bluuebunny/crossref_metadata_2025 huggingface dataset:
Combinatory Least Slack and Kuhn Tucker Optimization for Multiobjective Flexible Job Shop Scheduling
Authors: Hemamalini T. , Geetha G.
Published: August 2021

The Multi-objective Flexible Job Shop Scheduling (MFJSS) problem, in which the order or processing sequence for a set of jobs through several machines is assigned in an optimal patterns have accepted sizeable attentiveness. Different types of scheduling rules and procedures for certain types of MFJSS have made progress from these endeavors. The scheduling problem is cumbersome to be made consistent due to different types of criteria involved. This is because in MFJSS, after the completion of a job on a machine, it may be transited between different machines and transit time may affect scheduling. However, the transit times are frequently ignored in the literature. In this paper, the transit time and the processing time are considered as the independent time into the MFJSS. In this paper, we propose Combinatory Least Slack and Kuhn Tucker Optimization (CLS-KTO) for the MFJSS problem with the objectives to minimize the mean tardiness, makespan and job completion time. The problem is addressed via assignment and scheduling model. First, by using well-designed processing and transit time and least slack variable, Combinatory Least Slack (CLS) algorithm is adapted for the CLS-KTO. Then, an Additive function is formulated by incorporating Combinatory Dispatching Rules into the adapted CLS, where some good machines are assigned for the corresponding job, therefore reducing mean tardiness. Furthermore, in the proposed sequencing part, an optimization model based on the Kuhn Tucker conditions and Lagrange Multiplier is adopted to handle the three objectives. In the experimental studies, the influence of mean tardiness on the performance of the proposed CLS-KTO is first examined. Afterwards, the effectiveness of makespan and job completion time in CLS-KTO is verified. Finally, extensive comparisons are carried out with the state-of-the-art methods for the MFJSSon benchmark OR instances. The results show that CLS-KTO performs better than other algorithms.
Study on reuse of grey water – A Review
Authors: Anuja J , Darshan B , Saraswathi G , Meyyappan N
Published: August 2021

Water scarcity is a huge problem and is been consistently increasing every year. Many of the water systems that keep ecosystems flourishing and feed a growing human population became stressed. Ocean, river, lake, streams are too much polluted. A lot of technologies are available on water recycling. Greywater is around 50% of household water usage but unfailing information relating to both the characteristics of greywater and the variety of recycling technologies are not available. In this review paper we have discussed the relative merits of different options available in greywater recycling and viability of onsite recycling systems.
Bioconversion of Food Waste with Cosubstrate to Electricity using Microbial Fuel Cell
Authors: Sambavi S.M. , Vishali S. , Asthika M. , Sriraaman M. , Mullai P.
Published: August 2021

Bioelectricity generation from canteen based food waste in microbial fuel cell (MFC) is an interesting alternative energy producing technology. In this research work, an equal proportion of confectionery wastewater and hostel food waste was homogenised and used as substrate. Agar salt bridge was used as proton exchange membrane (PEM). At the end of 212th h of the experiment, the COD concentration decreased to 2800 mg COD/L with the COD removal efficiency of 85.86 %. A maximum potential of 2250 mV and current of 22.50 mA with external resistance of 100Ω at the end of 65th hour was generated.
An Effective Analysis of Data Clustering using Distance-based K- Means Algorithm
Authors: Ramkumar P. , Kalamani P. , Valarmathi C. , Sheela Devi M.
Published: August 2021

Real-world data sets are regularly provides different and complementary features of information in an unsupervised way. Different types of algorithms have been proposed recently in the genre of cluster analysis. It is arduous to the user to determine well in advance which algorithm would be the most suitable for a given dataset. Techniques with respect to graphs are provides excellent results for this task. However, the existing techniques are easily vulnerable to outliers and noises with limited idea about edges comprised in the tree to divide a dataset. Thus, in some fields, the necessacity for better clustering algorithms it uses robust and dynamic methods to improve and simplify the entire process of data clustering has become an important research field. In this paper, a novel distance-based clustering algorithm called the entropic distance based K-means clustering algorithm (EDBK) is proposed to eradicate the outliers in effective way. This algorithm depends on the entropic distance between attributes of data points and some basic mathematical statistics operations. In this work, experiments are carry out using UCI datasets showed that EDBK method which outperforms the existing methods such as Artificial Bee Colony (ABC), k-means.
Review Paper on Development of Mobile Wireless Technology
Authors: Kumar Pardeep , Sumit
Published: August 2021

Wireless technology these days is very quickly becoming crescent. A network that was recently wired to get online was required. Just wired phones have been a thing of the past. In the past four decades, mobile networks have thrived immensely. The starting point was the 1G cellular concept where ‘G’ stances for generation linkages. This had fully developed very rapidly, generating 1G, 2G, 3G and gradually transferring into 4G from generation to generation. And now people are utilizing the 4G networks. 5G network will nearly stretch its wings to conquer this complex world of cell technology. Integrated 5G work is continuing, with complete service planned in 2020. The development of 5G technology is the perfect solution for the many problems facing us today with today’s innovations. 5G will become an intelligent technology that will limit to a single global uniform body the number of different innovations. This paper is mostly about the evolution of mobile wireless networks like 1G and 5G as well as how they vary and their benefits and drawbacks.
Securing VANET Using Blockchain Technology
Authors: Ravi Nikhil , Verma Sahil , Kavita  , Jhanjhi NZ , Talib M N
Published: August 2021

VANET permits communication from V2V or in this specific communication which is generated by the vehicle. Because of this to a broad range of technologies and facilities, like protection for travelers, improved traffic capacity, and infotainment, It’s has been closely researched. In this paper, we implement the algorithm for security while rewarded will be added to the client. we also analyze the VANET through the blockchain technologies and IOV with blockchain. IOV has improved traffic safety. A period now is ripening for paving the way for a new wave of autonomous cars with modern technologies and creative protection initiatives by integrating smart cars on the Internet of Vehicles (IoV).
A Comprehensive Survey on Load and Resources Management Techniques in the Homogeneous and Heterogeneous Cloud Environment
Authors: Kaur Ramanpreet , Verma Sahil , Kavita  , Jhanjhi NZ , Talib M N
Published: August 2021

Resource scheduling is a challenging job in multi-cloud environments. The multi-cloud technology attracted much research to work on it and look forward to solving the problems of vendors lock-in, reliability, interoperability, etc. The uncertainty in the multi-cloud environments with heterogeneous user demands made it a challenging job to dispense the resources on demand of the user. Researchers still focused on predicting efficient optimized resource allocation management from the existing resource allocation policies in multi-cloud environments. The research aims to provide a broad systematic literature analysis of resource management in the area of multi-cloud environments. The numbers of optimization techniques have been discussed among the open issues and future challenges in consideration due to flexibility and reliability in present environments. To analyses the literature work, it is necessary to cover the existing homogenous/heterogeneous user demands and cloud applications, and algorithms to manage it in multi-clouds. In this paper, we present the definition and classification of resource allocation techniques in multi-clouds and generalized taxonomy for resource management in cloud environments. In the last, we explore the open challenges and future directions of resource management in a multi-cloud environment.
Accurate Detection of Multi-layer Packet Dropping Attacks Using Distributed Mobile Agents in MANET
Authors: Boopathi Mythili , Seetha R.
Published: August 2021

Detecting multi-layer packet drop attacks may result in extraordinary computational overhead in Mobile Ad Hoc Networks (MANET). Most of the existing works consider only data packet drop ignoring the routing packets drops. In this paper, a technique for accurate detection of malicious multi-layer packet drop attacks using mobile agents (MPDDMA) is proposed. In this technique, mobile agents are deployed in each node to detect selective dropping of routing and data packets by the malicious nodes. The source node identities the nodes whose route request and route reply count significantly differs from others by a margin. Similarly, the source node identifies the nodes whose packet received count significantly differs from others by another margin. The source then applies Fuzzy logic decision model with these margin values and MAC layer packet drop value as input variables and returns the output as probability of maliciousness (PrM). Experimental results show that MPDDMA technique achieves better detection accuracy and reduced packet drops.
Optimization Of Adsorption Of Congo Red By Corn Cob Powder Using Support Vector Machine
Authors: Murugeswari R. , Kannan R. , Ananthakumar K.
Published: August 2021

Escalating environmental information is compelling waste initiators to bear in mind new alternatives like adsorption for the removal of dye in tinted waste water. Owing to outstanding expenses of commercially activated carbon (CAC), inexpensive adsorbent with high adsorption capacity have achieved growing consideration. The current study offers with exploitation of an inexpensive, waste adsorbent material of corn cob powder and enhancing the situations for removing the Congo red dye from an aqueous solution with the help of central composite design (CCD) experiment. UV-Visible Spectrophotometer is applied to establish the concentration of dye within the waste water. The surface uptake capability (SUC) of corn cob powder will increase when the initial concentration of dye, contact time and temperature becomes increased. The SUC decreases with increase in measure of adsorbent and pH level of the medium. Support Vector Machine (SVM) employing central composite design turned into used at the required mixtures of five self determining factors (dye attention, adsorbent dosage, contact time, pH and temperature). By using these subsequent circumstances, dye concentration 80 mg/L, adsorbent dosage 0.05 g/L, contact time 15 min, pH 7.0 and temperature 300C, we have achieved the maximum level of adsorption capacity as 50.0 mg/g. This research procedure will take long time to analyze and it is prolonged manner. But growing pollutants will motive severe harm to the environment. So it’s miles vital to pick out on fastest answer for this problem. In this proposed approach a Support Vector Machine based online solution is achieved for eliminating the Congo red dye from the aqueous solution. The SVM expected SUC is as compared with an experimental result. The accuracy of the proposed SVM Model has been predicted by the simulation result. The study specifies the corn cob powder becomes efficient and also an inexpensive opportunity for removing the Congo red dye.
Classification of Admission Data Using Classification Learner Toolbox
Authors: Senthamil Selvi M. , Jansi Rani S.
Published: August 2021

The analysis of data useful for further process and find the usefulness for the futher. In education sector, Admission is hottest topic. For the counselling of the admission in reputed institution or foreign university, the past data of the person are taken into the consideration. In this Paper, Admission data taken from the reputed Website (Dataset Weblink) and conduct the study of classification methods like Naïve bayes and its accuracy using Matlab. The performance of different classification methods from MATLAB classifier learner toolbox for admission data. Finally, the paper choosen the suitable classification method for the admission data set.
Privacy Preserving On Remote Sensing Data Using Reversible Data Hiding
Authors: Saravanan K , Suganthi K , Kalaiselvi R , Divya B , Dilip Kumar S
Published: August 2021

The method of steganography covers message in the cover file and forms a stego file. Imagery needs a method that will boost protection, minimise distortion in the stego file and recover data without failure. There is a need for reducing transmitting time in the age of multimedia and the Internet. The main purpose of this project is to create safe contact between the sender and the recipient through emails and other modes of communication. A reversible data hiding algorithm was proposed in the integer wavelet transformation (IWT) domain to resolve the image distortion problem. This strategy aims to incorporate data into IWT coefficients of higher frequencies. After wavelet coefficients are collected by converting the integer wavelet data into high-frequency subbands HL, LH and HH, the human eyes would have fewer recognisable objects. After data is incorporated in such IWT coefficients, reverse integral wavelet transformation can occur following application. The stegno image was further encrypted by using Elliptic Curve Cryptography (ECC). The process of encryption enhances the image security during data transmission. In our proposed work inverse wavelet transformation (IWT) and Elliptic Curve Cryptography (ECC) algorithms are effectively utilized to achieve highly secure communication.
A Novel Coplanar Based Adder Logic Design Using QCA
Authors: Navaneetha Velammal M , Hannah Blessy P , Friska J , Rajeshwari A
Published: August 2021

Now a days, VLSI is a one of the top most technology are used in the field of electronics communication. It is used to create an integrated circuit by merging million of MOS transistor into a single chip. In VLSI, most of the transistors are design in micro scale level. Now a days people will want all materials are in compact size. So, it is necessary to design a circuit in nanoscale level. In the field of VLSI, CMOS technologies are used for designing a integrated circuit (IC) chips. But in CMOS, size that are used to designing a circuit is in micro scale level. So researcher is introducing new nanotechnology that new technology is called QCA technology. Logic function gate is a one of the fundamental components to design an any circuit in electronics communication. In this paper, novel coplanar approach to designing an efficient QCA based 4-bit full adder using XOR/XNOR logic gate is proposed. QCA Designer Version 2.0.3 simulation tools are used in this proposed method. Performance is analysed and verified to determine the capabilities of proposed full adder.
Enhanced Deep Learning Approach For IoT Enabled Sensitive Clinical Data Analytics
Authors: Mohamed Aslam M A , Kalaimani Shanmugam E V R M , Dilip Kumar S
Published: August 2021

With the enormous upgrade of clinical sensors, it has acquired developing interest to investigate the Healthcare Internet of Things (H-IoT) because of its wide relevance for wellbeing of patient. Current medical services are providing only a limited significance with the emergence of a new strain Covid-19. People are dealing with an issue of unforeseen demise because of different ailment which is a direct result of absence of clinical consideration to the patients at perfect time. Hence in this situation, an IoT based smart healthcare checking framework is necessary during this pandemic. In this paper, an enhanced deep learning framework is proposed that efficiently deep belief network perform IoT-enabled clinical data analytics. The proposed framework is utilized to PIMA Indian physiological parameter dataset quantify to the actual boundaries like internal heat level, heart beat rate, and oxygen level checking with the assistance of sensors. The proposed framework involves the secured cloud infrastructure where the clinical sensor data are acquired and stored. For secured cloud storage and to provide an improved security, Improved Elliptic Curve Cryptography (IECC) algorithm utilized set up a transfer a medical records trust between the doctors and patients centralised repository trailed by enabling a typical session key for communication. The proposed solution automatically predicts any abnormalities exist in the patient and it is communicated to the medical experts for disease diagnosis and appropriate medical consultancy is provided for the patient through secured channel. The proposed framework is deployed in real-time environment for remote healthcare especially in rural area.
Random Forest (RF) based identification of rice powder mixture using terahertz spectroscopy
Authors: Friska J , Navaneetha Velammal M , Rajeshwari A , Hannah Blessy P
Published: August 2021

Adulteration is a severe problem in agriculture field. It may cause some dishonest traders in the marketing side. For their own wish, dishonest traders make adulteration products for higher profit. In consumer side, agro product adulterations provide some unhealthy situation. It may cause severe health problem and also some incurable disease. Its right time, need to find an adulteration various level of agro products. For detecting rice adulteration, to collect spectral data for mixed rice powder (low quality rice powder and high quality rice powder), and a Fast Independent Component Analysis (FICA) algorithm is used to extract valuable information. Then, apply Random Forest Classifier algorithm for classifying purpose, whether the mixture is low quality or high quality. It achieves high accuracy with a single model and also easy to implement.
Smart Urban Water Quality Prediction System Using Machine Learning
Authors: J Bharath Singh , S Nirmitha , S S Kaviya
Published: August 2021

The World Health Organization says that every year more than 3.4 million people die as a result of water-related diseases. Quality of water serves as a powerful environmental determinant and a foundation for the prevention and control of waterborne diseases. The project aims to design a water quality prediction system using Machine learning based on the water standards suggested by BIS to prevent deaths due to water related diseases. The quality is predicted based on parameters such as pH, Temperature, TDS, Turbidity and Conductivity value. The dataset is preprocessed and split into test and training data. The data is fed into regression algorithm and been evaluated. Sensors that can measure the water parameters are also been implemented. A webpage interfaced with the Machine Learning model is created to upload sensor values and the corresponding water quality is predicted. This project can be used in urban areas to predict the quality of the drinking water thereby preventing the spread of diseases such as dysentery, typhoid and cholera due to consumption of contaminated water.
Effective fault detection approach for cloud computing
Authors: Ashritha Pola , Banusri M , Namitha R , Shiny Duela J
Published: August 2021

In cloud computing, accessibility to data anytime is crucial, acquiring data and maintaining that data without any loss or incursion is an essential task. A cloud service must have the potential to recognize unexpected faults and respond effectively. Hence, a system to identify faults is developed which recognizes anomalies using various techniques and algorithms. Several different types of faults occur in cloud computing which causes the poor performance of cloud computing. The various types of faults occurred are collected and classified using a fuzzy one class support vector machine and long short term memory(LSTM) algorithm. Comparative analysis of accuracy and precision is done with various algorithms like Naive Baye Algorithm, Decision Tree Algorithm, K-Neighbors Algorithm, and Logistic Regression Algorithm. Experimental results show that Logistic regression gives the best accuracy, precision and performance for detecting faults among the aforementioned algorithms. The efficacy of our model is illustrated in experimental results.
BAT algorithm based MPPT technique for bidirectional converter in photovoltaic system under partial shading condition
Authors: Ishwarya S , Janani D , Shadika R , Sureka M
Published: August 2021

A photovoltaic cell is related in nursing device. It converts energy of sunbeams directly into electricity by electrical process impact. Electrical phenomenon system could be a device that converts alternative energy into current. Partial shading has high affect on photovoltaic system. Photovoltaic system generates electrical power which relies on solar irradiance. The photovoltaic system is always affected by the partial shaded system. So that, the maximum power cannot be obtained easily. Some effects on photovoltaic system by partial shading are air, trees shadow, thunders. However, some techniques to find maximum power are PSO, P&L, FL and ANN. Maximum power point is tracked by BAT algorithm. Because, it is swarm intelligence based method. In the global optimization BAT algorithm has high accuracy, and good dynamic performance. It has quick convergence rate. In addition to BAT algorithm, bidirectional converter is used. A bidirectional converter allows power in both reverse and forward direction. It is capable of performing both step-up and step-down functions and it also performs continuous power flow in the circuit. By using BAT algorithm and bidirectional converter, maximum power can be tracked and output can be improved.
Plagiarism Detection through Data Mining Techniques
Authors: Nennuri Rajashekar , Geetha Yadav M , Samhitha M , Sandeep Kumar S , Roshini G
Published: August 2021

Plagiarism is a problem that is becoming more prevalent as technology advances and the use of computer systems grows in comparison to previous generations. Plagiarism is the unauthorized use of another person’s work. Since manual plagiarism detection is difficult, this method should be automated. Plagiarism detection can be done using a variety of methods. Some of the research focuses on intrinsic plagiarism, while others focus on extrinsic plagiarism. Data mining is an area that can assist in both detecting plagiarism and improving the reliability of the operation. Plagiarism can be detected using a variety of data mining techniques. Text mining, clustering, bi-grams, tri-grams, and n-grams are some of the techniques that can assist with this. In this paper we will use the data mining techniques to increase the efficiency of detection of plagiarism.
Preface
Authors: Vergel-Ortega M , Rincón Leal O L , Dueñas Ramírez L M
Published: August 2021

V International Meeting of Mathematical Education

The objective of the V International Meeting on Mathematics Education (V IMME) is to create and maintain a space that privileges and promotes the culture of mathematics, reflection and discussion on the education and application of mathematics, statistics, its history, evolution and didactics, and its interrelation with the sciences. At the meeting, researchers, scientists, and mathematics teachers socialize the results of research, consolidate networks for the exchange of successful experiences, to strengthen mathematics education at different educational levels, promote innovation and encourage the creation of policies, models, educational strategies, tools, and techniques in various areas of mathematics. They also promote innovation and encourage the creation of policies, models, educational strategies, tools and techniques in different areas of knowledge, and foster students' interest in research.

V International Meeting of Mathematical Education, Organizing Committee, International Scientist Committee, International Scientific Committee, Invited Speakers are available in this pdf.
Applications of linear algebra to the study of mathematical modelling of the physical phenomena of heat conduction by electricity
Authors: Nolasco Serna C , Afanador Garcia N , Guerrero Gómez G
Published: August 2021

The study of the phenomenon of electrical conduction has its origin in two historical antecedents, Fourier’s law and Maxwell’s equations. The mathematical formulation of electrical conduction has been extensively studied and the differential equations describing the phenomenon are known. The mathematical solution of the physical model of electrical conduction employs different techniques, the best known of which are the Fourier series, Grenn functions and Bessel equations. The purpose of this research is to present a model of heat conduction with the use of electric current that dissipates heat by convection. The research proposes a method for solving the mathematical model associated with the conduction phenomenon using linear algebra. The advantage of using linear algebra will allow to establish a step-by-step procedure that could be used to study phenomena related to heat conduction, in addition to allowing its implementation through programming. In order to establish the fit of the method derived from linear algebra, the analytical solution and the solution proposed in the research were compared to verify that the proposed method fits with a small error.
Detection of water leaks with Dowsing technique and Reynold’s transport theorem
Authors: Pérez-Carrascal K , García-Guarín J
Published: August 2021

Zahorí techniques are traditionally used to detect water currents in land for subsequent extraction. On the other hand, water leaks represent economic losses in factories and residences. It is enough to survey a city and determine the exaggerated number of residential leaks. Once the leak appears, a corrective action must be taken, this action is founded in itself and in the problems derived from this failure; and it is that knowing the exact location of a leak is risky if strictly collateral damage appears in the property. This research proposes to complement two different techniques, the first detects the presence of water based on the Dowsing search, and the second uses the Reynolds Transport Theorem to detect the leak relying on numerical methods and computational simulation. The Dowsing search proved to be reliable to detect the presence of water, the Reynolds Transport Theorem, yields the location of the leak with an average relative error of 10.6727% and the computational simulation corroborates Darcy’s Law. Therefore, the method proposed in this investigation is sufficient for the corrective management of leaks.
Teaching physics through the implementation of a didactic strategy for the integration of knowledge in secondary school students
Authors: Prada Nuñez R , Hernández C A , Gamboa A A
Published: August 2021

The objective was to evaluate the implementation of the knowledge integration model in high school students studying physics in a public educational institution in the city of San José de Cúcuta, Colombia. A quasi-experimental model was applied. An intervention was implemented as a didactic strategy for the integration of knowledge based on the Pragmatic Pedagogical Principles, its operative criteria, and activities. Conceptual progress is reported by means of Hake’s normalized factor or gain, which was modified to the rating scales, and the results of partial exams are considered, implementing a continuous and formative evaluation system. The results were compared between the experimental and control groups. It was found that the experimental group showed better academic achievement and performance than the control group. This suggests that the results generated a continuous learning progress thanks to the application of the operative judgments of the corresponding principles.
Analysis of variables related to the mass flow of gaseous emissions in beehive ovens
Authors: Mendoza–Lizcano S M , Palacios–Alvarado W , Medina–Delgado B
Published: August 2021

In the combustion processes of the ceramic industry, large amounts of pollutant gas concentration are generated, so it is necessary to measure the system and the physical phenomenon, as well as the variables inherent to the process, for subsequent estimation in terms of physical magnitudes, and a dimensional analysis, this allows to generate approximations in the causal relationships of the variables. The objective of the research is to analyze the behavior of the variables involved in the process and the influence of the mass flows of polluting gases. An exploratory and experimental methodology was used, for this, the data were taken with the technique of direct measurement in the sources of gas emissions and subsequently subjected to simulation in software such as AMOS V24.0 and LISREL V8.8., on the other hand, the data were subjected to an exploratory and confirmatory factorial analysis, using SPSS software version 24.0. As a result, the variables capacity and production are practically identical, which leads to a high correlation and, consequently, an undesired multicollinearity between the variables, so the suggestion is to omit one of them. On the other hand, the sulfur percentage variable is inversely correlated with most of the variables and its saturation is not clear, so it is theoretically sustained as a latent variable of the SO2 indicator.
A mathematical model for the simulation of the Magdalena River in the city of Barrancabermeja, Colombia
Authors: Cely-Calixto N J , Bonilla-Granados C A , Carrillo Soto G A
Published: August 2021

The integration of mathematical models allows the simulation of the spatiotemporal behavior of water quality parameters of a river. The representation of reality and different scenarios through simulation makes it possible to know the variations in water quality of a receiving water source associated with liquid discharges. Therefore, for this study, the mathematical model QUAL2K was applied to simulate the water quality of the Magdalena River in the section that crosses the city of Barrancabermeja, Colombia. For this purpose, a database of hydro-climatological records from 1977 to 2020 was used. Among the analyses, dissolved oxygen and biochemical oxygen demand were considered as water quality parameters. As a result of the initial data processing of the distribution tests and Kolmogorov goodness of fit, the best fit with the normal distribution was obtained for the estimation of flow rates. The concentrations of the water quality parameters dissolved oxygen and biochemical oxygen demand were represented in the mathematical model, which shows the dilution capacity of the pollutant loads of the wastewater, due to the high flow of the Magdalena River in the study section.
Relevance of the use of measurement units and orders of magnitude in the training of civil engineers
Authors: Márquez Peñaranda J F , Cáceres Rubio J R , Pineda Rodríguez J R
Published: August 2021

Worldwide, a typical civil engineering program focuses in formal, natural, and applied sciences within an environment of ethical and social responsibility. Mathematics and computer sciences are the main formal sciences. The most widely used natural sciences are physics, earth science, and chemistry. On the other hand, a student who begins the professional cycle of the program must develop skills in applied science to solve practical problems. Complex processes and concepts requiring skills related to mathematics and physics must be developed. Such processes and concepts demand an impeccable handling of operations which involve diverse precision degrees, measurement units and a high variety of basic and derived quantities. This work describes the identification and classification of the main errors made by students when solving written exams applied in a natural environment of structural design courses. Data were collected during four years at a university in Colombia. Report of errors was grouped into five categories named modelling, quantities, regulation, signs, and others. Collected errors were evaluated qualitatively and quantitatively. In addition, each error was assigned to a risk level (high, intermediate, low) according to its potentiality to generate catastrophic errors in professional practice. The quality and number of observed errors seem to be correlated with the time of year in which they occur. On the other hand, the high-risk errors resulted to outweigh the two lower risk levels. This finding is worrying and serves as the basis for making an urgent call to review the way of teaching and its relationship with practical results. In synthesis, this study presents a novel manner to study the formation errors in engineering civil programs. In the near future, it is expected to use the results of this research to propose a procedure for the design and feedback of teaching strategies consistent with the evaluation objectives of each course.
The rubric as an assessment tool for solving problem situations in the physics and mathematics teaching context
Authors: Salazar-Torres J , Rincón Leal O , Vergel Ortega M
Published: August 2021

Polya propose the didactic problem-solving strategy to strengthen the teaching and learning processes in the mathematic field. Thus, this strategy can be applied in other fields such as physics teaching the article proposes an evaluation strategy based on the design of a rubric to assess the processes associated with solving mathematical problems, as a classroom research work based on Research, Pedagogical Action. As one of the results, an analytical rubric composed of criteria and indicators associated with the steps of Polya problem solving is proposed, as well as a reflection associated with the teaching of problem solving in the engineering area.
Climate change, riverine flood risk and adaptation for the conterminous United States
Authors: Wobus Cameron , Porter Jeremy , Lorie Mark , Martinich Jeremy , Bash Rachel
Published: August 2021

Riverine floods are among the most costly natural disasters in the United States, and floods are generally projected to increase in frequency and magnitude with climate change. Faced with these increasing risks, improved information is needed to direct limited resources toward the most cost-effective adaptation actions available. Here we leverage a newly available flood risk dataset for residential properties in the conterminous United States to calculate expected annual damages to residential structures from inland/riverine flooding at a property-level; the cost of property-level adaptations to protect against future flood risk; and the benefits of those adaptation investments assuming both static and changing climate conditions. Our modeling projects that in the absence of adaptation, nationwide damages from riverine flooding will increase by 20%–30% under high levels of warming. Floodproofing, elevation and property acquisition can each be cost-effective adaptations in certain situations, depending on the desired return on investment (i.e. benefit cost ratio), the discount rate, and the assumed rate of climate change. Incorporation of climate change into the benefit-cost calculation increases the number of properties meeting any specified benefit-cost threshold, as today’s investments protect against an increasing frequency of future floods. However, because future expected damages are discounted relative to present-day, the adaptation decisions made based on a static climate assumption are very similar to the decisions made when climate change is considered. If the goal is to optimize adaptation decision making, a focus on quantifying present-day flood risk is therefore at least as important as understanding how those risks might change under a warming climate.
Analysis of Air Pollutions’ Effects on Chinese Children, Adolescents, and Young Adults
Authors: Zhang Muqing
Published: August 2021

In recent years, air pollution in China is becoming more and more serious. Due to air pollution, people were forced to wear masks on streets and some schools even suspended their classes. Many researches had proved that air pollution will cause severe damages to human health. This research focused on reviewing the previous studies on the air pollution’s effects on Chinese children, adolescents, & young adults (the target population), and tried to provide suggestions for future research. The previous researches conducted on this topic were searched on cnki.net and Pubmed and collected. The obtained papers are selected and analyzed. It can be concluded that air pollution had huge effects on the target population’s respiratory system, cardiovascular system, and mental state.
Industry Chain and Technology Trends in China’s Solid-state Battery Industry
Authors: Zhang Lei , Liu Yingqi , Pang Beibei
Published: August 2021

Solid-state battery is different from traditional lithium-ion battery, which is a kind of battery using solid electrode and solid electrolyte, and it has the advantages of high safety, long life, high charging and discharging efficiency, good high temperature resistance, simple assembly and processing, and easy to scale up. This paper first analyzes the industrial chain of solid-state batteries in China and the stakeholders in the process of industrial development, and finally draws a technology roadmap for the development of China’s solid-state battery industry based on industrial characteristics. In the future, along with energy transformation and national policy support, the focus should be on solid state electrolytes for solid state batteries, and gradually realize the development path of solid state battery electrolytes from liquid state of traditional lithium-ion batteries to solid-liquid hybrid, gel, solid state, and all-solid state.
Extreme-rainfall Data as a Basis for Landslide Warnings: a Case Study of a Road in Central Taiwan
Authors: Lin Ji-Yuan , Chao Jen-Chih , Wu Cheng-Lin , Hsieh Wei-Fang
Published: August 2021

In recent years, an increase in extreme rainfall events linked to global warming has led to increases in the number and intensity of disasters such as landslides, landslips, and debris flows in Taiwan. This study focuses on the impact of such events, especially during typhoons, on County Road 89: the main traffic artery in Renai Township, Nantou County. Specifically, it will use an inverse distance weighting method (IDW) to analyze how rainfall at the four rainfall stations in Nantou, located at Renai, Ruiyan, Cuiluan and Cuihua, may related to damage events at the 12.3k, 22.53k, 32.5k, 46.3k, and 49k points on County Road 89. Then, landslide road-damage warning ranges will be drawn up using various combinations of data, including cumulative rainfall, maximum rainfall within a 24-hour period, and I-R alert model (I: rainfall intensity, R: cumulative rainfall), with an I-T alert model (I: rainfall intensity, T: rainfall duration) for comparison. This will yield an optimal warning value for the landslide-prone area of the focal road. Finally, data from County Road 89 will be compared against data from the Lishan landslide area, to ascertain whether/how such warning values should differ across geographic areas. The results are expected to usefully inform follow-up disaster prevention planning as well as further academic research on this topic.
Benefits of the Completion of Sofia’s Subway System as Part of Sustainable Urban Mobility
Authors: Tzvetkova S D
Published: August 2021

Over the past several years all European capitals have been dealing with traffic-related problems, the harmful influence of passenger transport on the environment, and the necessity to adopt measures for achieving sustainable urban mobility. The dynamic development of the city of Sofia in recent years has led to an increased number of personal vehicles, air pollution, and the necessity for servicing large passenger flows effectively and relieving traffic in the city’s center. The global practice is to solve urban mobility transport problems in larger cities with a population of over one million by developing a subway system which should become the primary mode of urban passenger transport, securing quick access to work places, guaranteeing high-quality, safe and secure travel, while simultaneously minimizing pollution, greenhouse effects and energy consumption. The purpose of the present article is to substantiate the necessity for finishing the construction of the capital’s subway system, to indicate the social benefits of the functioning of the first and second subway lines in the context of sustainable urban mobility, and to prognosticate the future social benefits of constructing and commissioning the third subway diameter through analysis of the dynamic of the city’s public transport and the available statistical data.
Test of Physical Quality Compost and PH of Combination of Water Hyacinth (Eichornia Crassipes Mart. Solm) and Goat Manure Using Rument Liquid Mol as Activator
Authors: Napoleon A , Sulistyani D P , Bakri
Published: August 2021

Abstract.This study aims to determine the quality of compost from a combination of water hyacinth (Eichornia crassipes Mart. Solm) and Goat Manure. The materials used in the research were goat manure, water hyacinth, and bioactivators. This study used a completely randomized design with 5 treatments and 5 replications consisting of treatment P1 = water hyacinth: goat manure (100%: 0%), P2 = water hyacinth: goat manure (75%: 25%), P3 = water hyacinth: goat manure (50%: 50%), P4 = water hyacinth: goat manure (25%: 75%), P5 = water hyacinth: goat manure (0%: 100%). The parameters measured in the study were physical quality (smell, moisture content, temperature, particle size and color) and pH. From the research results obtained showed that the best ratio of water hyacinth and goat manure was 50 % : 50 % in all parameters, both physical properties and pH is in accordance with SNI 19-7030-2004.
Moler Disease of Shallot in the Last Three Years at Brebes Central Java: The Intensity and Resulting Yields Losses is Increasing
Authors: Supyani  , Poromarto SH , Supriyadi  , Hadiwiyono
Published: August 2021

Shallots are one of the important commodities in Indonesia, and have become a mainstay for farmers in certain areas. This is due to the high economic value, short life, and an average harvest time of only two months. In addition, Brebes district, Central Java is one of the production centers, and farmers here have complained about an increasing disturbance and attacks in recent years. This condition is observed in the form of pathgen Fusarium oxysporum f.sp. cepae, responsible for twisting leaf symptoms, and popularly termed “moler” disease. Moreover, Indonesian references show reports on the predominance from the 1970‘s, with the name “busuk umbi” Fusarium. This disease is attributed by many others as the basal plate rot, and is estimated to be important in various shallot producing countries. The paper reports on the attack state within the last three years were based on a direct survey of farmers in Brebes. This was conducted with 35 respondent farmers at 7 sub-districts of shallot production centers. The results show a gradual increased in disease intensity and the resulting yield loss within the last three years. In addition, moler intensity was higher in the rainy season, and inappropriate cultivation practices are were estimated as one of the important driving factors.
Phytochemical and Antioxidant Analysis of Fermented ‘Dayak’ Wild Yam (Dioscorea hispida Dennst), Purple Yam (Dioscorea alata) and Air Potato (Dioscorea bulbifera L.) Tuber Flour
Authors: Rudito  , Suwarto  , Witono Yuli , Saragih Bernatal , Tangke Arung Enos
Published: August 2021

Tubers of Dioscorea spp. contain many compounds that have physiological activity that can act as antioxidants and are proven to have various health uses. Antioxidant compounds have a very important role in the health of the human body. Various scientific evidence show that antioxidant compounds reduce the risk of various chronic diseases such as cancer and coronary heart disease.The study aimed to determine the phytochemical content and antioxidant activity of fermented Dayak wild yam (Dioscorea hispida Dennts), Purple Yam (Dioscorea alata var. Purpurea) and Air Potato (Dioscorea bulbifera) tubers flour was carried out. Phytochemical testing was carried out by the Harborne method (1987) and antioxidant activity using DPPH (1,1-diphenyl-2-picrylhydrazyl) method. The data obtained were analyzed descriptively from the average value of 3 replications for each parameter. Phytochemical analysis results showed the presence of alkaloids, tannins, triterpenoids and carbohydrates. While the results of the antioxidant activity testing showed that the IC50 value of fermented Dayak wild yam flour (WYF) was 227.43 ppm, air potato tuber flour (APF) was 15.77 ppm and purple yam tuber flour (PYF) was 7.70 ppm. Thus it can be concluded that all three tubers belonging to Dioscorea spp. all of them contain antioxidants with the order of the strength of antioxidant activity sequentially from the strongest to the weakest are PYF, APF and WYF.
Physical and Chemical Quality of Bento Rayap Grass Haylage (Leersia Hexandra) Supplemented with Water Mimmosa (Neptunia Oleracea)
Authors: Riswandi  , Ali A I M , Muhakka  , Imsya A , Abrar A , Sahara E , Hamzah B , Supriadi A , Alpian P
Published: August 2021

The effect of water mimmosa addition on the physical and chemical quality of Bento Rayap grass haylage was evaluated. The haylage material was fermented for 21 days and the physical quality of the resulting product was analyzed through organoleptic test and proximate analysis. Research variables consist of several treatments i.e. A0 (100% Bento Rayap grass), A1 (90% Bento Rayap grass + 10% water mimmosa), A2 (80% Bento Rayap grass + 20% water mimmosa) and A3 (70% Bento Rayap grass + 30% water mimmosa). The parameters observed were (1) physical quality includes color, aroma, texture, fungus and temperature while (2) chemical quality includes dry matter (DM) content, organic matter (OM), crude protein (CP), crude fiber (CF), and acidity (pH). The analysis result shows the addition of water mimmosa improved the physical quality of haylage from Bento grass. Water mimmosa addition also affects the chemical quality of Bento grass haylage confirmed by variance analysis result which gave statistically significant difference (P < 0.05). The property affected were DM, OM, CP, CF and pH. It was concluded that the addition of water mimmosa improved the physical and chemical quality of Bento Rayap grass haylage.
Effect of Flue Gas Oxygen Content to Gas-Gas Heater Requirement in Limestone Forced Oxidation Desulfurizer System
Authors: Reza A M , Heksaprilla A B , Chariri F , Tasyrifah U , Gani M B A , Suwondo P D
Published: August 2021

To comply the regulation, the sulfur dioxide (SO2) concentration should be reduced to designated standard of emission which was stated in the regulation. It causes many coal fired power plant (CFPP) need to procure a new or upgrade their desulfurization equipment. In this study the desulfurization method focused on the usage of Limestone forced oxidation (LSFO). The study is based on subcritical 300 MW CFPP and the specification of coal for the calculation was taken from coal properties of Palu 3 CFPP. There are two cases and two configurations in this study. The first case is flue gas oxygen content of 3.5% and the second is 7%. Then in the configuration of with or without gas-gas heater (GGH). The oxygen content condition in the flue gas have an influence to the presence of GGH within LSFO desulfurizer system. The lower of oxygen content in the flue gas then increase the tendency to use GGH.