Many statistical and MOLAP applications use multidimensional arrays as the basic data structure to allow the efficient and convenient storage and retrieval of large volumes of business data for decision making. Allocation of data or data compression is a key performance factor for this purpose because performance strongly depends on the amount of storage required and availability of memory. Thi...

Although wireless sensor networks (WSNs) are powerful in monitoring physical events, the data collected from a WSN are almost always incomplete if the surveyed physical event spreads over a wide area. The reason for this incompleteness is twofold: i) insufficient network coverage and ii) data aggregation for energy saving. Whereas the existing recovery schemes only tackle the second aspect, we ...

As an interdisciplinary discipline, data mining (DM) is popular in education area especially when examining students’ learning performances. It focuses on analyzing educational related data to develop models for improving learners’ learning experiences and enhancing institutional effectiveness. Therefore, DM does help education institutions provide highquality education for its learners. Applyi...

In this paper we utilising some popular educational data mining (EDM) methods to explore and mine educational data resulted from a system that supports reflection for learning called Reflect. Our objective is to study whether using the Reflect helps students learn better in the subject. First, we explore data by means of statistical analyses. Then, we used clustering and classification techniqu...

The array aliasing mechanism provided in the Connection Machine Fortran (CMF) language and run{time system provides a unique way of identifying the memory address spaces local to processors within the global address space of distributed memory architectures, while staying in the data parallel programming paradigm. We show how the array aliasing feature can be used eeectively in optimizing commu...

Novel techniques for multi-bit oversampled data conversion are described. State-of-the-art oversampled data converters are analyzed, leading to the conclusion that their performance is limited mainly by low-resolution signal representation. To increase the resolution, high-performance, high-resolution internal D/A converters are required. Unit-element mismatch-shaping D/A converters are analyze...

Once the financial and operating data have been collected, and the results compiled, the next step in the performance evaluation process is calculation of the values of the performance indicators, and interpretation and reporting of the results. This section describes three ways to interpret the results of the proposed performance evaluation framework: 1) comparison of system results to norms o...

Recent times have seen an explosive growth in the availability of various kinds of data. It has resulted in an unprecedented opportunity to develop automated data-driven techniques of extracting useful knowledge. Data mining, an important step in this process of knowledge discovery, consists of methods that discover interesting, non-trivial, and useful patterns hidden in the data [SAD+93, CHY96...

A data warehouse is a large electronic repository of information that is generated and updated in a structured manner by an enterprise over time to aid business intelligence and to support decision making. Data stored in a data warehouse is non-volatile and time variant and is organized by subjects in a manner to support decision making (Inmon, Rudin, Buss, & Sousa, 1998). Data warehousing has ...

Current communications tools and libraries for high performance computing are designed for platforms and applications that exhibit relatively stable computational and communication characteristics. In contrast, the demands of (1) mixed environments in which high performance applications interact with multiple end users, visualizations, storage engines, and I/O engines { termed`distributed labor...