bluuebunny/crossref_metadata_2025_split huggingface dataset:
Milk quality testing using intelligent inference performance evaluation system integrated with IoT
Authors: Suresh Babu G , Rama Krishna V , Dharma Teja V , Balraj Yadav S 
Published: May 2018

One of the major used food item in day to day life is milk. Many large-scale industries are in the distribution of milk products. Quality of milk is one of the major factor in the food processing system and customers appreciate quality products. IoT is revolution and it is using extensively in our day to day life. Our project is about maintaining the quality of the milk as it’s a perishable product. In this paper we concentrated on how the milk is depending on the different factors available in it and each one effects the quality. An attempt is made to analyze the data from the sensors with IoT used in the milk production with the help of Artificial Neural Network (ANN). The results are exhibited through an example.
Secure automated threat detection and prevention (SATDP)
Authors: Ramaiah CH , Adithya Charan D , Syam Akhil R 
Published: May 2018

Secure automated threat detection and prevention is the more effective procedure to reduce the workload of analyst by scanning the network, server functions& then informs the analyst if any suspicious activity is detected in the network. It monitors the system continuously and responds according to the threat environment. This response action varies from phase to phase. Here suspicious activities are detected by the help of an artificial intelligence which acts as a virtual analyst concurrently with network intrusion detection system to defend from the threat environment and taking appropriate measures with the permission of the analyst. In its final phase where packet analysis is carried out to surf for attack vectors and then categorize supervised and unsupervised data. Where the unsupervised data will be decoded or converted to supervised data with help of analyst feedback and then auto-update the algorithm (virtual analyst). So that it evolves the algorithm (with active learning mechanism) itself by time and become more efficient, strong. So, it can able to defend form similar or same kind of attacks.
Robust and brittle secured video for IOT
Authors: Lakshmi Narayanan K , P. Ramesh G , Divya V 
Published: May 2018

In this paper the system is mainly designed for the military purpose security since now-a-days securing our military has become a difficult task .our live is mainly dependent on other objects mainly we are computer based living and digital image processing plays a vital role in it. This process has much advantage as well as some disadvantage. A VLSI circuit is built with many millions of IC chip, so it is considered to be indivisible for the construction purpose. The internet-of things (Iot) is a electronic device which is connected to the vehicle and the building item which is used to generate many secured techniques which is connected with the software, electrical, electronics and mechectronics devices and human recourses also. Better Portable Graphics Algorithm with a Context-Adaptive Binary Arithmetic Coding (CABAC) encoding algorithm is used in the existing system this process is affected by the Gaussian noise, low compression ratio and time delay to overcome above issues and enhanced with Secure Better Portable Graphics (SBPG) compression algorithm with HEVC is present .The proposed architecture is suitable for high performance imaging in the Iot and for the high quality compression files and secured transformation of image and video captured in the digital camera. Encryption and watermarking are the two technique used in the process. The watermarking technique is more secure than the previous system. This process produces high quality JPEG, and high PSNR ratio. The scrambling algorithm is used in the encryption process. It is used for providing secured image.
A Versatile and Cost Effective Multimodal Wheelchair
Authors: Sampath Dakshina Murthy A , Rudra Pratap Das Dr , S.Koteswara Rao Dr 
Published: May 2018

The aim of this endeavor is to design a wheelchair to suit to the needs of such persons .By incorporating temperature and humidity sensor, IR sensor, FSR sensor and voice recognition sensor/module ,the device is quite versatile in attending to the basic problems encountered .After testing ,it was found that this apparatus helps in avoiding obstacles. If allows the person to use his tongue of required. The additional benefit is to have voice recognition for movement .Cost effectiveness is yet another merit of the proposed system.
Interrelationship identification between humans from images using two class classifier
Authors: Verma Amit , Meenpal T , Acharya B 
Published: May 2018

The paper proposes an automatic interrelationship identification algorithm between human beings. The image database contains two interrelationship classes i.e. two people hugging and handshaking each other. The feature detection and feature extraction has been done using bag of words algorithm. SURF features and FAST features are used as feature detectors. Finally, the extracted features have been applied to SVM for classification. We have tested the classifier against a set of test images for both feature detectors. Finally, the accuracy of the classifier has been calculated and confusion matrix has been plotted.
Swarm-dular quadcopter: bringing swarm robotics and modular robotics together
Authors: Mohan Deepak , R. Guruprasad K 
Published: May 2018

In this paper, we present a new concept in robotics, which we call as swarm-dular robotics, by bringing together swarm robotics and modular robotics. We propose a swarm-dular quadcopter, which is a modular quadcopter, where, multiple wheeled ground robots (AGVs), which are part of a heterogenous swarm or multi-robotic(agent) system (MRS or MAS), attach/dock together to form an aerial quadcopter robot. We provide a conceptual design and demonstrate the proposed system using simulation experiments in Robot Operating System (ROS). Behavior of the system as both a swarm and a modular quadcopter UAV are demonstrated.
Inverted dual U slot loaded truncated microstrip patch antenna for wireless applications
Authors: Thandapani Kavitha , Subramani Shiyamala 
Published: May 2018

Dual U Slot Loaded Truncated Microstrip Patch Antenna is designed for wireless applications. The proposed geometry comprised of two inverted U slots in truncated circular patch antenna operation covering 2.24 to 2.72 GHZ frequency bands are obtained. It is found that the slot and truncated is used to improve the bandwidth and return loss respectively. The resonant frequency is found to be 2.5GHZ. The bandwidth of the proposed antenna for lower and upper resonant frequency is found to be 19.2%. The proposed antenna is fed by 50Ω co-axial probe feed and simulated on Rogers RT/duroid5880 substrate. Rogers RT/duroid 5880 substrate has dielectric constant and loss tangent of 2.2 and 0.0009 respectively. An air gap is used in this proposed design for tuning the desired frequencies and increasing the bandwidth. The antenna shows an acceptable gain of 2.1dB to 5.7dB with unidirectional pattern over the obtained frequency band.
Optimal Deployment of Camera Mounted UAVs Performing Search
Authors: Marina D’Souza Jeane , Suresh Rao Siddhartha , R. Guruprasad K 
Published: May 2018

In this paper we address a problem of optimal deployment of camera mounted UAVs for a multi-robot search application. Here multiple UAVs carrying downward facing cameras are required to look for targets of interest in a search area. The lack of information about the presence or absence of targets is modeled as an uncertainty density distribution over the search area and this uncertainty is reduced as the information is gathered using the onboard cameras. The UAVs are required to get deployed so as to maximize the uncertainty reduction. We provide a model for search effectiveness of the camera and use it to formulate a strategy for optimal deployment of UAVs. It is shown that a centroidal Voronoi configuration, where each UAV (camera) is located at the centroid of the corresponding Voronoi cell is an optimal deployment. We provide simulation results to demonstrate that the proposed optimal deployment strategy successfully deploys the UAVs into centroidal Voronoi configuration, which maximizes the uncertainty reduction using cameras as search sensors.
Remote software update in trusted connection of long range IoT networking integrated with versatile edge cloud
Authors: Caroline Kalaiselvi R , Mary Vennila S 
Published: May 2018

The Internet of Things (IoT) prompts can administered by gathering data from little sensor gadgets. As of late, stockpiling less detecting gadgets have been utilized to actualize IoT administrations. They rely upon conveyed programming from a system server to work benefit capacities and IoT administrations are in view of gathered client data. In this way, it is critical to keep up trusted associations aid programming conveyance or information transmission. In the event that a system association is deceitful, stable information transmission can't be accomplished. Dishonest information associations cause numerous issues in IoT administrations. In this manner, this paper proposes a product refresh strategy in trusted association of IoT organizing. The technique utilizes Low Power Wide Area Network (LPWAN) as long-go IoT organizing innovation and utilizations a portable edge cloud to enhance registering effectiveness in an entrance arrange that comprises of IoT gadgets with lacking assets. In the strategy, the versatile edge cloud is coordinated into a door, and forms detecting information and remote programming updates of LPWAN. IoT gadgets can get programming capacities from the versatile edge cloud. The proposed strategy investigates measurable data about associations in a get to arrange and decides the LPWAN put stock in associations. At that point, programming updates can be performed over the confided in association. Utilizing trusted associations prompts an expanded bundle conveyance rate and decreased transmission vitality utilization. The strategy is contrasted with at present accessible frameworks through PC recreation and through computer simulation and this method’s efficiency is validated.
A performance analysis of clustering based algorithms for the microarray gene expression data
Authors: Yuvaraj K , Manjula D 
Published: May 2018

Current advancements in microarray technology permit simultaneous observing of the expression levels of huge number of genes over various time points. Microarrays have obtained amazing implication in the field of bioinformatics. It includes an ordered set of huge different Deoxyribonucleic Acid (DNA) sequences that can be used to measure both DNA as well as Ribonucleic Acid (RNA) dissimilarities. The Gene Expression (GE) summary aids in understanding the basic cause of gene activities, the growth of genes, determining recent disorders like cancer and as well analysing their molecular pharmacology. Clustering is a significant tool applied for analyzing such microarray gene expression data. It has developed into a greatest part of gene expression analysis. Grouping the genes having identical expression patterns is known as gene clustering. A number of clustering algorithms have been applied for the analysis of microarray gene expression data. The aim of this paper is to analyze the precision level of the microarray data by using various clustering algorithms.
Gene selection and dynamic neutrosophic cognitive map with bat algorithm (DNCM-BA) for diagnose of rheumatoid arthritis (RAs)
Authors: Chithra B , Nedunchezhian R 
Published: May 2018

Rheumatoid Arthritis (RA) is an autoimmune inflammatory rheumatic disease that has emotional impact on various body parts and tissue, principally the synovial joints. RA is a complex disease similar to many other autoimmune diseases, in which environmental aspects, genetic variants, as well as arbitrary events cooperate to activate pathological pathways. Choosing the appropriate gene for sample classification is very hard in numerous gene expression analyses in RA, in which authors attempt to find out the least probable set of genes, even now which could attain better predictive performance. On the other hand, the accuracy of classification is not up to the mark. As a result, for identifying RA disease, this research presents a gene selection as well as classification technique. Initially, with the aim of decreasing the time complexity, this disease dataset is preprocessed. Next, so as to decrease the amount of gene, the gene data is chosen from the preprocessed data by means of filter based gene selection techniques: Chi-square (CHI), Information Gain (IG), Consistency Based Subset Evaluation (CS) and Correlation Based Gene Selection (CGS). Thirdly, for the purpose of the classification of RA disease, a Dynamic Neutrosophic Cognitive Map with Bat Algorithm (DNCM-BA) is presented, that is well-suited with the medical routine and it is proposed for supporting gene expression beforehand and accurate diagnosis of RA patients. As a result, RA disease is not permitted from moving to progressive phases and the difficulty of emerging insistent as well as erosive arthritis for RA patients will get reduced. Finally, the outcome confirms that the DNCM-BA technique provides better performance while matched up with FCM–Particle Swarm Optimization (FCM-PSO), Fuzzy C Means (FCMs), Dynamic Firefly Algorithm Fuzzy C Means (DFAFCM) and Dynamic Fuzzy C Mean (DFCM) clustering algorithms in regard to precision, accurateness, recall and F-measure.
Studies on mechanical properties of luffa acutangula/lignite fly ash reinforced composites
Authors: Jino R , Sriraman M , Arthika B , G. Ashok K 
Published: May 2018

The demand of using natural fibers in various applications were increasing day by day due to its eco friendly nature over the artificial fiber based polymer matrix composites. This paper describes the fabrication and evaluation of mechanical and thermal properties of Luffa Acutangula fiber with and without Lignite Fly Ash. The lignite fly ash was added as a filler material in the ratio of 0, 0.5, 1, 1.5, percent of weight along with the matrix and fiber. The laminates were fabricated using hand layup technique and the samples were prepared based on ASTM standards for testings.The tensile test was performed using universal testing machine. The addition of filler lignite fly ash has shown the improvement in mechanical and thermal properties of laminated composites. The Tensile, flexural, and compression test was conducted for the fabricated samples and it was observed that the influence of lignite fly ash on natural fiber leads to the increase in tensile strength and compressive strength but the flexural strength was reduced for the fabricated laminates with the filler material lignite fly ash. The morphological analysis was carried out for finding the fractured surface and material failures using scanning electron microscope (SEM).
Internet of things for industrial monitoring and control applications
Authors: A. Karthika R , Rahamtula Shaik , Anusha Yalavarthi 
Published: May 2018

Smart enterprise is an observing, controlling and investigating carrier which incorporates wireless transmission generation and electronic sensor innovation. It permits the client to get the overall scope of services, the opportunity for continuous monitoring and automated controlling of industrial environment. This paper was advanced to provide internet based totally smoke and temperature and security tracking. This device is allowed to track the facts every time & everywhere from the source of the internet whenever we login into internet. This paper also concludes that person can set restriction for above parameters & if these parameters cross beyond that cost, it's going to activate the devices. As a part of its alarm gadget, it'll play the recorded sounds: “intruder” or “smoke detected” when there may be a detection. The credit score card size Raspberry Pi (RPI) with Open source pc vision (OpenCV) software program handles the photo processing, control algorithms for the alarms and sends captured snap shots to consumer’s e mail through wireless. In this project Raspberry Pi3B+ is used.
CAD system: a content based image retrieval approach for pulmonary nodule detection in CT images
Authors: Ram Sajeev , . Shylaja , Sahayadhas Arun 
Published: May 2018

This paper proposes Computerized Aided Detection System (CAD) which uses Content Based Image Retrieval (CBIR) to detect cancer nodules present in an image. The CAD system is concerned for the radiologists to identify lung cancer at premature stages, which are very tiny nodules that are not able to seen by naked eye. In modern years, Image processing techniques play a key role in predicting diseases at early stages in particular in various cancer types such as liver cancer, breast cancer etc. This paper comprises of four steps: i) preprocessing an image in order to lessen the noise level and the accuracy of the image is to be improved, so that the accuracy in detection will be higher. ii) The image is segmented based on Marker-Controlled Watershed Segmentation. iii) The features of the nodules present in the image are extracted using GLCM. iv) The nodules are classified based on the extracted features using KNN classifier. The Content Based Image Retrieval Technique is used which is used to redeem query based images in the database by combining feature extraction and similarity matching methods. For experimentation of proposed technique, CT images are used which are extracted from Lung Image Database Consortium database (LIDC).
IoT based smart traffic signal monitoring system using vehicles counts
Authors: Kumar Janahan Senthil , R.M. Veeramanickam M , Arun S , Narayanan Kumar , Anandan R , Javed Parvez Shaik 
Published: May 2018

Traffic signal management is one of the major problematic issues in the current situation. Such scenarios, every signal are getting 60 seconds of timing on the road at a regular interval, even when traffic on that particular road is dense. As per this proposed model in this article, which will be optimized the timing interval of the traffic signal purely depends on the number of vehicles on that particular roadside. The major advantage of this system is that it can able to decrease the more waiting time for the drivers to cross road signal. In this model, we are using the clustering algorithms model which is based on KNN algorithm. Using this algorithm new model will be liable to determine expected required timing as per provided inputs to the signal which is vehicles count. The input of these systems is vehicles counts on each side of the road from crossing signal. And this input will be determined on much time is to be provided. “Case studies on this system are traffic network and real-time traffic sub-networks are organized to get the effectiveness of the proposed model.”
Prediction of gestational diabetes diagnosis using SVM and J48 classifier model
Authors: Saradha S , Sujatha P 
Published: May 2018

Knowledge Discovery in Databases (KDD) process is also known as data mining. It is a most powerful tool for medical diagnosis. Due to hormonal changes, diabetes may occur during pregnancy is referred as Gestational diabetes mellitus (GDM). Pregnant Women with GDM are at highest risk of future diabetes, especially type-2 diabetes. This paper focuses on designing an automated system for diagnosing gestational diabetes using hybrid classifiers as well as predicting the highest risk factors of getting Type 2 diabetes after delivery. One of the common predictive data mining tasks is classification. It classifies the data and builds a model based on the test data values and attributes to produce the new classified data. For detecting GDM and also its risk factors, two classifier models namely modified SVM and modified J48 classifier models are proposed. The data set were collected from various hospitals and clinical labs and preprocessed with discretize filter using weka tool. Missing values are replaced by the suitable values. The final preprocessed data applied in the proposed classifier Model. The output of the proposed model is compared with all the other existing methodologies. Since the proposed model modified J48 classifier model produces more accuracy and low error rate against other existing classifier models.
A study on competence and enrichment of virtualization in cloud computing
Authors: V. Anbazhagu U , Maheshwaran P , S. Archana K , Gowr Sheela 
Published: May 2018

The aim of this research is to study and enhance the applications of most profitable technology in cloud computing ever "Virtualization". Back then, a 15 years before, nobody knows about the technology named cloud computing exists. But now, every technology such as personal computer, mobile phone, tablet PC, even televisions rely on cloud computing. Cloud computing helps greatly in reducing costs, scalability and flexibility in computer services. Virtualization is the technology that helps cloud computing to emerge in a large profitable level. Using virtualization (such as server, network and storage virtualization technologies), the resource cost is reduced in great level.
Fire fighting robot with vision camera and gas sensors
Authors: Boopalan S , Narendra Prasad G , Swaraj Paul C , Narayanan Kumar , Anandan R 
Published: May 2018

Yearly there are 150+ deaths are occurring due to fire fighting operations. Most of the deaths are due to presence of poisonous gases being present in the fire fighting areas. If we able to inform fire fighter worker about the presence of gases and hazardous situation, we can able to save their lives. In now-a-days robots play a vital part in industry and normal life of human beings , robots are the assemble of different parts or things which are made by human in order to complete any work with more accuracy. “Fire Fighting Robot with gas sensors”. The design is costless and will do lot of work. It can be used in industry and for domestic purpose. Important parts involved in the construction of robot are gas sensors, water tank, wireless remote and wireless android device Wi-Fi enabled Camera, A wireless robot will do effective work, thereby making it possible to control the robot from remote location. Keeping all above factors in mind the Robot is capable of being remotely controlled and live video buffering i.e. possessing a multimedia interface was convinced and developed.
An overview of various ad hoc routing protocols in MANET
Authors: Arumugam Saritha , Kumar N 
Published: May 2018

Mobile ad hoc network is a wireless network which has peer to peer process .it is established to achieve a group of network to be connected in wireless network. It is a large network that transfers the data from source to destination .Here we are computing the routing protocols like (DSDV, AODV, OLSR, DSR, TORA, and ZRP) which is analyzed in the form of packet delivery ratio, throughput, end to end delay, Routing overhead. There are three types of ADHOC network routing protocol 1) table driven proactive protocol acts as background traffic generally, in ADHOC network the location of one node is send to other node through location this nodes transfer the data from one to other its done by DSDV and WRP. 2) on demand driven reactive it establish route between nodes when they are required to route packet data it is done by DSR and AODV. 3) hybrid protocol each node has its own zone radius.