Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

A nano manganese dioxide (MnO₂) was electrodeposited galvanostatically onto a carbon fiber (CF) surface using the simple method of anodic electrodeposition. The composite electrode was characterized by field emission scanning electron microscopy (FESEM), and X-ray diffraction (XRD). Very few studies investigated the efficiency of this electrode for heavy metals removal, especially chromium. The electrosorption properties of the nano MnO₂/CF electrode were examined by removing Cr(VI) ions from aqueous solutions. NaCl concentration, pH, and cell voltage were studied and optimized using the Box-Behnken design (BDD) to investigate their effects and interactions on the electrosorption process. The results showed that the

The operation of production planning is a difficult operation and it's required High effect and large time especially it is dynamic activity which it's basic variables change in continuous with the time, for this reason it needs using one of the operation research manner (Dynamic programming) which has a force in the decision making process in the planning and control on the production and its direct affect on the cost of production operation and control on the inventory.

      In this paper, the researcher suggested using the Genetic algorithm method to estimate the parameters of the Wiener degradation process,  where it is based on the Wiener process in order to estimate the reliability of high-efficiency products, due to the difficulty of estimating the reliability of them using traditional techniques that depend only on the failure times of products. Monte Carlo simulation has been applied for the purpose of proving the efficiency of the proposed method in estimating parameters; it was compared with the method of the maximum likelihood estimation. The results were that the Genetic algorithm method is the best based on the AMSE comparison criterion, then the reliab

The process of evaluating business processes, complex, repetition of procurement processes, need for raw materials and frequency of demand, which makes dealing with suppliers in the evaluation process, making the need for a process intervention in the process. Lighter on the other hand.

Many Iraqi companies suffer from problems related to suppliers, and cases of administrative and financial corruption are often raised regarding this type of contract and from this reality the necessity of researching this problem and trying to develop some solutions to reduce its impact on the companies' work, by using a method that works according to the standards adopted in Evaluation and selection of the supplier in the

Transparent nano- coating was prepared by Sol-Gel method from titanium dioxide TiO₂ which has the ability to self-cleaning coating used for hospitals, laboratories, and places requiring permanent sterilization. Three primary colors are selected (red, blue, and yellow) as preliminary study to the effect of these colors on the nano-coating. Three traditional oil paints color were used as base, then coated by a layer of TiO₂-Sol and deposited on the paints. The optical properties of TiO₂-Sol were measured; the maximum absorption wavelength at (λ_max=387 nm), the refractive index (n=1.4423) and the energy band gap (E_g=3.2 eV). The structure properties found by X-ray diffraction of TiO

Slag of aluminum is a residue which results during the melting process of primary and secondary aluminum production. Salt slag of aluminum is hazardous solid waste according to the European Catalogue for Hazardous Wastes. Hence, recovery of aluminum not only saves the environment, but also has advantages of financial and economic returns. In this research, aluminum was recovered and purified from the industrial wastes generated as waste from both of State Company for Electrical and Electronic Industries (Baghdad/AlWaziriya) and General Company for Mechanical Industries (Babylon/-Al-Escandria). It was found that these wastes contain tiny proportions of other elements such as iron, copper, nickel, titanium, lead, and potassium. Wastes were

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol