Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of supplementary feeding of azolla (Azolla pinnata) on carcass quality and biochemical parameters of broiler

An experiment was conducted at Poultry unit, Deptt of Animal Husbandry and Dairy Science, Dr. B.S. Konkan Krishi Vidyapeeth Dapoli, Maharashtra to determine effect of Azolla feeding on carcass quality and biochemical parameters of broilers. A total 120 chicks (144) were reared together until 9 days of age in brooding stage. On 10 day, the chicks were weighed individually and distributed randomly into four dietary groups with five replications and each replication have six chicks. A control diet (T0) containing 0.0 % Azolla and three experimental diets in which Azolla was partially (5% T1), (10% -T2) and T3 replaced (15%) by Azolla (Azolla pinnata) were prepared. The results showed that 10 per cent azolla meal significantly improved live weight (2464.46 g), carcass weight (1932.20 g) and dressing percentage (72.47 %). The blood biochemical parameters investigated are viz., hemoglobin (Hb), glucose and total protein. The data revealed that Hb, glucose and total in normal range. Therefore, it can be concluded that Azolla meal @ 10 per cent in the diet of broilers used for improved carcass quality and biochemical parameters.
International Journal of Advance Research in Computer Science and Management Studies

In commercial public cloud the cloud computing enables the model of data service outsourcing. In this project, we define and solve the problem of ranked keyword search over cloud data. Ranked search greatly enhances system usability by enabling search result relevance ranking instead of sending undifferentiated results and further ensures the file retrieval accuracy. We explore the statistical measure approach i.e. relevance score, from information retrieval with focus on ranking and several components of an information retrieval system to build a searchable index.
Resilient Back-Propagation Neural Network Based Breath Analysis System for Non- Invasive Prediction of Blood Glucose

Diabetes is a global epidemic now with millions of people and the number is continuously on the rise. The diabetic patient has to monitor the blood glucose levels throughout the day at regular intervals of time for proper diagnostics. But, most of the blood glucose monitors present in the market are invasive and the patient has to prick the skin for collecting the blood sample. To ease this sort of suffering there is a need to develop non-invasive methods for the blood glucose detection. This paper explores the use of neural networks based upon resilient back propagation for detecting the blood glucose by monitoring the acetone levels in the breath sample. Sample hardware has been developed having several sensors for detecting the acetone levels in the breath. The developed hardware has been used in conjunction with the designed neural network for the non-invasive detection of the blood glucose.
Preventing Cyber Attacks Against Smart Grids Using UTM Devices With A Mutual Efficient Authentication Protocol

— Smart grids are bilateral interconnected networks in which, data and information play a crucial role in the process of energy distribution. Thus, according to increasing development and complexity, they are mentioned as the cyber-physical systems. Obviously, the security and economic situation of countries are largely dependent on performance stability and safety of these systems. According to the high dependence of the smart grids to measurement sensors and communication technologies, these networks are very vulnerable to cyber attacks. Load reduction (LR) attacks that lead to false data injection (FDI) on Advanced Metering Infrastructure (AMI) sensors and produce the misleading operational decision of the power system are too important among all cyber attacks. So we proposed an efficient authentication protocol with identity protection for smart grids based on elliptic curve cryptography in which the substations and smart appliances realized mutual authentication and key agreement via a tamper-resistant smart card so that the adversary cannot obtain the real identities of them. As a result, the attacker cannot begin a cyber attack with impersonation and false data injection.
Retrospective Audit on the use of Albumin-Bound Paclitaxel (Nab-Paclitaxel) and it`s Outcomes in Dubai Hospital

Submit Manuscript | http://medcraveonline.com Abbreviations: SB: Solvent-Based; Nab-Paclitaxel: AlbuminBound Paclitaxel; FDA: Food and Drug Administration; DHA: Dubai Health Authority; DH: Dubai Hospital; MTD: Maximum Tolerated Dose; AUC: Concentration-Time Curve; PFS: Progression-Free Survival; OS: Overall Survival; ORR: Objective Response Rate; ECOG: Eastern Cooperative Oncology Group; RECIST: Response Evaluation Criteria in Solid Tumors; NSCLC: Non Small Cell Lung Cancer
BIOTRANSFORMATION OF PROGESTERONE TO 17Α-HYDROXYPROGESTERONE BY USING PLANT CELL SUSPENSION CULTURE OF CATHARANTHUS ROSEUS

Objective: The present investigation was aimed to perform biotransformation potential of Catharanthus roseus. Methods: Cell suspension culture of C. roseus were prepared by using Murashige and Skoog medium. Biotransformation of an important bioactive progesterone (4-pregnane-3, 20-dione) was confirmed by cell suspension culture of Catharanthus roseus . Results: Progesterone, which was used as precursor in cell suspension culture, was found to be bio transformed within three days into a new product through a regioselective hydroxylation process. The results confirmed that most of the progesterone added, was hydroxylated at its 17α-position leading to 17α-hydroxyprogesterone as a major biotransformation product after twelve days of incubation with 20% v/v cell density. The optimum biotransformation was achieved with the concentration of 100μg/ml progesterone at pH 5.5. Similarly, glucose was found as the most suitable source of carbon. The optimum incubation time was observed to be 12 days at 20% v/v cell density. Also higher progesterone biotransformation was observed using un immobilized cells as compared to immobilized cells. Conclusion: The results of present work suggest that C. roseus can successfully biotransformed to the product similar to an original organic substrate, which is entirely synthetic. Such a biotechnological process could be of great interest for production of new chemical compounds like cortisone, hydroxycortisone and other important steroids.
Direct Torque Control of Induction Motor using3 Level and 5 Level PWM Inverter

Multilevel inverter technology is being used in multitude of high-voltage, high-power energy systems which include high-power drive applications for electric vehicles,mills, conveyors, pumps, fans, blowers, compressors, etc. Multilevel inverters offer considerable inherent advantages as compared to their two-level counter parts.Multilevel inverter circuit is obtained by connecting number of smaller discrete voltage sources so they generate the output voltage waveforms with more steps of smaller magnitudes, which is more closer to sine wave. The problems associated with two level inverters are electromagnetic interference, switching losses, switch voltage stress, and harmonic distortion. Field Orientation Control and Direct Torque Control are two well-known, high performance methods for speed control of induction motors Out of these two methods motor control by direct torque control has become more popular.It gives high dynamic performance of instantaneous electromagnetic torque. The major attributes of DTC method are ability to achieve fast response of torque and flux, simple control scheme, less computational requirements and offers decoupled control of torque and flux. Work presented in this paper deals with simulation of Direct Torque Control of Induction Motor Drive using Three Level and Five Level PWM Inverter using Diode Clamped Multilevel Inverter topology, simulations of are carried out in MATLAB/SIMULINK Keywords—Multilevel inverter, diode clamped multilevel inverter, direct torque control(DTC),space vector pulse width modulation (SVPWM), torque ripple, flux ripple.
Spectrum Sensing Algorithms for Cognitive Radio Systems

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of cognitive systems is spectrum sensing, that consists the analysis of the radio frequency spectrum. In particular, CR has been mainly studied in the context of opportunistic spectrum access, in which secondary devices are allowed to transmit avoiding harmful interference to higher priority systems, called primary users. Thus cognitive nodes must implement signal detection techniques to identify unused bands for transmission. We focused different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. We consider the presence of practical impairments, such as parameter uncertainties, and analyze algorithm design. We aim at providing contributions to the main classes of sensing techniques, from basic energy detection, to cooperative eigen value based algorithms, to wideband approaches, touching also simple localization strategies for CR networks. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the unknown noise power is estimated at the receiver. This analysis allows deepening the phenomenon of the Signal-To-Noise Ratio (SNR) wall, providing the conditions for its existence. This work highlight that the presence of the SNR wall is deter-mined by the accuracy of the noise power estimation process.
Opportunistic Relaying in Cooperative OFDM Networks with Limit Feedback

—In cooperative OFDM networks, subcarrier mapping (SCM) scheme is an efficient solution to evidently improve the average system capacity. However perfect channel state information (CSI) of each subcarrier is required, which leads to large feedback amount of CSI. In this paper, we considered the scenario of multi-relay OFDM relay networks with limit feedback CSI, in which subcarrier mapping scheme is adopted. An opportunistic relaying strategy is proposed. The transmission scheme, which is based on instantaneous channel quality, is selected to offer maximum the end-to-end system capacity. The simulations show that the proposed solution can achieve almost asymptotically performance as full CSI feedback scheme with large number of subcarriers.
Residual Life Assessment of Concrete Structures-A Review

Reinforced concrete (RC) structures constructed over decades ago approaching the end of their service life, show serious level of deterioration and hence assessment of service life of structural materials and components is gaining significance. With the increased efforts of researchers, development in computer knowledge and advancement in building materials science, prediction of service life of structures is possible. Recently, computational methods such as Finite Element Method (FEM or FEA), Finite Difference Method (FDM) and Artificial Neural Network (ANN) are becoming popular among researchers for modeling the service life of reinforced concrete structures. This paper presents the methodologies for residual strength evaluation of concrete structural components using Linear Elastic and Nonlinear Fracture Mechanics Principles.
Comparative diagnostic method of herpes encephalitis by LAMP (Loop- Mediated Isothermal Amplification) and MRI (Magnetic Resonance Image) method in Tertiary Care Center

Herpes Simplex Encephalitis (HSE) is the most common cause of fatal sporadic acute encephalitis occurring worldwide, contributing to 10-20% cases of viral encephalitis. The present study was aimed to which method cheap, rapid and cost-effective method in the diagnosis of herpes simplex encephalitis (HSE). Out of fifty cases of suspected HSV encephalitis, seven cases were positive magnetic resonance image (MRI) that shows T2 hyperintence lesion in temporal lobe. Five by loop-mediated isothermal amplification (LAMP) method. Maximum number of cases was seen in 13-20 years of age group. As compared to MRI, LAMP method is 71.4% sensitive, 100% specific with positive prediction value of 100% and negative prediction value of 93.48%. MRI findings are common in all confirmed cases of HSV encephalitis i.e. hyper intense signals on T2W1 in median temporal areas. We concluded that MRI is best investigation in diagnosis of HSE but is costly and not available in rural and semi urban area of developing countries like India. Although LAMP method is cheap, rapid and cost-effective method in the diagnosis of HSE.
Production and Application of Phosphate Solubilizing Bacteria as Biofertilizer: Field Trial at Maize Field, Uchalan, Burdwan District, West Bengal

Soil microorganism plays an important role in regulating the levels of carbon, nitrogen, phosphorus and sulphur at the rhizosphere. Solubilization of macronutrient is an important aspect in plant growth and development research. Phosphorus is one of the vital nutrient required for optimum growth of plant. Phosphate Solubilizing Bacteria (PSB) plays an important role in increasing the phosphate uptake by the plants. Pikovskaya medium containing TCP or tricalcium phosphate helps in isolation of PSB from soil sample. Isolated strains were tested and screened by Halo zone formation and pH test. The selected strains showing marked decrease in pH and clear zone formation was selected for field trial. The objective of this study was to ascertain that PSBs isolated from the soil sample can be used as biofertilizer. Application of PSBs with a carrier mixed with maize seeds in the field of study and compared against a control field and against commercially available fertilizer showed that PSBs can improve the quality of soil and in turn improved the growth and development of the plants. Keywords— Biofertilizer, Phosphate Solubilizing Bacteria, chemical fertilizer, plant growth, soil fertility, field trial.
Design Of Wide Band Microstrip Bandstop Filter With Open-Circuited Stubs For Wireless Communication Applications

— Filters play an important role in most RF and Microwave applications. Currently, the electromagnetic spectrum is limited, and the applications are restricted to occupy just a portion of frequency range without affecting the equipment working out of band and also, without being affected by adjacent devices. Emerging applications such as wireless communications continue challenging RF/Microwave filters performance with even more stringent requirements, higher performance, smaller size, lighter weights, and low cost. Depending on the requirements and specifications, filters can mainly be designed with lumped or distributed elements. This paper describes the design of a newly proposed wide band micro strip band stop filter with open circuited stubs. This paper represents the design, simulation and fabrication of wideband bandstop filter using microstrip which is designed to have a center frequency of 2.5GHz. The filter is fabricated on a FR-4 substrate having dielectric constant 𝜺 𝒓 =4.4 and thickness h=1.6mm. Microstrip technology is used for simplicity and ease of fabrication. The design and simulation are performed using method of moments based electromagnetic simulator IE3D.
Survey of Clustering Applications

— Data mining is the process of collecting and analyzing useful patterns from huge amount of data, it has five major functions, clustering is one of them. In clustering, we make clusters of same data. The items in one group of cluster are alike while different from items which are in some other group of cluster. In image segmentation clustering approach is used for making segments of images and identifying the disease, for this purpose the Fuzzy C-means algorithm is used. Clustering is used in social network analysis using collaborative filtering recommendation, in which memory-based and model-based algorithms are used. K-means algorithm is used in credit card fraud detection for identifying the clusters. It works along the HMM model for identifying credit card frauds. In medical world for disease analysis an improved Fuzzy C-means algorithm which is termed as 3SW-FCM algorithm is used which can analyze the characteristics of disease and provide an accurate base for doctor’s diagnosis. Greedy Agglomerative technique is a clustering category used for combining objects together grounded on resemblance which is used in grouping with respect to
A Heuristic Approach to Achieve Optimal Capacity and Reduction in Bit Error Rate for MIMO based Land Mobile Satellite System

The proposed technique is a heuristic approach to transmit beamforming, an improved BER performance is achieved in the absence of channel statistics. The heuristic beamforming approach based on signal processing technique enables the realization of an alternative to ensure a relatively high degree of satellite coverage directionality without increasing the complexity of satellite payload capability. This paper proposes transmit beamforming in the absence of channel statistical measures. Based on this, system parameters such as Capacity and BER are analyzed. The results obtained are in line with the theoretical values . It is observed that a SNR of 10 dB results in a BER of 10 -3.8 for 16 QAM which is a significant improvement over the conventional technique which has a BER of 10 -0.5 for the same signal to noise ratio value.
The Use of Artificial Intelligence in Forest Product Manufacturing: A Lowcost Improvement in Competitiveness

On the other hand, the wood product manufacturing industry is characterized by significant competition, high variability in customer's requirements, and the need to develop more and more price competitive products. These interrelated factors force manufacturers to continuously adjust, control and optimize their manufacturing parameters in order to develop products of higher quality that better fit the customer needs at a lower cost.
Isometric Relocation of Data by Sequencing of Sub-Clusters for Privacy Preservation in Data Mining

— Privacy preservation in data mining is a pioneering research area as the security of increasing amount of data is under risks. Privacy preservation in Data Mining [PPDM] is a delicate task as there is a trade-off between data Anonymization and their utility. Existing PPDM techniques uses Anonymization using randomization, generalization or suppression which reduces the utility of data. They also do not work on the data mining parameters like correlation, centroids etc., This paper provides a solution to handle this trade-off in an efficient way using Isometric relocation. The work uses isometric relocation as it maintains the correlation and data mining results. The methodology is explained with the algorithm and its performance is compared using real-life datasets with existing techniques on various metrics after exhaustive experimentations.
Comparison of Algorithms for Solving Traveling Salesman Problem

— Travel Salesman Problem is one of the most known optimization problems. While an optimal solution cannot be reached, non-optimal solutions approach optimality and keep running time fast. In this paper, the most used algorithms to solve this problem are comparedin terms of route length, elapsed time and number of iterations. The TSP is simulated using different scenarios examples and the convergence is checked for each case.
Program Development For Energy Demand Forecasting And Its Application For A Site

Demand forecasting is defined as a prediction of the amount of electrical energy, peak power demand and number of customers made by marketing companies in order to make energy planning for the future by setting different scenarios at certain time intervals [1]. Demand forecasting is analyzed in three different topics; short, medium and long term as terms. In the application stage of this study, short term demand forecasting is emphasized, and two different forecasting models are created based on the total load and the region by using artificial neural network method. Forecasting process was performed with these two different models. The results were compared and the failure rate of the models was tried to be reduced. In creation of the models, Artificial Neural Network method was used. As a result, the average failure rate of the model based on the total load was 7.04% while the average failure rate of the model based on regional load was 7.66% according to the randomly selected forecasting values for a week.
Readability Improvement in JAVA language by Using Segmentation Techniques

: With the goal of increasing program readability for easier understanding, coding guidelines often include formatting standards such as indenting loop and conditional branch body statements. Similarly, good programming practice suggests that programmers use blank lines to visibly delineate between code segments that represent different algorithmic steps or high level actions. Unfortunately, programmers do not always follow these guidelines. While editors and IDEs can easily indent code based on syntax, they do not currently support automatic blank line insertion, which presents more significant challenges involving the semantics. This paper presents a heuristic solution to the automatic blank line insertion problem, by leveraging both program structure and naming information to identify “meaningful blocks”, consecutive statements that logically implement a high level action. It is a technique to do segmentation in the Java code. Such Segmentation in the code will result in an efficient way of handling the program, finding the bugs and readability of the program. The technique relies on identifying those blocks which are meaningful and have a comprehend structure.
Global Leadership: A Privation for Global Corporate

MNEs, small and medium-sized enterprises (SMEs) and born global are all representatives of a changing business environment, by their participation in international business. Where international business is a term used for describing businesses ability to move factors of production across countries in order to gain a competitive edge. International business opportunities illustrate the choices a business face today (Czinkota et al., 2009).
ELK Asia Pacific Journals – Special Issue ISBN: 978-81-930411-4-7 SOLVING MULTI-OBJECTIVE PROBLEM ON SUPPLY CHAIN PERFORMANCE MEASURE BY MULTI- OBJECTIVE EVOLUTIONARY ALGORITHM

In this paper, we have proposed a new multiobjective supply chain problem related to the performance measure of a supply chain. The problem consists of four objectives, viz., 1) minimization of total cost, 2) minimization of total inventory, 3) minimization of bullwhip effect, and 4) maximization of service level. These four objectives are the expressions for the four performance measuring factors for a supply chain. The problem has been solved by two algorithms – 1) modified Nondominated Sorting Genetic Algorithm-II (NSGAII) and 2) the original NSGA-II. Comparison between the experimental results for the two algorithms shows that the proposed modified NSGA-II performs significantly better than the original NSGA-II. Keywords— Multi-Objective Evolutionary Algorithm, Nondominated Sorting Genetic Algorithm-II (NSGA-II), Supply Chain, Performance Measure