Miracle-dz/UniFAR-FTUs huggingface dataset:
DAMAGE ASSESSMENT IN STRUCTURE USING FREQUENCIES AND OPER DEFLECTION SHAPES

This paper describes the application of vibration modal analysis for monitoring and locating damage inside a wooden wall structure, by evaluating damage-sensitive parameters such as resonant frequencies shapes (ODS). Artificial damage was created in one of the walls of a specially constructed room. The wall was excited using an impact hammer and its frequency response was measured with a laser vibrometer. Damage extracted from the frequency response and utilized for assessing damage, both qualitatively and quantitatively. Resonant frequency shifts and changes in ODS were used for detecting and monitoring the progression of damage, qualitatively. These methods make direct use of FRF data will help a lot in identifying da
A Survey Paper On Drowsiness Detection & Alarm System for Drivers

Our safety is the first priority while travelling or driving. One mistake of the driver can lead to severe physical injuries, deaths and significant economic losses. Nowadays there are many systems available in market like navigation systems, various sensors etc. to make driver’s work easy. There are various reasons especially human errors which gives rises to the road accidents. Reports say that there is a huge increment in the road accidents in our country since last few years. The main reason occurring from the highway accidents is the drowsiness and sleepiness of driver while driving. It is a necessary step to come with an efficient technique to detect drowsiness as soon as driver feels sleepy. This could save large number of accidents to occur. We conduct the survey on various designs on drowsiness detection methods to reduce the accidents.
INTELLIGENT ALCOHOL DETECTION SYSTEM FOR CAR

The purpose of this project is to develop vehicle accident prevention by method of alcohol detector in an effort to reduce traffic accident cases based on driving under the influence alcohol. This project is developed by integrating the alcohol sensor with the microcontroller 16F877A. The alcohol sensor used in this project is MQ-2 which to detect the alcohol content in human breath. An ignition system which will produce spark plugs is build up as a prototype to act like the ignition starter over the vehicle’s engine. The ignition system will operate based on the level of blood alcohol content (BAC) from human breaths detected by alcohol sensor.The main purpose behind this project is “Drunk driving detection”. Now a days, many accidents are happening because of the alcohol consumption of the driver or the person who is driving the vehicle. Thus Drunken driving is a major reason of accidents in almost all countries all over the world. Alcohol Detector in Car project is designed for the safety of the people seating inside the car. This project should be fitted / installed inside the vehicle.
A Survey of Duplicate And Near Duplicate Techniques

---- World Wide Web consists of more than 50 billion pages online. The advent of the World Wide Web caused a dramatic increase in the usage of the Internet. The World Wide Web is a broadcast medium where a wide range of information can be obtained at a low cost. A great deal of the Web is replicate or near-replicate content. Documents may be served in different formats: HTML, PDF, and Text for different audiences. Documents may get mirrored to avoid delays or to provide fault tolerance. The problem of finding relevant documents has become much more prominent due to the presence of duplicate data on the WWW. This redundancy in results increases the users’ seek time to find the desired information within the search results, while in general most users just want to cull through tens of result pages to find new/different results. This survey paper has a fundamental intention to present an review of the existing literature in duplicate and near duplicate detection of general documents and web documents in web crawling.
Antimicrobial finishes for Textiles

Infestations by micro-organism instigate cross disease by pathogens and odor develops in fabric have direct contact with the skin. Moreover, discoloration, tints and loss of functional characteristics of textiles are consequence of microbial damage. Antibacterial finished textile is an important area for medical and hygienic applications and there is enormous need of non-toxic and eco-friendly antimicrobial agents. The synthetic biocides finishes extensively reported were polyhexamethylenebiguanide (PHMB), quaternary ammonium compounds (QACs), metals (including metal oxides and salts), triclosan and n-halamines. Whereas, the natural based biocides (aromatic compounds, dyes, essential oil), chitosan and antimicrobial peptides (AMPs) were mainly considered among plant-based extracts. This paper will cover briefly, review of the latest research work on antimicrobial finishing, types of finish agents and various current developments in antimicrobial finishing to minimize the risks associated with application of organic, inorganic and plant based antimicrobial finishes.
FORMULATION AND EVALUATION OF NATURAL ULTRASOUND GEL FOR PHYSIOTHERAPY TREATMENT

: Commercially available ultrasound gel contains lot of chemicals like carbapol R 940 polymer and phenoxyethanol which are allergenic to skin, expensive and not available in enormous quantities. The demand for ultrasound gel is due to its wide range of applications medical and paramedical fields. Hence, our objective was to formulate and evaluate the ultrasound gel made from natural starch powder. The gel was made by heating water with corn starch. The formulated gel was used for physiotherapy ultrasound treatment with the addition of Aloe vera gel to get fast pain relief in the affected area. The results showed that the formulated ultrasound gel and its ingredients were consistent in quality and can be easily used. The formulated ultrasound gel was found to be superior to commercially available gel in part of pain management score. It is concluded that the formulated ultrasound gel can be used for ultrasound physiotherapy treatment. However, further studies are warranted to confirm its effectiveness and also to develop into commercial standards.
497-504 Mehdi-April 24 2015- F

In this paper, a new wireless power transmission me thod is proposed to supply deep brain stimulators. By using a wireless charger, the surge ry for replacing the stimulator’s batteries and all of its problems including infection, pain, and making patients uneasy, have been omitted. The Resonance inductive coupling (RIC) method is chosen among the different wireless power transmission methods and a resonance-based structur e is designed. There are some simulations and practical experiments at the end of the paper w hich show this structure can generate 324 milliwatt power. Also, the efficiency of this system in 10mm distance is 41.62%
Performance Comparison of Adaptive Filter Algorithms for ECG Signal Enhancement

In this paper various adaptive filter based algorithms that can be applied to ECG signal in order to remove various artefacts from them are presented. The goal of the paper is to show the comparison based on signal to noise ratios of all the adaptive filter algorithms used for the analysis of ECG signals with Power line Interference. Simulation studies shows that the proposed novel algorithms like NLMS and DLMS based adaptive systems present better performances compared to existing realizations LMS, SRLMS and NSRLMS based procedures in terms of signal to noise ratio. Keywords—ECG, Adaptive filter Algorithms, LMS, NLMS, DLMS, SRLMS, NSRLMS.
Semantic Object Extraction of Videos using FCM-GA in VISCOM

— Video-based applications are largely being used. these days. These applications include video surveillance, criminal detection and sports video analysis etc. In order to extract video semantic content, an Automatic semantic content extraction framework is used which make use of VISCOM to extract object, events, concepts and represents spa tial /temporal relationship between them. In this model image segmentation is being performed using Genetic algorithm based classifier. To find the optimal solution from genetic algorithm, it is required to maintain the larger population size. In some cases, however, the cost to evaluate each individual is relatively high and it is difficult to maintain large population. To overcome this problem a partially evaluated GA based fuzzy clustering technique is used which considerably reduces evaluation cost without any loss of its performance. It evaluates only one representative for each cluster. Proposed hybrid approach uses Fuzzy c-means clustering algorithm in combination with GA. FCM helps GA in selecting the population and fitness function is applied using FCM. When we apply fuzziness and number of iterations on the candidate population, we get the clustered population which is fed to Genetic Algorithm and segmentation takes place. For Empirical study sports videos are used to evaluate the implemented proposed approach.
Synthesis of Cr2O3/TiO2 Nanocomposite and its Application as the Blocking Layer in Solar Cells

In this study, Cr2O3/TiO2 nanoparticles were synthesized using sol-gel method. TiO2 as one of the most important semiconductor materials with a variety of applications in many fields including photocatalysis and solar cells combined with Cr2O3 as a mineral material and one of the basic oxides used as pigments to improve properties such as mechanical strength, thermal stability form the Cr2O3/TiO2 nanocomposite showing attractive applications in photocatalysis and solar cells. To this end, its application in solar cells has been investigated to testify its performance. The results were promising in the case of solar cell. Cr2O3/TiO2 nanocomposite solution formed a compact layer with low defects and grain boundaries while it was sprayed as blocking layer (TiO2) in superstrate structure CZTS solar cells (Glass/FTO/TiO2/In2S3/CZTS/carbon). Compared to individual TiO2 blocking layer, the asdeposited layer showed better quality and performance. X-Ray was used to confirm synthesized nanoparticles and their morphology was investigated by Field-Emission Scanning Electron Microscopy (FE-SEM).
Impact of Prior-preparation on Error Correction during Classroom Oral Discourse: Study of the Self- repair Behavior of Sri Lankan ESL Learners

This study is concerned with the organization of linguistic repair during classroom oral production. It aims to investigate the effect of preparation prior to an oral delivery on the selfrepair behavior of an ESL (English as a Second Language) learner. The notion that preparation with time, material & practice is essential for a flawless oral delivery is examined in this study based on the assumption that prior-preparation generates a favorable impact on the patterns of error correction. A quantitative approach is used in collecting and analysing the data on the frequency of self-repair type, strategy, initiation technique and the grammatical accuracy of repair during prepared and impromptu speeches of a sample of adult Sri Lankan learners learning English as second language in the tertiary education system. The results reveal that planning does not necessarily affect the repair behavior and effectiveness and efficiency of the oral delivery of the learner.
IN VITRO ANTIFUNGAL, ANTIBACTERIAL AND ANTIOXIDANT ACTIVITY OF ESSENTIAL OIL FROM THE AERIAL PARTS OF AGRIMONIA AITCHISONII SCHONBECK TEMESY FROM HIMALAYAN REGION

The essential oil from the aerial parts of Agrimonia aitchisonii Schonbeck Temesy growing in the Himalayan region is evaluated for its antifungal, antibacterial and antioxidant activity. The oil has shown 100% mycelia growth inhibition against S. sclerotiorum, A. tenuis, C. graminicola and F. oxysporum at a concentration of 2000μg/ml, 2000μg/ml, 3000μg/ml and 3000μg/ml respectively. However R. solani was found less susceptible to the oil of Agrimonia aitchisonii. The IC50 values showed a range from 41. 10μg/ml – 85. 44μg/ml as compared to standard fungicides with IC50 values 32. 8μg/ml – 98. 6μg/ml. The spore germination inhibition test has shown the IC50 values as 101. 4μg/ml, 314. 74μg/ml and 684. 7μg/ml for A. tenuis, C. graminicola and F. oxysporum respectively. The ZOI for the test bacterial strains at a concentration of 500μg/ml were Gram negative bacteria Pseudomonas aeruginosa 424 (7mm), Escherichia coli 443 (4mm), Aeromonas hydrophila 646 (8mm) and Gram positive bacteria Bacillus subtilis 441 (4mm) and Staphylococcus aurieus 737 (6mm). The oil has shown 435.7 ± 0.004 mg/ml gallic acid equivalent per 100mg of the oil as total phenolic content and 423 ± 0.003 mg/ml quercetin equivalent per 100 mg of the oil as total World Journal of Pharmaceutical Research SJIF Impact Factor 6.805 Volume 5, Issue 3, 1747-1763. Research Article ISSN 2277– 7105 Article Received on 18 Jan 2016, Revised on 08 Feb 2016, Accepted on 28 Feb 2016
DO FINANCIAL CONSTRAINTS EXPAND LEASE FINANCING CAPACITY? IN PERSPECTIVE OF MALAYSIAN FIRMS

The purpose of this study is to analyse the relationship between financial constraint factors that can affect the chosen of leasing for the firm in Malaysia. The sample of data consist of 1150 firms including listed firm, unlisted firm and SMEs with the total number of firm-years observation are 8339. This study cover 7 years period from year 2007 until 2014. The dependent variable are lease ratio and debt ratio while the independent variable are the financial constraint determinant such as internal funds, growth, collateral, and size. This study also include control variables such as uniqueness (R&D expenses), tax loss and macroeconomics factor such as based lending rates (BLR). The results indicate that not all financial constraint firm tend to used lease financing compare to debt financing. It depends on what types of financial constraint that the firm face. For this analysis, the firm that have financial constraint in internal funds, collateral and size tend to used lease compare to debt financing. However, for the firms have less growth opportunities, it is difficult for them to choose either lease or debt financing because of their future survival.
Sentence Level Sentiment Analysis using Deep Learning Method

An Emoji is a small image representing facial expression, entity or a concept that can be either static or animated. In this paper, Emojis are used to study both crosslanguage and language based sentiment patterns. All the languages do not come with fair amount of labels. Emojis are useful signs of sentiment analysis in cross-lingual tweets. In this paper, an approach is proposed to extend the existing binary sentiment classification using multi-way classification. A novel Long Short-Term Memory (LSTM) - Convolutional Neural Networks (CNN) based model is proposed to obtain sentiments from emojis. The sentiments are classified using Deep Learning method like CNN. The proposed system outperforms the existing system in terms of Accuracy, Precision, Recall, F-Measure and Time Period. Finally the researcher manifests the fact that the CNN and LSTM combination as model shows an immense improvement to detecting the sentiment targets.
BOTNET DEFENSE IDENTIFICATION USING PULL AND PUSH MECHANISM

Botnet is a computer network that are owned and controlled bya an bot attacker. Botnets are one of the most serious threats to today’s internet. Botnet are a major threat to internet because it consists of large pool of compromised computer that are organized by a master. Some model is necessary to develop the intelligence to identify, detect, and mitigate the risk of an attack. E.g Zombie armies carry out sophisticated attacks to disrupt, gather sensitive data or increase armies. Armies are in the 1000’s to cumulative calculating power. Communication network allows bots to evolve on a compromised host. So it became a cybercriminal threat to society. This paper states the motivation change in computer hacking and also systematically to study P2P botnet along multiple dimensions in botnet construction, command and control mechanisms, performance measurements and mitigation approaches.
Technical, Allocative, Scale and Economic Efficiencies of Paddy Production farms in Terai and Coastal Zones of West Bengal using Data Envelopment Analysis

The dream of agricultural growth in less developed countries with given scanty resource endowment and limited technology could be achieved by enhancing the efficiency of production. Data envelopment analysis is used to estimate the technical, allocative, economic and scale efficiencies of farms under paddy production in terai and coastal agroclimatic zones of West Bengal. The results revealed that most of the fields have high mean technical (≥ 0.90) and scale (≥ 0.93) efficiencies, implying that inputs are used in minimum levels necessary to achieve given output levels. On the other hand, most of the fields’ exhibited allocative (≥ 22%) and economic (≥ 28%) inefficiencies imply that the existence of inefficiency in application of inputs necessary to achieve cost minimization. The paddy farms in terai zone have exhibited high efficiency scores compared to the farms in coastal zone.
An Encroachment Detection and Protection Using Data Mining and Forensic Techniques

— User IDs and passwords are the main login patterns used by the computer systems for the authentication purpose. By sharing the passwords with a third party there will exists a security issue. Internal encroachment is hard to detect. Because most encroachment detection systems and ﬁrewalls identify and isolate malicious behaviors launched from the outside world of the system only. To accurately detect the attacks, we have to analyze the system calls (SC) generated by commands. Here we propose a security system to detect insider attacks at SC level with the help of data mining and forensic techniques. The security system is named as Encroachment Detection and Protection System (EDPS). The EDPS creates users’ personal proﬁles to keep track of users ’usage habits as their forensic features and determines whether a valid login user is the account holder or not by comparing his/her current computer usage behaviors with the patterns collected in the account holder’s personal proﬁle. The EDPS prevents a system from insider attacks with an identification accuracy of 94.29% and response time is less than 0.45 s.
Detection of Lung Boundary in Chest X-rays using Adaptive Lung Atlas and Graph Cuts

In contrast to film X-rays the advent of digital X-rays has led to the use of computer assisted systems to automatically detect and diagnose diseases. Though CT and MRI are known for its diagnostic superiority Chest X-rays still remains the mainstay of chest imaging and is widely used by doctors to access various chest related ailments which includes pathologies related to lungs, esophagus, blood vessel, diaphragm, trachea, bronchia etc. The applicability of any computer aided diagnosis system (CAD) mainly depends on the accurate segmentation of the region of interest (ROI). In this work we have attempted to accurately segment the lung boundary using atlas based methods and non-rigid registration of atlases to patient specific adaptive lung models. The proposed work first applies a content based retrieval approach to select similar X-rays (lung masks) to that of the test X-ray using similarity measures and then an atlas of the test lung is obtained by SIFT-flow registration of the test X-ray with that of the retrieved masks. Finally graph-cut optimization is applied to extract the exact lung boundary.
Cooperative Caching Using Dynamic Nodes for Efficient Data Access in Disruption Tolerant Network

- Disruption Tolerant Networks (DTNs) are characterized by unpredictable node mobility, low node density and lack of global network information. Most of research efforts in DTNs focus on data forwarding; only limited work has been made on providing efficient data access to mobile users. Here we propose a novel approach to support cooperative caching in DTNs, which provides the sharing and coordination of cached data among multiple nodes and reduces data access delay. Our basic design is to intentionally cache data at a set of Network Central Locations (NCLs), which can be easily accessed by other nodes in network. An efficient scheme which ensures appropriate NCL selection based on a probabilistic selection metric and coordinates multiple caching nodes to optimize the tradeoff between caching overhead and data accessibility. Extensive trace-driven simulations show that our approach signiﬁcantly improves data access performance compared to existing schemes .
An Improved Efficient Certificate Less Data Transmission (CL-EKM) In Mobile Ad-Hoc Network

: Wireless Sensor Networks (WSNs) have recently developed as a platform for numerous important surveillance and control applications. In the third phase of this research work, a Hybrid Group based Re-Key Management Scheme (HG-RMS) is proposed for securing the group combination in WSN. The suggested HG-RMS approach uses the Hybrid Energy Efficient Distributed (HEED) protocol for electing the group controller for every group. The generation and distribution of keys to the group controllers is performed using RSA algorithm. By exploiting the key exchange mechanism a secure communication is provided between the users. The forward and backward secrecy is achieved using re-keying phase. When compared to the existing Cluster based Group Key Management (CL-GKM), the energy consumption, privacy level, memory, key accuracy and time consumption of the proposed approach is optimal. In this research work, a certificate less effective key management (CL-EKM) is proposed for securing the group combination in WSN. By exploiting the key exchange mechanism a secure communication is provided between the users. The forward and backward secrecy is achieved using re-keying phase. When compared to the existing Methods, the energy consumption, privacy level, memory, key accuracy and time consumption of the proposed approach is optimal.
PERFORMANCE EVALUATION OF CLUSTERING BASED CONTENT BASED IMAGE RETRIEVAL SYSTEMS

-Retrieving images from available databases attracted researchers due to its ability to retrieve images in accurate and reliable way. Content based image retrieval scheme (CBIR) has lot of advantages over conventional META data based image retrieval scheme. The computer vision based application has huge importance in the field of digital image processing and content based image retrieval scheme (CBIR) yields good results based on three contents namely color, shape and texture. The color based content based image retrieval (CBIR) scheme is simple and efficient. Although tremendous progress has been made in the past years on image retrieval schemes but still acquiring images from large data sets based on various traditional image retrieval schemes is concerned area in the image processing domain. The proposed work presents content based image retrieval scheme (CBIR) based on three algorithms namely (a) Content based image retrieval scheme (CBIR) based on histogram properties (b) Content based image retrieval scheme (CBIR) based on histogram properties with K-Means clustering (c) Content based image retrieval scheme (CBIR) based on histogram properties with pillar K–means clustering. Finally the simulation results shows better accuracy and reliability in retrieving images in digital computers and the performance of the proposed system overcomes the disadvantages of the traditional systems.
A New Approach of Prediction of Memory Leak in the Cluster Computing Applications

paper presents a memory leak prediction algorithm for the cluster computing applications. This proposed algorithm uses process characteristics to calculate the exact memory requirement and uniquely identifies maximum memory utilization of an application before the application starts its execution. During the appffplication execution phase, memory leaks in the application processes in the cluster is identified by existing Dynamic Memory Monitoring Agent (DMMA) gives information to the end users to make corrective actions and removes memory leak processes from the affected nodes. This unified approach increases the reliability and fault tolerant in the cluster computing.