Effect of temperature on the removal of lead(II) by adsorption on China clay and wollastonite

The removal of Pb(II) from aqueous solution by adsorption on china clay and wollastonite is an attractive process. The amount of Pb(II) removed by adsorption is highly dependent on the temperature of the adsorbate solution and favours low temperature. The equilibrium times were noted, i.e. 90 min for china clay and 120 min for wollastonite. The various rate parameters of the adsorption process have been determined at different temperatures. The activation energies were determined and found to be ?5.345 kJ mol^?1 and ?8.730 kJ mol^?1 for Pb(II)-china clay and Pb(II)-wollastonite systems, respectively. The adsorption isotherm was measured experimentally at various temperatures. The negative values of enthalpy change (ΔH = ?77.95 kJ mol^?1 and ?16.40 kJ mol^?1 for china clay and wollastonite, respectively) indicate the exothermic nature of the adsorption processes for both systems. The isosteric heats of the adsorption process have been determined at various surface coverages of the adsorbents used. The various thermodynamic parameters have been calculated to elucidate the mechanism involved in the adsorption process.     

A Wireless Instructor System for Computer-Supported Collaborative Learning Requiring Immersive Presence (CSCLIP)

The Computer-Supported Collaborative Learning Requiring Immersive Presence (CSCLIP) concept has been established with the objective of extending and enhancing thee-learning experience of distance education, especially for classes that involve laboratory (lab) experiments. The CSCLIP concept defines immersive presence as an inherent requirement that enables cognitive, affective, and most importantly psychomotor learning objectives to integrate into designs and concepts for next generation e-learning systems (Sharda et~al., 2003). Within the CSCLIP architectural framework, the Wireless Instructor (WI) system has been conceptualized and developed as an essential device to effectively support teaching while roaming instructional features for both local and distance students. The WI system provides cost effective means to establish a real-time immersive presence for the distance learning (DL) student and his/her lab group peers. The technical design and system architecture to create a WI system are introduced in this paper. The objective of the WI system is to make the learning experience more vivid and interactive by enabling the DL students, as well as the local students that are not in the same room with the instructor(s) at the same time, to be able to flexibly interact with the instructor(s) in real-time. With this system the students can experience real-time or non-real-time virtual tours with the instructor(s), enabling the students to visit places that may not be easily accessible due to distance, limited space and/or time, cost, or possible danger. The WI system consists of two major sub-components. First is a wireless audio and video (AV) system, which transfers real-time AV signals to and from the instructor(s) to all students. Second is the wireless instructor locator & data assistant system. These two systems can be combined into one WI unit, but as the applied development technologies are somewhat distinct, their features and architectural designs will be described separately throughout this paper. Integration of the two systems will enable further capabilities.This revised version was published online in March 2005 with corrections to the cover dateThis project was funded by the U.S. Department of Education (DoE) award no. P116Z020042 project titled Telecommunications Virtual Laboratory Development.     

Activation of ethyl acetate over metal substituted MCM-41: application to alkylation and acylation

Al-MCM-41, Fe,Al-MCM-41 and Zn,Al-MCM-41 materials with different silicon to metal ratios were synthesized hydrothermally and characterized by XRD, BET, FT-IR, Acidity measurement by pyridine adsorbed FT-IR spectroscopy, ²⁹Si and ²⁷Al MAS NMR and ESR techniques. The orderly arrangement of mesoporous materials was clearly revealed from the XRD patterns. ²⁹Si and ²⁷Al MAS NMR established the co-ordination environment of silicon and aluminium. Electron paramagnetic resonance (EPR) study confirmed the co-ordination environment of Fe in Fe,Al-MCM-41 framework. The catalytic activity of these materials was evaluated in the vapour phase alkylation and acylation of ethylbenzene with ethyl acetate in the temperature range between 250 and 400 °C. The products were found to be 1,3-diethylbenzene (1,3-DEB), 1,4-diethylbenzene (1,4-DEB), 1,2-diethylbenzene (1,2-DEB), 4-ethylacetophenone (4-EAP) and acetophenone (AP). The reaction products revealed that activation of ethyl acetate is a convenient route for both alkylation and acylation reactions. The order of the catalysts activity for the reaction is found to be Fe,Al-MCM-41 (50) > Fe,Al-MCM-41 (100) > Zn,Al-MCM-41 (50) > Zn,Al-MCM-41 (100) > Al-MCM-41 (50) > Al-MCM-41 (100). In addition to the density of acid sites, the strength of acid sites is also important for this reaction. The effects of temperature, feed ratio, WHSV and time on stream were also examined and the results are discussed.     

Trust model for certificate revocation in ad hoc networks

In this paper we propose a distributed trust model for certificate revocation in ad hoc networks. The proposed model allows trust to be built over time as the number of interactions between nodes increase. Furthermore, trust in a node is defined not only in terms of its potential for maliciousness, but also in terms of the quality of the service it provides. Trust in nodes where there is little or no history of interactions is determined by recommendations from other nodes. If the nodes in the network are selfish, trust is obtained by an exchange of portfolios. Bayesian networks form the underlying basis for this model.     

Experimental Investigation for Performance Study of Wire Electrochemical Spark Cutting of Silica Epoxy Nanocomposites

Purpose

Polymer Nanocomposites are advanced engineering composites with enhanced properties. These materials play a central role in various industrial sectors. The growing awareness of the key parameters (which influence the physical properties) with different combination of matrix-reinforcement, are making them more attractive in various applications. Machining of these materials is a challenging task for engineers with their properties (hardness and brittleness) due to various combinations of matrix-reinforcement. Therefore, the aim of present work is to investigate the machining behaviour of Silicon Dioxide (silica) Epoxy Nanocomposite due to straight cutting by using Wire Electrochemical Spark Cutting (WECSC) process.

Method

A specific number of experiments were conducted based on one parameter at-a-time approach to study the effect of influencing input parameters.

Result

The effect of various process parameters namely voltage supply, electrolyte concentration, wire velocity, pulse-on time and silica particle concentration (Cp) such as 3%, 4% and 5% (weight percent) on performance measures such as material removal rate (MRR) and surface roughness were demonstrated experimentally.

Conclusion

WECSC has been found effective technique for cutting of Silicon Dioxide Epoxy Nanocomposite. It is reported that MRR increases with decrease in silica particle concentration in Silicon Dioxide Epoxy Nanocomposite.

     

FogMed: A Fog-Based Framework for Disease Prognosis Based Medical Sensor Data Streams

Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor data streams, named FogMed. This framework aims to improve the disease prediction accuracy by achieving two objectives: QoS guarantee of fog services and anomaly prediction of Medical data streams. We build a virtual FogMed environment and conduct comprehensive experiments on the public ECG dataset to validate the performance of FogMed. The experiment results show that it performs better than the cloud computing model for processing tasks with different complexities in terms of time efficiency.