them. A fast space-vector pulse width modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analyzed.
Abstract: This study examined the effect of porous dielectric silica gel the discharge ignition voltage and input power in a plasma reactor. For the experiment was used a plasma reactor with two mesh electrodes made of stainless steel with a mesh size of 0.1x0.1mm. The study analyzed and compared with parameters such as power, ignition and operation voltage of the reactor for two dielectrics a porous and glass. During experiment were observed several new phenomena conducted for porous dielectric. The first phenomenon was the reduction the ignition voltage discharge to volume around few hundred volts. Second it was increase input power six times more compared with power those obtained for the glass dielectric. Thirdly difference it is ΔV between ignition voltage Vi and operating voltage reactor Vm for porous dielectric it was 11%, while ΔV for the glass dielectric it was 60%. Also change the discharge characteristics from DBD for glass dielectric to the streamer resistance discharge for the porous dielectric.
Abstract: Television news has gained a new dimension in terms
of ideological approaches as a result of such factors as globalization,
cross monopolization, presence of international companies etc. and
certain strategies have been developed at the production, presentation
and distribution stages of news. In this study, television news about a
process called “settlement process” was investigated. In this
framework, news about the settlement process on TV channels of
TRT 1, ATV, FOX TV, NTV, HABERTÜRK, TRT HABER and
STV was investigated using the content analysis method in terms of
the strategies the ideology construction, attitude towards the party in
power, attitude towards parties in opposition and attitude towards
BDP (Peace and Democracy Part) and Imrali (the island where
Abdullah Ocalan, head of PKK, is kept). First, the aforementioned
TV channels were selected randomly from 3 groups in order to be
able to reveal the representational capacity of commercial, news and
public channels.
The study covers 557 news items broadcast in the main news
bulletins between the dates of 15 March 2013 and 15 March 2013.
While there was a positive attitude towards the government in a
sizable portion of the news about the settlement process (63.6%), the
attitude of 25.3% of the news was impartial towards the government
and 11.3% had a negative attitude. On the other hand, there was a
negative attitude towards the Opposition in a considerable portion of
the news about the settlement process (56.1%). The attitude of 35.9%
of the news towards the Opposition was impartial whereas 8.0% had
a positive attitude. While 34.9% of the news about the settlement
process used the legitimization strategy from among the ideology
construction strategies, 22.8% used the unification strategy, 15.7%
the reification strategy, 15.6% fractional and 11%
concealment/mystification strategy.
Abstract: A cross-sectional survey to ascertain the capacity of laboratory persons in using ICTs was conducted in 15 Ugandan districts (July-August 2013). A self-administered questionnaire served as data collection tool, interview guide and observation checklist. 69 questionnaires were filled, 12 interviews conducted, 45 HC observed. SPSS statistics 17.0 and SAS 9.2 software were used for entry and analyses. 69.35% of participants find it difficult to access a computer at work. Of the 30.65% who find it easy to access a computer at work, a significant 21.05% spend 0 hours on a computer daily. 60% of the participants cannot access internet at work. Of the 40% who have internet at work, a significant 20% lack email address but 20% weekly read emails weekly and 48% daily. It is viable/feasible to pilot informatics projects as strategies to build bridges develop skills for e-health landscape in laboratory services with a bigger financial muscle.
Abstract: Polyurethane foam is functionalized with Sulfonic acid groups to remove lead ions (Pb2+) from drinking water through a cation exchange process. The synthesis is based on addition polymerization of the -NCO groups of an isocyanate with the –OH groups of a polyol to form the urethane. Toluene-diisocyanateis reacted with Polypropylene glycol to form a linear pre-polymer, which is further polymerized using a chain extender, N, N-bis(2-hydorxyethyl)-2-aminoethane-sulfonic acid (BES). BES acts as a functional group site to exchange Pb2+ ions. A set of experiments was designed to study the effect of various processing parameters on the performance of the synthesized foam. The maximum Pb2+ ion exchange capacity of the foam was found to be 47ppb/g from a 100ppb Pb2+ solution over a period of 60 minutes. A multistage batch filtration process increased the lead removal to 50-54ppb/3g of foam over a period of 90 minutes.