Miracle-dz/UniFAR-FTUs huggingface dataset:
191-195 Leela Kaur

Heavy metals are the most common non-biodegradable pollutants. Various remediation methods have been used for the treatment of heavy metal contaminated water. However, phytoremediation technology is currently being used due to its economically feasible and ecologically viable advantages. The aim of this study was to examine the role of pH in the accumulation capacity of Lemna minor in Pb and Ni contaminated water. The removal rate of Pb and Ni from L. minor was 99.99% and 99.30% respectively, after 28 days of exposure to the 10 mgl Pb and Ni contaminated water at pH 5-6 and pH 6 respectively.
Paper—Family Volunteers as Alternative Future Resources: School Leaders’ Belief and Practices Family Volunteers as Alternative Future Resources: School Leaders’ Beliefs and Practices

Schools and community engagement are seen as effective factors for making schools a thoughtful place. This casestudy employed mixed methodology to explore the phenomena of parent involvement and to know the exact characteristics of the leadership style in the school. This case study examined and described school leaders’ perspectives, attitudes and practices towards parents’ involvement in an Abu Dhabi primary school using a variety of data sources including, interviews, open-ended teachers’ questionnaires, school selfassessment surveys and mothers’ council self-assessment surveys. The findings revealed that the school leaders effectively employ multiple collaborative, shared and transformational leadership practices to improve parent/family volunteering. Teachers and parents have good communications. The mothers’ council and the administration enhanced many different parental activities. There are some barriers in parents ‘participation like language and the lack of the awareness of important role of parents in the school. The implications of this study revolve around the important roles the school leaders have in helping parents feel supported and encouraging family volunteering. The school leaders have to increase the encouragement of parents’ involvement in general and family volunteering in particular. This study is a calling for a shift from random acts of parents’ involvement to coherent, comprehensive, continuous, systematic and equitable family volunteering approach. Keywords—Family volunteering, school – family partnerships, family engagement, school leaders, parents’ involvement, Collaboration, transformational and shared leadership, and family volunteering.
BIG FIVE PERSONALITY FACTORS CONTRIBUTION IN SMUGGLING CRIME

The current research aims to the identification of the personality types of smuggling criminals and nonsmuggling criminals. Hypotheses were these, they’re more likely to be smuggling criminal’s personality extroverted. There to be more likely non smuggling criminals have introverted personality. There is significantly difference in smuggling criminals and non smuggling criminal’s behavior. For this purpose, IPIP big five personality scale was administered to a sample volume of (N=100) individuals from which (n= 50) were smuggled criminals selected from different jails of Hazara division and (n= 50) were non smuggling criminals from Hazara division by applying a purpose sampling technique, the statistical parametric independent t test method was applied to confirm or reject the research hypotheses. The research findings approved the hypotheses and suggest there significant differences between the smuggling criminals and non-smuggling criminals types of personality. Results findings exposed smuggling criminals commonly more posses the extroverted personality.
Synthesis and Characterization of Silver Nano Particles using Tecoma Stans Flower Extract

Metallic nanoparticles are mostly used in every phase of science and technology including medical fields and are still attracting the scientists to explore new dimensions for their respective worth which is generally attributed to their corresponding small sizes. The silver nano particles have attained a special focus among various noble metal nanoparticles due to their anti microbial significance. In the proposed method, to avoid the usage of harmful chemicals colloidal silver nano particles are obtained using green synthesis method which is eco friendly and cost effective. In this reaction, Tecoma stans flower extract is affianced to serve reducing and capping agents. During synthesis of nanoparticles , the parameters silver ion concentration, plant extract volume and reaction time have been studied. To reveal the nature of the nanoparticles, the synthesized nano particles are characterized using ultraviolet–visible (UV–vis) spectroscopy, x-ray diffractometry (XRD), transmission electron microscope (TEM), and particle size analysis (PSA). The size of the nanoparticles are ranging from 20-50nm. The high-density uniform nanoparticles can be obtained by optimizing the experimental conditions. The uniform and stable silver nanoparticles are prepared in this method.
Syzygium polyanthum (Wight) Walp. leaves extract as the antifungal agent for oral candidiasis

Fungal infections are common diseases throughout much of the world. In humans, these infections occur when an invading fungus colonizes an area of the body and overgrowth so the immune system cannot handle it. There are millions of fungal with different species on earth and about 300 of those are reported cause human diseases. [1-3] In human, Candida albicans is the most prevalent fungal species that is asymptomatically colonizes many areas of the body, particularly the genitourinary and gastrointestinal tracts of healthy individuals. However, C. albicans can be an overgrowth and lead to be harmful when host immunity was altered, resident microbiota presence, stress induction, and other factors can lead to C. albicans infections. [4] Two types of human infections caused by C. albicans are superficial infections such as oral candidiasis (OC) or vaginal (vulvovaginal candidiasis) candidiasis and Research Article
A Review on Different Topologies Static Synchronous Compensator

Rapidly acting static synchronous compensator (STATCOM), a member of FACTS devices, is a capable technology being widely used as the state the-art dynamic shunt compensator for reactive power control in transmission and distribution system. In the last 25 years, technocrats have made extensive research on STATCOM technology due to which, many STATCOM controllers based on the self commutating solid-state voltagesource converter (VSC) have been developed and commercially put in operation to control system dynamics under stressed conditions. Because of its many attributes, STATCOM has emerged as a qualitatively superior controller relative to the line commutating static VAR compensator (SVC). This controller is called with different terminologies as Static advanced static VAR compensator, advanced static VAR generator or static VAR generator, Static Condenser, synchronous solidstate VAR compensator, VSCbased SVC or self SVC or static synchronous compensator (SSC or S2C). The developm ent of STATCOM controller employing various solidstate converter topologies, magnetic configurations, control algorithms, switching techniques and so on, has been well reported in literature with its versatile applicati ons in power system. A review on the state STATCOM technology and further research potential are presented.
Double Guard: Detecting and Preventing Intrusions In Multi-tier Web Applications

— In today's world we have many issues in internet security and privacy. We use internet in travelling, social media, banking, study etc. But we often face the problems with the privacy of the network system. To accommodate this increase in application and data complexity, web services have moved to a multi-tiered design wherein the web server runs the application front-end logic and data is outsourced to a database or file server. IDS plays a key role in computer security technique. But it also has drawbacks of its own. To overcome those drawbacks Double guard technique is introduced. I implemented double guard using IIS(internet information and service manager), an in built web server of windows 7 ultimate, with My SQL. This paper presents Double Guard, an IDS system that models the network behaviour of user sessions across both the front-end web server and the back-end database. By monitoring both web and subsequent database requests, it's possible to ferret out attacks that an independent IDS would not be able to identify. Furthermore, it quantify the limitations of any multitier IDS in terms of training sessions and functionality coverage. I am implementing the prevention techniques for attacks. I am also finding IP Address of intruder.
RECOMMENDATIONS USING COLLABORATIVE FILTERING

- Recommender systems are being increasing used to improve user experience in many areas. The most common technique used for recommendations is collaborative filtering. Recommender systems based on collaborative filtering work on past user-item relationships from a group of user who share similar taste and using these predictions are generated. In this paper we have explored how collaborative filtering can be used to recommend fitness plans to users. We have shown how ratings are collected from the user to rate items and how the similarity is computed to give personalised recommendations to users. Working of the proposed system as an android app has also been discussed.
Understanding of Basic Design Process and Techniques for Effective Museum Exhibition Design

Museum plays an important role in preserving of cultural heritage to make it relevant to be regularly practiced and learned within communities and between generations. In context of that facts, there are certain types of delivery techniques used to demonstrate and delivery the information that are needed to know by new generation. And museums traditionally have transferred the collections-based through a variety of media presentation in the exhibition. Therefore, a few exhibitions are failed in gaining the visitors attention, engagement, interaction and further experiences. This moreover giving another effect where the richness of collections and all knowledge in the world will not grow and further are not appreciated by new generation. Towards this, in preparing an exhibition design for a museum is highly required the team to know not only the right visual elements in order to engage with the visitors but also understanding space, material and techniques. Thus, by examining the complexity of the design process of museum exhibition particularly on interface design production and techniques of exhibition, the outcomes will be significantly be a best-practiced for future museum exhibition performance in helping the shaping of knowledge for community.
Genetics of TSE Susceptibility and Options for Disease Surveillance

The transmissible spongiform encephalopathies (TSEs) are invariably fatal, neuro-degenerative diseases that are characterized by a long period of latency followed by a short clinical illness. TSE diseases are found both in animals and man. Scrapie has been known in sheep and goats for more than 250 years but bovine spongiform encephalopathy (BSE) in cattle was first recognized in 1986 (Wells et al., 1987). Diseases apparently related to BSE have been identified in a diverse range of animal species, such as mink, cats, and deer. Chronic wasting disease in elk is a TSE disease that is wide spread in western United States. In man, CreutzfeldtJacob Disease (CJD), Gerstmann-Straussler-Scheinker (GSS) and familial fatal insomnia (FFI) syndrome are associated with variations in the PrP gene and occur in families. However, CJD can also occur as a sporadic disease that has a genetic component and most likely environmental triggers that are as yet unidentified. Kuru is a TSE of man that was identified in the Fore tribe in Papua New Guinea and was propagated by cannibalistic rituals (Alpers & Gadjusek, 1965, Matthews et al., 1968).
Fast Analysis of Sensor Data over MapReduce using Spark

A bstrac t — Big data analysis is emerging rapidly due to the tremendous volume of data, velocity at which the data is flowing in the organizations and the variety of data. In recent years due to the spurt in Internet of Things (IoT), data generated by the sensors is growing exponentially thus transforming into big data. Thus data collection, processing and extracting useful information from such increasing high velocity and high volume of sensor data poses a challenge for the researchers. Apache Spark is an open source, a general purpose engine for rapid large-scale data processing. To overcome the data replication and disk I/O overhead of sharing data between parallel operations in Hadoop, Spark uses the primitive called Resilient Distributed Datasets (RDD’s) which provides the programmers a fault tolerant and in - memory data storage across cluster nodes without replication that increases the processing speed of the applications to several magnitudes. We propose a method to analyze the sensor data using the Spark.
Big Data Analytics for Healthcare Organization, BDA Process, Benefits and Challenges of BDA: A Review

Day by day, data grows exponentially large using advanced technology and it requires effective analytical techniques to analyze the unknown and useful facts, patterns, associations and new trends which will provide new way for giving treatment to diseases and to provide good quality healthcare at low cost for everyone. This paper describes uncover valuable insights, various lifestyle choices, some social determinants, clinical and financial factors that it may effect the overall health of an individual. It also presents how to analyze the facts by using big data analytics to improve the healthcare in the world and also describes the various steps involved in Big Data Analytics process and discusses its advantages and challenges which show impact on healthcare organization.
CLINICAL OUTCOME OF SINGLE IMPLANTS UNDERWENT IMMEDIATE, EARLY AND DELAYED NON-OCCLUSAL LOADING

Aim: To compare the effectiveness of conventional/delayed loading (group I), early loading (group II) and immediate non occlusal loading (group III) of single implants by assessing peri-implant marginal bone level, width of attached gingiva and probing depth. Material and method: Thirty patients requiring single tooth replacement were selected from the OPD of Department of Prosthodontics & Crown and Bridge. In group I, 10 implants were placed at healed sites following standard two stage procedure of implant placement. In group II, 10 implants were placed at healed sites following which a healing abutment was placed at stage I surgery. Following which a definitive restoration was placed on definitive abutment 3 weeks after surgery. In group III, 10 implants were placed at healed sites following which a definitive abutment was placed at stage I surgery. The crestal bone was evaluated around the definitive abutment after placement of provisional/definitive restoration, at baseline (after loading) and 6 months using CBCT. Results: In group I the change in mean crestal bone level change from baseline to 6 months on buccal, lingual, mesial and distal sites were 0.47±0.14mm, 0.49±0.15mm, 0.49±0.14mm and 0.49±0.14mm respectively, in group II 0.50±0.09mm, 0.43±0.07mm, 0.45±0.08mm and 0.44±0.06mm respectively and in group III 0.43±0.08mm, 0.43±0.06mm, 0.39±0.06mm and 0.46±0.08mm respectively. Conclusion: The results are conclusive of the fact that the placement of definitive abutment at stage I surgery i.e. immediate loading results in a lesser vertical bone loss around implants followed by early loading and then by delayed loading.
Hybridization of Improved K-Means and Artificial Neural Network for Heart Disease Prediction

The healthcare field is composed of a variety of data, but the task of getting efficient knowledge and hidden information from those data is very difficult and time-consuming by the traditional method. Data mining technique is supportive for extracting valuable knowledge as well as hidden information from heath care system. Recently, abundant software’s, tools and various algorithms have been studied by the researchers for developing efficient medical decision support systems. Moreover, latest algorithms and innovative tools are continuously added day by day for making existing work more efficient. Last few years, heart disease is the major reason of death all over the world. Detection of heart disease is one of the vital issue s and many researchers are developing intelligent medical decision support systems to get better the ability of the physicians. In heart disease diagnosis and treatment, single data mining techniques are giving the satisfactory level of accuracy. But to increase the accuracy level we can use hybrid data mining techniques. In this paper, Improved K-means and ANN are combined to achieve an efficient result in heart disease diagnosis.
Authentication in Wireless Sensor Networks

: Wireless Sensor Networking (WSNs) is a region of incredible enthusiasm to both scholarly community and industry. WSNs raise countless, mechanical, logical, non military personnel and business applications to another level, permitting financially savvy detecting, particularly where human perception or conventional sensors would be unwanted, wasteful, costly, or risky. Indeed, even from their soonest applications, sensor systems have been focused for assault by foes with enthusiasm for blocking the information being sent, or in lessening the capacity of the system to do its main goal. There are a great deal of conceivable assaults against WSNs, which have distinctive goals, are performed at various levels, and result in various outcomes. Remote sensors have restricted vitality and computational capacities, making numerous conventional security procedures troublesome or difficult to be used. Likewise, they are regularly sent in open unattended regions, permitting physical assaults, for example, sticking, hub catch and altering. Then again, consistent assaults incorporate the HELLO flooding assault, the Sybil assault, the sinkhole assault, the wormhole assault, the blackhole assault, and the Distributed Denial of Service (DDoS) assault. Noteworthy research exertion is done to address every one of these issues. Wireless Sensor Networking (WSNs) is a developing field of research that presents analysts with testing objectives under tight outline imperatives. The requirement for inventive and imaginative security conventions is clear, since current security instruments are excessively asset serious as far as power, memory and preparing capacities of sensor organize hubs.
International Journal of Soft Computing and Engineering

The consistency test is one of the critical components both in AHP and ANP. It is necessary to make sure if the judgment result is accuracy and reliable. This paper stated a specific process of consistency test in ANP with group judgment under intuitionistic fuzzy environment. A two steps de-fuzzification technique with intuitionistic fuzzy number reduction and generalized mean computation is proposed to apply in this study. The group consistency is also fully tested in two stages. This proposed process exposes that it is comprehensive and feasible. Besides, the application of maximum eigenvalue threshold method, a new consistency test index to check for the consistency, is an advantage because it reduces a lot of operations.
Schmitt Trigger Based SRAM Using CNTFET Technology

: Due to the disadvantages of CMOS technology when the dimension of the device is scaled down and developing embedded application connect with technology scaling challenges, considerable attention is given to alternate technology for low voltage and low power designs. In this paper single cell of 6T SRAM and Schmitt trigger based SRAM has been designed for 32nm technology using CNTFETs. The result of the design is validated by HSPICE simulation for accuracy with 32 nm CNTFETs PTM models and results are compared.
Hybrid Clustering Algorithm for Time Series Data Stream: Current State of the Art

: Clustering time series data is a trouble that has applications in an extensive variety of areas and has recently evoked a large amount of research. Time series data may contain large and outliers. In addition, time series data is a one kind of special data set where attributes have a temporal ordering. Therefore clustering of time series data is a good issue in the data mining process. Different techniques and various clustering algorithms have been proposed to assist clustering of time series data sets also different kinds of non-developmentary optimization techniques and clustering algorithms have been applied for clustering multivariate time series data in some applications, usually they produces poor efficient results due to the dependency on the initial set of values and their poor performance in manipulating multiple objectives. Sometimes Time series data doesn’t contain same length and they usually have missing values, the basic measure Euclidean distance and dynamic time warping cannot be applied for such datasets to measure the similarity of objects. The clustering algorithms and its effectiveness on various applications are compared to develop a new method to solve the existing problem. Henceforth, this presents a survey on dissimilar clustering algorithms available for time series datasets. Moreover, the uniqueness and ceiling of previous researches are also discussed and further it contains short descriptive taxonomy of Data Mining Techniques and Tools.
Preliminary Investigation on Phytochemical Composition and Anti-bacterial Activity of the Root of Cousinia microcarpa Boiss. Asian J. Med. Pharm. Res., 4 (4): 156-159

Tribes in the Hezarmasjed protected area of Iran used Cousinia microcarpa Boiss. root for the treatment of various disorders like respiratory problems, pulmonary infections, remedy of wounds, mouth ulcers, treatment of toothache, joints pain and rheumatism as a folk medicine. This investigation was conducted to authenticate some aspects of this conventional application scientifically. Cousinia microcarpa Boiss. roots were screened phytochemically for the presence of secondary metabolites by using standard methods. The antibacterial activities of the different extracts was also investigated against two Gram-positive and three Gram-negative bacterial strains through disc diffusion assay. The phytochemical analysis of extracts of the roots with different solvents such as methanol, ethanol, chloroform and distilled water demonstrate the presence of active components like tannins, flavonoids, terpenoids etc. All the extracts were found to possess different degrees of antibacterial activity except distilled water extract. Our results indicated that Gram-positive bacteria are more sensitive than the Gramnegative bacteria. Among the microbial strains evaluated Staphylococcus aureus was found to be the most susceptible, based on the results demonstrated from the inhibition zones. The findings of this paper confirmed potential antibacterial activities of the plant's root. Thus, Cousinia microcarpa Boiss. root can be considered as a candidate for new antibacterial drugs due to its extensive spectrum activity. Further surveys are required to estimate its safety and toxicity.
Fingerprint and location based multifactor authentication for mobile applications

Authentication, which involves the verification of identity, is one of the most important security features. It usually depends on three factors: something you know (knowledge), something you have (token) and something you are (biometrics). In this paper, we propose the use of biometrics (fingerprints) with a fourth factor, namely location (i