Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship and meanings of words in the document. As a result the sparsity and semantic problem that is prevalent in textual document are not resolved. In this study, the problem of sparsity and semantic is reduced by proposing a graph based text representation method, namely dependency graph with the aim of improving the accuracy of document clustering. The dependency graph representation scheme is created through an accumulation of syntactic and semantic analysis. A sample of 20 news groups, dataset was used in this study. The text documents undergo pre-processing and syntactic parsing in order to identify the sentence structure. Then the semantic of words are modeled using dependency graph. The produced dependency graph is then used in the process of cluster analysis. K-means clustering technique was used in this study. The dependency graph based clustering result were compared with the popular text representation method, i.e. TFIDF and Ontology based text representation. The result shows that the dependency graph outperforms both TFIDF and Ontology based text representation. The findings proved that the proposed text representation method leads to more accurate document clustering results.
Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreThe study of the validity and probability of failure in solids and structures is highly considered as one of the most incredibly-highlighted study fields in many science and engineering applications, the design analysts must therefore seek to investigate the points where the failing strains may be occurred, the probabilities of which these strains can cause the existing cracks to propagate through the fractured medium considered, and thereafter the solutions by which the analysts can adopt the approachable techniques to reduce/arrest these propagating cracks.In the present study a theoretical investigation upon simply-supported thin plates having surface cracks within their structure is to be accomplished, and the applied impact load to the
... Show More3D‐printed scaffolds loaded with healing directed agents could be employed for better treatment outcome in regenerative dentistry. The aim of this study was to fabricate and characterize simple 3D‐printed poly lactic acid (PLA) scaffolds coated with nanoHydroxyapatite (nHA), Naringin (NAR), or their combination, and testing their morphological, chemical, mechanical, antibacterial, biocompatible and bioactive properties. Methodology: Two variants pore sizes, 300 and 700 μm, of 3D‐printed PLA disc scaffolds measuring (10 × 1 mm) were fabricated. These scaffolds were dip‐coated with nHA, NAR, or both (nHA/NAR). Field emission scanning electron microscopy (FeSEM), energy‐dispersive X‐ray spectroscopy (EDX), Fourier transfo
... Show MoreThe problem of research was to identify after the use of cost technology based on specifications in the validity of determining and measuring the costs of the implementation of contracting, by applying to al-Mansour General Construction Contracting Company as an appropriate alternative to the traditional costing system currently adopted, which is characterized by many shortcomings and weaknesses Which has been reflected in the validity and integrity of the calculations. To solve this problem, the research was based on the premise that: (The application of cost technology based on specifications will result in calculating the cost of the product according to the specification required by the customer, to meet his wishes properly and witho
... Show MoreRecently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse
... Show MoreA Multiple System Biometric System Based on ECG Data
In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform
A series of liquid crystals comprising a heterocyclics dihydro pyrrole and 1,2,3-triazole rings [VII]-[X] were synthesized by many steps starting from a reaction of 3,3'-dimethyl-[1,1'-biphenyl]- 4,4'-diamine with chloroacetyl chloride in a mixture of solutions DMF and TEA to synthesise the compounds [I], then the compounds [I] reacted with malononitrile in 1,4-dioxane and TEA solutions to produce compounds [II], then the first step is repeated with compound [II] where it reacted with chloroacetyl chloride in mixture of DMF and TEA to give compound [III], this compound reacted with sodium azide in the presence of sodium chloride and DMF as solvent to produce the compound [IV], which reacted with acrylic acid by a 1.3 dipolar reaction in sol
... Show MoreWireless channels are typically much more noisy than wired links and subjected to fading due to multipath propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.
In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at
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