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Amrita Agrawal, Deepika Garg, Arun Kumar, Rakesh Kumar Performance Analysis of the Water Treatment Reverse Osmosis Plant
In this research paper, profit analysis of a Water Treatment Reverse Osmosis (RO) Plant is carried out by using the Regenerative Point Graphical Technique (RPGT) under specific conditions for system parameters. The paper analyzes the behavior of a water treatment RO plant consisting of subunits namely Multimedia filter (MMF), Cartridge filter (CF), High-pressure pump (HPP), RO System (ROS). The system is in a working state when all subunits are in good condition. A repair facility is accessible for all subunits. Availability of the plant, Busy Period of the Server (BPS) and Expected number of inspection by the repairman (ENIR) is calculated by using the RPGT technique. Finally, numerical analysis is carried out for calculating the performance measures and their comparisons.
DOI: https://doi.org/10.24412/1932-2321-2021-363-16-25
Jiju Gillariose, Ehab M. Almetwally, Joshin Joseph, Vishna Devi Reliability Test Plan For The Marshall-Olkin Extended Inverted Kumaraswamy Distribution
This paper mainly interested in studying the wider range behavior of the Marshall-Olkin extended inverted Kumaraswamy distribution. The parameters of model are estimated by various estimation methods. A reliability sampling plan is proposed which can save the test time in practical situations. Some tables are also provided for the new sampling plans so that this method can be used conveniently by practitioners. The developed test plan is applied to ordered failure times of software release to provide its importance in industrial applications.
DOI: https://doi.org/10.24412/1932-2321-2021-363-26-36
Gurami Tsitsiashvili, Marina Osipova Cluster Formation In An Acyclic Digraph Adding New Edges
In this paper, we construct an algorithm for converting an acyclic digraph that defines the structure of a complex system into a class of cyclically equivalent vertices by adding several additional edges to the digraph. This addition of the digraph makes it possible to introduce negative feedbacks and, consequently, to stabilize the functioning of the complex system under consideration and so to increase its reliability.To do this, the original digraph is transformed into a bipartite undirected graph, in which only the input and output vertices and the edges between them remain. In the constructed bipartite undirected graph, we search for the minimal edge cover and restore the orientation of the edges in it. Next, we construct an algorithm for adding new edges, based on the search for Hamiltonian (or Eulerian) paths and turning the minimum edge cover into a class of cyclically equivalent vertices. The minimal number of edges to be added is not larger than the number of edges in the minimum edge cover.
DOI: https://doi.org/10.24412/1932-2321-2021-363-37-40
Kamlesh Kumar Shukla, Rama Shanker Truncated Shukla Distribution: Properties And Applications
In this paper, Truncated Shukla distribution has been proposed. Some statistical properties including moments, coefficient of variation, skewness and index of dispersion have been derived. Survival and Hazard functions are derived and its behaviors are presented graphically. Maximum likelihood method of estimation has been used to estimate the parameter of proposed model. Simulation study of proposed distribution has also been discussed. It has been applied on three data sets and compares its superiority over two parameter Power Lindley, Gamma, Weibull, Shukla distributions and one parameter Truncated Akash, Truncated Lindley, Lindley and Exponential distributions.
DOI: https://doi.org/10.24412/1932-2321-2021-363-41-55
Garima Saxena, R. K. Sharma, Chandrashekhar Chauhan, Ankit Agrawal Dynamical Behavior of an SEIS Epidemic Model with Nonlinear Incidence Rate
In this paper, an epidemic model with nonlinear incidence rate is studied. The basic reproduction number ( ) is calculated. The local and global stability of the disease free equilibrium and the endemic equilibrium of the model are discussed and also the global asymptotical stability of the disease free equilibrium and endemic equilibrium are discussed. The stability analysis of the model shows that the system is locally asymptotically stable at disease free equilibrium and endemic equilibrium under suitable conditions. Moreover, show that the disease free equilibrium and the unique endemic equilibrium of the system is globally asymptotically stable under certain conditions. Finally, numerical simulations are given to support some of the theoretical results.
DOI: https://doi.org/10.24412/1932-2321-2021-363-56-62
Sarla More, Diwakar Shukla
In a multiprocessor computer system, there exist a ready queue of large number of processes waiting for computing resources allocation by the processors. These jobs may have size measure, which are additional information priory known while entry to the ready queue. Suppose the sudden system breakdown occurs and recovery management is required immediately. At this stage, one can find some processes who are completely finished, some partially processed, some blocked by processors and remaining waiting for allocation in the ready queue. Prime act of a system manager is to evaluate the maximum time required to process all the remaining jobs. This paper presents an estimation strategy for such, derived by applying the lottery scheduling, sampling technique and imputation methodology. Expressions for mean squared error of the proposed strategy are derived and optimized for suitable selection of system parameters. Three cases are discussed and compared and consequent results are numerically supported. It is found that at the optimal choice of constants in the estimation methodology, the shortest confidence interval can be predicted estimating the remaining required time. Such findings are useful as a part of disaster management of a cloud based multiprocessor data centre.
DOI: https://doi.org/10.24412/1932-2321-2021-363-63-80
Gaurav Kant Shankhdhar, Himanshu Pandey, Atul Kumar Pal, Sumit Mishra
Today, the general situation worldwide is that the hospitals, sanatoriums and medical colleges are running out of beds, oxygen, medical staff, ventilators and other required paraphernalia that is mandatory for the treatment of the vicious pandemic [1]. The requirement is for a system that takes in some input parameters like Oxygen level of the patient, pulse rate and respiration rate and in turn predicts the Life Risk Rate of that patient [2]. The model used here is a fuzzy regression model that gives the prediction of Life Risk Rate between 1 and 10 units. The lower the predicted Life Risk Rate, the better the chances of survival of the Covid patient. But if the predicted Life Risk Rate is more than the mean of the observations of the Risk in the dataset, then immediate emergency is needed. The benefit of this system is that the patients requiring immediate admission and treatment can be filtered and medical aid in hospital be thereby provided for critical patients. Rest may be home quarantined and domestic medical aid may be given to them until in some unfortunate situation their Risk Rate is near alarming. This paper aims to provide some help in this crucial situation.
DOI: https://doi.org/10.24412/1932-2321-2021-363-81-98
Abdullahi Sanusi, Ibrahim Yusuf, Na’fiu Hussain
Computer Based Test System also known as an e-examinations system, is software that can be used to administer examinations for distant or in-house applicants via internet or in an internet. Computer Based Test System/Software comprises of many components. So, it is vital to ensure its smooth operation, which can be achieved by the proper operation of its components/subcomponents. It is necessary to improve components/subcomponents operational availability. For this reason, the present research proposes to explore Computer Based Test System reliability indices using a RAMD technique at the component/subcomponent level. As a result, all subsystem/component transition diagrams are constructed, and the Chapman-Kolmogorov differential equations are formulated using the Markov birth-death process. For various subsystems/components of the system, numerical findings for reliability, availability, maintainability, and dependability, all of which are crucial to system performance, have been obtained and given in tables and figures. Other measurements, such as MTTF, MTBF, dependability ratio, and dependability minimum have also been obtained. Based on the numerical results, the most significant subsystem/component has been determined and the significance of the research has been emphasized.
DOI: https://doi.org/10.24412/1932-2321-2021-363-99-114
Anas Sani Maihulla, Ibrahim Yusuf, Saminu I. Bala
Today, reverse osmosis (RO) is a critical technique in the production of fresh water all over the world. As a result, downtimes due to repairing operations (after breakdowns, membrane blockage, pressure losses, etc.) or preventative maintenance (cleaning of membranes, component replacements, etc.) must be kept to a minimum in duration and frequency to guarantee optimum availability. Indeed, enhancing the availability (or dependability) of the RO plant as a whole system leads to a significant decrease in operating and maintenance expenses. We look at a recursive technique for reliability, availability, maintainability, and dependability in this study (RAMD. In addition, the efficacy of a RO unit, mean time to failure (MTTF), mean time to repair (MTTR), and dependability ratio were evaluated. The primary goal is economic optimization. For the method's validation, we utilized data from a RO unit that had a repair rate and a failure rate during a one-year period. It was demonstrated that all subsystems (pretreatment, dosage, etc.) had high availability. The high-pressure pump has a somewhat lower availability. For example, 0.59113 was the lowest availability for all subsystems, and it is for the RO membrane, which is where the majority of the purifications take place. A sensitivity analysis was performed to identify the essential components for the RO plant's availability. The collected findings demonstrate that the availability, reliability, dependability, and maintainability of the high-pressure pump have a significant impact on the overall system availability. As a result, special care should be given in the selection and maintenance of the high-pressure pump.
DOI: https://doi.org/10.24412/1932-2321-2021-363-115-131
Satish Kumar Das, Uttpal Bhattacharjee, Amit Kumar Mandal
Emotion is a conscious mental reaction accompanied by physiological and behavior changes in human body.In speaker authentication system, emotional state of the speaker plays a vital role. Recently, the field of speaker recognition in emotional context attracts more and more attention of many research focuses. However, to implement more realistic and intelligent emotional speaker recognition system it is interesting to study this system under real life conditions. Speech emotion recognition is a system in which speech signals are processed to classify the embedded emotions. In recent past, speaker emotion recognition has gained a lot of attention from different researchers as it has many applications. In this regards, study of prior works is useful for further research in the field of speaker verification in emotional context. So, performance and reliability of Emotional Speaker Recognition System depend on the proper selection of features to characterize different emotional states, feature extraction approaches and databases. In this paper we briefly discuss about different features, feature extraction approaches and emotion recognition and speaker verification databases.
DOI: https://doi.org/10.24412/1932-2321-2021-363-132-148
Mustafa Kamal
Accelerated life testing (ALT) is a time-saving technique that has been used in a variety of sectors to get failure time data for test units in a relatively short time it takes to test them under regular operating circumstances. One of the primary goals of ALT is to estimate failure time functions and reliability under typical use. In this article, an ALT with k increasing stress levels that is stopped by a type II progressive censoring (TIIPC) scheme is considered. At each stress level, it is assumed that the failure times of test units follow a generalized Pareto (GnP) distribution. The link between the life characteristic and stress level is considered to be log-linear. The maximum likelihood estimation (MLE) method is used to obtain inferences about unknown parameters of the model. Furthermore, the asymptotic confidence intervals (ACIs) are obtained by utilizing the inverse of the fisher information matrix. Finally, a simulation exercise is presented to show how well the developed inferential approaches performed. The performance of MLEs is assessed in terms of relative mean square error (RMSE) and relative absolute bias (RAB), whereas the performance of ACIs is assessed in terms of their length and coverage probability (CP).
DOI: https://doi.org/10.24412/1932-2321-2021-363-149-159
Yogesh Pal, Santosh Kumar, Madhulika Singh, Shweta Dwivedi Validation Of DNAFIDs Model Through Finite State Machine
The assurance of quality and reliability of process models and workflows is essential for model driven software development. There are numerous ways to achieve these objectives. One is model checking through which it can be verified that a model satisfies specific logical rules. The model to be checked is usually given as finite state machine. Rules have to be specified at the level required by the model checker. In this work, we develop a model for validating the DNA profiling through finite state. This enables the research/business process professionals to use model checking techniques and to produce higher quality research/business models for subsequent software development. The approach is demonstrated by validating event-driven process chains.
DOI: https://doi.org/10.24412/1932-2321-2021-363-160-167
Mei Tuan Teng, Sin Yin Teh, Khai Wah Khaw, XinYing Chew, Wai Chung Yeong Design of One-sided Modified S Control Charts for Monitoring a Finite Horizon Process
Control charting techniques are widely used in the manufacturing industry. One of the common charts that are used to monitor process variability is the S control chart. Finite horizon process monitoring has received great attention in the last decade. In the current literature, no attempt has been made to monitor the process variability in a finite horizon process. To fill this gap in research, this paper proposes two one-sided modified S charts for monitoring the standard deviation in a finite horizon process. The performance of the proposed charts is evaluated in terms of the truncated average run length and truncated standard deviation of the run-length criteria. The numerical performances of the proposed charts are shown with the selection of numerous process shifts. The effect of the sample sizes, the number of inspections and the process shifts are studied.
DOI: https://doi.org/10.24412/1932-2321-2021-363-168-182
Ismail Tukur, Kabiru H. Ibrahim, Muhammad Salihu Isa, Ibrahim Yusuf
The determination of this paper is to study reliability measures and routine analysis of computer network, which is a combination of four subsystems A, B, C and D and all the subsystem connected in series parallel pattern, the subsystem A is client, the subsystem B is load balancer and subsystem C is servers which is divided in to two subsystem (i.e. subsystem C1 and subsystem C2) and C1andC2 served as computer servers together with two unit each and working 1-out-of-2: G policy, and subsystem D is centralized server. The system has two types of failure, degraded and complete failure. The system can completely fail due to failure of one of the following subsystems A, B, C and D. The system is at partial failed state if at least one unit is working in either subsystem C1 or subsystem C2.The system is examined using supplementary variables techniques and Laplace transform. General distribution and copula family are employed to restore degraded and complete failed state respectively. Calculated results have been highlighted by the means of tables and graphs.
DOI: https://doi.org/10.24412/1932-2321-2021-363-183-194
Tripti Dahiya, Deepika Garg, Sarita Devi, Rakesh Kumar Reliability Optimization Using Heuristic Algorithm In Pharmaceutical Plant
In this paper, reliability of the liquid medicine manufacturing system of pharmaceutical plant named as Yaris Pharmaceuticals is enhanced on solving a redundancy allocation problem with the help of three algorithms HASL1 (Heuristic algorithm with selection factor 1), HASL2 (Heuristic Algorithm with Selection factor 2) and HASL3 (Heuristic Algorithm with Selection factor 3). It is ensured that redundancy is allocated within given cost constraints to maximize system reliability. Post allocation of redundancy the results of these algorithms are analyzed with the help of graphs, it has been found that the reliability of the system is optimized.
DOI: https://doi.org/10.24412/1932-2321-2021-363-195-205
Marwa KH. Hassan
Redundancy is an approach to improve the reliability system. There are three main models of redundancy. In a system with standby redundancy, there are number of components only one of which works at a time and the ther remain as standbys. When an impact of stress exceeds the strength of the active component, for the first time, it fails and another from standbys, if there is any, is activated and faces the impact of stresses, not necessarily identical as faced by the preceding component and the system fails when all the components have failed. In This paper, we consider the problem of estimation the reliability of a multicomponent stress- strength system called N-M- cold -standby redundancy. This system includes N- subsystem consisting of M- independent distributed strength components only one of which works under the impact of stress. The system fails when all the components have failed. Assuming the stress and strength random variables have the generalized linear failure rate distribution with common scale parameters and different shape parameter. The reliability estimated based on progressive type II data. Simulation study is used to compare the performance of the estimators. Finally, real data set is used the proposed model in practice.
DOI: https://doi.org/10.24412/1932-2321-2021-363-206-219
Shanti Parkash, P.C. Tewari Critical Review Of Rams Tools And Techinques For The Analysis Of Multi Component Complex Systems
This work provides the critical review of usefulness of Reliability, Availability, Maintainability and Safety (RAMS) approaches in complex mechanical systems. A broad range of research works available such as articles, conference proceedings and books covering RAMS approaches in industries as well as in the field of research is critically reviewed. These include different tools, techniques and methods which may be helpful in qualitative as well as in quantitative analysis. It provides the informations about the past and current scenario of RAMS practices in industries as well as in research. In this work the authors look for certain articles which included two or more aspects of RAMS. Limited work is reported in the field of safety.
DOI: https://doi.org/10.24412/1932-2321-2021-363-220-227
Komal D. Anadkat, Dr. Hiteishi M. Diwanji Effect Of Activation Function In Speech Emotion Recognition On The Ravdess Dataset
Since last decade, Speech Emotion recognition has attracted extensive research attention to identify emotions by user’s pitch and voice. Many research has been done in this field to recognize emotions using different machine learning as well as deep learning approaches. In this paper, we tried three different machine learning algorithms named SVM, Logistic regression and Random forest which take four different features named MFCC, Chroma, Mel-scale spectrogram and tonnetz as an input on RAVDESS dataset where SVM is more accurate than others. As deep learning approaches are more capable to identify hidden patterns and classify the data more accurately, we tried popular algorithm like MLP, CNN and LSTM. In deep learning approach, activation function is one of the most dominant parameters which a designer can choose to make classification more accurate. In this paper, we tried to show the effect of different activation functions on the overall accuracy of the model and analyzed the results.
DOI: https://doi.org/10.24412/1932-2321-2021-363-228-236
Valentin Vankov Iliev On the Use of Entropy as a Measure of Dependence of Two Events
We define degree of dependence of two events A and B in a probability space by using Boltzmann-Shannon entropy function of an appropriate probability distribution produced by these events and depending on one parameter (the probability of intersection of A and B) varying within a closed interval I. The entropy function attains its global maximum when the events A and B are independent. The important particular case of discrete uniform probability space motivates this definition in the following way. The entropy function has a minimum at the left endpoint of I exactly when one of the events and the complement of the other are connected with the relation of inclusion (maximal negative dependence). It has a minimum at the right endpoint of I exactly when one of these events is included in the other (maximal positive dependence). Moreover, the deviation of the entropy from its maximum is equal to average information that carries one of the binary trials A [ Ac and B [ Bc with respect to the other. As a consequence, the degree of dependence of A and B can be expressed in terms of information theory and is invariant with respect to the choice of unit of information. Using this formalism, we describe completely the screening tests and their reliability, measure efficacy of a vaccination, the impact of some events from the financial markets to other events, etc. A link is available for downloading an Excel program which calculates the degree of dependence of two events in a sample space with equally likely outcomes.
DOI: https://doi.org/10.24412/1932-2321-2021-363-237-248
C. P. Yadav, Jitendra Kumar, M. S. Panwar
In this paper, Marshall-Olkin inverse Maxwell distribution is proposed by generalizing the inverse Maxwell distribution under the Marshall-Olkin family of distribution that leads to greater flexibility in modeling various new data types. The basic statistical properties for the proposed distribution including moments, quantile function, median, skewness, kurtosis, and stochastic ordering are derived. Point estimates for the parameters are obtained by using two well known methods maximum likelihood and maximum spacing methods. The confidence intervals are used by using asymptotic properties of maximum likelihood estimators and boot-p methods. We have applied the proposed distribution under different real-life scenarios such as record value problem, system lifetime distributions, stress-strength reliability and random censored problems. For illustration purposes, simulation and real data results are established.
DOI: https://doi.org/10.24412/1932-2321-2021-363-249-272
Tijjani A. Waziri, Ibrahim Yusuf On Discrete Scheduled Replacement Model of a Series-Parallel System
This paper investigated the properties of discrete scheduled replacement model of a series-parallel system, with six units. The six units of the system formed three subsystems, which are subsystems A, B and C. Subsystem A is having three parallel units, subsystem B is having a single unit and subsystem C is having two parallel units. It is assumed that, the repairable system is subjected to two categories of failures (Category I and Category II). The mathematical expressions for both reliability function and failure rates, and an elementary renewal theorem were used based on some assumptions in constructing the discrete scheduled replacement model for a series- parallel system. A simple illustrative numerical example where made available, so as to study the properties of the replacement model constructed.
DOI: https://doi.org/10.24412/1932-2321-2021-363-273-283
V. Jilesh, Aifoona Ahammed P.M A New Generalization of Exponential Distribution for Modelling reliability Data
In this paper, a new generalization of the exponential distribution is proposed. Different properties, important reliability measures and special cases of this distribution are investigated. Unknown parameters are estimated using the maximum likelihood method of estimation. A simulation study is carried out to assess the accuracy of the maximum likelihood estimates. Two real data sets are successfully modelled with the proposed distribution.
DOI: https://doi.org/10.24412/1932-2321-2021-363-284-294
M. L. Soujanya, P. Vijaya Laxmi Analysis on Dual Supply Inventory Model having Negative Arrivals and Finite Life Time Inventory
In this paper the impact of dual supply chain on a perishable inventory model with negative arrivals is evaluated. The perishable and replenishment rates of dual suppliers are distributed exponentially. Arrival process follows Poisson distribution and the probability for an ordinary customer is p and for the negative customer is q. Limiting distribution of the assumed model is obtained. Numerical results are presented for cost function and various system performance parameters. The impact of dual suppliers on the optimal reorder points will be useful in developing strategies for handling various perishable inventory problems with replenishment rates.
DOI: https://doi.org/10.24412/1932-2321-2021-363-295-301
Sophia P.Thomas, Lishamol Tomy, K.K.Jose Harris Extended Two Parameter Lindley Distribution and Applications in Reliability
This paper introduces a new generalization of the two parameter Lindley distribution distribution namely, Harris extended two parameter Lindley distribution. Various structural properties of the new distribution are derived including moments, quantile function, Renyi entropy, and mean residual life. The model parameters are estimated by maximum likelihood method. The usefulness of the new model is illustrated by means of two real data sets on Wheaton river flood and bladder cancer. Also, we derive a reliability test plan for acceptance or rejection of a lot of products submitted for inspection with lifetimes following this distribution. The operating characteristic functions of the sampling plans are obtained. The producer’s risk, minimum sample sizes and associated characteristics are computed and presented in tables. The results are illustrated using two data sets on ordered failure times of products as well as failure times of ball bearings.
DOI: https://doi.org/10.24412/1932-2321-2021-363-302-321
Deepika Rajoriya, D. Shukla
Consider a graphical population of vertices (nodes) and edges, where edges are connected with vertices to form a Bipartite graph. A complete Bipartite graph has vertices that can be partitioned into two subsets such that no edge has both endpoints in the same subset, and every possible edge connected to vertices in different subsets is a part of graph. In real life, there may hundreds of cities where at least one possible way exists reaching source to destinations. Several tourist places and small towns are the examples where the road transportation is available between origin and destination and these roads constitute Bipartite graph when they are like edges. The travel needs resource consumption who could be measured through resource-score. Walking at the hill station needs more energy consumption than at the plane area. This paper suggests an example to estimate the resource consumption by the values of score. Further, paper proposes a sample based methodology for calculating the average resource consumption between a pair of small town (city) and tourist place. Bipartite graph is used as a model tool. A single-node systematic sampling procedure is proposed under the Bipartite graph setup which is found useful for solution. The suggested estimation strategy is optimum at specific choice of parametric values. For quick selection, ready-reckoner tables are prepared who provide immediate optimum choice of constant. Results are numerically supported by the empirical study and proved by the calculation of confidence intervals.
DOI: https://doi.org/10.24412/1932-2321-2021-363-322-338
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