The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

A Pap test can identify the pre-cancerous and cancerous problem in the vagina and uterine cervix. Cervical tumour is the easiest gynecologic disease to be diagnosed, treated and prevented using regular screening tests and follow-up. This review aimed to explore the opinion of specialists about cytological changes and the precancerous lesions with Pap smear test and visual inspection of the cervices, also to determine the relationship of this malignancy with demographic characteristics of patients. Results showed that few cervical cancer and pre-cancer were with women in postmenopausal period, but more were with women in the premenopausal period. Visual inspection of the cervix can show erosion lesions by gross inspection. Upon cytology exam

Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

Copper electrodeposition by electrorefining process in acidic sulfate media contains 40 g/l of cupric ions and 160 g/l of sulfuric acid was achieved to study the influence of the operating parameters on cathode purity, surface morphology, deposition rate, current efficiency and power consumption. These operating parameters and there ranges are: current density 200, 300 and 400 A/m², electrolyte temperature 35, 50 and 65 ^oC, electrodes spacing 15, 30 and 45 mm and electrolyte residence time 6, 4 and 2 h were utilized. XRF, SEM and EDX analyses were attained to clarify the properties of the produced cathode.

Carrying strength is one of the important physical capabilities in the field of competitive sports, which affects the success of the sports training process and helps players to continue to perform skillfully, physically and tactically for as long as possible, and the capacity for endurance varies depending on the type of sports activities, it may sometimes be very short. And with a high level of intensity, such as gymnastics and wrestling movements, and it may be long, and with a medium level of intensity, as in basketball, football and other games. The research community represents a sample of Baghdad players for teams (football, basketball, handball, volleyball, wrestling, weightlifting) and for the sports season (2017-2018 AD) for ages

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

Empirical equations for estimating thickening time and compressive strength of bentonitic - class "G" cement slurries were derived as a function of water to cement ratio and apparent viscosity (for any ratios). How the presence of such an equations easily extract the thickening time and compressive strength values of the oil field saves time without reference to the untreated control laboratory tests such as pressurized consistometer for thickening time test and Hydraulic Cement Mortars including water bath ( 24 hours ) for compressive strength test those may have more than one day.