Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

Prostate cancer (PC), accounts for more than one-fourth of all cancer diagnoses, and the most frequently diagnosed cancer among men in 2022. The immunoglobulin (IG) Program death ligand-1(PD-1) cell surface receptor is predominantly expressed on the surface of many cells. The purpose of this study was to demonstrate the relationship between Program death ligand expression and some aggressive features of prostate cancer including perineural invasion, vascular invasion and necrosis. Thirty cases of prostate cancer with age range from 60 to 80 year old and 30 cases of normal prostate tissue with age under 25 year old were separated into two groups in a retrospective case-control

            Colon cancer is an abnormal growth of cells that occurs in the large intestine. Sometimes growth remains restricted for a relatively long time before it becomes a malignant tumor and then spreads through the intestinal wall to the lymph nodes and other parts of the body. The study aims to estimate the effectiveness and partial purification of lipoxygenase (LOX) enzyme and measure gamma-glutamyle transferase (GGT) activity in serum patients of colon cancer in Baghdad. The study included (80) case male patients with colon cancer with (50) samples of apparently healthy males (control) as comparison group. The result displayed a noteworthy increase in lipoxygenase effectivene

Let A ⊆ V(H) of any graph H, every node w of H be labeled using a set of numbers; , where d(w,v) denotes the distance between node w and the node v in H, known as its open A-distance pattern. A graph H is known as the open distance-pattern uniform (odpu)-graph, if there is a nonempty subset A ⊆V(H) together with  is the same for all . Here  is known as the open distance pattern uniform (odpu-) labeling of the graph H and A is known as an odpu-set of H. The minimum cardinality of vertices in any odpu-set of H, if it exists, will be known as the odpu-number of the graph H. This article gives a characterization of maximal outerplanar-odpu graphs. Also, it establishes that the possible odpu-number of an odpu-maximal outerplanar graph i

Roller compacted concrete (RCC) is a special type of concrete with zero or even negative slump consistency. In this work, it had aimed to produce an RCC mix suitable for roads paving with minimum cost and better engineering properties so, different RCC mixes had prepared i.e. (M1, M2, M3, and M4) using specified percentages of micro natural silica sand powder (SSP) as partial replacement of (0%, 5%, 10%, and 20%) by weight of sulfate resistant Portland cement. Additionally, M-sand, crushed stone, filler, and water had been used. The results had obtained after 28 days of water curing. The control mix (M1) had satisfied the required f ‘c with accepted results for the other tests. M2 mix with SSP of 5% had