SpeechActs: a spoken-language framework

SpeechActs is a prototype testbed for developing spoken natural language applications. In developing SpeechActs, our primary goal was to enable software developers without special expertise in speech or natural language to create effective conversational speech applications-that is, applications with which users can speak naturally, as if they were conversing with a personal assistant. We also wanted SpeechActs applications to work with one another without requiring that each have specific knowledge of other applications running in the same suite. A discourse management component is necessary to embody the information that allows such a natural conversational flow. Because technology changes so rapidly, we also did not want to tie developers to specific speech recognizers or synthesizers. We wanted them to be able to use these speech technologies as plug-in components     

Interactive graphic data processing in cartography

This paper deals with the work and importance of interactive data processing as a system for assisting in the work of cartography. Both hardware and software concepts for the SICAD interactive graphic system for cartography are presented and explained using practical examples.     

Interactive transmission processing for large images in a resource-constraint mobile wireless network

In the state-of-the-art methods for (large) image transmission, no user interaction behaviors (e.g., user tapping) can be actively involved to affect the transmission performance (e.g., higher image transmission efficiency with relatively poor image quality). So, to effectively and efficiently reduce the large image transmission costs in resource-constraint mobile wireless networks (MWN), we design a content-based and bandwidth-aware Interactive large Image Transmission method in MWN, called the I it. To the best of our knowledge, this is the first study on the interactive image transmission. The whole transmission processing of the I it works as follows: before transmission, a preprocessing step computes the optimal and initial image block (IB) replicas based on the image content and the current network bandwidth at the sender node. During transmission, in case of unsatisfied transmission efficiency, the user’s anxiety to preview the image can be implicitly indicated by the frequency of tapping the screen. In response, the transmission resolutions of the candidate IB replicas can be dynamically adjusted based on the user anxiety degree (UAD). Finally, the candidate IB replicas are transmitted with different priorities to the receiver for reconstruction and display. The experimental results show that the performance of our approach is both efficient and effective, minimizing the response time by decreasing the network transmission cost while improving user experiences.     

A hybrid scheme for processing data structures in a dataflowenvironment

The asynchronous nature of the dataflow model of computation allows the exploitation of maximum inherent parallelism in many application programs. However, before the dataflow model of computation can become a viable alternative to the control flow model of computation, one has to find practical solutions to some problems such as efficient handling of data structures. The paper introduces a new model for handling data structures in a dataflow environment. The proposed model combines constant time access capabilities of vectors as well as the flexibility inherent in the concept of pointers. This allows a careful balance between copying and sharing to optimize the storage and processing overhead incurred during the operations on data structures. The mode] is compared by simulation to other data structure models proposed in the literature, and the results are good     

Interactive computer-aided design of non-hybrid and hybrid plate girders

An interactive microcomputer program is presented for design of welded stiffened steel plate girders according to the AISC specification. The program is capable of designing hybrid girders and takes into account the tension-field action of the web. This program demonstrates the effectiveness of microcomputers in practical design of structures.     

Interactive graphics software for an undergraduate course in digital signal processing

The advantages of using a suite of computer programs developed to aid the teaching of undergraduate students in the principles and applications of digital signal processing are discussed. One particular interactive graphics program which displays z-plane diagrams and the related frequency response graphs is described and examples of the display presented. Some experience in using this software is presented.     

Controlling quantum information processing in hybrid systems on chips

We investigate quantum information processing, transfer and storage in hybrid systems comprised of diverse blocks integrated on chips. Strong coupling between superconducting (SC) qubits and ensembles of ultracold atoms or NV-center spins is mediated by a microwave transmission-line resonator that interacts near-resonantly with the atoms or spins. Such hybrid devices allow us to benefit from the advantages of each block and compensate for their disadvantages. Specifically, the SC qubits can rapidly implement quantum logic gates, but are “noisy” (prone to decoherence), while collective states of the atomic or spin ensemble are “quiet”(protected from decoherence) and thus can be employed for storage of quantum information. To improve the overall performance (fidelity) of such devices we discuss dynamical control to optimize quantum state-transfer from a “noisy” qubit to the “quiet” storage ensemble. We propose to maximize the fidelity of transfer and storage in a spectrally inhomogeneous spin ensemble, by pre-selecting the optimal spectral portion of the ensemble. Significant improvements of the overall fidelity of hybrid devices are expected under realistic conditions. Experimental progress towards the realization of these schemes is discussed.     

A framework for hybrid model predictive control in mineral processing

Model Predictive Control (MPC) is an advanced technique for process control that has seen a significant and widespread increase in its use in the process industry since its introduction. In mineral processing, in particular, several applications of conventional MPC can be found for the individual processes of crushing, grinding, flotation, thickening, agglomeration, and smelting with varying degrees of success depending on the variables involved and the control objectives. Given the complexity of the processes normally found in mineral processing, there is also great interest in the design and development of advanced control techniques which aim to deal with situations that conventional controllers are unable to do. In this aspect, Hybrid MPC enables the representation of systems, incorporating logical variables, rules, and continuous dynamics. This paper firstly presents a framework for modeling and representation of hybrid systems, and the design and development of hybrid predictive controllers. Additionally, two application examples in mineral processing are presented. Results through simulation show that the control schemes developed under this framework exhibit a better performance when compared with conventional expert or MPC controllers, while providing a highly systematized methodology for the analysis, design, and development of hybrid MPC controllers.     

Two-stage hybrid flowshop scheduling with simultaneous processing machines

Simultaneous processing machines, common in processing industries such as steel and food production, can process several jobs simultaneously in the first-in, first-out manner. However, they are often highly energy-consuming. In this paper, we study a new two-stage hybrid flowshop scheduling problem, with simultaneous processing machines at the first stage and a single no-idle machine with predetermined job sequence at the second stage. A mixed integer programming model is proposed with the objective of minimizing the total processing time to reduce energy consumption and improve production efficiency. We give a sufficient and necessary condition to construct feasible sequencing solutions and present an effective approach to calculate the time variables for a feasible sequencing solution. Based on these results, we design a list scheduling heuristic algorithm and its improvement. Both heuristics can find an optimal solution under certain conditions with complexity O(nlogn), where n is the number of jobs. Our experiments verify the efficiency of these heuristics compared with classical heuristics in the literature and investigate the impacts of problem size and processing times.     

Simulation of image data processing by hybrid sampling

Hybrid sampling is used in both two dimensional transform and hybrid (transform-DPCM) processing of standard digitized images of the GIRL and MOONSCAPE. Maximum variance zonal and threshold samplings are compared with ratios of combination of the two (hybrid sampling), for different data compression ratios. A quantization and bit allocation scheme is also employed and bits per pixel and mean square error between the original and reconstructed images are used as performance criteria, to determine the effectiveness of hybrid sampling when compared to threshold and maximum variance zonal samplings. Optimal ratio in terms of bit rate, mean square error and image quality is sought.     

HFIM: a Spark-based hybrid frequent itemset mining algorithm for big data processing

Frequent itemset mining is one of the data mining techniques applied to discover frequent patterns, used in prediction, association rule mining, classification, etc. Apriori algorithm is an iterative algorithm, which is used to find frequent itemsets from transactional dataset. It scans complete dataset in each iteration to generate the large frequent itemsets of different cardinality, which seems better for small data but not feasible for big data. The MapReduce framework provides the distributed environment to run the Apriori on big transactional data. However, MapReduce is not suitable for iterative process and declines the performance. We introduce a novel algorithm named Hybrid Frequent Itemset Mining (HFIM), which utilizes the vertical layout of dataset to solve the problem of scanning the dataset in each iteration. Vertical dataset carries information to find support of each itemsets. Moreover, we also include some enhancements to reduce number of candidate itemsets. The proposed algorithm is implemented over Spark framework, which incorporates the concept of resilient distributed datasets and performs in-memory processing to optimize the execution time of operation. We compare the performance of HFIM with another Spark-based implementation of Apriori algorithm for various datasets. Experimental results show that the HFIM performs better in terms of execution time and space consumption.     

Unified-memory-based hybrid processing for partition-oriented subgraph matching on GPU

World Wide Web - Subgraph isomorphism is a well known NP-hard problem that is to find all the matched subgraphs of a query graph in a large target graph. The state-of-the-art GPU-based solution is...     

A hybrid scheduling approach for a two-stage flexible flow shop with batch processing machines

In this paper, we discuss a flexible flow shop scheduling problem with batch processing machines at each stage and with jobs that have unequal ready times. Scheduling problems of this type can be found in semiconductor wafer fabrication facilities (wafer fabs). We are interested in minimizing the total weighted tardiness of the jobs. We present a mixed integer programming formulation. The batch scheduling problem is NP-hard. Therefore, an iterative stage-based decomposition approach is proposed that is hybridized with neighborhood search techniques. The decomposition scheme provides internal due dates and ready times for the jobs on the first and second stage, respectively. Each of the resulting parallel machine batch scheduling problems is solved by variable neighborhood search in each iteration. Based on the schedules of the subproblems, the internal due dates and ready times are updated. We present the results of designed computational experiments that also consider the number of machines assigned to each stage as a design factor. It turns out that the proposed hybrid approach outperforms an iterative decomposition scheme where a fairly simple heuristic based on time window decomposition and the apparent tardiness cost dispatching rule is used to solve the subproblems. Recommendations for the design of the two stages with respect to the number of parallel machines on each stage are given.     

Multi-grid ion thruster lifetime simulation using hybrid parallel processing

The Journal of Supercomputing - An object-oriented PIC-DSMC numerical code using the C++ programing language was developed to predict the grid erosion and lifetime of the multi-grid and, in...     

Interactive smart battery storage for a PV and wind hybrid energy management control based on conservative power theory

This paper presents interactive smart battery-based storage (BBS) for wind generator (WG) and photovoltaic (PV) systems. The BBS is composed of an asymmetric cascaded H-bridge multilevel inverter (ACMI) with staircase modulation. The structure is parallel to the WG and PV systems, allowing the ACMI to have a reduction in power losses compared to the usual solution for storage connected at the DC-link of the converter for WG or PV systems. Moreover, the BBS is embedded with a decision algorithm running real-time energy costs, plus a battery state-of-charge manager and power quality capabilities, making the described system in this paper very interactive, smart and multifunctional. The paper describes how BBS interacts with the WG and PV and how its performance is improved. Experimental results are presented showing the efficacy of this BBS for renewable energy applications.     

Interactive 3D/2D visualization for geophysical data processing and interpretation

A new 3D/2D interactive display server was developed for the IGeoS geophysical data processing framework presented earlier. With introduction of this major component, the framework becomes conceptually complete and potentially bridges the gap between traditional processing and interpretation geophysical software.The display server utilizes Qt toolkit and OpenGL graphics libraries while taking advantage of the object-oriented design of the core data processing system. It operates by creating image object trees that are automatically propagated to the server(s) residing on the same or remote hosts and producing complex, structured, and interactive data displays. The displays support custom interactive graphical user interfaces, which are constructed entirely by the user and do not require computer coding. With over 200 specialized processing tools available, this approach allows creating 3D visualizations and building custom interactive data analysis, interpretation, and modeling tools in many areas of application. In particular, we show examples of integration of seismic ray tracing, gravity, and receiver function modeling and inversion in deep crustal studies.     

Interactive hybrid (symbolic-numeric) system approach to near optimal design of mechanical components

A hybrid symbolic-numeric system, referred to as OPTDEX, (Optimal Design Expert) for the optimal design of mechanical components and systems has been developed. The system is written in Golden Common LISP and IBM Professional (Ryan-McFarland) FORTRAN for execution on the IBM PC/AT microcomputer. Graphical output has been implemented using the Graphical Kernal System (GKS) standard. This microcomputer-based implementation makes the system particularly attractive as an easily accessible, low-cost engineering analysis and design tool.Experience with the system indicates that the time required to achieve, at least partially optimized engineering design solutions, is similar to that which may be expected with standard, nonoptimization-based microcomputer computation. Any added computational time may be justified and subsequently offset by increased long-term design efficacy.The OPTDEX protocol (Fig. 1) assumes a modular form, whereby each level can be modified, updated, and enhanced independently of the others to accommodate various design philosophies and the subdivision of large-scale design problems. A design cell approach has been adopted that has the capability of addressing the design of various mechanical components and systems. The current version of the OPTDEX design cell library, which is undergoing revision and expansion, includes speed reducer, bearing, coupling, and shaft design capabilities.This modular structure and generalized design cell approach, which underlies the OPTDEX system, establishes the basis of a formalized methodology for mechanical engineering design, which may be extended to include other design-related disciplines as well. For example, with the addition of appropriate design cells, the system can be configured for VLSI circuit design in electrical engineering, scheduling, and job routing in industrial engineering, and structural design in civil engineering.     

Interactive movie elements in a pervasive game

This paper presents our research initiatives around new user experiences in the area of pervasive mixed reality crossmedia gaming. In a prototypical game, The Epidemic Menace, we combined static and interactive story telling elements to create a mixed reality experience. As part of this research initiative we also investigated how elements of the real world and virtual worlds could produce a new environment where physical and digital objects can co-exist and interact with each other, we wanted to evaluate how linear stories could be integrated into a game flow and how they could be used to extend game experiences. A new form of interactive entertainment that is not limited to hardware based games or linear storylines but includes a truly interactive TV experience was one of our goals.     

Large-scale,high-resolution agricultural systems modeling using a hybrid approach combining grid computing and parallel processing

The solution of complex global challenges in the land system, such as food and energy security, requires information on the management of agricultural systems at a high spatial and temporal resolution over continental or global extents. However, computing capacity remains a barrier to large-scale, high-resolution agricultural modeling. To model wheat production, soil carbon, and nitrogen dynamics in Australia's cropping regions at a high resolution, we developed a hybrid computing approach combining parallel processing and grid computing. The hybrid approach distributes tasks across a heterogeneous grid computing pool and fully utilizes all the resources of computers within the pool. We simulated 325 management scenarios (nitrogen application rates and stubble management) at a daily time step over 122 years, for 12,707 climate–soil zones using the Windows-based Agricultural Production Systems SIMulator (APSIM). These simulations would have taken over 30 years on a single computer. Our hybrid high performance computing (HPC) approach completed the modeling within 10.5 days—a speed-up of over 1000 times—with most jobs finishing within the first few days. The approach utilizes existing idle organization-wide computing resources and eliminates the need to translate Windows-based models to other operating systems for implementation on computing clusters. There are however, numerous computing challenges that need to be addressed for the effective use of these techniques and there remain several potential areas for further performance improvement. The results demonstrate the effectiveness of the approach in making high-resolution modeling of agricultural systems possible over continental and global scales.