Design and Control of PEM Fuel Cell Diffused Aeration System using Artificial Intelligence Techniques

Fuel cells have become one of the major areas of research in the academia and the industry. The goal of most fish farmers is to maximize production and profits while holding labor and management efforts to the minimum. Risk of fish kills, disease outbreaks, poor water quality in most pond culture operations, aeration offers the most immediate and practical solution to water quality problems encountered at higher stocking and feeding rates. Many units of aeration system are electrical units so using a continuous, high reliability, affordable, and environmentally friendly power sources is necessary. Aeration of water by using PEM fuel cell power is not only a new application of the renewable energy, but also, it provides an affordable method to promote biodiversity in stagnant ponds and lakes. This paper presents a new design and control of PEM fuel cell powered a diffused air aeration system for a shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence (AI) techniques control is used to control the fuel cell output power by control input gases flow rate. Moreover the mathematical modeling and simulation of PEM fuel cell is introduced. A comparison study is applied between the performance of fuzzy logic control (FLC) and neural network control (NNC). The results show the effectiveness of NNC over FLC.

Fuzzy Tuned PID Controller with D-Q-O Reference Frame Technique Based Active Power Filter

Active power filter continues to be a powerful tool to control harmonics in power systems thereby enhancing the power quality. This paper presents a fuzzy tuned PID controller based shunt active filter to diminish the harmonics caused by non linear loads like thyristor bridge rectifiers and imbalanced loads. Here Fuzzy controller provides the tuning of PID, based on firing of thyristor bridge rectifiers and variations in input rms current. The shunt APF system is implemented with three phase current controlled Voltage Source Inverter (VSI) and is connected at the point of common coupling for compensating the current harmonics by injecting equal but opposite filter currents. These controllers are capable of controlling dc-side capacitor voltage and estimating reference currents. Hysteresis Current Controller (HCC) is used to generate switching signals for the voltage source inverter. Simulation studies are carried out with non linear loads like thyristor bridge rectifier along with unbalanced loads and the results proved that the APF along with fuzzy tuned PID controller work flawlessly for different firing angles of non linear load.

Balancing Strategies for Parallel Content-based Data Retrieval Algorithms in a k-tree Structured Database

The paper proposes a unified model for multimedia data retrieval which includes data representatives, content representatives, index structure, and search algorithms. The multimedia data are defined as k-dimensional signals indexed in a multidimensional k-tree structure. The benefits of using the k-tree unified model were demonstrated by running the data retrieval application on a six networked nodes test bed cluster. The tests were performed with two retrieval algorithms, one that allows parallel searching using a single feature, the second that performs a weighted cascade search for multiple features querying. The experiments show a significant reduction of retrieval time while maintaining the quality of results.

Metoprolol Tartrate-Ethylcellulose Tabletted Microparticles: Development of a Validated Invitro In-vivo Correlation

This study describes the methodology for the development of a validated in-vitro in-vivo correlation (IVIVC) for metoprolol tartrate modified release dosage forms with distinctive release rate characteristics. Modified release dosage forms were formulated by microencapsulation of metoprolol tartrate into different amounts of ethylcellulose by non-solvent addition technique. Then in-vitro and in-vivo studies were conducted to develop and validate level A IVIVC for metoprolol tartrate. The values of regression co-efficient (R2-values) for IVIVC of T2 and T3 formulations were not significantly (p

Join and Meet Block Based Default Definite Decision Rule Mining from IDT and an Incremental Algorithm

Using maximal consistent blocks of tolerance relation on the universe in incomplete decision table, the concepts of join block and meet block are introduced and studied. Including tolerance class, other blocks such as tolerant kernel and compatible kernel of an object are also discussed at the same time. Upper and lower approximations based on those blocks are also defined. Default definite decision rules acquired from incomplete decision table are proposed in the paper. An incremental algorithm to update default definite decision rules is suggested for effective mining tasks from incomplete decision table into which data is appended. Through an example, we demonstrate how default definite decision rules based on maximal consistent blocks, join blocks and meet blocks are acquired and how optimization is done in support of discernibility matrix and discernibility function in the incomplete decision table.

New Graph Similarity Measurements based on Isomorphic and Nonisomorphic Data Fusion and their Use in the Prediction of the Pharmacological Behavior of Drugs

New graph similarity methods have been proposed in this work with the aim to refining the chemical information extracted from molecules matching. For this purpose, data fusion of the isomorphic and nonisomorphic subgraphs into a new similarity measure, the Approximate Similarity, was carried out by several approaches. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting several pharmacological parameters: binding of steroids to the globulin-corticosteroid receptor, the activity of benzodiazepine receptor compounds, and the blood brain barrier permeability. Acceptable results were obtained for the models presented here.

Faculty-Industry R&D Joint Ventures: Barriers VS Incentives for Developing Nations

The aspiration of this research article is to target and focus the gains of university-Industry (U-I) collaborations and exploring those hurdles which are the obstacles for attaining these gains. University-Industry collaborations have attained great importance since 1980 in USA due to its application in all fields of life. U-I collaboration is a bilateral process where academia is a proactive member to make such alliances. Universities want to ameliorate their academic-base with the technicalities of technobabbles. U-I collaboration is becoming an essential lane for achieving innovative goals in this century. Many developed nations have set successful examples to prove this phenomenon as a catalyst to reduce costs, efforts and personnel for R&D projects. This study is exploits amplitudes of UI collaboration incentives in the light of success stories of developed countries. Many universities in USA, UK, Canada and various European Countries have been engaged with enterprises for numerous collaborative agreements. A long list of strategic and short term R&D projects has been executed in developed countries to accomplish their intended purposes. Due to the lack of intentions, genuine research and research-oriented environment, the mentioned field could not grow very well in developing countries. During last decade, a new wave of research has induced the institutes of developing countries to promote R&D culture especially in Pakistan. Higher Education Commission (HEC) has initiated many projects and funding supports for universities which have collaborative intentions with industry. Findings show that rapid innovation, overwhelm the technological complexities and articulated intellectual-base are major incentives which steer both partners to establish faculty-industry alliances. Everchanging technologies, concerned about intellectual property, different research environment and culture, research relevancy (Basic or applied), exposure differences and diversity of knowledge (bookish or practical) are main barriers to establish and retain joint ventures. Findings also concluded that, it is dire need to support and enhance cooperation among academia and industry to promote highly coordinated research behaviors. Author has proposed a roadmap for developing countries to promote R&D clusters among faculty and industry to deal the technological challenges and innovation complexities. Based on our research findings, Model for R&D Collaboration for developing countries also have been proposed to promote articulated R&D environment. If developing countries follow this phenomenon, rapid innovations can be achieved with limited R&D budget heads.

Audio Watermarking Based on Compression-expansion Technique

A novel robust audio watermarking scheme is proposed in this paper. In the proposed scheme, the host audio signals are segmented into frames. Two consecutive frames are assessed if they are suitable to represent a watermark bit. If so, frequency transform is performed on these two frames. The compressionexpansion technique is adopted to generate distortion over the two frames. The distortion is used to represent one watermark bit. Psychoacoustic model is applied to calculate local auditory mask to ensure that the distortion is not audible. The watermarking schemes using mono and stereo audio signals are designed differently. The correlation-based detection method is used to detect the distortion and extract embedded watermark bits. The experimental results show that the quality degradation caused by the embedded watermarks is perceptually transparent and the proposed schemes are very robust against different types of attacks.

Evaluation of Urban Development Proposals An ANP Approach

In this paper a new approach to prioritize urban planning projects in an efficient and reliable way is presented. It is based on environmental pressure indices and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity of rank ordering urban development proposals according to their environmental pressure. The technique combines the use of Environmental Pressure Indicators, the aggregation of indicators in an Environmental Pressure Index by means of the Analytic Network Process method and interpreting the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts- judgments on each of the indicators into one Environmental Pressure Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts- estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The method has been applied to the proposal for urban development of La Carlota airport in Caracas (Venezuela). The Venezuelan Government would like to see a recreational project develop on the abandoned area and mean a significant improvement for the capital. There are currently three options on their table which are currently under evaluation. They include a Health Club, a Residential area and a Theme Park. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional techniques such as environmental impact studies, lifecycle analysis, etc. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods.

Language and Retrieval Accuracy

One of the major challenges in the Information Retrieval field is handling the massive amount of information available to Internet users. Existing ranking techniques and strategies that govern the retrieval process fall short of expected accuracy. Often relevant documents are buried deep in the list of documents returned by the search engine. In order to improve retrieval accuracy we examine the issue of language effect on the retrieval process. Then, we propose a solution for a more biased, user-centric relevance for retrieved data. The results demonstrate that using indices based on variations of the same language enhances the accuracy of search engines for individual users.

On Face Recognition using Gabor Filters

Gabor-based face representation has achieved enormous success in face recognition. This paper addresses a novel algorithm for face recognition using neural networks trained by Gabor features. The system is commenced on convolving a face image with a series of Gabor filter coefficients at different scales and orientations. Two novel contributions of this paper are: scaling of rms contrast and introduction of fuzzily skewed filter. The neural network employed for face recognition is based on the multilayer perceptron (MLP) architecture with backpropagation algorithm and incorporates the convolution filter response of Gabor jet. The effectiveness of the algorithm has been justified over a face database with images captured at different illumination conditions.

Effect of Supplemental Irrigation, Nitrogen Chemical Fertilizer, and Inoculation with Rhizobium Bacteria on Grain Yield and Its Components of Chickpea (Cicer arietinum L.) Under Rainfed Conditions

In order to study the effects of supplemental irrigation, different levels of nitrogen chemical fertilizer and inoculation with rhizobium bacteria on the grain yield of chickpea, an experiment was carried out using split plot arrangement in randomize complete block design with three replication in agricultural researches station of Zanjan, Iran during 2009-2010 cropping season. The factors of experiment consisted of irritation (without irrigation (I1), irrigation at flowering stage (I2), irrigation at flowering and grain filling stages (I3) and full irrigation (I4)) and different levels of nitrogen fertilizer (without using of nitrogen fertilizer (N0), 75 kg.ha-1 (N75), 150 kg.ha-1 (N150) and inoculation with rhizobium bacteria (N4). The results of the analysis of variance showed that the effects of irrigation, nitrogen fertilizer levels and bacterial inoculation, were significant affect on number of pods per plant, number grains per plant, grain weight, grain yield, biological yield and harvest index at 1% probability level. Also Results showed that the grain yield in full irrigation treatment and inoculated with rhizobium bacteria was significantly higher than the other treatments.

Identifying Potential Partnership for Open Innovation by using Bibliographic Coupling and Keyword Vector Mapping

As open innovation has received increasingly attention in the management of innovation, the importance of identifying potential partnership is increasing. This paper suggests a methodology to identify the interested parties as one of Innovation intermediaries to enable open innovation with patent network. To implement the methodology, multi-stage patent citation analysis such as bibliographic coupling and information visualization method such as keyword vector mapping are utilized. This paper has contribution in that it can present meaningful collaboration keywords to identified potential partners in network since not only citation information but also patent textual information is used.

A Hybrid Data Mining Method for the Medical Classification of Chest Pain

Data mining techniques have been used in medical research for many years and have been known to be effective. In order to solve such problems as long-waiting time, congestion, and delayed patient care, faced by emergency departments, this study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees. The methodology is applied to real-world emergency data collected from a hospital and is evaluated by comparing with other techniques. The methodology is expected to help physicians to make a faster and more accurate classification of chest pain diseases.

An Implicit Region-Based Deformable Model with Local Segmentation Applied to Weld Defects Extraction

This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.

Royal Mound “Baygetobe“ from the Burial Ground Shilikty

Mounds are one of the most valuable sources of information on various aspects of life, household skills, rituals and beliefs of the ancient peoples of Kazakhstan. Moreover, the objects associated with the cult of the burial of the dead are the most informative, and often the only source of knowledge about past eras. The present study is devoted to some results of the excavations carried out on the mound "Baygetobe" of Shilikti burial ground. The purpose of the work is associated with certain categories of grave goods and reading "Fine Text" of Shilikti graves, whose structure is the same for burials of nobles and ordinary graves. The safety of a royal burial mounds, the integrity and completeness of the source are of particular value for studying.

Applying Lagrangian Relaxation-Based Algorithm for the Airline Coordinated Flight Scheduling Problems

The solution algorithm, based on Lagrangian relaxation, a sub-gradient method and a heuristic to find the upper bound of the solution, is proposed to solve the coordinated fleet routing and flight scheduling problems. Numerical tests are performed to evaluate the proposed algorithm using real operating data from two Taiwan airlines. The test results indicate that the solution algorithm is a significant improvement over those obtained with CPLEX, consequently they could be useful for allied airlines to solve coordinated fleet routing and flight scheduling problems.

A Physics-Based Model for Fast Recovery Diodes with Lifetime Control and Emitter Efficiency Reduction

This paper presents a physics-based model for the high-voltage fast recovery diodes. The model provides a good trade-off between reverse recovery time and forward voltage drop realized through a combination of lifetime control and emitter efficiency reduction techniques. The minority carrier lifetime can be extracted from the reverse recovery transient response and forward characteristics. This paper also shows that decreasing the amount of the excess carriers stored in the drift region will result in softer characteristics which can be achieved using a lower doping level. The developed model is verified by experiment and the measurement data agrees well with the model.

Hydrogen Production from Alcohol Wastewater by Upflow Anaerobic Sludge Blanket Reactors under Mesophilic Temperature

In this work, biohydrogen production via dark fermentation from alcohol wastewater using upflow anaerobic sludge blanket reactors (UASB) with a working volume of 4 L was investigated to find the optimum conditions for a maximum hydrogen yield. The system was operated at different COD loading rates (23, 31, 46 and 62 kg/m3d) at mesophilic temperature (37 ºC) and pH 5.5. The seed sludge was pretreated before being fed to the UASB system by boiling at 95 ºC for 15 min. When the system was operated under the optimum COD loading rate of 46 kg/m3d, it provided the hydrogen content of 27%, hydrogen yield of 125.1 ml H2/g COD removed and 95.1 ml H2/g COD applied, hydrogen production rate of 18 l/d, specific hydrogen production rate of 1080 ml H2/g MLVSS d and 1430 ml H2/ L d, and COD removal of 24%.

Integrated Energy-Aware Mechanism for MANETs using On-demand Routing

Mobile Ad Hoc Networks (MANETs) are multi-hop wireless networks in which all nodes cooperatively maintain network connectivity. In such a multi-hop wireless network, every node may be required to perform routing in order to achieve end-to-end communication among nodes. These networks are energy constrained as most ad hoc mobile nodes today operate with limited battery power. Hence, it is important to minimize the energy consumption of the entire network in order to maximize the lifetime of ad hoc networks. In this paper, a mechanism involving the integration of load balancing approach and transmission power control approach is introduced to maximize the life-span of MANETs. The mechanism is applied on Ad hoc On-demand Vector (AODV) protocol to make it as energy aware AODV (EA_AODV). The simulation is carried out using GloMoSim2.03 simulator. The results show that the proposed mechanism reduces the average required transmission energy per packet compared to the standard AODV.