Swara Novel Complete Pdf Download [EXCLUSIVE]

Conclusions: Gibson Deletion is a novel, easy and convenient application of isothermal in vitro assembly, that performs with high efficiency and can be implemented for a broad range of applications.

At its core, the novel is a tale of two girls on two different timelines occasionally bridged by a mysterious portal and their shared search for a complete picture of their origins. Gibney surrounds that story with reproductions of her own adoption documents, letters, family photographs, interviews, medical records, and brief essays on the surreal absurdities of the adoptee experience.

Swara Novel Complete Pdf Download

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In recent years, multi-criteria decision-making (MCDM) methods have gained significant attention and have been widely applied in diverse domains to facilitate decision-making processes. In this paper a novel MCDM methodology including an interval valued picture fuzzy (IVPF) SWARA & CODAS methodology is introduced and applied to the renewable energy source selection problem in Turkey. The IVPF SWARA method is used for determination of criteria weights and the IVPF CODAS method is used for the selection of the best alternative. The contribution of this study is two folded; first, a novel extension of CODAS method by IVPFS; second, development of a novel SWARA & CODAS methodology. The obtained results are compared with an interval valued picture fuzzy AHP & TOPSIS methodology, and a sensitivity analysis is conducted to show the validity and robustness of the developed methodology. It has been observed that the proposed methodology provides robust and valid results.

This study uses innovative methodologies to evaluate the adoption of KM processes on SCP under uncertain environments and involving multi-decision-makers. The proposed integrated model demonstrates flexibility and practicality in combining KM and SCM, leading to improved SCP. Notably, this study presents the development of IVN-SWARA and the use of the integrated IVN-SWARA - IVN-HOQ decision tool, which are novel contributions to the existing literature.

Zhong, J., Cheng, H., Gholami, H., Letchumanan, L.T. and Toptanc, . (2023), "Supply chain performance: a novel integrated decision-making model", Management Decision, Vol. 61 No. 10, pp. 3053-3081. -07-2022-0961

In today's challenging industry conditions, where being good is not enough to be successful, companies trying to be the best, need consultancy in different fields. Consulting firms provides consultancy services to businesses, and they need to determine the most appropriate one for them. Fuzzy MCDM (Multi Criteria Decision Making) methods are appropriate to solve consulting firm selection problem. In this study, consulting firm selection problem of a textile company operating in Istanbul, Turkey is handled by using a novel combined fuzzy MCDM method based on IMF-SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) and F-CODAS (Fuzzy COmbinative Distance-based Assessment) methods. The importance weights of the criteria are calculated with IMF-SWARA method. Findings indicate that the top three important criteria are respectively, experience, references, and reliability. Then, F-CODAS method is used to rank the consulting firms and the best one is presented to the Human Resources department of the textile company. This study contributes to the existing literature in various aspects. It suggests a novel combined fuzzy MCDM method to solve consulting firm selection and a new Fuzzy CODAS based on TFNs is proposed. Moreover, HR managers can use the findings of this study to evaluate consulting firms.

Samudrara Swara is a critically acclaimed novel written by Pratibha Ray in the Odia language. The book was first published in 1977 and has been reprinted in six subsequent editions. The hardcover edition of the book is published by Adya Prakashani and has a total of 280 pages.

In recent years, Iran has experienced many landslides due to high tectonic activity, and a variety of geological and climatic conditions. This paper proposes a novel hybrid model based on step-wise weight assessment ratio analysis (SWARA) method and adaptive neuro-fuzzy inference system (ANFIS) to evaluate landslide susceptible areas using geographical information system (GIS). At first, based on an inventory map, landslide locations were randomly divided into two parts, 70% of which were used for generating the landslide hazard map and 30% of which were used for the validation of the model. Then, twelve landslide predisposing factors, such as lithology, slope angle, slope aspect, plan curvature, profile curvature, altitude, distance to streams, distance to faults, distance to roads, land use, seismicity, and rainfall were considered for the analysis. All the factors were then weighted by the SWARA method. Considering the nature of predisposing factors, they were split into two groups, factors with discrete data and factors with continuous data. For factors with discrete data, the SWARA method was used for final weight of each class, and for factors with continuous data, results related to the center of each class were obtained from the SWARA method. Subsequently, AFNIS was used to obtain weight of each value. All the values obtained from the model were then used to generate the landslide hazard map of the study area. Finally, the landslide hazard map was validated by receiver operating characteristics (ROC) using both success rate curve and prediction rate curve. 70% of observed landslides were used for the former while the remaining was used for the latter. The validation results showed that the area under the success rate curve and prediction rate curve (AUC) are 0.84 and 0.80 respectively. Additionally, the prediction performance of the SWARA method for landslide hazard mapping was investigated and the results were compared with those obtained from the proposed model. The comparison revealed that the developed model has better prediction ability for landslide hazard assessment. The results also indicated that the proposed model used in this study produced satisfactory and reliable landslide hazard map, which can be used for preliminary land use and infrastructure planning in Iran.

This paper presents a novel two-stage framework to extract opinionated sentences from a given news article. In the first stage, Naive Bayes classifier by utilizing the local features assigns a score to each sentence - the score signifies the probability of the sentence to be opinionated. In the second stage, we use this prior within the HITS (Hyperlink-Induced Topic Search) schema to exploit the global structure of the article and relation between the sentences. In the HITS schema, the opinionated sentences are treated as Hubs and the facts around these opinions are treated as the Authorities. The algorithm is implemented and evaluated against a set of manually marked data. We show that using HITS significantly improves the precision over the baseline Naive Bayes classifier. We also argue that the proposed method actually discovers the underlying structure of the article, thus extracting various opinions, grouped with supporting facts as well as other supporting opinions from the article. 17dc91bb1f