Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Test Script Generation from Natural Language Query

: Development and Testing is a very important part of any product development cycle. There exist numerous modules that need to be tested in a product or software after each build. Addition, modification or deletion of new procedures requires thorough testing of the complete product. Test scripts are generated for the ease of testing. It is observed that most of the procedures in test scripts are repeated. Converting natural language query into test scripts reduces the effort of the test engineer by finding relevant procedures in already existing database. The proposed system accepts a natural language query and converts the query into an executable test code using various NLP techniques. This paper explain two methods that are used to generate test script from Natural language query.
Cyphostemma Glaucophilla: Lipid lowering and micro nutrient booster

Cyphostemma glaucophilla is used in treating malnutrition traditionally in the Igala speaking area of Kogi state of Nigeria. [18] had reported its potential in cardiovascular health and in electrolyte balance. The effects of aqueous leave extract of Cyphostemma glaucophilla on lipid profile and plasma electrolytes were evaluated in albino rats. The lipid profile was determined using standard kits obtained from Randox and electrolytes were analyzed using a flame photometer. Significant (p 0.05) effect on the concentration of Hydrogen carbonate. Result has established ethno medical claim on extract in managing cardiovascular health and macro nutrient malnutrition.
Association Rules Mining Using Effective Algorithm: A Review

Association rule mining is one of the most popular techniques of data mining methods whose aim is to extract associations among sets of items in transaction databases. However, mining association rules often results in a very large number of found rules, leaving the database analyst with the task to go through all the association rules and discover interesting ones. In this paper mining association rules has attracted a lot of attention in the research community. Several techniques for efficient discovery of association rules have appeared. However, with the increase in the size of the databases and for efficient decision making, selective marketing, market basket analysis, catalogue marketing industry etc. To reduce the limitation of Apriori algorithm of generating large number of association rules, we proposed an algorithm in this research work. In the proposed method, initially we applied Apriori algorithm in order to generate frequent item-sets and then frequent item-sets are used to generate association rules. KeywordsAssociation rule mining, Apriori algorithm, FP-Growth Algorithm.
TRANSIENT STABILITY IMPROVEMENT OF STATCOM USING PI CONTROLLER

Abstract — Transmission networks of modern power systems are becoming increasingly stressed because of growing demand and restrictions on building new lines. One of the consequences of such a stressed system is the threat of losing stability following a disturbance. Flexible ac transmission system (FACTS) devices are found to be very effective in stressing a transmission network for better utilization of its existing facilities without sacrificing the desired stability margin. Flexible AC Transmission System controllers, such as STATCOM and SVC, employ the latest technology o f power electronic switching devices in power transmission systems to control voltage and power flow.
An Efficient Guilt Detection Approach for Identifying Data Leakages

— In this paper we develop a model for assessing the “guilt” of agents. We also present algorithms for distributing objects to agents, in a way that improves our chances of identifying a leaker. Finally, we also consider the option of adding “fake” objects to the distributed set. Such objects do not correspond to real entities but appear realistic to the agents. In a sense, the fake objects acts as a type of watermark for the entire set, without modifying any individual members. If it turns out an agent was given one or more fake objects that were leaked, then the distributor can be more confident that agent was guilty. A distributor owns a set T = {t1, t2, . , tm} of valuable data objects. The distributor wants to share some of the objects with a set of agents U1, U2,… Un, but does not wish the objects be leaked to other third parties. The objects in T could be of any type and size, e.g., they could be tuples in a relation, or relations in a database. An agent Ui receives a subset of objects Ri ⊆ T, determined either by a sample request or an explicit request:
A Robust Keywords Based Document Retrieval by Utilizing Advanced Encryption System

--------------------------------------------------------------------- Abstract - As the digital data increases on servers different researcher have focused on this field. As various issues are arise on the server such as data handling, security, maintenance, etc. In this paper document retrieval was proposed that efficiently the fetch document as per query. Here hash based indexing of the dataset document was done by utilizing term features. In order to provide privacy for the terms each of this is identified by a unique number and each document has its hash index key for identification. Experiment was done on real and artificial dataset. Results shows that NDCG, precision, recall parameter of the work is better as compare to previous work on different size of datasets.
Review on Cognitive Cellular Network

- All over the world static allocation of spectrum scheme is commonly used which is allocated to specific technology based on various services such as mobile, broadcast or fixed and mobile satellite services. These wireless communication systems are represents 2G and 3G systems with all evolution phases towards 4G systems. The complexity of wireless networks needs a detailed design drafted with great care, especially related to energy efficiency and bandwidth. Bandwidth efficiency is very important parameter, as it is directly related to frequency spectrum, which is naturally core and scarce resource. But using this technique the spectrum allocation is fixed and day by day availability of spectrum is reduced. Many new wireless applications cannot be rolled out due to scarcity of free spectrum. Hence, new technique is introduced which is known as cognitive radio. The cognitive radio has been proposed as the future technology to fulfill the ever growing need of the radio spectrum by allocating the spectrum dynamically without creating any influence for the licensed legitimate users. The digital dividend of 700MHz band creates an opportunity for cognitive radio making broadband wireless access cost effective. Cognitive Radio offers a solution by utilizing the spectrum holes that represent the prospective opportunities for non-interfering usage of spectrum which requires three main tasks-Spectrum Sensing, Spectrum Analysis and Spectrum Allocation. Cognitive Radio Systems are expected to increase the efficiency of the overall spectrum use by availing new sharing opportunities and also to offer more flexibility to applications as an outcome of their capability to adapt their operations to external and internal factors. Spectrum sensing consists of fetching the characteristics for spectrum usage across multiple dimensions and parameters such as space, time, frequency, and code and deciding the type of signals which are occupying the spectrum. In this project, OFDM based Cognitive Radio and Spectrum sensing techniques named Energy Detection Based Spectrum Sensing with Wavelet packet transform and Cyclostationary Spectrum sensing are described and discussed upon.
Design & Analysis of Different Types of Sleepy Methods for Future Technologies

- As low power circuits are most popular now a days as the scaling increase the leakage power in the circuit also increases rapidly, so for removing these kind of leakages and to provide a better power efficiency, we are using different types of power gating techniques. In this paper we are going to analyse the different types of circuits with different types of power gated circuits using low power VLSI design techniques and we are going to display the comparison results between different nanometer technologies. The simulations were done using Microwind Layout Editor & DSCH software.
A REVIEW ON ANGIOGENESIS

Angiogenesis is the extension of blood vessels from the pre existed vasculature. It is an important process which involves the formation and development of blood vessels, so it is supportive in healing of wound while its inhibition may help to restrict the size of tumor. The angiogenesis activity was involved in many physiological and pathological conditions. When this balance is disturbed, the result is either too much or too little angiogenesis. The body controls angiogenesis by producing a precise balance of growth and inhibitory factors in healthy tissues. Excessive angiogenesis occurs in diseases such as cancer, diabetic blindness, age-related macular degeneration, rheumatoid arthritis, psoriasis and for these Anti angiogenic therapies are aimed to halt new blood vessel growth. Insufficient angiogenesis occurs in diseases such as coronary artery disease, stroke, and chronic wounds. Therapeutic angiogenesis aimed to stimulate new blood vessel growth with growth factors is being developed to treat these conditions. Angiogenic gene therapy is also being developed as a method to deliver angiogenic growth factors to the heart, limbs, and wounds. Currently there is no angiogenic gene therapy and drugs approved by FDA for the treatment of ischemic cardiovascular disease. But FDA approved device is used to stimulate NBV to grow in diseased hearts is a laser used in a technique called Direct Myocardial Revascularization.
Environmental Impact Assessment for the Conservation of Environment and Sustainability

Environmental impact assessment is the study that f ocuses on the effects of a proposed project,plan or a programme on the environment. EIA is a relatively n ew planning and decision-making tool. It ensures th at t e potential problems are foreseen and addressed at an early stage in project planning and design. Envir onmental assessment is taken up in this paper as a rapid ass essment technique for determining the current statu of the environment and identifying impact of critical acti vities on environmental parameters. The paper highl ights methodology, evaluation of current stage, legal fra me work, principles of environmental impact assessm ent, and case study,for predicting the environmental consequ ences of any project under consideration for develo pment.
SERUM LACTATE LEVELS IN PROGNOSTICATION OF PATIENTS IN SEPSIS OR SEPTIC SHOCK *Dr

Introduction: multicentric study done on 5,478 ITU admissions, mortality was 59% of which 25% of patient in SIRS with organ dy becomes important to point our focus on early and aggressive measures to reverse sepsis. In a country like India, decision on type and extent of interven Hence, it is one such p help prognosticate. Aims and Objective: determine the better predictor of mortality. 2. non-survivors. Methodology: shock were included in the study and lactate levels were measured at clearance was also calculated. Results: clearance did not show any positive predictive value. An initial lactate levels of 1.45 could be taken as a cut off for predicting Discussion: initial lactate as well as lactate clearance to mortality whereas correlation between lactate clearance and offered to a major concern of financial constraints by relatives. Conclusion: be used as a pa the extent of
Autoimmune thyroiditis – Correlation of clinico-radiological presentation, thyroid profile and cytomorphological spectrum

Background: Thyroiditis is the second most common thyroid lesion next to endemic goitre diagnosed on FNA in iodine (I2) deficient areas. Although FNAC is the gold standard for diagnosis of thyroiditis, accurate diagnosis of a thyroid lesion at FNAC requires not just an in depth study of the cytomorphology but also a thorough clinicoradiological and serologic correlation. Aim: To study and correlate the clinical, radiologic, serologic and cytomorphological spectrum of autoimmune thyroiditis. Materials and methods: Retrospective study involving 150 cases was conducted. Clinical history (age, sex, symptoms with their duration and other signs, other significant medical/surgical history), TFT, were noted from the medical record available with the patient and also from Endocrinology department records. Results: Incidence of autoimmune thyroiditis was found to be 13.4%. Majority of the patients were females (96.7%), 53.3% of cases were seen in the age group of 21-40 years. 80.6% patients had a diffusely enlarged thyroid gland clinically. 92.7% patients showed grade I/II goitre. USG also showed a diffuse enlargement in 85.3% cases. Of the 150 patients with autoimmune thyroiditis, 110(73.3%) patients were euthyroid while 32 (21.3%) patients were hypothyroid at the time of FNAC. Only 8(5.3%) patients showed evidence of hyperthyroidism. 8% patients showed subclinical hypothyroidism. Prevalence of euthyroid autoimmune thyroiditis appeared high in our study. Among the cytomorphological features, presence of lymphocytes was consistently seen in all cases of chronic lymphocytic thyroiditis /mixed thyroiditis. Hurthle cells were seen in 68.6%, eosinophils were seen in 16.6%, giant cells and granulomas were noted in 29.3% and 8.6% cases respectively. L:E ratio was Shweta P. Bijwe, Arunkumar D. Chopwad. Autoimmune thyroiditis – Correlation of clinico-radiological presentation, thyroid profile and cytomorphological spectrum. IAIM, 2018; 5(1): 50-63. Page 51 high in 101 (67.3%) cases ranging from 2:1 to 10. TFC destruction and grade III thyroiditis showed a significant association. Conclusion: Autoimmune thyroiditis was seen more commonly in females. Majority cases were seen in age group of 21-40 years of age. Lymphocytes, germinal centre cells, thyroid follicular destruction and Hurthle cells form important cytological features, while giant cells, eosinophils, granulomas were other cytomorphologic features in the diagnosis of autoimmune thyroiditis. Clinically and radiologically most of patients showed diffuse enlargement of thyroid gland. Majority of patients in our study were euthyroid at time of presentation. Prevalence of euthyroid autoimmune thyroiditis appeared high in our study. TFC destruction and grade III thyroiditis showed a significant association.
Corpus-based Analysis of Collocational Errors

The present study investigates the use of high-frequency verb collocations in L2 learner English. Although it has been widely accepted that collocations are essential to language use, until recently, the complexity of collocations was mainly hidden. However, developments in the new technology of corpus linguistics and the availability of large electronic texts from spoken and written sources have made possible new perspectives to learner language use. In addition, learner corpus data constitutes a new type of performance data which offers a valuable view of learners’ errors and non-errors as well. This study is thus embedded in a combination of elaborate manual investigation and computer-aided analysis using a concordance program, WordSmith Tools. The results of this study show that errors are not entirely mismatch between the verb and the noun, and other types such as prepositional errors and determiner errors were relatively more frequent among advanced L2 learners. It is also found that the interference of the Korean learners’ L1 plays a role in the use of collocations. Based on the results, some suggestions are made for collocation learning that is helpful for EFL learners.
AT-SITE FLOOD ANALYSIS USING EXPONENTIAL AND GENERALIZED LOGISTIC MODELS IN PARTIAL DURATION SERIES (PDS)

Flood Frequency Analysis (FFA) uses both flood peak series, i.e. Annual Maximum Series (AMS) and Partial Duration Series (PDS). AMS analyses number of peaks equal to number of observation years using a single best fit probability distribution, while PDS analyses peaks over a threshold value adopting Poisson distribution (PD) and negative binomial (NB) distribution counting occurrences of peaks (μ) over threshold and exponential distribution (ED), generalized logistic distribution (GLD) or Pareto distribution (GP) for magnitude. Both ED and GLD method are used to analyze at-site extreme flood information in the PDS model at Champua gauging site under Baitarani Basin, Odisha (India). Performances of AMS/PD-ED, AMS/NB-ED, AMS/PD-GLD, AMS/NB-GLD are compared in terms of uncertainty of T-year event estimator. Results show AMS/PD-ED model yields lower variance of T-year estimate than AMS/NB-ED model, while AMS/NB-GLD gives less variance in comparison to AMS/PD-GLD. Results indicate that in case of ED, flood quintiles are acceptable for μ≤8 and T≤500 within 95% confidence limit, while they are comparable for μ≤3 and T≤100 in case of GLD distribution. To summarize, NB distribution is preferred for number of flood peaks if coupled with GLD for flood exceedances and Poisson distribution in case of ED for flood exceedances values.
Design and Development of Abstractness in Graph Mining Technique using Structural Datum

-Graphs are everywhere, ranging from social networks and mobile call networks to biological net-works and the World Wide Web. Mining big graphs leads too many interesting applications including cyber security, fraud detection, Web search, recommendation, and many more. In this paper we describe a technique for the conversion of real-time environment to a Graph Mining pattern. We analyze very large, real world graphs with billions of nodes and edges. Our findings include digraph structures in the connected component size distribution. In the future we will extend our research to propose a GraphTemplateConverter for any real-time complex entities.
Network Data Classification through Artificial Neural Networks and GenClust++ Algorithm

Information systems are becoming more and more complex and closely linked due to the exponential use of internet applications. These systems are encountering an enormous amount of traffic, this traffic can be a normal one destined for natural use or it may be a malicious one intended to violate the security of the system. Therefore, a defense method needs to be in place. One of the commonly used tools for network security is the Intrusion Detection System (IDS). An IDS, while ensuring real - time connectivity, tries to identify fraudulent activity using predetermined signatures or pre-established network behavior while monitoring incoming traffic. Intrusion detection systems based on signature or behavior cannot detect new attacks and fall when small deviations occur. Also, current anomaly detection approaches suffer often from high false alarms. As a solution to these problems, machine learning techniques are a new and promising tool for the identification of attacks. In this paper, the authors present a hybrid approach, combining artificial neural networks and a hybrid clustering algorithm based on k-means and genetic algorithm called GenClust++. The final framework leads to a fast, highly scalable and precise packets classification system. We tested our work on the newly published dataset CICIDS 2017. The overall process was fast, showing high accuracy classification results.
An SMC based RZVDPWM Algorithm of Vector Controlled Induction Motor Drive for Better Speed Response with Reduced Acoustical Noise

22 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. Abstract: In this paper, an sliding mode controller (SMC) based Random Zero vector Distribution PWM (RZVDPWM) algorithm of vector controlled induction motor drive for better speed response with reduced Acoustical Noise is analyzed. In order to mitigate the difficulty faced in the conventional Space Vector PWM (SVPWM) approach, the proposed RZVDPWM algorithm is created by taking the concept of Simplified PWM sequence. This algorithm is developed by using the concept of random number generation technique. Simulation studies are carried out to validate proposed RZVDPWM algorithm, the results obtained are presented and compared. The simulation results shows that the overall performance of SMC based RZVDPWM drive is better when compared to SVPWM technique under different conditions of operation.
Anti-inflammatory and anti-oxidant activity of Dialium dinklagei Harms. (Leguminosae)

Dialium dinklagei is a plant used in the management of pain, arthritis, rheumatism, pulmonary diseases and as a laxative in Ghanaian folklore medicine. However there is no scientific validation of these pharmacological activities. Therefore in this research, the anti-oedematogenic and antioxidant activity of a hydro-ethanolic extract of D. dinklagei was evaluated. In vivo anti-inflammatory activity was done by the carrageenan induced oedema in 7 day old chicks. The antioxidant activity was investigated in vitro by the DPPH radical scavenging and phosphomolybdenum total antioxidant capacity assays. D. dinklagei exhibited a dose-dependent antiinflammatory activity with ED50 of 10.6 mg/kg body weight compared to diclofenac sodium (ED50 = 4.03 mg/kg body weight). It showed considerable antiradical activity (EC50 = 39.6) and a total antioxidant capacity of 581.58 mg of vitamin C per gram of extract. The phytochemicals tannins, alkaloids and terpenoids present in the plant could be responsible for its anti-inflammatory and antioxidant effects. Thus the present study has given scientific credence to the use of D. dinklagei in ethnomedicine for the management of painful inflammatory conditions
Determinants Influencing Fishing Income to the Coastal Households of Indian Ocean

This paper assesses the determinants influencing fishing income of households living in coastal areas of Indian Ocean by using Mafia District, Tanzania as a case study. Data collected by using survey and participatory rural appraisal (PRA) to 120 randomly households. Collected data were analysed both statistically and contently. The result revealed that, there are several economic activities conducted in the study area, where 41.47% of the households indicated that fishing is the major economic activity for their livelihood with average income per day of 24.41 USD (51 250 TZS); whereas, fish related activities contributes 7.14 USD (15 000 TZS) and other economic activities wealth 2.38 USD (5000 TZS) per day. The paper concludes that fishing contributes higher household’s income compare to other activities. The paper recommends the government or other stakeholders to provide credit or subsides in improved fishing gears so as to acquire sustainability.