A joke is something that is said, written, or done to cause amusement or laughter. It could be a short piece or a long narrative joke, but either way it ends in a punchline, where the joke contains a second conflicting meaning. Sometimes when we read a joke, we understand it directly and fully, but this is not always the case. When a writer writes a joke, he intends to manipulate the reader in a way that the reader doesn’t get the joke at once. He does that by using pun on words or any other word play. We, as listeners to the joke, try to get the message depending mostly on the tone of the voice, in addition to other factors concerning vocabulary and grammar. But as readers of the joke, we need more other factors in order to get to the intended meaning of the joke. One of these important factors is punctuation. Punctuation is the use of certain signs which help understand a piece of writing. It is used to create clarity, sense, and stress in contexts, because using the correct punctuation helps us to convey our thoughts as we intend them to. So is the use of punctuation marks in writing a joke is essential in order to understand it? Or is it just helpful sometimes? What happens if the writer doesn’t use punctuation marks when writing the joke? Would this affect us in getting the meaning of the joke? In this study we try to answer these rising questions.
Steganography is a mean of hiding information within a more obvious form of
communication. It exploits the use of host data to hide a piece of information in such a way
that it is imperceptible to human observer. The major goals of effective Steganography are
High Embedding Capacity, Imperceptibility and Robustness. This paper introduces a scheme
for hiding secret images that could be as much as 25% of the host image data. The proposed
algorithm uses orthogonal discrete cosine transform for host image. A scaling factor (a) in
frequency domain controls the quality of the stego images. Experimented results of secret
image recovery after applying JPEG coding to the stego-images are included.
Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image
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In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .
The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. In this work, we implement an interaction between the feedforward neural network and the stream cipher, so the secret message will be encrypted by unsupervised neural network method in addition to the first encryption process which is performed by the stream cipher method. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding le
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in this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators
In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.
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Due to the difficulties that Iraqi students face when writing in the English language, this preliminary study aimed to improve students' writing skills by using online platforms remotely. Sixty first-year students from Al-Furat Al–Awsat Technical University participated in this study. Through these platforms, the researchers relied on stimuli, such as images, icons, and short titles to allow for deeper and more accurate participations. Data were collected through corrections, observations, and feedback from the researchers and peers. In addition, two pre and post-tests were conducted. The quantitative data were analysed by SPSS statistical Editor, whereas the qualitative data were analyzed using the Piot table, an Excel sheet. The resu
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