Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis, Characterization and Antimicrobial activity of Amidoximated Acrylic Copolymer

Copolymer membranes were fabricated into DMP and copolymer was treated with HA in aqueous solution at 60-80°C. In the amidoximation process, a part of nitrile groups of copolymer is converted into amidoxime groups. The characterization of virgin and amidoximated acrylic copolymer membranes were carried out by using various techniques as Fourier transform infrared, X-ray diffraction, thermogravimetric analysis, Scanning electron microscope etc. With the amidoximation process various significant changes in the copolymer properties such as functionality, crystallinity, thermal behavior, hydrophilicity, elemental composition and surface morphology were observed.
Recovering and optimization routing reply for AODV in mobile ad-hoc networks

— The topology of a mobile ad hoc network (MANET) may change unexpectedly and rapidly due to the mobility of its nodes, and thus, setting up a highly reliable route is very challenging. Most protocols of ad hoc networks are composed of two main mechanisms, “Route Discovery” and “Route Maintenance”, that work together to allow the nodes to discover and maintain routes to arbitrary destinations. It is well known that broadcasting, a mechanism for route discovery and route maintenance in Ad hoc On-demand Distance Vector (AODV) routing protocols wherein a source node broadcasts a route request to all other nodes in the network, has a limitation of a high number of unsuccessful packet deliveries. The loss of route reply packets will cause serious impairment to the performance of on-demand routing protocols as well as increasing the cost. The AODV–Recovering and Optimization Routing Reply (RORR) mechanism proposed in this paper is expected to eleminate the wastage of control packets while finding the route to destination using the concept of ‘trustworthy distance’. In addition, if a link breakage occurs while route reply packets are being sent, this mechanism will identify a new route with the help of a ‘recover node’. We performed extensive simulation studies to evaluate the performance of AODV-RORR and found that RORR improved the performance of AODV significantly in a wide range of system parameter values and in all critical metrics, including packet delivery ratio, control overhead and end-to-end delay.
Design And Implementation Of A Door Locking System Using Android App

: The Android Operating System finds wide use in smart phones and tablets and is thus suitable for home controllers. This project presents a smart home controller that uses the Bluetooth in an Android device to control the operation of an automated security door system. The software was designed using an Android app that generates a password that is recognized by the Bluetooth to control the opening and closing of the door located at some distance from the user. The Bluetooth module that is installed on the door receives the commands from the android phone, and passes these commands to the microcontroller that controls the opening and closing of the door. The design was simulated in Proteus integrated development environment after which the hardware was built on experimental boards. The performance of the system agrees excellently with its conception. The system can be used in various situations where access to an enclosure need to be secured
Antibiotic Profile of Bacterial Species Isolated from Broiler Chickens with Cellulitis.

The present study was carried out to isolate and identify the bacterial agents involved in field cases of avian cellulitis in broiler chickens and also to examine isolated bacteria for antibiotic susceptibility. The study was applied on 290 broiler chickens, aged 30-35 days, suffered from cellulitis (65 with head and 225 body lesions) to isolate bacterial agents. All obtained isolates were identified and tested for the pathogenicity based on Congo red assay. Disc diffusion test was used to study the sensitivity pattern of bacterial isolates with determination of multiple antibiotic resistance index. Results revealed that all head and 91.5% of body samples were positive on bacteriological examination. E. coli was the most prevalent isolate (45.2%), followed by staphylococci (33.2%), Clostridia (5.4%), streptococci (5.1%), Proteus mirabilis (4.4%), Enterobacter spp. (3.2%), Pseudomonas aeruginosa (2.2%), and Aeromonas spp. (1.2%). Congo red binding test was positive for P. aeruginosa (100%), Clostridia (72.7%), E. coli (65.8%), staphylococci (62.2%), Aeromonas spp. (60%), P. mirabilis (38.9%), Enterobacter spp. (38.5%) and streptococci (33.3%). Serological typing of E. coli identified nine O serotypes, with high predominance of O78 (19%). On antibiotic susceptibility profiling, E. coli isolates demonstrated 83.1-92.9% resistance to chloramphenicol, tetracycline, and enrofloxacin. Staphylococci isolates showed high resistance to ampicillin (97.0%) and clindamycin (82.9%). Clostridial and Aeromonas spp. isolates showed 100% resistant to tetracycline, enrofloxacin, and cefotaxime. Enterobacter spp. showed 100% resistance to chloramphenicol and cefotaxime. P. aeruginosa had 100% resistance to tetracycline and enrofloxacin. Also, streptococci isolates showed 100% resistance to erythromycin. Totally, 56.3% bacterial isolates were multidrug-resistant, 23.8% extensively drugresistant and 1.5% pan drug-resistant. The present study concluded that E. coli is the most predominant pathogen involved in cellulitis, particularly O78 serotype. In addition, this study demonstrated high prevalence of multidrugresistant bacteria among isolates, particularly against commonly used antibiotics. Therefore, it is recommended to use antibiotic sensitivity tests and accurate therapeutic doses to efficiently treat and control bacterial infections in poultry.
Antiangiogenic Activity of Pithecellobium Dulce Methanolic Leaf Extract Using Hen Cam Method

Vijaya Institute of Pharmaceutical Sciences for Women,Enikepadu, Vijayawada. Corresponding Author: shanthikrupa@gmail.com __________________________________________________________________________________ Abstract Switching from the avascular phase to the vascular phase is a necessary process for tumor growth but none of the conventional therapies targets the inhibition of cancer angiogenisis. The present study aims at the extraction of the flavonoid from the leaves of Pithecellobiumdulce plant using methanol and determining the antiangiogenic activity of the methanolic extract using the innovative HEN-CAM model. Materials and Methods: The PithecellobiumdulceMethanolic leaf extract (PDME) was subjected to the phytochemical analysis. Thirty eggs were procured and divided into five groups(n=6). Group I, II III, IV and V are treated with Distilled Water, Hydrocortisone, PDME 10 μg/ml, 100 μg/ml and 1000 μg/ml respectively. The HENCAM Method was used to determine antiangiogenic effect of PDME using Antiangiogenic score, Branching Points and CAM Vascularity of eggs. The final results of our study had shown that the Hydrocortisone is having more angiogenic score (2), followed by the 1000 μg/ml PDME (1.89). Branching points of Distilled Water is 83.00, Hydrocortisone is 48.00, 1000 μg/ml PDME is 46.00. Based on the computed data using the formula for CAM Vascularity, Hydrocortisone and 1000 μg/ml PDME had shown the highest inhibition. The present study findings, conclude that the PDME containing phytochemicals like flavonoids, can act directly on the tumor blood vessels, inhibit the origin of the tumour at their molecular level and produces a strong antiangiogenic effect. In future the anticancer theraphy should also include the use of cheap, less toxic, easily available antiangiogenic plant extracts like PDME, to inhibit the progression of cancer.
Hand Gesture Recognition in Multi-space of 2D/3D

Summary Recent human-computer interaction studies focus on natural interface based on hand/finger movements by tracking body motion using various sensors. In this paper, we propose ‘Surface Gesture’ recognition method using both 2D surface information and 3D spatial information. ‘Surface Gesture’ is composed of continuous gestures using 2D and 3D coordinates in multi spaces. We use a touchscreen to obtain the 2D coordinate and depth sensors to obtain finger coordinates in 3D space. We decompose ‘Surface Gesture’ into 3 particular steps and recognize ‘Surface Gesture’ with tagging a label on each step. By combining accurate 2D plane information and natural 3D space gestures, our method provides a more convenient and familiar way to interact with computers. We conducted an experiment to evaluate performance of the recognition engine. Experimental results show that the proposed method provides a 94% recognition rate on particular step and an 82% recognition rate on ‘Surface Gesture’
IPL-2017 Cross Country Cluster Analysis

In this paper, an attempt has been made to study the performance of Cricket Players playing in IPL from different countries using analysis of Key Performance Indicators and to know the insights regarding which country players plays well in the League. Indian players excluded from the research as it is an Indian League in which seven out of possible eleven should be from India. Some other countries are also not considered i.e. Bangladesh, Afghanistan, Sri Lanka as count of players from these countries are very less and they are outliers for our analysis. The dataset of Players has been considered from IPL10, 2017 (20 over’s), over which cluster analysis has been applied and the findings of this study reveals that based on the Key Performance Indicators, players of England performs well from their counterparts. These kinds of research could help the franchisees to decide on their next year’s strategy although these analyses could be done at more historical data say all the IPL versions for more accuracy. KeywordsIPL , KPI, Cricket, Cluster Analysis, Buckets
AN APPROACH TO REDUCE FRAGMENTATION FOR DEDUPLICATION BACKUP STORAGE BY EXPLOITING BACKUP HISTORY AND CACHE KNOWLEDGE

: In backup systems, the chunks of each backup are physically scattered after deduplication, which causes a challenging fragmentation problem. Deduplication results inevitably in data fragmentation, because logically continuous data is scattered across many disk locations. In this work we focus on fragmentation caused by duplicates from previous backups of the same backup set, since such duplicates are very common due to repeated full backups containing a lot of unchanged data. In order to reduce the fragmentation, we propose History-Aware Rewriting algorithm (HAR) and Cache-Aware Filter (CAF). HAR uses historical information in backup systems, and CAF exploits restore cache knowledge. To reduce the metadata overhead of the garbage collection, we further propose a Container-Marker Algorithm (CMA) to identify valid containers instead of valid chunks.
Review Paper on Search and Rescue Robot for Victims of Earthquake and Natural Calamities

A rescue robot is a robot that has been designed for the purpose of aiding in most rescue workforces. In most of common circumstances that skill rescue robots are mining fortunes, urban ruins, imprisoned situations, and blasts. Rescue robots were used in the search for victims and survivors after the September 11 occurrences in New York city. The reimbursement of rescue robots to these operations include reduced personnel rations, reduced fatigue, and access to otherwise unapproachable areas.The Robotic search and rescue is valuable since robots may be deployed in dangerous environments without putting human responders at peril conditions. This project is a prototypical which is extensively used for military applications.PIR sensor is used to detect human. A Passive Infra Red sensor (PIR sensor) is an electronic device which measures infrared light radiating from objects in its field of interpretation. Seeming motion is detected when an infrared source with one temperature, such as a human, passes in noticeable of an infrared source with another temperature, it detects. It acts as a motion finder. This robot uses RF technology controlled by RF remote controller. This can be enthused forward and reverse direction using geared motors of 60RPM. Also this robot can gross high-pitched turns towards left and right directions. This project uses ARM7 MCU as its controller. Also a wireless camera with voice is rim to the kit. We are exhausting the GPS module for exact location tracker of robot when human body is detected. KeywordDC motor, GPS, PIR sensor, Wireless Camera, GSM, ARM7 MCU, Buzzer, USAR(Urban Search and Rescue Robot). __________________________________________________*****_________________________________________________
IMPLEMENTATION OF PUBLIC KEY CRYPTOGRAPHIC SYSTEM: RSA

: In many business sectors secure and efficient data transfer is essential. To ensure the security to the applications of business, the business sectors use Public Key Cryptographic Systems (PKCS). An RSA system generally belongs to the category of PKCS. RSA encryption is one of the public-key methods that have been popular in last decade. In particular, the RSA algorithm is used in many applications. Although the security of RSA is beyond doubt, the evolution in computing power has caused a growth in the necessary key length. The performance characteristics of RSA are observed by implementing the algorithms for computation. In this paper, RSA was implemented through an encryption and decryption procedures over different key sizes.
Hybrid Machine Learning Algorithm for Human Activity Recognition Using Decision Tree and Particle Swarm Optimization

: Activity recognition aims to recognize the actions and goals of one or more agents from a series of observations on the agents' actions and the environmental conditions. This paper presents different data mining algorithms for efficiently mine the human activity recognition using smart phones. The overall objective of this research work is to evaluate the performance of the J48, LAD tree and random forest tree based data mining algorithms. Then a new hybrid algorithm will be proposed for the human activity recognition using smart phones. The hybrid algorithm utilizes particle swarm optimization with decision tree algorithm to enhance the results further. The comparative analysis with existing techniques clearly indicates that the proposed technique outperforms over the available techniques.
A REVIEW ON DYNAMIC COMMUNITY IDENTIFICATION IN INTERACTION NETWORKS

Network consists of community structure, if nodes of the network can be easily clustered into group of nodes such that each set of nodes are heavily connected internally. In social media users interact in diverse ways. One of the types of network is interaction network; where it acknowledges not only social web, but also precise time that nodes take in interaction. A central problem is to study and identify core communities i.e. set of entities among which interactions are prevalent and uniform. In social groups membership often changes, it makes very hard to distinguish structure of communities. Existing method focuses on issue of identifying interaction networks in concrete dynamic communities, where edge corresponds with a time-stamp, and for the same set of nodes multiple edges may fall . In addition to the basic characteristics of node this method considers interaction time for community analysis. In some specific time instances groups of individuals who interact with each other are represented in such communities. Proposed work focuses on social network analysis using additional information such as frequency, hash tags, vocabulary for discovering the community which may result in finding community in an efficient way.
A Survey on Automatically Annotating Learning Objects with Competence Leveling

Online learning is becoming an essential part of educational institutes. Educational institutes apply competence in order to know the ability or skill of students. Many educational resources are available online. The learning objects enriched with compete nce information supports the learners for retrieving the relevant resource. The non-annotated learning objects pose a challenge for efficiently accessing and retrieving the learning resources by the users; that is the cold-start problem. To address this problem, learning resources are automatically annotated by automatic tag annotation method which is known as α-tagging LDA method, i.e. Latent Dirichlet Allocation which is based on a probabilistic topic model. The competence levels which are annotated to learning objects by experts in the subjects of their interest is a time consuming process. Therefore the learning resources which are available online could not enclose competence information due to this problem. This survey studies how educational resources are assigned automatically with competence levels, the approaches are: first facilitate competence assignment task by experts and second: supporting the learners to search and retrieve proper leveled material. The main focus of this survey is to enrich learning resources with competence, which provides the learners in identifying the effective resources which make the learners reach their target competence.
Comparative Study of Initial Centroid based K-Mode Algorithm

— Clustering is one of the techniques of the data mining, which defines classes and put the objects into one group having similar properties and objects having dissimilar properties into another group. An extension of the K-Means Algorithm, K-Mode Algorithm, is partitioning based clustering algorithm but it does not guarantee for the optimal solution. In this paper, there is the comparative analysis of Ini_Distance and Ini_Entropy Algorithm with Cao’s methods, WK-Mode with Chan’s Algorithm, Harmonic K-Mode with K-Mode and EC K-Mode Algorithm on real datasets. These algorithms are based on the selection of initial centroids in which the clustering accuracy is improved. The algorithms discussed in this study can be improved further by other better optimization techniques through research made in this field.
A Strategic Framework for Feature Selection in Banking Sector for Credit Risk Analysis

: Feature selection in data mining is critical as it generates optimum subset of features which are relevant for any classification model study. Selecting the optimum subset of features helps to improve the performance of the classifier. A large volume of data gets accumulated on a daily basis in banking industry as part of its various operations. Data is collected and stored in data warehouses for further processing. Information obtained from this data related to customers, transactions, services etc, if analyzed closely can contribute to the growth of industry to a large extent. But the vastness of data and the large number of features in the database makes this analysis a tedious process. Feature selection helps to remove the irrelevant features that adversely affect the performance of learning process in a classifier. A framework combining both filter and wrapper approaches are proposed in our work and an aggregate ranking strategy is followed to select the best features for classification. Naïve Bayes classifier is used in the wrapper method. A district bank dataset is used for testing both approaches and optimum features are selected for further experimental studies in classification.
Drug Eluting Beads for Unresectable Hepatocellular Carcinoma: Does it Need Another Look? Egyptian Single Center Pilot Study

Background: Transarterial chemoembolization (TACE) is a commonly used primary treatment for unresectable hepatocellular carcinoma (HCC). Drug eluting beads is a system that potentially can improve TACE outcome. Aims: This study was held to compare between conventional TACE (cTACE) and TACE using drug eluting beads (DEB) regarding safety, progression free survival and overall survival. Methods: In this non-randomized pilot study fifty HCC proven patients were allocated to either conventional TACE group (n = 25) or using drug eluting beads group (n=25) during the period from April 2011 till October 2014. Patients were followed up for tumour progression and survival till October 2017. Repeated TACE sessions were performed individually on demand according to the allocated line of treatment. Results: Fifty patients with HCC (5 BCLC A and 45 BCLC B) with mean age 56.78 ± 6.3 years were included. Both groups were matched regarding baseline characteristics, tumour burden, Child class and BCLC stage. TACE using DEB was associated with less hepatotoxicity. Median time to progression was four months in both groups’ Patients who underwent TACE using drug eluting beads showed significant better o median survival time than those underwent cTACE (26 versus 18 months respectively with p value 0.014). Three years survival was 32% in conventional TACE and 44% in drug eluting beads. In conclusion TACE using DEB was associated with less hepatotoxicity. Patients received TACE using drug eluting beads showed significantly better median survival time. Trial registration number: ClinicalTrials.gov (NCT03007225)
on Recent Trends in Science, Technology, Management and Social Development

In this work, we present a deep learning model based on reinforcement learning that is tied to an AI agent. The agent successfully learns policies to control itself in a virtual game environment directly from high-dimensional sensory inputs. The model is a convolutional neural network, trained with a variant of the Q-learning algorithm, whose input is raw pixels and whose output is a Q-value directly associated with the best possible future action. We apply our method to a first-person shooting game - Doom. We find that it outperforms all previous approaches and also surpasses a human expert.
Enjoyable Informal Learning at Cultural Heritage Site using Mobile Augmented Reality: A Conceptual Model

: Currently, learning at cultural heritage sites is not adequately provided and supported by the current existing information display provided at the sites although visitors require it. Mobile augmented reality is an alternative way to cater the problem which could enhance the visiting experience through the concept of enjoyable informal learning. Therefore, this study proposes a conceptual model of mobile augmented reality for cultural heritage site towards enjoyable informal learning experience for the visitors. Critical analyses, literature review, and comparative studies of seven related conceptual models are conducted to define the research gap and suggest the components of the proposed model. The outcome of this study is the proposed model which is expected to be as a guideline for the development of mobile AR application for cultural heritage sites, where visitors would enjoy and learning informally with the application.
SECURITY AND EFFICIENT SERVING IN PUBLIC DATA SCRUTINIZE IN POVERTY CLOUD COMPUTING

Users in a particular group need to compute signatures on the blocks in shared data so that the shared data integrity can be confirmed publicly Various blocks in shared data are usually Enabling complete user control over his data, anonym sing security the sensitive data in outsourcing, finding the data owner take data access the serve take helping in the progress of strengthening the security and efficient model in Cloud Computing number of models is Homomorphism Authenticable Ring Signature (HARS), security and efficient public auditing System for data storage security is discussed Public key cryptosystem the MD5 Message-Digest Algorithm is depicted. Proof Irretrievability system for public verifiability is described. Dynamic Provable Data Possession (DPDP) to enlarge the PDP model is discussed in detail. LT codes based cloud storage service (LTCS) to empower efficient decoding Markel Hash Tree (MHT) for the block tag security message is discussed the semi trusted cloud can resign the blocks that were previously signed by the revoked user with the valid proxy re-signatures, when a user in the group is revoked.