Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Selection Algorithm Using Fast Clustering and Correlation Measure

--------------------------------------------------------------------- Abstract - Nowadays most of the application uses tens of thousands of data for their processes. It’s very difficult task to make partition of objects having similar features or properties into a group. These groups are classified and features are selected among them. This feature selection should be done such a way that it gives effective and accurate result. Feature selection has been an active research area in pattern recognition, statistics and data mining community. Idea behind feature selection is to choose a subset of input variables by eliminating features with little or no predictive information The Fast Clustering selection method produces highly effective and efficient results. In this paper, The FAST clustering method is explained including correlation techniques for removing irrelevancy among datasets. The FAST works in two steps, making clusters of datasets using Minimum Spanning Tree and then obtain a effective feature among all forest cluster. Various correlations techniques can be added for increasing effectiveness of the feature selection. All clusters resulted in this selection algorithm are relatively independent of each other.
Comparison of Topical Anesthetic Gel, Pre-Cooling, Vibration and Buffered Local Anesthesia on the Pain Perception of Pediatric Patients during the Administration of Local Anesthesia in Routine Dental Procedures

Introduction: As a dentist, administering anesthesia to patients, especially children proves to be one of the most difficult parts of a procedure. Also, poor pain control adds on to the fear and anxiety of the needle that might interfere with appropriate dental management. So, several desensitization methods were aimed to reduce are being tried out recently. Material and methods: 40 children aged between 7 to 13 years were included. On a random basis, the subjects were allocated into four groups. Application of topical anesthesia at the site of administration of local anesthesia, pre-cooling the anesthetic site prior to the administration of local anesthesia, vibratory stimulus at the site of administration of local anesthesia, buffering the local anesthetic agent were the groups from 1 to 4 respectively. During the administration of infiltration anesthesia, the pain perception was assessed using Wong-Baker Faces Pain Rating Scale. The statistical analysis was performed using SPSS software. Results: Greatest pain reduction was observed in the pre-cooling group with mean pain score 2.4 followed by vibration group with mean pain score 2.6 then buffered local anesthesia with mean score of 5.6 and lastly topical anesthesia with 6.2 mean score. Mann-Whitney test showed that pre-cooling was statistical significance compared with topical anesthesia and buffered local anesthesia (P<0.001). Conclusions: Pre-cooling of the injection site before infiltration anesthesia is an easy, reliable and effective technique with no additional cost and was found to reduce discomfort and facilitate clinical management.
Design of Load Balancing Technique for cloud Environment using Live Migration of Virtual Machines

Cloud Computing is promising in today’s internet world. Cloud computing provides computing resources on demand on a pay per use basis. Live migration of Virtual Machine is an important part in cloud computing. With the increasing demand of cloud computing, organizations’ data is heavily loaded in the cloud. This may cause Virtual Machine failure. Some datacenters are heavily loaded with the data and some datacenters are not. This may cause load imbalance. So, load balancing becomes an important task in cloud computing. Live virtual machine migration is used for load balancing. Most of the studies proposed the techniques for single virtual machine migration, multiple virtual machine migration, and load management. Sometimes, unnecessary virtual machine migration may happen. We will design a load balancing technique which will allocate Virtual Machines initially in order to prevent unnecessary virtual machine migrations.
Quantifying the Amount of Training Needed for Novice Ultrasonographers to Become Proficient in Measuring Left Ventricular Mass Index

Introduction: Undiagnosed, or masked, hypertension may occur in up to a third of patients with normal clinical blood pressures. Masked hypertension could be detected by measuring left ventricular mass index (LVMI) using point-of-care ultrasound as it directly correlates with ambulatory blood pressures. This study was designed to determine how much training is needed for a novice to develop proficiency measuring LVMI. Methods: This is a pilot prospective cohort study comparing an instructed novice learner group to an expert control assessing improvement in LVMI using limited echocardiography. The scans took place at the University of South Carolina School of Medicine Ultrasound Institute. The novices were two PGY-3 family medicine residents and two medical students. Three attending physicians and one cardiology ultrasound technician served as expert ultrasonographers. Each novice completed a minimum of 30 scans on volunteers. Training utilized self-directed online modules and a group training lab involving real-time feedback from an expert while scanning volunteers. Then the novices completed individual blinded volunteer scanning with an expert proctor. The average of the three expert ultrasonographer measurements were used as the control during this study. Results: LVMI Deviation was plotted as a function of the number of scans attempted and fit to a linear regression model. According to the model, novices would need to attempt greater than 35 scans to approximate the expert’s measurements. Conclusion: Our data suggest that it is possible for novices to accurately perform point-of-care ultrasound to measure LVMI after 35 supervised examinations. This is well within the reach of most practicing primary care physicians. Confirmatory studies will be required.
A NOVEL APPROACH FOR WEB SERVICES COMPOSITION AND VERIFICATION

: Web services are a very appropriate communication mechanism to perform distributed business processes among several organizations. A concept of service composition, combining existing Web services easily as our needs change, is one of the key features of the technology. Many new standards have been defined to solve web service composition problem, for example BPEL4WS. BPEL4WS provides an initial work for forming an XML specification language for defining and implementing business process workflows for web services. The main problems with most practical approaches to service composition are the verification of correctness of service composition. It has to depend on formal verification method which helps to check the correctness of services composition. The proposed system concentrates on both composition and verification of web services. In this paper, an algorithm is introduced for the verification of web services composition using Muller Automata. The web services are composed using BPEL4WS and it is transformed into Promela (It is the input language of SPIN model checker). Finally, verification algorithm is designed and verified using Muller automata.
Coevolution Evolutionary Algorithm: A Survey

: Evolutionary Computing techniques have become one of the most powerful tools for solving optimization problems and is based on the mechanisms of natural selection and genetics. In Evolutionary Algorithm, Co-evolution is a natural choice for learning in problem domains where one agent’s behaviour is directly related to the behaviour of other agents. Co-evolution provides a framework to implement search heuristics that are more elaborate than those driving the exploration of the state space in canonical evolutionary systems. This paper presents the concept of Co-evolutionary learning and explains a search procedure which successfully addresses the underlying impediments in Co-evolutionary search. Co-evolution employs evolutionary algorithms to solve a high-dimensional search problem by decomposing it into low-dimensional subcomponents. The objective of this survey is to discuss about the various existing Co-evolutionary algorithm and their successful implementation in real world optimization problem. Hence the outcome of the study is to bring out the various research opportunities in implementing the concept of Co-evolution for many optimization problems in different application
Relationship Between Interpersonal Influence and E-wom in Social Networking Sites

: Enhanced socialization activities by individuals over online social networking platforms, marketers have found themselves a great opportunity to engage in peer to peer (P2P) communication via electronic word of mouth.The three behavioural dimensions highlighted in past literature about electronic word of mouth are information pass along behaviour, opinion giving and seeking behaviour. In order to study the association between social relationships and eWOM (Electronic word of mouth) in online social network websites one of the prominent social relationships of interpersonal influencehas been selected, because it acts as a major factor in decision making by consumers. Keeping the same in mind interpersonal influence has been considered, to study its relationship with electronic word of mouth in online social network sites. For abetter understanding of thestated relationship, three constituents of interpersonal influence i.e. value expressive, utilitarian & informational influence have been considered.
Analyzing the mediating role of Brand association for Brand awareness and loyalty

Brands are of top priority and interest for many companies and marketing Professionals. Marketing managers are continuously realizing the power of the brands. In today’s competitive environment measuring the exact association of brands is most desirable goal for the organizations. The aim of research is to test empirically the mediating role of brand association for brand awareness and brand loyalty of customers and non-customers. In order to investigate the mediating role of the brand association for customers and non-customers, primary data were collected through a survey from both customers and non-customers of a mobile phone. Findings of the study confirm the mediating role of the brand association for awareness and loyalty for both customers and non-customers. Statistical Results show that Brand associations mediating role does not differ for customers and non-customers, across the product categories whereas the level of the association influents the level of the loyalty for a product.
Adsorptive Potential of Acid Modified Moringa Oleifera Wastes for Tannery Effluent Decontamination

Introduction The production of leather, leather goods, leather boards and fur produces numerous by products, solid wastes, high amounts of wastewater containing different loads of pollutants and emissions into the soil and air. The uncontrolled release of tannery effluents to natural water bodies increases health risks for human beings and environmental pollution. Effluents from raw hide processing tanneries, which produce wet blue, crust leather or finished leather, contain compounds of trivalent chromium (Cr) and sulphides in most cases. Organic and other ingredients are responsible for high BOD (biological oxygen demand) and COD (chemical oxygen demand) values and represent an immense pollution load, causing technical problems, sophisticated technologies and high costs in concern with effluent treatment [1]. Contamination of tannery waste water with organics and inorganics is a matter of concern, because of their harmful effects on living organisms. Adsorption process is superior to any other method by virtue of its low initial cost, low energy requirement, simplicity of design and possibility of reusing the spent carbon via regeneration. Adsorbent such as activated carbon available to remove organic compounds from wastewaters are costly and hardly available [2,3]. Base on this, there is a need to study the effectiveness of uptake of pollutants from tanneries by considering cost effectiveness, availability and favorable adsorptive properties.
MFCC and its applications in speaker recognition

: Speech processing is emerged as one of the important application area of digital signal processing. Various fields for research in speech processing are speech recognition, speaker recognition, speech synthesis, speech coding etc. The objective of automatic speaker recognition is to extract, characterize and recognize the information about speaker identity. Feature extraction is the first step for speaker recognition. Many algorithms are suggested/developed by the researchers for feature extraction. In this work, the Mel Frequency Cepstrum Coefficient (MFCC) feature has been used for designing a text dependent speaker identification system. Some modifications to the existing technique of MFCC for feature extraction are also suggested to improve the speaker recognition efficiency.
Success and Failure of Entrepreneurs in Implementation of Strategic Programs in Small Scale Enterprises in Two States of India: A Comparative Study

Purpose: Gujarat and Odisha are two different provinces in the Indian sub-continent under South-Asiatic region. Gujarat, with less mineral resources, tribal population, moderate poverty developed much economically due to installation of industries, particularly, small scale sector. On the other hand, Odisha, in spite of its vast natural resources like minerals, forests, rivers, population, flora and fauna, long coast line, natural harbors and surplus electricity has all characteristics of poverty. These phenomena led to an approach. Approach: Both the states have similarities in many cases, yet Odisha perish in poverty. Small Scale Industries (SSIs) flourish in Gujarat but become sick in Odisha. Causes to these aspects draw serious attention of the people of Odisha. A study was initiated in this regard to find out the draw backs of poor performance of the state in SSIs sector. Findings : The study revealed that a careful implementation of strategic programmes with judicious use of own social and financial resources in the factory premises and outside the state made Gujarat SSEs more advantageous for high economic growth which was not observed in case of Odisha SSEs. Future Implication: The prosperity of Gujarat SSIs have been described through five major elements of strategy eg. Arena, vehicle, differentiators, staging and economic logic. Strategic programme-activities of Gujarat and Odisha have been compared, differences brought out for the Odisha entrepreneurs to consider and follow for high growth of the SSEs in the state. Key Words : Arena, vehicle, differentiators, staging, economic logic, entrepreneurs, strategy and implementation.
ANTIDIABETIC AND ANTIOXIDANT POTENTIAL OF HYDROALCOHOLIC EXTRACT OF MORINGA OLEIFERA LEAVES IN STREPTOZOTOCIN-INDUCED DIABETIC RATS

The present study aimed to evaluate antidiabetic and antioxidant activities of 70% ethanolic extract of Moringa oleifera leaves (MOLEt) in streptozotocin-induced diabetic rats. Diabetes was induced in male Wistar rats by single intraperitoneal injection of streptozotocin (60 mg/kg b.wt.). The diabetic rats were administered orally with MOLEt at three different doses (100, 250 and 500 mg/kg b.wt./day) for 60 days. The results were compared with glibenclamide (5 mg/kg b.wt./day) treated rats. The streptozotocin treated control rats showed a significant increase in fasting blood glucose and glycosylated hemoglobin (HbA1c) with a concomitant decrease in serum insulin level and glycogen content in liver. Moreover, the levels of lipid peroxide (TBARS) in pancreatic tissue were significantly increased with a concurrent decline in antioxidant markers (SOD, CAT, GSH and ascorbic acid). The histopathological picture of the pancreatic islets showed degenerative and atrophic changes. Oral administration of MOLEt (100, 250 and 500 mg/kg b.wt./day) or glibenclamide for 60 days showed significant reduction in blood glucose and HbA1c levels and an elevation in serum insulin and hepatic glycogen levels. The extract treatment also reduced TBARS levels and improved the levels of antioxidant markers in the pancreas. The histomorphological picture of pancreas in MOLEt treated diabetic rats showed marked sign of amelioration. These results were comparable to reference drug, glibenclamide. The results of present study showed that MOLEt posseses significant antidiabetic and antioxidant activities.
Detection of Pesticides in Buffalo Milk Collected from Different Areas of Gandhinagar and Ahmedabad by Thin Layer Chromatography

Different pesticides have been used in tropical countries to control agricultural pests. Problem of the presence of pesticides in milk contributes to the serious issue of human health. The identification of organophosphorous (chlorpyrifos) pesticides in buffalo milk collected from different localities of Gandhinagar and Ahmedabad was performed. Milk was monitored by using TLC (thin layer chromatography) technique for 3 pesticides residues namely Dichlorovos, Chlorpyrifos and DDT (dichlorodiphenyltrichloroethane) to determine the degree of contamination. Extraction was performed with Hexane: Acetone: 1:1. Extracted milk samples spotted on TLC with pesticides standards. The analysis showed that most of the milk samples were contaminated by the pesticides. Identification of pesticides was done through RF (Retention factor) value and color of the spot developed after spraying the reagent with the standards. Confirmation of pesticides was done through GC-MS. Results showed that 40 % of the milk samples were contaminated with pesticides residues of organophosphorous (chlorpyrifos) was most significantly present in milk samples. The intake of the pesticide contaminated milk might pose health hazardous to humans in this local.
Design for Tapered transitions From Microstrip Lines to Substrat Integrated Waveguide at Ka Band

In this paper, the concept of substrate integrated waveguide (SIW) technology is used to design filter for 30 GHz communication systems. SIW is created in the substrate of RT/Duroid 5880 having relative permittivity = 2.2 and loss tangent tanφ = 0.0009. Four Via are placed on the century filter the structures of SIW are modeled using and have been optimized in software HFSS (High Frequency Structure Simulator), à transition is designed for a Ka-band transceiver module with a 28.5GHz center frequency, and then the results are verified using another simulation CST Microwave Studio (Computer Simulation Technology). The return loss are less than -18 dB, and 13 dB respectively. The insertion loss is divided equally -1.2 dB and -1.4 respectively.
Deinterleaving of Radar Signals and its Parameter Estimation in EW Environment

-The ultimate goal of passive Electronic Warfare (EW) systems is to classify radar signals. When a group of emitters are present in the scene (EW Environment) from the adversaries, deinterleaving of multiple emitters is a vitally important task. This task is based on time difference of arrival (TDOA) by using sequential search algorithm. It is used to perform the threshold as exponential function to detect the signals. This paper presents a novel technique to classify the signal types and estimating those signal parameters. The results are simulated using MATLAB Simulator.
An Experimental Analysis of P2P Reputation Management Using Distributed Identities and Decentralized Recommendation Chains

— PEER-TO-PEER (P2P) networks are self-configuring networks with minimal or no central control. P2P networks are more vulnerable to dissemination of malicious or spurious content, malicious code, viruses, worms, and Trojans than the traditional client-server networks, due to their unregulated and unmanaged nature. By introduction of a central trusted authority like a Certificate Authority (CA) can reduce the difficulty of securing P2P networks. The major disadvantage of the centralized approach is, if the central authority turns malicious, the network will become vulnerable. The reputations of the peers are used to determine whether a peer is a malicious peer or a good peer. Once detected, the malicious peers are ostracized from the network as the good peers do not perform any transactions with the malicious peers. Expulsion of malicious peers from the network significantly reduces the volume of malicious activities. All peers in the P2P network are identified by identity certificates (aqua identity). The reputation of a given peer is attached to its identity. The identity certificates are generated using self-certification, and all peers maintain their own (and hence trusted) certificate authority which issues the identity certificate(s) to the peer. Each peer owns the reputation information pertaining to all its past transactions with other peers in the network, and stores it locally. A two-party cryptographic protocol not only protects the reputation information from its owner, but also facilitates secure exchange of reputation information between the two peers participating in a transaction
AUTOMATIC DETECTION OF BRAIN TUMOR BY IMAGE PROCESSING IN MATLAB

-Tumor is unwanted growth of unhealthy cell which increase intracranial pressure within skull. Pattern Recognition area is one of the emerging and innovative area for biomedical application. The strategy presented in this paper involves Preprocessing, Segmentation, feature extraction and detection of tumor from MRI scanned brain images. Magnetic Resonance Imaging (MRI) is a non-invasive imaging modalities which is best suited for the detection of brain tumor. The method proposed in this paper is fuzzy c-means (FCM) Segmentation which can improve medical image segmentation. The algorithm will easy to handle and faultless identification of tumor in scanned region. A user friendly environment is created by using GUI in MATLAB. Here, we develop an automated brain tumor detection system for MRI scanned images. By using the GUI tool the physician and other practitioners are facilitated in detecting the tumor and its geometrical feature extraction. This work help in recognition of tumor which in turn save the precious time of doctor and pathologist to diagnose the tumor automatically in short span of time.