SR-Tree Packing

In multimedia databases, the spatial index structures based on trees (like R-tree, M-tree) have been proved to be efficient and scalable for low-dimensional data retrieval. However, if the data dimensionality is too high, the hierarchy of nested regions (represented by the tree nodes) becomes spatially indistinct. Hence, the query processing deteriorates to inefficient index traversal (in terms of random-access I/O costs) and in such case the tree-based indexes are less efficient than the sequential search. This is mainly due to repeated access to many nodes at the top levels of the tree. In this paper we propose a modified storage layout of tree-based indexes, such that nodes belonging to the same tree level are stored together. Such level-ordered storage allows to prefetch several top levels of the tree to the buffer pool by only a few or even a single contiguous I/O operation (i.e. one-seek read). The experimental results show that our approach can speedup the tree-based search significantly.

Spatial databases are optimized for the management of data stored based on their geometric space. Researchers through high degree scalability have proposed several spatial indexing structures towards this effect. Among these indexing structures is the X-tree. The existing X-trees and its variants are designed for dynamic environment, with the capability for handling insertions and deletions. Notwithstanding, the X-tree degrades on retrieval performance as dimensionality increases and brings about poor worst-case performance than sequential scan. We propose a new X-tree packing techniques for static spatial databases which performs better in space utilization through cautious packing. This new improved structure yields two basic advantage: It reduces the space overhead of the index and produces a better response time, because the aX-tree has a higher fan-out and so the tree always ends up shorter. New model for super-node construction and effective method for optimal packing using an improved str bulk-loading technique is proposed. The study reveals that proposed system performs better than many existing spatial indexing structures.

As a member of R-tree family, R*-tree is widely used in multimedia databases and spatial databases, in which NN (Nearest Neighbor) search is very popular. According to our investigations, (1) the degree of objects clustering in the leaf nodes is a very important factor on performance of NN search; (2) Normally, in R*-tree, its objects are not well-clustered in their leaf nodes. This paper proposes a new index structure, called Clustering-Based R*-tree (denoted CBR*-tree), for static databases by introducing clustering technology to R*-tree. Although some packing algorithms for R-trees have been proposed, all of them try to pack the same (or roughly same) number of objects in each leaf node, which often result in that the distribution of objects in leaf nodes can not reflect their actual distribution. The experimental results show that the CBR*-tree has better NN search performance than R*-tree and packed R-trees.

We propose the PATRICIA-hypercube-tree, or PH-tree, a multi-dimensional data storage and indexing structure. It is based on binary PATRICIA-tries combined with hypercubes for efficient data access. Space efficiency is achieved by combining prefix sharing with a space optimised implementation. This leads to storage space requirements that are comparable or below storage of the same data in non-index structures such as arrays of objects. The storage structure also serves as a multi-dimensional index on all dimensions of the stored data. This enables efficient access to stored data via point and range queries. We explain the concept of the PH-tree and demonstrate the performance of a sample implementation on various datasets and compare it to other spatial indices such as the kD-tree. The experiments show that for larger datasets beyond 10^7 entries, the PH-tree increasingly and consistently outperforms other structures in terms of space efficiency, query performance and update performance. For some highly skewed datasets, it even shows super-constant performance, becoming faster for larger datasets.

Keywords: Indexing; R* tree indexing; P+ tree indexing.

Academia Materials Science, 2024

Phase change materials (PCMs) are employed for the thermal energy storage owing to their high heat storage ability, narrow temperature difference between storage and retrieval of latent heat energy, and availability in a variety of phase change transition temperatures. Numerous research attempts have been made to develop a broad array of PCMs based on inorganic, organic and polymeric compounds for diverse area of applications. To improve the performance efficiency and proper handling of PCMs, they are often encapsulated or confined within a shape-stabilized supporting material of an inorganic or organic origin. This review emphasizes on the current research status of the polymer-based PCMs developed using the various PCMs-polymer combinations available, material characteristics, encapsulation, and shape-stabilization methods and provides detailed information on the contribution of polymers towards the enhancement of PCM end product properties, in the state of the art of thermal energy storage technology.

XXIV Settimana della Lingua Italiana nel Mondo

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2023

With the onset of the technological revolution, the efficiency of the current manual systems has been improved drastically and the accuracy of the products produced are also increasing. The most affected of the fields from this technological change is Education. The combination of Education with technology has been coined as a new term of edtech.

Internet Of Things

Kouka Ourania, 2023

The large–scale excavations at Liman Tepe under the direction of Hayat Erkanal exposed the most impressive harbour site in Western Anatolia that was continuously inhabited from the Neolithic to the end of the Bronze Age. In the successive architectural phases, changing patterns in settlement planning, communal buildings, house forms, the distribution of industrial activities, and local and imported prestige objects were observed from the Chalcolithic (Ch) to the Early Bronze Age (EBA), and particularly from the EBA I to the EBA II, when the settlement was transformed to a local urban center in the Izmir Region and encompassed a strongly fortified peninsula and an also fortified part that was extending in the fruitful plain of Urla. This paper will debate specific categories of material culture from the EBA I – II (early) settlement phases (VI.1d–1a and V.3b–3a; ca. 3000–2750 BC), and the symbolic value in their specific contexts. The debate will be based on a preliminary settlement and household analysis, and aims to detect symbols that may have acted on personal and/or communal level, and conveyed social, economic and political realities in the early 3rd mill. BC.