Search results for: Energy performance

Authors: Nikola Vlahovic, Blazenka Knezevic, Petra Batalic

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In this paper, we will present a research about feasibility of implementing unmanned aerial vehicles, also known as 'drones', in logistics. Research is based on available information about current incentives and experiments in application of delivery drones in commercial use. Overview of current pilot projects and literature, as well as an overview of detected challenges, will be compiled and presented. Based on these findings, we will present a conceptual model of business process that implements delivery drones in business to business logistic operations. Business scenario is based on a pharmaceutical supply chain. Simulation modeling will be used to create models for running experiments and collecting performance data. Comparative study of the presented conceptual model will be given. The work will outline the main advantages and disadvantages of implementing unmanned aerial vehicles in delivery services as a supplementary distribution channel along the supply chain.

Keywords: Business process, delivery drones, logistics, simulation modelling, unmanned aerial vehicles.

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Authors: Jagath Samarabandu, Xiaoqing Liu

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Using bottom-up image processing algorithms to predict human eye fixations and extract the relevant embedded information in images has been widely applied in the design of active machine vision systems. Scene text is an important feature to be extracted, especially in vision-based mobile robot navigation as many potential landmarks such as nameplates and information signs contain text. This paper proposes an edge-based text region extraction algorithm, which is robust with respect to font sizes, styles, color/intensity, orientations, and effects of illumination, reflections, shadows, perspective distortion, and the complexity of image backgrounds. Performance of the proposed algorithm is compared against a number of widely used text localization algorithms and the results show that this method can quickly and effectively localize and extract text regions from real scenes and can be used in mobile robot navigation under an indoor environment to detect text based landmarks.

Keywords: Landmarks, mobile robot navigation, scene text, text localization and extraction.

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Authors: Fl. Loury, P. Sablonière

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In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.

Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.

Keywords: Molten Salt Storage System, Concentrated Solar Tower Power Plant, Robust Stochastic Model Predictive Control.

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Authors: V. K. Banga

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Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: Artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic.

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Authors: Michael Grigutsch, Peter Nyhuis

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Due to the volatile global economy, enterprises are increasingly focusing on logistics. By investing in suitable measures a company can increase their logistic performance and assert themselves over the competition. However, enterprises are also faced with the challenge of investing available capital for maximum profits. In order to be able to create an informed and quantifiably comprehensible basis for a decision, enterprises need a suitable model for logistically and monetarily evaluating measures in production. Previously, within the frame of Collaborate Research Centre 489 (SFB 489) at the Institute for Production Systems and Logistics, (IFA) a Logistic Information System was developed specifically for providing enterprises in the forging industry with support when making decisions. Based on this research, a new initiative referred to as ‘Transfer Project T7’, aims to develop a universal approach for logistically and monetarily evaluating production measures. This paper focuses on the structural measure echelon storage and their impact on the entire production system.

Keywords: Logistic Operating Curves, Transfer Functions, Production Logistics, Storages Echelon.

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Authors: R. Poonkuzhali, M. Y. Sanavullah, A. Sabari, T. Dhivyaa

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Opportunistic Routing (OR) increases the transmission reliability and network throughput. Traditional routing protocols preselects one or more predetermined nodes before transmission starts and uses a predetermined neighbor to forward a packet in each hop. The opportunistic routing overcomes the drawback of unreliable wireless transmission by broadcasting one transmission can be overheard by manifold neighbors. The first cooperation-optimal protocol for Multirate OR (COMO) used to achieve social efficiency and prevent the selfish behavior of the nodes. The novel link-correlation-aware OR improves the performance by exploiting the miscellaneous low correlated forward links. Context aware Adaptive OR (CAOR) uses active suppression mechanism to reduce packet duplication. The Context-aware OR (COR) can provide efficient routing in mobile networks. By using Cooperative Opportunistic Routing in Mobile Ad hoc Networks (CORMAN), the problem of opportunistic data transfer can be tackled. While comparing to all the protocols, COMO is the best as it achieves social efficiency and prevents the selfish behavior of the nodes.

Keywords: CAOR, COMO, COR, CORMAN, MANET, Opportunistic Routing, Reliability, Throughput.

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Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: Acute hepatitis, Medical resource cost, Artificial neural network, Support vector regression.

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Authors: Zhao Jing, Bai Yongqing, Shi Qiaofang, Zang Yang, Zhang Huaihao

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Advances in software technology enable the computational chemistry to be commonly applied in various research fields, especially in pedagogy. Thus, in order to expand and improve experimental instructions of computational chemistry for undergraduates, we designed an introductory experiment—research on acrylamide molecular structure and physicochemical properties. Initially, students construct molecular models of acrylamide and polyacrylamide in Gaussian and Materials Studio software respectively. Then, the infrared spectral data, atomic charge and molecular orbitals of acrylamide as well as solvation effect of polyacrylamide are calculated to predict their physicochemical performance. At last, rheological experiments are used to validate these predictions. Through the combination of molecular simulation (performed on Gaussian, Materials Studio) with experimental verification (rheology experiment), learners have deeply comprehended the chemical nature of acrylamide and polyacrylamide, achieving good learning outcomes.

Keywords: Upper-division undergraduate, computer-based learning, laboratory instruction, amides, molecular modeling, spectroscopy.

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Authors: Zulaiha Ali Othman, Helmi Md Rais, Abdul Razak Hamdan

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Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). Ants communicate to each other through chemical substances called pheromones. Modeling individual ants- ability to manipulate this substance can help an ACS find the best solution. This paper introduces a Dynamic Ant Colony System with threelevel updates (DACS3) that enhance an existing ACS. Experiments were conducted to observe single ant behavior in a colony of Malaysian House Red Ants. Such behavior was incorporated into the DACS3 algorithm. We benchmark the performance of DACS3 versus DACS on TSP instances ranging from 14 to 100 cities. The result shows that the DACS3 algorithm can achieve shorter distance in most cases and also performs considerably faster than DACS.

Keywords: Dynamic Ant Colony System (DACS), Traveling Salesmen Problem (TSP), Optimization, Swarm Intelligent.

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: Local nonlinear estimation, LWPR algorithm, Online training method.

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Authors: Florence Uchendu, Tola Atinmo

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Nigerian bread is baked with vitamin A fortified wheat flour. Study aimed at determining its contribution to preschoolers- vitamin A nutriture. A cross-sectional/experimental study was carried out in four poor-urban Local Government Areas (LGAs) of Metropolitan Lagos, Nigeria. A pretested food frequency questionnaire was administered to randomly selected mothers of 1600 preschoolers (24-59 months). Retinyl Palmitate content of fourteen bread samples randomly collected from bakeries in all LGAs was analyzed at 0 and 5 days at 25oC using High Performance Liquid Chromatography. Data analysis was done at p<.05. Mean total intake of vitamin A from bread was 220.40μgRAE (733.94±775.68i.u). Bread contributed 6.5–178.4% of preschoolers RDA (1333i.u/400μgRAE). Mean contribution to vitamin A intake was 55.06±58.18%. Strong statistical significant relationship existed between total vitamin A intake and % RDA which was directly proportional (p<.01). Result indicates that bread made an important contribution towards vitamin A intake in poor-urban Lagosian preschoolers.

Keywords: Bread, dietary intake, Lagos metropolis, preschoolers

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Authors: Karim Sobh, Khaled El-Ayat, Fady Morcos, Amr El-Kadi

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Distributed applications deployed on LEO satellites and ground stations require substantial communication between different members in a constellation to overcome the earth coverage barriers imposed by GEOs. Applications running on LEO constellations suffer the earth line-of-sight blockage effect. They need adequate lab testing before launching to space. We propose a scalable cloud-based network simulation framework to simulate problems created by the earth line-of-sight blockage. The framework utilized cloud IaaS virtual machines to simulate LEO satellites and ground stations distributed software. A factorial ANOVA statistical analysis is conducted to measure simulator overhead on overall communication performance. The results showed a very low simulator communication overhead. Consequently, the simulation framework is proposed as a candidate for testing LEO constellations with distributed software in the lab before space launch.

Keywords: LEO, Cloud Computing, Constellation, Satellite, Network Simulation, Netfilter.

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Authors: Porojan S., Sandu L., Topală F.

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Simulation of occlusal function during laboratory material-s testing becomes essential in predicting long-term performance before clinical usage. The aim of the study was to assess the influence of chamfer preparation depth on failure risk of heat pressed ceramic crowns with and without zirconia framework by means of finite element analysis. 3D models of maxillary central incisor, prepared for full ceramic crowns with different depths of the chamfer margin (between 0.8 and 1.2 mm) and 6-degree tapered walls together with the overlying crowns were generated using literature data (Fig. 1, 2). The crowns were designed with and without a zirconia framework with a thickness of 0.4 mm. For all preparations and crowns, stresses in the pressed ceramic crown, zirconia framework, pressed ceramic veneer, and dentin were evaluated separately. The highest stresses were registered in the dentin. The depth of the preparations had no significant influence on the stress values of the teeth and pressed ceramics for the studied cases, only for the zirconia framework. The zirconia framework decreases the stress values in the veneer.

Keywords: Finite element analysis, full ceramic crown, zirconia framework, stresses.

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Authors: K. Sontaya, B. Pitiyont, V. Punsuvon

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The objective of this study is to investigate the performance of the electrocoagulation process for color and COD removal in palm oil wastewater using a 10 L batch reactor. Iron was used as electrodes and the distance between electrodes was 2 cm. The effects of operating parameters: current voltage (6, 12 and 18 volt), reaction time (5, 15, 30, 45 and 60 min) and initial pH (4 and 9) of treatment efficiency were examine. The result showed that decolorization and COD removal efficiency increased with the increase in current voltage and reaction time. The proper condition for decolorization achieved at initial pH 4 and 9 were current voltage of 12 volt, reaction time 30 min. The decolorization efficiency reached 90.4% and 88.9%, respectively. COD removal was achiveved at current voltage 12 volt, reaction time 15 min. COD removal efficiency was 89.2 % and 83.0%, respectively. From the results, to show electrocoagulation process can treat palm oil mill wastewater in both acidic and basic condition at high efficiency for color and COD removal. Consequently, electrocoagulation process can be used or applied as a post-treatment step to improve the quality of the final discharge in term of color and residual COD removal.

Keywords: COD removal, decolorizaton, electrocoagulation, iron electrode, palm oil mill wastewater.

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Authors: Ahmad H. Abdelgwad, Ahmed A. Nashat

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Landmine detection is an important and yet challenging problem remains to be solved. Ground Penetrating Radar (GPR) is a powerful and rapidly maturing technology for subsurface threat identification. The detection methodology of GPR depends mainly on the contrast of the dielectric properties of the searched target and its surrounding soil. This contrast produces a partial reflection of the electromagnetic pulses that are being transmitted into the soil and then being collected by the GPR.  One of the most critical hardware components for the performance of GPR is the antenna system. The current paper explores the design and simulation of a pyramidal horn antenna operating at L-band frequencies (1- 2 GHz) to detect a landmine. A prototype model of the GPR system setup is developed to simulate full wave analysis of the electromagnetic fields in different soil types. The contrast in the dielectric permittivity of the landmine and the sandy soil is the most important parameter to be considered for detecting the presence of landmine. L-band horn antenna is proved to be well-versed in the investigation of landmine detection.

Keywords: Full wave analysis, ground penetrating radar, horn antenna design, landmine detection.

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Authors: Jagannath Aryal, Don Kulasiri, Dishi Liu

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This paper describes the optimization of a complex dairy farm simulation model using two quite different methods of optimization, the Genetic algorithm (GA) and the Lipschitz Branch-and-Bound (LBB) algorithm. These techniques have been used to improve an agricultural system model developed by Dexcel Limited, New Zealand, which describes a detailed representation of pastoral dairying scenarios and contains an 8-dimensional parameter space. The model incorporates the sub-models of pasture growth and animal metabolism, which are themselves complex in many cases. Each evaluation of the objective function, a composite 'Farm Performance Index (FPI)', requires simulation of at least a one-year period of farm operation with a daily time-step, and is therefore computationally expensive. The problem of visualization of the objective function (response surface) in high-dimensional spaces is also considered in the context of the farm optimization problem. Adaptations of the sammon mapping and parallel coordinates visualization are described which help visualize some important properties of the model-s output topography. From this study, it is found that GA requires fewer function evaluations in optimization than the LBB algorithm.

Keywords: Genetic Algorithm, Linux Cluster, LipschitzBranch-and-Bound, Optimization

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Authors: Irfah Najihah Basir Malan, Norhana Salamudin, Noryati Ahmad

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Corporate ownership structure is an important factor influencing firm performance. This study aims to answer the question whether pyramid structure has negative effect on firm value. This study is important because the ownership of public listed companies in Malaysia is highly concentrated. The concentrated ownership such as Malaysia, agency conflict is prevalent between controlling shareholders and minority shareholders. Accordingly, the dominant role of shareholders in firms allows the controlling shareholders (including managers) to expropriate the interest of the minority shareholders for their own private advantage. This research is conducted on pyramidal firms in Malaysia. Applying the Attig Model as the underlying statistical test, it is found that firm value is negatively related to pyramid ownership of Malaysian public listed firms due to the mismatch between cash flow rights and control rights. Future research needs to focus on identifying the heterogeneous factors that improve the generalizability of research.

Keywords: Pyramid structure, Cash flow right, Control right, Firm value, Attig model.

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Authors: Dingding Chen, Kazuo Arakawa, Masakazu Uchino, Changheng Xu

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Vacuum assisted resin transfer moulding (VARTM) is a promising manufacture process for making large and complex fiber reinforced composite structures. However, the complexity of the flow of the resin in the infusion stage usually leads to nonuniform property distribution of the produced composite part. In order to control the flow of the resin, the situation of flow should be mastered. For the safety of the usage of the produced composite in practice, the understanding of the property distribution is essential. In this paper, we did some trials on monitoring the resin infusion stage and evaluation for the fiber volume fraction distribution of the VARTM produced composite using the digital image correlation methods. The results showthat3D-DIC is valid on monitoring the resin infusion stage and it is possible to use 2D-DIC to estimate the distribution of the fiber volume fraction on a FRP plate.

Keywords: Digital image correlation, VARTM, FRP, fiber volume fraction.

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Authors: Juhee Lee, Yongjun Lee

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In designing a low-energy-consuming buildings, the heat transfer through a large glass or wall becomes critical. Multiple layers of the window glasses and walls are employed for the high insulation. The gravity driven air flow between window glasses or wall layers is a natural heat convection phenomenon being a key of the heat transfer. For the first step of the natural heat transfer analysis, in this study the development and application of a finite volume method for the numerical computation of viscous incompressible flows is presented. It will become a part of the natural convection analysis with high-order scheme, multi-grid method, and dual-time step in the future. A finite volume method based on a fully-implicit second-order is used to discretize and solve the fluid flow on unstructured grids composed of arbitrary-shaped cells. The integrations of the governing equation are discretised in the finite volume manner using a collocated arrangement of variables. The convergence of the SIMPLE segregated algorithm for the solution of the coupled nonlinear algebraic equations is accelerated by using a sparse matrix solver such as BiCGSTAB. The method used in the present study is verified by applying it to some flows for which either the numerical solution is known or the solution can be obtained using another numerical technique available in the other researches. The accuracy of the method is assessed through the grid refinement.

Keywords: Finite volume method, fluid flow, laminar flow, unstructured grid.

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Authors: Gokhan Dok, Hakan Ozturk, Aydin Demir

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The behavior of reinforced concrete (RC) members is quite important in RC structures. When evaluating the performance of structures, the nonlinear properties are defined according to the cross sectional behavior of RC members. To be able to determine the behavior of RC members, its cross sectional behavior should be known well. The moment-curvature (MC) relationship is used to represent cross sectional behavior. The MC relationship of RC cross section can be best determined both experimentally and numerically. But, experimental study on RC members is very difficult. The aim of the study is to obtain the MC relationship of RC shear walls. Additionally, it is aimed to determine the parameters which affect MC relationship. While obtaining MC relationship of RC members, XTRACT which can represent robustly the MC relationship is used. Concrete quality, longitudinal and transverse reinforcing ratios, are selected as parameters which affect MC relationship. As a result of the study, curvature ductility and effective flexural stiffness are determined using this parameter. Effective flexural stiffness is compared with the values defined in design codes.

Keywords: Moment-curvature, reinforced concrete, shear wall, numerical.

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: Anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines.

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Authors: Eman M. Wahba, Noha M. Galal, Khaled S. El-Kilany

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Spare parts inventory management is one of the major areas of inventory research. Analysis of recent literature showed that an approach integrating spare parts classification, demand forecasting, and stock control policies is essential; however, adapting this integrated approach is limited. This work presents an integrated framework for spare part inventory management and an Excel based application developed for the implementation of the proposed framework. A multi-criteria analysis has been used for spare classification. Forecasting of spare parts- intermittent demand has been incorporated into the application using three different forecasting models; namely, normal distribution, exponential smoothing, and Croston method. The application is also capable of running with different inventory control policies. To illustrate the performance of the proposed framework and the developed application; the framework is applied to different items at a service organization. The results achieved are presented and possible areas for future work are highlighted.

Keywords: Demand forecasting, intermittent demand, inventory management, integrated approach, spare parts, spare part classification

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Authors: Pei-yih Ting, Dream-Ming Huang, Xiao-Wei Huang

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Frequently a group of people jointly decide and authorize a specific person as a representative in some business/poitical occasions, e.g., the board of a company authorizes the chief executive officer to close a multi-billion acquisition deal. In this paper, an integrated proxy multi-signature scheme that allows anonymously vetoable delegation is proposed. This protocol integrates mechanisms of private veto, distributed proxy key generation, secure transmission of proxy key, and existentially unforgeable proxy multi-signature scheme. First, a provably secure Guillou-Quisquater proxy signature scheme is presented, then the “zero-sharing" protocol is extended over a composite modulus multiplicative group, and finally the above two are combined to realize the GQ proxy multi-signature with anonymously vetoable delegation. As a proxy signature scheme, this protocol protects both the original signers and the proxy signer. The modular design allows simplified implementation with less communication overheads and better computation performance than a general secure multi-party protocol.

Keywords: GQ proxy signature, proxy multi-signature, zero-sharing protocol, secure multi-party protocol, private veto protocol

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Authors: Toi Limazie, Xun'an Zhang, Xianjie Wang

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This paper focuses on the Mega-Sub Controlled Structure Systems (MSCSS) performances and characteristics regarding the new control principle contained in MSCSS subjected to strong earthquake excitations. The adopted control scheme consists of modulated sub-structures where the control action is achieved by viscous dampers and sub-structure own configuration. The elastic-plastic time history analysis under severe earthquake excitation is analyzed base on the Finite Element Analysis Method (FEAM), and some comparison results are also given in this paper. The result shows that the MSCSS systems can remarkably reduce vibrations effects more than the mega-sub structure (MSS). The study illustrates that the improved MSCSS presents good seismic resistance ability even at 1.2g and can absorb seismic energy in the structure, thus imply that structural members cross section can be reduce and achieve to good economic characteristics. Furthermore, the elasto-plastic analysis demonstrates that the MSCSS is accurate enough regarding international building evaluation and design codes. This paper also shows that the elasto-plastic dynamic analysis method is a reasonable and reliable analysis method for structures subjected to strong earthquake excitations and that the computed results are more precise.

Keywords: controlling effectiveness, Elasto-plastic dynamic analysis, Mega-Sub Controlled Structure, Plastic hinge pattern.

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Authors: Md Abdullah Al Faruque, Ram Balachandar

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Sudden change of bed condition is frequent in open channel flow. Change of bed condition affects the turbulence characteristics in both streamwise and wall-normal direction. Understanding the turbulence intensity in open channel flow is of vital importance to the modeling of sediment transport and resuspension, bed formation, entrainment, and the exchange of energy and momentum. A comprehensive study was carried out to understand the extent of the effect of Reynolds number and bed roughness on different turbulence characteristics in an open channel flow. Four different bed conditions (impervious smooth bed, impervious continuous rough bed, pervious rough sand bed, and impervious distributed roughness) and two different Reynolds numbers were adopted for this cause. The effect of bed roughness on different turbulence characteristics is seen to be prevalent for most of the flow depth. Effect of Reynolds number on different turbulence characteristics is also evident for flow over different bed, but the extent varies on bed condition. Although the same sand grain is used to create the different rough bed conditions, the difference in turbulence characteristics is an indication that specific geometry of the roughness has an influence on turbulence characteristics. Roughness increases the contribution of the extreme turbulent events which produces very large instantaneous Reynolds shear stress and can potentially influence the sediment transport, resuspension of pollutant from bed and alter the nutrient composition, which eventually affect the sustainability of benthic organisms.

Keywords: Open channel flow, Reynolds Number, roughness, turbulence.

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Authors: Rupinder Kaur, Parmjit S. Panesar, Ram S. Singh

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Whey is the lactose rich by-product of the dairy industry, having good amount of nutrient reservoir. Most abundant nutrients are lactose, soluble proteins, lipids and mineral salts. Disposing of whey by most of milk plants which do not have proper pre-treatment system is the major issue. As a result of which, there can be significant loss of potential food and energy source. Thus, whey has been explored as the substrate for the synthesis of different value added products such as enzymes. β-galactosidase is one of the important enzymes and has become the major focus of research due to its ability to catalyze both hydrolytic as well as transgalactosylation reaction simultaneously. The enzyme is widely used in dairy industry as it catalyzes the transformation of lactose to glucose and galactose, making it suitable for the lactose intolerant people. The enzyme is intracellular in both bacteria and yeast, whereas for molds, it has an extracellular location. The present work was carried to utilize the whey for the production of β-galactosidase enzyme using both yeast and fungal cultures. The yeast isolate Kluyveromyces marxianus WIG2 and various fungal strains have been used in the present study. Different disruption techniques have also been investigated for the extraction of the enzyme produced intracellularly from yeast cells. Among the different methods tested for the disruption of yeast cells, SDS-chloroform showed the maximum β-galactosidase activity. In case of the tested fungal cultures, Aureobasidium pullulans NCIM 1050 was observed to be the maximum extracellular enzyme producer.

Keywords: β-galactosidase, fungus, yeast, whey.

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Authors: Muhammad Faisal Zafar, Dzulkifli Mohamad, Razib M. Othman

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On-line handwritten scripts are usually dealt with pen tip traces from pen-down to pen-up positions. Time evaluation of the pen coordinates is also considered along with trajectory information. However, the data obtained needs a lot of preprocessing including filtering, smoothing, slant removing and size normalization before recognition process. Instead of doing such lengthy preprocessing, this paper presents a simple approach to extract the useful character information. This work evaluates the use of the counter- propagation neural network (CPN) and presents feature extraction mechanism in full detail to work with on-line handwriting recognition. The obtained recognition rates were 60% to 94% using the CPN for different sets of character samples. This paper also describes a performance study in which a recognition mechanism with multiple thresholds is evaluated for counter-propagation architecture. The results indicate that the application of multiple thresholds has significant effect on recognition mechanism. The method is applicable for off-line character recognition as well. The technique is tested for upper-case English alphabets for a number of different styles from different peoples.

Keywords: On-line character recognition, character digitization, counter-propagation neural networks, extreme coordinates.

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Authors: Sanaz Seraj, Shohre Rouhani

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Recently, graphene has gained much attention because of its unique optical, mechanical, electrical, and thermal properties. Graphene has been used as a key material in the technological applications in various areas such as sensors, drug delivery, super capacitors, transparent conductor, and solar cell. It has a superior quenching efficiency for various fluorophores. Based on these unique properties, the optical sensors with graphene materials as the energy acceptors have demonstrated great success in recent years. During quenching, the emission of a fluorophore is perturbed by a quencher which can be a substrate or biomolecule, and due to this phenomenon, fluorophore-quencher has been used for selective detection of target molecules. Among fluorescence dyes, 1,8-naphthalimide is well known for its typical intramolecular charge transfer (ICT) and photo-induced charge transfer (PET) fluorophore, strong absorption and emission in the visible region, high photo stability, and large Stokes shift. Derivatives of 1,8-naphthalimides have found applications in some areas, especially fluorescence sensors. Herein, the fluorescence quenching of graphene oxide has been carried out on a naphthalimide dye as a fluorescent probe model. The quenching ability of graphene oxide on naphthalimide dye was studied by UV-VIS and fluorescence spectroscopy. This study showed that graphene is an efficient quencher for fluorescent dyes. Therefore, it can be used as a suitable candidate sensing platform. To the best of our knowledge, studies on the quenching and absorption of naphthalimide dyes by graphene oxide are rare.

Keywords: Fluorescence, graphene oxide, naphthalimide dye, quenching.

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Authors: Arnab Majumdar, Srimani Sen

Abstract:

In this paper, a vivid simulated study has been made on 35 GHz Ka-band window frequency in order to judge and compare the DC and high frequency properties of cubic ZnB-GaN with the existing hexagonal 4H-SiC. A flat profile p⁺pnn⁺ DDR structure of impatt is chosen and is optimized at a particular bias current density with respect to efficiency and output power taking into consideration the effect of mobile space charge also. The simulated results obtained reveals the strong potentiality of impatts based on both cubic ZnB-GaN and hexagonal 4H-SiC. The DC-to-millimeter wave conversion efficiency for cubic ZnB-GaN impatt obtained is 50% with an estimated output power of 2.83 W at an optimized bias current density of 2.5×10⁸ A/m². The conversion efficiency and estimated output power in case of hexagonal 4H-SiC impatt obtained is 22.34% and 40 W respectively at an optimum bias current density of 0.06×10⁸ A/m².

Keywords: Cubic ZnB-GaN, hexagonal 4H-SiC, Double drift impatt diode, millimeter wave, optimized bias current density, wide band gap semiconductor.

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Authors: B. D. Polat, O. Keles

Abstract:

Physical vapor deposition under conditions of an obliquely incident flux results in a film formation with an inclined columnar structure. These columns will be oriented toward the vapor source because of the self-shadowing effect, and they are homogenously distributed on the substrate surface because of the limited surface diffusion ability of ad-atoms when there is no additional substrate heating.

In this work, the oblique angle electron beam evaporation technique is used to fabricate thin films containing inclined nanorods. The results demonstrate that depending on the thin film composition, the morphology of the nanorods is changed as well. The galvanostatic analysis of these thin film anodes reveals that a composite CuSn nanorods having approximately 900mAhg^-1 of initial discharge capacity, performs higher electrochemical performance compared to pure Sn nanorods containing anode material. The long cycle life and the advanced electrochemical properties of the nanostructured composite electrode might be attributed to its improved mechanical tolerance and enhanced electrical conductivity depending on the Cu presence in the nanorods.

Keywords: Cu-Sn thin film, oblique angle deposition, lithium ion batteries, anode.

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