bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of Thermodynamics of Adsorption of Cadmium Ions Cd (II) from Model Solutions by Glass Fiber Materials
Authors: Letenkova I V 
Published: September 2021

Abstract
Thermodynamic regularities of the adsorption of cadmium ions Cd (II) using BSTV basalt fiber and M20-STV-2.0 and M20-UTV-0.6 glass fibers are investigated. The adsorption capacity of the investigated fibers with respect to the cadmium ion Cd (II) was determined. The degree of adsorption, values of the distribution coefficient, and adsorption equilibrium constants for the Langmuir and Freundlich models were determined. The adsorption equilibrium for the cadmium ion Cd (II) is well described by the Langmuir model. Thermodynamic characteristics of the process were determined: the change in the Gibbs energy, the change in the enthalpy and entropy of the adsorption process at three temperatures. The change in the Gibbs energy corresponds to the spontaneous occurrence of the adsorption process. A decrease in the change in the Gibbs energy of adsorption in a series of fibrous materials (BSBV basalt fiber–M20-STV-2.0 glass fiber–M20-UTV-0.6 glass fiber) is due to the entropy effect. The adsorption of cadmium ions Cd (II) on glass fiber materials is exothermic. The values of the thermal effects, found by the graphical method in accordance with the isobar equation of the chemical reaction, do not exceed 25 kJ / mol and indicate the physical nature of the process.
Application of Earth Remote Sensing Data in the Practice of Hunting Design
Authors: Lukashik E E 
Published: September 2021

Abstract
According to the strategy for the development of the hunting economy in the Russian Federation until 2030, one of the principles of sustainable and rational hunting use is the monitoring of the resources used and a reliable assessment of the state of their habitat. The solution of modern problems of classification and typological assessment of the habitat of hunting animals is possible using multispectral satellite imagery, reflecting the whole variety of natural landscapes, types of vegetation and other properties of the earth’s surface. The article discusses the features of mapping the habitat of hunting animals using data from remote sensing of the Earth by classifying objects on satellite images according to various criteria corresponding to certain habitats of animals. Methods for interpreting satellite images for determining the categories and classes of the habitat of hunting animals are indicated, the results of a typological assessment of the habitat of hunting animals on the territory of the Priilmensky landscape of the Novgorod region are presented.
Biological Products for Integrated Protection Systems for Greenhouse Vegetables and Ware Potatoes
Authors: Lysov A K , Morozov D O , Naumova N I 
Published: September 2021

Abstract
The article presents research materials on the widespread use of multifunctional biological products against fungal and bacterial pathogens on the main vegetable crops cultivated in greenhouses and on potatoes. For protected ground crops: cucumber, tomato, eggplant, protection systems have been developed that help protect plants from diseases during the entire growing season. The introduction of these systems into production makes it possible to completely reduce or minimize the use of chemical plant protection products on these crops and thereby reduce the negative impact on the environment, as well as improve the quality and safety of crop products. The article presents the main biological products that are included in the potato protection system, including Kartofin, SK and Sternifag, SP.
Organization and improvement of biochemical control of full-fledged feeding of cows
Authors: Semkiv M V 
Published: September 2021

Abstract
The current development of dairy cattle breeding raises an urgent problem of feeding improvement; it concerns the preparation of high-quality feed and diets depending on the physiological state of the animal. While solving this problem, it is necessary to pay special attention to the organization and improvement of biochemical control of full-fledged feeding of cows. This research pays considerable attention to the theoretical component of the topic, namely, it justifies the significance of zootechnic and physiological-biochemical methods used on dairy farms in order to control the completeness of cows feeding. The analytical study is based on the monitoring of biochemical control methods used in the studied farm for the purpose of prompt response to the organization of full-fledged feeding of cows; the recommendations are given on testing biological fluids in real time. The research also touches upon the aspect associated with metabolic disorders, which appears with an imbalance of vital substances in the diet and does not display any symptoms. The long-term influence of unbalanced feeding leads to diseases of animals and, accordingly, to economic damage due to a sharp decrease in milk production, reproductive capacity and other indicators. As a result, the genetic potential of animals is not fully realized. In this regard, it is evidently confirmed that in order to increase the productivity of black-and-white cows, it is necessary to constantly improve and optimize their feeding diets, to monitor the physiological state of animals using biochemical indicators.
Monitoring of Sowing Oats for Disease Infection in the Conditions of the Collective Farm “Russia” Spk of Novgorod Region
Authors: Toshkina E A 
Published: September 2021

Abstract
Phytosanitary diagnostics and phytosanitary expertise are the main stages of the overall phytosanitary monitoring system. The aim of the study was to monitor oats of the seed variety Borrus for disease incidence in the conditions of the collective farm “Russia” SPK of Soletsky district of Novgorod region. According to the results of the research, two main diseases were identified on crops of common oats - red-brown spotting and powdery mildew. The spread and development of these diseases on oat crops was influenced by the prevailing weather conditions of the growing seasons of 2019 and 2020. Based on the monitoring of the phytosanitary diagnostics of crops, the study of the spread and development of diseases, the farm proposed measures to reduce the degree of manifestation and infection of all grain crops, regardless of weather conditions and allowed to improve the quality of grain.
Differentiation of Production of the Regional Agro-Industrial Complex as a Factor in Ensuring the Economic and Social Stability of a Territory
Authors: Vinogradova O N 
Published: September 2021

Abstract
The article presents the results of a study of enterprises in the agro-industrial complex of the Novgorod region. A study of the structure of production of agricultural products was carried out, key directions of development were identified, problem areas were outlined, a number of recommendations were made to improve the processes of development of territorial industries in order to ensure the stability of the socio-economic development of the relevant areas of the region. A comprehensive approach to the development of branches of the regional agro-industrial complex is proposed, based on the differentiation of agricultural production and the improvement of processing and marketing processes. The need for a comprehensive application of advanced achievements of scientific and technological progress and elements of promoting the digital economy to ensure the progressive development of the regional agricultural sector is determined. Conclusions are formulated regarding the importance of the development of the agro-industrial complex as one of the main factors in ensuring not only food security, but also an element of ensuring the economic and social stability of the territory.
The modelling of particulate matter concentration using mass balance model in surface coating activities at finishing room of shipbuilding process
Authors: Santiasih I 
Published: September 2021

Abstract
The surface coating process of shipbuilding produces pollutants in the form of particulate matter (PM10 and PM2,5), potentially generating environmental pollution and respiratory problems in workers. The concentration of indoor particulate matter (PM) can be predicted using mass balance model. This study aims to prove that mass balance can be employed to estimate the concentration of PM. Mass balance is calculated from the concentration of pollutants, inserted into indoor, indoor emission rate, airflow rate and pollutant removal rate. The model estimation results show that PM10 concentrations on the first day, second day, third day and fourth day were 1,22 mg/m3, 1,52 mg/m3, 1,84 mg/m3 and 1,80 mg/m3. While the PM2,5 concentration on the first day, second day, third day and fourth day was 2,67 mg/m3, 3,03 mg/m3, 2,99 mg/m3 and 3,15 mg/m3. The RMSE values on day 1 to day 4 for PM10 were 0.679412, 0.565597, 0.682349, 0,546626, while for PM2.5 are 0,755513, 0,980255, 0,975141 and 1,108106. Giving evidence that mass balance model was reliable that proved by the lower value of RMSE which is generally less than one. It proves that the concentration of PM (PM10 dan PM2,5) is close to actual value of PM concentration from measurement results.
Dynamic time distribution system monitoring on traffic light using image processing and convolutional neural network method
Authors: Rifai M , Budiman R A , Sutrisno I , Khumaidi A , Ardhana V Y P , Rosika H , Tibyani  , Setiyono M , Muhammad F , Rusmin M , Fahrizal A 
Published: September 2021

Abstract
The number of vehicles that continues to increase every time can cause congestion and increase the potential for accidents. One type of violation that often results in accidents is motorists who break through traffic lights when the red light is on. One factor that encourage motorists to not obey traffic light signs is due to the distribution of green time which tends to be fast on relatively dense tracks. This final project aims to get dynamic green light on traffic light according to the volume of the vehicle for each lane using convolutional neural network method and can detect traffic light violations in the form of breaking the stop line markings on zebra cross. The sensor used is camera. There are three cameras used in each line. The number of cars detected will be sent to microcontroller via laptop. The data on the number of cars is used as input for the convolutional neural network to produce output data that serves as reference for obtaining the length of time for the green light. If the car stops above or exceeds the stop line on zebra cross when the red light is on, the car will be detected as violation.
Design automatic waitress in android based restaurant using MQTT communication protocol
Authors: Ardhana V Y P , Tibyani  , Harianto F A S , Sarwadi  , Pratama R A , Sutrisno I , Endrasmono J , Soekarta R 
Published: September 2021

Abstract
Currently, many technologies are created to facilitate and help solve problems in society. The development of technology and industrial automation encourages people to fulfill their daily needs quickly, precisely and efficiently. At this time, a variety of automatic equipment that supports human performance in carrying out their duties has been widely used, ranging from simple control tools to robotics with a variety of up-to-date technology bases. how to queue in front of the cashier and be delivered by the waiter to the dining table which utilizes a lot of Human Resources with various risks such as dishes or even fallen humans. Automatic serving is an alternative for serving food in a modern style. In the process of serving food, it is carried out by placing the food on the robot, using a stepper motor, the robot can walk and by using the photodiode sensor to detect food running on the food tray it will automatically stop in front of the table of customers who have ordered through the android application that has been provided in each table to seat. This system is expected to be able to make the system at the restaurant and its visitors safer and more comfortable.
Safe distance reminder system on ship against port for the standing process using image processing
Authors: Santosa A W B , Hardianti A , Hasugian S , Sutrisno I , Khumaidi A 
Published: September 2021

Abstract
Since ancient times, Indonesia has been known as a country that conducts trading activities. However, the number of accidents when the ship is about to dock is an indication of the need to improve the marine transportation system. The factors that cause accidents include human, technical and weather errors. Seeing these conditions and also related to the increasingly rapid development of technology, modern solutions for detecting objects using cameras can be developed. By using a PC as a video processor from a camera that works in real time and can classify several ship objects using the Convolutional Neural Network (CNN) method. As well as being able to estimate the distance of the object where the ship must turn off the engine before docked with the camera using Stereo Vision. and the results of the algorithm processing can be translated into a signal that will be sent to the harbormaster and also the ship that will dock as an output. Then the ship that will dock can find out the distance where the ship has to turn off the engine through the signal sent or siren. The average total accuracy of the system which is able to detect ships is 97.15%.
Application of Machine Learning Method to Predict Reliability in Lubricating Oil System Components
Authors: Arumsari Nurvita , Pamuji Feby Agung , Puspita Bianda Devi 
Published: September 2021

AbstractIn predicting the reliability and failure of components, classical methods are often used by determining the distribution between failure times. Sometimes, the determination of this distribution does not always match the data pattern that is owned because of the limited data records and the many types of distribution that must be chosen. In addition, how much influence the time series has on components cannot be clearly analyzed. Therefore, in this study a prediction will be carried out by combining classical methods with machine learning, namely Support Vector Regression (SVR) and Least Square Support Vector Regression (LSSVR). Both methods are considered capable of improving the prediction accuracy of a series of data. The results showed that the classical combined method with LSSVR had better accuracy than SVR.
Monitoring system on towercopter using ELM (Extreme Learning Machine) method
Authors: Santoso A D , Nurkhamidah L , Tibyani  , Ardhana V Y P , Sutrisno I , Putra Z M A , Kahar M S 
Published: September 2021

Abstract
Towercopter has experienced rapid development in recent years. Towercopter is a tool with one brushless motor and one propeller that is installed between two support poles. Towercopter requires balance to be able to move during takeoff or houvering. In this final project, a study will be developed using three brushless motors. Towercopter is a singlecopter prototype that specifically moves vertically. The load disturbance test on the system causes the towercopter to become unstable while working towards the setpoint. It needs to be controlled so that it is stable. So to solve these problems a prototype is made. Towercopter in this final project is a prototype designed using three brushless motors and 3 propellers which are mounted on two support poles, namely stainless axles. Using two sharp irradi sensors to detect height and slope. The purpose of this final project is to produce an altitude control on a towercopter using the ELM (Extreme Learning Machine) method.
Assesment dermoscopy images of skin lesion using U-Net segmentation for clinicians teledermatology
Authors: Ciptaningrum A , Purnama I K E , Rachmadi R F 
Published: September 2021

Abstract
Standard solutions to the process of assessing skin lesions are based on a medical pathology examination using dermoscopy images. Fortunately, abovementioned-mentioned diagnosis and treatment quite often show a defect-prone, yet in the hands of accomplished health care professionals. Due to the rapid development of skin cancer lesions, computational analysis is required. In order to minimize the probability of error, a segmentation task is required in which multiple medical analyzes can be conducted. These frameworks are generally required versatile and need assistance from advanced computing power. The proposed system is tested with datasets for dermoscopy images of clinical signs. U-Net segmentation method provides greater segmentation result IoU 94.37, Dice Coefficient 88.11, precision 90.87, recall (sensitivity) 91.82, accuracy 94.55, loss 16.8, and F1-score 91.34.
Extraction of keywords in the abstract of scientifics papers using BERT
Authors: Ikhsan M , Rachmadi R F , Yuniarno E M 
Published: September 2021

Abstract
Keywords are used to facilitate searches, inaccurate keyword determination, which can result in searches for journals that do not match the intended title. To overcome this, it is necessary to implement a keyword search in the abstract using deep learning methods from a journal to produce the right keywords that will distinguish journals from one another. The purpose of this study is to implement a keyword search system in abstracts using the Bidirectional Encoder Representations from Transformers (BERT) method as an abstract word search system that produces keyword answers that have context according to the desired keyword results. The results of this study get optimal results in the epoch 500, and from these results using a dataset with of 444 training data and 10 test data for testing.
The influence of quenching on fatigue life of Ti6Al4V alloy
Authors: Belan J , Bokůvka O , Uhríčik M , Kuchariková L , Vaško A 
Published: September 2021

Abstract
Titanium Ti6Al4V alloy falls into the α+β category alloy system. It is widely used due to its unique mechanical and physical properties which can be modified by applied heat-treatment. The α-phase is considered to be the main phase influencing mechanical properties of an alloy such as ultimate tensile strength or ductility. However, it has also influence on the fatigue life where the form and presence of α-phase in prior β grains may increase or decrease fatigue life. The length and width of α-lamellae influence on fatigue life is well-known. A lot of authors have done their experiments on alloys with Widmanstätten or acicular α-phase structures. Our goal was to obtain an α’-martensitic structure in prior p grains and investigate its influence on fatigue life. To fulfil this goal the heat-treatment consisted of heating near above β-transus temperature 1050°C for a dwell time of 3 hours followed by water quenching was applied. After heat-treatment, the set of specimens with dimensions 10 mm x 9 mm x 55 mm were subjected to three-point bending fatigue test with the parameter of cycles asymmetry R < 1 and test frequency f = 69 Hz. The S-N curve of fatigue life was plotted after the fatigue test and SEM fractography analysis of fractured surfaces was done as well. Our results were compared to previous fatigue test done on alloy with α-lamellae structure.
Influence of rolling speed during hot forming using HDQT-R 30-12 machine on the properties of stainless steel 08Ch18N10T
Authors: Jirkova H , Janda T , Peković M , Říha J , Mach J , Krsová D 
Published: September 2021

Abstract
Mechanical properties of austenitic stainless steels can be improved by a suitable combination of forming and heat treatment operations. In addition to rolling reduction and speed, the heat treatment parameters are very important as well. Heat treatment typically combines solution and stabilization annealing. In components of WWER nuclear reactors, most of which are made of these steels, it is necessary to achieve the prescribed hot mechanical properties. Bars of 30 mm diameter made of titanium stabilized 08Ch18N10T steel were rolled in an incremental rolling machine. After induction heating to 950°C, different roll speeds were used, from 200 rpm to 25 rpm. The rolled bars were cooled in water and stabilization annealed at 720°C for 10 hours or at 800°C for 1 hour. Mechanical properties were determined by tensile testing at room temperature and at 350°C. Slower rolling speeds led to lower elongation (40%) than the faster ones (50%). Metallographic evaluation focused on the effect of forming on the grain size.
Preparation of Ti-Al-Si alloys with the various contents of aluminium and silicon
Authors: Knaislová A , Linhart J , Novák P , Szurman I , Čegan T , Juřica J , Vojtĕch D 
Published: September 2021

Abstract
The intermetallics based on Ti-Al system are a relatively new class of high-temperature construction materials that combine unique physical and mechanical properties for use in aircraft engines, industrial gas turbines, or automotive industry. They are characterized by low density, good mechanical properties at high temperatures and good oxidation resistance. Addition of silicon into the Ti-Al alloys improves oxidation resistance and ultimate tensile strength in compression, but the complicated production limits wider use of these Ti-Al-Si intermetallic alloys. In this work, two main technologies of preparation of intermetallic compounds will be compared-melting and powder metallurgy.
Temelin Irradiated Cladding Project – TIRCLAD
Authors: Linhart Stanislav , Bĕláč Josef , Ševeček Martin , Řeháček Radomír , Starý Vladislav 
Published: September 2021

Abstract
It is widely known, that zirconium-based alloys have been used for nuclear fuel cladding fabrication for decades [1], [2]. Therefore, it is crucial for fuel vendors, utilities as well as safety authorities to understand their behaviour during reactor operation with strong fast neutron and gamma irradiation. To complement the information about material properties for current as well as prospective advanced zirconium-based alloys, a long term research project implemented by ALVEL has been carried out, in cooperation with its partners (ČEZ, Škoda Nuclear Machinery, UJV Rez, Research Centre Rez) [3], [4]. The project is implemented on the background of a large material research program sponsored by JSC TVEL and ČEZ (this program started in 2012 and it is planned to be finished in 2024). It is fully independently implemented in the Czech Republic.
Irradiation of material samples started at Temelin NPP in 2014 and finished in spring 2020. The first three batches were already transported to UJV Rez and Research Centre Rez for post-irradiation evaluation. After finishing testing of reference non-irradiated samples testing in 2018 (determination of initial state, mechanical properties and as-received microstructure), six batches of irradiated material have been analysed sequentially with their increasing neutron fluence. The final irradiation damage of the last sixth batch corresponds approximately to fuel burnup of 80 MWd/kgU.
This paper presents the developed methodologies and the expected experimental and other important outcome. Several material properties are being studied on different scales including high resolution microstructural and chemical analysis, creep and mechanical behaviour, nanoindentation, oxide layer morphology. The main objectives of the project include evaluation of materials’ microstructural and bulk properties and the derivation of dose- and temperature-dependent correlations that can be implemented into FEM models and fuel performance codes such as FRAPCON/FRAPTRAN [5], [6] or Transuranus [7]. These models can be then used to support licensing of new designs influenced by fuel cladding behaviour during long term dry storage, justification of dry storage for an extended period of time or justification of new safety criteria that can lead to enhanced operation of VVER reactors and spent nuclear fuel storage [8].