Miracle-dz/UniFAR-FTUs huggingface dataset:
Disease Detection of Cotton Leaves Using Advanced Image Processing

In this research, identification and classification of cotton diseases is done. The pattern of disease is important part where some features like the colour of actual infected image are extracted from image. There are so many diseases occurred on cotton leaf so the leaf color is different for different diseases. This paper uses k-mean clustering with Discrete Wavelet Transform for efficient plant leaf image segmentation and classification between normal & diseased images using neural network technique. Segmentation is basic pre-processing task in image processing applications and it is required to extract diseased plant leaf from normal plant leaf image and image background. Image segmentation is necessary to detect objects and borderlines in images. Even though different methods are already proposed, it is still hard to accurately segment a random image by one specific method. In last years, additional attention has been given to merge segmentation algorithm and feature extraction algorithm to enhance segmentation results.
Performance of Heuristic Algorithms in minimizing BER for Robust Turbo Codes

- The third component introduced in conventional turbo codes in recent days is effective in improving the performance of the code. But under noisy environments the parameters such as permeability and permittivity rates are static and hence their adapatability to noisy environment is poor. To overcome the aforesaid drawback A3D-TC was proposed in our previous paper[29]. In our present paper a comparison has been made between two heuristic algorithms viz.,Genetic algorithm and Simulated annealing algorithm. The parameters are made adaptive by generating a knowledge source using both Genetic algorithm and Simulating Annealing algorithm. The source output is fed to the feed forward neural network. The bit error rate at decoding section is tried to minimize in an effective way by the third component parameters generated from the neural network. Under various noisy environments, the experimental results compare the performance of A3D-TC using both Genetic algorithm and simulated annealing algorithm.
Evolocumab and Alirocumab: A Review of the Emerging Role of Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Inhibitors in the Management of Hyperlipidaemia

This article reviews the emerging role of Proprotein Convertase Subtilisin/Kexin type 9 (PCSK9) inhibitors in the management of hyperlipaedemia. Two PCSK9 inhibitors, Evolocumab and Alirocumab, have been recently approved by the National Institute for Health and Care Excellence (NICE) for patients who are at high risk of cardiovascular disease who cannot tolerate statins or those who fail to achieve appropriate levels of low density lipoprotein (LDL) despite maximum statin therapy. In this article we discuss the pathophysiology of PCSK9 Inhibitors as well as summarising the outcomes of the various clinical studies carried out on Evolocumab and Alirocumab. We also review the current NICE indications, contraindication, and the annual cost of each of these drugs.
Thermal Analysis Study in an Annular Diffuser Fitted with Different Hub Geometries

The enhancement of temperature distribution for turbulent flow through an annular diffuser fitted with helical screw-tape hub and twisted square hub were numerically investigated in the present study. The simulations were performed using three twist ratios y/w of 1, 1.5, and 2 for the helical screw-tape hub and three twist ratios y/w of 1.16, 1.5, and 2.3 for the twisted square hub with Reynolds number 4x10 4 . The annular diffuser geometries and the inlet condition for both hub arrangements were kept constant. The obtained results show that the insertion of the helical screw-tape hub and the twisted square hub will force the temperature to distribute in a helical motion; thereby the turbulence intensity will increase. However the findings showed that the temperature distribution rate was increased with decreasing twist ratio under the same operating conditions. The best temperature distribution was provided by twist ratios y/w = 1 and y/w = 1.16 for the helical screw-tape hub and the twisted square hub, respectively. KeywordsNumerical analysis, temperature distribution, annular diffuser, twists ratio, helical screw-tape hub, twisted square hub, swirl flow
Performance Evaluation of Concrete Using Bottom Ash as Fine Aggregate

95 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: F3779048619/19©BEIESP  Abstract: The engineering and construction industry has faced many challenge for consuming, “Sustainable green and recycled products” in manufacture of concrete. Coal Bottom Ash (CBA) has the potential to be used as concrete materials in place of fine aggregate. Bottom ash is the dominant solid residue generated in power stations. In this study, experimental investigation has been conducted to assess the performance of bottom ash as fine aggregate with various percentages (20 %, 40 %, 60 % & 100 %) in cement concrete subjected to chemical curing. The concrete specimens were casted and tested for compressive strength and tensile strength at 7, 28 and 90 days. The functional properties like Sorptivity, Water Permeability, Rapid Chloride Penetration, Sulphate and Acid Resistance were tested on 28, 56 and 90 days old specimens. It is observed that bottom ash replacement up to 40 % as fine aggregate in cement concrete is durable.
Secure Data-Gathering Mechanisms in Wireless Sensor Networks with Multiple M-Collectors

--Several studies in recent years introduces mobility elements for data gathering in the wireless sensor network. Typically, practical constraints preclude a mobile element is moving through the field and collect all nodes activity in the sensor network and the solution must involve a combination of a mobile element visiting a several subtree of the nodes, while other all nodes communicate their data to the cache points wirelessly. Considering the utilization of multiple M-collectors using a data gathering algorithm where multiple M-collectors traverse through several shorter sub tours concurrently to reduce the distance and time constraints. The Multi-Hop Data Gathering Algorithm (MH-DGA) is reduce the Link broken by automatic modification in the routeand making longer network lifetime than in a network with static data sink or in a network which uses the mobile collector ( which can only move along straight lines, reaches maximum distance to the sink node and increase the capacity of the network ). This concludes that Multi-hop mobile data-gathering scheme can increasethe maximum distance to the Sink node and also increase the coverage area of the network. In addition, the proposed securedata-gathering scheme is introduce in the network and Mobility movement performance is improved. While using the Mobility in the network is significantly improved to the network lifetime and more secure the network. Also predominantly reduces the power consumption, time latencies and packet losses.
Abandoned Object Detection with Region of Interest

: Abandoned object detection is an essential requirement in many video surveillance contexts. In this paper, we propose a method to detect abandoned object from surveillance video. Different from conventional approaches that mostly rely on pixel-level processing, we perform region-level analysis in both background maintenance and static foreground object detection. In background maintenance, region-level information is fed back to adaptively control the learning rate. In static foreground object detection, region-level analysis double-checks the validity of candidate abandoned blobs. Different from conventional approaches that mostly rely on pixel-level processing, we perform region-level analysis. In this paper, we present an abandoned object detection system based on blob detection methods are aimed at detecting regions. In a digital image that differs in properties, such as brightness or color, compared to surrounding regions. Informally, a blob is a region of an image in which some properties are constant or approximately constant. All the points in a blob can be considered in some sense to be similar to each other. In this paper we are performing a real time application using the Raspberry Pi processor and a Raspberry Pi camera.
Underground Coal Gasification: an alternate, Economical, and Viable Solution for future Sustainability

The Energy demand in the world is increasing drastically, and coal is the major raw material in producing energy. Countries such as China, USA, India, Australia, Indonesia, Russia, South Africa, Germany, Poland, and Kazakhstan play a vital role in hard coal strip surface mining: extracting of coal through Mining process is dangerous work, as most of the coal is too deep, and creates unwanted pollution and is economically not effective. Coal releases enormous quantity of unwanted green house gas emission when it is burnt. Therefore, there is a need in technology for clean and efficient usage of coal: Underground coal gasification (UCG) is an economical, clean coal technology using un-mined method of converting coal into a combustible gas in-situ, without bringing up the CO2, and ash residue which is left out after burning the coal. This process is performed under the earth surface in-order to eliminate traditional method of extracting the coal through strip coal mining process. UCG offers more proven advantages over conventional Mining and gasification. This is an attempt to show that UCG is an alternate, economical, and viable solution for future sustainability.
A Comparative Study on Apache Spark and Map Re Performance Analysis U

With the unremitting advancement of internet, IT and enhancement of technology, tremendous growth of data has been observed. Data is getting generated at very tremendous speed, referred to as Big Data. Big Data has gained more prominence in recent times wi continuous explosion of data resulting from various sources. The major focus of this paper is to compare performance between Hadoop and Spark on iterative and machine learning algorithm. Hadoop and Spark both are processing model for analysing big data their performance varies significantly based on the use case under implementation. In this paper, we compare these two frameworks along with providing the performance analysis using a standard machine learning algorithm for classification (knn) and Pag Rank algorithm.
THE INFLUENCE OF ENTREPRENEURS’ STRATEGIC AGILITY AND DYNAMIC CAPABILITY ON THE OPPORTUNITY PURSUIT PROCESS OF NEW VENTURES: EVIDENCE FROM SOUTH KOREA

This study proposes a process for successful opportunity pursuit based on entrepreneurs’ strategic agility and firms’ dynamic capabilities. An in-depth case study is conducted with five Korean ventures to expand our understanding of how venture firms identify, develop and realize new business opportunities. The process undertaken by venture firms to develop opportunities is a critical engine for attaining competitive advantage. Through longitudinal and in-depth case studies on the five new venture firms, the opportunity pursuit process and the key factors affecting its success are analyzed qualitatively based on CEO or founder interview data. The three major study findings are as follows. First, the strategic agility and alertness of the founder are associated with successful opportunity recognition and pursuit. Second, a dynamic convergence of the core firm competences-resource, network and knowledge-is critical for successful opportunity development. Third, rapid changes in firms’ external and internal environments are related to successful opportunity pursuit.
Croslinking of Chitosan with Cotton using Polycarboxylic Acids

-Chitosan can be crosslinked with cellulose using PCAs and therefore better bonding has resulted between chitosan and cotton fabric. Because of the better bonding of chitosan and the crosslinking of cellulose by PCAs, an optimum blend of functional properties viz., antimicrobial protection, low flammability characteristics, improved crease recovery with greater strength retention, excellent soil release properties and reduced stiffness can be achieved in cotton. Antimicrobial property exhibited by the fabric treated with all combination samples is good with zone of inhibition ranging from 21 to 25mm for E.coli and 24 to 27mm for S. aureus. All the chitosan and PCAs combination samples show class I flammability which means that these samples are suitable for applications that require lower flammability. 5% MA and chitosan sample show a flame propagation time of 16.84s, which is the highest among all the samples and is comparable to that of THPC treated control fabric. Combination of PCAs with chitosan has imparted excellent soil release characteristics in the finished fabric with a maximum soil release grade of 5. This enhances the easy-care nature of the fabric. CRA of the finished sample has increased up to 261 which is very much closer to the value of 265 for the resin treated control sample. Strength loss values are very low compared to the control samples. 18.7% of tensile strength loss has been obtained for 5% MA and chitosan combination. In case of tearing strength, almost all samples exhibited strength loss values in the range of 13% 15%. On comparison with resin treated sample, all the samples treated with combination of PCAs and chitosan have better strength retention both in tensile and tearing strength. Though all combinations of PCAs and chitosan have been found to be successful in imparting the functional properties, MA combinations with chitosan have an edge over combinations of chitosan with other two PCAs.
Performance Validation of MQoSM and Resource Reservation Polices for MANETS over Long Area and Heavy Load

Summary It is very common issue that on any network especially MANET, when number of node/users increase with increase in distance of service area then QoS of network is automatically degraded. In this regard authors have presented MQoSM with its supporting Preempted resource reservation polices those works effectively with excellent results of QoS parameters as Jitter, Delay, Packet Drop and most important Throughput, even on heavy load of user nodes and large area of service. The verification experiments were performed and tested in simulation scenario by using OPNET MODULATOR 14.0
Energy Efficient Clustering Protocol for Wireless Sensor Networks Using Particle Swarm Optimization Approach

- WSN comprises of a considerable amount of small and limited power sensor elements that are arbitrarily or physically conveyed over an unattended target region. WSNs have potential applications in atmosphere observing, calamity cautioning frameworks, medicinal services, security surveillance, and reconnaissance frameworks. The main drawback of the wireless sensor network is the restricted power sources of the sensing elements. Expanding the lifetime of the Wireless Sensor systems, energy preservation measures are vital for enhancing the execution of WSNs. This paper proposes LEACH-P which is a novel approach to improve existing LEACH protocol using PSO based clustering. The proposed algorithm is simulated broadly and the results are compared with the existing algorithm to determine its supremacy in terms of network lifetime, stability period and number of data transmitted to the base station
Blue Native Page in Combination with Mass Spectrometry as an Effective Tool to Study Multi-Enzyme Complex’s in Secretome of Aerobic Fungus

The past decade has seen a large global interest in the development of renewable energy sources, and bio-products based on plant biomass. This is owing to the abundance of lignocellulosic material on the planet and due to their high sugar content. However plant biomass is a complex matrix of hemicellulose and aromatic lignin interacting with core cellulose making it remarkably resistant towards enzymatic saccharification [1,2]. In nature many microorganisms decompose plant biomass by secreting battery of carbohydrases capable of degrading cellulose and hemicellulose. The carbohydrate active enzyme system of bacteria and fungus can be largely considered as complexed or non-complexed enzymes. Several anaerobic cellulolytic bacteria are known to produce cell associated cellulosome. Cellulosome is a large extracellular multicomponent complex containing several cellulolytic and xylanolytic enzymes tightly bound to scaffolding protein. Such an organisation of hydrolases in close proximity to bacterial cell enhances synergy between constituent enzymes and allows efficient uptake of the hydrolysis products by minimizing the distance over which these oligomers needs to diffuse in order to reach host cell. On the other hand, several aerobic fungi and bacteria secrete free form of various carbohydrases that act synergistically on lignocellulose. However, few recent reports documented the formation of multienzyme complex in secretome of aerobic fungi and suggested enzyme complex formation as an effective strategy for efficient hydrolysis in aerobic fungi [3-5]. Protein-protein interaction among these carbohydrate active enzymes has also been proposed to potentially improve their stability [6,7].
A Maximum Likelihood (ML) based OSTBC-OFDM System over Multipath Fading Channels

This paper proposes a space-time block-coded orthogonal frequency-division multiplexing (STBC-OFDM) scheme for frequency-selective fading channels which does not require channel knowledge either at the transmitter or at the receiver. This paper proposed a generalized maximum likelihood estimation decoding algorithm. Due to the orthogonality nature of STBC, the rule for decoding was reduced to a single step. The performance investigation of the proposed system was done over Rayleigh fading channel and also over the Rician fading channel. Simulation results reveal the performance of proposed STBC communication system is near optimum.
Apache Hadoop Yarn Performance Analysis and Tuning through guided Configuration Parameter Setting on Single Cluster

: In recent year huge amount of data generated through various kinds of social networking sites, scientific devices, Sensors is called big data. It is big question how to store, process and analyze these big data. Apache Hadoop Yarn is open source framework which provides solution for big data. Apache Hadoop Yarn provides components like HDFS to store data in locally as well as distributed and MAPREDUCE programming for processing this data. When user deploys Apache Hadoop Yarn, it provides hundreds of default configuration parameters which are common for all kind of jobs which leads to under utilization of or over utilization of resources like CPU, I/O, Memory etc. But in real situation all jobs requires different parameter configuration. In this research Apache Hadoop Yarn performance analysis done through various kind of benchmark like TeraGen, TeraSort, TeraValidate, Word Count, TestDFSIO Read and TestDFSIO Write on single cluster hadoop environment and tune performance through the customization of Hadoop Configuration Parameters. Apache Hadoop Yarn performance is improved through customization of parameter configuration value as compare to default configuration parameter value. Finally provides guided configuration parameter setting value so that it helps other user for performance tuning of apache hadoop.
Wireless Controlling of Electrical Lighting Systems through Digital Signal to Reduce the Complexity in the Electrical Network

: The innovative approach of wireless controlling in electrical lighting systems through electrical digital signal is presented in this study, which can be used to replace the wired wall switches in order to reduce the complexity in the electrical network while enhancing the operational safety. Importantly, the system would facilitate to communicate very effectively without any interference between devices, when more wireless control devices used in large electrical systems in industries and it introduces two way communication for status indication. The developed system consist of a PIC18F452 Microcontroller Unit , a RF Module , a Switch Unit , a Relay Unit , an AC Current Sensing Circuit , a Voltage Regulator and a Power Supply Unit . The central process of constructing the system was designing and implementing the Switch Unit and the Relay Unit to control the electrical load connected to the Relay Unit . The developed system operates on XBee networking protocol IEEE 802.15. 4 and functions within the ISM 2.4 GHz frequency band and are pin-for-pin compatible with each other whereas the effective outdoor distance range is radially outward of 70 m. Moreover, specific advantages and conveniency of using the developed system over conventional wired network is also been discussed.
TREATMENT OF BACTERIA CAUSING BURN WOUND INFECTIONS BY LACTOBACILLUS REUTERI AS A PROBIOTIC

This study aimed to investigate the effect of Lactobacillus reuteri on pathogenic bacteria isolated from burn wound infections. A total of 51 swabs were obtained from patients of both sexes who admitted to AlKindy Teaching Hospital suffering from invasive burn wound infections for the period of November2014 to February 2015.The most common detected pathogenic species were Pseudomonas aeruginosa(43.7%) followed by Staphylococcus aureus (18.7%), Klebsiella pneumoniae (15.6%), coagulase-negative Staphylococci (9.3%), E. coli (4.6%), and each of Ps. putida, Ps. alcaligenes, Enterobacter cloacae, Acinetobacter baumannii, and Stenotrophomonas maltophilia (1.5%). Antibiotic susceptibility of isolates towards 10 commonly used antibiotics showed that all isolates were sensitive to Amikacin and Imipenem except of Stenotrophomonas maltophilia which was resistance to Imipenem. Adversely, all isolates were resistant to the penicillin group with the exception of coagulase-negative Staphylococci which were moderately sensitive to Ampicillin. When used as a probiotic, Lactobacillus reuteri excreted antibacterial activity against the burn wound infections bacteria. The maximum inhibition zone caused by Lb.reuteri concentrated filtrate was achieved against Ps. aeruginosa1 when it reached 18 mm followed by S. aureus17.2, while the minimum inhibition zone (7 mm) was against Acinetobacter baumannii.