Preventing Cyber Attacks using Artificial Intelligence
Exploring Advantages and Challenges of Chatbot Integration in Human-Robot Interaction
Counterfeit Currency Detection using Machine Learning
Artificial Intelligence use in Lung Cancer Screening to Improve Patient Recovery
An Analysis of Various Crypto Coins and their Suitability for Real-Time Applications
Design and Evaluation of Parallel Processing Techniques for 3D Liver Segmentation and Volume Rendering
Ensuring Software Quality in Engineering Environments
New 3D Face Matching Technique for an Automatic 3D Model Based Face Recognition System
Algorithmic Cost Modeling: Statistical Software Engineering Approach
Prevention of DDoS and SQL Injection Attack By Prepared Statement and IP Blocking
The aim of this research is to develop an intelligent service system to receive, manage, and serve text messages sent by system users asking for files stored in a system database. The proposed system needs to understand the received text message and takes the decision about the required files. The system handles files and a corresponding computer program and a corresponding computer-readable storage, which can be used for handling e-mail attachments and sent the requested files to the user email. To improve the designed text message recognition system, the combination of two methods have been used, a supervised learning multilayer neural networks trained with back propagation and Soundex algorithms. Experimental results show that the combination of two classification techniques to recognize and manipulate the received text message improves the classification accuracy.
Multi-computer systems (MCSs) are efficient in solving computing-intensive problems. A MCS consists of a number of processing elements (PEs) and an interconnection network (IN). A fault in any PE and/or the IN can lead to losses in sensitive data and/or the overall throughput. In this paper, we provide a review of the fault tolerance and reliability assessing techniques of mesh MCSs. A number of fault-tolerant routing techniques are analyzed including the dimension ordering, the turn model, and the block-fault model. In reliability analysis, we consider the sub-mesh reliability exact and approximate models and the task-based reliability computation. It is expected that some of the techniques and algorithms covered in this paper can have applications in the domain of wireless mesh networks.
ECG is a very important tool for the primary diagnosis of heart disease; it gives a full picture about the electrophysiology of the heart and the ischemic changes that may occur like the myocardial infarction, conduction defects and arrhythmia. For this reason ECG signal must be clearly represented and filtered to remove all noise and artifacts from the signal. ECG is one of the biosignal that is considered a non-stationary signal and needs a hard work in denoising. In this paper a new approach of denoising of EGG signal is proposed in using Wavelet Transform WT. Different ECG signals are used to evaluate the method using MATLAB’ software. The presented method showed better results than conventional methods particularly in ECG signal case.
In this paper a retrieval study for natural image learning environment is proposed. The content of this paper is a result of projects called Image content-based retrieval on a natural image database. The objective of this project is to develop an image content-based search engine, which can perform identity check of a natural image. It is well known that conventional natural image databases can only be retrieved by text-based query. In this paper we use the shape, color, and other features extracted from a captured natural image to search the natural image database. The developed technique is able to perform scale, translation, and rotation invariant matching between natural images. Currently, the database contains several hundreds of natural images. In future, we shall enhance the capability of the search engine to deal with more than 30,000 natural image species, which is the total amount of natural image species along the coast.
As the dimension of interconnects in Integrated circuits has become dominant, the inductive effects of the wires cannot be ignored anymore. At high frequency, the return current distributes itself close to the signal path and any increase in the inductance of the return path hampers signal integrity. The multi-layered power distribution network (PDN) is stressed when many devices draw current simultaneously, creating noise in the supply rails. This high speed current not only causes ground bounce and power supply sag but it also needs a low inductance return path. Since high frequency involved in contemporary signaling makes the interconnects to behave as lossy transmission lines, the chip may sustain less noise margin due to environmental or process variations. If the inductive effort is considered, the design will be more robust and variability-free, thus improving the defect tolerance. In this paper, a SPICE based analysis of “on-board” high speed return current path is conducted and techniques and results are then extended for “on-chip” return current path analysis. In addition to avoiding operational failures, a priori knowledge of signal and its respective return path would greatly help to simplify interconnect designing and routing.
In the recent past, the development of computer aided diagnosis systems has been prepared to assisting the physicians for better decision making. This has motivated the research in creating vast amount of image database in the hospitals and health care centers. It has been reported that the brain tumor is one of the major causes leading to higher incidence of death in human. Physicians face challenging task in extracting the features and decision making form. The computerized tomography (CT), which is found to be the most reliable method for early detection of tumors. Due to the high volume of CT images to be used by the physicians, the accuracy of decision making tends to decrease. This has further increased the demand to improve the automatic digital reading for decision making. This paper proposes the tumor detection in brain images. The authors investigate the use of different data mining techniques namely, neural network and association rule mining for anomaly detection and classification. The method proposed makes use of association rule mining technique to classify the CT scan brain images into three categories namely normal, benign and malignant. It combines the low-level features extracted from images and high level knowledge from specialists. The developed algorithm can assist the physicians for efficient classification with multiple keywords per image to improve the accuracy. The results show that the classification accuracy has been obtained as 75% for the classifier using association rule and 70% for neural network classifier, making it a suitable scheme for image mining applications.
Analog-to-digital converters (ADCs) have been an essential part of many systems employed in mission critical applications. Their fault tolerance has been an increasingly important issue. The notion of fault tolerance includes fault detection (or testing). Automatic test equipment (ATE) has been extensively used to perform sophisticated testing of ADCs. However, ATE can not be utilized in the field due to extremely high cost. In addition, the bandwidth of the ATE is normally lower than the bandwidth of the ADC being tested, which makes it difficult to accomplish at-speed testing requirements. It is important, therefore, to embed test hardware into ADC itself. The methods employed at ATE are complex and inconvenient for built-in realization. More advantageous are the methods exploiting accumulation of output responses. The size of the accumulator depends on the number of responses. In order to achieve greater fault coverage, this number is kept large, complicating the implementation. On the other hand, signature analysis used in digital systems testing is well suited for compaction of “lengthy” responses, and it is characterized by small hardware overhead and low aliasing probability. In this work, we apply a signature analysis principle for the compaction of output responses of an ADC. The permissible tolerance bounds for a fault-free ADC are determined, and the aliasing rate is estimated. Examples are given.
Wireless etworks ecome more widely used to support advanced services. A researcher has been interested in having Internet connectivity in space for quite some time. This would allow scientists with direct Internet access to data and devices on the satellites. The rotation of Low Earth Orbiting (LEO) satellites around the Earth result in handover of satellites between ground stations. Two types of handover can be observed in space: Link layer and Network layer. Researchers have been developing a Seamless IP diversity-based Generalized Mobility Architecture (SIGMA) to ensure smooth handovers of end to end connections between nodes on Earth and satellites. In this paper, we provide a survey of the various types of handovers in the space environment, followed by simulation results of SIGMA handover performance in a space environment.
The word steganography comes from the Greek Steganos, which mean covered or secret and graphy mean writing or drawing. There are many techniques in steganography such as least significant bit insertion (LSB), masking and filtering, and transformation techniques. The LSB technique is common, which randomly select the pixels of the cover-object that is used to hide the secret message. It is possible to combine the techniques by encrypting message using cryptography and then hides the encrypted message using steganography. The resulting stego-image can be transmitted without revealing that secret information is being exchanged. Furthermore, even if an attacker were to defeat the steganographic technique and detect the message from the stego-object, he would still require the cryptographic decoding key to decipher the encrypted message. In this paper we proposed the image restoration technique in Stenography. In this paper we blur image before hiding the message image using special Point Spread Function and randomly generated key. We have used two input key values as parameters of PSP. At the time of blurring the image, the different new third key value is generated for different message images. These keys are used at the time of the deblurring of the message image which are kept secrete. For recovering the real message image we need to get image from stego image and then restore it. It is very difficult to restore message image without knowing PSF and third key value. We found, this technique is less time consuming, simple and robust.
