Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Study of Gravel Suspension Properties of Hydroxyethyl Cellulose and Xanthan Gravel Pack Fluids

Transportation of proppant from surface to the desired location downhole during gravel packing operations in the petroleum industry is challenging. Various fluid systems have been used to do this. Depending on the type of polymer used as viscosifier, the fluid systems have different properties. Part of the criteria used to qualify gravel carrier fluids in hydraulic fracturing and gravel pack operations is their ability to suspend and transport solids. Almost all fluids can transport solids if the velocity is high enough. However, at low velocity or in a static state, the tendency of the solids to settle out is high for many fluids. Therefore, it is essential to formulate fluid system that is capable of proppant suspension and transport, especially at the low velocity areas of the wellbore during job execution. The fluid property and gel structure play a very important role in this regard. In this paper, the sand suspension properties of Hydroxyethyl cellulose (HEC) and xanthan polymer fluids were investigated at various temperatures for different polymer loadings. The study showed that settling rate is affected by thermal stability of the polymer fluid system and by the rate of degradation of the polymer by chemical breakers. HEC exhibited higher apparent viscosity than xanthan for the same polymer concentration, but xanthan showed superior sand suspension capability than HEC at the same condition. The result obtained can help in engineering designs to determine optimum pump rate without fear of proppant settling out of the suspension. Keywords—Gravel suspension, hydroxyethyl cellulose, proppant, rheology, xanthan.
FIELD ORIENTED CONTROL

AC induction motors of different power ratings and sizes can be utilized in applications ranging from consumer to automotive goods. A few of these applications from the multitude of possible scenarios demand for high speeds while high torque at low speeds only. A common everyday example with these mechanical requirements is of the motor installed in a washing machine. This requirement can be addressed through Vector Field Oriented Control or the FOC of an Induction machine. The objective of this Application Note is developing and implementing an efficient Field Oriented Control (FOC) algorithm that could be implanted to control the speed and torque of three phase asynchronous motors more effectively and efficiently. KEYWORDSvector-control, speed control, torque control, induction motor, speed regulator, IGBT Inverter
Enhanced SWASP Algorithm for Mining Associated Patterns from Wireless Sensor Networks Dataset

A Wireless Sensor Network are successfully deployed for various applications such as low cost area monitoring, environment monitoring, industrial and machine health monitoring, and military surveillance and they are spatially distributed autonomous sensors to monitor conditions such as physical and environmental. WSNs generate a large amount of data streams. Mining useful information from these data stream is a challenging task. Many algorithms have been proposed to extract the useful knowledge from sensor data and the widely used algorithm is Associated Sensor Pattern and compact tree structure, called Associated Sensor Pattern tree which uses pattern growth-based approach to generate all associated patterns with only one database scan over dataset. But when data stream flows through associated sensor pattern may fail to capture the significance of recent data. To overcome this limitation Associated Sensor Pattern tree is further enhanced to Sliding Window Associated Sensor Pattern tree by adopting sliding observation window and updating the tree structure accordingly and a mining algorithm Sliding Window Associated Sensor Pattern is used to mine recent associated patterns. But the limitation of Sliding Window Associated Sensor Pattern is that it takes too much time to mine associated patterns for large dataset. To enhance the performance of this algorithm, the dataset is partitioned into different sub parts and by using this partitioned dataset the Sliding Window Associated Sensor Pattern algorithm are run parallel by using multithread concept. And this enhanced algorithm reduces the total execution time and also increases the memory efficiency.
Implementation of Baugh-Wooely Multiplier and Modified Baugh Wooely Multiplier Using Cadence (Encounter) RTL

— High speed, low power consumption are key requirement to any VLSI design. The power efficient multipliers play an important role. This paper presents an efficient implementation of a high speed, low power multiplier using shift and adds methods of Baugh Wooely Multiplier. This study presented the design and implementation of Baugh wooely multipliers using Cadence (Encounter) RTL Complier. In this work, Modified Baugh Wooely is having least area, power and delay. The Modified Baugh wooley architecture is 109X faster than Conventional array multiplier and 102X faster than conventional Baugh Wooley. The operating frequency of 5 x 5 Design Modified Baugh Wooley multiplier is 160MHz. The Selection of Multiplier should be done depending on performance measure and application nature.
Nighttime Fears of Adolescents and Young Adults

Nighttime fears and fear of the dark are interchangeable concepts in literature. To a moderate extent, these types of fears are considered to be common among children and adolescents. Previous studies investigated children’s and adolescents’ thoughts about the content and origin of nighttime fears and the ways they cope with these fears. However, studies barely investigated this phenomenon beyond adolescence. Our study contributes to fill this research gap. Eighty-three adolescents with an average age of 14.76±. 51 (34 females) and 57 young adults with an average age of 22.31±2.18 (29 females) participated in our study. We used a self-developed scale to measure their intensity of fear of the dark. Participants answered open-ended questions referring to the content and origin of fear of the dark and to their ways of coping with this fear. Associations of scores and answer categories with age and gender were tested. The frequency of adolescents’ and young adults’ fear of the dark didn’t differ significantly, while females reported more frequent nighttime fears than males. There were no gender or age differences regarding specified contents. Compared to adolescents, university students reported
Intelligent Inter and Intra Network Traffic Estimation Technique for DDoS Attack Detection using Fuzzy Rule Sets for QoS Improvement

:- The quality of service of any network has higher dependency at throughput, latency and service completion strategies. In modern communication systems, there are many loopholes, which could be used by some malicious users to perform various network attacks so that the performance of the network is degraded. There are many denial of service when an approach has been discussed towards the problem of network threats, but still suffers the quality of denial of service attack detection. Propose a service-constrained approach learns the network traffic in various ways like the traffic incurred within the network and that comes from external network. The method uses various features like hop count, hop details, payload, TTl, time and so on. To maintain a rule set with fuzzy value where each rule specifies the feature of genuine packet being received. The incoming packet has to meet any of the rules and the attribute of the packet has to lie between the ranges of values in the rule. The proposed method estimates the inter traffic and intra traffic through the routes of the packet being transferred to identify the genuine nature of the packet being received. In addition, the method maintains set of logs where the packet features are stored to compute the legitimate weight of each packet being received. Based on compute inter and intra traffic values the received packets trustworthy is computed to allow or deny the packet. The proposed method increases the accuracy of DDOS attack detection and helps to improve the performance of the network.
IMPACT OF CAREER DEVELOPMENT ON STAFF COMMITMENT IN SELECTED NIGERIA’S PUBLIC SECTOR PARASTATALS : AN EMPIRICAL STUDY

This study adopted a descriptive survey in its design and covered a population of 30 senior staff members in Enugu Electricity Distribution Company (EEDC), Owerri branch. Due to the smallness of the population, the entire population was used as its sampled unit. Data was generated through a five point likert scale questionnaire, and the hypotheses tested with t-test (t) with the aid of the 20.0 version of statistical package for social sciences (SPSS 20.0). This paper concludes that organizations should begin to identify career development beyond just a onetime event or an act to incentivize employees. They should see it as a continuous process and a strategic activity of the human resource department that can ensure the attainment of both the economic and psycho-social need of the employees with the profit and sustainability goals of the organization. Sequel to the results obtained in this study, the following recommendations are made; Organizations should invest more in career development with special interest in innovation driven skills and that there is need to guarantee employees security if their commitment must be secured and sustained
Int. J. Biosci

Characterize selected tea varieties and clones based on molecular characteristics having maximum bands on using markers to find out the best tea variety/clone for high yield and drought tolerance. For DNA analysis 8 genotypes of tea were screened out with 10 SCoT (Start Codon Targeted Polymorphism) primer and 6 genotypes were screened with 4 RAPD primers. Out of these 10 SCoT primers used against genomic DNA of tea clones, however total 4 loci were generated by 3 SCoT primers with range of bands size at 200-2200bp. The S 11 proved the best primer as it showed maximum number of bands. Clone P3 and P8 resultant best for tea flush and shoot length but remained poor for genetic diversity. While clone Aa561 shows strong genetic diversity among other clones and placed out of that group. In view of different traits performance the clone Aa117/NTHRI was good comparatively on genetic diversification characters. * Corresponding Author: A. Waheed  abdulw900@gmail.com International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print) 2222-5234 (Online) http://www.innspub. net Vol. 10, No. 1, p. 142-151, 2017
Simulation of MUSIC and RLS Algorithm for Adaptive Antenna Array

292 ISSN: 2278 – 1323 All Rights Reserved © 2015 IJARCET  Abstract—Radio frequency spectrum is considered to be an expensive resource to the users. Its efficient utilization is possible using Smart or Adaptive Antenna array system to explore capabilities of wireless systems for optimization of service quality and capacity. Two major issues in smart antennas are Direction of Arrival (DOA) estimation and beamforming. The Direction of Arrival of all the incoming signals including the interfering signals is estimated using DOA algorithms. Some of the DOA algorithms are the MUSIC (Multiple Signal Classification), Root MUSIC, and ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques). Beam is steered in the direction of the desired signal and null are placed in the direction of the interfering signal. So, different beamforming algorithms are used like LMS, RLS. In this paper we have analyzed MUSIC Direction of Arrival (DOA) estimation and RLS algorithm for beamforming.
Int. J. Biosci

In this study, antibiotic and heavy metal resistant bacteria were isolated from the agriculture field’s soil around sugar industry situated in Roorkee, District Haridwar, Uttarakhand (India). The antibiotic and heavy metal resistance profiles of the isolates were determined. Fifteen antibiotics and five heavy metals were used for reference. Four promising isolates were recovered, two gram positive E-2 and E-10 and two gram negative isolate E-7 and E-9. Detailed morphological, biochemical, and molecular characterization was done to identify the bacteria. The isolates E-2 and E-10 were identified as Bacillus licheniformis sp, and Teribacillus aidingensis sp. while E-7 and E-9 were identified as Chryseobacterium indologenes sp. , and Enterobacter cloacae sp. respectively. These isolates were found resistant to heavy metals such as Ni2+, Pb2+, Cu2+, Zn2+ and Hg2+ at different concentrations ranging from 0.05 mM to 12 mM. The trend for tolerance of heavy metals by isolates was as follows: E-2:Ni = Cu >Pb> Zn > Hg, E-7: Ni > Cu = Zn >Pb> Hg, E-9:Pb = Ni > Cu = Zn > Hg and E10:Zn > Ni > Cu >Pb> Hg. The Anti-biogram pattern indicates that all isolates were showing resistance against more than five antibiotics and all are designated as multi-drugs resistant bacteria. These bacteria can be explored for bio-absorption of heavy metals from contaminated sites. * Corresponding Author: Saurabh Saini  saurabh.microbio@gmail.com International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print), 2222-5234 (Online) http://www.innspub. net Vol. 8, No. 2, p. 36-46, 2016
Attribute Based Revocable Data Access Control for Multi Authority Cloud Storage

— Cloud Computing is emerging tremendously due to its advantages and the flexible storage services provided by it. Due to this the number of users has reached at the top. Obviously the users will be sharing the sensitive data through the cloud. And the user can’t believe the untrusted cloud server. Hence the data access control has become very challenging in cloud storage system. In existing work revocable data access control scheme is proposed for multi-authority cloud storage systems which supports the access control based on the authority control. The authorized users who have eligible attributes given by multiple authorities can access the data. But it could not control the attacks which can occur by the authorized user who are not having eligible attributes. In this work we propose a new algorithm Improved Security Data Access Control which overcomes the problem exists in the existing work. And also include the efficient attribute revocation method for multi authority cloud storage.
Fortification of Multiple Parallel Assay Operations with Cross Contamination Avoidance in a Restricted Biochip

Digital microfluidic biochips are modification many areas of Biochemistry, Biomedical sciences, and Microelectronics. It is also known as ‘Lab-on-a-Chip’ for its recognition as an alternative to laboratory experiments. In recent times, because of urgency and cost efficacy, several assay operations are required to be performed at the same time. So, parallelism is a must in designing biochips. Having an area of a given chip as a constraint, how efficiently we can use a restricted sized chip and how much parallelism can be built-in are the objectives of this paper. A specific application of an assay may characterize a sample where, say only one type of reagent and multiple samples have been considered, or vice versa, and determine some parameter(s) of the sample(s) under requirement in parallel. In our experimentation, we essentially do this task in parallel for five such sets of sub-regions of a given restricted sized chip in digital microfluidics using an array based partitioning pin assignment technique, where cross contamination problem has also been considered, and efficiency of proper taxonomy of a given sample has also been enriched.
A QUANTITATIVE STUDY OF THE AUTOMATIC SPEECH RECOGNITION TECHNIQUE

: In the last two decades, few researchers have worked for the development of Automatic Speech Recognition Systems for most of these languages in such a way that development of this technology can reach at par with the research work which has been done and is being done for the different languages in the rest of the world. Punjabi is the 10th most widely spoken language in the world for which no considerable work has been done in this area of automatic speech recognition. Being a member of Indo-Aryan languages family and a language rich in literature, Punjabi language deserves attention in this highly growing field of Automatic speech recognition. The Speech is most prominent & primary mode of Communication among of human being. Today, speech technologies are commercially available for an unlimited but interesting range of tasks. These technologies enable machines to respond correctly and reliably to human voices, and provide useful and valuable services.
Effective Object Boundary Detection using Color Double Opponency

: In this system we are aiming two basic visual features, Brightness and color and to combine these two facts to maximize the reliability of boundary detection in natural scenes, we propose a new framework based on the color-opponent mechanisms of a certain type of color-sensitive double-opponent(DO) cells in the primary visual cortex of HVS(human visual system). This type of DO cells has oriented receptive field with both chromatically and spatially opponent structure. The proposed framework is a feed forward hierarchical model, which has direct counterpart to the color-opponent mechanisms involved in from the retina to V1. In addition, we employ the spatial sparseness constraint (SSC) of neural responses to further suppress the unwanted edges of texture elements. Experimental results show that the DO cells we modelled can flexibly capture both the structured chromatic and achromatic boundaries of salient objects in complex scenes when the cone inputs to DO cells are unbalanced. Meanwhile, the SSC operator further improves the performance by suppressing redundant texture edges. With competitive contour detection accuracy, the proposed model has the additional advantage of quite simple implementation whitlow computational cost.
An Efficient Visualization and Segmentation of Lung CT Scan Images for Cancer Detection

:- Interpretation of medical images is often difficult and time consuming, even for experienced physicians. The aid of image analysis and machine learning can make this process easier. The medical service has been enriched with a lot of new techniques for diagnostic imaging during the last decades. In recent years the image processing mechanisms are used widely in several medical areas for improving earlier detection and treatment stages, in which the time factor is very important to discover the disease in the patient as possible as fast, especially in various cancer tumors such as the lung cancer, breast cancer. Lung cancer images passed basic three stages to achieve more quality and accuracy in our experimental results : firstly image enhancement stage which is low pre-processing image techniques: Gabor filter using a Gaussian rule in which produced the best resultant enhanced images, then auto-enhancement method then FFT(Fast Fourier Transform) respectively. In the image segmentation stage, thresholding segmentation mechanism by Otsu thresholding algorithm and marker using the gradient magnitude as the segmentation function and computed the watershed transform of the segmentation function. Finally features which help to make a comparison between normal and abnormal images were. PCA and LDA techniques were used to extract the general features from an image and in practical session, two features computed were: black and white pixels percentage of the input image and the second feature is image Masking and labeling.
An Efficient Clustering Method for Atmospheric Conditions Prediction using ART Algorithm

- Ambient air temperatures prediction is of a concern in environment, industry and agriculture. The increase of average temperature results in global warming. The aim of this research is to develop artificial neural network based clustering method for ambient atmospheric conditions prediction in Indian city. In this paper, we presented a clustering method that classifies cities based on atmospheric conditions like Temperature, Pressure and Humidity. Data representing month-wise atmospheric conditions are presented to Adaptive Resonance Theory Neural Network to form clusters which represents association in between two or more cities. Such associations predict atmospheric conditions of one city on the bases of another. ART based clustering method shows that the months of two cities which fall in the same cluster, represent similar atmospheric conditions in them.
PRIVATE SEARCHING ON ENCRYPTED CLOUD DATA

- Cloud computing provides services like software, computation and storage services for which end-user need not worry about knowledge of the physical location and configuration of the system that delivers the services. Data leakage is a major problem in cloud computing and the privacy of user is under serious threat. The goal of the system is that, server shouldn't have any knowledge on the data it has got and the interests of the user, thus protecting the privacy of the user. Server should not understand the keywords interesting to the user and the documents containing those keywords. We intend to provide privacy by encrypting the data outsourced to the cloud. But a strong encryption will make it difficult to search files. Sensitive data is encrypted using a homomorphic encryption scheme, so that operations on encrypted data is equivalent to the operations on plaintext. This paper suggests a privacy preserving search scheme that is flexible to be applied for a sender-receiver scenario and data outsourcing scenario. The latter scenario is modified for a dynamic group of users. The scheme assures both data privacy and member privacy, by using the Paillier cryptosystem. The paper suggests a new approach using self-blinding property of the cryptosystem, to provide additional security.
Eye Detection Using Composite Cross Correlation from Face Images in Varied Head Pose

This paper presents a Composite Cross Correlation technique for detecting eye in varied head pose of face images. The proposed composite template consists of two single templates; the first template is created by taking the left half of a left eye and the second template by flipping the first template horizontally. We suggest other composite templates of entire face template to determine how many eyes should appear, one in profile face image and two in frontal face image. The experimental result was conducted on Psychological Image Collection at Stirling (PICS) database. The database has face images with five head poses in the range -90°, -45°, 0°, 45° and 90°. The results obtained using the proposed technique shows significant improvement in terms of detection rate compared to single cross correlation or using eye template of entire eye images
Earnest Access of Divulging and Aversion of DDOS Attack

In recent days, technology has reached new heights. In the same way malicious programs has also touched the level of sky and the above. Secret information are nowadays stored and managed through high secure sites. However, critical problems like hacking happens due to DDOS(Distributed Denial of Service Attacks) resulting in crashing of website for certain period of time and hacking of sensitive information thereby affecting the services issued. Such problems can be sorted by the scope of MASTDP (Multiple Authenticated Scoring Technique for denial and prevention of DDOS attacks). In this technique, internet protocol address and physical address of the users are entered and stored in the history and scores will be allotted for each and every entry. Similarly, horizontal and vertical communication scoring are given for every entry based on the vulnerability of the user (using scores). At-last, by association rule, users with peak scores are denied entry from the network or site.