Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to evaluate the pronunciation of the Arabic alphabet. Voice data from six school children are recorded and used to test the performance of the proposed method. The padding technique has been used to augment the voice data before feeding the data to the CNN structure to developed the classification model. In addition, three other feature extraction techniques have been introduced to enable the comparison of the proposed method which employs padding technique. The performance of the proposed method with padding technique is at par with the spectrogram but better than mel-spectrogram and mel-frequency cepstral coefficients. Results also show that the proposed method was able to distinguish the Arabic alphabets that are difficult to pronounce. The proposed method with padding technique may be extended to address other voice pronunciation ability other than the Arabic alphabets.
In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.
Honorifics are linguistic expressions which maintain social as well as religious respect to other people. They are linguistic techniques which express politeness to other interlocutors. Semantically speaking, honorifics are of two types: al-Laqab (title) and al-Kuniya (teknonyms) following a specific word order. They form part of the Arab recognitions and are mold into their social and communicative competence.
The study focuses upon religious and regional honorifics which convey deference and respect. It assumes that religious and cultural recognitions play vital roles in formulating and embedding the sense of honorifics. It is hypothesized that Arab people express respect to religious personalitie
... Show MoreThis thesis study (pen weight and diversity of Arabic calligraphy), including the Arabic script went through multiple bodies, it came through the natural evolution of societies, and helped in the renovation and development of calligraphy after they gained a clear identity as a result of development that has occurred in the materials and writing instruments, especially industry pen that led to the diversity of Arabic calligraphy, and through the exploratory research and modeling study, which was obtained that the researcher could pose a problem discussed in the first chapter of his study follows by asking: is the pen is the weight of the role in the diversity of Arabic calligrap
... Show MoreTwo unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac
The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. E
... Show MoreThis paper investigates the collocational use of irreversible food binomials in the lexicons of English (UK) and Arabic (Iraq), their word-order motivations, cultural background, and how they compare. Data consisted in sixteen pairs in English, versus fifteen in Arabic. Data analysis has shown their word order is largely motivated by logical sequencing of precedence; the semantically bigger or better item comes first and the phonologically longer word goes last. These apply in a cline of decreasing functionality: logical form first, semantic importance second, phonological form last. In competition, the member higher in this cline wins first membership. While the entries in each list clearly reflect culturally preferred food meals in the UK
... Show MoreDetermining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show More