Commercial airlines and the passengers suffer from flight delay. Flight delay causes huge loss for the airlines and unsatisfied passengers. The researchers attempt to solve this problem through prediction extensively by machine learning approach and data mining tools. Accurate and robust performance is still to get through existing models. Our proposed hybrid approach is intended to use the power of machine learning as data mining tool and to predict the delay using classification algorithm of deep learning. An extensive evaluation of the proposed method is carried out by comparing the performance by using two data sets: one is local and the other is benchmark from Kaggle to obtain the best performing classifier. Three predictive models were applied on the datasets: logistic regression, decision tree and the proposed approach. The result shows that the proposed method performed well as comparing to the existing state-ofthe art.
Objectives Worldwide, diabetic neuropathy (DN) is a major complication of diabetes mellitus. The direct renin inhibitor aliskiren is recognized as a treatment for cardiovascular disease in diabetic patients, but little is known about its potential benefits in cases of diabetic neuropathy. Accordingly, we investigated the effects of aliskiren (ALIS) and gliclazide (GLZ) and their combination therapy on peripheral neuropathy in streptozotocin‐induced diabetic rats. Methods In total, 112 adult Sprague‐Dawley rats were used for this study. Diabetes was induced using streptozotocin (STZ), whereas the control group was treated with an equal volume of citrate buffer. The diabetic rats were divided randomly into six groups according to the proposed treatment regime: diabetic control (DC), gliclazide (GLZ), aliskiren (ALIS), ramipril (RAM), (GLZ + ALIS) and (GLZ + RAM). Behavioural responses to thermal (hot‐plate) and mechanical (tail‐pinch) pain were evaluated. After eight weeks of daily treatments, the animals were fasted and sacrificed. The blood samples were collected, with the serum separated and subjected to various biochemical and enzyme analyses so as to assess the effect of the treatments on diabetic peripheral neuropathy. Results After 8 weeks, aliskiren alone and in combination with gliclazide therapy had a significant effect (P < .001) in reducing blood glucose levels and showed increased hot‐plate and tail‐flick latencies compared with the diabetic control group. The threshold of mechanical hyperalgesia was also significantly elevated (P < .001). Conclusions/Interpretations These data suggest that either aliskerin alone or in combination with gliclazide can protect against the development and progression of diabetic neuropathy.
Phishing is one of the most common social engineering attacks that users over the internet fall for. An example is voting systems, and because such systems should be accurate and error free, phishing prevention techniques are crucial. Visual Cryptography (VC) is utilized for efficient voting system authentication to cast votes. VC is one of the most secure approaches for privacy protection as it ensures the confidentiality of the voting system. This paper discusses proposed phishing prevention methods and compares different proposed methods.
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