bluuebunny/crossref_metadata_2025_split huggingface dataset:
Strength characteristics of banana and sisal fiber reinforced composites
Authors: Vidya Bharathi S , Vinodhkumar S , Saravanan M.M 
Published: February 2021

Abstract
The steadily growing demand for various materials of buildings, the availability of natural sources was decreasing. It is necessary to use alternative materials for the construction of buildings. Fibers are of two types. They’re natural and artificial fibers where natural fibers are abundant and cheap in manufacturing, eco-friendly and renewable. Natural fibers have less density, low cost and fewer durability when compare to artificial fibers. The composite materials were reinforced by using natural fibers. By adding these natural fibers the properties of concrete in mechanical behavior were improved. Here banana and sisal natural fibers have been employed as reinforcement in composite materials. The abundant source of banana fiber is peduncle and pseudo-stem and sisal fiber is a leaf fiber that is very strong. There were many research works with the adoption of these fibers are in numerous percentages like 0%, 0.5%, 1%, 1.5% and 2% in concrete(M25 grade) and was casted by using Ordinary Portland Cement(53grade). This paper overviews the particulars and results of preceding years research papers and also compares the strength properties of banana fibers and sisal fibers viz tensile, flexural strength (modulus of rupture) and compression strength (cube strength).
Treatment of contaminated wastewater from Textile industry: A review
Authors: Naveenraj V. , Prabakaran  , Kulanthaivel P. 
Published: February 2021

Abstract
This review sums up the ongoing dye removal advancements from wastewater like biological, physical and chemical methods. Colour containing wastewater ought to be treated with adequately so as to prevent unfavourable impacts on the climate and water assets. Wastewaters from the textile industry are dangerous effluents containing poisonous complex segments that without suitable treatment seriously sway the climate; making unsafe impacts the amphibian environments, just as to human wellbeing. Thus, it is the point of this exploration to expand the extent of expected arrangements, proposing practical high-performing consolidated techniques with promising advantages for future modern applications. A couple of chemical and physical procedures were utilized for the wastewater treatment containing dyes, at any rate execution of these frameworks have the mindful constrains of being costly, not prepared to the whole finish of shadings from wastewater, and making basic measures of filth that can be reason to associate pollution issues.
Study and Simulation of Autonomous Quadrotor Tracking a Pre-Defined Trajectory Using Matlab
Authors: Chinnasamy Jegadheesan , Periasamy Somasundaram , Singh Ajit Pal , Mohanesh S , Manikandan R , Gokul L , Deepak S 
Published: February 2021

Abstract
The automated airborne vehicle (UAV) is an airplane that is worked without a human pilot. It was controlled either by the controller of a pilot or self-governingly by locally available PCs on the ground or in another vehicle. Modern Quadrotors are evolving than the old designs into a small agile vehicle. The quadrotor is increasingly becoming more and more popular, there is an increasing need for making this vehicle autonomous. The Methods for developing autonomous unmanned aerial vehicles has been an active area of research under the mobile platform. There are many commercially available drone platforms but all of them are required user interaction through a controller. In this work, we have created a control algorithm and trajectory generation for a smooth minimum snap trajectory through the given waypoints. Each waypoint specifies the desired position velocity, yaw, pitch, and roll angles. Such waypoints generated by our algorithm generate a smooth minimum snap trajectory between these waypoints. A PID controller is used to control the motions of the quadrotor in all planes.
Performance Analysis of Wi-Fi and LoRa Technology and its Implementation in Farm Monitoring System
Authors: Muthukrishnan H , Jeevanantham A , Sunita B , Najeerabanu S , Yasuvanth V 
Published: February 2021

Abstract
One of the most interesting technology named Internet of Things made the world to move in smarter way. IoT is an idea of associating devices to internet which works automatically without human presence. Along with IoT different wireless technologies greatly supports in communication. Wide range communication and short range communication are made possible using IoT. These communications through IoT is done via technologies like Wi-Fi, Bluetooth, ZigBee, LoRa, NB-IoT, etc. In agriculture sector, these technologies helps in monitoring environmental factors in smarter way which yields more efficient crops but it works for only certain range. Some of the long range communicating technologies are NB-IoT, LoRa. Low Power wide area network will provide long range communication at low power consumption. LoRa is used to monitor the environmental factors in two different areas. Data from different areas is collected using LoRa device. Here, the comparisons in features of Wi-Fiand LoRa is graphically presented. Features like power, time, data rate for both Wi-Fi and LoRa has been analysed in this project. The data collected here is environmental factors such as moisture, temperature, humidity, motion and light. This project describes the features of Wi-Fi vs LoRa in agriculture for communication.
Development of peanut separator and thruster
Authors: Srinivasan M , Nithya Sai S , Alexander Albert , Prabhakaran N , Gokul C , Visalaxi G 
Published: February 2021

Abstract
Peanuts have been in existence since the beginning of human life. It has a high carbon content and is rich in oil and protein. Peanut oil extraction is more common in most developing countries. Peanut is a commonly used, edible commodity, and oil is used as a cooking medium. Upon oil extraction, the by-product of the peanut cake often contains 43-65 per cent protein and 6-20 per cent fat, which is usually used as feed for cows and goats. There is currently a shortage of farm workers and an increase in harvesting costs. The factors mentioned above mean that farmers are not interested in growing peanuts. The removal of peanut shells is a time-consuming and costly operation. During harvesting, the temperature is very high, making it impossible for humans to work. Peanut thresher is used to solve these problems by removing peanuts that minimize time and expense. Our project focuses mainly on the design and development of a peanut cutting machine with a 0.5 hp motor. The workers removed the peanut capsules from the harvest at the beginning. The output of this method was very poor and did not meet consumer demand because it was a time-consuming operation. The main part of our project is a rotating drum with nails. They feed the peanuts to the rotating drum. Rotating drum tips isolate the pods from field harvest. There are large peanut harvesters on the market, but small farmers cannot afford these harvesters. Our machine is small, light and inexpensive. Farmers with a small farm may afford to use our machine.
A novel method for sample preparation of SMA spring for micro-structural studies
Authors: Santhanam R , Krishna Y , Sivakumar M S 
Published: February 2021

Abstract
NiTi alloys are most widely used shape memory alloys (SMA). SMA in spring form is best suited for actuators as they can generate considerable forces and large displacements. Often it is necessary to know the micro structure of SMA to conclude their state as fully austenite or fully martensite at near room temperature. Sample preparation of wire for micro structural study is easier when compared to spring. This paper reveals a novel method of sample preparation for micro structural study using optical and scanning electron microscopes, of commercially available SMA spring in as received condition for which a prior history is unknown.
Marketing decision making using sentiment score with co-extracting opinion target words from reviews
Authors: Saravanan T M , Kavitha T , Hemalatha S , Kumar Gourav 
Published: February 2021

Abstract
This paper proposes a broad-spectrum outline that utilizes natural language processing approaches counting sentiment analysis, web mining that uses clustering schemes to acquire fresh outcome elicited from reviews in support of diverse features of products. An ultimate part in the scheme is finding positive and negative sentiment scope for all features of a product in the given reviews. Massive figures of product reviews are crawling on the Web with the rapid development of Internet. Commencing these reviews, customers can get hold ofactualexamination of product rank and unswerving supervision of their acquisition actions. Withdrawal feelings from web reviews have developed into a gradually more fiery activity and haveengrossed a vastpact of considerationcommencingthe researchers. The key task for opinion mining is obtaining opinion emotions from reviews in online, the novelfactor involves in identifying relations between words. The project proposes a new scheme that contains graph based co-ranking scheme that is employed in finding poise of every word. Then, words with superiorpoise are withdrawn as opinion objects. Based on the nearest neighbor rule we compare with previous schemes, the scheme more preciselycaptures opinion relations, particularly for elongated cover relations. The investigationaloutcome shows that the schemesuccessfully outperforms all other methods and techniques.
Multi stratagem analysis of sentiments on twitter data using partial phrase harmonizing
Authors: Saravanan T M , Kavitha T , Hemalatha S , Kumar Ankit 
Published: February 2021

Abstract
Sentiment analysis is constructive in the application environment for business intelligence and suggests systems because it is a very easy medium for the two ends of the availability to communicate. Numerous strategies and schemes have been worn inside the sentiment analysis, such as language processing, polarity lexicons, machine learning, and psychometric scales which establish diverse types of analyzing sentiments as assumptions ended, scheme reveals, and corroboration data set. Since the internet has to turn into a commanding resource of retrospect the sphere of sentiment is moreover referred to as Sentiment Analysis or Opinion Mining. It has seen an enormous boost in academia over the decades. Analyzing sentiment to extract sentiments in different levels like word, sentence, and document provides articles’ feeling polarities. While well identified consumers’ sentiments articulated in sentences by opinion. Customary machine learning schemes cannot virtuously mirror the views of writers. This paper proposes a scheme called multi-strategy sentiments with semantic resemblance to disentangle the topic with partial phrase matching. Additionally, the Naïve Bayes classification is applied to search for the probability of the distribution of knowledge in different categories of knowledge set.
Smart bins for garbage monitoring in smart cities using IoT system
Authors: Ravi V R , Hema M , SreePrashanthini S , Sruthi V 
Published: February 2021

Abstract
It is predicted that by 2025 more than 75 billion IoT devices will be linked with internet. Due to technological development and increase in population, industrializationand urbanization, the entire countries should need to formulate ecological development schemes. In connection with this, many countries are endowing large amount of money towards building smart cities. In the proposed work an IoT integrated smart bin for Smarter Waste Disposal Systemis devised. The proposed system will consist of waste bin that are equipped with ultrasonic sensor to detect garbage fullness, Load sensor to measure weight of the garbage, GPS sensor to locate bin location and Gas sensor to measure hazardous gas emission from bin. These sensors are interfaced with ESP 8266 NodeMCU module which a microcontroller is having cost effective Wi-Fi microchip with complete TCP or IP stack. The ESP 8266 can communicate with Wi-Fi modems present in the smart city which are in turn connected with cloud using internet. The proposed system can send alert message to municipal authorities whenever the height of garbage in the bin is greater than threshold value and also stores the data in cloud for future action.
Design And Fabrication Of Semi-Automated Facsimile Stamping Machine
Authors: Praveen Kumar S , Hehma Gayatri R , Nathiya S , Hemachander R 
Published: February 2021

Abstract
The main objective of this paper is to reduce the timing of higher officials to sign in large number of same documents. Manual signing of documents adds time shortage in Public Work Department. Moreover, the manual process is time consuming and not suitable for signing a greater number of documents. The proposed model involves the arrangement of documents, positioning of facsimile, stamping the facsimile and take out the printed documents to distribute station. Thus, this model signs a greater number of documents within a short time. Pneumatic power is fruitfully utilized in this paper and the system is controlled by an Arduino controller. Positioning of facsimile is done by the lead screw arrangement with the help of sensors. The finished documents are then sucked by vacuum cup and taken out simultaneously. Our real time implementation helps them in unveiling such condition. The paper consists of two sections namely mechanical section and control section. The control section consists of Arduino controller and Relays. Arduino controller is used to control the DC motor and the relays are used to actuate the mechanical sections. The mechanical section consists of lead screw arrangement, pneumatic piston, suction cup and facsimile.
A Machine learning approach to monitor Brain Health and epilepsy detection
Authors: Manimegalai M , Nirmala Devi P , Mekala V , Haripriya S , Jawahar B , Mageshkumar M 
Published: February 2021

Abstract
Brain health is a major concern worldwide and in India. There are a ton of neurological issues that may influence the mind and one such issue is epilepsy. Epilepsy is one of the preeminent generally happening neurological issues. Electroencephalography (EEG) signals help in the examination and conclusion of epilepsy by recording the exercises inside the cortical districts of the epileptic patient. Conventional techniques for breaking down an EEG signal for epileptic seizure discovery are tedious. A proposed work of robotized seizure recognition systems utilizing an AI strategy is proposed to supplant these conventional techniques. The proposed work is completed with a real-time dataset of epileptic patients taken at a different period. The two basic steps involved during this project are pre-processing and classification. Information pre-preparing is an information mining procedure that includes changing crude information into a reasonable arrangement. Classification is the process of predicting the class of a given dataset. The classifiers used are SVM, Naive Bayes, Random Forest classifier. The random forest is most preferred for its decision trees where the model has low variance and also for its high predictive performance. The proposed system helps in daily monitoring the brain health of epileptic patients using a mobile application. This system mainly focuses on rehabilitated patients. Once when the patients use a wireless wearable headband the signal is monitored and their health condition is detected using a mobile application.
Min-Time TS: task resource mapping algorithm in cloud computing
Authors: Kamalam G K , Kalaiyarasi T , Monaa S V , Gurudharshini B 
Published: February 2021

Abstract
Internet-established cloud environment provides enormous amount of ubiquitous, distributed resources such as processors, memory, and software. In recent years, task scheduling and resource allocation has become a significant issue in cloud computing. Task scheduling plays a crucial role in cloud system performance. For achieving elegant performance, arises a need of efficient scheduling technique. Numerous algorithms developed for scheduling. In this paper, we have proposed an efficient approach which schedules the tasks to the available cloud resources by forming a task pair. Min-Time TS algorithm forms a finite number of task sets; each set consists a pair of tasks one from Group G1 and another from Group G2 and are scheduled with minimum layover time.
Effective Pre-Migration Mechanism for Dynamic Load Balancing In Cloud Computing Environment
Authors: Nanthiya D. , Keerthika P. , Gopal S.B. , Gokul V. 
Published: February 2021

Abstract
The effect of cloud computing has a huge preferences over all areas. The virtualization strategies made it conceivable to scale in all zones. This prompts the budgetary and prudent development in all nations. The clients frequently demand the cloud datacenters and workers for their cycle. It makes weighty traffic in both cloud worker and server farm. This weighty traffic prompts load imbalancing and furthermore the unpredicted disappointments may prompt execution debasement. Certain precautionary measures must be taken care of to distinguish the virtual machine disappointment. Anticipating the virtual machine disappointment is troublesome along these lines; our proposed work amasses in appropriate booking of the cloudlets thinking about the heap in the virtual machine. On the off chance that any chance of burden imbalancing happens when after the cloudlet is booked at that point utilizing pre movement calculation, the cloudlets are moved to another virtual machine. This paper joins the heap adjusting system with pre movement calculation for planning the cloudlet. The proposed work is actualized in the cloudsim in addition to apparatus.
Brain tumor detection from MRI images using deep learning techniques
Authors: Gokila Brindha P , Kavinraj M , Manivasakam P , Prasanth P 
Published: February 2021

Abstract
Brain tumor is the growth of abnormal cells in brain some of which may leads to cancer. The usual method to detect brain tumor is Magnetic Resonance Imaging(MRI) scans. From the MRI images information about the abnormal tissue growth in the brain is identified. In various research papers, the detection of brain tumor is done by applying Machine Learning and Deep Learning algorithms. When these algorithms are applied on the MRI images the prediction of brain tumor is done very fast and a higher accuracy helps in providing the treatment to the patients. These prediction also helps the radiologist in making quick decisions. In the proposed work, a self defined Artificial Neural Network (ANN) and Convolution Neural Network (CNN) is applied in detecting the presence of brain tumor and their performance is analyzed.
Optimization of ductility and yield strength on Al2024/B4C composite material using Taguchi Technique
Authors: Bharath L , Sreenivasa Reddy M , Girisha H N , Balakumar G 
Published: February 2021

Abstract
In the present investigation, Al2024 alloy reinforced with boron carbide particulates with three different mesh size (100, 200 and 300) have been chosen for the preparation of MMCs. Stir casting route was adopted by varying weight percentage of boron carbide particulates by 1 wt.%, 3 wt.% and 5 wt.%. The cast component was machined through conventional lathe machine tool as per ASTM E8-16a size for tensile test specimen. The tensile test specimens have been subjected to solutionzing treatment at 520 for24 hours followed by water quenching. The quenched test specimens are then subjected to artificial ageing at 175 for holding duration of 1 hr., 3 hrs. and 5 hrs. The tensile specimens after artificial ageing were tested using UTM to evaluate the ductility and yield strength of the formed composite material. It is noticed that ductility found to be decreased with increase in wt.% of boron carbide in the Al2024 alloy, whereas yield strength was found to be improved. Taguchi Technique was adopted to evaluate the S/N ratio, optimization, influence of process parameter and regression equation were derived for the confirmation of experimental results through Minitab software. SEM images reveal the uniform distribution of boron carbide in Al2024 alloy. Ductile tearing was observed in pure Al2024 alloy and the formed composite material.
RETRACTED: Wireless Sensor Network to Connect Isolated Nodes using Fuzzy Based Link Assessment Technique
Authors: Ganesh Babu R , Elavarasi P , Nivedaa GA , Rani Krishna M , Manikandan G 
Published: February 2021

Abstract
A simultaneous geography control effort is implemented for full-reachability systems and a genetic algorithm with dynamic transformation to find the break-through in a blaze-scene. Theproposed scheme efficiently takes care of the issue of separate node for transmission run. The suggested technique makes it possible to improve the display of the genetic algorithm in order to maintain a strategic distance from the possible arrangements which fall into nearby ideal. Different experimental simulations have to be confirmed the performance quality, reliability and timeliness of designed approaches. In the Wireless Sensor established network, can connect at least two sensors in a network sensors and deliver jointly via the obtained transmission extend to form the network of total accessibility. Accordingly, excellent blaze exhaust system with complete network accessibility the proposed approaches in this paper established topology and real-time routing methods. This device supports the protection and security of individuals in a blaze scene.
Reactive Power Control of Single Phase Grid Connected Photovoltaic System
Authors: Iniya V , Maniraj P , Anushiya S , Sarathapriya M , Sowmiya S , Suresh M , Srinivasan M 
Published: February 2021

Abstract
This paper illustrates the compensation of reactive power delivered to the grid connected inverter of photovoltaic system. By reason of weather condition sun irradiance will change, it does not deliver constant power to the grid it seems to voltage drop, poor power factor and so on. Usage of line frequency transformer can be removed while integrating the renewable energy sources to the grid without affecting the system characteristics. Here, LUO converter is designed and implemented along with the single phase inverter to integrate the solar PV to the grid without transformer usage. Fuzzy logic controller is developed to retrieve larger power from the photovoltaic system and also PI controller is used to regulate active and reactive power transfer to grid. MATLAB Simulation result shows the controlled reactive power of the grid connected photovoltaic system.
Measurement and Analysis of Power Quality Issues Due to Electric Vehicle Charger
Authors: Sabarimuthu M. , Senthilnathan N. , Monnisha A.M. , KamaleshKumar V. , Krithika Sree S. , Mala Sundari P. 
Published: February 2021

AbstractThis paper analyzes the aspects of power quality issues such as harmonics distortion and their effects in charging the electric vehicle. The harmonics produced is measured by using fluke power quality meter. The on-board and off board chargers are also discussed with their circuit diagram. It includes the fluke meter for measuring the harmonic distortion that occurs in the charger of the electric vehicle. The harmonics produced in the charger is measured and analyzed using simulink model also. The harmonic disturbances generated are also noted. The recommendations and suggestion based on the result analysis are also discussed