A Simple Algorithm for Generating a New Two Sample Type-II Progressive Censoring with Applications

In this article, we introduce a simple algorithm to generating a new type-II progressive censoring scheme for two samples. It is observed that the proposed algorithm can be applied for any continues probability distribution. Moreover, the description model and necessary assumptions are discussed. In addition, the steps of simple generation algorithm along with programming steps are also constructed on real example. The inference of two Weibull Frechet populations are discussed under the proposed algorithm. Both classical and Bayesian inferential approaches of the distribution parameters are discussed. Furthermore, approximate confidence intervals are constructed based on the asymptotic distribution of the maximum likelihood estimators. Also, we apply four methods of Bootstrap to construct confidence intervals. From Bayesian aspect, the Bayes estimates of the unknown parameters are evaluated by applying the Markov chain Monte Carlo technique and credible intervals are also carried out. The Bayes inference based on the squared error and LINEX loss functions is obtained. Simulation results have been implemented to obtain the accuracy of the estimators. Finally, one real data set has been analyzed for illustrative purposes both the proposed algorithm and methods of estimation

A Spectral Estimation of Discrete Harmonizable Process

In this paper, we develop the non-parametric spectral analysis for non-stationary discrete-time stochastic processes. This development will be investigated by using the multi-tapering and averaging technique. In particular, we obtain an estimator for the spectral density function of a harmonizable time series. This estimator is constructed by dividing the available time series into a number of overlapped and non-overlapped segments and then a multi-tapering technique is applied for each segment. Also, we obtain an estimator for the auto-covariance function and another estimator for the spectral distribution function of these processes, based on the spectral density estimator. Statistical properties of these estimators are investigated, including the asymptotic behaviour of the bias and covariance

ELLIPTIC CURVES PUBLIC KEY TRAITOR TRACING SCHEME

In this paper we use the elliptic curves system in the Public Key Traitor Tracing Scheme. The Elliptic Curve points form Abelian group that used in the Public Key Traitor Tracing Scheme. The main advantage of elliptic curves systems is thus their high cryptographic strength relative to the size of the key. We design and implement an elliptic curves public key encryption scheme, in which there is one public encryption key, but many private decryption keys which are distribute through a broadcast channel, the security of the elliptic curves public key encryption scheme based on the Elliptic Curves Decisional Diffie Hellman(ECDDH) problem that is analogous to Decisional Diffie Hellman(DDH) problem, but it is more intractable than DDH problem

Reliability and Cost-Benefit Efficient in a Two-Dissimilar- Unit with Warm Unit Standby Case Subject to Arbitrary Repair and Replacement

In this paper, we deal with a warm case of standby system made up of two-dissimilar-units. One of these units is a high quality unit, while the other is a low quality one and may require repairs or replacement with a different lesser device in the event of failure, so the first unit is given priority in use. Assume that an arbitrary distribution for repairing the main unit and standby unit. We also examine all transition probabilities and calculate mean sojourn time, availability, and repair time. In the end, we use all of the previous measurments to evaluate the cost-benefit of the system

Studies of oil from cowpea (vigna unguiculata ( l.) walp.) cultivars commonly grown in Pakistan

The physiochemical properties and fatty acid ( FA) composition of oil from seeds of 4 cowpea cultivars viz., Elite, CP(1), White Star and SA dandy, commonly grown in Pakistan, were investigated. Oil contents ranged from 2.71-2.96% with triacylglycerols being present in highest amount. Iodine values were found highest in CP1 while SA dandy and CP1 excelled in saponification values and acid values, respectively. Despite variations unsaturated fatty acids were observed as being present in higher concentration in all cultivars. Among sterols, stigmasterol was present in highest amount followed by beta-sitosterol and campesterol. Among tocopherols, alpha-, and beta-tocopherols were observed as being present in highest and lowest concentrations, respectively. Results from most of the parameters revealed not significant (

Antifungal and nematicidal activity of selected legumes of Pakistan

The antifungal activity of legume seed extracts was tested against 6 fungi, viz., Trichophyton longifusus, Candida albicans, Aspergilus flavus, Microsporum canis, Fusarium solani and Candida glaberata. The extracts showed moderate activity against different fungal strains. Nematicidal activity has also been carried out to evaluate their potential toxicity against juveniles of the root-knot nematode Meloidogyne spp. In vitro results showed that ethanolic extract of these legumes caused appreciable mortality of second stage juveniles of Meloidogyne javanica and Meloidogyne incognita. The concentrations used @ 1% and 0.5% were found more effective and produced significant results as compared to 0.25%, and 0.1%. The mortality rate increased with increasing exposure time for most of the extracts

Forecasting Remission Time of a Treatment Method for Leukemia as an Application to Statistical Inference Approach

In this paper, Weibull-Linear Exponential distribution (WLED) has been investigated whether being it is a well - fit distribution to a clinical real data. These data represent the duration of remission achieved by a certain drug used in the treatment of leukemia for a group of patients. The statistical inference approach is used to estimate the parameters of the WLED through the set of the fitted data. The estimated parameters are utilized to evaluate the survival and hazard functions and hence assessing the treatment method through forecasting the duration of remission times of patients. A two-sample prediction approach has been applied to obtain a predictive sample based on the Bayes estimates of the parameters. The statistical inference approach is applied to the case of censored data namely Type-II hybrid censoring scheme, which is common in clinical studies

Estimation of quality deterioration in different rice genotypes infested by Tribolium castaneum (herbst) under a biotic stress

Rice being a major crop of Pakistan contributes major part of our economy and provides energy to a major population. So study was carried out to determine potential of nutritive losses in six rice genotypes against red flour beetle, Tribolium castaneum (Herbst) at 28oC, 32oC and 35oC. For nutritive losses, crude protein, fiber, ash and moisture content was analyzed through proximate analysis after 90 days of beetle infestation. Results deduced from the present findings shown significantly (P < 0.05) substantial variations in nutritional composition of rice grains in some advanced rice genotypes when exposed to artificial infestation of red flour beetle. High moisture content was observed in KSK-133 and Basmati-2006 as compared to KSK-282. Loss in crude fat and protein were maximum in KSK-282 and minimum in KSK-133 and Basmati-2006. Crude fiber was significantly (P < 0.05) high where insect infestation was low and least value where maximum infestation caused by insect. Ash content was severely affected by destructive activity of insects in all genotypes. In aggregate qualitative losses were significantly (P < 0.05) high in KSK- 133, Basmati-2006 and Basmati-515 and low in Basmati-385 and KSK-133 proving susceptible and resistance respectability, respectively. Findings should be incorporate in breeding programme and can also be helpful in post-harvest storage

A Secure Healthcare 5.0 System Based on Blockchain Technology Entangled with Federated Learning Technique

In recent years, the global Internet of Medical Things (IoMT) industry has evolved at a tremendous speed. Security and privacy are key concerns on the IoMT, owing to the huge scale and deployment of IoMT networks. Machine learning (ML) and blockchain (BC) technologies have significantly enhanced the capabilities and facilities of healthcare 5.0, spawning a new area known as "Smart Healthcare." By identifying concerns early, a smart healthcare system can help avoid long-term damage. This will enhance the quality of life for patients while reducing their stress and healthcare costs. The IoMT enables a range of functionalities in the field of information technology, one of which is smart and interactive health care. However, combining medical data into a single storage location to train a powerful machine learning model raises concerns about privacy, ownership, and compliance with greater concentration. Federated learning (FL) overcomes the preceding difficulties by utilizing a centralized aggregate server to disseminate a global learning model. Simultaneously, the local participant keeps control of patient information, assuring data confidentiality and security. This article conducts a comprehensive analysis of the findings on blockchain technology entangled with federated learning in healthcare. 5.0. The purpose of this study is to construct a secure health monitoring system in healthcare 5.0 by utilizing a blockchain technology and Intrusion Detection System (IDS) to detect any malicious activity in a healthcare network and enables physicians to monitor patients through medical sensors and take necessary measures periodically by predicting diseases.Comment: 20 pages, 6 tables, 3 figure

MONITORING SYSTEM FOR DETECTION OF OVER SPEED OBJECT

This paper introduces a system, which can be applied for monitoring of the speed of moving objects using a single camera. The Monitoring System is developed to monitor one moving object at a time with its speed being monitoring using a sequence of video frames. Field test has been conducted to capture real-life data and the processed results are presented. Multiple moving objects and noisy data problems are considered.The proposed system depends on evaluating the position and the orientation of moving objects in real world according to suitable reference point, on the screen, which can be selected by the user (static object)