Miracle-dz/UniFAR-FTUs huggingface dataset:
Production and Characterization of Hydrocarbon Degrading Peroxidase from Rhizopus and Saccharomyces Species

The production, characterization and partial purification of hydrocarbon degrading peroxidase from di-culture of Rhizopus and Saccharomyces species was assessed. The fungi were isolated from hydrocarbon polluted soil and identified using standard microbiological and biochemical techniques. Fermentation was carried out for enzyme production and the extracellular extract was precipitated with 50% ammonium sulphate salts and further purified by gel filtrationusing sephadex G100 gel and by dialysis. The enzyme activity and stability was assayed against varied pH and temperature. Four genera of fungi which included Saccharomyces, Penicillium, Rhizopus and Aspergillus species were isolated from the crude oil polluted soil of which Saccharomyces sp. and Rhizopus sp. produced peroxidase. Maximum enzyme production occurred on day 8. The enzyme activity was optimum at a pH of 4.5 and temperature of 50°C. The Km and VMAX were 1.8 mg/mL and 20.3 µmol/min respectively, against the 5 mM of O-dianisidine substrate. Stability studies showed that the peroxidase was stable in the presence of Ca2+, Mg2+ and Co2+, with Ca2+ showing the best stability. In conclusion, peroxidase was partially purified from di-culture of Saccharomyces and Rhizopus species isolated from crude oil polluted soil. The presence of this enzyme in crude oil polluted soil may suggest its implication in the degradation of crude oil. Further studies need to be done to assess the potential of this enzyme in the degradation of crude oil.
AN EFFICIENT MINING FOR MAXIMAL FREQUENT SEQUENCE PATTERN USING BINARY DIGIT REPRESENTATION AND SAME SUPPORT VALUE

: Mining Sequential Frequent Pattern gives more patterns to user. It is perplex for decision making in business and other applications in Data mining. Because of that the Maximal Closed Frequent Sequential Pattern Mining is proposed by many researchers. However, the Maximal Pattern is mined from vast sequence database which gives more number of patterns. This research paper is proposed the Efficient Maximal Closed Frequent Sequence Pattern (EMaxSPAN) to reduce the processing time and the Patterns by same support threshold value by user given minimum support value. The efficiency is experimented in real time sequence databases.
Boundary Condition in Particle-based Visual Simulation of Plume Fluid

Recently, in the field of CG, the animation of flame or smoke which uses the fluid simulation is researched. In this paper, we researched the particle-based visual simulation of plume fluid. Plume is fluid with a mushroom-like shape. For example, it is explosive flame or cumulus. Plume, such as continuously growing flame or cloud with an expansive gush, is a difficult phenomenon to represent with a high level of reality. We adopted the recursive particle generator for the representation of the plume, and discussed the boundary condition in this case.
Design & Implementation of ANFIS System for Hand Gesture to Devanagari Conversion

-Sign language mainly uses hand gesture for communicate between vocal and hearing impaired people and normal people. It is also used to share message. This research work presents a simple sign language recognition system that develops using ANFIS & neural network. Devanagari language is one of the most used for writing. The system works uses functions like skin color detection, convex hull, contour detection and identification of extrema points on the hand. This is technology which is convert image from video acquisition into Devanagari Spoken language. The database of all alphabets is created first then after feature extraction of all images. The features calculated first then from centroids values trained Neural network. The Algorithms for training neural network is linear vector Quantization. The feature extraction point trained in neural network after that from a new recognizes hand gesture and translate sign language into Devanagari alphabets. The system architecture contains video acquisition, image processing, feature extraction & neural network classifier. This system is used to recognize more alphabets which can sign with one and two hands movement. This system useful to identify the gesture after that sign translating Devanagari language. This project aims to develop and test a new method for recognition of Devanagari sign language. To do so preprocessing, contour & convex based feature extraction is done. The method is evaluated on database and proves to be superior than rule based methods. To identify Devanagari alphabets of sign language, in an image morphological operation and skin color detection is performed. A MATLAB implementation of the complete algorithm is developed and conversion of sign language into Devanagari spoken language with the better accuracy.
PERFORMANCE EVALUATION OF SPEAKER IDENTIFICATION SYSTEM FOR MALE SPEAKER DURING ADOLESCENCE

A voice mutation commonly refers to the deepening of voice of people from early to late adolescent stages. Males experience a more dramatic voice mutation than females during adolescence. This paper presents experiment for performance evaluation of speaker identification system for male speaker during adolescent stages. A text independent, closed set speaker identification system is implemented using Mel-Frequency Cepstral Coefficients (MFCC) and Dynamic Time warping (DTW) algorithms in MATLAB for training and testing of recorded short sample sentences of native Hindi male speaker during adolescent stages for speaker identification accuracy. The system achieved approx 98% speaker identification accuracy for the speech sentences trained against sample sentence of corresponding age but speaker identification performance was insignificant when trained speech sample sentence was of different age from the age of testing speech sentences. The results show strong influence of voice mutation on the speaker identification and the voice biometrics during adolescent stages may need careful sampling of speech data.
METHOD DEVELOPMENT AND VALIDATION OF SIMULTANEOUS DETERMINATION OF HYDROCHLOROTHIAZIDE AND LOSARTAN IN TABLET DOSAGE FORM BY RP-HPLC

Fixed-dose combinations have several advantages comparing with a single drug and separate agents. For simple dosing regimens and their synergistic antihypertensive action, a combination of hydrochlorothiazide and losartan potassium is widely prescribed. In this study, an HPLC-UV method was developed and validated for the simultaneous determination of hydrochlorothiazide and losartan in bulk and pharmaceutical formulation. The method was optimized selecting chromatographic conditions of 60: 40 acetonitrile: water, ACE3-C18 column (250 mm × 4.6 mm 5 μm), 20 μl injection volume, the flow rate of 1 ml/min at ambient temperature (25 °C), and 226 nm. The method was validated giving good precision (RSD% < 1), acceptable linearity (R2 ≥ 0.997), and low LOD and LOQ (0.5 and 1.5 μg/ml, respectively). Successful application on pharmaceutical dosage tablet form gave recovery percent within acceptance criteria (92% and above) indicating that the proposed method is simple and reliable for the determination of LOP and HCTZ and hence can be applied for routine analysis in quality control laboratories. INTRODUCTION: Hypertension or high blood pressure is a chronic medical condition in which the blood pressure in the arteries is elevated. It is one of the most prevalent vascular diseases and considered as the main risk factor for cardiovascular, cerebrovascular, and peripheral vascular diseases that include coronary disease, stroke, peripheral artery disease, renal disease, and heart failure. Treatment with many medications known as anti-hypertensives is available to lower high blood pressure, and they include some different classes of drugs. QUICK RESPONSE CODE DOI: 10.13040/IJPSR.0975-8232.10(1). 227-31 The article can be accessed online on www.ijpsr. com DOI link: http://dx.doi. org/10.13040/IJPSR.0975-8232.10(1). 227-31 Fixed-dose combinations have many benefits comparing with a single drug and separate agents. Clinical practices proved that using combinations of antihypertensive drugs with complementary mechanisms of action is a marked increase regarding effects to reduce blood pressure levels more rapidly, convenience, improving treatment compliance, and low-cost treatment of hypertension 1 . Combination of hydrochlorothiazide and losartan potassium is widely prescribed by the physicians due to simple dosing regimens and their synergistic antihypertensive action, improved hypertension control and fewer dose-dependent side effects 2 . So it is essential to develop a simple method for simultaneous estimation of HCT and LOP in a combined formulation. Hydrochlorothiazide chemical name is 2H-1, 2, 4-Benzothiadiazine-7sulfonamide, 6-chloro-3, 4-dihydro-, 1, 1-dioxide Fig. 1.
Association Rule Mining Using Particle Swarm Optimization

: Data mining is the process of discovering new relevant information in terms of patterns from large amount of data. Association rule mining is one of very important data mining techniques. Swarm optimization is a new subfield of artificial intelligence which studies the cooperative performance of simple agents. In this paper, proposed a new efficient algorithm for exploring high-class association rules by particle swarm optimization (PSO) algorithm. The proposed method mine interesting and understandable association rules without using the minimum support and the minimum confidence thresholds in only single scan. To prove the practical significance of the approach, this approach is implemented on Microsoft Visual Studio 4.0. Experimental evaluation shows the efficiency of proposed algorithm in terms of computation time.
Awareness of Air Pollution through IoT

: At present the ambient Air is polluted with hazardous gases emitted by motor vehicles, home electronic appliances and industrial factories. The ambient air is polluted with higher levels of the hazardous gasses like Particulate Matter, Nitrogen Dioxide, Sulphur Dioxide, Carbon monoxide, Ammonia etc. This polluted air is adversely affects the health of humans, animals, birds and the growth of trees. The Nature and its beautiful treasure are damaging a lot. So, how to avoid these adversaries of polluted air? If we aware the people with the information of toxic levels of harmful gases in ambient air, then people can take precautions about their health and they can think about the reduction of the air pollution. This awareness of air pollution can be give to the people by using Internet of Things (IoT) applications. There are several IoT applications available to know the air pollution levels. Those are Breezo Meter, Plume Air Report, Safar Air etc.
Performance Analysis and Validation of Fuzzy based Secure LAR Routing Protocol in MANETs using NN Tool

---Artificial neural network can be used for predicting because of having the capability of examining and determining the historical data used for prediction. ANN has better accuracy than statistical and mathematical models. ANN works on the principle of biological neurons which is a type of data driven technique. The training simulation results indicate the feed forward back propagation model two input neurons and one output unit produce best predictive results for neural network. By varying the simulation, train the neural network in the performance function namely LAR, Secure LAR and FZ-S-LAR, the transfer functions TRANsig to validate the results. The results obtained after training the data under different scenarios mse gives better validation results. The errors obtained the training errors for mse is 0.99571, testing error is 0.98694 and validation is 0.98496.
Design and Fabrication of Mechatro Hand

The main objective of this work is to design and fabricate an artificial robot hand to mimic the human hand. Each finger in the hand had fifteen degrees of freedom and capable of applying independent forces to grasp an object. Forward and Reverse kinematics has then been done on the designed hand using D-H method in order to find joint angles for the different configurations. Keywords—Mechatro Hand, Kinematic Analysis, Denavit-Hartenberg (D-H), Flex sensors.
Social CRM: A Survey on Various Techniques for Text Analysis in Social Media

— Customer relationship management (CRM) refers to practices, strategies and technologies that companies use to manage and analyse customer interactions and data throughout the customer life cycle, with the goal of improving business relationships with customers, assisting in customer retention and driving sales growth. CRM systems are designed to compile information on customers across different channels which includes the company's website, telephone, live chat, direct mail, marketing materials and social media. CRM systems can also be analysed to get informations like the purchase history, buying preferences and concerns. In this era where everyone is connected through social media, the relevance of improvement over CRM by analysing the opinions expressed by the customers can provide useful insights. Social networking websites, such as Facebook, Twitter etc. are rich in texts that enable user to create various text contents in the form of comments, wall posts, social media, and blogs. Due to ubiquitous use of social networks in recent years, an enormous amount of data is available via the Web. Application of text mining techniques on social networking websites can reveal significant results related to person-to-person interaction behaviours. In this paper an effort is made to understand the necessity of social CRM, which enables us to find general opinion about any specific subject, human thinking patterns, and group identification in large-scale systems . The various techniques used for text analysis are discussed.
Evaluating the Relationship between Calendar Anomalies and Stock Return of TSE Listed Companies

To expand the financial literature and also in view of the necessity of updating in today's knowledge of the world, this research examines one of the most recent issues of financial management, means science of behavioural finance that is dedicated to the behavioral character of the capital market and the study of the behavioral and psychological aspects of the capital market. In this field, one of the interesting topics is the calendar effects that deal with the anomalies in behavior and performance of market in different times of day, week, month and year. The problem that follows in this study is to investigate the relationship between weekdays, including the categories of periodic or calendar effects, on stock returns, and claims that there are heterogeneous returns on different days of the week, at that time, it would be possible to generate extra returns by formulating strategies for these daily patterns. To achieve this goal, five hypotheses have been formulated and 160 companies were selected from listed companies in the Tehran Stock Exchange for a period of 5 years, 2012 to 2016. The method of this research is applied and descriptive-correlational. To test the hypotheses, linear regression model and panel data are used. The results of testing the hypotheses show that there is a significant relationship between calendar events and stock returns and the effect of Tuesday has been significant in estimations.
Bayesian Spam Filtering In Online Social Networks

: Online Social Networks offer for social interactions and information sharing among peoples, but it includes security and privacy issues. OSNs allow users to limit access to shared data; OSNs currently do not provide any mechanism to enforce privacy concerns over data associated with multiple users. To overcome this, we put forward an approach which supports the protection of shared data associated with multiple users in OSNs. We are developing an access control model to capture the core of shared authorization requirements, along with a multiparty policy specification scheme and a policy enforcement mechanism.
Computations Preserving Privacy for User Shared Images with Discovering Friends in Social Networks

-At present, billions of user shared images are generated by individuals in many social networks daily and this particular form of user data is indeed very accessible to others due to the nature of online image sharing. Some users also hide or limit the information of their connections from the public in social media platforms due to privacy concerns. Accessing these SGs is getting more difficult and costly in today’s online social networks, and novel applications using SGs become almost impossible to be offered independently by third-party practitioners and individuals. IndexTerms—bigdata, Connection, Discovery, Recommendation, Social Network Analysis, User-Shared Images.
Is Cyclic Stimulation of the Breast Epithelium the Key Hormonal Factor Behind Breast Cancer

Exposure to many regular menstrual cycles during a life time or many cycles before first full term pregnancy may be a key factor behind the hormonal stimulation of the breast epithelium and the hormonal carcinogenesis. Most of the risk factor studies on the breast cancer and cycle characteristics were done before 2010. A consistent picture emerges that many regular cycles is an important risk factor and that early age at menarche, late menopause, few children, and late age at first full term pregnancy, short nursing and a short interval between onset of menses and establishment of regular menses may be surrogates for this risk. A majority of studies have been retrospective often using for cycles average cycle length recorded at one occasion. There is a great need to do large prospective studies following women for a life time. Valid data on menstrual cycle characteristics is needed for creating optimal risk factor models.
Review on Cognitive Radio Network

-As the increased demands of wireless channel, there is the need for the proper utilization of the spectrum which leads us to the new technique called cognitive radio technologies. Static spectrum allocation need to merge with a technique where it can be share for the proper utilization of the spectrum. Higher capacity requirement is of great need. As long as the technology is been evolving the requirement of more capacity is also increasing. This paper gives an overview on different work done for increasing capacity over the years.
Efficient Load Balancing and Service Broker Policy Using Local and Global Representatives in Cloud Computing

Cloud computing is a technology in the field of computing which offer services to the customer from anywhere at any time [1]. In the cloud, resources are shared all around the work for quick servicing to the customer. The aggregation of two terms is referred as cloud computing. The term “cloud” is a pool of different resources offers services to the end customers and “computing” is done based on the Service Level Agreement (SLA) to make the resources efficiently to the customers. Load balancing is an important challenge in the environment of the cloud to increase the utilization of resources [3]. Here we proposed an algorithm which is based on load balancing and service broker policy. We user two representative thin the proposed approach local representative and global representative Local user representative is used to predict the parameters of user task and based on priority it allocate the task to the Virtual Machine (VM). Then for scheduling the task and provide the services to the users based on the available cloud brokers global user representative used Dynamic Optimal Load-Aware Service Broker (DOLASB). we used two scenario with different no. of user requests , in these scenario result of our proposed method is better as compared with the other existing methods in terms s of Execution Time, Makespan, Waiting Time, Energy Efficiency and Throughput.
Affine Control Systems

In this paper we deal with affine control systems o n non-compact Lie group cx+e group. First we study topological properties of the state space Ef(1) and the automorphism orbit of Ef(1). Affine control system, non-compact Lie group state space Ef(1). Affine control systems on the generalized Heisenberg Lie groups are studied. Affine algebra, automorphism Keyword: Affine algebra, automorphism non Lie group, state space Ef(1), automorphism orbit of Ef(1), affine control system. INTRODUCTION The purpose of this paper affine control systems on some specific lie group is called cx+e group by relating to associated bilinear parts. Related to the affine control system on lie groups, in Ef(1). The authors Ayala and San Martin have the su b algebra of the Lie algebra Ef(G) generated by the vector fields of a linear control system the drift vector field X is an infinitesimal automorphism i.e.,( is a oneparameter subgroup of Aut(G); have lifted the system itself to a rightinvariant control system on Lie group Ef(1) for compact connected and non semi-simple Lie group. The affine control systems on a non group cx+e group have been investigated and given characterization. 1. Affine Control Systems on Lie Groups If G is a connected Lie group with Lie algebra L(G) , the affine group Ef(G) of G is the semi of Aut(G) with G itself i.e., Ef(G) = Aut(G) group operation of Ef(G) . | Volume – 2 | Issue – 5 | JulAug 2018 6470 | www.ijtsrd. com | Volume Journal of Trend in Scientific and Development (IJTSRD) International Open Access Journal n Non-Compact Lie Group , G. Pushpalatha , 2Assistant Professor Vivekanandha College of Arts and Sciences for Women, Namakkal, Tamilnadu, India
MR-proANP and Procalcitonin improve survival prediction in Ventilator Associated Pneumonia

From the Clinic of Pulmonary Medicine and Respiratory Cell Research, 1 Division of Anesthesiology and Surgical Intensive Care Medicine, Division of Medical Intensive Care Medicine, University Hospital, Basel CH-4031, Switzerland; Department of Adult Critical Care Medicine, University Hospital, CH-1011 Lausanne, Switzerland; the Division of Pulmonary, Allergy and Critical Care Medicine, 5 UMass Memorial Medical Center, 01655 Worcester, MA, USA; and the Harvard School of Public Health, 6 02115, Boston, MA, USA
Sociodemographic and cultural determinants of seeking family planning knowledge and practice among a Sudanese community

Pregnancy related health consequences remained a part of public health concern, which has to be considered for women in Sudan. Family planning as mentioned by the United Nations is the first pillar for safe motherhood. As stated by the World Health organization (WHO) “Family planning: allows people to attain their desired number of children and determine the spacing of pregnancies. It is achieved through use of contraceptive methods and the treatment of infertility”.