The Effective Design of Small Business's Website Interface With Regards To CRM Theories

E-Commerce is an ever growing area of business that shows no signs of slowing down. Everyday more and more people are buying products online. Searching for a product within an E-Commerce website is different than browsing the aisles of the local department store. Therefore this is an important area that marketers focus in order to discover the potential of World Wide Web to bring huge profits to the business. The success of e-commerce for any company is greatly dependent on the appropriate design of its Website. This study investigates the determinants of an effective Website. A literature survey indicated that the major categories of determinants are: page loading speed, business content, navigation efficiency, security, and marketing/customer focus. This project emphasizes on the effective interface design for e-commerce website in a broader perspective of Customer Relationship Management. Basically, these research papers focus on the design of interface which should be incorporated by small business industry particularly in Malaysia. A brief explanation on project overview and also problem statement is provided at the early chapter. A thorough literature review has been done on the interface subject where the author focus more on the design and user interface of the propose website. In addition, the author observes many Malaysian e-commerce websites interface design, analysts and come out with propose design. The targeted audience for this prototype is for all users no matter what type of gender, profession or age. Finally, based on the guidelines of designing good interface, the author develops a prototype website that incorporates the concept of e-loyalty with regards to customer relationship management (CRM) theories

An efficient mechanism for searching arabic audio libraries

In this paper we propose an approach that allows the user to query an Arabic audio library using voice. We use a combination of class-based language models and robust interpretation to recognize and identify the spoken keywords. The mechanism uses a Large Vocabulary Recognition System (LVCSR) to implement the functionality of an Arabic authority control system. A series of experiments were performed to assess the accuracy and the robustness of the proposed approach: restricted grammar recognition with semantic interpretation, class-based statistical language models (CB_SLM) with robust interpretation, and generalized CB-SLM. The results have shown that the combination of CB-SLM and robust interpretation provides better accuracy and robustness than the traditional grammar-based parsing. © 2004 IEEE

Identifying semantically similar arabic words using a large vocabulary speech recognition system

Users search digital libraries for book references using one or more attributes such as keywords, subject and author name. Some book titles might contain the keyword that the user specified and thus these titles will directly qualify as candidate results. On the other hand there are other titles that are relevant but do not contain the same exact search keyword. A user expects to retrieve all titles that are relevant to a specified keyword. Similarly when searching for an author name, the system should be able to retrieve the different forms of the name. The library science community developed a mechanism called authority control that allows the user to do a comprehensive search and retrieve all the records that are relevant to the query keyword. In this paper we propose an approach that allows the user to query an Arabic audio library using voice. We use a combination of class-based language models and robust interpretation to recognize and identify the spoken keywords. The mechanism uses a Large Vocabulary Recognition System (LVCSR) to implement the functionality of the authority control system. A series of experiments were performed to assess the accuracy and the robustness of the proposed approach: restricted grammar recognition with semantic interpretation, class-based statistical language models (CB_SLM) with robust interpretation, and generalized CB-SLM. The results have shown that the combination of CB-SLM and robust interpretation provides better accuracy and robustness than the traditional grammar-based parsing

Special track on E-business applications

The increasing popularity and advances in e-business environment are enabling the development of new classes of applications and the emergence of new trends in the design of online business systems

An indexing method for answering queries on moving objects

We consider the problem of indexing a set of objects moving in d-dimensional spaces along linear trajectories. A simple external-memory indexing scheme is proposed to efficiently answer general range queries. The following are examples of the queries that can be answered by the proposed method: report all moving objects that will (i) pass between two given points within a specified time interval; (ii) become within a given distance from some or all of a given set of other moving objects. Our scheme is based on mapping the objects to a dual space, where queries about moving objects are transformed into polyhedral queries concerning their speeds and initial locations. We then present a simple method for answering such polyhedral queries, based on partitioning the space into disjoint regions and using a B+-tree to index the points in each region. By appropriately selecting the boundaries of each region, we guarantee an average search time that matches a known lower bound for the problem. Specifically, for a fixed d, if the coordinates of a given set of N points are statistically independent, the proposed technique answers polyhedral queries, on the average, in O((N/B)1-1/d ·(log B N)1/d +K/B) I/O\u27s using O(N/B) space, where B is the block size, and K is the number of reported points. Our approach is novel in that, while it provides a theoretical upper bound on the average query time, it avoids the use of complicated data structures, making it an effective candidate for practical applications. The proposed index is also dynamic in the sense that it allows object insertion and deletion in an amortized update cost of log B (N) I/O\u27s. Experimental results are presented to show the superiority of the proposed index over other methods based on R-trees. © 2005 Springer Science + Business Media, Inc

An indexing method for answering queries on moving objects

We consider the problem of indexing a set of objects moving in d-dimensional spaces along linear trajectories. A simple external-memory indexing scheme is proposed to efficiently answer general range queries. The following are examples of the queries that can be answered by the proposed method: report all moving objects that will (i) pass between two given points within a specified time interval; (ii) become within a given distance from some or all of a given set of other moving objects. Our scheme is based on mapping the objects to a dual space, where queries about moving objects are transformed into polyhedral queries concerning their speeds and initial locations. We then present a simple method for answering such polyhedral queries, based on partitioning the space into disjoint regions and using a B+-tree to index the points in each region. By appropriately selecting the boundaries of each region, we guarantee an average search time that matches a known lower bound for the problem. Specifically, for a fixed d, if the coordinates of a given set of N points are statistically independent, the proposed technique answers polyhedral queries, on the average, in O((N/B)1-1/d ·(log B N)1/d +K/B) I/O\u27s using O(N/B) space, where B is the block size, and K is the number of reported points. Our approach is novel in that, while it provides a theoretical upper bound on the average query time, it avoids the use of complicated data structures, making it an effective candidate for practical applications. The proposed index is also dynamic in the sense that it allows object insertion and deletion in an amortized update cost of log B (N) I/O\u27s. Experimental results are presented to show the superiority of the proposed index over other methods based on R-trees. © 2005 Springer Science + Business Media, Inc

High Performance Spatial Indexing for Parallel I/O and Centralized Architectures

Recently, spatial databases have attracted increasing interest in the database field. Because of the volume of the data with which they deal with, the performance of spatial database systems' is important. The R-tree is an efficient spatial access method. It is a generalization of the B-tree in multidimensional space. This thesis investigates how to improve the performance of R-trees. We consider both parallel I/O and centralized architectures. For a parallel I/O environment we propose an R-tree design for a server with one CPU and multiple disks. On this architecture, the nodes of the R-tree are distributed between the different disks with cross-disk pointers ( 'Multiplezed R-tree a). When a new node is created we have to decide on which disk it will be stored. We propose and examine several criteria for choosing a disk for a new node. The most successful one, termed 'Prozimity Indew' or PI, estimates the similarity of the new node to other R-tree nodes already on a disk and chooses the disk with the least degree of similarity. For a centralized environment, we propose a new packing technique for R-trees for static databases. We use space-filling curves, and specifically the Hilbert curve, to achieve better ordering of rectangles and eventually to achieve better packing. For dynamic databases we introduce the filbert R-tree, in which every node has a well defined set of sibling nodes; we can thus use the concept of local rotation [47]. By adjusting the split policy, the Filbert R-tree can achieve a degree of space utilization as high as is desired. (Also cross-referenced as UMIACS-TR-94-131

Throughput, Spectral, and Energy Efficiency of 5G Massive MIMO Applications Using Different Linear Precoding Schemes

— A promising massive multiple input multiple output (M-MIMO) system is required to meet the growing need for highly traffic data, highly-resolution of streaming video, and intelligent communication on the fifth-generation wireless networks (5G). M-MIMO systems are essential for the optimization of the trade between energy efficiency (EE), throughput (R), and spectral _efficiency (SE) in wireless 5G networks. M-MIMO system architecture is proposed in this paper to enhance the trade-off between energy efficiency and uplink and downlink throughput at the optimum EE. Furthermore, using linear precoding techniques such as M MMSE, RZF, ZF, and MR, the EE-SE trade-off is optimized for uplink and downlink (M-MIMO) systems. The analysis of simulation results proved that throughput (R) is enhanced by increasing the number of antennas at optimum EE. After that, the proposed trading scheme is optimized and improved using M_MMSE compared to RZF, ZF. Finally, the results prove that M_MMSE gives the optimum trade-off between EE and R at the proved optimum ratio between the number of active antennas and the number of active users UE