bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancement of an electric drill body using design for additive manufacturing
Authors: Srinivasan Naveen Raj , Chamala Vaishnavi J , Varun Darshan BL , Srajaysikhar D , Sakthivel G , Raghukiran N 
Published: July 2021

Abstract
Our research work involves the use of the use of digital manufacturing tools to develop a novel design alternative to an existing application. An everyday electric drill machine has been considered and had its functionality enhanced by redesigning its body in accordance with the solutions aimed at mitigating a few shortfalls, which primarily involves its safety aspects and ease of use, while also not compromising on its extant operating capacity as well as retaining the ability to be wielded by professionals well-versed in handling the original machine. To that end, we deconstructed the CAD (Computer-Aided Design) model of a conventional drill, and attached an auxiliary (precision) grip through generative design- a superior designing experience that is powered by Alternative Intelligence-by using Autodesk Fusion 360 software. Then, it was converted to an STL file (Standard Tessellation Language), which is a competent file format for subjecting the design to the various pre-processing steps required for creating a physical model of it using additive manufacturing. Firstly, file repair and manipulation tasks were carried out through Autodesk Meshmixer and Netfabb, with the latter also doubling up as the implement used for carrying out the printability analysis, orientation optimization, construction of support structures, and finally, slicing. The finished model was of the dimensions of 165.3820 mm x 204.4808 mm x 76.2340 mm, which indicates that the design alterations did not produce a vastly different version of machine than the original one. However, the output would be considerably efficient since the overall weight is reduced, and the presence of auxiliary handle would bestow more control on the operator. This also renders the body of the electric drill a monolith, which would enable a simpler assembly operation during the manufacturing stage. The material of choice was Orgasol polyamide- a natural polyamide 12 powder possessing the physical and chemical properties suitable for this application. The specific additive manufacturing process to be used was determined to be Selective Laser Sintering, and a printer capable of performing the same was identified as Formlabs Fuse 1. The aforementioned printability analyses were carried out in accordance with these considerations and the model was found to be well in order for the same.
Notifier of Mushroom Cultivation Room using EdSim51 Simulator
Authors: Goh Z M , Alhady S S N , Wahab A A A , Othman W A F W 
Published: July 2021

Abstract
This project aims to design a notifier of a cultivation room used to cultivate king oyster mushrooms (P. eryngii spp.) using an SHT75 temperature and humidity sensor. When the temperature or humidity of the cultivation room is beyond the mushrooms’ growing condition, the notifier will notify the cultivator by showing the texts to let the cultivator be conscious of the surrounding temperature and relative humidity. In this project, 8051 microcontrollers simulator (EdSim51) used to design the notifier. The component used to imitate the function is the SHT75 sensor, Liquid Crystal Display (LCD) module, Light Emitting Diode (LED) bank and Universal Asynchronous Transmitter (UART-Tx). Temperature and humidity parameter classed into low, normal, fruiting, high and over-limit condition. The system developed was successfully detected all the parameter. The notifier designed can solve the problems faced by most cultivators in cultivating mushrooms and helps to grow other plants in the future.
A Review on Unmanned Crop Detection Techniques
Authors: Miruthula S , Logeshwari NA , Manickaraj VN , Praveen M , Dhivyasri G 
Published: July 2021

AbstractThe programmed water system frameworks are received as of late to provide support to the agriculturists in turn reducing the manpower and improving cost effective techniques. In this paper, a detailed survey is done analysing the crop detection techniques which are in existence. This paper provides an insight study on pH level monitoring in the soil, water and soil nutrients management techniques, temperature and humidity measurement, surveillance of crop field and other smart irrigation techniques utilized for monitoring the farmland. This paper discusses about the effective methodology with enhanced technique that could be implemented in future to attain better performance and user-friendly for the farmers.
Automatic Load Frequency Control in an Isolated Micro-grid with Superconducting Magnetic Energy Storage Unit using Integral Controller
Authors: Rajaguru V , Annapoorani Iyswarya 
Published: July 2021

Abstract
Due to depletion of fossil fuels and increasing power demand, employing Renewable Energy Sources (RES) in the form of micro-grid has become very essential. However, the reliable operation and control relies on the intermittent nature of RES and maintaining the frequency within the acceptable limit is the challenging task in isolated micro-grid. This paper presents the Automatic Load Frequency Control (ALFC) in an isolated Micro-Grid (MG) with Superconducting Magnetic Energy Storage (SMES) unit using Integral controller, to enhance the stability of the system frequency. The simulation result shows that the dynamic performance of the proposed system is significantly improved while incorporating the SMES Unit. The simulations are carried out in MATLAB – Simulink.
Green House Management System using EdSim52
Authors: Pei Y L , Alhady S S N , Othman W A F W , Wahab A A A 
Published: July 2021

Abstract
Crop cultivation has been around for a long time and plays essential roles in many fields. Growing plants’ growth quickly affects climate conditions, especially temperature and relative humidity. Therefore, the simple Green House Management System designed using an SHT75 sensor to detect the temperature and relative humidity inside the greenhouse. The temperature and relative humidity calculated in the form of degree Celcius and percentage. The data then displayed on the LCD monitor. The water pump activated if the temperature and relative humidity are larger than 35°C or below 45%. If the relative humidity is above 45%, the ventilation fan is activated. The user can also use the PC keyboard connected to the activated water pump or ventilation fan. This report explains the design process while highlighting the problems faced by the farmer. Lastly, the conclusion of this project based on the objective and the results obtained. Besides, some suggestions discussed based on the design for the future development of the system.
Design of a low cost system for determination of fat using IOT and ML
Authors: Patil A A H , Jakatdar E G , Bhadreshwarmath S C , Kumbhar V R , Mitragotri P P , Deshmukh B B , Mistry R D 
Published: July 2021

Abstract
The husbandry is very important business of Indian farmer. Dairies collect milk from farmer everyday & payments for this milk are done according to the quantity and quality of milk. This rate depends on various quality parameters of the milk. Fat is one of most important component of milk. Due to its higher importance along other quality parameters of milk, it becomes mandatory for the determination of fat percentage especially for the milk vendors, small dairy owners etc. The classical method used to determine the fat percentage in milk is Gerber method. It’s a chemical test which is destructive in nature. Due to inclusions of various chemicals it becomes time consuming procedure for determination of fat in milk. Due to this, the number of samples that can be tested is very low in a given period of time. This paper presents the design and development of Milk Fat Analyser. The system is built by interfacing Light Dependent Resistor (LDR) with Raspberry pi Microprocessor. The parameter that is measured is fat percentage. The result obtained is displayed on screen which provides a good interface to the user. This project aims to provide a low cost, fairly accurate and reliable system to the farmers, small dairy shop owners and similar small factories where quality of milk matters while processing it to make other milk products and also for supplying milk consumed by people at large. Experimental results show that the method with Machine learning algorithm can detect fat with fair accuracy.
Pressure Cooker Whistle Notification Using Arduino Based Wireless Sensor Networks
Authors: Adarsh JK , Kishore R , Arul R 
Published: July 2021

Abstract
In this paper, a new safety method is proposed to reduce the pressure cooker risks, accidents due to the carelessness of the user. The main aim of the paper is to introduce a gadget that can be used to keep track of the whistle count and notify the user in real-time about the whistle count through their mobile phones. This way the user can keep track of the whistle count and can turn off the pressure cooker when their desired whistle count is reached. Sound sensors are used to detect the sound wave of the pressure cooker whistle. The whistle count is recorded using an Arduino and the notification is sent to the user’s mobile via the Blynk application. Blynk is being the open-source platform for a modular graphical user interface to control experimental tools based on Arduino, it extends Arduino’s capabilities allowing instrument makers to easily create a custom user interface program that runs on a connected computer. This device can be used in an indoor environment.
Stock Price Prediction using Fractional Gradient-Based Long Short Term Memory
Authors: Singh N , Sugandha  , Mathur T , Agarwal S , Tiwari K 
Published: July 2021

AbstractDeep Learning is considered one of the most effective strategies used by hedge funds to maximize profits. But Deep Neural Networks (DNN) lack theoretical analysis of memory exploitation. Some traditional time series methods such as Auto-Regressive Integrated Moving Average (ARIMA) and Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) work only when the entire series is pre-processed or when the whole data is available. Thus, it fails in a live trading system. So, there is a great need to develop techniques that give more accurate stock/index predictions. This study has exploited fractional-order derivatives’ memory property in the backpropagation of LSTM for stock predictions. As the history of previous stock prices plays a significant role in deciding the future price, fractional-order derivatives carry the past information along with itself. So, the use of Fractional-order derivatives with neural networks for this time series prediction is meaningful and helpful.
Deep Learning Algorithms for Tool Condition Monitoring in Milling: A Review
Authors: Patil S S , Pardeshi S S , Patange A D , Jegadeeshwaran R 
Published: July 2021

Abstract
The 4th Industrial Revolution (Industry 4.0) necessitates implementing the prognostics and health management (PHM) practices in manufacturing processes. The traditional machine learning approach has well assisted the PHM practices within the same data distributions. However, when a high noise environment, versatile operating conditions, and cross-domain machining is considered, it still lacks key steps of generalizing unknown tool faults. In an attempt to address PHM practices under such domains, a generic Deep Learning-based scheme is gaining significant attention. In this paper, an inclusive review is presented in order to provide an insight into the application of DL in tool condition monitoring (TCM), particularly in milling. Commonly used DL algorithms and their applications toward TCM are initially discussed and number of illustrative DL models applied for TCM is presented. Later, emergent DL themes & their computational techniques are summarized with an intention to provide framework for domain generalization. Finally, challenges in further exploration and futuristic trends in TCM are discussed.
Survey on Wireless Sensor Network, Its Applications and Issues
Authors: Sharma Shweta , Kaur Amandeep 
Published: July 2021

Abstract
WSN is a network comprising of various sensor nodes that are highly energy efficient used in various applications now a days. It helps in transmitting data from sensor nodes to the base stations in a highly reliable and secured manner. It plays a very important role in real world and integrates with many other technologies like Cloud Computing, Internet of Things (IoT). Different researchers continuously attempted to work on different constraints under Wireless Sensor Network which further becomes research motivation. In this paper, we highlighted various issues facing by different researchers while data transmission among sensor nodes. WSNs are used in various areas in all over the world, and significant progress has been made to expand the use of sensor nodes over the past two decades.
A Systematic Review on Extreme Programming
Authors: Shrivastava Anchit , Jaggi Isha , Katoch Nandita , Gupta Deepali , Gupta Sheifali 
Published: July 2021

Abstract
Since the advent of start-ups and old companies starting to shift to e-business, it has become troublesome to choose the right methods for projects that’s where extreme programming came to use. In this paper, we tried to compile different applications of the same. Extreme programming is a well-known agile method for software development. Extreme programming ensures customer satisfaction, better software quality and efficient project management. The team size is usually small but the group is team-oriented. It is a dynamic software development model, i.e., continuous discussion and integration of new features and ideas is the cornerstone of this model.
Prediction of tool wear in milling of Inconel 625 using and integrated kurtosis-based algorithm with vibration signals
Authors: Mohanraj T , Shanmugam A 
Published: July 2021

Abstract
Tool wear may depreciate the quality of the machined product owing to its poor surface roughness and dimensional inaccuracy. Tool condition monitoring system (TCMs) is necessary for the manufacturing industry to obtain better quality products with minimal time and improve productivity. Currently, TCMs uses different sensor signals and features to examine the tool wear. In this work, an Integrated kurtosis-based algorithm for Z-filter (I-Kaz) 2D and 3D analysis is employed to examine the vibration signals in milling of Inconel 625 for monitoring the tool condition during the milling process. The results from vibration signals revealed that the I-Kaz coefficient correlates with flank wear. I-Kaz coefficient was increased for raise in flank wear. When the I-Kaz 2D coefficient value increased above 0.5, it indicates that the tool was worn out and has to be replaced.
Friction Stir Welding Tool Condition Prediction Using Vibrational Analysis Through Machine Learning – A Review
Authors: Balachandar K , Jegadeeshwaran R , Lakshmipathi J , Saravanakumar D 
Published: July 2021

AbstractFriction stir welding (FSW) is a relatively new solid-state joining process. This joining technique is energy efficient, environment friendly, and versatile. In particular, it can be used to join high-strength aerospace aluminum alloys and other metallic alloys that are hard to weld by conventional fusion welding. FSW is considered to be the most significant development in metal joining in a decade. Recently, friction stir processing (FSP) was developed for micro structural modification of metallic materials. In this review article, the current state of understanding and development of the FSW and FSP tool process parameters are addressed. To identify the tool parameters, it is necessary to monitor the tool condition. Diagnosis the recognition of the nature and cause of a certain phenomenon. It is generally used to determine cause and effect of a problem. Machine fault diagnosis, a field of finding faults arising in machines. To identify the most probable faults leading to failure, many methods are used for data collection, including vibration monitoring, Thermal imaging, Oil particle analysis etc. Then these data’s are processed using methods like spectral analysis, wavelet analysis, wavelet transform, Short term fourier transform, high resolution spectral analysis, waveform analysis etc. The results of this analysis are used in a root cause failure analysis in order to determine the original cause of the fault. This paper presents a brief review about one such application known as machine learning for the friction stir welding tool monitoring.
Design of IoT based Platform Development for Smart Home Appliances Control
Authors: Kolanur C B , Banakar R M , Rajneesh G 
Published: July 2021

Abstract
The advent of industrial automation has brought about a substantial change in the human lifestyle and the way human interaction with machines. One of the major technological interventions in day-to-day life is the role of automation, which has uplifted the living standards in developed countries and fostered humans’ dependency for accomplishing recurring tasks. The latest and most adopted technology for remotely monitoring and controlling any machine or device is the Internet of Things-which has become one of the industry standards for automation. Multiple edge computation capable embedded devices and machines are connected to the internet as independent nodes, which can be monitored and controlled remotely with the use of IoT. Adapting this cutting-edge technology for household appliances to monitor and control them is often seen nowadays. This is fast and reliable but arrives with its own snags such as availability of internet at place where user and also the device/appliance is located, use of single control strategy which hampers and restricts the user always to carry the remote or to stay in the vicinity of the device to be controlled in case of wifi or Bluetooth controlled automation. The proposed research focuses on the adoption of multiple strategies to control each device/appliance to empower the end-user without being restricted to depend on a single strategy remote controlling system. The core part of the proposed research revolves around the Message Queuing Telemetry Transport (MQTT) protocol but can be activated with multiple routes such as touch-based sensing panels, cellphone-based controlling, web-enabled controlling or even gesture-based controlling of the appliances resulting in an ameliorative user experience and interactions with machines.
Organic LED Farming for Self Sustainability During Post COVID-19
Authors: Koushik P , Karthikeyan P , Keerthi M , Manikandan M 
Published: July 2021

AbstractAn organic LED (Light emitting diode) farming using artificial intelligence is the way to increase crop production effectively with LED lights. Users can able to select specific range of wavelength to induce targeted photomorphogenic, bio chemical, or physiological plant responses. LED can prevent physiological disorder that are commonly existing in indoor environments, and helps in reducing if pest and diseases pressure in growing plants.
Design and Development of a Farmer Friendly All-Terrain Guided Vehicle
Authors: Keesara Surakshith Reddy , Gurusamy Murali Mohan 
Published: July 2021

Abstract
Farming is a labour intensive occupation and there is heavy shortage of agricultural labours due to rapid urbanization. In India agriculture contributes about 15% of the gross domestic product and there is need for mechanizing the agricultural activities to meet the raising demand for food and labour shortage. In this regard, a guided all-terrain vehicle will be designed and developed in this study to help the farm labour in his regular agricultural activities. The all-terrain vehicle has capability to traverse through rough terrains and it will be IoT(Internet of Things) enabled so that it can communicate with the various subsystems in the cloud and can be also monitored and controlled remotely. The vehicle will be guided and controlled by human through a proper interface. It will be designed with farming specific accessories hence it would reduce human efforts during his farming activities. Thus the proposed vehicle will act as farmer’s friend in assisting him to perform his tasks and thereby increasing his productivity.
Tuning of PID Controller with Differential Evolution Algorithm for LCC Resonant Converter
Authors: Bhuvaneswari C. , Abitha Memala W. , Barnabas Paul Glady J. 
Published: July 2021

Abstract
This paper deals with the optimization of LCC Resonant Converter based on Differential Evolution Algorithm. Closed Loop Analysis of LCC Resonant Converter have been Simulated by tuning PID Controller for different values of Kp, Ki and Kd values. Optimum Values of Kp, Ki and Kd were obtained using Differential Evolution Algorithm and these values were fitted to Obtain Maximum Output Voltage with LCC Resonant Converter. Initially three Variables namely Series Inductance, Series Capacitance and Parallel Capacitance were considered, out of which the Value of Series Capacitance was tuned with Differential Evolution.
In-depth scrutinization of In- Mold Electronics for Automotive applications
Authors: Srinivasan KP , Muthuramalingam T 
Published: July 2021

Abstract
Conductive inks have been extensively researched owing to their popularity in Printed Electronics and Flexible Electronics. IME is one of the most important technological developments of this century. In an effort to summarize the latest advancements created by Injection Molding, Thermoforming and Printed Electronics in the field of In-Mold Electronics, this consolidated report describes the key technologies and challenges in meeting the requirement of Automotive Cockpit Electronics and its specifications, as well as an overview of Touch Capacitive sensors development with a range of conductive inks and techniques.
Smart Frontal Safety System for Automobiles
Authors: Govardhan Y.S. , Sai Doodi Maheedar , Sakthivel G , Raghukiran N , Saravanakumar D 
Published: July 2021

Abstract
The focus of this work is to develop a new safety system in addition to reduce accidents for innocents in automobiles. When confronted with an accident, the only safety measure which we bet our lives on is “airbags”. In several cases, airbags alone may not be able to completely protect the passengers in the vehicle due to the high magnitude of the impact. In the present work, a new safety upgrade will be modeled in vehicles to absorb the sudden frontal impacts while in motion. The ultrasonic sensors are placed in the front portion of the vehicle which is set to propagate and receive ultrasonic waves while moving. The change of distance from the sensor to the obstacle is monitored continuously and in the event of an emergency, the frontal safety system in the vehicle gets activated. In such an event, the bumper or a metallic formed plate is actuated forward to a certain distance and upon striking the obstacle, the impact force is then reduced by shock absorbers or springs provided in the safety system. Hence, the impact transmitted to the passengers inside the vehicle is less when compared to the direct impact.