E-system for education company

E-System for Education Company (EEC) is an online based management system for the purpose of making management much more systematic,secure and efficient.There are three main users which are staff,admin and customer which are parents by Tan Educations.The system has total six modules which are login and registration,lessons module,staff management, student management,courses and classes management and billing management.The problem statement of this system which is the current system which are only filing system that able to record the students,payment,records by handwriting and there is no well documented data in the current system for managing student and staff information and the records are incomplete.The objectives of this system are to develop a computerized and systematic online education based company,and to store the kindergarten information in database for effective management of the data.Existing systems in the market that is similar with E-System for Education Company, programming languages and tools used are compared.Rapid Application Development (RAD) has been implemented to develop this system.There are four phases which are requirements planning,user design, construction and cutover

Predicting The Malaysian Gross Domestic Product Using Sliding Window Technique

In Malaysia, the quarterly economic growth is announced two months after the end of every quarter. Market players, who need to know the future behaviour of economic growth before making important business decisions, would therefore need to forecast the growth rather than waiting for the announcements all the time. However, conventional forecasting methods have flaws as the margin of error is not within the acceptable error margin. This study aims to discover patterns of the Malaysian GDP growth using sliding window technique. Discovered patterns were tested and the forecasting results are promising

A conformance test framework for the DeviceNet fieldbus

The DeviceNet fieldbus technology is introduced and discussed. DeviceNet is an open standard fieldbus which uses the proven Controller Area Network technology. As an open standard fieldbus, the device conformance is extremely important to ensure smooth operation. The error management in DeviceNet protocol is highlighted and an error injection technique is devised to test the implementation under test for the correct error-recovery conformance. The designed Error Frame Generator prototype allows the error management and recovery of DeviceNet implementations to be conformance tested. The Error Frame Generator can also be used in other Controller Area Network based protocols. In addition, an automated Conformance Test Engine framework has been defined for realising the conformance testing of DeviceNet implementations. Automated conformance test is used to achieve consistent and reliable test results, apart from the benefits in time and personnel savings. This involves the investigations and feasibility studies in adapting the ISO 9646 conformance test standards for use in DeviceNet fieldbus. The Unique Input/Output sequences method is used for the generation of DeviceNet conformance tests. The Unique Input/Output method does not require a fully specified protocol specification and gives shorter test sequences, since only specific state information is needed. As conformance testing addresses only the protocol verification, it is foreseen that formal method validation of the DeviceNet protocol must be performed at some stage to validate the DeviceNet specification

Evaluation of the cytotoxic effects of ophthalmic solutions containing benzalkonium chloride on corneal epithelium using an organotypic 3-D model

<p>Abstract</p> <p>Background</p> <p>Benzalkonium chloride (BAC) is a common preservative used in ophthalmic solutions. The aim of this study was to compare the cytotoxic effects of BAC-containing ophthalmic solutions with a BAC-free ophthalmic solution using an organotypic 3-dimensional (3-D) corneal epithelial model and to determine the effects of latanoprost ophthalmic solution and its BAC-containing vehicle on corneal thickness in a monkey model.</p> <p>Methods</p> <p>The cytotoxicity of commercially available BAC-containing ophthalmic formulations of latanoprost (0.02% BAC) and olopatadine (0.01% BAC) was compared to that of BAC-free travoprost and saline in a corneal organotypic 3-D model using incubation times of 10 and 25 minutes. To compare the extent of differentiation of 3-D corneal cultures to monolayer transformed human corneal epithelial (HCE-T) cell cultures, expression levels (mRNA and protein) of the corneal markers epidermal growth factor receptor, transglutaminase 1 and involucrin were quantified. Finally, latanoprost ophthalmic solution or its vehicle was administered at suprapharmacologic doses (two 30 μL drops twice daily in 1 eye for 1 year) in monkey eyes, and corneal pachymetry was performed at baseline and at weeks 4, 13, 26 and 52.</p> <p>Results</p> <p>In the 3-D corneal epithelial culture assays, there were no significant differences in cytotoxicity between the BAC-containing latanoprost and olopatadine ophthalmic solutions and BAC-free travoprost ophthalmic solution at either the 10- or 25-minute time points. The 3-D cultures expressed higher levels of corneal epithelial markers than the HCE-T monolayers, indicating a greater degree of differentiation. There were no significant differences between the corneal thickness of monkey eyes treated with latanoprost ophthalmic solution or its vehicle (both containing 0.02% BAC) and untreated eyes.</p> <p>Conclusion</p> <p>The lack of cytotoxicity demonstrated in 3-D corneal cultures and in monkey studies suggests that the levels of BAC contained in ophthalmic solutions are not likely to cause significant direct toxicity to epithelium of otherwise normal corneas.</p

Synthesis and characyerization of polymeric nanopracticles and thin films

This project focuses on the synthesis and characterization of colloidal polypyrrole and starch-based microgels. The colloidal polypyrrole were synthesized through the chemical polymerization of pyrrole with FeC13.6H20 in aqueous solution of methycellulose. Colloidal polypyrrole were being characterized with respect to its particle morphology, particle sizes, stability, chemical structure and electrochemical properties. tarch-based microgels were synthesized in the water in oil emulsion using epichlorohydrin (ECH) as the cross-linker. These microgels were being characterized with respect to their morphology, particle sizes, pasting characteristic and chemical structure. Colloidal polypyrrole appeared to be globular in shape, 100-580 run in diameter and readily formed aggregations in water. Starch-based microgels were observed to be spherical in shape and of much reduced granule size than native starches. Results of FTIR and UV-VIS showed that both colloidal polypyrrole and the starch microgel samples possessed very similar physical and chemical properties but distinctively different from their original materials. The RV A results showed significant decrease in viscosity of the cross-linked starch microgels as compared to that ofthe native starches

Improved fuzzy hashing technique for biometric template protection

Biometrics provides a new dimension of security to modern automated applications since each user will need to prove his identity when attempting an access. However, if a stored biometric template is compromised, then the conventional biometric recognition system becomes vulnerable to privacy invasion. This invasion is a permanent one because the biometric template is not replaceable. In this paper, we introduce an improved FuzzyHashing technique for biometric template protection purpose. We demonstrate our implementation in the context of fingerprint biometrics. The experimental results and the security analysis on FVC 2004 DB1 and DB2 fingerprint datasets suggest that the technique is highly feasible in practice

Controlled synthesis of nanostructures and their optical properties

Master'sMASTER OF SCIENC

Conventional versus digital preoperative templating in primary total hip arthroplasty at Hospital Sultanah Bahiyah

Introduction and objectives: Templating is part of preoperative planning for total hip arthroplasty surgery. Conventionally this was done using on acetate transparent films overlaid on hard copy radiographs. With the emergence and implementation of digital radiograph, digital templating software was introduced in total hip arthroplasty. We conducted the study to compare the accuracy of conventional templating techniques and digital templating techniques in primary total hip arthroplasty. Methodology: This was a retrospective study done on 73 cases where primary total hip arthroplasty was performed for osteoarthritis, avascular necrosis of femoral head and femoral neck fracture in Hospital Sultanah Bahiyah Alor Setar, Kedah, Malaysia from June 2011- June 2014. In a separate sitting, conventional templating was performed using hard copy radiographic films with implant specific templates whereas digital templating was performed using a magnification- calibrated digital radiographic images and TraumaCadTM templating software on a computer workstation. Paired t tests were used to determine the accuracy of conventional templating versus digital templating. We also used Bland-Altman Method and to determine the agreement between conventional method and actual implant as well as digital method and actual implant. Results: Both the conventional and digital template had quite a good agreement with the actual implant in predicting the acetabular cup and femoral stem size. However, digital templating had higher agreement to the actual implant size as compared to conventional templating in predicting the acetabular cup and femoral stem size. Conventional templating significantly under predicted cup size (P-value = 0.003) and the digital templating slightly over predicted the cup size but was not statistically significant (P-value =0.501). Conventional templating significantly over predicted femoral stem size ( P-value = 0.004) while digital templating slightly over predicted the femoral stem size but was not statistically significant (P-value =0.103). Therefore digital templating is more accurate than conventional templating in the preoperative assessment. Conclusion: Digital templating is more accurate in predicting the acetabular cup and femoral stem size than conventional templating using the available software. Key words: Templating , conventional, digital, total hip arthroplast

Dynamic signature verification based on hybrid wavelet-Fourier transform

In this paper, we propose a dynamic signature verification system which integrates hybrid of Discrete Wavelet Transform and Discrete Fourier Transform (DWT-DFT) for feature extraction. In feature matching, Euclidean distance and Enveloped Euclidean distance (EED) (a variant of Euclidean distance) are used. Distances of features are fused into a final score value and used to classify whether a genuine or a forgery signature. A benchmark database, SVC2004 which compose of Task 1 dataset and Task 2 dataset validate the effectiveness of this proposed system. Experimental results reveal a 7.08% EER for skilled forgeries and 2.37% EER of random forgeries in Task 1 dataset; and 8.61% EER for skilled forgeries and 2.05% EER for random forgeries in Task 2 datase

Breast cancer classification with histopathological image based on machine learning

Breast cancer represents one of the most common reasons for death in the worldwide. It has a substantially higher death rate than other types of cancer. Early detection can enhance the chances of receiving proper treatment and survival. In order to address this problem, this work has provided a convolutional neural network (CNN) deep learning (DL) based model on the classification that may be used to differentiate breast cancer histopathology images as benign or malignant. Besides that, five different types of pre-trained CNN architectures have been used to investigate the performance of the model to solve this problem which are the residual neural network-50 (ResNet-50), visual geometry group-19 (VGG-19), Inception-V3, and AlexNet while the ResNet-50 is also functions as a feature extractor to retrieve information from images and passed them to machine learning algorithms, in this case, a random forest (RF) and k-nearest neighbors (KNN) are employed for classification. In this paper, experiments are done using the BreakHis public dataset. As a result, the ResNet-50 network has the highest test accuracy of 97% to classify breast cancer images