Performance Analysis of Flattened Dispersion on Silica based PCF of Hybrid Hexagonal Lattice

The technology of optical fibers has improved dramatically in recent decades. While the basic principle of guiding light, total-internal reflection, has been known for a long time, the ability to manufacture materials such as silica into very pure, very small, and very long strands has only recently emerged. Researcher across the world is starting to investigate a new kind of optical guidance. In this work, I focused on understanding and analyzing the model behavior of micro-structured fiber. Micro-structured fibers are fibers with a complex dielectric topology, and offer a number of novel possibilities, compared to standard optical fiber. It has been reported that PCF can realize endlessly single-mode guiding, controllable nonlinearity, flexible chromatic dispersion over a wide wavelength range, large effective area and highly birefringence. Generally, PCFs can be classified into two different types by their light-guiding mechanism

Comparative Study of PCF Structure at Different Air Hole Pitch

Photonic crystal fibers (PCF) play most interesting and promising role in optical communication industry than conventional optical fibers. There are several unusual optical properties of PCF, which makes PCF more flexible and useful than conventional one. These properties are single mode operation, flattened dispersion, zero chromatic dispersion.. These properties are achieved by carefully design the PCF structure. This paper proposes a PCF structure of fused silica glass with an array of circular or elliptical air holes running along its length. In this paper I proposed 3 PCF designs with varying hole pitch and compared their results. The methodology I adopted to propose these designs with circular air holes is, by changing the pitch of the air hole rings. I designed the PCF structure with three different hole pitch of 2.0µm,2.03µm,2.05µm. By this investigation I selected the design with hole pitch=2.0µm as my best result, because it provide very low confinement loss less than 10-5dB/km in the wavelength from 1.1?m to 2.0?m, zero dispersion at 1.55µm wavelength, and ultra flat dispersion over a wide wavelength range 1.1µm to 2µm range

Effect of nitrogenous fertilizer and blue green algae on grain yield, chlorophyll and protein content on two rice (Oryza sativa) varieties Jaya and Sarju-52

In Agronomic studies on individual and integrated application of Blue Green Algae (BGA) biofertilizer with graded levels inorganic nitrogen under field conditions and possible utilization of these organisms to meet at least a part of the nitrogen requirement of rice were carried out during Kharif season at agriculture research station of Nawabganj, Bareilly, India. Application of BGA @ 12.5 Kg/ha in combination with 80 Kg/ha as urea recorded favourable results in the two rice varieties (Jaya & Sarju-52) and it is comparable with grain yield, chlorophyll and protein content at recommended doses of 160Kg/ha. Thus, it may be concluded that the use of biofertilizer (blue green algae) in rice crop can save at least 40 Kg/ha/year with increased yield

WORKING OF ACONTEXT-AWARE CONVERSATIONAL ENTITY

Abstract —  Introduction of new technologies in to the world is increasing rapidly and in order to assist the users to get equipped with such technologies industries are providing customer care services. Contacting a customer care service is subjective to several overheads of selecting options from a listed set, waiting for the switching between selections and awaiting the support of a customer care executive as the process usually requires a human intervention. Hence, a substitute for a personnel is required by the IT industries in order to automate the communication process in assisting the customers. Chatbots with context aware question-answering capabilities can be viewed as a good solution to such customer-care assistance. Development of a chatbot and the complexities involved in getting it to work effectively is delineated in this paper

Changes in blood Cr level and its oxidative status among leather tannery workers of District Kanpur in North India

Chromium (Cr) sulfate is used in the tannery industry as a basic tanning agent. Workers are directly exposed to the Cr due to unawareness and no safety protocols. Therefore, the present study aimed to investigate the oxidative stress of Cr in tannery workers of District Kanpur in North India. Two groups of the population were for the study, Group I included 50 directly exposed people employed in tannery industries, whereas Group II included 50 healthy people with no previous exposure to Cr. The concentration of total Cr in blood samples was measured by Inductively coupled plasma mass spectroscopy (ICP-MS). Oxidative status was measured by antioxidant enzyme assays such as Catalase (CAT), Glutathione Peroxidase (GPx) and Glutathione Reductase (GR). Statistical analysis observed a significant (p<0.001) increase of Cr concentration in Cr-exposed Group compared to controls which were not exposed to Cr. The level of CAT (9.73 ± 1.68 u/mg) was significantly (p<0.001) higher in Cr-exposed group as compared to control (6.00 ± 0.86 u/mg) while GPx (40.02 ± 5.43 u/mg) and GR (5.29 ± 1.59 u/gHg) concentration is significantly (p?0.001) lower in Cr-exposed group compared to control (59.71 ± 5.09 u/mg and 10.77 ± 2.32 u/g Hg, respectively. In Pearson correlation analysis, blood Cr level showed a significant correlation (p<0.05) with oxidative status. In Pearson correlation analysis, blood Cr level showed a significant correlation (p<0.05) with the oxidative status of the exposed population. The outcome of this study may help the early detection of hazardous impact of Cr on tannery workers, which will be crucial for reducing health risk and exposure.

Automated Detection of Acute Leukemia using K-mean Clustering Algorithm

Leukemia is a hematologic cancer which develops in blood tissue and triggers rapid production of immature and abnormal shaped white blood cells. Based on statistics it is found that the leukemia is one of the leading causes of death in men and women alike. Microscopic examination of blood sample or bone marrow smear is the most effective technique for diagnosis of leukemia. Pathologists analyze microscopic samples to make diagnostic assessments on the basis of characteristic cell features. Recently, computerized methods for cancer detection have been explored towards minimizing human intervention and providing accurate clinical information. This paper presents an algorithm for automated image based acute leukemia detection systems. The method implemented uses basic enhancement, morphology, filtering and segmenting technique to extract region of interest using k-means clustering algorithm. The proposed algorithm achieved an accuracy of 92.8% and is tested with Nearest Neighbor (KNN) and Naive Bayes Classifier on the data-set of 60 samples.Comment: Presented in ICCCCS 201