Miracle-dz/UniFAR-FTUs huggingface dataset:
Autoconfiguration of OCTANE Nodes in MANET to Reduce flooding

: MANET is infrastructure less network and the routing protocol in MANET is not designed specifically with dynamic, self-starting behavior required for wireless networks. Each and every node in MANET acts as a forward and receiver node. Performance of most of the protocols is not encouraging in a highly dynamic interconnection topology. Most routing protocols in MANETs rely on a flooding mechanism to broadcast data and control packets over the entire network for establishing routes between source destination pair. However, the basic nature and characteristics flooding mechanism causes a large number of packets propagation in MANETs. This will eventually overload the network and traffic is congested affecting the overall performance of network. So, there is a need of such a protocol which not only reduces the flooding but also reduces the routing overhead. In this paper, a reliable broadcast approach for MANET is proposed, which improves the transmission rate. This work proposes a methodology where certain nodes are assumed to be high energy transmission nodes known as Octane Routing Node (ORN)/ High Power Routing (HPR) nodes, or Tower Node (TN) in the network which are utilized for routing. The route is established only through these nodes which are capable of communicating to long distance. Since the proposed approach reduces the flooding, we have considered functionality of the proposed approach with AODV variants. The effect of network density on the overhead and collision rate is considered for performance evaluation. The performance is compared with the AODV variants found that the proposed approach outperforms all the variants
Organizational Culture, Knowledge Sharing, and Intellectual Capital: Directions for Future Research

Organizational culture and knowledge sharing are two significant factors for the long-term success of an organization. As the sum of all knowledge used to develop a business and gain competitive advantage, intellectual capital is a mechanism for organizational performance. Despite that, existing evidence recounts the individual role of knowledge sharing on the organization’s intellectual capital; there is a lack of exploration and explanation of the role of organizational culture, knowledge sharing environment, and intellectual capital. This paper presents a conceptual model on the relationship between organizational culture, knowledge sharing practices (i.e. knowledge types, knowledge sharing approaches and knowledge sharing processes), and organization performance. The model proposes the potential measures of an organisation’s knowledge sharing environment and the role of organisational culture in shaping knowledge sharing practices and intellectual capital development and utilisation. Hypothetically, we argue that organisation culture is positively related to the organisation’s knowledge sharing environment, which in turn is positively related to its intellectual capital. On the other hand, we propose that organisational culture is positively related to intellectual capital. This paper indicates directions for further research and discusses the potential implications for theory and practice on knowledge management.
VIRTUAL KEYBOARD: AN INTELLIGENT INTERACTION SYSTEM FOR DESKTOP USING STANDARD CAMERA.

A virtual keyboard is a type of keyboard which doesn’t require any external physical support and can be operated by simply moving fingers, rather than typing on the physical keys of keyboard. Camera tracks the finger movements of typist to get the correct keystroke. The software and hardware type recognizes the typed characters and passes to the computer. The Proposed system is performed as: the typing will be captured by camera and the object can be discernible from background using BLOB Analysis. Then we estimate the location of user’s fingertip by fingertip detection. By using Shadow analysis, we check whether the fingertip is in contact with the table keyboard mat. Mapping the touch to keystrokes and recognize the character and finally, sending the keystroke to the display screen.
X-Ray Based Germination Test of Cotton Seed

In this paper we used digital image processing for germination from X-ray images of cotton seeds. Germination is the process by which a plant grows from a seed. The methods discussed in this paper are internal damages, embryo, and percentage of germination of cotton seeds. The recent development of digital image processing techniques for monitoring cotton seed germination has been done. X-ray analysis can be used to determine the quality of cotton seeds, showing the cause of bad germination. X-ray images provide information on the internal structure and morphology of seeds, mechanical damage, and percentage of empty and filled seeds, micro fractures, possible embryo deformations and insect infestation. This paper various digital image processing techniques which reduces the labour input required to evaluate seedling growth rate and increases the accuracy of these measurements. X-ray photographs were prepared with Faxitron 43805N X-ray Film exposed at 10kev, 2mA(soft X-ray) at a distance of 35cm from the X-ray source for 2min. X-ray photographs were evaluated based on embryo morphology and the presence of endosperm. Embryo morphology was scored as either normal or abnormal.
Robust Rician Noise Estimation and Filtering for Magnetic Resonance Imaging

This paper proposes a novel method for Rician noise in Magnetic Resonance Imaging (MRI). Noise in MRI is predominantly is Rician, which is signal dependent and it severely affects the contrast of the image. Pixelwise S estimate is highly effective for asymmetric distributions which are often encountered in the regions containing edges. UDWT provides effective representation of noisy coefficients. Pixelwise S estimate based wavelet transform combined with Thresholding and Bilateral Filtering provides efficient feature based preservation. The performance metrics both quantitative and qualitative, demonstrate the effectiveness of the proposed method in Rician denoising.
A Survey on Recent Trends in Digital Data Storage on DNA

DNA (deoxyribonueclicacid ) which is said to be the blue print of human life, is recognized as a powerful storage medium for storing digital information. The binary information of the digital data can be mapped to the four building nucleotides adenine, guanine, cytosine, and thymine. A very large data can be stored within a small of part of DNA.The storage is made by the process of encoding the digital information to the nucleotides. The encoded information is synthesized to get a sequence. The sequence obtained is further decoded to retrieve the data.Using the DNA as a storage medium has several advantages such as tremendously reducing the storage space and preserving the data for very long time. At the same time it has a constraint that synthesizing a DNA is a very expensive process. This survey elaborates recent new trends adopted by several scientists of different institutes to store and retrieve data on DNA Strand. <br>
Comparative Analysis of Fuzzy Inference Systems for Air Conditioner

In today’s world there is exponential increase in the use of air conditioning devices. The enhancement in utilization of such devices makes it essential for them to work with their full capability and efficiency. The fuzzy inference systems are best suited for the applications requiring easy interpretation, human reasoning, accurate decision making and control. The fuzzy inference systems resemble human decision making and generate precise solutions from approximate information. A comprehensive review of fuzzy inference systems with weighted average and defuzzification is covered in this paper. The objective of the paper is to provide the comparative analysis of fuzzy inference systems. This paper is a quick reference for the researchers in studying the characteristics of fuzzy inference system in air conditioner.
A STUDY ON IMPACT OF E-BANKING AWARENESS ON CUSTOMERS’ ATTITUDE TOWARDS ITS USE

his study aims to assess the influence of awareness on customers’ attitude towards e-banking in Delhi. It investigates whether the attitude varies among e-banking users on the factors such as perceived ease of use, perceived usefulness, perceived security & privacy and perceived risk due to difference in their degree of awareness on these factors. The research constructs were developed based on the Technology Acceptance Model (TAM) and incorporated two additional elements of perceived security & privacy and perceived risk. Factor analyses and regression technique were employed to study the relationship. The results show that difference in customers’ attitude among e-banking users depends up on the difference of their degree of awareness on factors such as perceived ease of use, perceived usefulness, perceived security & privacy and perceived risk. Therefore, this paper suggests managerial implications for retail bankers in Delhi to increase the degree of awareness among e-banking users.
Experimental Investigation of High Speed Micro-Drilling on SS 316L Material Using GRA

SS316L is considered for the study as it is used as a best substitute for titanium alloys which are used for trauma and orthopedic medical implants.Objective of the project is to investigate and optimize the process parameters when drilling at high speed for machining a micro hole on SS316L using tungsten carbide micro drill. There are two machining parameters of this experiment which are spindle speed, and feed rate to be varied to investigate the optimum condition for response parameters like Temperature, thrust force, machining time and MRR. To overcome the difficulty of wandering motion of tool, increased machining time, or sudden failure of drill tool Peck drilling Cycle has to be used for drilling holes. SEM analysis is carried out to compare the surface roughness and burr formation in holes and VMS (Video Measuring System) is used for carrying out the roundness measurement. Additionally, the GRA (Gray relational analysis) has been applied to determine the most significant factors to influence the response. --------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 15-06-2018Date of acceptance: 30-06-2018 -------------------------------------------------------------------------------------------------------------------------------------
DEVELOPMENT AND VALIDATION OF CAPECITABINE TABLET (PHARMACEUTICAL DOSAGE FORM) BY USING RP-HPLC METHOD.

: A new precise accurate and reliable validated method for the determination of Capecitabine was developed by using reverse phase high performance liquid chromatography in pharmaceutical dosage forms. Spectrophotometer determination was carried out at an absorption maximum of 240nm by using methanol. The linearity was over the concentration range of 20-120 µg/ml with correlation coefficient 0.999. Chromatographic separation was carried out by using a mobile phase of methanol: Acetonitrile: water (80:20:80 V/V) on Waters 2487 dual absorbance column in an isocratic mode at a flow rate of 1.1 ml/min with UV detection at 240 nm. The developed methods were found to be precise and accurate for the estimation of Capecitabine in pharmaceutical dosage forms and could be used for routine analysis. method development and guidelines for method validation. The results indicate that the proposed methods are sensitive, accurate, precise, simple and reproducible and can be used for routine determination of Capecitabine tablets and its impurities in bulk drug samples and pharmaceutical formulations.
A Novel Approach for Social Network Analysis & Web Mining for Counter Terrorism

-Terrorists and extremists are increasingly utilizing Internet technology as an effective mode to enhance their ability to influence the outside world. Lack of multilingual and multimedia terrorist/extremist collections and advanced analytical methodologies; limit our experiential understanding of their Internet usage. To address this research gap, we explore an integrated approach for identifying and collecting terrorist/extremist Web contents and to discover hidden relationships among communities. It has been shown in the literature that content analysis gives more insight of technical sophistication, content richness; whereas the link analysis focuses on the web interactivity. A dark web attribute system has made the sincere effort on identifying and comparing terrorist website with genuine web sites by using content and link analysis still there is scope in the same area as proposed in [1]. This proposed work focuses on identifying & analyzing new web page attributes. It is aimed to compare different terrorist/extremist sites with genuine sites and accordingly prepare metrics which can be further used for identification of other sites of terrorist/extremist groups. Also proposed work focus on to visualize and analyze hidden domestic terrorism communities and intercommunity relationships among all web sites in our collection.
AWARENESS AND ATTITUDE OF SCHOOL STUDENTS TOWARDS ENVIRONMENT

Environment and the organisms are two dynamic and complex component of nature. Environment regulates the life of the organisms including human beings. Human beings interact with the environment more vigorously than other living beings. It is the sum total of conditions in which an organism has to survive or maintain its life process. It influences the growth and development of living forms. In this paper an attempt has been made to study the awareness and attitude of school students towards environment and related issues. To study this phenomena survey method has been used. The study was conducted on 160 students (girls and 80 boys). The students were randomly selected from different schools of Shimla. For the purpose of data collection environmental attitude scale and environmental awareness tests were administered on them. The data was collected personally from the schools. To analyze the data t-ratio was calculated. The results revealed that both male and female have equal awareness towards environment and female students are having better attitude towards environment than male students.
Context Based Query Auto-Completion

— Auto-Completion is the first service the user uses to search and formulate the query. In the increased world of Web today, accessing information is one of the most frequent task. The users have to type each word or character sequentially and spend more time in completing the query. Often for a single query search engines returns thousands of Web pages, which are irrelevant to the user’s intended query. Querying techniques are used by most of the search engines . Query Auto-completion service help the user formulate their queries as they type and save users time. It is difficult for query auto-completer to accurately predict what the user is typing. Query Auto-completion often miss predicts the user’s query when their input prefix is too short (e.g. one or two characters). In this work we illustrate query auto-completion based on context, recent click through's, user’s current location and time, keywords, and sessions and by considering these factors the suggestion quality will be considerably higher even for short prefixes. We used the standard MostPopular Completion, Nearest Completion and Hybrid Completion algorithms. We calculated MRR values of the three algoritms and compared our results. The Nearest Completion algorithm has 32.7% better predictions than Most Popular algorithm. And the average MRR for Hybrid Completion is 0.83 which is higher than both the algorithms in giving more relevant predictions for the user’s queries with 1 or 2 of prefix length. We then considered the user’s current location for auto suggestion and the predictions of correct suggestions are better with location.
Unified Noise Reduction using Adaptive Radial Basis Function

The images captured by SAR and sonar are blurred and corrupted more by speckle noise and also other types of noise like Gaussian noise and salt & pepper noise. Denoising all types of noises to get perfect image is a vital challenge, earlier works on the same mode addressed with one filter for one noise, there is no one common or unified filter which can denoise all types of noise. Therefore in this paper, we have designed a filter which not only removes speckle noise, but also combination of other noises. Here IUNR (Intelligent Unified Noise Reduction) algorithm is proposed which is based on neural network called adaptive radial basis function acts as a unified filter for Denoising. Proposed method needs a single noisy image to train the adaptive radial basis function neural network to learn the correction of the noisy image. The Gaussian kernel function is applied to reconstruct the local disturbance appeared because of the noise. The proposed adaptive radial basis function network is compared with the fixed form which has fixed spread and the center value of kernel function. This method can correct the image suffered from different varieties of noises like speckle noise, salt & pepper noise and Gaussian noise separately or combination of noise. Various standard test images are considered for test purpose with different levels of noise density and performance of proposed algorithm is compared with adaptive wiener filter.
Image Restoration by Improved Iterative Shrinkage Thresholding Algorithm

The problem of restoration of digital images plays a central role in multitude important applications. A particularly challenging instance of this problem occurs in the case when the degradation phenomenon is modelled by ill-conditional operator. In such situation, the presence of noise makes it impossible to recover a valuable approximation of the image of interest without using some priori information called as simply priors is essential for image restoration, rendering it stable and robust to noise. Particularly, if the original image is known to be a piecewise smooth function, a total variation (TV) based image restoration can be applied. This paper proposes an algorithm for unconstrained optimization problem where the objective function includes a data fidelity term and a nonsmooth regulaizer.Total Variation method is employed to find solution of the problem based on the Improved Iterative Shrinkage Thresholding Algorithm (IISTA). IISTA is performed through a recursive application of two simple procedures linear filtering and soft thresholding. An experimental result shows that proposed algorithm performs well when compared with the existing methods.
Diagnostik und Bedeutung der Hepatitis E Virus Infektion

Zusammenfassung: Zur Diagnostik der Hepatitis E Virus (HEV) Infektion stehen heutzutage verschiedene virologische Methoden zur Verfügung. Die vermehrte Wahrnehmung sporadischer Fälle akuter Hepatitis E in Deutschland lenkt die Aufmerksamkeit zunehmend auf zoonotische Übertragungen des Virus. Die Kenntnis über unterschiedlich virulente HEV-Genotypen ist sowohl in Hinblick auf Epidemiologie und Krankheitsverlauf, als auch bei der Entwicklung und Auswahl diagnostischer Werkzeuge von Bedeutung. Es existieren eine Vielzahl enzymatischer und proteinbasierter Tests (ELISA, LIA, Western Blot), die anti-HEV IgG oder IgM Antikörper verschiedener HEV-Genotypen detektieren, jedoch große Unterschiede in Bezug auf Sensitivität und Spezifität aufweisen. Die heutzutage gebräuchlichste und am schnellsten auszuwertende Methode zur Diagnosesicherung einer Hepatitis E ist die PCR. Moderne, auch kommerziell erhältliche PCR-Kits können alle vier humanpathogenen Genotypen nachweisen. Zur Differenzierung der Genotypen wird in der Regel eine Sequenzierung durchgeführt, die bisher jedoch nur bei spezieller epidemiologischer Fragestellung von Relevanz ist. Methoden wie Antigennachweis, Virusanzucht oder T-Zell Assays haben bislang keine Bedeutung in der Routinediagnostik. Auch in Zukunft werden neue Erkenntnisse über die Pathogenese des Virus, seine klinische Relevanz bei bestimmten Patientengruppen (z.B. Immunsupprimierten) und die Anwendung antiviraler und prophylaktischer Therapien (Impfung) Leistungsmerkmale existierender Testformate herausfordern und die Anforderungen an durchführende diagnostische Labore erhöhen.
Checking the feasibility of power line communication channel with noise using OFDM Technique

: We know that research on digital communication has been widely developed in the past few years and offers a high quality of transmission in both the medium guided (wired) & unguided (wireless) communication environment. Coupled the devices with new modulation technique OFDM (Orthogonal Frequency Division Multiplexing) which is known as digital multicarrier communication technique and one of the most suitable method for the digital data transmission over a limited bandwidth. OFDM is a type of multichannel modulation that divides a given channel into many parallel sub channels or subcarriers, so that multiple symbols are sent in parallel. In this paper, design and analysis of OFDM system for power line channel based communication is proposed. for encode the signal convolutional encoder & for decode Viterbi decoder used. In doing so, MATLAB are used to simulate the operation of virtual transmitter and receiver. The performance of the system design is analyzed with noise occurs in the channel without reducing it. This paper results will show that for which a comparative performance studies using the Bit Error Rate (BER) plots was conducted for numerous simulations scenarios. These simulation scenarios include the use of different modulation types like BPSK, QPSK, QAM.
Segmentation Approach Based on LRTM

— Texture refers to the variation of gray level tones in a local neighbourhood. The “local” texture information for a given pixel and its neighbourhood is characterized by the corresponding texture unit. This paper describes new statistical approaches for texture segmentation, based on minimum and maximum of fuzzy left and right texture unit matrix. In these methods, the “local” texture information for a given pixel and its neighbourhood is characterized by the corresponding fuzzy texture unit. The proposed Minimum Fuzzy Left and Right Texture Unit Matrix (MFLRTU) and Maximum Fuzzy Left and Right Texture Unit Matrix (MXFLRTU) segmentation methods overcome the computational complexity of Fuzzy Texture Unit (FTU) by reducing the texture unit from 2020 to 79. The proposed schemes are compared with the Wavelet Transform with Image Fusion (WTIF) in [20]. The results demonstrate the efficacy of the proposed methods.
Key Pre-Distribution Methods of Wireless Sensor Networks – A Survey

— Wireless Sensor Networks (WSN) consists of numerous small nodes which observe the environment that they are deployed in and transmit information like temperature, sound, movement etc. The security of this information is of top priority. There are many security mechanisms that are available and many researches being conducted on improvising these mechanisms. Various studies imply that the key management is one of the most efficient methods in providing a better security against various types of attacks. In this paper, the major key pre-distribution methods are discussed along with their advantages and disadvantages and how each method is different between other methods.