Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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

Decision-making in Operations Research is the main point in various studies in our real-life applications. However, these different studies focus on this topic. One drawback some of their studies are restricted and have not addressed the nature of values in terms of imprecise data (ID). This paper thus deals with two contributions. First, decreasing the total costs by classifying subsets of costs. Second, improving the optimality solution by the Hungarian assignment approach. This newly proposed method is called fuzzy sub-Triangular form (FS-TF) under ID. The results obtained are exquisite as compared with previous methods including, robust ranking technique, arithmetic operations, magnitude ranking method and centroid ranking method. This

Electro coagulation treatment was used for zinc removal from electroplating wastewater of the State Company for Electrical Industries . This wastewater, here consists zinc ions with maximum concentration in solution of 90 ppm .

The parameters that influenced the wastewater treatment are: current density in the range  1-1.4 mA/cm2, pH  in the range 5-10, temperature in the range 25-45°C and time in the range 10-180 minute.

The research is a laboratory experimental type using batch system for electrical process with direct current. The cell comprised of aluminum electrode as anode and stainless steel electrode as cathode. Thirty experiments and one hundred fifty sample lab tests were carried out in this research

   Ni-Co-Mn-Mg ferrite nanoparticles with the formula (Ni,Co)xMn0.25-xMg0.75Fe2O4 were synthesized in this work by employing the sol-gel auto-combustion process, with nitrates used as the cations source and citric acid (C6H8O7) as the combustion agent. X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray (EDX), and a vibrating sample magnetometer (VSM) were used to characterize the structural, morphological, and magnetic properties of ferrite powders. The XRD measurements showed crystallite sizes ranging between 24 - 28 nm. The FE-SEM images show the presence of agglomeration as well as a non-homogeneous distribution of the samples. On the other hand, the stoichiometry of the react