bluuebunny/crossref_metadata_2025 huggingface dataset:
An Enhanced Approach for Decision Support System Using Fuzzy Soft Set
Authors: Jayagowri P , Arockiaraj S , Karthik R
Published: July 2021

The support group issue of choice has been vague in recent years and has played a major role. There was an additional method for the approval of articles from infinite multi-spectator results. This approach includes the preparation of a parametric comparison table for a decision support device for a floating soft array. Real issues change in the fields of engineering, municipal and medical science, economics, and how they can be resolved depending on the sophistication and inexactness of the concepts of mathematics. In recent years, a new form of inference was designed to deal with those systems effectively. All these include fuse theory, probability theory, contradictory sets, intuitive fuse sets, rough sets theory, statistical interval theory, etc. that can be used to solve different forms of system-integrated complexity and inaccuracy. Both of these proposals are linked to an inherent disadvantage, though, which is that the parameterization process of both hypotheses is inadequate.
CNN and Computational Configuration Mathematical Chromosomal Defect Analysis in Medical Images
Authors: SureshAnand M , Reddy Gangireddy Prabhakar , Jaanaa Rubavathy S , Kalaiselvi Geetha M
Published: July 2021

Chromosomal defect analysis plays an important role in current medical care and diagnosis as one of the principal methods in cytogenetics via the processing of a medical picture. There are two main elements of human karyotype analysis: first, chromosomes are separated by digital images of the chromosome metaphase under the microscope. Chromatids are then closely analyzed, compared, organized and categorized. The segmentation and classification operation is tedious, where conventional geometric or mathematical approaches have only limited impact due to low precision, according to this technique. In most cases however, the workflow is still highly supervised and errors are still required by humans. This paper provides an optimised workflow to isolate and automatically identify chromosomes by a combination of many CNN and mathematical optimizations called mCNN GO. Mask R-CNN is investigated to separate the chromosome from chromosome metaphase images and train mCNN GO to identify the sub-images. We apply a new functional approach to synthesize images on the labelled data in order to enhance the efficiency of the segmentation network. Moreover, to ensure accuracy of the results, we create computational algorithms to straighten the genomes before registration. Experimental findings indicate that our methods for automated karyotype analysis are greatly superior to state-of-the-art.
An Educated Peer Discovery Expanding Blockchain Framework
Authors: Singuluri Prem Kumar , Basha Shaik Lal John , Ahamed Shaik Khaleel , Nithya M
Published: July 2021

The key benefit of blockchain Bitcoin-style networks is their immutability and autonomous power. Bitcoin is suffering from scalability problems in spite of its performance. Unless it is rendered more scalable, the promise of blockchain technology cannot be achieved completely. We broaden an earlier study on a fundamental balance between the blockchain system’s efficiency and forking rate. We also suggest a system to improve blockchain device efficiency by reducing block spread time. Informed neighbor selection is adopted by the proposed system. Miners detach from neighbors with restricted bandwidth and choose higher bandwidth nodes. To test the efficiency of the proposed system, we construct a Blockchain Interactions Emulator. In standard operations proposed system increases the performance by 20% by ∼40%.
The methodology for communication problem in telecom sector using fuzzy sub-monoid and group theory
Authors: Jayagowri P , Karpagavalli K , Karthik R
Published: July 2021

In order to address the ‘channel’ problem for telecommunications operators, this study is a pioneer in the application of Fuzzy Sub monoid and Group Theory to the communication channel system. The channel entity community model was developed for the transmission of information in the channel system to analyses the operation of channel entities. The channel system network traffic equations were developed in accordance with the theory of stream conservation and the channel network matrix. The matrix dimensionality was reduced on the basis of the channel entity Fuzzy Sub monoid and group model. A solution to the flow-state transfer relationship of the channel system is obtained, which will be very useful for telecommunications operators to create a high-level mobile e-commerce application model and architecture.
Detection of Motorcycle Theft Using Force Sensing Resistor and Ultrasonic Sensor
Authors: Balamurugan S , Govind K , Kamalesh M , Jeevaharan M J , Natarajan V
Published: July 2021

This essay provides a technique for continued motorcycle surveillance to avoid theft of the bike at the moment. If someone attempts to steal the vehicle, the buzzer will alarm the surrounding and with the use of FSR and ultrasonic sensor theft is detected and the system will send a message/phone call and the car owner will be given the current location of the vehicle. GPS stands as a back-up so that we can have a complete track of the vehicle during the theft.
Wind Energy Generation Based for Grid Connected System Using Zeta Converter and Terminal Sliding Mode Control
Authors: Pradip C , Saju N , Tresa Sangeetha S V , Raj Murugananth Gopal
Published: July 2021

In this paper, the wind energy system (WES) is interfaced with the grid system using a permanent magnet synchronous generator (PMSG) with robust control of terminal sliding mode controller (SMC) is proposed. In this system, voltage source inverter (VSI) with three phases has connected in grid side using less resistive losses of LCL filter but without using grid connection transformer. The ZETA converter is utilized to develop the voltage of DC link wind system connected rectifier. The high voltage gain is achieved by using the PWM switching signals for the converter. The grid side VSI is used to provide the reliable, efficient and supplying secure with the power, and it is controlled using the control strategy of terminal sliding mode controller (TSM). The proposed system results are verified, and the TSM control’s achievement is based on VSI, which is connected in the grid side validated using MATLAB/Simulink.
Grid Interfaced Windfarm Using Dynamic Voltage Restorer for Power Compensation with Pv Fed Sepic Converter
Authors: Senthil Nayagam V , Pattanaik Balachandra , Sekar K , Manikandan S
Published: July 2021

In this paper, the wind energy generation farm is connected with the grid system. The dynamic voltage restorer (DVR) is installed to control the grid side’s under and overvoltage. The photovoltaic (PV) system is installed in the DVR system, and the voltage of the grid over and under voltages is also addressed to achieve the proposed system’s high efficiency. The grid voltage compensation is harvested from PV and injected through the DVR. The boost converter is used in the existing systems to improve the available power from PV. In this system, the SEPIC converter is used to achieve high voltage gain from the PV plant to improve DC link capacitor voltage which is the inverter input source. The DVR based wind energy farm using PV with SEPIC system results are achieved in MATLAB/Simulink.
A Design Space Exploration of VLSI Extreme Machine Learning
Authors: Gopi B , Arulkumaran G , Parameshwaran R , Khan Vijitha
Published: July 2021

Radiation acceptance in FPGAs is an increasing priority, especially for dependable data processing in electronic equipment used during engineering and geostationary operations. A loss in FPGA board’s durability based on a single impact made by radioactive contaminants is the impetus behind the whole study. Inefficiency is a widely used method to increase the potential of radioactivity systems for data integrity. In excess usage of the zone, delay, and transmission range, durability brings with an overload. Also, with replication induction methods or even the quantity of backup stages, the defective system designs differ in configuration and resources use. The electromagnetic background varies based on the atmosphere and space climatic conditions and during the project’s operational time cycle. About the particular radiation level can also minimize the overhead costs attributable to maintenance at a run. In this article, we design a Dynamic Reliability Management scheme that uses, perceives, determines any appropriate durability degree, and implements operated reorganization using the radiation details, thereby varying the system reliability of the target computing modules. DRM specially developed flow produces a catalogue of similar compatible circuit applications with different output factor amplitudes. Spin software flow picks a necessary redundancy level using the radioactivity data and reconstructs the computational module with the relevant compatible module. The consequences of defects, errors and deficiencies caused by planetary protons emanating from solar radiation on ambient electronic structures in many sectors will begin with a simple but detailed analysis. Prevention steps against particle adverse effects, looking at different levels of both the architecture system from material to the device level, are applied. Challenges are also addressed to maintain effectiveness in the future advancement of technology. For random - access records, switch, GPU and operating networks, such problems in control measures are raised.
Design of Low Power and Failure Free SRAM Cell Using Read Assist Circuits
Authors: Ramamohan Reddy K , Aruna Priya P
Published: July 2021

Static Random Access Memory (SRAM) is one of the main peripherals in all the Very-large-scale Integrated (VLSI) chips, which enact a vital part in all executable applications. The write ability and read stability are prime factors with low power supply and improve operation speed with temperature, process, and voltage variations. In VLSI design, the System on Chip (SoC) performance is improved by applying low power supply and change in few Pico seconds of cycle times or memory access. The read/write operation is not accurate in lower supply voltage because it will not flip to the desired voltage levels. For improving performance, proposed an SRAM cell to flip to the desired voltage levels to reduce readability failures in low supply voltages. The additional requirement is needed to increase the chip’s performance with lower supply voltages, and continuously additional circuit techniques are needed for obtaining the SRAM memory’s readability and writing ability. In this paper, different performance improvement methods of SRAM memory cells are analyzed. The reduced word line voltage read assist circuit is designed for the SRAM memory cell.
Performance analysis of Cooperative underlay CRN in NOMA aided Energy harvesting for multiple secondary users
Authors: Kalaimagal G , Vasanti M S
Published: July 2021

This paper proposes a relaying scheme in an underlay cognitive radio network(CRN), where a source node desires to transmit the information simultaneously to more than two desired destinations. The power required for the relay operation is based on applying energy harvesting from the base station (BS). The proposed paper also includes Non-orthogonal multiple access (NOMA) with fixed power allocation to the different users to perform the decoding process irrespective of the channel condition. We have proposed a mathematical expression for the analysis of outage probability for the different users. In this respect, the linear model is discussed for perfect successive interference cancellation (SIC) at the receiver. Using the fixed power allocation process, we have simulated different output parameters such as Bit Error Rate (BER), NOMA capability, and the outage probability.
Analysis of Ultrasound Transducer Probe and Alternate Material for Its Foot Print
Authors: Joseph Raj P L , Kalimuthu K
Published: July 2021

A 128-element color ultrasound transducer probe (Sonoray – DS50PLUS-C352UB) compatible with any machine is analyzed. Various coating methods were discussed; the footprint is coated with TiO2 by the dip coating method, and characterization is done simultaneously. Curvilinear ultrasound transducer probe is most used to scan the abdomen part of the human body. Its characteristics were analyzed to find an appropriate alternate nanomaterial to be coated over its footprint to make the device a cost-effective one with even better output. Before and after the nanomaterial is coated, Fesem, EDS, and XRD tests were done over the transducer footprint. The dip coating method is easier, quicker, and cheaper but less effective among various coating methods.
A Multilayer Neural Networks Supervised Learning Algorithm Based Energy-Efficient VLSI Processor Design
Authors: Mohanapriya R. , Vijendra Babu D. , SathishKumar S. , Sarala C. , Anjali E. , Elumalai J.
Published: July 2021

Neural networks are abstract structures modeled by the brain to store evidence in the form of spikes. When introduced in VLSI circuits, neural networks are supposed to have new computer processing methods and economically viable computer simulations. We suggest a novel set of training examples for neural nets spatial and temporal coding in this article. In just this procedure, going through the roof neuronal is programmed to promote analogue VLSI applications with resistor analogue memory, from which incredible energy consumption can be accomplished. Can also suggest many strategies to boost efficiency on a model training and prove that the proposed method’s SVM classifier is as high as it was for the retrained dataset’s province temporal coding Computational Intelligence algorithms. Incorporating the developed framework can even recommend very massive circuit boards. The frequency analogue circuits utilize intermittent processing to reimburse capacitance processes, unlike the traditional analogue voltage and current type circuitry being used compute-in-memory circuits. Even though connectors lacking operating amps can still be constructed, it can also be controlled with incredibly low energy consumption. Finally, the preservation of the designed highlights algorithms toward alterations from the system’s production phase and is inevitable in analogue VLSI deployment.
Performance Evaluation of LDCMAC for Wireless Sensor Networks
Authors: Amru M , Pothalaiah S , Sowmya T
Published: July 2021

Wherever sensor nodes in each other’s contact range (CR) exist, the data packets may be transmitted in the same loop when a wireless sensor network (WSN) occurs. On a present contentious sequential MA protocol, so few nodes can forward their data packets through multiple layers in a single loop. Consequently, there has been a notable improvement in propagation time (E2ETD) with increasing nodes. The article suggests supporting event-driven WSNs with a low-delay containment-based contending sync MAC (LDCMAC) protocol. LDCMAC doubles the level of nodes that may send their databases within the same interval while nodes has data packets in one CR.LDCMAC is assessed and its performance is compared with CL-MAC protocol using NS-3 simulations. The findings show that the LDCMAC exceeds substantially the E2ETD and packet delivery ratio of CL-MAC.
Vehicle Theft Identification and License Authentication Using IoT
Authors: Verma Aryan , Seth Shikhar , Kumar Abhit , Sarada V
Published: July 2021

In this 21st century, it is difficult to trace the device on real-time platforms. To overcome this complex situation leads to developing a fingerprint cum GPS/GSM tracking prototype. This prototype model proposes that the system will get the location of the vehicle, i.e., latitude and longitude of the vehicle, and the tracing is done with the SMS sent on the receiver’s phone by sending SMS via GSM module to make the vehicle security feature to work online that is stored and can be viewed real-time by sending data by ESP module serving as a wireless fidelity module. The theft vehicle is then detected by sending the message from the tracker to the owner’s phone. On the receiver’s phone, the owner will get the emergency message, where the owner can send back the SMS to the GSM module to stop the vehicle motor using a microcontroller.
Effective Parametric Image Sequencing Technology with Aggregate Space Profound Training
Authors: Rajeshkannan S , Mishra Suman , Ganesh Babu T R , Mohankumar N
Published: July 2021

That containing the full workflow of evaluation, patient stratification, treatment preparation, operation and follow-up is assisted by robot and quick solutions for target identification and segmentation. Present state-of-the-art describing approaches are generally established on computer teaching approaches that use supervised learning image databases. The reliability in processing large volumetric images and the need for powerful, representative image characteristics reflect two major challenges to be tackled. In high-dimensional spaces where the object of interest is parametric, traditional volume scanning methods do not scale to the vast spectrum of possible possibilities. The representativeness of the picture is subject to considerable manual engineering efforts. We suggest a process in the sense of volumetric image parsing for object identification and segmentation to solve a two-step study problem: structural position approximation and boundaries differentiation. To this end, we implement a new paradigm, MSDL, which uses the advantages of efficient object approximation in marginalised centralised environments and the automatic functional nature of the network architecture of Deep Learning (DL). Intelligent systems immediately define and detach explicative properties immediately from close to zero image data, but just the approximation’s high difficulty restricts their use in the volume context.
Cardiac Arrest Prediction using Machine Learning Algorithms
Authors: Karthikeyan R , Vijendra Babu D. , EKarthik  , Suresh R. , Nalathambi M , Dinakaran S.
Published: July 2021

Cardiac arrest and other cardiovascular problems are the most prevalent issue among millions of men, and there are numerous causes that function as the basis of this crisis, such as people’s wellbeing, mainly because of job stress, exhaustion, bad food quality, and an elevated cholesterol level as a consequence of the lack of technology cardiac disease. Many scientific and medical support programs change every day, yet every program has its own special features, advantages and disadvantages. The goal of this article is to research the probability of cardiac arrest based on various regulated or unregulated variables in specific data set machine learning algorithms.
Convolutional Neural Network Architecture Based on FPGA with Reduced Requirements for Parameters
Authors: Muthu Krishnammal P , Padmavathy T V , Shakunthala M , Vimal Kumar M N
Published: July 2021

The progress of deep learning has rapidly accelerated development at an exponential rate of existing technologies. Deep convolutionary algorithms have received much popularity due to exceptional success in various technology application areas. Although the quality was outstanding, their modernising has, therefore, always posed a challenge, particularly for resource-restricted hardware devices, due to their memory and computational access intensive nature of CNNs. Research article suggests a new lowered Cnn that is used for implementations for image recognition, resulting in a major decrease in the number of the communication network. Influenced by Squeezed Network, our process of reductions substitutes convolution kernel clusters with larger particles but eliminates entirely minimum duration apart from the last classification level. If implemented in software, the building model means lower computation time. By placing all qualified neural network thought-provoking Xilinx modules, we decided to utilise structure. The system design requires 2x lower complexity and a 1.2x Delay Informational processing relative to Cnns, culminating in a successful hardware design.
RETRACTED: FPGA-based adaptive linear-line approximation and implementation for optimum photovoltaic device power control
Authors: Mohandas R , Omkumar S , Rubesh Kumar T , Rukmani Devi D
Published: July 2021

Photovoltaic technology is one of the greatest attractions among the various renewable energy sources, coupled with the availability of atmospheric temperature in quantity and without emissions of greenhouse gases due to its poor PV power. Therefore, networking opportunities lie in applying electrical power generation and transmission methods to produce voltage level with favorable rates for effective application. The photovoltaic panel’s suitable methodology is important for analyzing, controlling, and monitoring a PV generator’s design. The photovoltaic system is the basic component of a PV device, so the PV array needs to be run at the highest power point to optimize the system’s energy production. In the system, a solar tracking system is needed to function at the maximum power point. The characteristics of a PV cell’s output power and energy are semi, and therefore its output fluctuates in compliance with the difference in solar irradiation and temperature. An amount of studies has been aimed at designing successful MPPT schemes over the last decade. Research projects are still increasing interesting; however, discovering building FACTS devices and resolving their digital quality issues. Besides, the architecture of MPPTs that could cope with irradiance and temperature is difficult. The establishment of innovative strategies and transmitted source inverter control techniques for a PV device with different pulse widths. To build a filter that remove the solar array PV panel’s using current instantaneous reactive power. The voltage regulation filter based mostly on PV array is then configured with adjusted adaptive threshold control with sequence analysis size. The MATLAB simulator and FPGA and legitimate digital numerical simulations are expected to show strong harmonic adjustment for the existing PV-based SAPF.
Renewable Energy Based Grid System Using UPQC for PQ Improvement
Authors: Murugan K , Guruprasad B , Perumal Varatharaju , Arul T G
Published: July 2021

This paper proposes the grid-connected renewable energy sources (RES) based power quality (PQ) improvement is accomplished using the power compensation device of a unified power quality conditioner (UPQC). In recent days, power quality improvement is essential to the grid system and connected sensitive loads. The photovoltaic (PV) system is utilized to the power provision for the UPQC device through a boost converter which improves the Dc link voltage with pulse width modulation control. The inverters in the UPQC device are controlled using the model predictive controller (MPC), improving the voltage and power compensation. The proposed system results are validated using the MATLAB/Simulink environment.
Diabetes disease prediction using decision tree for feature selection
Authors: Sadhasivam Jayakumar , Muthukumaran V , Thimmia Raja J , Joseph Rose Bindu , Munirathanam Meram , Balajee J M
Published: July 2021

In this paper more than one approaches are evaluated to optimise machine learning models for diabetes disease diagnosis. The main goal is to sort the medical data computation and choose the most suitable parameters to construct a faster and more perfect model using feature selection. Reducing the number of features to construct a model could direct to more useful machine learning algorithms which helps the doctors to focus on what are the most significant assessment to take into story. Feature selection is one of the process in machine learning which choose a subset of topical features namely variables for construction of models. In this research paper we use three feature selection techniques like Recursive Feature Elimination (RFE), Genetic Algorithm (GA) and Burota Package. After using feature selection at the end we use Decision Tree to predict the diagnosis Diabetes using a dataset named Pima Indian Diabetes Dataset and verify the performance of result model.
Test Study on Concrete by Partial Replacement of Cement with GGBS
Authors: Ramalakshmi M , Parkavi R
Published: July 2021

A Composite material of the solid that having its remarkable physical and mechanical quality, which chiefly helps the business, likes development. The current investigation is done in two stages in an underlying blend of M30 grade concrete, and part of the way supplanted from concrete to GGBS by 0%, 2%, 4%, and 6% analyses are utilized to locate the greatest substitution rate and accomplished the solid strength attributes. This work is experimented that the GGBS based material have achieve to improve in length intended to 30% substitution of cement at the period of 7, 14, and 28 days. As far as cost is concerned, the expense of GGBS in the market, including bundling and moving, is multiple times not exactly of OPC. In this way, the incomplete substitution of OPC in cement by GGBS isn’t just practical yet also encourages environmentally-friendly removal of the waste slag into a valuable item produced in enormous amounts from the iron and steel enterprises. The ideal strength was accomplished with the blend of 6% of GGBS with concrete.
An IoT Based Safe Assembly Point Alert System
Authors: Mangayarkarasi T , Umapathy K , Sivagami A , Subitha D
Published: July 2021

A large population depends on many industries for its livelihood like electrical, embedded, software product sectors. An IoT environment includes feedback phones that use smart devices, such as MCU (microcontroller unit), sensors and different sensors, collect, distribute, and act on messages they collect from their environment. IoT systems share the sensory data they receive when data has been either sent to the cloud for global applications or analysis by linking to an IoT gateway or other edge device. For the electrical maintenance occur in the industries will need a specific alert signal. The loss of manufacturing workers/workers may be controlled by a specific, minor accident. Therefore, it is essential to provide an emergency device able to detect the non-safety state of coal and produce an alarm to reduce the possibility of risks in the system. We are proposing an IoT-based alert system via mobile phones, as smartphones’ general usage is very common in the industries rather than using a walkie-talkie.
Design and analysis of hydraulic fixture for hydraulic lift housing
Authors: Jegan M M , Pitchia Krishnan B , Shanmugam Manoj Kumar , Infant Kebin Raj P , Bose K T
Published: July 2021

Fixtures are used to hold the work piece during machining operations. It is also used during the time of inspection, welding and assembling process. This paper presents, design analysis and development of hydraulic fixture for real industrial fixture. The component is hydraulic lift housing which is tractor part. The operations to be performed are milling, drilling, reaming & chambering on VMC. In existing design, the fixture set up is done by hydraulic. The existing fixture design is vibration occurs from the machining process, so product quality is less. From existing research analysis in this area, our project idea is extra hinge clamp device has to be added. Hydraulic fixture to reduce vibration and increase the product quality. In this research is analyzed by ANSYS we have found that the new fixture design will be better than existing model because the new model will give the less amount of vibration than existing model.
Design of Deep Neural Architecture for Brain Cancer Classification Using Pyramid Design
Authors: Mohan Kumar S , Yadav K P
Published: July 2021

In this study, Deep Neural Network (DNN) with Pyramid Design (PD) is developed for brain image classification. The main objective is to design a non-invasive procedure for diagnosing brain cancer using deep learning. The signal intensities obtained from the brain tissues using Magnetic Resonance Imaging (MRI) can be used for effective treatment. A pyramid consists of a predefined number of convolution layers and a max pool layer to abstract features. In the DNN-PD approach, the pyramid is stacked with an increasing number of convolution layers and convolution filters from one pyramid to the next pyramid and so on. The stacking is employed recursively to get more accurate results. It shows that the proposed architecture gives efficient results with 98.5% accuracy using REpository of Molecular BRAin Neoplasia DaTa (REMBRANDT) database. The diagnostic results of the proposed Deep Neural architecture with the expert’s analysis can reduce the biopsies, a dangerous procedure with a great deal of pain.
A review on arbuscular mycorrhizal fungal communities in response to disturbance
Authors: Amalia A V , Dewi N R , Heriyanti A P , Daeni F , Atunnisa R
Published: July 2021

Disturbance, both natural and anthropogenic, is considered a major structuring force in communities and influences overall species. Arbuscular mycorrhizal (AM), a symbiosis between plants and members of Glomeromycota fungi, enhances water and nutrient supply. These fungi play a significant role in the establishment and resilience of vegetation. Understanding arbuscular mycorrhizal (AM) fungus response to disturbance is necessary to preserve and rehabilitate functional plant communities in a post-disturbance landscape. The methods used in this study is a literature review. Firstly, the researcher determines the scope definition of the disturbance type used in the study. The next step is to find a research study that describes the community response, such as the diversity and community changes of AM fungi. The researcher then analyzes the response in different types of disturbances and synthesizes AM fungal diversity and community structure responses. In some studies, soil disturbance reduces AM fungal diversity, spore density, and changes or unchanged in community composition. These findings indicated various responses to disturbance in diversity and community structure.
Project Based Learning (PjBL) integrated with realia media towards learning outcomes on students’ creativity and learning interest in classification of living things at SMA Negeri 3 Tondano
Authors: Nukak S K , Rayer D J J , Maramis A A
Published: July 2021

The purpose of this study was to see student learning outcomes using the Project-Based Learning (PjBL) learning model combined with realia media on students’ creativity and learning interest in the classification of living things at SMA Negeri 3 Tondano. The form of research used is a quasi-experimental research design with the non-equivalent pretest-posttest control group design. The research subjects were students of class X MIPA III and X MIPA IV totalling 52 students. The instruments used are creativity rubrics, learning interest questionnaires, and multiple choice questions. The creativity rubric is used by researchers to assess creativity during the learning process through indicators of student creativity, namely fluency, flexibility, authenticity and detail. Students’ interest in learning questionnaires were filled in by students to assess the extent of students’ interest in learning and were given multiple choice questions that were used to measure student learning outcomes whether they experienced differences in grades in the control and experimental classes. The results showed that there was an increase in learning outcomes in the experimental class for the pre-test 8.00 and for the post-test 10.84 with students’ creativity in working on realia media (herbarium) where the assessment was based on four indicators, 75% fluency in good category, 60% flexibility in sufficient category, Originality 88% with very good category and 66% elaboration with good category. Creativity also assesses the Realia Media Making Practicum Report (herbarium) based on four fluency indicators reaching 70% in the good category,
Description and analysis of physics process on island hilly land for learning the availability of clean water for junior high school students
Authors: Marianus M , Laira A
Published: July 2021

The surrounding environment has many facts and phenomena that teachers can use as a learning resource for students. The characteristics of land and process physics the inclusion of rainwater into the surface of the soil can be excavating physical concepts to become learning materials. This research aims to measure, analyze and describe the process of physics, infiltration and erosion surfaces and design and implement learning activities outside the classroom. This research uses methods of descriptive analysis. The outdoor research shows that the fastest infiltration process is on grass fields and the largest erosion potential on the open land. The results of the infiltration and erosion measurement of the surface are connected with the concept of science based on the fact phenomenon, implemented to the students with a form of assessment of the process ability and learning group achievement of students seen in the average results, as for the level of diversity of score variation between facts and the overall phenomenon seen from the value of variances. The results of this study became a teaching material as a supporter of science learning design that utilizes the environment in the form of thematic learning.
The development of Geogebra-assisted mathematics learning media on geometry of space flat-side of cubes and blocks
Authors: Pakaya A , Machmud T
Published: July 2021

The purpose of this research is to develop the mathematics learning media assisted by Geogebra on Geometry of space flat-side of cubes and blocks. This study uses the ADDIE development model, which are Analysis, Design, Development, Implementation and Evaluation. The subjects of this study were students of class VIII SMP. The results of the study based on the validation of media experts and material experts show that this Geogebra-assisted learning media is appropriate and suitable for use in the mathematics learning process. Meanwhile, based on the evaluation by the teacher, this developed media achieved practical criteria. The overall student response to this learning media is in the very positive category with a percentage of 87.1%. Thus it can be concluded that the Geogebra-assisted mathematics learning media is feasible, valid and practical to be used in mathematics learning on geometry of space flat-side of cubes and blocks.
Numerical solution for system with Atangana-Baleanu-Caputo derivative: An influenza epidemic model
Authors: Purnomo A S , Darti I , Suryanto A
Published: July 2021

In this work, we discuss the fractional three strain influenza epidemic model with vaccination for strain 1 and awareness of strain 2. We use Atangana-Baleanu in the Caputo sense. We show that the model has a unique solution, and we perform the numerical simulation with various values of derivative order. It is shown that by decreasing the value of the derivative order, the maximum value also decreases.
Use of the four-tier diagnostic test with PIMCA model on learning of microscope
Authors: Lampeang N S , Mondolang A H , Tumangkeng J V , Makahinda T , Umboh I , Poluakan C
Published: July 2021

In learning physics, students often find misconceptions. This research aims to determine misconceptions on the subject of an optical microscope by using the four-tier diagnostic test with the PIMCA model (Presentation, idea mapping, conceptualization, and assessment formative) which was introduced and developed by Cosmas Poluakan. The method used is the One Group Pre-test – Post-test Design with 24 respondents as prospective physics teacher’s students at the Department of Physics, Manado State University. The instrument used is a test instrument in the form of a (four-tier diagnostic test). The research started with the pre-test, the implementation of the physics learning followed the 4 steps of the PIMCA model and ended with a post-test. The results showed a pre-test average value of 45 and the average post-test value of 93. Based on the research results, it is shown that the learning outcomes of the students with the PIMCA MR-SR learning model increase on the subject of the optical microscope.
Phyphox application with PIMCA learning model
Authors: Mayampoh L B , Tulandi D A , Rende J , Poluakan C , Komansilan A
Published: July 2021

Research has been to do related to the experiment of Doppler effects using the phyphox application with the PIMCA learning model. Online laboratories will be the solution in the era of the Covid-19 pandemic, which still requires students to learn from home. PIMCA learning model, introduced by Cosmas Poluakan, is go together by experimental steps with the Phyphox application. The purpose of this research is to describe the ability of students to understand the concept of the Doppler effects through Doppler effects experiments. The research method begins with preliminary tests and followed by conduct the experiments with Phyphox after the PIMCA model step. The research was conducted in the physics department of Manado State University on odd semester students. The results showed that the average percentage of pre-test results was 28.125%, while the average percentage after the test was 78.125%. These results show that by doing the Phyphox experiment with PIMCA learning, students can improve their mastery the concept of Doppler effects. The observations also showed that experiments with the Phyphox application with PIMCA model learning steps could be carried out individually. The implications of this study makes it possible to carry out individual experiments at anytime and anywhere.
The use of the MR-SR based PIMCA learning model in eye as optical tools subject
Authors: Mamengko C Q , Poluakan C , Mondolang A H , Taunaumang H , Mongan S W
Published: July 2021

The learning model has long been the focus in almost all research on physics education. Research was carried out on the physics learning model in the subject optical tool. The purpose of this study was to find out learning outcomes using the PIMCA learning model (Presentation, Idea Mapping, Conceptualization, and Assessment Formative) introduced and developed by Cosmas Poluakan. This research method uses the group pretest-posttest design. This research was conducted at the Manado State University Department of Physics with 24 students as respondents. The data collection instrument was a test. The research procedure started with the pre-test, followed by the implementation of physics learning according to the four steps of the PIMCA model, which ended with a post-test. The results of the data analysis gave an average of 43.75 before the test and 77.08 after the test. The results of this study show that student learning outcomes increase in optical eye subject. The results showed that the MR-SR-based PIMCA learning model was very effective in the physics learning process of eye as an optical tool subject.
Seismicity of Suwawa Timur area based on analysis of earthquake: the depth and magnitude
Authors: Ponto N F , Manyoe I N , Zakaria S A P , Usman M M , Sumarjis S A I
Published: July 2021

North Sulawesi is an area close to the earthquake source due to tectonic processes such as active faults. This study aims to analyze the earthquake in Suwawa Timur from the earthquake depth and magnitude data. The method used in this research is a qualitative method by collecting and processing earthquake data. The analysis was carried out by creating a seismicity map of the Suwawa Timur area. The map shows that the earthquake points in Suwawa Timur are at shallow earthquakes (0 - 70 km) and moderate earthquakes (70 - 300 km). Shallow earthquakes are usually sourced from active seismic movement activity. Lithological conditions and structural geology affect the magnitude and depth of the earthquake value. Zonation map relates to the epicenter point of Suwawa Timur. Suwawa Timur is dominated by minor earthquakes (0.0 - 3.9), light earthquakes (4 - 4.9), and there is one point of a moderate earthquake (5 - 5.9).
Geological study of Pantai Indah for geotourism development based on geological observation and assessment of science, education, tourism and the risk degradation
Authors: Arifin Y I , Manyoe I N , Napu S S S
Published: July 2021

Gorontalo has geological diversity that can be developed for geotourism. One of the tourist destinations of Gorontalo that has geological features is Pantai Indah. This study aims to examine the geological features in the Pantai Indah area based on the assessment of the value of science, education, tourism and the risk of degradation. The method used is geological observation and geological feature assessment issued by the Geological Agency. The research’s results reveal that the landforms of Pantai Indah were composed of intrusion hills and marine plains. The lithology of the Pantai Indah area is granite and alluvial deposits. There is a geological structure that is indicated as a normal fault. The weighting of the criteria for the values of science, education, tourism and the risk degradation in the Pantai Indah area is 53.75%, 77.5%, 65%, 76.25%, respectively.
Analysis of fluid characteristics and estimation of geothermal reservoir temperature in Kaleosan Area, North Minahasa Regency
Authors: Polii J , Wantalangi W , Tambahani B , Ratumbuysang R
Published: July 2021

The appearance of manifestation characterizes the existence of geothermal potential. This research was conducted in the Kaleosan area of North Minahasa Regency, in North Sulawesi Province, Indonesian, which has a manifestation of hot water with a temperature of 90°C with pH of 6.89, and there are silica deposits around it, all of which are characteristics of a water-dominated geothermal reservoir. This research was carried out by analyzing the characteristics of the surface fluid samples of the Kaleosan hot water manifestations. Analysis of fluid characteristics using the Q-SO4-HCO3and Na-K-Mg. From the Q-SO4-HCO3diagram, it is found that the geothermal fluid in Kaleosan is a type of chloride. The high chloride content is thought to be due to the increase in geothermal fluids containing CO2and condensing in shallow aquifers. From the Na-K-Mg diagram, it is obtained that the Kaleosan hot springs are immature water where this manifestation fluid has undergone dilution and cooling by meteoric water during its trip to the surface. From the quartz silica geothermometer, the reservoir temperature estimate is 236.6°C, which indicates that the geothermal reservoir in the Kaleosan area is a high enthalpy geothermal system.
Vision-based Position estimation and Indoor scene recognition algorithm for Quadrotor Navigation
Authors: Anbarasu B , Anitha G
Published: July 2021

In this paper, an effective and simple Grid based vanishing point detection position estimation algorithm and Enhanced GIST descriptors based indoor scene recognition algorithm for navigation of MAV in indoor corridor environment is described. Two different classifiers, k-nearest neighbour classifier and support vector machine is employed for the categorization of indoor scenes into corridor, staircase or room. Indoor scene classification was performed on Dartaset-1. In the training phase of the indoor scene recognition algorithm, GIST, HODMG and Enhanced-GIST feature vectors are extracted for all the indoor training images in the Dataset-1 and indoor scene classifiers are trained for the extracted image feature vectors and assigned image labels of the indoor scenes (corridor-1, staircase-2 and room-3). In the testing phase of the indoor scene recognition algorithm, for each unknown test image frame GIST, HODMG and Enhanced-GIST feature vectors are extracted and the indoor scene classification is performed using a trained scene recognition model. The proposed indoor scene recognition algorithm using SVM with Enhanced GIST descriptors produced high recognition rates of 99.33% compared to the KNN classifiers. After recognizing the indoor scene as corridor, the MAV has to estimate its position based on the detection of vanishing point in the indoor corridor image frames. Experimental results show that the proposed method is suitable for real time operations.
Development of quadruped walking robot with passive compliance legs using XL4005 buck converter
Authors: Wong L H , Sivanesan S , Faisol M F A , Othman W A F W , Wahab A A A , Alhady S S N
Published: July 2021

A quadruped walking robot has an advantage on uneven terrains. In a real-world application, robots can carry heavy loads and can scout in a dangerous area. The main disadvantages of walking robots are relatively slow and high energy consumption. In recent years developed quadruped robots are mimicking several kinds of mammals. Bio-inspired mechanisms are helping to improve the overall performance. The implementations have reduced energy consumption, enhance stability, and a more comprehensive range of locomotion—this article introduces a quadruped robot with passive-compliance three segments’ legs. The leg compliance is implemented by adding an elastic spring to the leg. From the experiment conducted, the fabricated quadruped walking robot’s average walking speed is 0.06850 m/s.
Development of a small scale cartesian coordinate farming robot with deep learning based weed detection
Authors: Rajalakshmi T S , Panikulam Patrick , Sharad Patil Kshunotra , Nair Rajeev Ravindran
Published: July 2021

Automated Cartesian coordinated farming is a system designed for agricultural purposes. Being one of the trends of development on automation and intelligence in the agricultural machinery, this system is able to perform certain basic elementary functions like seed sowing, spraying, watering, etc. The idea of robotics technology is being applied in agriculture. This is being designed in minimizing the labor of farmers apart from increasing the speed and accuracy of the work. A scalable Cartesian coordinate based system is modeled, which can take care of a particular area of farm land or a garden until it is time for harvesting. The system starts by planting individual seeds at predetermined locations and then automatically waters it with the exact amount required for each type of plant. It has the ability to measure soil humidity and rainfall so that water can be used depending upon on the nature of the day. The proposed system makes use of a YOLO (You Only Look Once) object detection technique to detect weeds. YOLO processes plant images at 45 frames per second in real-time, which is faster than other object detection techniques. Here, the image is divided into several grid cells before being processed. The bounding boxes as well as the class probabilities are predicted by one single neural network, in a single evaluation. This effectively boosts the speed and accuracy of weed detection.
Design and development of a low-cost pole climbing robot using Arduino Mega
Authors: Khairam H , Choong Y M , Ismadi N S N , Othman W A F W , Wahab A A A , Alhady S S N
Published: July 2021

Nowadays, climbing robots are widely used in industrial and hazardous environments for inspection purposes. On the other hand, the Pole climbing robot can help workers fix maintenance, power transmission, etc. This article aims to design and fabricate an autonomous pole climbing robot, which can climb upward/downward a pole. The robot has two grippers at the top and bottom of the robot body, climbing along a pole by alternating release/grip mechanism. The robot body and robot grippers are fabricated using a rapid prototyping machine using PLA material. The prototype of the robot is tested on a pole of diameter 110 cm. The average time taken for the robot to climb 40 cm on a straight pole is 18.18 s and 17.21 s for upward and downward motion, respectively.