Multi-period design of heat exchanger networks

Heat exchanger networks are an integral part of chemical processes as they recover available heat and reduce utility consumption, thereby improving the overall economics of an industrial plant. This paper focuses on heat exchanger network design for multi-period operation wherein the operating conditions of a process may vary with time. A typical example is the hydrotreating process in petroleum refineries where the operators increase reactor temperature to compensate for catalyst deactivation. Superstructure based multi-period models for heat exchanger network design have been proposed previously employing deterministic optimisation algorithms, e.g. (0005 and 0180). Stochastic optimisation algorithms have also been applied for the design of flexible heat exchanger networks recently (0110 and 0115). The present work develops an optimisation approach using simulated annealing for design of heat exchanger networks for multi-period operation. A comparison of the new optimisation approach with previous deterministic optimisation based design approaches is presented to illustrate the utilisation of simulated annealing in design of optimal heat exchanger network configurations for multi-period operation.     

Embedded passive components in advanced 3D chips and micro/nano electronic systems

Microsystem Technologies - Electronic devices are shrinking day by day, while the speed and reliability is increasing. At the same time, IC designs and micro/nano electronic systems are becoming...     

Coupling of optimal variation of parameters method with Adomian’s polynomials for nonlinear equations representing fluid flow in different geometries

In this study, we describe a modified analytical algorithm for the resolution of nonlinear differential equations by the variation of parameters method (VPM). Our approach, including auxiliary parameter and auxiliary linear differential operator, provides a computational advantage for the convergence of approximate solutions for nonlinear boundary value problems. We consume all of the boundary conditions to establish an integral equation before constructing an iterative algorithm to compute the solution components for an approximate solution. Thus, we establish a modified iterative algorithm for computing successive solution components that does not contain undetermined coefficients, whereas most previous iterative algorithm does incorporate undetermined coefficients. The present algorithm also avoid to compute the multiple roots of nonlinear algebraic equations for undetermined coefficients, whereas VPM required to complete calculation of solution by computing roots of undetermined coefficients. Furthermore, a simple way is considered for obtaining an optimal value of an auxiliary parameter via minimizing the residual error over the domain of problem. Graphical and numerical results reconfirm the accuracy and efficiency of developed algorithm.

     

ICT for socio-economic development: A citizens’ perspective

There is a widespread belief that information and communication technologies (ICTs) can play a significant role in the socio-economic development of a developing country. ICT has the potential to affect many aspects of economic and societal activities such as GDP growth, employment, productivity, poverty alleviation, quality of life, education, and healthcare. While the literature provides a myriad of definitions and elements of socio-economic development, the focus tends to be on theoretical conceptualizations from various disciplines and impacts from isolated individual projects. In particular, the impact of ICT on socio-economic development has not been carefully examined from the viewpoint of the ultimate stakeholder, the citizens of a country, who are the final consumers of the technology. This study fills this gap by focusing on the citizens’ view in describing ICT-driven socio-economic development in a developing country. A theoretical framework influenced by the “capabilities approach” was developed to guide this research, and the interpretive stance was used to conduct the study. More specifically, the narrative research method, which is seldom used in IS research but is appropriate for this study, was used. Narratives allow deeper and profound insights into social representations and participants' beliefs about the role of ICT in socio-economic development. Using this methodology, a model of the impact dimensions of socio-economic development is presented.     

Nanotechnology based electrical control and navigation system for worm guidance using electric field gradient

Microsystem Technologies - The objective of this research paper is to find the way to guide the worms in an electric field gradient for a specific time period. Research has been done to guide the...     

Motion optimization of human body for impulse-based applications

This paper presents the optimal motion generation of the kinematic redundant human body model for impulse-based applications. Inspired by effective and safe motion generation of the human body, we propose a motion generation algorithm considering the external and internal impulses. Firstly, the cost function is defined using the closed form model of external and internal impulses. Then, the self-motion is exploited by using the gradient projection method to generate the optimal motions. Furthermore, the proposed methodology is verified through simulations considering a 4-DOF planar human body model for landing on ground and ball kicking applications and a 3-DOF human arm model for sawing task. It is found that, considering the internal and external impulses for optimization, the optimized posture’s results are well identical to the human body behavior in daily impulse-based motions.     

Classifying and Summarizing Information from Microblogs During Epidemics

During a new disease outbreak, frustration and uncertainties among affected and vulnerable population increase. Affected communities look for known symptoms, prevention measures, and treatment strategies. On the other hand, health organizations try to get situational updates to assess the severity of the outbreak, known affected cases, and other details. Recent emergence of social media platforms such as Twitter provide convenient ways and fast access to disseminate and consume information to/from a wider audience. Research studies have shown potential of this online information to address information needs of concerned authorities during outbreaks, epidemics, and pandemics. In this work, we target three types of end-users (i) vulnerable population—people who are not yet affected and are looking for prevention related information (ii) affected population—people who are affected and looking for treatment related information, and (iii) health organizations—like WHO, who are interested in gaining situational awareness to make timely decisions. We use Twitter data from two recent outbreaks (Ebola and MERS) to build an automatic classification approach useful to categorize tweets into different disease related categories. Moreover, the classified messages are used to generate different kinds of summaries useful for affected and vulnerable communities as well as health organizations. Results obtained from extensive experimentation show the effectiveness of the proposed approach.     

Silhouette-based human action recognition using SAX-Shapes

Human action recognition is an important problem in Computer Vision. Although most of the existing solutions provide good accuracy results, the methods are often overly complex and computationally expensive, hindering practical applications. In this regard, we introduce the combination of time-series representation for the silhouette and Symbolic Aggregate approXimation (SAX), which we refer to as SAX-Shapes, to address the problem of human action recognition. Given an action sequence, the extracted silhouettes of an actor from every frame are transformed into time series. Each of these time series is then efficiently converted into the symbolic vector: SAX. The set of all these SAX vectors (SAX-Shape) represents the action. We propose a rotation invariant distance function to be used by a random forest algorithm to perform the human action recognition. Requiring only silhouettes of actors, the proposed method is validated on two public datasets. It has an accuracy comparable to the related works and it performs well even in varying rotation.