bluuebunny/crossref_metadata_2025 huggingface dataset:
A Defect-Sensitive Loss Function based on Siamese Network to Defect Detection with Imbalanced Samples
Authors: Luan Chenhui , Jing Zhengbiao , Zuo Jinghao
Published: March 2021

Surface defect detection for industrial production is tough for variety of defects and limited defect samples which make it difficult to extract expected effective defect features. To solve this problem, a defect-sensitive loss function based on Siamese Network is proposed for detecting defects of industrial production surface. The learning process minimizes the designed loss to drive the intra-class distance of the defect-free images to be smaller and enlarge the distance between hardest defect image and the defect-free images. The proposed method is evaluated on a real-word dataset. Experimental results show 100% accuracy for proposed method with imbalanced rate 10:1 and 50:1, indicating its advantage over classification CNN method. Comparison experiments show that proposed loss function outperforms other recent published loss function, the proposed loss function can be more sensitive to defect samples.
Motion simulation of Bionic Auxiliary Device for Ankle Rehabilitation based on small driving moment function
Authors: Li Hongpeng , Xia Chen , Li Feilong , Yin Jun , Wang Xiaoliang , Cheng Jiacai , Yang Bingran , Dong Penchant , Chen Enzhi
Published: March 2021

A kind of auxiliary device for ankle rehabilitation based on a ball pin vice is introduced in this paper first. The device has two degrees of freedom, while three-dimensional movement of the ankle can be achieved approximately. The modeling and simulation process of the ankle joint rehabilitation device are described in this paper. Motion simulation is preceded by using ADAMS for researching its dynamics and kinematics performance when the upper platform adopts small driving moment function to control the movement. The results are compared with the results of motion simulation driven by modified constant velocity function. The results show that the maximum driving torque of the motor driven by the small driving moment function is less than the maximum driving torque of the motor driven by the modified constant velocity function, which has a certain effect on saving energy consumption of the motor.
Simulation and Research on Dynamic Crushing of Rod Concrete
Authors: Zhu Ying , Meng Zhaoxing , Lv Haiqiang
Published: March 2021

The dynamic mechanical properties of waste glass powder concrete are studied, and the dynamic compressive strength, peak strain, stress-strain curve and dynamic enhancement factor change with strain rate and waste glass powder content are analyzed. Based on the HJC model of concrete, the SHPB test was simulated by ANSYS/LS-DYNA software. With the increase of impact pressure, the phenomenon from block spalling to aggregate crushing appears. When the impact velocity is low, several radial through cracks appear in the test block, and the test block is separated into several blocks with larger volume. With the increase of impact velocity, multiple cracks develop simultaneously.
Design and Simulation of Elevator Emergency System Based on TIA Portal V15.1
Authors: He Huajin , Long Yinxin , Yu Wei
Published: March 2021

The main control system of the elevator can issue different instructions for the operation of the elevator according to the different needs of users, so as to achieve the purpose of transporting people and goods efficiently. With the continuous development of China’s elevator industry and the significant increase of elevator installed capacity[1], In practical engineering, higher requirements are put forward for elevator safety. In this regard, based on Siemens Portal platform, this paper designs an automatic control emergency system including overweight, over travel protection, door opening and closing protection, to assist the main control system to maintain the normal operation of the elevator. The proposed scheme is simulated in the Elevator Simulation platform, and the results show that the emergency system can effectively prevent the wrong operation during the operation of the elevator, and greatly improve the safety of the elevator. At the same time, because the system is written in LAD language and has good readability and portability, it can be widely used in the elevator master control system with Siemens PLC as the main controller.
Research of Gear Modification on Noise Optimization of EV Reducer
Authors: Liu Jing , Xiong Fei , Wei Dan , Chen Chen , Sun Chao
Published: March 2021

Based on the simulation software MASTA of gear system, the micro-modification optimization can effectively improve the howling noise. Through gear contact spot test and simulation calibration, the correction model of gear can be established. In order to reduce the transmission error of gear, and optimize the gear contact pattern, the micro modification of gear was researched. It is found that the micro modification of gears can effectively improve the howling noise of gears. The study could improve the ability of independent research and development of gear system.
Research on Pressure Loss and Compensation in Automatic Detection of Pressure Quality of Hydrocephalus Shunt
Authors: Dong Quancheng , Ji Ping , Wan Min , Shi Kai , Sun Xuan
Published: March 2021

In the automatic pressure quality detection of hydrocephalus shunts, the extension pipes installed on the test piece, the mounting base of the sensor, etc. will cause pressure loss, resulting in distortion of the detection results. This paper uses CFD software to simulate and analyze the pressure loss along the way caused by the extension pipeline and the local pressure loss caused by the installation base. According to the factors affecting the pressure loss along the way such as liquid flow rate, pipeline inner diameter, pipeline length, etc., the pressure loss along the way under different pipeline lengths, different pipeline inner diameters, and different flow speeds are measured, and single-factor and multi-factor influences are carried out according to the simulation data. Analyze and establish a regression model for pressure compensation. According to the main influencing factors of local pressure loss, sudden reduction ratio, and flow rate, pressure field analysis is carried out. The simulation results show that single factors such as flow velocity and inner diameter, as well as the coupling effect of pipeline inner diameter and flow velocity, have a significant impact on pressure loss along the way, and an increase in the sudden reduction ratio will lead to an increase in local pressure loss. Experimental verification shows that the constructed pressure loss regression model can effectively compensate for the automatic pressure detection of hydrocephalus shunt.
Research on Power Enterprise Data Model Online Management Decision System Based on Big Data
Authors: Cheng Zhihua , Ye Yong , Huang Wensi , Zhang Yiqi , Lan Liang
Published: March 2021

At present, with the development of cloud computing and data analysis technology, big data technology based on cloud computing is also making continuous progress. As a cutting-edge technology based on cloud computing processing technology, big data technology is widely used in our daily production and life, bringing great convenience to our work, study and life. Under the background of today’s big data era, the new era has brought great impact on all walks of life. If everything wants to keep pace with the development pace of the times, it is necessary to carry out reform, innovation and development. In order to deal with the challenge brought by this impact, this paper proposes a research method of online management decision system of power enterprise data model based on big data background. Through big data technology, the current research status of online management decision system of power enterprise data model is analyzed. Combined with the new requirements of big data era, a set of electric power suitable for the new era is formulated Development plan of enterprise data model online management decision system. Through long-term research and observation, it can be found that the method proposed in this paper is of great significance to the research of power enterprise level data model online management decision-making system based on big data background.
Simulation and Analysis of Radial Temperature for Aluminum Conductor Steel Reinforced with 1250mm2 Large Cross-Section
Authors: Zhang Jian , Liu Shengchun , Liu Zhen , Zhang Zhao
Published: March 2021

In order to meet the growing demand for electricity, the construction of UHVDC project has vigorously carried out. With the improvement of voltage level, the cross-section of conductor also increases. For large cross-section conductor, the number of steel and aluminum single wires and layers of the conductor are large, and the internal structure is very complex. It has been proved that there is a temperature difference in the radial direction of the conductor due to the contact heat transfer between steel and aluminum based on previous studies. However, most studies are focused on normal conductors, not large cross-section conductors. Therefore, in this paper, the geometric model and temperature calculation model for 1250mm2 large cross-section ACSR conductor, which is widely used in UHVDC, were established. Simulation of conductor temperature distribution was carried out, and the influence of wind velocity, environment temperature and current on radial temperature difference was analyzed. The results show that, with the increase of wind velocity and the decrease of current, the radial temperature difference of conductor decreases gradually, while the environment temperature has little influence on the radial temperature difference.
Power Towers Knowledge Base Model Construction and Inference Analysis Based on Ontology
Authors: Gao Yuan , Wang Hongxing , Huang Zhen , Zhou Hang , Zhou Shikang
Published: March 2021

Due to the knowledge limitations in current traditional manual inspection of power towers and the difficulty of knowledge sharing and management, this paper would discuss the components of power towers with the characteristics and connections of different components based on the analysis on manual inspection. And then, an ontology-based knowledge model construction would be established for power towers. Finally, the potential association relationships in the model would be analysed according to the ontology inference rules, and the hidden information was excavated with several examples. The establishment of this knowledge base provides technical support for the path planning of UAV’s automatic inspection and helps with the fault diagnosis and identification so that it improves the sharing and reusability of knowledge in the field of power towers.
Research and Application of a New Type of Substation Transportation Inspection Simulation Training System
Authors: Wang Meikun , Gao Feng , Shi Jiaoyang , Zheng Wensu , Zhao Xilan , Wang Tuo
Published: March 2021

For the shortcomings of the existing professional training for substation operation inspection, this paper proposes a design of a new type of substation operation inspection simulation training system based on networking, adaptive learning, gamification and other technologies. The system solves the problem that substation operators lack modern training tools and cannot carry out networked simulation learning, and conduct targeted and personalized learning based on user knowledge and skills. The system lacks guidance and evaluation functions in the learning process, and the system lacks interest and cannot effectively stimulate learners’ interest in learning and other issues. The research results of this article have been successfully applied in the Gansu Electric Power Company and have obtained good training effects.
Using Machine Learning to Inductively Learn Semantic Rules
Authors: Jabardi Mohammed H. , Hadi Asaad Sabah
Published: March 2021

The Semantic Web and Machine Learning usually are seen as incompatible approaches toward Artificial Intelligence. A proposal presented for integrating the two paradigms and used data from Twitter regarding legitimate and fake accounts. Online Social Networks (OSN) such as Twitter have become a part of our lives due to their ability to connect peo-ple around the world, share documents, photos, and videos. OSN’s such as Facebook, Twitter and LinkedIn have approximately 500 million users over the world; this massive population of OSN causes different kinds of problems regarding data security and privacy. Unauthorised users infringe on the privacy of legitimate users and abuse names and cre-dentials of victims by creating a fake account. We utilised Machine Learning to inductive-ly learn the rules that distinguished a phoney account from a real one. We then imple-mented those rules in a Web Ontology Language (OWL) ontology using the Semantic Web Rule Language (SWRL). This integration provides the benefits of the data-driven ML approach combined with the explicit knowledge representation and the resulting ease of explanation and maintenance of the Semantic Web paradigm.
Transmittance on combinatorial structures of triple potential barriers
Authors: Supriadi B , Nasiroh C , Pratikha A R , Kaulyn M A , Putri D K S , Anggraeni F K A
Published: March 2021

Semiconductor materials used as potential barriers in the study are GaAs, GaSb, and AlAs. These materials will be arranged in certain combinations to form triple potential barrier structures and the effect of combinations will be analysed against transmission coefficient values. In this study, the maximum energy of the electron is 1 eV and the matrix propagation method is used where the effect of the combinations structure on transmission coefficient values is numerically analysed using a computational program. The results showed that the structuring potential barrier affects the value of the transmission coefficient. In the uniform barriers arrangements, the value of the transmission coefficient decreases with increasing potential barrier energy. Whereas in the arrangement of different barrier combinations, two opposing combination arrangements have the same transmission coefficient values. Thus, from six combination arrangements, there are three kinds of transmission coefficient values. The maximum transmission coefficient value is 1.000 in the triple potential barrier of GaSb at 0.49 eV. Research on the tunnel effect contributed to the development of electronic and optoelectronic devices such as transistors and lasers.
The relation between H2SO4 content on latex and irritant contact dermatitis on workers in plantation area company of sumber tenggulun Jember
Authors: Kiptiyah M , Wahyuni D
Published: March 2021

Dermatitis was a type of skin disease which caused by skin inflammation. The Irritant Contact Dermatitis (ICD) was a reaction which appeared when the skin got contact to toxic chemicals which caused to inflammation. The aim of this research was to examine characteristics of workers and H2SO4 content which were related to the case of irritant contact dermatitis on rubber plantation workers in a plantation area company of Sumber Tenggulun Tanggul Jember. The research design was descriptive quantitative research which would figure out the causal relationship of contact dermatitis disease to the workers, particularly in the relation with chemicals. The research population was taken from all workers in the plantation area company of Sumber Tenggulun Jember. The data sampling exerted total sampling technique on 35 samples. The data analysis was logistic regression method which aimed to analyze the data by describing or illustrating the collected data as it should be without drawing any general conclusion or generalization. The research finding referred that factors of age, gender, genetics, chemicals use, and exposure characteristic affected insignificantly to the case of irritant contact dermatitis. The plantation should recommend the workers to wear personal protective equipment as an earlier protection from the dangers of accident and occupational disease.
The diversity of freshwater fish in sanenrejo and wonoasri river resorts from meru betiri national park
Authors: Subchan W , Susilo V E , Khairiyah Y , Wahyudewantoro G , Ariyunita S , Rohman A
Published: March 2021

Freshwater fish diversity is the number of fish species found in freshwater areas. This research is an exploratory study aimed at the diversity of freshwater fish in the Sanenrejo and Wonoasri Resort’s Rivers of Meru Betiri National Park. Fishes were caught using gill nets with mesh sizes 0.5 inch and handnet The level of diversity of freshwater fish in the Sanenrejo and Wonoasri Resorts is classified as being moderate with the diversity index values in the Sanenrejo and Wonoasri Resorts respectively 1.5902 and 2.2323 while the overall index value is 2.4102. Freshwater fish found consisted of 15 species, namely: Barbodes binotatus, Trichopodus trichopterus, Neovespicula depressifrons, Rasbora lateristriata, Planiliza subviridis, Orechromis niloticus, Eleotris melanosoma, Dermogenys pusilla, Periopthalmus argentilineatus, Pterygoplichthys pardalis, Channa gachua, Butis butis, Nemacheilus fasciatus, Siycopterus cyanocephalus, and Monopterus albus.
Phytoremediation of phosphate using Typha sp. and Echinodorus palaefolius
Authors: Fitria F L , Dhokhikah Y
Published: March 2021

Jember Regency is an agricultural area. Giving fertilizer is one of the agricultural activities. It usually contains a phosphate. If fertilizer is used too much, it will cause environmental pollution. The level of phosphate pollutants increase that can cause eutrophication. Phytoremediation is a plants utilization technology to reduce pollutants. This study aims to determine the effect of Typha sp. and Echinodorus palaefolius to reduce phosphate levels from fertilizer residues. The research reactor was a batch. The reactor used bed evapotranspiration system. Phytoremediation test analysis was carried out every two days for 8 days. Typha sp. and E. palaefolius on the day 8th observation levels phosphate were down by 90,33% and 92,86%. The most efficient in this experiment was E. palaefolius.
Multi arm bandit optimization to mitigate covid19 risk
Authors: Aurachman R.
Published: March 2021

Covid19 pandemic has occurred since 2019. The spread of the virus prevents humans from doing their normal activities. The inability of people to have normal activities also has a bad effect on the economy. The government is trying to start opening public activities in the hope of sustaining economic growth. However, this policy risks doubling the spread of the virus. This research proposes a way to mitigate the risk of the pandemic using multi arm bandit optimization. With this approach, the system is guided to independently look for which sectors can be opened and which sectors should be closed temporarily.
On rainbow antimagic coloring of graphs
Authors: Budi H S , Dafik  , Tirta I M , Agustin I H , Kristiana A I
Published: March 2021

A rainbow antimagic coloring is one of new topics in graph theory. This topic is an expansion of rainbow coloring that is combined with antimagic labeling. The graphs are labeled with an antimagic labeling, and then the sum of vertex label have to obtain a rainbow coloring. The aim of the rainbow antimagic coloring research is to find the minimum number of color, called rainbow antimagic connection number, denoted by rac(G). In this research, we studied some simple graphs to be colored with rainbow antimagic coloring. The graphs we used are lollipop, stacked book, Dutch windmill, flowerpot and dragonfly. In this research, we aimed to develop new theorem. Based on the results, we got some theorems about rac(G) for the rainbow antimagic coloring. In addition, on some graphs that we use, we get rac(G) equal to rc(G), rainbow connection number. Instead, on the others, the value of rac(G) cannot reach the rc(G).
On resolving total dominating set of sunlet graphs
Authors: Ervani R S R , Dafik  , Tirta I M , Alfarisi R , Adawiyah R
Published: March 2021

The set D ⊆ V(G) is called dominating set on graph G so that every vertex not in D is adjacent to at least one vertex in D. The set Dt
⊆ V(G) is called total dominating set on graph G so that the vertex in Dt
are neighboring at least one dot in Dt
. The smallest cardinality of the total dominating set is referred to as total domination number. The total domination number in G is shown by γt
(G). The set of vertex Dt
⊆ V(G) is resolving total dominating set from G if the vertex representation u,υ ∈ V(G) with respect to x ∈ Dt
is r(υ|Dt
) so that r(υ|Dt
) ≠ r(u|Dt
). The smallest cardinality of Resolving total dominating set in G is shown by γrt
(G). In this article, we provide the results of the study for the differentiating number of total dominance from sunlet graphs.
The effect of the Covid 19 pandemic on the development of the knowledge graph as an integrated recovery accelerator
Authors: Sardjono W , Selviyanti E , Tohir M , Azizah R
Published: March 2021

The spread of the 2019 Corona virus Disease pandemic (Covid-19) resulted in many organizational entities being forced to redesign business processes, reducing the cost of reducing working hours, to terminating employment (layoffs). The informal sector has the worst impact. Thus, both the government and the private sector make various efforts in overcoming problems of social impact that arise. One of them is through the formation of the Task Force for the Acceleration of Handling Covid19 (covid19.go.id) as a single contact crisis center. However, the extent of the impact that arises will result in preventive, curative and promotive efforts at risk of not being handled properly. The implementation of knowledge management based on graphs (knowledge graph) will enable agile integration between various sources of information. The Graph Data Model captures the relationships of various different entities by connecting them through the edge of information extracted from various heterogeneous sources. After the data is represented in a graphical format, there are various analytic graph techniques for asking multi-hop (multi-node) relationships between entities in the knowledge graph that is built. In addition, graphs allow users to visualize data quickly, interactively and exploratively for analysis.
Resolving independent domination number of some special graphs
Authors: Mazidah T , Dafik  , Slamin  , Agustin I H , Nisviasari R
Published: March 2021

Dominating set is a set D of vertices of graph G(V, E) and every vertex u ∈ V(G) − D is adjacent to some vertex υ ∈ D. The set D is called independent set if no two vertices in D are adjacent. Independent domination number of G is the minimum cardinality of D and denoted by γi
(G). The metric representation of vertex υ in connected graph G with respect to an ordered set W = w
1,w
2,w
3,…,wk
of vertices is the k-vector r(υ|W) = (d(υ|w
1), d(υ|w
2), d(υ|w
3),…, d(υ|wk
)), where d(υ, w) represents the distance between the vertices υ and w. The set W is resolving independent dominating set for G if W is independent in G, and distinct vertices of G have distinct representations with respect to W. The minimum cardinality of resolving independent dominating set is called resolving independent domination number and denoted by γri
(G). In this paper, we analyze the resolving independent domination number of path graph, cycle graph, friendship graph, helm graph, and fan graph.
Global issues: utilization of e-commerce and increased use of mobile commerce application as a result of the covid-19 pandemic
Authors: Sardjono W , Selviyanti E , Mukhlis M , Tohir M
Published: March 2021

Covid-19 is a global emergency epidemic that affect all areas of life including the economy. Growth in the world economy has decreased due to lack of purchasing power that lasts for only at home policy. This policy is carried out to prevent the spread of covid-19, which on the other hand actually increases the use of e-commerce and mobile commerce as means of shopping. The use of e-commerce and mobile commerce is considered capable of helping consumers to buy basic necessities and health that are needed during activities at home. Buying and selling transaction through e-commerce and mobile commerce have increases during covid-19. Which is then utilized by e-commerce and mobile commerce by providing various attractive offers for consumers. The consumer does not need to interact with the seller and the items needed will be sent home.
Effect of problem based learning models with 3D thinking maps on creative thinking abilities and physics learning outcomes in high school
Authors: Bektiarso S , Dewi D R , Subiki
Published: March 2021

The purpose of this study is to examine the effect of Problem Based Learning with 3D thinking maps on the ability to think creatively and physics learning outcomes. This research is a true experimental research design with the Posttest Only Control Design. The data analysis technique used is a statistical test with a different test technique (t-test) using SPSS 23. Experimental class learning using Problem Based Learning accompanied by 3D thinking maps, whereas for the control class do not use it. The normality test results of student learning outcomes in the experimental and control classes are not normal, so the t test on student learning outcomes uses the Mann Whitney U Test. T test results of student learning outcomes that have a Sig (2-tailed) value of 0,000 then the value is below 0.05 which indicates that Ha is accepted (Ho is rejected) then it can be concluded that the Problem Based Learning model with 3D thinking map affects the physics learning outcomes in high school.
Introduction of the integrative STEAM approach as a learning innovation in the COVID-19 pandemic in South Kalimantan
Authors: Pasani C F , Amelia R
Published: March 2021

The COVID-19 pandemic has forced all communities to have technological knowledge, particularly in the education sector. This study aimed to introduce the integrative STEAM approach as a learning innovation in the COVID-19 pandemic for schools in South Kalimantan, Indonesia. The implementation of the 2013 thematic integrative curriculum in elementary schools is a unique challenge for parents in guiding their children. One of the suitable approaches following this demand is integrative STEAM (Science, Technology, Engineering, Arts, and Mathematics). This approach is able to perform creative and innovative learning by utilizing integrated technology in accordance with the 2013 Curriculum in elementary schools. The total of 120 correspondents participated in the service activities aimed to introduce this approach, and it consisted of Elementary School teachers and its students’ aide in the South Kalimantan. This introductory activity began with the presentation of the approach, followed by a discussion session as well as questions and answers, which ends with an evaluation of its implementation by filling a questionnaire. The results showed that 93.75% of the participants were interested in the presented topics since they aroused their curiosity. Therefore, it can be concluded that there is an increase in insight and knowledge about the integrative STEAM approach to the participants.
Model of developing key performance indicator to increase the quality of education during the Covid-19 pandemic
Authors: Selviyanti E , Sardjono W , Mukhlis M , Tohir M , Maswar M , Fariz A
Published: March 2021

Indonesia is one of the countries whose people are most affected by the 2019 corona virus (COVID-19). When the corona virus spreads faster, the Indonesian government imposed large-scale social restrictions in big cities to villages in Indonesia. With the changing situation in carrying out work activities during this pandemic, it will certainly affect the quality of organization in companies and the quality of education in schools and colleges. In order to identify all processes in teaching and learning activities that are running well or not, schools need to monitor and measure employee performance. Key performance indicators (KPIs) are generally used as benchmarks to determine how well a company’s performance can be represented by employee performance. In this study, the key performance indicator preparation process was carried out through the stages of designing a questionnaire, distributing questionnaires to employees in educational institutions, conducting factor analysis and then developing a KPI model. The output is in the form of a KPI model that can be used as a reference in the formation of KPIs in educational institutions, namely Y = 5,360 + 1,380 X1-1, 068 X3.
Blended learning: its effect towards Higher Order Thinking Skills (HOTS)
Authors: Yusuf I , Widyaningsih S W , Prasetyo Z K , Istiyono E
Published: March 2021

This research was aimed at evaluating the HOTS of the students after implementing the blended learning model. This research was a quasi-experimental type of pre-test post-test control group design. The purposive sampling technique was used to determine 2 research samples, namely biology education class as an experimental class taught using blended learning and mathematics education class as a control one. The purposive sampling technique was used to determine 2 research samples. The instrument used in this study was HOTS which consisted of 24 multiple choice items that had met validity and reliability criteria. The data of students’ HOTS was obtained from pre-test and post-test scores. The analysis technique was in the form of gain and effect size test as well as prerequisite test and hypothesis testing. The analysis results showed differences in the experimental class average post-test scores were 66.52 ± SD 17.69 and the control class was 42.01 ± SD 22.55, the experimental class gain score was 0.58 (medium) and the control class was 0.24 (low) and the experimental class effect size was 2.39 (high) and the control class was 0.53 (medium). The result of normality and homogeneity test of HOTS data showed normal and homogeneous results so that it could be proceed with hypothesis testing through t test. The result of the t-test analysis with a significant value (2 tailed) was 0.00 less than 0.05 or there were significant differences. It can be inferred that HOTS taught by students through blended learning is better than conventional models.
Analysis of physics concept in the traditional brown sugar making process
Authors: Sholihah L , Rahmania U G , Rumiati  , Munawaroh F , Handayani R D , Lesmono A D
Published: March 2021

Brown sugar is one of the traditional artificial sweeteners that is widely used by Indonesian people. Unfortunately, society considers that the brown sugar-making process is only a step of unscientific traditions and habits. This research aims to explore the physical concepts of heat transfer in making traditional brown sugar. Data were gathered through interviews, documentation, and observation. Analysis of the data used is descriptive qualitative with triangulation techniques. This research represented that brown sugar manufacturing contains heat transfer processes of conduction, convection, and radiation in the Ndewan processes. The conduction process occurred in the furnace (heat source), which propagates in the pan during the heating process, and the convection process happened when the palm sap is heated. Also, the radiation process transpired around the furnace. This study is expected as alternative teaching material in the learning physics class to be more contextual.
Prospective teacher’s expectation of students’ critical thinking process in solving mathematical problems based on Facione stages
Authors: Tohir M , Maswar M , Mukhlis M , Sardjono W , Selviyanti E
Published: March 2021

The professional teachers have to know about the students’ critical thinking process. So, a teacher can teach mathematics kindly to students at school. Then, all prospective teachers have to like that to be ready to be a good facilitator in the process of learning mathematics at school and others. This study aimed to describe the critical thinking process expected by prospective teachers to students in solving mathematical problems based on critical thinking stages of Facione’s theory. The research method used is descriptive research employing a qualitative approach. The subject of the study was the prospective mathematics teachers who were students of the Mathematics Study Program at Ibrahimy University, Situbondo, Indonesia. The data were collected by giving an essay test item to prospective teachers. The test was given to collect data related to the critical thinking process of prospective mathematics teachers. Moreover, the data collected through observations, tests, and interviews were analyzed and tested for their validity by using triangulation. The data analysis technique used is qualitative descriptive data analysis. The results of this study indicate that: (1) each of group subjects’ expectations tend to have different expectations for students’ critical thinking processes; (2) the high-group subject tend to expect that students follow and complete all of the critical thinking process stages according to Facione’s theory; (3) the moderate and low-group subjects tend not to expect their students to follow and complete all of the critical thinking process stages according to Facione’s theory; and (4) the percentage of indicators achievement of critical thinking processes expected by prospective teachers to students in solving problems based on Facione theory was revealed to be; Identify (57.14%), Define (50%), Enumerate (78.57%), Analyze (50%), List (39.29%), and Self-Correct (32.14%). The results of this study can serve as the fundamental to be discussed within the teacher’s summit in finding out the critical thinking process expected by teachers towards the students, because it will have a positive impact both on themselves and their students.
Analysis of image representation capability in physics learning through the textbook based process image
Authors: Jamilah R N , Mahardika I K , Indrawati
Published: March 2021

Physics is closely related to verbal concepts, pictures, graphics, and mathematics. The results of learning physics can not only be seen through the ability of students to represent physical concepts verbally and mathematically, but can also be seen through the ability to represent in the form of images and graphics. This study aims to analyze the abilities of students in interpreting process images in physics learning in the subject of direct current electricity. This study uses quantitative descriptive research by involving high school/MA grade XII students as research subjects. The analysis in this study was carried out with the analysis of several related journals. The results showed that the level of students’ ability to interpret images in textbooks based on physics learning through physics based textbooks in the process included in the sufficient category.
Uphill running exercise of speed on futsal extracurricular high schools
Authors: Hartati  , Aryanti S , Destriana  , Pangestu E
Published: March 2021

The purpose of this study is to determine the effect of uphill running exercises on the speed of soccer extracurricular participants in senior high school number 6 Palembang. This research is an experimental research design with Quasi Experimental Design in the Nonequivalent Control Group Design. The population in this study is 60 people, and the sample in this study is the same as the total population. The sampling technique in this study uses a systematic sampling technique with ordinal pairing system. The experimental group was the group given treatment in the form of Uphill running while the control group is the group that was not treated. The type of instrument used in this study is the 60meter run test or often called the 60meter sprint test. This form of test is used in the initial test (pre-test) and final test (post-test) which aims to determine the fastest time prediction level of students, the results obtained by the average experimental group time at pre-test of 75 and post-test 79.1, and obtained the average results the average time of the control group at the pre-test was 74.9 and the post-test was 76.4. After testing the results of the data were analyzed using statistical data analysis techniques t test with a significant level (α = 0.05). Based on the data analysis of the research results obtained tcount = 14.33, and ttable = 1.675. The findings in this study are that uphill running exercises significantly influence the speed of soccer extracurricular participants. it can be concluded that the existence of uphill running training can affect the speed of the futsal extracurricular participants.
A predicting method for the health state of the rolling bearing
Authors: Jiang Hongyan , Fang Dianjun
Published: March 2021

As an important component of rotating machinery, the health of rolling bearings is related to the normal operation of the whole machinery. A Period-Sequential Index (PSI) method was used for forecasting the three working states of the rolling bearing: health, fault, or failure. A sample from the vibration signals of the bearing, running only 2538 min because of a fault of its inner race, were tested by using the PSI algorithm. The results show that, this proposed PSI algorithm showed satisfactory forecasting quality in predicting whether the bearing is working in a healthy state or not. And, the value of the mean absolute percentage error at a fault state or a failure state was higher than that at a health state.
Applying value stream mapping in packaging industry: a case study
Authors: Joochim O , Jungthawan S
Published: March 2021

The aim of this paper is to increase the productivity of a packaging manufacturing process by using lean manufacturing technique. The current system of this packaging manufacturing process has been mapped using Value Stream Mapping (VSM) tool. This tool is a lean manufacturing tool, and the wastes in the current system are identified. The case study shows how the VSM tool has been utilized for identifying and decreasing the waste in the manufacturing process resulting of the total cost saving of 3,247,251 Thai Baht (THB) per year.
Modified Vgg Deep Learning Architecture For Covid-19 Classification Using Bio-Medical Images
Authors: ANAND R , SOWMYA V , VIJAYKRISHNAMENON  , GOPALAKRISHNAN E.A. , SOMAN K.P.
Published: March 2021

The world encountered a deadly disease by the beginning of 2020, known as the coronavirus disease (COVID-19). Among the different screening techniques available for COVID-19, chest radiography is an efficient method for disease detection. Whereas other disease detection techniques are time consuming, radiography requires less time to identify abnormalities caused by the disease in the lungs. In this study, one of the standard deep learning architectures, VGGNet, is modified for classifying chest X-ray images under four categories. The planned model uses images of four classes, namely COVID, bacterial, normal, and viral images. The performance matrices of the planned model are compared with five deep learning architectures, namely VGGNet, AlexNET, GoogLeNET, Inception-v4, and DenseNet-201.
Performance Analysis of Dimensionality Reduction using PCA, KPCA and LLE for ECG Signals
Authors: Haris Mita J , Ganesh Babu C , Gowri Shankar M
Published: March 2021

Machine Learning is a predominantly developing field in the current scenario due to spontaneous growth in size of data. Dimensionality Reduction is significant step used in machine learning. The Imprecation of dimensionality refers to the difficulty that comes up when working with high dimensional data. The Proposed work developed to reduce the risk of high dimensional data representation in the form of low dimensional data representation. This paper presents the dimensionality reduction practices such as Principal Component Analysis (PCA), Kernel PCA and Locally Linear Embedded (LLE).
Multi-objective economic dispatch of distributed generation using differential evolution algorithm
Authors: Mariakuttikan Arumugababu , Rajaram Mahalakshmi , Ananthan Bhuvanesh , Subramanian Kannan , Pandiyan Murugesan Karuppasamy
Published: March 2021

Economic Dispatch (ED) deals with the allocation of the essential load amid the existing power plants such that the operating cost is reduced. The ED problem is framed as a nonlinear optimization problem with subjected constraints. In this study, a distributed generation (DG) optimization using a multi objective differential evolution (MODE) algorithm is explored. This study aims to find out the minimum fuel cost, environmental pollution penalty cost and minimum system real power loss. MODE algorithm is implemented on 33-bus distribution system (DS) to obtain the ideal real power dispatch of DGs. Four DGs are considered which having two diesel generator, one wind generator and one fuel cell. The result shows the minimized value of Fuel/Emission penalty cost and power loss in the DG units using MODE algorithm when compared with Multi Objective Particle Swarm Optimization (MOPSO) algorithm.
Fake news detection using machine learning and Natural Language Inference (NLI)
Authors: Sabarmathi K R , Gowthami K , Sanjay Kumar S
Published: March 2021

The proliferation of misleading facts in everyday get right of to media retailers such as social media, news through online mode, FM Radio, newspapers, TV channels have found it difficult to select authoritative news outlets, for that reason growing the need for ai technologies capable of offer insights into the accuracy of internet resources. We recognize the computerized identification of false news in online mode in this paper. Our approach to this identification of fake news is in two procedural ways. First, we present two new datasets for the undertaking of fake information identification which covers several domains. The Natural Language Interference (NLI) models are also trained. The data collection, interpretation, and testing process are clarified in depth and present various research analyses at the identity of linguistic variations in false and truthful data. Second, we test and train a set of mastering discoveries to create precise fake news detectors. We shall see the process in fake- news detection.
Visual Speech Recognition using Convolutional Neural Network
Authors: Soundarya B , Krishnaraj R , Mythili S
Published: March 2021

Visual speech Recognition or Lip reading is used for teaching differently abled persons to communicate with others. It has been determining speech by looking at the movement of the lips. There are many practical difficulties in traditional lip-reading recognition systems like complicated image processing, difficult to teach classifiers and recognition processes will take a long time. In our paper, we proposed the use of convolutional neural networks- Hidden Markov model (CNN-HMM) in lip reading. Since CNN will assign importance to an input image, it is easier to see a difference among the images. HMM used to handle the dynamics of the image sequence. First we convert the incoming video into images and these images selected for further operation. HMM provides a highly reliable way of speech recognition.
Selective activation of Forearm muscles for improving Wrist Joint Stability
Authors: Arulkumar A , Babu P
Published: March 2021

The wrist movements has important role in the daily life activities. Flexion, ExtensionandAbduction and Adduction are acceptable movements in the wrist. The Strength training of extensionis necessary for prevention of wrist sprains due to flexion movements because flexionforce is morethan extension Aim of this study was to improve the muscle strength by human resistive trainingand inspecting selective activation of forearm muscles in the above movements. 10 subjects wererecruited for performing maximum Isometric contraction at human resistive training and Flexorcarpiulnaris, Flexor carpi radialis,Extensor carpi radialislongusExtensor carpi ulnarisand abductorpollicislonguswereselected for investigation. Surface electromyography was used to get thecontraction level. Ourresult showed co activation of investigated muscles were less in synergistic thanagonist function (FCU:during Abduction 45%, ECU: during Abduction 37%, FCR:during adduction43%, ECRL: during adduction 29%, APL: during flexion 23%) (P<0.0001).In the APL investigation, there was significant difference observed in the interaction effect (P=0.054, F(3, 9)=140.29,ηp2
=0.205). In the isometric training, biomechanical stability of radio carpal and midcarpal wasimproved due to strengthening of forearm muscles.
RETRACTED: Sentimental analysis using Machine learning techniques on python
Authors: Sampoornam K P , Hemalatha B , Kaaviyasri M , Jaya Priyanka K
Published: March 2021

Really, a sentiment alludes to the mirrored image of feelings of people. The modern-day globe seems concerning the strings of feelings. People pleasure this is specific trouble, love, contempt and so on thru precise activities. Division of feelings i.e. good, terrible and nonpartisan, is called emotional analysis. The goal this is essential to research how textual content exam techniques may be nicely used to dive right into a percent of the supplied facts in a improvement of posts zeroing in on diverse styles of tweets dialects, tweets volumes on twitter. The project this is complete finished the use of Python.
A Novel Method of Billing System Using Deep Learning
Authors: Haritha J , Prakash K , Navina B , Saveetha S
Published: March 2021

In order to make the billing process of goods easier and quicker for the customers as well as the shopkeepers, the RFID tags and the bar-codes are used in most of the products. But for the edible products like fruits and vegetables, these tags cannot be used as each item has to be stuck with the tag and its weight must be measured individually. To overcome this, a system is designed in which the weighing and billing of the fruits and vegetables are automated. The proposed billing system consists of Raspberry pi, a microprocessor with a camera module and a load cell. Using Raspberry pi 3 camera module, images of fruits and vegetables are captured and are recognized by using the deep learning technique, ImageNet which is built on Convolutional Neural Network (CNN) architecture and a machine learning technique, K-means clustering is used for classifying the products into corresponding groups. The camera module captures the images of the fruits and vegetables placed on the tray under which the load cell is placed for the weighing purpose. The price of various items per kg is given as an input to the microprocessor. As a result, the Raspberry pi computes the total cost of the items and displays it on the monitor. The general-purpose high-level programming language, Python is used for developing the efficient deep learning algorithm.
Desıgn of Dual Feed Antenna for ultra Wıde Band Applıcatıons
Authors: Priyadharsini S. , Nataraj B.
Published: March 2021

In this study, a simple architecture of UWB antenna with microstrip patch operating in a frequency range of 3.1 to 11 GHz with dual feed structure is proposed. The compactness and low profile of the designed antenna has gained its importance in commercial and industry oriented applications. The proposed antenna radiates well with good return loss, radiation pattern and gain. The results have been obtained by simulating and testing the proposed antenna. The proposed antenna uses FR4 as substrate. The antenna is simulated using HFSS 13.