Populärmusik i TV-reklam : En kvalitativ undersökning av musiken som betydelsebärande teckensystem

This paper examines a popular music song (Heartbeats by Jose Gonzalez) as a sign system in television advertising. The study was conducted through qualitative questionnaires in connection to an audio-visual method of analysis called Masking. The method facilitates the analysis of isolated parts in the audio-visual spectrum by masking/hiding parts of the audio-visual totality.The survey had seven respondents where a hermeneutic epistemological approach was used. For the analysis Cooper's theory of brand identity (Practical and Symbolic Attitudes to Buying Brands) was used together with an interaction model for music in audio-visual advertising called "Modes of music-image interaction”. The results showed that the music was associated with values as genuine, honest, responsibility, purity, independence and innovation. The music's symbolic values helped to position the brand in a lifestyle context. The music also helped to express the target group’s identity and attitudes by being innovative and independent. It also enhanced the perception of the visual colour rendition in the film. In general the television advertisement perceived more positive and entertaining when the music was present. In other words the music's social and cultural position contributed to raise the film's credibility. A deeper social and cultural value was created in the movie through resonance between symbolic values of the music and symbolic values of the film.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Independent Domain of Symmetric Encryption using Least SignificantBit : Computer Vision, Steganography and Cryptography Techniques

The rapid development of data transfer through internet made it easier to send the data accurate and faster to the destination. There are many transmission media to transfer the data to destination like e-mails; at the same time it is may be easier to modify and misuse the valuable information through hacking. So, in order to transfer the data securely to the destination without any modifications, there are many approaches like cryptography and steganography. This paper deals with the image steganography as well as with the different security issues, general overview of cryptography, steganography and digital watermarking approaches.  The problem of copyright violation of multimedia data has increased due to the enormous growth of computer networks that provides fast and error free transmission of any unauthorized duplicate and possibly manipulated copy of multimedia information. In order to be effective for copyright protection, digital watermark must be robust which are difficult to remove from the object in which they are embedded despite a variety of possible attacks. The message to be send safe and secure, we use watermarking. We use invisible watermarking to embed the message using LSB (Least Significant Bit) steganographic technique. The standard LSB technique embed the message in every pixel, but my contribution for this proposed watermarking, works with the hint for embedding the message only on the image edges alone. If the hacker knows that the system uses LSB technique also, it cannot decrypt correct message. To make my system robust and secure, we added cryptography algorithm as Vigenere square. Whereas the message is transmitted in cipher text and its added advantage to the proposed system. The standard Vigenere square algorithm works with either lower case or upper case. The proposed cryptography algorithm is Vigenere square with extension of numbers also. We can keep the crypto key with combination of characters and numbers. So by using these modifications and updating in this existing algorithm and combination of cryptography and steganography method we develop a secure and strong watermarking method. Performance of this watermarking scheme has been analyzed by evaluating the robustness of the algorithm with PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) against the quality of the image for large amount of data. While coming to see results of the proposed encryption, higher value of 89dB of PSNR with small value of MSE is 0.0017. Then it seems the proposed watermarking system is secure and robust for hiding secure information in any digital system, because this system collect the properties of both steganography and cryptography sciences.

Prospective teachers’ conceptions of what characterize a gifted student in mathematics

This paper explores Swedish prospective teachers’ conceptions of what characterise a gifted student in mathematics. This was studied through a qualitative questionnaire focusing on attributions. The results show that a majority of the students attribute intrinsic motivation to gifted students, more often than extrinsic motivation. Other themes were other affective factors (e.g. being industrious), cognitive factors (e.g. easy to learn), and social factors such as good behaviour and background.

The effects of attitudes and personality traits on mode choice

We hypothesise that differences in people's attitudes and personality traits lead them to attribute varying importance to environmental considerations, safety, comfort, convenience and flexibility. Differences in personality traits call be revealed not only in the individuals' choice of transport, but also in other actions of their everyday lives-such as how much they recycle, whether they take precautions or avoid dangerous pursuits. Conditioning on a set of exogenous individual characteristics, we use indicators of attitudes and personality traits to form latent variables for inclusion in an, otherwise standard, discrete mode choice model. With a sample of Swedish commuters, we find that both attitudes towards flexibility and comfort, as well as being pro-environmentally inclined, influence the individual's choice of mode. Although modal time and cost still are important, it follows that there are other ways, apart from economic incentives, to attract individuals to the, from society's perspective, desirable public modes of transport. Our results should provide useful information to policy-makers and transportation planners developing sustainable transportation systems.