Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Validation of an HPLC-DADMethod for the Determination of Coumarinin Syrups with Guaco and Critical Analysis ofDrug Labels

We carried out an investigation with the purpose to evaluate the real concentration of coumarin by high performance liquid chromatography with diode array detector (HPLCDAD) in some guaco syrups and associations (Mikania glomerata Spreng.), marketed in Sao Paulo, Brazil. At first, we developed some analytical method parameters and then we investigated the quality of nine commercial syrups, purchased in pharmacies, compounding pharmacy and another in a house of Northeast herbals, called “lambedor of guaco, composed of natural herbs”. We also carried out an investigation about package and drug label of the studied products, according to ANVISA standardization. The most syrups samples have a lower coumarin concentration than those recommended by ANVISA as a minimum daily dose. Regarding to packaging and drug label, many of them are complies with the current legislation, while others are in a complete disagreement. Despite the importance of this plant species for the Brazilian herbal medicine, including those belonging to the official list of the Unified Health System, many efforts are still needed to offer to the Brazilian population adequate quality products. Therefore, it is necessary a better supervision about quality control of phytomedicines.
REAL TIME ABANDONED BAG DETECTION USING OPENCV

— Abandoned Object Detection is one of the important tasks in video surveillance system. This paper proposes a work related to automatic detection of abandoned and unknown objects using background subtraction, morphological operation and centroid method. The aim of the approach is to automatically recognize activities around restricted area to improve safety and security of the servicing area. The system takes as input from the camera, tracking and recognition results and fuses these into object estimation. A proposed algorithm for object tracking in video, based on image segmentation is proposed. With the image segmentation all objects in video can be detected whether they are moving or not by using segmentation re-sults of successive frames. Consequently, the proposed algorithm can be applied to multiple movements.The algorithm was tested on real time video surveillance system and it produces very low false alarms and missing detection. This approach definitely provides security and detects the moving object in real time video sequence and live video streaming. Qualitative and quantitative results in terms of Detection Rate (DR), False Alarm Rate (FAR), success rate and average processing time per frame are given. The proposed algorithms are compared with the established methods based on simple difference and background subtraction.
Usage of Similarity Measures to Cluster Related Web Links

— The explosive amount of information present on the internet attracted many users. Due to the unstructured property of the data present on the internet the users are unable to retrieve the needed information in efficient manner. We concentrated on providing related pages which are of current interest to the user. To make this happen we collected different hyperlinks, transformed them to documents and used the numerical measures like Euclidian distance and Cosine similarity to measure the orientation of the websites to each other. Then applied the clustering algorithm to find out which of them are more associated to each other and are likely to form a cluster.
Features Extraction from opinions via Domain Relevance

: Now a days with increased use of social media, user reviews on any product plays a significant role. The existing opinion mining techniques operate only on single review corpus; it doesn’t consider distribution of opinion features across different corpora. A new technique is proposed to extract opinion features from online reviews across two corpora, one a given review corpus and other is contrasting corpus. This discrepancy is evaluated using domain relevance. The first step is to find candidate opinion features in domain review corpus using syntactic dependence rules. This evaluate intrinsic domain relevance scores for each candidate on domain-dependent corpora and extrinsic domain relevance score on domain-independent corpora. A candidate features which are less generic and more domain specific are the final opinion features. This interval thresholding is called as the intrinsic and extrinsic domain relevance.
Study on 5G Mobile Communication

: Impetus for millimeter wave is the upshot of topical advancement in innumerable new technologies in the mobile communication arena. With abrupt upsurge in the mobile data demand, the fifth generation (5G) mobile network would impressively escalate communication capability by expending the bulky expanse of spectrum in the millimeter wave (mm Wave) bands. The mm Wave communication system distinct from prevailing other communication systems, in terms of high propagation loss, directivity, and sensitivity to blockage. This distinctive of mm Wave communication announces numerous encounters to completely exploit the potential of mm Wave communication. This work presents the incentive for new mm- wave cellular systems, approach, in terms of extents of gain, path loss, for the design of future mm-wave cellular systems operating at 28 and 38 GHz frequencies. These frequencies can be used when engaging steerable directional antennas at base stations and mobile devices.
Targeted Contrast-Enhanced Ultrasound for Inflammation Detection

Molecular imaging is a form of nanotechnology that enables the noninvasive examination of biological processes in vivo. Radiopharmaceutical agents are used to target biochemical markers, permitting their detection and evaluation. Early visualization of molecular variations indicative of pathophysiological processes can aid in patient diagnoses and management decisions. Molecular imaging is performed by introducing into the body molecular probes, which are often contrast agents that have been nanoengineered to target and tether to molecules, thus enabling their radiologic identification. Through a nanoengineering process, ultrasound contrast agents can be targeted to specific molecules, extending ultrasound’s capabilities from the tissue to molecular level. Molecular ultrasound, or targeted contrast-enhanced ultrasound (TCEUS), has recently emerged as a popular molecular imaging technique due to its ability to provide real-time anatomic and functional information without ionizing radiation. However, molecular ultrasound represents a novel form of molecular imaging and consequently remains largely preclinical. This review explores the commonalities of TCEUS across several molecular targets and points to the need for standardization of kinetic behavior analysis. The literature underscores evidence gaps and the need for additional research. The application of TCEUS is unlimited but needs further standardization to ensure that future research studies are comparable.
Stress Degradation Studies And Validation Method For Quantification Of Aprepitent In Formulations By Using RP-HPLC

A Stability indicating reverse phase high performance liquid chromatography method has been developed for the estimation of Aprepitant in tablet dosage form. A Thermosil symmetry C18 column having dimensions of 150×4.6mm and 5μm particle size, with mobile phase containing a mixture of water and Acetonitrile in the ratio of 30:70 v/v was used. The flow rate was 1ml/min and the column effluents were monitored at 220 nm. The retention time for Aprepitant was found to be 2.8 min. The proposed method was validated in terms of linearity, accuracy, precision, LOD, LOQ and robustness. The LOD and LOQ were found to be 0. 085μg/ml and 0. 28μg/ml respectively. The method was found to be linear in the range of 50 – 90 μg/ml with regression coefficient (r=0.999). The % recovery for the Aprepitant was found to be 100.7 and the forced degradation studies were also carried out as per ICH guidelines. There was complete separation of degradation and Aprepitant peak, which demonstrate the specificity of assay method for estimation of Aprepitant in the presence of its degradation products and it can be employed as a stability indicating one. Due to simplicity, rapidity and accuracy of the proposed stability indicating HPLC method and it is useful for quality control analysis.
A Review of Oil-Spill Detection Techniques using Marine SAR images

Oil spills have been a major cause of Marine Pollution and a risk to Marine Life. Due to its hazardous outcomes, Oil spill detection has become prominent job of marine inspectors. Also, many industries discharge there waste oil in Oceans to get rid of it without coming in notice of pollution control board. Such cases are known as illegal oil spills and such oil spills need to be detected as accurately and immediately as possible. To do so, many technologies are advent. SAR images have been employed in many cases to detect such spills mostly by human operators. To automate such thing, machine learning and classification based approaches are used. This paper reviews such techniques in order to evaluate the overall advancement in accuracy of detection of such techniques. Keywords—Remote Sensing, SAR, Oilspill Detection, Classification, Review
A Survey on Panorama Image Stitching

: Panorama image stitching is process of combining two or more images of the same scene into one high resolution image called as panoramic image. In today’s world an image stitching is considered as an dynamic research area in computer visualization and graphics. Image stitching literature shows that image stitching is still a challenging problem for single and panoramic images. In recent years many algorithms deal with panoramic image stitching problem. Panorama Image stitching process can be divided into four main components – image registration, Image warping, color correction, image labeling and image blending. This paper present a survey about the process of panorama image stitching. The main components of panorama image stitching will be described in this paper. A framework of a complete panorama image stitching system based on these approaches will be introduced. Finally, we are going to discuss the current challenges of panorama image stitching technique.
A Novel Method on Malayalam Handwritten Character Recognition

— Handwritten Character Recognition (HCR) is one of the most challenging and active areas of research in the field of pattern recognition. It has a wide range of applications like preservation of documents into digital form, managing rare books etc. HCR is a difficult process due to the variants of handwriting styles of different individuals. Thus the success rate of any HCR system greatly depends upon the language that these systems are working on, and the amount of character sets in each language. Malayalam, a south Indian language and official language in the state of Kerala has a rich amount of character sets. Recognizing all those characters is a difficult task. In any types of character recognition systems, recognition rates play a vital role in the overall efficiency of the system. Several researches are going on this field to improve recognition rates. This paper deals with texture extraction model for character recognition process. In this model co-occurrence matrix and Euclidean distance are used to recognize the characters in an image.
Dissemination Techniques in VANET: A Survey

— VANETs (vehicular ad hoc networks) are emerging as a new network environment for intelligent transportation systems. Many of the applications built for VANETs will depend on the data push communication model, where information is disseminated to a group of vehicles. Various Approaches of data dissemination in vehicular network can be used to inform vehicles about dynamic road traffic condition so that a safe and efficient transportation system can be achieved. In this paper, we have reviewed various data dissemination techniques and did the comparison of two important approaches of dissemination.
REVIEW ON VIDEO ENHANCEMENT TECHNIQUES

: Video enhancement is one of the most important and difficult components in video research. The aim of video enhancement is to improve the visual appearance of the video, or to provide a better transform representation for future automated video processing, such as analysis, detection, segmentation, recognition, surveillance, traffic, criminal justice systems. In this paper overview of video enhancement processing techniques and analysis algorithms are described. The study is further going on to find a technique so that more accuracy can be obtained in 3D Video enhancement.
Performance Evaluation of WiMAX-OFDM System over different SUI Channels

– At present, telecommunication industries are highly concerned with the wireless transmission of data which can use various transmission modes, from point-to-multipoint links. It contains full mobile internet access. Various applications have already been applied so far using WiMAX, as alternative to 3G mobile systems in developing countries. The paper built a simulation model based on 802.16 OFDM-PHY baseband and demonstrated in different simulation scenarios with different modulation techniques; BPSK, QPSK, 16-QAM and 64-QAM to find out the best performance of physical layer for WiMAX Mobile. The Stanford University Interim (SUI) channel model under varying parameters is selected for the wireless channel in the simulation. The performance is recorded on the basis of BER, and SNR output through MATLAB Simulation.
A Survey on Security and Privacy Implications of Privacy Preserving Data Mining

Huge volume of detailed personal data is regularly collected and sharing of these data is proved to be beneficial for data mining application. Such data include shopping habits, criminal records, medical history, credit records etc . On one hand such data is an important asset to business organization and governments for decision making by analyzing it. On the other hand privacy regulations and other privacy concerns may prevent data owners from sharing information fo r data analysis. In order to share data while preserving privacy data owner must come up with a solution which achieves the dual goal of privacy preservation as well as accurate clustering result. The sharing of data is often beneficial in data mining applications. It has been proven useful to support both decision-making processes and to promote social goals. However, the sharing of data has also raised a number of ethical issues. Some such issues include those of privacy, data security, and intellectual property rights. In particular, we address the problem of transforming a database to be shared into a new one that conceals private information while preserving the general patterns and trends from the original database. To address this challenging problem, we propose a unified framework for privacy-preserving data mining that ensures that the mining.
A Comparative Study on Educational Data Mining Using Classification Techniques

: Most of the institutions are looking forward for the solution for student’s better performance in their Education. Every institution is ready to implement different methods to understand students thinking and their needs. Educational data mining (EDM) is a most important and focused research area. In EDM different type of student data were collected and implemented through various data mining techniques. Classification Algorithms like Decision trees, K-Nearest Neighbor, Neural Networks, Naïve Bayes and so on were used. This paper on the EDM compares the classification algorithms used in EDM.
Semi-synthesis of Chitosan with High Molecular Weight and Enhanced Deacetylation Degree

Chitosan is a cationic polymer with different biomedical, biotechnological, environmental, industrial and agricultural applications. Various methods were suggested to prepare chitosan from its natural ancestor polymer, chitin, but the controlling of the molecular weight and degree of deacetylation of the resulting polymer was a problem where there is an inverse relationship between them. This study aimed at modifying the sequence of deacetylation process in combination with number of cooling/heating cycles for chitin to produce chitosans with high molecular weight as well as enhanced deacetylation. The produced chitosans were tested for their molecular weights, chemical structure, deacetylation degrees, antioxidant properties and purity. With the proposed modification of polymer deacetylation, different chitosans of different degrees of deacetylation but similar molecular weights were prepared. This may represent a more economical method for the production as well as applications of different types of chitosan.
DEEP LEARNING APPROACH MODEL FOR VEHICLE CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The Vehicle detection is used to identify the vehicles in any video or image file. The process of detection of vehicles includes the object detection by considering the vehicles as the primary object. By taking the images form aerial or horizontal view and from road or parking using surveillance cameras, the detection process can be initiated. A vehicle recognition method based on character-specific extremely regions (ERs) and hybrid discriminative restricted Boltzmann machines (HDRBMs) is performed by top-hat transformation, vertical edge detection, morphological operations, and various validations. It proposed a novel algorithm to identify the density of vehicles by using the vehicle detection and classification algorithm by implementing the hybrid deep neural network over the huge dataset of video and images that are obtained from the satellite images. For feature extraction Non-negative Matrix Factorization (NMF) and SVM compression is used. Where, compression is used to increase the response time for detection and classification. The proposed model has been designed for the vehicle position identification as well as the vehicle type classification using the deep neural network. The proposed model has been tested with a standard dataset image for the result evaluation .
APPLICATION OF IOT-WSN IN HOME AUTOMATION SYSTEM: A LITERATURE SURVEY

: Life become very simpler and easier in all phases with the improvement of Automation technology. Today, automatic methods are being chosen over manual method. Internet became a part of life, and IoT is the modern and emerging internet skill with the quick increase in the number of users of internet. From industrial appliance to user, IoT is a developing network of everyday object which can share data and complete responsibilities when you are busy with other events. Using IoT with Wireless Home Automation system (WHAS) is a method which control home functions and features automatically through computers or mobile devices. Study of Internet of things (IoT) has become the motivation for years with the enlargement of human-computer interaction skill and development of people’s living standards. Smart home system has drawn more and more attention in IoT. This paper is based on wireless sensor network and IoT for home automation which explore the architecture of home automation system with advantages.
Urbanization Analysis Using Spatial Support and Improved Random forest Decision Tree Approach

Summary Urbanization is the major strategy that leads to the loss of the various biodiversity and the homogenization of geological habitat. Thus, it is necessary to study and analyze the drastic changes occurred due to global urbanization periodically. The periodical assessment of urbanization gives rise to the development of various techniques and rules from several researchers. This paper is also a part of development over the urban-land cover analysis. It introduces a Budget in Random Forest Decision tree (RFDT) approach that preserves the statistical features and object boundaries and help in improving the classification accuracy. The system implements a spectral band segmentation method, which differentiates the remote sensory images as Land Cover (LC) and Land Use (LU). The proposed RF algorithm of decision trees attempts to provide an improved efficiency over the other existing methods that is obtained from the experimental verification of the earlier algorithms with the proposed. The comparison report shows the performance of the algorithm from 2007 to 2013 respectively.
A randomized controlled trial to compare crystalloid and colloid co-loading in preventing spinal hypotension in parturients undergoing caesarean section

Background: Spinal anaesthesia is the preferred technique for operative delivery in parturients, but associated hypotension can be detrimental for both mother and fetus. Different types (Crystalloid or colloid) and timings (preload or co-load) of fluids have been tried to decrease the incidence of hypotension. In our study, we planned to compare the efficacy of crystalloid co-loading and colloid co-loading in preventing hypotension in patients undergoing elective caesarean section under spinal anaesthesia. Methods: 70 full term pregnant women with uncomplicated pregnancies scheduled for elective caesarean section under spinal anaesthesia were randomized to two groups to receive either crystalloid co-load or colloid co-load. Patients received either 15ml/kg of ringer’s lactate or 8ml/kg of 6% hydroxyl ethyl starch after cerebrospinal fluid was tapped during spinal anaesthesia. Blood pressure, heart rate, and oxygen saturation were measured every two minutes for first 20 minutes and every five minutes till the end of procedure. Vasopressor was administered if systolic pressure was less than 80% of baseline pressure. APGAR scores, nausea, and vomiting were also monitored. Statistical analysis: Student’s t-test, chi-square test, fisher exact test. Results: There was no statistically significant difference among the groups regarding systolic blood pressure and vasopressor requirements. The fall in diastolic blood pressure and mean arterial pressure was more in the crystalloid co-load group compared to the colloid co-load group. Neonatal outcomes and incidence of nausea and vomiting were comparable statistically among the two groups. Conclusion: Colloid co-loading, even though better than crystalloid co-loading in preventing hypotension in pregnant patients undergoing caesarean section under spinal anaesthesia, they are ineffective as a single measure as incidence of hypotension in both the groups >50%.
Review of Asymmetric Key Cryptography in Wireless Sensor Networks

In wireless sensor networks (WSN’s), our main aim is to ensure the confidentiality of the data which has been sensed , aggregated and communicated to the base node. This will be achieved using key management. Symmetric key management uses only one key for encryption and decryption.Symmetric key management is generally preferred in WSN, because it will consume less battery power, memory and induces less computation overhead. Asymmetric key cryptography uses two separate keys , for encryption and decryption but those two keys are interconnected with complex mathematical algorithm. Since it is using complex mathematical algorithms it will induce huge overhead on power , computation and memory Asymmetric key cryptography is not preferred in WSN. Asymmetrickey cryptography is more secured and efficient when compared to symmetric key cryptography, this paper analyzes various opportunities of implementing asymmetric cryptography in wireless sensor networks. (WSN : Wireless Sensor Networks)