3,968 research outputs found
Philometra otolithi Moravec & Manoharan 2013
No full textPhilometra otolithi Moravec & Manoharan, 2013 Host: Otholites ruber (Bloch & Schneider, 1801) (Perciformes: Sciaenidae). Site of infection: Gonads. Locality: South Bali Sea, Indonesia. Date of collection: 26 July 2013. Prevalence: 4 infected/8 examined, mean intensity 1.5 nematode per fish, range 1–3. Specimens deposited: Museum Zoologicum Bogoriense, Indonesia (MZBNa 726-729). Remarks. Several specimens of P. otolithi were reported from the gonads of 4 individual Otolithes ruber. This species was originally described from the gonads of O. ruber (type host) in the Bay of Bengal off the eastern coast of India, based on female worms (Moravec & Manoharan 2013). Furthermore, Moravec et al. (2014) described male specimens of P. otolithi also from same host species in the Sea of Oman, off Iran. This species can be easily recognized by having a large anterior oesophageal bulbous inflation with a conspicuosly large buccal cavity (Moravec & Manoharan 2013). This character was also seen in our specimens, together with the same host and site compared with the original description. This species is the third identified philometrid nematode obtained from a fish gonad in Indonesian waters.Published as part of Dewi, Kartika & Palm, Harry W., 2017, Philometrid nematodes (Philometridae) of marine teleosts from Balinese waters, Indonesia, including the description of Philometra damriyasai sp. nov., pp. 577-584 in Zootaxa 4341 (4) on page 581, DOI: 10.11646/zootaxa.4341.4.9, http://zenodo.org/record/104052
Identity-conscious vs identity-blind: hotel managers' use of formal and informal diversity management practices
No full textAbstract not availableAshokkumar Manoharan, Michael J. Gross, Shruti R. Sardeshmuk
A statistical framework for a new Kavya-Manoharan Bilal distribution using ranked set sampling and simple random sampling
No full textIn survival and stochastic lifespan modeling, numerous families of distributions are sometimes considered unnatural, unjustifiable theoretically, and occasionally superfluous. Here, a novel parsimonious survival model is developed using the Bilal distribution (BD) and the Kavya-Manoharan (KM) parsimonious transformation family. In addition to other analytical properties, the forms of probability density function (PDF) and behavior of the distributions' hazard rates are analyzed. The insights are theoretical as well as practical. Theoretically, we offer explicit equations for the single and product moments of order statistics from Kavya-Manoharan Bilal Distribution. Practically, maximum likelihood (ML) technique, which is based on simple random sampling (SRS) and ranked set sampling (RSS) sample schemes, is employed to estimate the parameters. Numerical simulations are used as the primary methodology to compare the various sampling techniques
On the Kavya–Manoharan–Burr X Model: Estimations under Ranked Set Sampling and Applications
No full textA new two-parameter model is proposed using the Kavya–Manoharan (KM) transformation family and Burr X (BX) distribution. The new model is called the Kavya–Manoharan–Burr X (KMBX) model. The statistical properties are obtained, involving the quantile (QU) function, moment (MOs), incomplete MOs, conditional MOs, MO-generating function, and entropy. Based on simple random sampling (SiRS) and ranked set sampling (RaSS), the model parameters are estimated via the maximum likelihood (MLL) method. A simulation experiment is used to compare these estimators based on the bias (BI), mean square error (MSER), and efficiency. The estimates conducted using RaSS tend to be more efficient than the estimates based on SiRS. The importance and applicability of the KMBX model are demonstrated using three different data sets. Some of the useful actuarial risk measures, such as the value at risk and conditional value at risk, are discussed
Classical and Bayesian Inference of Engineering and Disability Data: Using the Kavya Manoharan Power Chris-Jerry Distribution under Hybrid Censoring
No full textIn this article, we study and introduce the Kavya-Manoharan power ChrisJerry distribution (KMPCJD) which is a new generation of the power Chris-Jerry distribution (PCJD) which is suitable for engineering and disability data. The probability density curves of KMPCJD demonstrate that it has practical applications in analyzing engineering and disability data in Saudi Arabia. Researchers have a lot of flexibility when developing statistical models for research on disability issues, since the hazard rate function (HRF) for KMPCJD can exhibit J-shaped, increasing, and decreasing trends. In addition, several significant KMPCJD features are calculated, including moments, reliability metrics, moment-generating function, and order statistics. Using data on engineering and disability difficulties, we estimate the parameters of KMPCJD and use classical and Bayesian techniques to assess their reliability and HRF under hybrid censored schemes. Asymptotic confidence/credible intervals are calculated. The numerical results show that when the sample size n increases while keeping other factors like r and T constant, the estimators for δ and λ show improved performance in terms of reduced Bias, mean square error (MSE), and narrower confidence intervals. Also, the Bayesian method also produces shorter credible intervals (LCCI) compared to the traditional confidence intervals (LACI) from ML and MPS methods, suggesting higher precision. To show the utility of the suggested distribution, it was tested in five datasets related to engineering and disability issues in Saudi Arabia. The KMPCJD performed better in terms of goodness of fit than a number of models, including the Kavya Manoharan Rayleigh inverted Weibull distribution, Kavya Manoharan Burr X distribution, exponentiated generalized power Lindley distribution, Weibull power Lindley distribution, power Lindley distribution, Kavya Manoharan generalized exponential distribution, power XLindley distribution, Kavya Manoharan unit exponentiated half logistic distribution, and PCJD. Due to its superior fit capabilities, the KMPCJD is suggested for data modeling in disciplines including engineering and disability difficulties.OPEN ACCESS Received: 27/08/2025 Accepted: 19/09/2025 Published: 27/11/202
Inference for a Kavya–Manoharan Inverse Length Biased Exponential Distribution under Progressive-Stress Model Based on Progressive Type-II Censoring
No full textIn this article, a new one parameter survival model is proposed using the Kavya–Manoharan (KM) transformation family and the inverse length biased exponential (ILBE) distribution. Statistical properties are obtained: quantiles, moments, incomplete moments and moment generating function. Different types of entropies such as Rényi entropy, Tsallis entropy, Havrda and Charvat entropy and Arimoto entropy are computed. Different measures of extropy such as extropy, cumulative residual extropy and the negative cumulative residual extropy are computed. When the lifetime of the item under use is assumed to follow the Kavya–Manoharan inverse length biased exponential (KMILBE) distribution, the progressive-stress accelerated life tests are considered. Some estimating approaches, such as the maximum likelihood, maximum product of spacing, least squares, and weighted least square estimations, are taken into account while using progressive type-II censoring. Furthermore, interval estimation is accomplished by determining the parameters’ approximate confidence intervals. The performance of the estimation approaches is investigated using Monte Carlo simulation. The relevance and flexibility of the model are demonstrated using two real datasets. The distribution is very flexible, and it outperforms many known distributions such as the inverse length biased, the inverse Lindley model, the Lindley, the inverse exponential, the sine inverse exponential and the sine inverse Rayleigh model
On Service-Oriented Architectures for Mobile and Internet Applications
No full textService-oriented architectures have been around for long now, but the surge in the Smartphone and tablet market and the wide availability of fast mobile networks now cast new light on service-oriented architectures. The diversity of mobile platforms demand application abstraction. Such abstraction can be made possible by adapting a service-oriented architecture where the bulk of the business logic is hosted as a service. A service-oriented architecture may appear to be unsuitable when mobile networks are slow or unreliable. However, most modern mobile networks are reliable and reasonably fast, and thus applications employing a service-oriented architecture do not necessarily reduce user experience when compared to native, device-hosted applications. This paper reviews some of the technological advantages and challenges arising from the use of a service-oriented architecture for mobile and Internet applications.http://www.thinkmind.org/index.php?view=instance&instance=ICNS+201
The Motor Vehicles Act in Relation and to Environmental Pollution in Bangalore
No full textAwareness of an Act is a key factor in ensuring its effective implementation. This is especially so, in the case of much welcome but often ignored legislations such as the Motor Vehicles Act, 1988. Christopher Manoharan and Sanjanthi Krishnappa study the awareness level of the anti pollution provisions of the Act within Bangalore city
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The Motor Vehicles Act in Relation and to Environmental Pollution in Bangalore
No full textAwareness of an Act is a key factor in ensuring its effective implementation. This is especially so, in the case of much welcome but often ignored legislations such as the Motor Vehicles Act, 1988. Christopher Manoharan and Sanjanthi Krishnappa study the awareness level of the anti pollution provisions of the Act within Bangalore city
Vocabulary learning strategies of English for business students / Nalini Manoharan
No full textThe research focuses on English vocabulary learning strategies used by the first and second semester of the academic year 2017 business students from one of the well known private colleges in Subang Jaya. The main aims of this study are to identify a) the most and least preferred vocabulary learning strategies used by business students and compare the vocabulary items used by low, average and high proficiency business students; b) contributing factors for business students in choosing particular vocabulary learning strategies. As this is a mixed method study, multiple sources of data were collected via semi-structured interviews with five pupils and a 25-items questionnaire based on Schmitt’s Taxonomy (1997) which was adopted from Natpassorn Rian Kamal (2008) administered to sixty eight business students. The data collected from the questionnaire was analyzed on percentages, frequencies, and means. The interview data were obtained and summarized. The finding of the study revealed that the most preferred vocabulary learning strategies were metacognitive strategies and the least preferred vocabulary learning strategies were social (consolidation) strategies by business students. Business students used vocabulary items to learn new words based on their level of proficiency. The finding based on the interview revealed many contributing factors for business students to use vocabulary learning strategies such as; a) improve other study skills; b) help and guide to remember new words; c) practical and convenient to use; d) build confidence e) make learning English more fun; and f) improve both English language and mother tongue
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