Rangkaian Neural Untuk Sistem Dapatan Semula Perkataan Daripada Pangkalan Data

Rangkaian neural buatan yang diaspirasikan oleh kecekapan otak manusia memproses maklumat digunakan dengan meluas dalam aplikasi-aplikasi yang melibatkan pengkelasan atau pemetaan corak. Kelebihan utamanya iaitu sifat ketegapannya dalam persekitaran hingar dan keupayaan untuk mengecam input yang tidak sempurna atau cacat menjadikannya alat yang sesuai digunakan untuk dapatan semula maklumat yang pantas berbanding kaedah p engkomputeran konvensional, bagi menangani cabaran dapatan semula yang lebih realistik. Dapatan semula bersekutu menggunakan rangkaian neural adalah untuk mendapatkan semula maklumat (rekod) dengan betul daripada pangkalan data bila kekunci input yang cacat dimasukkan. Model rangkaian neural yang digunakan dalam kajian ini adalah rangkaian Counter propagation, yang merupakan gabungan rangkaian Kohonen dengan algoritma pembelajaran tidak terselia dan rangkaian terselia Grossberg, dengan sifat pengkelasan corak tanpa penyeliaan pada lapisan Kohonen menjadi bahagian paling penting bagi sistem. Kajian memfokuskan penyelidikan kepada prestasi rangkaian khususnya ketepatan pengkelasan bila skema-skema pengkodan yang berbeza digunakan untuk mewakilkan input. Tujuh skema pengkodan telah diaplikasikan dalam kajian ini, dengan jumlah bit perwakilan dan asas pengkodan yang berbeza. Data-data yang digunakan untuk ujian merupakan set bebas ralat, set data dengan ralat tunggal dan set yang mempunyai ralat berganda. Secara keseluruhannya semua eksperimen memberikan keputusan pengecaman yang baik, malah dengan setiap skema perwakilan yang digunakan, rangkaian telah berjaya mengecam dengan tepat kesemua set ujian dengan peratus pengecaman 100%, walaupun dengan bilangan unit persaingan, bilangan pusingan dan masa latihan yang tersendiri. Walau bagaimanapun, rangkaian yang mengaplikasi skema perwakilan dengan asas pengkodan tertentu menunjukkan prestasi yang lebih baik berbanding penggunaan skema tanpa asas pengkodan. Kajian menunjukkan ketepatan pengkelasan dan kecekapan sistem dipengaruhi oleh bentuk perwakilan input yang digunakan, saiz lapisan persaingan serta tempoh pusingan latihan yang optimum

Biometric Verification System for Automated Teller Machine (ATM)

Biometric Verification System for Automated Teller Machine (ATM) will serve as an alternative for the current verification system that uses ATM card and personal identification number (PIN) to protect against fraud and effectively eliminating most common attempts to gain unauthorized access. With biometric technology, customer can gain access to their account through smart card approach combined with biometric technology to automatically identify individuals using their distinct physical or behavioral characteristics. The main objective of this project is to solve the problems that arise from using PIN as the base of ATM verification system. These include unauthorized access into financial accounts, stealing money, ATM fraud and many more. To ensure a reliable project output, the author had outlined the scope of study for the proposed project. It involves the study of ATM system, biometrics technology, architecture, the benefits and the drawback of each approach and the current trend in the market. The development of this system will be based on the RAD methodology

Applied of image processing technique on semi-auto count of skin spot

Skin is the biggest organ in the human body and works to separate the inner body part from outer environment. In the skin, there are sebaceous glands found inside the pores of the skin. They are at all over the body except for the palms of the hands and the feet soles. There are more sebaceous glands on the face and scalp than elsewhere. Sebaceous gland secretes an oily protective skin surface, sebum, which is against pathogens and also help to slow down the skin ageing process [1]. They can help to maintain the moisture of the skin. However, the sebaceous glands become overactive sometimes, thus, producing too much sebum and the pores can get clogged together with dead skin [2][3]. This will results in having blackheads along with other factors. Blackhead is one of an acne vulgaris type [4]. It is a small dark spots on the skin that sometimes hard to be seen under a naked eye. If the clogged pores infect the glands, the accumulated sebum may form a sac and slowly increase in size. Lack of sebum production can also provide unsatisfied result that could cause dry skin, which makes the skin, looks rough and dull

Imageability, age of acquisition, and frequency factors in acronym comprehension

In spite of their unusual orthographic and phonological form, acronyms (BBC, HIV, NATO) can become familiar to the reader, and their meaning can be accessed well enough that they are understood. The factors in semantic access for acronym stimuli were assessed using a word association task. Two analyses examined the time taken to generate a word association response to acronym cues. Responses were recorded more quickly to cues which elicited a large proportion of semantic responses, and those which were high in associative strength. Participants were shown to be faster to respond to cues which were imageable or early acquired. Frequency was not a significant predictor of word association responses. Implications for theories of lexical organisation are discussed

A normative study of acronyms and acronym naming

Acronyms are an idiosyncratic part of our everyday vocabulary. Research in word processing has used acronyms as a tool to answer fundamental questions such as the nature of the word superiority effect (WSE) or which is the best way to account for word-reading processes. In this study, acronym naming was assessed by looking at the influence that a number of variables known to affect mainstream word processing has had in acronym naming. The nature of the effect of these factors on acronym naming was examined using a multilevel regression analysis. First, 146 acronyms were described in terms of their age of acquisition, bigram and trigram frequencies, imageability, number of orthographic neighbors, frequency, orthographic and phonological length, print-to-pronunciation patterns, and voicing characteristics. Naming times were influenced by lexical and sublexical factors, indicating that acronym naming is a complex process affected by more variables than those previously considered

A naturally inspired statistical intrusion detection model

Growing interest in computational models based on natural phenomena with biologically inspired techniques in recent years have been tangible. The use of immune mechanisms in intrusion detection is promising. In [1] we proposed a new IDS model based on the Artificial Immune System (AIS) and a statistical approach. In this paper we are going to enhance that model in terms of detection speed and detection rate as well as overall overload. In contrast with the work in [1] here we do not use the concept of clonal selection and we use binary detector sets which leads to lower overload and therefore higher performance. The model is examined with DARPA data set which is famous among IDS researchers

IP spoofing defense : current issues, trend and challenges.

In current Internet communication world, validity of the source of IP packet is an important issue. The problems of IP spoofing alarm legitimate users of the Internet. This paper review recent progress of spoofing defenses by various researchers.Techniques and mechanisms proposed are categorized to better illustrate the deployment and functionality of the mechanism.Overall, this paper summarizes the current anti spoofing mechanism on the Internet

Towards green frameworks for digital forensics investigation

Despite the fact that digital forensics involves strict procedures and complies with fixed regulations and principles, but as this paper presents, there are plenty of opportunities that can be practically employed in digital forensics to make this science greener. Virtualization can cost effectively reduce the number of workstations running forensic tools in the lab. Cloud computing and consolidating servers and storage devices in green data centers not only facilitate managing and securing services but also decline the number of required network and cooling facilities. Forensic labs can also be optimized with regard to environmental preservation. Using remote protocols and digitalizing paperwork procedures are environmentally helpful practices to accelerate investigation progress as well. Improving electrical power needs of labs and forensic devices is another issue that should be taken into consideration. Employing storage devices with optimal energy usage in digital forensics may highly reduce energy consumption. This paper study established green technologies particularly in information technology field and suggests a framework for implementing compatible techniques in digital forensics in order to reduce greenhouse gas pollutants, limit carbon emissions, and preserve the environment