Ophthalmology is an important branch of biomedical field which needs computer-aided automated techniques for pathology identification in human eye. The focus of this work is on the procedure of automatedtechnique used in the identification of retinal sickness in diabetic retinopathy. DR is a common visional sickness and main cause of vision loss. Diabetic macular edema (DME) is a problem of DR. DME arises from swelling of the
An effective computer aided technique was presented based on the merits of Haar Wavelet Transform, k- means clustering, ‘Bag of Words’ and SIFT for feature extraction and classification using the back propagation neural network. The contributed scheme is proving to be improvised in classification since it uses ‘Bag of Words’ for efficient feature extraction and classification. The proposed scheme has the potential of preprocessing and resizing the fracture and non- fracture bone x- ray images for effective dissemination. The experiments are conducted using 300 X-ray images collected from the Sona Scans Private Limited, Puducherry. The experimental results of the proposed computer aided technique are proven to be better than the detection technique facilitated with the traditional SIFT technique.
One of the fast and easy ways to access updated academic and research resources around the world is through Internet which along with its advantages, it has its own disadvantages as well. Including its disadvantages we can point out to easier stealing the scientific researchers’ literatures by jobber people and this technique is also a growing challenge in the virtual world. Plagiarism means re-use of the ideas, results and/or the words of another person who has presented them for the first time without explicitly mentioning the references and authors [1,2]. "Textual" Plagiarism is one of the most common types of plagiarisms which mostly take place in universities and official organizations and today with the increasing amount of information they are detectable using automated and sophisticated methods.  In a general categorization, language text plagiarism detection is categorized into two categories: the first category is monolingual and/or homogenous English in comparison
In  the authors used AMNESIA technique to secure vulnerable statement by combining static analysis with statement generation and runtime monitoring. They used static analysis of Java programs to compute a finite-state machine model that captures the lexical structure of SQL queries issued by a program. They analyzed the vulnerable SQL statement, then generate a general acceptable SQL statement model, and allow or deny each statement based on how it compares to the model at runtime. In the study they conducted, they used five real world Web applications and applied AMNESIA to each of the applications. SQL injection attacks cause SQL queries issued by the program to deviate from this model and were detected. Although the technique is effective because it detects injection attacks and it avoids runtime taint-tracking, it suffers some drawbacks. Their solution uses exceptions to indicate potential attacks which could cause overhead on the part of the developers. Also, the conservative nature of its static analysis and its inability to distinguish different courses of inputs can lead to a higher rate of false positives. In , the authors proposed SQLGuard technique for detecting injection attacks. They use SQLGuard to secure vulnerable SQL statements by comparing the parse tree of an SQL statement before and after user input and only allow SQL statements to execute if the parse trees match. In their study, they used one real-world Web application for each application. They technique was able to stop all the SQLIAs after testing it and it generated no false positives. However, their technique had some overheads. First, the developer must rewrite all the SQL codes to use their custom libraries. This is quite a difficult time, consuming and costly task on the part of the application developers. There is also the problem of computational overhead due to dynamic statement validation by removing vulnerability and allowing all inputs.Therefore, SQLGuard is not flexible enough, because the source code of the
the plaque regions and obtained a high accuracy of 100% to differentiate Sym and Asym cases based on early changes in the FWR. The key points of our study can be summarized as follows: (1) by using a reduced feature set (seven features) we could obtain high classification performance; (2) the technique is suitable to be tested in a clinical environment, because the clinician simply has to feed the ultrasound image to get the classification (the entire process of segmentation and classification requires less than 20 minutes); (3) the high classification performance indicates that this system could be further explored as a possible adjunct diagnostic system; (4) the system is totally user independent and, thus, it doesn't introduce inter-operator variability into the classification results.
246 Figure 13(b). Acetabular and patient’s information
To test the accuracy and utility of the acetabular implant size recognition technique, an experiment was conducted with assistance from a surgeon for the observational (manual) method to determine the acetabular implant size. The results by the observational approach were compared to the results produced by our automatedtechnique. The testing recorded the acetabular implant size to be used and the time taken by both methods. Ten randomly selected X-rays of unidentified patients were used for templating for both techniques. The difference between the two sizes were calculated and shown in table 2.
body. Brain tumours need to be controlled and treated. Detecting brain tumors can be a challenging and especially in its early stages. Detecting tumours non-invasively from medical images is a good option for early detections. There are several hurdles in processing medical images for tumour detection. This paper proposes a novel technique that classifies and predicts tumours in the brain called AHCP. It is an automatedtechnique with an accuracy of 95% in tumour detection.
E-mail: firstname.lastname@example.org;email@example.com;firstname.lastname@example.org Abstract— Modern technologies have reached our
garage to secure the cars and entrance to the residences for the demand of high security and automated infrastructure. The concept of intelligent secure garage systems in modern transport management system is a remarkable example of the computer interfaced controlling devices. License Plate Recognition (LPR) process is one of the key elements of modern intelligent garage security setups. This paper presents a design of an automated secure garage system featuring LPR process. A study of templates matching approach by using Optical Character Recognition (OCR) is implemented to carry out the LPR method. We also developed a prototype design of the secured garage system to verify the application for local use. The system allows only a predefined enlisted cars or vehicles to enter the garage while blocking the others along with a central-alarm feature. Moreover, the system maintains an update database of the cars that has left and entered into the garage within a particular duration. The vehicle is distinguished by the system mainly based on their registration number in the license plates. The tactics are tried on several samples of license plate’s image in both indoor and outdoor setting.
A technique for the semi-automated tracing of ice margins in remotely sensed images is an essential facility required to support research being undertaken by the Antarctic Climate and Ecosystems CRC to determine the current mass-balance of the Antarctic ice sheet. The work described here has shown that an active-contour based approach has the potential to be a useful technique for enabling semi-automated ice margin tracing to be carried out (M.Moffew, private communication, 2001). The contour-based approach is particularly suitable for tracing the long, and sometimes broken, edges which represent ice margins in remotely sensed images because, unlike more locally-based line tracing techniques, it maintains the connectivity of the line at all times. This research has confirmed that an active- contour approach, which takes a user-specified initial contour, positioned in the vicinity of an ice margin, and then refines it via a deformation process until it precisely defines the margin, is an effective approach for this application.
HIP authentication is one of the most recent technical mechanisms in combating malicious automated script. It is a security measure which uses computer programs that automatically generate and grade puzzles that most people can solve without difficulty, but that current programs cannot. The literature review has served to bring to light other varieties of forms of CAPTCHA that users are not familiar with. The point is not to support the reader with deep knowledge of the various forms of HIP authentication: Implicit CAPTCHA, Quiz CAPTCHA, Spatial CAPTCHA, Speech CAPTCHA, BONGO HIP, Gimpy CAPTCHA and Sound-based CAPTCHA but rather to show how these HIP authentication are surprisingly alike in conception. They all function and mainly make use of the same techniques. In this review, various forms of HIPs authentications have been reviewed and it has become clear that the inner workings of these systems are overall significantly and is geared at combating malicious automated scripts. Evaluating HIPs has been one of most interesting aspects of the research, and users’ views and observations have been made very clear. The use of HIPs have become an increasingly essential part of most web sites such as Yahoo!, many free email service providers, web blog, financial institutions and banks, along with many other organizations, are being forced to employ the HIPs techniques as a result of the enormous activities of bots. These have helped in reducing cyber crimes, stopping spam posts and automated
II. LITERATURE SURVEY
Automated online blood bank database:
A number of online blood bank databases are available, however none of them offer the capability for a direct contact between the donor and recipient. This is a major drawback particularly in cases where there is an urgent need of blood. Our project aims to overcome this communication barrier by providing a direct call routing technique using Asterisk hardware. A blood bank database is created by collection of details from various sources like Blood banks, NSS, NGO's, hospitals and through web interface. The data collected will be maintained in a central server. This central server will be associated with a Toll free number that can be used to connect to it. The willingness of donor and the closeness of the donor to the place from where the call is coming are also accounted for in defining this algorithm. Based on the algorithm the most eligible donor is found out. From the server the call from the required person is routed to the eligible donor's number. Such a system considerably cuts down on the overheads involved in referring to an online database and then calling the donors and verifying their willingness at a time when there is a critical need for the blood.
In this chapter air-coupled ultrasonic techniques are demonstrated on concrete, aluminum, steel plate, and LDPE plate. The goal of these experiments is to perform the inspection in a non-contact manner on various materials. Given the state of current technology, there are various air-coupled ultrasonic transducers, but they only work well with non-metallic materials or thin metal plates using a through-transmission technique because of the high impedance mismatch between air and metal. Three different experimental concepts are demonstrated: 1) line-source air-coupled ultrasonic array sensors in through-transmission mode, 2) point-source air-coupled ultrasonic generation using a Rayleigh wave, and 3) laser array detector on steel plate. The result of this research will contribute to the field of non-contact railway axle inspection and ultrasonic NDT.
As technology is starting to conquer every strata of the society, the war for protecting confidential data from being intercepted is growing intense by the hour. Biometric- security stands out as the most secure form of authentication in high security zones such as defense, space missions and research head-quarters. Today, forms of password-protection range from face- recognition to retina -scan. Here, we develop a system for recognizing and converting lip movement of an individual into a recognized pattern which is set as a password for the system using image-processing. This system is also a break-through for providing people with motor-disabilities a robust and easy way of protecting their data. By capturing and tracing the successive movement of lips during speech, the corresponding word can be detected. The captured images are represented as points on a two-dimensional flat manifold that enables us to efficiently define the pronunciation of each word and thereby analyze or synthesize the motion of the lips. The motion of lips helps us track the word syllable-by-syllable. With multiple levels of image processing, it becomes possible to set the matching parameters to a very close value, hence not allowing any brute- force or other infamous hacking techniques to break into the user’s system. This lip reading technique also serves applications in areas where communication via direct speech is not possible.
In this paper, we described a novel dual-contour propaga- tion technique for measuring volume-time curves (VTCs), validated it against manually drawn contours, and dem- onstrated its utility in a clinically-relevant patient popula- tion. This method requires nothing more than standard short-axis and long-axis CMR acquisitions and routinely drawn ED and ES contours. We show that the dual-prop- agated contours can be used to accurately measure peak ejection and filling rates compared to the reference stand- ard of manually-drawn contours. The dual-contour prop- agation technique provides a fast, practical means of measuring volume-based indices of systolic and diastolic ventricular function from routine clinical CMR.
For noncomplex geometry, image processing based tool-path generation has the potential to simulate and visualize machining tool operations. Processing STL file format is selected due to its simplicity and reliability to generate and parse tool path coordinate points. Two different manufacturing processes, such as milling and turning operations, are considered to develop the concept of automated tool-path generation using multilevel processing. In general, parametric model segmentation, point cloud generations from the segmented and sliced model, binary logic container creation, 2D projection, and transformation of the 2D projected model into the binary image are the main procedures we applied. In the meantime, production process variables and parameters are formulated and abstracted into the main algorithm to generate a machine-readable language like G- code. The result showed, the accuracy of the path is affected by segmentation and 3D to 2D conversion processes. The grid container which has a logic to discriminate a part of an object which is enclosed inside the object depends on sample size. The higher the sample, the better the result, but the slower the process. This research will benefit both academia and smaller companies to realize a more reliable and smaller depth-of-cut. In future work, higher-order motion generation techniques should be investigated for jerk and undesired vibrations during the cutting process.
The segmentation framework in this paper is implemented in MATLAB version 7.0. GMM based automatic contour initialization technique works well on short axis view of mid slice image at its end diastolic phase. But when applied to apical slice the proposed method could not initialize the contour near the object of interest. To overcome this limitation, the probability map of the blood pool of every slice is masked by the LV and RV binary model from the previous segmented slice. This eliminates the unwanted regions that do not belong to the blood class. Fig 6.a. shows that Li’s method  based on the adaptive propagation term leaks through the weak boundary, and Fig. 6.b. shows the successful segmentation of myocardium using the proposed image based speed term. Also we compare effectiveness of the enhanced edge indicator function used in this paper. Fig. 7.a shows the myocardium segmentation with the conventional edge indicator combined with the stopping force d s
C onventional MR imaging spine examinations lack stan- dardization and are technologist-dependent. They are costly and time-consuming, often requiring 1–2 hours to im- age the entire spine fully. Additionally, spinal anatomic vari- ance and limited coverage in MR imaging studies cause diffi- culties in definitive numbering of vertebrae and disks, resulting in an increased risk of performing spinal interven- tion at an incorrect level. 1 MR imaging quality is also reduced in patients with back pain or spasms who cannot remain mo- tionless during image acquisition. To address these concerns, Weiss et al 2 developed the automated spine survey iterative
Social media platforms, thanks to their inherent nature of quick and far-reaching dissemination of information, have gradually supplanted the conventional media and become the new loci of political communication. These platforms not only ease and expedite communication among crowds, but also provide researchers huge and easily accessible information. This huge information pool, if it is processed with a systematic analysis, can be a fruitful data source for researchers. Systematic analysis of data from social media, however, poses various challenges for political analysis. Significant advances in automated textual analysis have tried to address such challenges of social media data. This paper introduces one such novel technique to assist researchers doing textual analysis on Twitter. More specifically, we develop a clustering methodology based on Longest Common Subsequence Similarity Metric, which automatically groups tweets with similar content. To illustrate the usefulness of this technique, we present some of our findings from a project we conducted on Turkish sentiments on Twitter towards Syrian refugees.
Abstract - The primary objective of this current paper is to design, develop and automate an approach called the Hypsometrical Approach (HA). This approach automated and developed as a decision support system using environmental indicators for managing and planning water resources. It servers to analyze and to make comparison of various current and future scenarios of different quantifiable indicators for any consideration and for various socio-economic aspects. It is also used as a decision tool to improve or at least to preserve environment and natural resources. HA needs to draw its data from different sources like satellite images and watershed information system such as watershed characteristics including equipment infrastructures (Drinking water supply, irrigation system), transportation infrastructures (Roads, dams), natural resources (Water, soils, and vegetation), human activities (Agriculture, urbanization and industry) and different socio-economic factors (Demography). Globally in this paper the automation of this Hypsometrical Approach is divided into two main parts, the first part based on identifying and extracting data pixel by pixel from classified satellite images using python programming language, and the second part related to the development of a system allowing users to generate and visualize different curves called hypsometrical curves developed using Java programming language. We can combine any hypsometrical curve with arithmetic operations (addition, multiplication, subtraction and division) in order to assess some other indicators such as water resources, watershed storage capacities, vegetation, soils and forest potentials curves. Briefly, the objective of automating hypsometrical approach is to make efficient decision to improve the socio-economic level and enhance sustainable development.