Enhanced Coagulation of Disinfection By-Products Precursors in Porsuk Water Resource, Eskisehir

Natural organic matter (NOM) is heterogeneous mixture of organic compounds that enter the water media from animal and plant remains, domestic and industrial wastes. Researches showed that NOM is likely precursor material for disinfection by products (DBPs). Chlorine very commenly used for disinfection purposes and NOM and chlorine reacts then Trihalomethane (THM) and Haloacetic acids (HAAs) which are cancerogenics for human health are produced. The aim of the study is to search NOM removal by enhanced coagulation from drinking water source of Eskisehir which is supplied from Porsuk Dam. Recently, Porsuk dam water is getting highly polluted and therefore NOM concentration is increasing. Enhanced coagulation studies were evaluated by measurement of Dissolved Organic Carbon (DOC), UV absorbance at 254 nm (UV254), and different trihalomethane formation potential (THMFP) tests. Results of jar test experiments showed that NOM can be removed from water about 40-50 % of efficiency by enhanced coagulation. Optimum coagulant type and coagulant dosages were determined using FeCl3 and Alum.

Interoperability in Component Based Software Development

The ability of information systems to operate in conjunction with each other encompassing communication protocols, hardware, software, application, and data compatibility layers. There has been considerable work in industry on the development of component interoperability models, such as CORBA, (D)COM and JavaBeans. These models are intended to reduce the complexity of software development and to facilitate reuse of off-the-shelf components. The focus of these models is syntactic interface specification, component packaging, inter-component communications, and bindings to a runtime environment. What these models lack is a consideration of architectural concerns – specifying systems of communicating components, explicitly representing loci of component interaction, and exploiting architectural styles that provide well-understood global design solutions. The development of complex business applications is now focused on an assembly of components available on a local area network or on the net. These components must be localized and identified in terms of available services and communication protocol before any request. The first part of the article introduces the base concepts of components and middleware while the following sections describe the different up-todate models of communication and interaction and the last section shows how different models can communicate among themselves.

The Effects of Peristalsis on Dispersion of a Micropolar Fluid in the Presence of Magnetic Field

The paper presents an analytical solution for dispersion of a solute in the peristaltic motion of a micropolar fluid in the presence of magnetic field and both homogeneous and heterogeneous chemical reactions. The average effective dispersion coefficient has been found using Taylor-s limiting condition under long wavelength approximation. The effects of various relevant parameters on the average coefficient of dispersion have been studied. The average effective dispersion coefficient increases with amplitude ratio, cross viscosity coefficient and heterogeneous chemical reaction rate parameter. But it decreases with magnetic field parameter and homogeneous chemical reaction rate parameter. It can be noted that the presence of peristalsis enhances dispersion of a solute.

A Grid-based Neural Network Framework for Multimodal Biometrics

Recent scientific investigations indicate that multimodal biometrics overcome the technical limitations of unimodal biometrics, making them ideally suited for everyday life applications that require a reliable authentication system. However, for a successful adoption of multimodal biometrics, such systems would require large heterogeneous datasets with complex multimodal fusion and privacy schemes spanning various distributed environments. From experimental investigations of current multimodal systems, this paper reports the various issues related to speed, error-recovery and privacy that impede the diffusion of such systems in real-life. This calls for a robust mechanism that caters to the desired real-time performance, robust fusion schemes, interoperability and adaptable privacy policies. The main objective of this paper is to present a framework that addresses the abovementioned issues by leveraging on the heterogeneous resource sharing capacities of Grid services and the efficient machine learning capabilities of artificial neural networks (ANN). Hence, this paper proposes a Grid-based neural network framework for adopting multimodal biometrics with the view of overcoming the barriers of performance, privacy and risk issues that are associated with shared heterogeneous multimodal data centres. The framework combines the concept of Grid services for reliable brokering and privacy policy management of shared biometric resources along with a momentum back propagation ANN (MBPANN) model of machine learning for efficient multimodal fusion and authentication schemes. Real-life applications would be able to adopt the proposed framework to cater to the varying business requirements and user privacies for a successful diffusion of multimodal biometrics in various day-to-day transactions.

A Performance Appraisal of Neural Networks Developed for Response Prediction across Heterogeneous Domains

Deciding the numerous parameters involved in designing a competent artificial neural network is a complicated task. The existence of several options for selecting an appropriate architecture for neural network adds to this complexity, especially when different applications of heterogeneous natures are concerned. Two completely different applications in engineering and medical science were selected in the present study including prediction of workpiece's surface roughness in ultrasonic-vibration assisted turning and papilloma viruses oncogenicity. Several neural network architectures with different parameters were developed for each application and the results were compared. It was illustrated in this paper that some applications such as the first one mentioned above are apt to be modeled by a single network with sufficient accuracy, whereas others such as the second application can be best modeled by different expert networks for different ranges of output. Development of knowledge about the essentials of neural networks for different applications is regarded as the cornerstone of multidisciplinary network design programs to be developed as a means of reducing inconsistencies and the burden of the user intervention.

Intelligent Solutions for Umbrella Systems in Telecommunication Supervision Systems

This paper indicate the importance of telecommunications supervision systems (TSS), integrating heterogeneous TSS into single system thru umbrella systems, introduces the structure, features, requirements of TSS and TSS related intelligent solutions.

Improved Wavelet Neural Networks for Early Cancer Diagnosis Using Clustering Algorithms

Wavelet neural networks (WNNs) have emerged as a vital alternative to the vastly studied multilayer perceptrons (MLPs) since its first implementation. In this paper, we applied various clustering algorithms, namely, K-means (KM), Fuzzy C-means (FCM), symmetry-based K-means (SBKM), symmetry-based Fuzzy C-means (SBFCM) and modified point symmetry-based K-means (MPKM) clustering algorithms in choosing the translation parameter of a WNN. These modified WNNs are further applied to the heterogeneous cancer classification using benchmark microarray data and were compared against the conventional WNN with random initialization method. Experimental results showed that a WNN classifier with the MPKM algorithm is more precise than the conventional WNN as well as the WNNs with other clustering algorithms.

Towards Modeling for Crashes A Low-Cost Adaptive Methodology for Karachi

The aim of this paper is to discuss a low-cost methodology that can predict traffic flow conflicts and quantitatively rank crash expectancies (based on relative probability) for various traffic facilities. This paper focuses on the application of statistical distributions to model traffic flow and Monte Carlo techniques to simulate traffic and discusses how to create a tool in order to predict the possibility of a traffic crash. A low-cost data collection methodology has been discussed for the heterogeneous traffic flow that exists and a GIS platform has been proposed to thematically represent traffic flow from simulations and the probability of a crash. Furthermore, discussions have been made to reflect the dynamism of the model in reference to its adaptability, adequacy, economy, and efficiency to ensure adoption.

An Agent Based Simulation for Network Formation with Heterogeneous Agents

We investigate an asymmetric connections model with a dynamic network formation process, using an agent based simulation. We permit heterogeneity of agents- value. Valuable persons seem to have many links on real social networks. We focus on this point of view, and examine whether valuable agents change the structures of the terminal networks. Simulation reveals that valuable agents diversify the terminal networks. We can not find evidence that valuable agents increase the possibility that star networks survive the dynamic process. We find that valuable agents disperse the degrees of agents in each terminal network on an average.

A Unique Solution for Designing Low-Cost, Heterogeneous Sensor Networks Using a Middleware Integration Platform

Proprietary sensor network systems are typically expensive, rigid and difficult to incorporate technologies from other vendors. When using competing and incompatible technologies, a non-proprietary system is complex to create because it requires significant technical expertise and effort, which can be more expensive than a proprietary product. This paper presents the Sensor Abstraction Layer (SAL) that provides middleware architectures with a consistent and uniform view of heterogeneous sensor networks, regardless of the technologies involved. SAL abstracts and hides the hardware disparities and specificities related to accessing, controlling, probing and piloting heterogeneous sensors. SAL is a single software library containing a stable hardware-independent interface with consistent access and control functions to remotely manage the network. The end-user has near-real-time access to the collected data via the network, which results in a cost-effective, flexible and simplified system suitable for novice users. SAL has been used for successfully implementing several low-cost sensor network systems.

Modelling the Sublimation-Desublimation Processes for Production of Ultrafine Powders

The purpose of this work is to establish the theoretical foundations for calculating and designing the sublimationcondensation processes in chemical apparatuses which are intended for production of ultrafine powders of crystalline and amorphous materials with controlled fractional composition. Theoretic analysis of the primary processes of nucleation and growth kinetics of the clusters according to the degree of super-saturation and the homogeneous or heterogeneous nature of nucleation has been carried out. The engineering design procedures of desublimation processes have been offered and tested for modification of the Claus process.

Biodiesel Production from Palm Oil using Heterogeneous Base Catalyst

In this study, the transesterification of palm oil with methanol for biodiesel production was studied by using CaO–ZnO as a heterogeneous base catalyst prepared by incipient-wetness impregnation (IWI) and co-precipitation (CP) methods. The reaction parameters considered were molar ratio of methanol to oil, amount of catalyst, reaction temperature, and reaction time. The optimum conditions–15:1 molar ratio of methanol to oil, a catalyst amount of 6 wt%, reaction temperature of 60 °C, and reaction time of 8 h–were observed. The effects of Ca loading, calcination temperature, and catalyst preparation on the catalytic performance were studied. The fresh and spent catalysts were characterized by several techniques, including XRD, TPR, and XRF.

Optimal Multilayer Perceptron Structure For Classification of HIV Sub-Type Viruses

The feature of HIV genome is in a wide range because of it is highly heterogeneous. Hence, the infection ability of the virus changes related with different chemokine receptors. From this point, R5 and X4 HIV viruses use CCR5 and CXCR5 coreceptors respectively while R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to classify by using the coreceptors of HIV genome. The aim of this study is to develop the optimal Multilayer Perceptron (MLP) for high classification accuracy of HIV sub-type viruses. To accomplish this purpose, the unit number in hidden layer was incremented one by one, from one to a particular number. The statistical data of R5X4, R5 and X4 viruses was preprocessed by the signal processing methods. Accessible residues of these virus sequences were extracted and modeled by Auto-Regressive Model (AR) due to the dimension of residues is large and different from each other. Finally the pre-processed dataset was used to evolve MLP with various number of hidden units to determine R5X4 viruses. Furthermore, ROC analysis was used to figure out the optimal MLP structure.

Hybrid TOA/AOA Schemes for Mobile Location in Cellular Communication Systems

Wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When fewer base stations (BSs) may be available for location purposes or the measurements with large errors in non-line-of-sight (NLOS) environments, it is necessary to integrate all available heterogeneous measurements to achieve high location accuracy. This paper illustrates a hybrid proposed schemes that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to give a location estimate of the MS. The proposed schemes mitigate the NLOS effect simply by the weighted sum of the intersections between three TOA circles and the AOA line without requiring a priori information about the NLOS error. Simulation results show that the proposed methods can achieve better accuracy when compare with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

SIP-Based QoS Management Architecture for IP Multimedia Subsystems over IP Access Networks

True integration of multimedia services over wired or wireless networks increase the productivity and effectiveness in today-s networks. IP Multimedia Subsystems are Next Generation Network architecture to provide the multimedia services over fixed or mobile networks. This paper proposes an extended SIP-based QoS Management architecture for IMS services over underlying IP access networks. To guarantee the end-to-end QoS for IMS services in interconnection backbone, SIP based proxy Modules are introduced to support the QoS provisioning and to reduce the handoff disruption time over IP access networks. In our approach these SIP Modules implement the combination of Diffserv and MPLS QoS mechanisms to assure the guaranteed QoS for real-time multimedia services. To guarantee QoS over access networks, SIP Modules make QoS resource reservations in advance to provide best QoS to IMS users over heterogeneous networks. To obtain more reliable multimedia services, our approach allows the use of SCTP protocol over SIP instead of UDP due to its multi-streaming feature. This architecture enables QoS provisioning for IMS roaming users to differentiate IMS network from other common IP networks for transmission of realtime multimedia services. To validate our approach simulation models are developed on short scale basis. The results show that our approach yields comparable performance for efficient delivery of IMS services over heterogeneous IP access networks.

Multi-Agents Coordination Model in Inter- Organizational Workflow: Applying in Egovernment

Inter-organizational Workflow (IOW) is commonly used to support the collaboration between heterogeneous and distributed business processes of different autonomous organizations in order to achieve a common goal. E-government is considered as an application field of IOW. The coordination of the different organizations is the fundamental problem in IOW and remains the major cause of failure in e-government projects. In this paper, we introduce a new coordination model for IOW that improves the collaboration between government administrations and that respects IOW requirements applied to e-government. For this purpose, we adopt a Multi-Agent approach, which deals more easily with interorganizational digital government characteristics: distribution, heterogeneity and autonomy. Our model integrates also different technologies to deal with the semantic and technologic interoperability. Moreover, it conserves the existing systems of government administrations by offering a distributed coordination based on interfaces communication. This is especially applied in developing countries, where administrations are not necessary equipped with workflow systems. The use of our coordination techniques allows an easier migration for an e-government solution and with a lower cost. To illustrate the applicability of the proposed model, we present a case study of an identity card creation in Tunisia.

Measuring Heterogeneous Traffic Density

Traffic Density provides an indication of the level of service being provided to the road users. Hence, there is a need to study the traffic flow characteristics with specific reference to density in detail. When the length and speed of the vehicles in a traffic stream vary significantly, the concept of occupancy, rather than density, is more appropriate to describe traffic concentration. When the concept of occupancy is applied to heterogeneous traffic condition, it is necessary to consider the area of the road space and the area of the vehicles as the bases. Hence, a new concept named, 'area-occupancy' is proposed here. It has been found that the estimated area-occupancy gives consistent values irrespective of change in traffic composition.

Stochastic Comparisons of Heterogeneous Samples with Homogeneous Exponential Samples

In the present communication, stochastic comparison of a series (parallel) system having heterogeneous components with random lifetimes and series (parallel) system having homogeneous exponential components with random lifetimes has been studied. Further, conditions under which such a comparison is possible has been established.

Load Balancing in Heterogeneous P2P Systems using Mobile Agents

Use of the Internet and the World-Wide-Web (WWW) has become widespread in recent years and mobile agent technology has proliferated at an equally rapid rate. In this scenario load balancing becomes important for P2P systems. Beside P2P systems can be highly heterogeneous, i.e., they may consists of peers that range from old desktops to powerful servers connected to internet through high-bandwidth lines. There are various loads balancing policies came into picture. Primitive one is Message Passing Interface (MPI). Its wide availability and portability make it an attractive choice; however the communication requirements are sometimes inefficient when implementing the primitives provided by MPI. In this scenario we use the concept of mobile agent because Mobile agent (MA) based approach have the merits of high flexibility, efficiency, low network traffic, less communication latency as well as highly asynchronous. In this study we present decentralized load balancing scheme using mobile agent technology in which when a node is overloaded, task migrates to less utilized nodes so as to share the workload. However, the decision of which nodes receive migrating task is made in real-time by defining certain load balancing policies. These policies are executed on PMADE (A Platform for Mobile Agent Distribution and Execution) in decentralized manner using JuxtaNet and various load balancing metrics are discussed.

Content and Resources based Mobile and Wireless Video Transcoding

Delivering streaming video over wireless is an important component of many interactive multimedia applications running on personal wireless handset devices. Such personal devices have to be inexpensive, compact, and lightweight. But wireless channels have a high channel bit error rate and limited bandwidth. Delay variation of packets due to network congestion and the high bit error rate greatly degrades the quality of video at the handheld device. Therefore, mobile access to multimedia contents requires video transcoding functionality at the edge of the mobile network for interworking with heterogeneous networks and services. Therefore, to guarantee quality of service (QoS) delivered to the mobile user, a robust and efficient transcoding scheme should be deployed in mobile multimedia transporting network. Hence, this paper examines the challenges and limitations that the video transcoding schemes in mobile multimedia transporting network face. Then handheld resources, network conditions and content based mobile and wireless video transcoding is proposed to provide high QoS applications. Exceptional performance is demonstrated in the experiment results. These experiments were designed to verify and prove the robustness of the proposed approach. Extensive experiments have been conducted, and the results of various video clips with different bit rate and frame rate have been provided.