Intelligent System Application to Monitor the Smart City Building Lighting

A smart city incorporates infrastructure methods that are environmentally responsible, such as smart communications, smart grids, smart energy, and smart buildings. The city administration has prioritized the use of cutting-edge technology and informatics as the primary strategy for enhancing service quality, with energy resources taking precedence. To achieve optimal energy management in the multidimensional system of a city tribe, it is necessary not only to identify and study the vast majority of energy elements, but also to define their implicit interdependencies. This is because optimal energy management is required to reach this objective. The lighting index is an essential consideration when evaluating the comfort indicators. In order to realize the concept of a smart city, the primary objective of this research is to create a system for managing and monitoring the lighting index. It is possible to identify two distinct phases within the intelligent system. Once data collection concludes, the monitoring system will be activated. In the second step, the operation of the control system is analyzed and its effect on the performance of the numerical model is determined. This evaluation is based on the proposed methodology. The optimized results were deemed satisfactory because they maintained the brightness index value (79%) while consuming less energy. The intelligent implementation system generated satisfactory outcomes, which were observed 1.75 times on average.     

Interaction of guided light in rib polymer waveguides with dielectrophoretically controlled nanoparticles

This work demonstrates an optofluidic system, where dielectrophoretically controlled suspended nanoparticles are used to manipulate the properties of an optical waveguide. This optofluidic device is composed of a multimode polymeric rib waveguide and a microfluidic channel as its upper cladding. This channel integrates dielectrophoretic (DEP) microelectrodes and is infiltrated with suspended silica and tungsten trioxide nanoparticles. By applying electrical signals with various intensities and frequencies to the DEP microelectrodes, the nanoparticles can be concentrated close to the waveguide surface significantly altering the optical properties in this region. Depending on the particle refractive indices, concentrations, positions and dimensions, the light remains confined or is scattered into the surrounding media in the microfluidic channel.     

Symmetry in scalar field topology

Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis because it gives deep insights into the properties of the underlying phenomenon. Though geometric symmetry has been well studied within areas like shape processing, identifying symmetry in scalar fields has remained largely unexplored due to the high computational cost of the associated algorithms. We propose a computationally efficient algorithm for detecting symmetric patterns in a scalar field distribution by analysing the topology of level sets of the scalar field. Our algorithm computes the contour tree of a given scalar field and identifies subtrees that are similar. We define a robust similarity measure for comparing subtrees of the contour tree and use it to group similar subtrees together. Regions of the domain corresponding to subtrees that belong to a common group are extracted and reported to be symmetric. Identifying symmetry in scalar fields finds applications in visualization, data exploration, and feature detection. We describe two applications in detail: symmetry-aware transfer function design and symmetry-aware isosurface extraction.     

Selection of industrial robots using compromise ranking and outranking methods

Selection of a robot for a specific industrial application is one of the most challenging problems in real time manufacturing environment. It has become more and more complicated due to increase in complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. At present, different types of industrial robots with diverse capabilities, features, facilities and specifications are available in the market. Manufacturing environment, product design, production system and cost involved are some of the most influencing factors that directly affect the robot selection decision. The decision maker needs to identify and select the best suited robot in order to achieve the desired output with minimum cost and specific application ability. This paper attempts to solve the robot selection problem using two most appropriate multi-criteria decision-making (MCDM) methods and compares their relative performance for a given industrial application. The first MCDM approach is ‘VIsekriterijumsko KOmpromisno Rangiranje’ (VIKOR), a compromise ranking method and the other one is ‘ELimination and Et Choice Translating REality’ (ELECTRE), an outranking method. Two real time examples are cited in order to demonstrate and validate the applicability and potentiality of both these MCDM methods. It is observed that the relative rankings of the alternative robots as obtained using these two MCDM methods match quite well with those as derived by the past researchers.     

A bandpass filter with adjustable bandwidth and predictable transmission zeros

In this article, a microstrip bandpass filter with an adjustable bandwidth and predictable transmission zeros is proposed. The proposed filter is implemented by combining two hairpin edge‐coupled resonators with interdigital capacitors. Compared to typical edge‐coupled filters, the proposed filter provides a wider bandwidth resulting from a higher coupling strength between its resonators. To further increase the coupling and consequently the bandwidth, a pair of etched slots in the ground plane is used. By adjusting the geometrical parameters of the interdigital capacitors and etched slots, the bandwidth can be easily adjusted. The filter features two transmission zeros, which are determined by means of the semi‐analytical model developed as part of this work. Furthermore, the proposed filters can be cascaded to obtain a sharper cutoff frequency response. Frequency responses of the filters from measurements are in good agreement with those simulated using IE3D in the 5–9 GHz range. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.     

Automated dynamic detection of busy–wait synchronizations

With the advent of multicores, multithreaded programming has acquired increased importance. In order to obtain good performance, the synchronization constructs in multithreaded programs need to be carefully implemented. These implementations can be broadly classified into two categories: busy–wait and schedule‐based. For shared memory architectures, busy–wait synchronizations are preferred over schedule‐based synchronizations because they can achieve lower wakeup latency, especially when the expected wait time is much shorter than the scheduling time. While busy–wait synchronizations can improve the performance of multithreaded programs running on multicore machines, they create a challenge in program debugging, especially in detecting and identifying the causes of data races. Although significant research has been done on data race detection, prior works rely on one important assumption—the debuggers are aware of all the synchronization operations performed during a program run. This assumption is a significant limitation as multithreaded programs, including the popular SPLASH‐2 benchmark have busy–wait synchronizations such as barriers and flag synchronizations implemented in the user code. We show that the lack of knowledge of these synchronization operations leads to unnecessary reporting of numerous races. To tackle this problem, we propose a dynamic technique for identifying user‐defined synchronizations that are performed during a program run. Both software and hardware implementations are presented. Furthermore, our technique can be easily exploited by a record/replay system to significantly speedup the replay. It can also be leveraged by a transactional memory system to effectively resolve a livelock situation. Our evaluation confirms that our synchronization detector is highly accurate with no false negatives and very few false positives. We further observe that the knowledge of synchronization operations results in 23% reduction in replay time. Finally, we show that using synchronization knowledge livelocks can be efficiently avoided during runtime monitoring of programs. Copyright © 2009 John Wiley & Sons, Ltd.     

Identifying and overcoming the challenges of implementing a project management office

With the ongoing challenge of successfully managing information technology (IT) projects, organizations are recognizing the need for greater project management discipline. For many organizations, this has meant ratcheting up project management skills, processes, and governance structures by implementing a project management office (PMO). While anecdotal evidence suggests that implementing a PMO can be quite difficult, few studies discuss the specific challenges involved, and how organizations can overcome them. To address this gap in existing knowledge, we conducted a Delphi study to (1) identify the challenges of implementing a PMO for managing IT projects, (2) rank these challenges in order of importance, (3) discover ways in which some organizations have overcome the top-ranked challenges, and (4) understand the role of PMO structure, metrics, and tools in the implementation of a PMO.We identified 34 unique challenges to implementing a PMO and refined this list to 13 challenges that our Delphi panelists considered most important. The top-three challenges were (1) rigid corporate culture and failure to manage organizational resistance to change, (2) lack of experienced project managers (PMs) and PMO leadership, and (3) lack of appropriate change management strategy. Through follow-up interviews with selected panelists, we identified a series of actions that can be taken to overcome these challenges including having a strong PMO champion, starting small and demonstrating the value of the PMO, obtaining support from opinion leaders, hiring an experienced program manager who understands the organization, bringing the most talented PMs into the PMO implementation team, adopting a flexible change management strategy, and standardizing processes prior to PMO implementation. The interviews were also used to better understand the role of PMO structure, metrics, and tools. In terms of PMO structure, we found that ‘light’ PMOs were more likely to be implemented successfully. Most organizations eschew formal metrics, instead relying on subjective indicators of PMO success. Lastly, it appears that PMO tools are difficult to implement unless a project management culture has been established.     

Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator

In cold season, wet snow ice accretion on overhead transmission lines increases wind load effects which in turn increases line tension. This increased line tension causes undesirable effects in power systems. This paper discusses the design of an observer-based boundary sliding mode control (BSMC) for 3 DOF overhead transmission line de-icing robot manipulator (OTDIRM). A robust radial basis functional neural network (RBFNN) observer-based neural network (NN) controller is developed for the motion control of OTDIRM, which is a combination of BSMC, NN approximation and adaptation law. The RBFNN-based adaptive observer is designed to estimate the positions and velocities. The weights of both NN observer and NN approximator are tuned off-line using particle swarm optimization. Using Lyapunov analysis the closed loop tracking error was verified for a 3 DOF OTDIRM. Finally, the robustness of the proposed neural network-based adaptive observer boundary sliding mode control (NNAOBSMC) was verified against the input disturbances and uncertainties.