Performance evaluation of semantic registries: OWLJessKB and instanceStore

Service discovery is a critical task in distributed computing architectures for finding a particular service instance. Semantic annotations of services help to enrich the service discovery process. Semantic registries are an important component for the discovery of services and they allow for semantic interoperability through ontology-based query formulation and dynamic mapping of terminologies between system domains. This paper evaluates two semantic registries—OWLJessKB implementation and instanceStore—to determine the suitability of these with regards to the query response time and the overall scalability for use in mathematical services. Mathematical ontologies from the MONET project are used to undertake comparison. The results demonstrate that the performance of registries may be compared across two axes: (1) time to initialize (i.e. time to load an initial ontology into memory); (2) time to query (i.e. time to reason with an ontology loaded into memory).     

Novel design to improve band to band tunneling and gate induced drain leakages (GIDL) in cylindrical gate all around (GAA) MOSFET

Microsystem Technologies - In this paper a cylindrical Dual Metal (DM) Dielectric Engineered (DE) Gate All Around (GAA) MOSFET has been proposed to resolve a big issue of Gate Inducted Drain...     

Design and analysis of novel micro displacement amplification mechanism actuated by chevron shaped thermal actuators

This paper presents design and analysis of microelectromechanical system (MEMS) based displacement amplification mechanism actuated using thermal actuators with enhanced performance. The proposed model consists of chevron shaped thermal actuators, an amplification mechanism capable of amplifying displacement 20 times and an electrostatic comb drives for sensing displacements. When voltage is applied to thermal chevrons, displacement is produced which is then amplified 20 times. Steady state static thermal electrical analysis is performed under variable resistivity and voltage bias of 2 V. In-plane reaction forces of magnitude 194.2 and 150.91 µN along X and Y-axis, respectively, thus producing displacement of 0.11 and 2.22 µm along X and Y-axis, respectively. Time domain simulations of device are carried with constant electrical resistivity, variable voltage and convective boundary conditions. Modal analysis of the mechanism is carried out to predict the natural frequencies and associated mode shapes of mechanism during free vibrations. The desired mode is at frequency of 286.160 kHz. Dynamic simulations including direct integration-transient, transient modal and steady state modal analysis are performed on the device for time span of 0.0006 s, under application of 25 g and frequency range of 200–300 kHz. Simulation results prove the viability of the mechanism as an amplification device with enhanced voltage–stroke ratio.

     

Fraudulent Firm Classification: A Case Study of an External Audit

This paper is a case study of visiting an external audit company to explore the usefulness of machine learning algorithms for improving the quality of an audit work. Annual data of 777 firms from 14 different sectors are collected. The Particle Swarm Optimization (PSO) algorithm is used as a feature selection method. Ten different state-of-the-art classification models are compared in terms of their accuracy, error rate, sensitivity, specificity, F measures, Mathew’s Correlation Coefficient (MCC), Type-I error, Type-II error, and Area Under the Curve (AUC) using Multi-Criteria Decision-Making methods like Simple Additive Weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results of Bayes Net and J48 demonstrate an accuracy of 93% for suspicious firm classification. With the appearance of tremendous growth of financial fraud cases, machine learning will play a big part in improving the quality of an audit field work in the future.     

The impact of big data analytics on firms’ high value business performance

Big Data Analytics (BDA) is an emerging phenomenon with the reported potential to transform how firms manage and enhance high value businesses performance. The purpose of our study is to investigate the impact of BDA on operations management in the manufacturing sector, which is an acknowledged infrequently researched context. Using an interpretive qualitative approach, this empirical study leverages a comparative case study of three manufacturing companies with varying levels of BDA usage (experimental, moderate and heavy). The information technology (IT) business value literature and a resource based view informed the development of our research propositions and the conceptual framework that illuminated the relationships between BDA capability and organizational readiness and design. Our findings indicate that BDA capability (in terms of data sourcing, access, integration, and delivery, analytical capabilities, and people’s expertise) along with organizational readiness and design factors (such as BDA strategy, top management support, financial resources, and employee engagement) facilitated better utilization of BDA in manufacturing decision making, and thus enhanced high value business performance. Our results also highlight important managerial implications related to the impact of BDA on empowerment of employees, and how BDA can be integrated into organizations to augment rather than replace management capabilities. Our research will be of benefit to academics and practitioners in further aiding our understanding of BDA utilization in transforming operations and production management. It adds to the body of limited empirically based knowledge by highlighting the real business value resulting from applying BDA in manufacturing firms and thus encouraging beneficial economic societal changes.     

The Impact of Social Media on Consumers’ Acculturation and Purchase Intentions

Social media has emerged as a significant and effective means of assisting and endorsing activities and communications among peers, consumers and organizations that outdo the restrictions of time and space. While the previous studies acknowledge the role of agents of culture change, it largely remains silent on the role of social media in influencing acculturation outcomes and consumption choices. This study uses self-administered questionnaire to collect data from 514 Turkish-Dutch respondents and examines how their use of social media affects their acculturation and consumption choices. This research makes a significant contribution to consumer acculturation research by showing that social media is a vital means of culture change and a driver of acculturation strategies and consumption choices. This study is the first to investigate the role of social media as an agent of culture change in terms of how it impacts acculturation and consumption. The paper discusses implications for theory development and for practice.     

Design and simulation of pyroelectric detectors with nanometer size spider-web for low thermal conductance

We report the design and simulation of uncooled pyroelectric detectors which utilizes a nanometer sized mesh or truss to support the suspended detector. Pyroelectric detector is a class of thermal detector in which the change in temperature causes the change in the spontaneous polarization in the sensing material. Ca modified lead titanate (PCT) was selected as the thermometer in the detector because of its high pyroelectric figure of merit. The design and simulation of pyroelectric detectors have been conducted by simulating the structure with Intellisuite™. Finite element method (FEM) was used to simulate the structural and thermal properties of the device. The simulated detectors had a spider web-like structure with each of the strut (ring) of spider web had a width of 100 nm. In the design, the pyroelectric detectors utilized Ni_0.8Cr_0.2 absorber, PCT sensing layer, Ti electrodes, Al₂O₃ structural layer to obtain low thermal conductance between the detector and Si substrate. Three different types of pyroelectric detectors were designed and analyzed. The first design had linear electrode and simple spider web support. The value of the thermal conductance of this detector was found to be 3.98 × 10⁻⁸ W/K. The second design had a longer thermal path than the first one and the thermal conductivity of this device was found to be 2.41 × 10⁻⁸ W/K. High detectivity was obtained by reducing the thermal conductance between the sensing layer and the substrate or the heat sink in the third design. The design was optimized for the best result by modifying the shape, dimension and thickness of various layers namely absorber, electrodes, sensing layer, and struts. The thermal conductance between the sensor and the substrate using the third design was found to be as low as 4.57 × 10⁻⁹ W/K which is significantly lower than previously reported values. The thicknesses of the web structure, web support, electrodes, sensing layer, and absorber of the final structure were 2, 1, 0.5, 2, and 0.2 µm respectively for this value of thermal conductance. The absorber diameter was 50 µm and the diameter of the spider web was 200 µm. A total of 80 struts with 100 nm width were used in the design.

     

Network-aware heuristics for inter-domain meta-scheduling in Grids

Grid computing generally involves the aggregation of geographically distributed resources in the context of a particular application. As such resources can exist within different administrative domains, requirements on the communication network must also be taken into account when performing meta-scheduling, migration or monitoring of jobs. Similarly, coordinating efficient interaction between different domains should also be considered when performing such meta-scheduling of jobs. A strategy to perform peer-to-peer-inspired meta-scheduling in Grids is presented. This strategy has three main goals: (1) it takes the network characteristics into account when performing meta-scheduling; (2) communication and query referral between domains is considered, so that efficient meta-scheduling can be performed; and (3) the strategy demonstrates scalability, making it suitable for many scientific applications that require resources on a large scale. Simulation results are presented that demonstrate the usefulness of this approach, and it is compared with other proposals from literature.     

Analysis of nutritional transport through a capillary: Normal and stenosed

Presented herein are the studies of nutritional transport from capillary to tissues in normal and stenosed arteries. The model incorporates modified Casson's fluid representation for the blood and symmetric stenosis has been assumed at some distance from the entry. Assessment of the severity of the disease could be made possible through the variation of a parameter named as retention parameter. Nutritional flux at the capillary wall is affected by the growing stenosis and its variation has been observed through a decreasing trend of the retention parameter from 1 to 0. Results for local variation of viscosity contrary to Fahraeus-Lindquist effect have been explained. Symmetry of the distribution of the wall shearing stress and resistance to flow and their growth with the developing stenosis is another important feature of this analysis. Taylor diffusivity coefficient increases considerably with growing stenosis and the nutritional transport to the deeper cells of the tissue will naturally decrease.     

The software architecture of a distributed problem‐solving environment

This paper describes the functionality and software architecture of a generic problem‐solving environment (PSE) for collaborative computational science and engineering. A PSE is designed to provide transparent access to heterogeneous distributed computing resources, and is intended to enhance research productivity by making it easier to construct, run, and analyze the results of computer simulations. Although implementation details are not discussed in depth, the role of software technologies such as CORBA, Java, and XML is outlined. An XML‐based component model is presented. The main features of a Visual Component Composition Environment for software development, and an Intelligent Resource Management System for scheduling components, are described. Some prototype implementations of PSE applications are also presented. Copyright © 2000 John Wiley & Sons, Ltd.