bluuebunny/crossref_metadata_2025 huggingface dataset:
Emotion Recognition in Hindi Language using Gender Information, GMFCC, DMFCC and Deep LSTM
Authors: Kumar Sandeep , Yadav Jainath
Published: August 2021

Long Short-Term Memory (LSTM) captures long-term dependencies accurately than other types of neural networks, and it is frequently used in deep learning. In this work, we have explored Deep LSTM with a dropout layer that minimizes the training overfitting. We have considered IITKGP-SEHSC emotional dataset for emotion recognition. We only deal with five types of emotions, namely angry, fear, happy, neutral, and sad emotions recorded from male and female speech. Since the IITKGP-SEHSC dataset is monolingual that means only spectral features are sufficient for emotion recognition. Traditional MFCC deals with low-frequency information. Here, we have explored two features, namely Gammatone Mel Frequency Cepstral Coefficient (GMFCC) and Discrete wavelet Mel Frequency Cepstral Coefficient (DMFCC). GMFCC deals with basilar membrane displacement obtained from the gammatone filter, and it is useful for recognizing gender from emotional speech. DMFCC deals with MFCC analysis on the high-frequency components of speech rather than the low-frequency components. In the proposed work, DMFCC has been explored for recognizing emotions from speech. The average accuracy of gender classification with Deep LSTM and GMFCC is 98.3%. The average emotion recognition rate with Deep LSTM and DMFCC is 92% and 88.7% individually for male speech and female speech, respectively. Our proposed model is built by combining the above sub-models, and it gives emotion recognition accuracy of 91.2% for male speech and 87.6% for female speech, respectively.
Ergonomic support system for construction worker’s hand arm for lifting tasks
Authors: Jain Saksham , Verma Himanshu , Khan Abid Ali
Published: August 2021

In this paper, a novel passive arm exoskeleton is introduced to assist the construction workers in load lifting/carrying tasks. The exoskeleton is designed based on torsion springs to generate assistive torque at the elbow and wrist joint and can fully support the weight of 8 kg task load. Static simulation of the springs and arm bracing was performed to check the correctness of the design parameters in ANSYS. The exoskeleton is extremely lightweight, economical, and easy to use as it provides a novel locking arrangement, which may allow workers to instantly disconnect the springs as per their need, making it highly suitable for the construction workers.
Detecting Pneumonia Lung Infection From X-Ray Images with Deep Learning
Authors: Raheja K , Goel A , Mahajan M
Published: August 2021

Pneumonia is one of the most prominent basis of premature death globally, according to some of the major health institutions like WHO more than 1 billion people around the world get infected and more than 4 million people die prematurely due to pneumonia lung infection. Detection of pneumonia infection requires a lot of medical tests, which can be expensive and time consuming. Deep Learning, the technology which gives computer systems the ability to learn and adapt through unstructured data in order to complex solve real world problems has the potential to make the detection of pneumonia easier, cost effective and less time consuming. The motivation behind this paper is to grasp the criticalness and utilizations of deep computational learning and Convolutional Neural Network (CNN) by executing it so as to recognize Pneumonia by examining a patient’s chest x-beam pictures.
IoT and Machine Learning Based Health Monitoring and Heart Attack Prediction System
Authors: Sahoo Sudarsan , Borthakur Priyanuj , Baruah Niharika , Chutia Bhaskar Pratim
Published: August 2021

The increased use of mobile technologies and smart devices in the area of health has caused great impact on the world. Health experts are increasingly taking advantage of the benefits of these technologies and hence generating a significant improvement in health care in clinical settings. Internet of things (IoT) and machine learning techniques can be used efficiently for this purpose. The objective of this work is to design and develop a real-time IoT based health monitoring and heart attack prediction system that integrates vital signs sensors, location sensors, ad-hoc networking and web portal technology to allow remote monitoring of patient’s health status and to predict the heart disease through various machine learning techniques. In this work it has ensured the correct and efficient transmission of the vital signs data to the ThingSpeak server through the internet via a given access point(AP) and notified the user of the same through the GSM module. A heart attack prediction system is also developed to predict the probability of heart attack from the available parameters. The novelty of the proposed work is that it takes the advantage of both the IoT and machine learning technology to monitor and predict the diseases. The proposed system is inexpensive too.
Emerging Applications of Artificial Intelligence in Structural Engineering and Construction Industry
Authors: Hooda Yaman , Kuhar Preeti , Sharma Kaushal , Verma Neeraj Kumar
Published: August 2021

With the beaming concept of Construction 4.0, the disciplines of structural engineering and construction industry needs an advancement for the data collection, interpretation and analysis. Augmented Intelligence and its various disciplines find an impressive application in the field of civil engineering for data requisition, management and performance. This study focuses on how AI and its various principles can be blended with the emerging areas of structural engineering, and how it is shaping the construction industry by employing in the major areas of monitoring of structural health, assessment of damages and construction management.
Artificial Intelligence Based Breath Analysis System for the Diagnosis of lung cancer
Authors: Binson V A , Subramoniam M
Published: August 2021

Breath analysis has become a promising tool for the detection of pulmonary diseases in recent years. This paper describes the fabrication of an artificial intelligence (AI) based e-nose system for discriminating lung cancer patients from healthy controls. Breath volatile organic compounds (VOC) can be easily analyzed using an electronic nose (e-nose) made of various gas sensor arrays. Metal oxide semiconductor (MOS)-based e-noses are getting popular in the VOC analysis of exhaled breath from humans. Here we have developed the e-nose system with a sensor array system of five MOS gas sensors and incorporated the controller and machine learning algorithms to process the data. The sensor array was designed with MOS sensors developed by Figaro USA and the data acquisition was carried out with the help of the Arduino Uno developer board. 40 healthy control samples and 24 lung cancer patient samples were analyzed using the developed e-nose system. The data analysis was done by two supervised classification algorithms random forest and logistic regression. Among this, random forest with 5-fold cross-validation gave better results with 85.38 % classification accuracy and 0.87 of AUC. This system can be further extended to the diagnosis of various other pulmonary diseases.
A Stacking Model for Aviation High Risk Event Decision Making
Authors: Monika  , Verma Seema , Kumar Pardeep , Kakran Mansi
Published: August 2021

Aviation accidents are one of the most causes of severe injuries and death worldwide. With the increase in inter-countries movement of the peoples around the world, air transportation is increasing at a much faster rate. As result possibilities of air accidents have also increased which may be due to inter-air collision, technical fault in airplane systems and pilot faults, etc. Nowadays aviation accidents have become one of the major causes of severe injuries and fatalities around the world. This attracts, the research community to look into the factors behind these accidents by applying data analysis techniques based on an advanced machine learning algorithm. This analysis would be beneficial in forecasting the high-risk events based on the available historical accident data. So, in this paper, we classify all aviation abnormal events into three groups with regards to their associated risk: low-risk events, medium-risk events, high-risk events and then deployed ML algorithms like Random Forest, Support Vector Machine (SVM), XGBoost, Logistic Regression, etc., to make forecasts about high-risk events. After analyzing the results, the performance of the hybrid model that is formed by stacking of best-performing algorithms is found to best in quantifying the high-risk events.
A Framework for Analyzing Road Accidents Using Machine Learning Paradigms
Authors: Shweta  , Yadav J , Batra K , Goel A K
Published: August 2021

Road Safety is a matter of great concern throughout the world. As number of casualties is increasing more than 4% annually in all age groups. It has been predicted that due to road accidents causality rate will grow around 8% till 2030. It’s entirely admissible and saddening to let citizens get killed in road accidents. As a result, to handle this sort of situation, an in-depth analysis is required. The Data of Road accidents are very heterogeneous in nature so analysis of such type of data is tricky. Segmentation is the main task for analyzing such data. So, K-means clustering method is mainly used for it as proposed in the research work. Second task of this model is to extract the data, images and hidden patterns by using Supervised Machine Learning algorithm that will help to form the policies for the prevention from road accidents. The combination of segmentation machine learning algorithm produces meaning full information.
Protection and Strengthening of Corroded Prestressing Tendons
Authors: Sharma Kaushal , Hooda Yaman , Kuhar Preeti , Verma Neeraj Kumar
Published: August 2021

As of late, structural deterioration of RC structures affected by corrosion is widely reported. A new evolution in maintenance of RC structures is by cathodic protection by the use of carbon fiber reinforced polymers (CFRP). Using steel bar as a cathode and wrapping of CFRP as anode, which prevents removal of concrete cover and blocks further corrosion of steel. This article presents the utilization of CFRP for the protection of the strand. Series of laboratory trials using cathodic protection systems were performed on pre-stressed concrete structures in order to set up reliable cathodic protection systems. To initiate initial corrosion in the specimens, pre-stressing tendon used as the cathode and CFRP used as the anode while the in the active protection, the impressed charge was passed through the strand. Then, CFRP sheets were bonded by using conductive adhesive to the block samples. Extensively corrosive environment was imposed on the samples for the particular period of time and it was observed that the active protection method is very effectual in slowing down the corrosion of the strand.
Assembling of Robots in Presence of Line Obstacles with Direction-only Axes Agreement
Authors: Sadhu A , Mukhopadhyaya S
Published: August 2021

This paper addresses the problem of assembling semi-synchronous oblivious robots in presence of horizontal line obstacles under direction only axes agreement model. In this article, a distributed algorithm is proposed for a swarm of autonomous mobile robots that are required to assemble over the boundaries of a rectangular bounded region within a finite amount of time. The robots are initially deployed randomly within the region and assumed to support the non-rigid motion. All the line-shaped obstacles are randomly scattered within the region and are assumed to be positioned horizontally, parallel to the top and bottom boundaries of the rectangular region. Though the robots are assumed to have unlimited visibility, these opaque obstacles restrict their vision. The existing solution to this problem assumes full axes agreement among the robots, whereas, the proposed solution assumes direction only axis agreement, a much weaker model. Our proposed algorithm is fault-tolerant and supports the collision-free movement of the robots. It successfully assembles robots on the left and right boundaries of the region.
Implementation of GPSR protocol with various mobility models in VANET Scenario
Authors: Raheja K , Mahajan M , Goel A
Published: August 2021

In Vehicular Ad hoc Networks (VANET), topology varies very frequently because vehicles move in high speed. VANET is deployed on road. In GPSR Protocol, as the data packets are forwarded depending upon on the beacon information sent by neighboring nodes, which contain the location of neighbors. Hence nodes move in mobile nature as they change their positions. Mobile pattern of node is reflected by Mobility Models, as they characterize the movement of users who are mobile on the road, with respect to their direction, velocity and location over a period of time. Mobility models are practiced in implementation of protocols and the pattern by which the mobility models reflect real world practices of vehicles on the roads. Using simple pattern randomly, graph constrained mobility models are common practices while doing research. These models donot describe mobility of vehicles in realistic manner. For instance while accelerating and decelerating in the presence of nearby vehicles, these situations greatly affect the Network performance. Selecting the mobility model which is realistic one is the main focus of this paper. To address the challenges such as high mobility of vehicle nodes on the road and random topology, VANET needs a suitable mobility model to obtain improved Packet Delivery Ratio, Throughput, End to End Delay etc. This paper first implements the GPSR Protocol and then GPSR is analyzed by applying different mobility models such as Random Way Point, Gauss Markov, Manhattan Grid, Reference Point Group and Random direction. Results are analyzed by taking the following parameters: Routing overhead, Throughput, PDR and End to End Delivery. The implementation is carried out using NS—2.35 and Bonmotion is used to create mobility models.
Quality-of-Service Prediction Techniques for Wireless Sensor Networks
Authors: Pundir Meena , Sandhu Jasminder Kaur , Kumar Ajay
Published: August 2021

The rapid development of smart sensor nodes generates great interest in Wireless Sensor Network (WSN). The distinct applications of these networks have evolved in the field of border surveillance, Internet of Things, agriculture, healthcare, and disaster monitoring. It is a complex task to satisfy the need for Quality-of-Service (QoS) in a real-world environment, due to the size and dynamic nature of the mobile sensor nodes. This paper addresses the QoS metric based on the layered architecture of WSN. There are two types of layered architectures, namely classic-layered architecture and cross-layered architecture. In a classic-layered architecture, QoS is achieved based on the individual layer. Due to the interconnected nature of these layers, it is difficult to achieve the overall QoS in a classic-layered architecture. This challenge is resolved with the help of cross-layered architecture. Further, the proposed statistical analysis illustrated the fact that the QoS metric enhances the performance of the network in terms of latency, throughput, energy, and reliability. Finally, the machine learning approaches are discussed in the light of QoS metrics to enhance the overall performance of the network.
Parametric optimization in WEDM with H-13 hot die-hard steel using Taguchi Method
Authors: Deshwal Monika , Deshwal Dinesh , Kumar Pardeep , Kannojiya Vikas
Published: August 2021

Good surface quality and the processing of complex shapes are the essential requirements in various manufacturing industries today. To achieve this, scientists are switching from a variety of conventional machining methods to non-traditional machining processes. Wire EDM (WEDM) is one of the most common non-traditional machining processes. In terms of quality, surface roughness (SR) is an important performance parameter in machining processes. The article summarizes the parameters that affect surface roughness.
Data Acquisition System for Preventive Maintenance of Equipment in the Urban Tunnels
Authors: Kumari Sumit , Siwach Vikas , Singh Yudhvir
Published: August 2021

Urban Tunnel construction for supporting the Under-ground Transit Solutions (UTS) namely Metros and Subways in highly densely populated locations involves huge power requirements. This power requirement is normally met by the power supplied by the power agencies for the over the ground requirements. However, in the cases of underground work at the drilling site or de-watering sites we need to use the smaller portable generator sets. These generator sets generate a lot of harmful gases and CO2 and in-cases of over loading lead to short circuits and also fire. In the cases of prolonged tunneling times these generators remain inside the tunnel and are not serviced on time leading to gen-sets often going out of order leading to loss of work and may also cause accidents. Regular maintenance enhances the lifespan of the generators. This paper takes the approach to provide a solution to the preventive generator maintenance problems which would take care of reliability issues. In the proposed design we monitor the vital parameters of the gen-sets like fuel levels, temperatures, loads (current and voltage), running time, last servicing time, average fuel consumption, last serviced dates, battery voltages, Air filter life etc. This information is then collected by an on-board Data Acquisition System (DAS) which is then passed on to Cloud via a Wi-Fi connection. Once this information is made available on the cloud, we can apply the Machine Learning Algorithms to predict the failure rates of the generators and calculate the RUL - Remaining Useful Life.
Optical Band Gap Determination of Ni-Al Doped Polyaniline at Room Temperature and Different Annealing Temperatures
Authors: Joshi G P , Tyagi Ankit , Meena SL , Chourasia Shubhangi , Saxena N S , Kumar Ajay
Published: August 2021

Spectroscopic techniques are very useful for characterizing semiconducting and conducting materials. The optical properties (specially reflection spectra) of polyaniline mix with metal Ni and Al with different composition in bulk form were studied. The reflection spectra of these materials are recorded by a Hitachi spectro-photometer model (330), at room temperature, in the wavelength range 300-600 nm. From the analysis of reflection spectra, polyaniline mix with metal Ni and Al have been found to have energy bandgap which decreases with increase of concentration of Al. an effort has also been made to study the structure formation using XRD techniques.
Reflective Practice of Pre-Service Mathematics Teacher on Online Learning
Authors: Abidin Z , Budayasa I K , Khabibah S
Published: August 2021

One important part of the teaching and learning process is reflection. The deeper a teacher’s reflection, the better it is for the improvement of subsequent learning. This study aims to determine the depth of reflective thinking of pre-service mathematics teachers on their teaching practices. This type of research is descriptive research with a qualitative approach. The learning was conducted online for two months by ten students of pre-service mathematics teacher at five different schools. There are four types of reflection depth used, namely general type, description type, argumentation type, and contribution type. The method used was observation and in-depth interviews which were also conducted online. The instruments used were observation sheets, interview sheets, questionnaire sheets and portfolios. The results showed that the depth of reflective thinking of pre-service mathematics teacher increases from argumentation type to contribution type. This has a positive impact on improving the quality of learning.
Development of Pop-up Book Mathematics Learning Media on Polyhedron Topics
Authors: Fazira S K , Qohar A
Published: August 2021

One of the difficulties of students studying the polyhedron topics is the visualization of the objects so that a learning media that can help and motivate students in learning polyhedron is needed. This research aims to develop a mathematics learning media in the form of a pop-up book to help students learn the material of polyhedron. This research is a development research that uses the Borge & Gall method, which consisted of several procedures as follows: (1) analysis of the to-be-developed product; (2) first product development; (3) validation and revision; (4) large-scale field tests; and (5) the final product. The subjects of this research were 30 students of 8th grade Sunan Kalijaga Malang Junior High School. The pop-up book media developed was declared as valid and received an excellent response from students. Teachers are advised to use a pop-up book media in polyhedron learning.
The impact of interactive online learning by Pear Deck during COVID-19 pandemic era
Authors: Haryani F , Ayuningtyas N
Published: August 2021

The COVID-19 pandemic surprises the world, switches every learning activity to online learning and increases online education platforms’ demand. However, teachers must be careful in choosing online education platforms as some online learning applications may look exciting but not give meaningful learning for students. This study uses the Pear Deck to build meaningful learning by establishing the interaction in a mindful activity. As an add-on application of PowerPoint or Google slides, Pear Deck is one solution for teachers to engage students in active and meaningful learning even though the learning mode is changed online. The participants of this study are 20 students from Linear Algebra class. After the class is over, the researcher distributes the questionnaire adopted from the Triple E Framework to assess online learning effectiveness. More than 75% of students responded that teaching and learning by using Pear Deck not only built the interaction as well as the engagement between teachers and students but also allowed them to enhance their knowledge and extend their knowledge through the learning activities. Finally, this research suggests that using the Pear Deck should be followed by the flexible type problem to enhance the higher-order thinking skill.
Promoting Prezi-PowerPoint presentation in mathematics learning: the development of interactive multimedia by using ADDIE model
Authors: Rosmiati U , Siregar N
Published: August 2021

Prezi-PowerPoint presentation results from developing learning media that combines PowerPoints with zoom-in and zoom-out effects, which are the hallmarks of Prezi. Prezi-PowerPoint presentation is a new learning medium for students designed to create an interactive and fun learning environment. The development of interactive learning media Prezi-PowerPoint presentations in mathematics learning aims to help students improve learning efficiency to achieve learning objectives. The research method used is research and development using the ADDIE model. The research implementation is limited to two media experts, one material expert, and three students. This is because the research was conducted at the time of the COVID-19 pandemic. The students response to the development of interactive learning media in the Prezi-Powerpoint presentation was good. It could happen because Prezi-PowerPoint presentation is a learning media that is new and attractive to students. Based on the feasibility test of learning media, it is obtained that the average percentage of the feasibility of developing learning media Prezi-PowerPoint presentation is suitable to use with good interpretation. Thus, Prezi-PowerPoint presentations are also relevant to use as an interactive learning media for students.
Promoting the middle school students’ engineering skills and conceptual understanding through STEM-based learning
Authors: Rusmana A N , Widodo A , Surakusumah W
Published: August 2021

Incorporating engineering in STEM education equips the students with the 21st-century skills to design solutions for real-world problems, thus, STEM-based learning has been widely studied. This study aims to examine whether STEM-based learning can promote students’ engineering skills and conceptual understanding. The participants were 68 seventh-grade middle school students, divided into 35 STEM and 33 non-STEM students. This study was conducted in environmental pollution topic where students design and make prototype to clean polluted air and water. The students’ engineering skills during the project were measured by rubric while their conceptual understanding was examined by multiple-choice question. The independent t-test was employed for data analysis. The result showed that engineering skills of STEM and non-STEM students significantly improved (p <.001) from pre to post-test and had a large effect size (d
stem=5.87, d
non-stem=3.19). The N-gain value of STEM students (M=0.62, SD=0.14) was higher than non-STEM students (M=0.20, SD=0.06). However, although concept test scores of STEM students increased significantly (p<.001), STEM students’ N-gain value (M=0.19, SD=0.30) was lower than non-STEM students (M=0.23, SD=0.20), indicating that the improvement is solely a learning effect, not because of STEM-based learning. To conclude, STEM-based learning successfully promotes the student’s engineering skills, but not conceptual understanding.
Trend of environmental science project: A reflection of Thailand GLOBE student research competition
Authors: Laplai Y
Published: August 2021

The Global Learning and Observations to Benefit the Environment (GLOBE) is an international science and education program that promote teaching and learning of science, enhance environmental literacy and awareness. The Institute for the Promotion of Teaching Science and Technology (IPST) acted as a country coordinator. IPST has implemented GLOBE throughout the country. One of the important approach is “GLOBE Student research competition (GLOBE SRC)”, this project aim to promote students to learn and share Earth System Science (ESS) research. The research focused on environmental science by using GLOBE measurement protocols. This study reflected outcome of the project such as the amount of ESS research, type of environmental science research and learning outcome of the project in 2009 - 2020. A total of 451 researches were analyzed in term of title and abstract. The result indicated that Survey research is 69%, Experimental research is 26%, and Invention research is 5%. The trend of the Experimental research increased and Invention research slightly increased in the last six years. The result indicated that this approach enabled students to improve their scientific inquiry, scientific thinking and scientific attitude. They received learning experiences that build 21st century competency to assist them in the future.
Embedding STEM in the mathematics classroom: A case study of vocational high school teacher’s practice
Authors: Marfuah M
Published: August 2021

Mathematics teachers often question the practice of Science, Technology, Engineering, and Mathematics (STEM) education without diminishing mathematics’s potential as a conceptual tool to solve problems. This qualitative case study research explores the STEM teaching practices carried out by two mathematics vocational high school teachers. Further exploration seeks to investigate how is mathematics playing a role in the STEM project they are carrying. Data were collected through documents and media analysis (lesson plans, students’ work, photos, and video) and interview with teachers. The findings showed that both teachers chose to implement the embedded-STEM approach in their first time STEM teaching experience. They used mathematics to facilitate students’ problem-solving, mathematics modelling, and reasoning in the STEM project. The teachers had different practices and perspectives in designing, implementing, and assessing embedded-STEM mathematics classrooms. The contribution of this research is to provide practical cases of embedded-STEM mathematics teaching, which may be relevant as a solution for countries that do not offer a specific STEM curriculum.
STEM partnership for design-based learning in PM 2.5 crisis for high school
Authors: Pimthong P , Kityakarn S , Munprom R , Lertcharoenrit T , Ugsonkid S
Published: August 2021

This collaborative action research aimed to understand how a schoolteacher, science educator, mathematics educator, scientist, and engineer were able to work collaboratively in STEM lessons. All researchers took part in STEM activity through design-based learning in the PM 2.5 crisis for high school students in Bangkok. A content analysis approach was used to analyse how the partnership works together and how STEM integration occurred across activities, such as lesson plans, classroom participation, and reflective journal. The positions and roles of science teachers, science and mathematics educators, scientists, and engineers were addressed. Three themes emerged as critical success factors from the present research, namely students’ learning, STEM integration, and good practices in STEM partnerships. This research suggests proper advance preparation for the members of a STEM partnership.
Analysing thai curriculum indicators on the basis of pisa competencies in science and mathematics
Authors: Yangjeen S , Angboonpong N , Chaiwongsurarit S
Published: August 2021

A great challenge of Thai students becoming quality global citizens considerably depends on an ability of education to provide sufficient knowledge, skills, and attributes, especially, in science and mathematics, to acquire competencies necessary for their lives in 21st century. Unfortunately, Thai students’ competencies in science and mathematics assessed by the Programme for International Student Assessment (PISA) still fall behind other students in several countries. This study analysed Thai Basic Education Core Curriculum indicators based on their relevancy to PISA key competencies in science and mathematics, and the key competencies that the core curriculum focuses on were found. Unfortunately, neither those focused competencies in science nor mathematics resulted in any predominant PISA results. This obviously illustrates that only a well-constructed curriculum cannot ensure quality of student learning, but the core curriculum is also required to be well-understood by teachers, who are responsible for delivering a quality learning to their students. It is anticipated that this study could provide a better understanding for Thai teachers that there is still plenty of rooms for improvement in student learning so that Thai students are well-prepared to confront challenges of the future awaits.
Applying home based STEM activities to promote students learning motivation during Covid-19 pandemic
Authors: Yunita H
Published: August 2021

Education today faces new challenges in implementing learning during the Covid -19 pandemic. A compulsion to keep a distance causes learning to be carried out remotely using online methods. During the distance learning process students undergo more independent learning at home and cannot interact directly with teachers and friends. This condition is one of the causes of the lack of student motivation. Family members are major learning companion during a pandemic who could deal directly with students. So that we need a learning innovation that can empower homes and family members as a primary place for learning during home learning activities. This study aims to promote student motivation during the Covid -19 pandemic by applied a home-based STEM model. This model applied when students make learning media on subject of the earth structure and water layers. This study used a Classroom Action Research approach. Class actions are implemented through two cycles of action. Data collection techniques are obtained through observation, interviews, documentation study, and literature study. The research was carried out on class VII-A within 22 students. The results showed that there was an increase in student motivation after the implementation of home-based STEM learning. This is because students feel challenged and have the freedom to develop ideas in making learning media by making use of existing materials. Student interactions with family members during the learning process also play a role in making learning more enjoyable and promote student learning motivation.
Science teachers’ professional development program for designing stem integrated lesson plan
Authors: Srikoom W
Published: August 2021

With the increasing focus on integrated STEM into classrooms to develop learners to meet the needs of complex societies. Thus, teacher development is required to success that point. In this study, researcher provided STEM- focused professional development ( PD) program to science teachers (n = 104). Then, teachers’ artifacts were examined to display the effects of the PD program through participants’ implementations. Descriptive statistic, STEM lesson plan analysis rubric, which developed in this study and content analysis were used to consolidate the findings. According to interventions and tools, the results indicate that STEM-focused PD supports participants to design varieties of STEM lesson plans, which categorized into five distinguished groups. Moreover, the effective and successful characteristics of professional development designing for integrating STEM into classroom were proposed to be developing guidelines’ principles and the challenges of instructing STEM lesson were pointed out as well.
Extreme cold events reduce the stability of mangrove soil mollusc community biomass in the context of climate impact
Authors: Chen Guogui , Gu Xuan , Liu Yi , Shi Xiaofang , Wang Wenqing , Wang Mao
Published: August 2021

The frequency and intensity of climate extreme events are expected to increase with global warming in the future. Climate extreme events, such as an extreme cold event (ECE) will continue to influence the stability of soil fauna community biomass, since climate changes often cause a shift in community compositions and structures (e.g. biomass). Few studies, however, have addressed the effects of climate extreme events on the stability of soil fauna community biomass. A field investigation was conducted from 2007 to 2010 to assess the influence of an ECE on the biomass stability of the soil mollusc community across four mangrove wetlands (∼450 km) in South China. Distance-decay and time-decay were used to test the spatiotemporal dynamics of the community biomass. Network analysis and null model were performed to detect the importance of competitive interactions in shaping the stability of the soil mollusc community biomass. The ECE reduced the biomass of the soil mollusc community but increased the complexity of the spatiotemporal patterns of the community biomass. The ECE increased divergent temporal succession and spatial segregation in the soil mollusc community biomass, reflecting the spatiotemporal dynamics of the soil mollusc community biomass influenced by the ECE. Importantly, the ECE decreased the biomass stability of the soil mollusc community by an average of 34.17%. An increase in the modularity of an interactive network (by 75%) and a rise in the intensity of species competition were found after the ECE, reflecting that the ECE enhanced the competitive interactions of the soil mollusc community. The changes in the biomass stability of the soil mollusc community potentially impact their ability to provide ecosystem functions and services such as food production and carbon sequestration for humans. In general, these findings provide valuable ecological insights concerning the effects of climate extremes on the stability properties of ecological soil communities, thereby providing potential applications for soil management and predicting climate changes.
Late twentieth century rapid increase in high Asian seasonal snow and glacier-derived streamflow tracked by tree rings of the upper Indus River basin
Authors: Chen Feng , Opała-Owczarek Magdalena , Khan Adam , Zhang Heli , Owczarek Piotr , Chen Youping , Ahmed Moinuddin , Chen Fahu
Published: August 2021

Given the reported increasing trends in high Asian streamflow and rapidly increasing water demand in the Indian subcontinent, it is necessary to understand the long‐term changes and mechanisms of snow- and glacier-melt-driven streamflow in this area. Thus, we have developed a June–July streamflow reconstruction for the upper Indus River watershed located in northern Pakistan. This reconstruction used a temperature-sensitive tree-ring width chronology of Pinus wallichiana, and explained 40.9% of the actual June–July streamflow variance during the common period 1970–2008. The high level of streamflow (1990–2017) exceeds that of any other time and is concurrent with the impact of recent climate warming that has resulted in accelerated glacier retreats across high Asia. The streamflow reconstruction indicated a pronounced reduction in streamflow in the upper Indus River basin during solar minima (Maunder, Dalton, and Damon). Shorter periods (years) of low streamflow in the reconstruction corresponded to major volcanic eruptions. Extreme low and high streamflows were also linked with sea surface temperature. The streamflow reconstruction also provides a long-term context for recent high Asian streamflow variability resulting from seasonal snow and glaciers that is critically needed for water resources management and assessment.
Transformer Order Demand Forecasting Based on Grey Forecasting Model
Authors: Xiao Chuncai , Liao Yumei
Published: August 2021

For a grey system, the known information is not enough to create an accurate physical model. But there are some rules or characteristics about time series in it. According to the grey system theory, the internal law can be found to a certain extent. According to the grey system theory, the order demand of transformer can be predicted. This prediction model overcomes the influence of the nonlinear relationship and random fluctuation of the system on the prediction accuracy. The experimental data also show that the prediction accuracy of the model is good, and the result is ideal. According to the prediction model, the transformer enterprises can adjust the production plan in time to adapt to the market changes and improve the economy of the transformer. At the same time, for the whole transformer market, timely prediction is also conducive to the state’s macro-control of the power industry and promote the development of power construction.
Study on the effect of income distribution on NOx emission reduction in China’s industry: based on threshold regression
Authors: Wang Xiaoshuo
Published: August 2021

This paper uses panel data of 30 provinces in China to study the emission reduction effect of different factors on NOx under different income levels, and focuses on the test of threshold characteristics of each influencing factor based on per capita GDP. The research shows that, on the whole, GDP per capita, population size, energy intensity, industrial structure and environmental regulation intensity have threshold characteristics for NOx emission intensity based on GDP per capita. Therefore, in order to improve NOx emission reduction effectiveness, the government should adopt different regional governance strategies based on the income characteristics of different regions.
Research on key technology of soil erosion control of transmission line project in Hilly Area
Authors: Li Li , Xin Hou Xin , Xiaofeng Chen , Xi Chen , Qian Hong
Published: August 2021

Transmission line engineering is characterized by long distance, scattered disturbance, great difference in natural conditions, various types and intensity of soil and water loss. The design of soil and water conservation measures is the key to the layout of soil and water conservation measures for transmission lines in hilly areas. This paper mainly discusses the land consolidation and slope protection technology. In order to provide reference for the typical design of soil and water conservation measures of power transmission and transformation project in hilly area.
A cost-benefit analysis of fuel-switching vs. use MGO: A CHINA-Europe container route case
Authors: Zhang ZhongHao , Liu Ding
Published: August 2021

With the increasingly strict environmental regulations, the relationship between supply and demand of ships in the post-epidemic era is tense, and ship operators are under tremendous pressure. In view of the existing strict sulfur emission reduction regulations and ship freight operating at high levels in the post-epidemic era, ship operators must choose cost-effective compliance options to create better environmental benefits. This study uses a cost-effective framework to analyze ship operations Supplier’s fuel switch and marine natural gasoline compliance options, and apply these options to specific liner routes through China’s SECA. We selected an international freight liner as the research object, and calculated the net present value of the compliance option in consideration of the fuel cost of the ship, the installation and operation and maintenance costs of the compliance option. The study mainly considered the influence of the navigation distance in the emission control area on the proportion of the total navigation distance, and also considered the fuel price difference that has a greater impact on ship operating costs. Our results show that in the post-epidemic era, in accordance with the requirements of environmental protection regulations, considering the ratio of SECA and the price difference between MGO and high-sulfur fuels, the use of fuel conversion is a necessary option. We also calculated the emissions of ships, and the results show that with the expansion of the emission control area, the use of MGO can achieve better emission reduction effects. Our results show that in the post-epidemic era, Considering the ratio of SECA and the price difference between low-sulfur and high-sulfur fuels, fuel conversion is the best option. We also calculated the emissions of ships, and the results show that with the expansion of the emission control area, the use of MGO oil can achieve better emission reduction effects.
Correlation of Energy Transition and Coordinated Development in the Beijing-Tianjin-Hebei (BTH) Region
Authors: Huang Ren , Chu Wenjia , Zhang Sufang
Published: August 2021

Due to the serious air pollution problem since 2012 in the Beijing-Tianjin-Hebei (BTH) region, the Chinese government launched the national strategy of the BTH Coordinated Development (the BTHCD). Meanwhile, energy transition is also a national strategy in the region. What is the relationship between these two strategies, and in particular how can energy transition serve BTHCD strategy? Firstly, the paper identifies the three main areas of the BTHCD strategy, namely, transportation integration, industrial upgrading and transfer, and ecological and environmental protection, and finds that the ultimate goals of the strategy are to promote economic growth and environment protection in the region. Then, an empirical study is conducted by using the BVAR model, which further shows the that energy transition and BTHCD are closely related. Finally, policy recommendations are made for enabling an energy transition that supports the BTHCD.
Overview of the Application of Energy Consumption Forecast Models in Energy Efficiency Optimization
Authors: Liu Ren , Wang Zhonghang , Chen Haihong , Yang Jie
Published: August 2021

Energy consumption analysis, and energy demand forecasting and energy conservation effect evaluation based on such analysis are important bases for energy efficiency management. The wide application of AI machine learning methods in energy consumption forecasting not only expands the research route of energy consumption forecasting, but also provides a new perspective for energy efficiency optimization. The purpose of this article is to summarize the important applications of AI machine learning methods in the research of energy consumption forecasting-data-driven models and traditional forward models, and the comparison and application of the two types of models, and conclude the common application scenarios and technical routes of forecast models in the research of energy efficiency optimization so as to provide comprehensive model methods, application scenarios, forecast conditions and other multi-dimensional bases for energy consumption forecasting researchers. On this basis, the research questions and development needs in the research of energy consumption forecasting at the application and basic levels are raised herein.
Research on the evaluation index system of “new energy cloud” operation mode based on CRITIC weighting method and AHP method
Authors: Wang Xingang , Zhou Zhuan , Sun Licheng , Xie Guohui , Lou Qihe
Published: August 2021

Accelerating the development of new energy is an inevitable trend of the energy low-carbon transition. Information technology means and new energy and new energy business management are combined by most energy enterprises, so as to further improve the coordination of source, network and storage load in the development of new energy, solve the problem of new energy consumption, and improve the management efficiency. This study takes the “new energy cloud” platform of State Grid Corporation of China as the research object. Firstly, the basic architecture and operation mode of the cloud platform is analyzed; secondly, according to the characteristics of the operation mode, the evaluation index system of the “new energy cloud” operation mode is constructed from four dimensions of business, capital, learning and growth, and data. At the same time, the actual data of nine provinces that have deployed the “new energy cloud” platform are selected, and the weight of the evaluation index is determined by using the CRITIC—AHP method. This study can provide a model reference for related energy enterprises to build new energy business management platforms, and provide a practical reference for the evaluation of new energy business operation mode.
Comparative Analysis of Typical Grab Knots Force Test in Rope Rescue
Authors: Zhang Yuhai , Li Jianfeng , He Zhongquan , Cheng Jianxin , Tan Zhiyong , Liu Liwen
Published: August 2021

Fire rescue is all-weather and all-time. Using rope rescue technology to carry out rescue operations is one of the efficient and convenient methods adopted by firefighters. Grab knots are an important part of this field. This article introduces typical grab knots such as Prusik knot, French knot, Klemheist knot and uses 10.5mm and 12.5mm as main ropes, 6mm, 7mm and 8mm as auxiliary ropes and related equipments in rope rescue to carry out parallel tests by using tensile testing machine. It can be found that the larger the diameter of rope, the greater the maximum tensile force the grab knot will bear. The larger the diameter difference between the main rope and auxiliary rope, the smaller the sliding distance is, and the force effect can be better. Those three types of grab knots have different characteristics and should be selected according to the actual situation. Relatively speaking, the Prusik knot is more suitable for fire rescue. It is hoped that it will help to improve the firefighters’ understanding of typical grab knots, and play a certain reference value for the safety assessment, so as to ensure the scientific and safety of rescue operations.