EXSHOF: An artificial intelligence approach to high-order filter synthesis

A two-tier expert-system-based synthesis of high-order filters is developed. Expert-system techniques have been used for choosing a particular biquad structure and for selection of the high-order filter structure as well. The data inputs will be either filter specifications or transfer functions and the output will be a detailed filter circuit with all its element values. EXSHOF ( pert System based ynthesis of igh rder ilter) is totally menu-driven and highly interactive. It assumes little knowledge of computers or filters from the user. The complete package is implemented in Turbo PASCAL and Turbo PROLOG languages.     

A high-quality dual-input differentiator

A dual-input ideal differentiator network design with a single resistor-controlled time constant and high-gain operational amplifier (OA) devices is described. At high frequencies, the network becomes functionally nonideal and its quality factor (Q) degrades because of the frequency-dependent gain of the OA. A suitable Q-compensation design that yields a 1:|A|² order of Q improvement at higher frequencies is proposed. The network exhibits high-frequency deemphasis characteristics due to the OA-poles which would suppress the high-frequency noise components     

Deflection characteristics of some special configurations of snake-type robots

The redundant robots analyzed here have large numbers of degrees of freedom. Such robots are analogous to snake or tentacles and are useful for operation in highly constrained environments and novel forms of locomotion — here it has been defined as critical manipulation. In this paper the end-point deflection of hyper-redundant robots have been studied by parameterization of the flexible links of the robot manipulator. A number of planar configurations of the redundant manipulator were taken into consideration for the present study and the configuration which gives minimum end-point deflection has been recommended for the critical manipulation. This work is significant for some of the research activities recently going on in NASA's Kennedy Space Center towards the application of hyper-redundant robots for manipulation inside the space Shuttle Cargo Bay.     

Technology roles and paths of influence in an ecosystem model of technology evolution

We propose a new conceptual model for understanding technology evolution that highlights dynamic and highly interdependent relationships among multiple technologies. We argue that, instead of considering technologies in isolation, technology evolution is best viewed as a dynamic system or ecosystem that includes a variety of interrelated technologies. By considering the interdependent nature of technology evolution, we identify three roles that technologies play within a technology ecosystem. These roles are components, products and applications, and support and infrastructure. Technologies within an ecosystem interact through these roles and impact each others’ evolution. We also classify types of interactions between technology roles, which we term paths of influence. We demonstrate the use of our proposed model through examples of wireless networking (Wi-Fi) technologies and a business mini-case on the digital music industry.

A theoretical and empirical investigation of multi‐item on‐line auctions

In this paper we explore and analyze the structure of Internet auctions from an analytical and an empirical perspective. Such web‐based auctions are rapidly emerging as a mercantile process of choice in the electronic marketplace. We observe current Internet auctions for one‐time products, such as rapidly aging hardware, and analyze them within the framework of the existing auction theory. While traditional auction theory focuses on single‐item auctions, we observe that a majority of on‐line auctions are multi‐item auctions. A significant contribution of this work is the theoretical derivation of the structure of the winning bids in multi‐item progressive on‐line auctions. Additionally, for comparative purposes, we explore the structural characteristics of alternative multi‐item auction mechanisms proposed in the auction theory. We derive hypotheses based on our analytical results and compare two different types of auction mechanisms. We test the traditional auction theory assumption regarding the homogeneity of bidders and present the first ever empirically derived classification and performance‐comparison of on‐line bidders. We test our hypotheses using real‐world empirical data obtained by tracking a premier web‐based auction site. Statistical analysis of the data indicates that firms may gain by choosing alternative auction mechanisms. We also provide directions for further exploration of this emerging but important dimension of electronic commerce. This revised version was published online in July 2006 with corrections to the Cover Date.     

Real-time classification of rotating shaft loading conditions usingartificial neural networks

Vibration analysis can give an indication of the condition of a rotating shaft highlighting potential faults such as unbalance and rubbing. Faults may however only occur intermittently and consequently to detect these requires continuous monitoring with real time analysis. This paper describes the use of artificial neural networks (ANNs) for classification of condition and compares these with other discriminant analysis methods. Moments calculated from time series are used as input features as they can be quickly computed from the measured data. Orthogonal vibrations are considered as a two-dimensional vector, the magnitude of which can be expressed as time series. Some simple signal processing operations are applied to the data to enhance the differences between signals and comparison is made with frequency domain analysis.     

Universal trajectories of scientific success

Success of a scientific entity generally undergoes myriad vicissitudes, resulting in different patterns of success trajectories. Understanding and characterizing the rise and fall of scientific success is important not only from the perspective of designing new mathematical models but also to enhance the quality of various real-world systems such as scientific article search and recommendation systems. In this paper, we present a large-scale study of the subject by analyzing the success of two major scientific entities—papers and authors—in Computer Science and Physics. We quantify “success” in terms of citations and in the process discover six distinct success trajectories which are prevalent across multidisciplinary datasets. Our results reveal that these trajectories are not fully random, but are rather generated through a complex process. We further shed light on the behavior of these trajectories and unfold many interesting facets by asking fundamental questions—which trajectory is more successful, how significant and stable are these categories, what factors trigger the rise and fall of trajectories? A few of our findings sharply contradict the well-accepted beliefs on bibliographic research such as “Preferential Attachment”, “first-mover advantage”. We believe that this study will argue in favor of revising the existing metrics used for quantifying scientific success.     

Visual perception-based criminal identification: a query-based approach

Abstract

The visual perception of eyewitness plays a vital role in criminal identification scenario. It helps law enforcement authorities in searching particular criminal from their previous record. It has been reported that searching a criminal record manually requires too much time to get the accurate result. We have proposed a query-based approach which minimises the computational cost along with the reduction of search space. A symbolic database has been created to perform a stringent analysis on 150 public (Bollywood celebrities and Indian cricketers) and 90 local faces (our data-set). An expert knowledge has been captured to encapsulate every criminal’s anatomical and facial attributes in the form of symbolic representation. A fast query-based searching strategy has been implemented using dynamic decision tree data structure which allows four levels of decomposition to fetch respective criminal records. Two types of case studies - viewed and forensic sketches have been considered to evaluate the strength of our proposed approach. We have derived 1200 views of the entire population by taking into consideration 80 participants as eyewitness. The system demonstrates an accuracy level of 98.6% for test case I and 97.8% for test case II. It has also been reported that experimental results reduce the search space up to 30 most relevant records.     

High power and low cross‐polarization microstrip patch array antenna at S‐band

This article reports the design and development of high power, low cross‐polarization, and high efficiency circularly polarized microstrip patch array antenna at S‐band, proposed for Indian Regional Navigation Satellite System payload. A novel feeding mechanism for truncated corner square patch based on square coaxial line for broadband impedance matching is discussed. Sequential rotation scheme for axial ratio improvement in an array is implemented. High power handling margins in critical regions of square coaxial line for multipaction breakdown is brought out. Measured 19 dB return loss bandwidth of array antenna is 15.6%. Axial ratio of 0.78 dB over global coverage is achieved in the desired frequency band of operation. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.