The Southern Cowpea Beetle Callosobruchus maculatus (F.) is one of the most widespread insect pests of stored legumes, causing a considerable loss during storage, decreasing the net weight of the crops, and resulting in reduced the quality of the crops. This study has been conducted to determine the lifetime, fertility and life table parameters of C. maculatus by using an alkaloids extract from Moringa oleifera leaves at different concentrations 1000, 2000, and 3000 ppm. The result was shown that the lowest survival rate was 49% at a concentration of 1000, 2000 ppm, as compared with the control which was 77%. The lowest reproductive rate (Ro) was 4.76 female/female/generation at the concentration of 1000 ppm, c

(Cu1-x,Agx)2ZnSnSe4 alloys have been fabricated with different Ag content(x=0, 0.1, and 0.2) successfully from their elements. Thin films of these alloys have been deposited on coring glass substrate at room temperature by thermal evaporation technique under vacuum of 10-5Torr with thickness of 800nm and deposition rate of 0.53 nm/sec. Later, films have been annealed in vacuum at (373, and 473)K, for one hour. The crystal structure of fabricated alloys and as deposited thin films had been examined by XRD analysis, which confirms the formation of tetragonal phase in [112] direction, and no secondary phases are founded. The shifting of main polycrystalline peak (112) to lower Bragg’s angle as compared to Cu2ZnSnSe4 angle refers to incorpora

The research explores through its three parts, to search for the unconscious and the collective unconscious in order to identify the per-formative stimuli and motives and their motivation to produce a performance that is consistent with the metaphysics of the myth or the epic and its different characters from other human characters. The paper also explores in its second section a sort of sacred performance energy. Together, along with motivating the mind and engaging the subconscious, comes a metaphysical text and with its characters and epic events.

A thin film of (SnSe) and SnSe:Cu with various Cu ratio (0,3,5 and 7)% have been prepared by thermal evaporation technique with thickness 400±20 nm on glass substrate at (R.T). The effect of Cu dopants concentration on the structural, morphological, optical and electrical properties of (SnSe) Nano crystalline thin films was explored by using X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), energy dispersive spectroscopy (EDS), UV–Vis absorption spectroscopy and Hall Effect measurement respectively. X-ray diffraction analysis reveal the polycrystalline nature of the all films deposited with orthorhombic structure which possess a preferred orientation along the (111) plane. The crystalline sizes o

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

Determining 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