Prestasi Kaedah Penilaian Pertanyaan Dalam Pangkalan Data Teragih

Tesis ini membincangkan tentang kajian kaedah-kaedah penilaian pertanyaan yang dipilih di dalam pangkalan data teragih (PDT). PDT adalah gabungan dua konsep teknologi iaitu pangkalan data dan sistem rangkaian komunikasi. Pertanyaan (query) yang diberi kepada PDT adalah dalam bentuk ungkapan kalkulus yang akan diterima oleh pemproses pertanyaan (query processor) dan diterjemahkan melalui empat aras pemprosesan iaitu pemecahan pertanyaan, penempatan data, pengoptimuman pertanyaan dan pengoptimuman setempat. Empat kaedah penilaian pertanyaan yang dipilih di dalam kajian ini ialah Hill-Climbing, SDD-l, AHY dan Sistem R * . Setiap kaedah mempunyai penyelesaian tersendiri yang melibatka

An overview on audio steganography techniques

Steganography is a form of security technique through obscurity; the science and art of hiding the existence of a message between sender and intended recipient. Steganography has been used to hide secret messages in various types of files, including digital images, audio and video. The three most important parameters for audio steganography are imperceptibility, payload (bit rate or capacity), and robustness. Any technique which tries to improve the payload or robustness should preserve imperceptibility. The noise which is introduced due to bit modification would limit payload. This paper presents a categorization of information hiding techniques and overviews those techniques that intend to improve payload and imperceptibility

Relationship between ae signal strength and absolute energy in determining damage classification of concrete structures

The most efficient tools in real monitoring system is acoustic emission (AE). This technique can be used to identify the damage classifications in RC structure. This research paper will mainly focus on the utilization of signal strength and Absolute energy (AE signal) in determining on the damage quantification for RC beam subjected to cyclic load test. The beam specimens size (150 X 250 X 1900) mm were prepared in the laboratory and tested with the four point bending test using cyclic loading together with acoustic emission monitoring system. The results showed that the analysis of AE data parameters is capable of determining the damage classification in concrete structures and the data corresponded to the visual observations during the increased loading cycle

Race classification using gaussian-based weight K-nn algorithm for face recognition

One of the greatest challenges in facial recognition systems is to recognize faces around different race and illuminations. Chromaticity is an essential factor in facial recognition and shows the intensity of the color in a pixel, it can greatly vary depending on the lighting conditions. The race classification scheme proposed which is Gaussian based-weighted K-Nearest Neighbor classifier in this paper, has very sensitive to illumination intensity. The main idea is first to identify the minority class instances in the training data and then generalize them to Gaussian function as concept for the minority class. By using combination of K-NN algorithm with Gaussian formula for race classification. In this paper, image processing is divided into two phases. The first is preprocessing phase. There are three preprocessing comprises of auto contrast balance, noise reduction and auto-color balancing. The second phase is face processing which contains six steps; face detection, illumination normalization, feature extraction, skin segmentation, race classification and face recognition. There are two type of dataset are being used; first FERET dataset where images inside this dataset involve of illumination variations. The second is Caltech dataset which images side this dataset contains noises

Strength and Quality Assessment of Recycled Aggregate and Crumb Rubber Concrete Using the Ultra Pulse Velocity Method

This study focuses on the strength and quality of concrete incorporated with recycled aggregate and crumb rubber through the compressive strength test and the Ultra Pulse Velocity (UPV) test. RA was used to replace coarse aggregate while CR was used to replace fine aggregate in concrete production. A total of 36 specimens consisting of cubes (100 mm 100 mm 100 mm) with partial replacements of 50% RA and 0, 1, 2, 3, 4, and 5% CR were prepared, subjected to water curing for 7 and 28 days and tested in terms of compressive strength and quality using the compressive strength test and the UPV method. The UPV test and the compressive strength test were conducted at day 7 and day 28. The results show that the compressive strength of concrete decreased slightly with the increase of rubber content. Additionally, the quality of concrete slightly decreased as the percentage of rubber content increased. Finally, the optimum percentages for partial replacement of concrete suggested based on the results are 3% CR and 50% RA as this concrete mix achieved the highest velocity in the UPV test and the highest compressive strength compared to the control mix

A Stock Market Trading System Using Deep Neural Network

The stock market prediction is a lucrativefield of interest withpromising profit and covered with landmines for the unprecedented. The mar-kets are complex, non-linear and chaotic in nature which poses huge difficultiesto predict the prices accurately. In this paper, a stock trading system utilizingfeed-forward deep neural network (DNN) to forecast index price of Singaporestock market using the FTSE Straits Time Index (STI) in t days ahead is pro-posed and tested through market simulations on historical daily prices. There are40 input nodes of DNN which are the past 10 days’opening, closing, minimumand maximum prices and consist of 3 hidden layers with 10 neurons per layer.The training algorithm used is stochastic gradient descent with back-propagationand is accelerated with multi-core processing. A trading system is proposedwhich utilizes the DNN forecasting results with defined entry and exit rules toenter a trade. DNN performance is evaluated using RMSE and MAPE. Theoverall trading system shows promising results with a profit factor of 18.67,70.83% profitable trades and Sharpe ratio of 5.34 based on market simulation ontest data

Mazdak technique for PSNR estimation in audio steganography

A novel method to estimate PSNR of the resu lt of audio steganography before embedding is presented. Estimated PSNR by proposed linear interpolation formula was tested and the result was almost the same with the obtained PSNR in practical way

A Novel WLAN Client Puzzle against DoS Attack Based on Pattern Matching

Despite the popularity of 802.11 based networks, they suffer several types of DoS attack, launched by an attacker whose aim is to make an access point (AP) unavailable to legitimate users. One of the most common DoS attacks on 802.11 based networks is to deplete the resources of the AP. A serious situation like this can occur when the AP receives a burst of connection requests. This paper addresses this common DoS attack and proposes a lightweight puzzle, based on pattern-matching. Using a pattern-matching technique, this model adequately resists resource-depletion attacks in terms of both puzzle generation and solution verification. Using a sensible series of contextual comparisons, the outcomes were modelled by a simulator, and the security definition and proofs are verified, among other results