bluuebunny/crossref_metadata_2025_split huggingface dataset:
Welding room development for simultaneous improvement of welder health and weld quality of gas metals arc welded aluminum AA5083-H112
Authors: Triyono Triyono , Harseno Anton , Muhayat Nurul 
Published: March 2024

This study investigated the weld joint mechanical properties and welding fume exposure associated with Gas Metal Arc Welding of aluminum AA5083-H112 in 27 different welding room environment conditions. These conditions consist of variation in temperature, as well as intake and exhaust wind velocities. The temperature varies as 19 °C, 27 °C and 35 °C. Both the intake and exhaust velocity vary as 0 m/s, 3.1 m/s and 5.5 m/s. The experimental findings underscore the pronounced influence of these factors on both weld quality and welder exposure to fumes. Notably, intake wind velocity emerges as the most critical factor, contributing significantly to 47.68 % in weld joint tensile strength. The temperature emerges as the least critical factor with 12.02 % of contribution. However, temperature became the most critical factor on weld joint impact energy with 54.89 % of contribution while exhaust wind velocity became the least with 3.89 %. Air quality monitoring highlights the importance of optimal intake and exhaust fan configuration to effectively reduce fume exposure. All examined welding room environment condition are deemed safe for the welder, as they do not exceed the Treshold Limit Value (TLV), except the condition where the welding room lacks of air circulation in intake and exhaust wind velocity of 0 m/s. The identified optimal welding room condition exerts a temperature of 27 °C, intake and exhaust wind velocity of 0 m/s and 3.1 m/s respectively. This condition not only achieves established weld quality standards but also ensures compliance with fume exposure regulation. This research provides valuable insights for optimizing welding room environment to simultaneously maintain weld quality and safeguard the well-being of welders
Determining features in the application of redundancy for the thermistor cubic transformation function using computer simulation
Authors: Shcherban’ Volodymyr , Korohod Hanna , Kolysko Oksana , Kyrychenko Anton , Shcherban’ Yury , Shchutska Ganna 
Published: March 2024

The object of research is the process of temperature measurement with a platinum thermistor. We have conducted studies on the cubic transformation function of the thermistor when using redundancy that yielded the equation of redundant measurements of the desired temperature. Owing to this, it became possible to directly apply the resulting equation without additional measures to linearize the function of the thermistor transformation. In addition, the obtained value of the desired temperature does not depend on the values of the parameters of the cubic transformation function and their deviations from the nominal values. Experimental studies have proven that the value of the normalized temperature T0 has a greater influence on the result of redundant measurements and the value of the normalized temperature DT on the entire range of measured temperatures Tx is almost unaffected. The best accuracy results (value of relative error δ=0.02 %) were obtained at T0 values lower than –60 °C. When the error of reproduction of normalized temperatures increased from ±0.02 °C to ±0.1 °C, the best accuracy results (value of relative error δ=0.06 %) were obtained at values of normalized temperature T0 below –130 °C. Analysis of results of the absolute error DT revealed that with an error of reproduction of normalized temperatures of ±0.02 °C and at T0=–180 °C, its value does not exceed 0.02 °C, that is, it is within the error of reproduction of normalized temperatures. This allows us to state that it is recommended to use sources of standardized temperatures of high accuracy during measurement control.
Thus, there are reasons to assert the prospect for redundant measurements when directly measuring temperature with a thermistor with a cubic transformation function with high accuracy
Implementing surface treatment and adhesive variations for bonded joints between composite gfrp and aluminum at 200 °C
Authors: Purnomo Herry , Rifa’i Muhammad Johan , Purwoko Purwoko , Vicarneltor David Natanael , Ibadi Mahfud , Setianto Muhamad Hananuputra , Yudanto Maulana , Rizkyta Ara Gradiniar 
Published: March 2024

Bonding dissimilar materials, specifically Glass Fiber Reinforced Polymer (GFRP) and Aluminum 6061 T651, at elevated temperatures, such as in fire accidents is challenging, where structural integrity and reliability are critical. We studied how surface roughness treatment affects the joint strength of three common adhesives in aircraft (Click Bond CB394-43, Loctite A9396, A9394) at 200 °C. The GFRP, composed of Gurit Prime 37 epoxy resin and E-Glass 7781 fibers produced through vacuum infusion with dimensions following ASTM D5868 standards, was lap shear tested with 2 mm/s stroke. Findings showed a substantial enhancement in joint strength due to surface treatment, sanding with 100-grid sandpaper for 20 seconds in parallel with the fiber direction, for all adhesives. A9396, A9394, and CB394-43 exhibited remarkable improvements of 1091.67 %, 45.92 %, and 30.09 %, respectively. The strain at break showed significant increases of 51.61 %, 121.95 %, and 100 %, respectively. Both surface-treated and untreated A9394 samples showed the highest strength among the adhesives. A9396 exhibited lower strength than CB394-43 without surface treatment, but it outperformed when surface-treated, highlighting its response to surface modification. Adhesive viscosity influences penetration on material surfaces, with A9396 being stiffer than the other adhesives. The analysis of ISO 4287 Ra values revealed that surface treatment led to increased roughness on the Aluminum surface while reducing roughness on the GFRP surface. These results offer valuable insights for optimizing GFRP-Aluminum bonding under elevated temperature conditions. Adjusting surface roughness significantly improves the interaction between Aluminum and GFRP with adhesives, resulting in enhanced joint strength. This knowledge can be applied in various engineering applications, particularly in industries where the performance and reliability of bonded joints are critical under high-temperature environments
Devising a method for the virtual clustering of the Internet of Things edge environment
Authors: Kuchuk Heorhii , Mozhaiev Oleksandr , Kuchuk Nina , Tiulieniev Serhii , Mozhaiev Mykhailo , Gnusov Yurii , Tsuranov Mykhailo , Bykova Tetiana , Klivets Sergii , Kuleshov Alexander 
Published: March 2024

The object of research is the process of load distribution in the edge environment of the Internet of Things.
The task to improve the efficiency of the functioning of the network of computing devices in the Internet of Things edge environment has been solved. Free resources of heterogeneous single-board computers were used to this end.
In the process of conducting research, an approach to the construction of an architecture for a virtual cluster of computers with limited resources was devised. The design took into account specific features of the edge environment on the Internet of Things. This has made it possible to propose a four-layer architecture instead of the standard seven-layer architecture of IoT sensor information processing device networks.
Stages in the virtual cluster construction in the edge environment on the Internet of Things were also defined. A three-stage procedure to form a virtual cluster was justified. This procedure made it possible to devise a method for the virtual clustering in the Internet of Things edge environment based on the proposed virtual cluster architecture.
The proposed method for building a virtual cluster in the Internet of Things edge environment was investigated. With a small network load, a virtual cluster has no advantage over a classic cluster. But with the growth of the network load, the virtual cluster prevails over the classic cluster in total performance; the advantage in total performance can exceed 10 %. It was also proven that for a heterogeneous environment, performance changes at full network load significantly depend on the number of virtual node groups. The research results on the method for building a virtual cluster in the Internet of Things edge environment can be explained by improving the balance of the network load at virtual clustering
Development of a method of increasing the efficiency of decision-making in organizational and technical systems
Authors: Owaid Salman Rasheed , Zhuravskyi Yurii , Lytvynenko Oleksandr , Veretnov Andrii , Sokolovskyi Dmytro , Plekhova Ganna , Hrinkov Volodymyr , Pluhina Tetiana , Neronov Serhii , Dovbenko Oleksii 
Published: March 2024

The object of the study is organizational and technical systems. The subject of the study is the decision-making process in the problems of management of organizational and technical systems. A method of increasing the efficiency of decision-making in organizational and technical systems using artificial intelligence is proposed. The research is based on the giant armadillo swarm algorithm to find a solution regarding the state of organizational and technical systems. Giant armadillo agents (GAA) are trained using evolving artificial neural networks, and an advanced genetic algorithm is used to select the best GAA. The method has the following sequence of actions:
– input of initial data;
– setting GAA on the search plane;
– numbering GAA in the swarm;
– determining the initial velocity of GAA;
– preliminary evaluation of the GAA search area;
– classification of food sources for GAA;
– sorting the best GAA individuals;
– attack on termite mounds by GAA;
– digging termite mounds by GAA;
– updating GAA positions;
– checking for the presence of a GAA predator;
– escape and fight against GAA predators;
– checking the stop criterion;
– training GAA knowledge bases;
– determining the amount of necessary computing resources of the intelligent decision support system.
The originality of the proposed method lies in setting GAA taking into account the uncertainty of the initial data, advanced procedures of global and local search taking into account the noise degree of data on the state of organizational and technical systems. The method makes it possible to increase the efficiency of data processing at the level of 14–19 % using additional advanced procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes
Improving a method for non-coherent processing of signals by a network of two small-sized radars for detecting a stealth unmanned aerial vehicle
Authors: Khudov Hennadii , Yarosh Serhii , Kostyria Oleksandr , Oleksenko Oleksandr , Khomik Mykola , Zvonko Andrii , Lisohorskyi Bohdan , Mynko Petro , Sukonko Serhii , Kravets Taras 
Published: March 2024

The object of this study is the process of detecting stealth unmanned aerial vehicles by a network of two small-sized radars with incoherent signal processing. The main hypothesis of the study assumed that combining two small-sized radars into a network could improve the quality of detection of stealth unmanned aerial vehicles with incoherent signal processing.
The improved method for detecting a stealth unmanned aerial vehicle by a network of two small-sized radars with incoherent signal processing, unlike the known ones, provides for the following:
– synchronous inspection of the airspace by small-sized radars;
– sounding signal emission by each small-sized radar;
– reception of echo signals from a stealth unmanned aerial vehicle by two small-sized radars;
– coordinated filtering of incoming echo signals (separation of echo signals);
– quadratic detection of signals at the outputs of matched filters;
– summation of the detected signals at the outputs of the matched filters;
– summation of the outputs of adders of two small-sized radars.
The scheme of a stealth unmanned aerial vehicle detector is presented, optimal according to the Neumann-Pearson criterion, with incoherent signal processing.
The quality of detection of a stealth unmanned aerial vehicle by a network of two small-sized radars with incoherent signal processing was evaluated. It was found that with incoherent processing, the gain in the value of the conditional probability of correct detection is on average from 19 % to 26 %, depending on the value of the signal-to-noise ratio. The gain in the value of the conditional probability of correct detection is greater at low values of the signal-to-noise ratio. At the same time, the gain in signal-to-noise value is more significant with coherent signal processing than with non-coherent signal processing by a network of two small-sized radars
Implementation of digital innovation on sustainability performance: the moderating role of green accounting in the industrial sector
Authors: Lisnawati Lisna , Aryati Titik , Gunawan Juniati 
Published: March 2024

Innovation is the solution that allows digital transformation to be implemented in many industrial sectors. With digital innovation, companies can move more freely in achieving sustainability performance, because digitalization is a cross-border discipline. Empirical studies that directly link digital innovation, sustainability and accounting are still very limited. To fill this gap, this study aims to examine the role of green accounting in the influence of human capacity building, digital innovation, and sustainability strategy on sustainability performance. This study employs quantitative content analysis on the annual reports and sustainability in the industrial sector listed on the IDX 2021–2022, comprising a total of 792 observational data using the PLS. The research results indicate that an increase of 32 % in human capacity building, 14 % in digital innovation and 12 % in sustainability strategy has a significant impact on sustainability performance. Another finding shows the results that green accounting is only able to strengthen the influence of digital innovation on sustainability performance and the rest weakens and does not even have a role as a moderating variable. The implications of this study are theoretically the development of new measures of digital innovation for the industrial sector. The practical implications suggest that to enhance sustainability performance, digital innovation is needed, starting from a pervasive digital culture extending to various aspects, including digital products, services & solution, digital supply chains, and digital accounting. The implications of implementing green accounting for industries indicate a 6.9 percent increase in the influence of digital innovation on sustainability performance
Method for early ignition detection based on the sampling dispersion of dangerous parameter
Authors: Pospelov Boris , Rybka Evgenіy , Krainiukov Olekcii , Fedyna Vasyl , Bezuhla Yuliia , Melnychenko Andrii , Borodych Pavlo , Hryshko Svitlana , Manzhura Svyatoslav , Yesipova Olha 
Published: March 2024

The object of the study is the selective dispersion of dangerous parameters of the gas environment during material fires. The practical importance of research consists in using the difference of sample dispersions of dangerous parameters of the gas environment on the intervals of absence and presence of ignition of materials for detection of ignition. The theoretical substantiation of the method of detecting fires in premises based on sample dispersions of current measurements of an arbitrary dangerous parameter of the gas environment, corresponding to the general populations of reliable absence and presence of fire, has been carried out. The method, at a given level of significance, determines the unbiased uniformly most powerful fire detection rule. This makes it possible to determine how much differences in sample variances are significant with a given level of significance and are caused by ignition or are random factors. Laboratory experiments were conducted to verify the proposed method. It was established that the influence of ignition on the value of the difference in the sample dispersion at the corresponding intervals of monitoring the carbon monoxide concentration, smoke density, and temperature of the gaseous environment of the laboratory chamber is different and depends on the type of ignition material. At the same time, the minimum difference of the sample dispersions is characteristic for observing the smoke density for all the studied materials. However, early detection of ignition of alcohol, paper, wood, and textiles when observing the smoke density is carried out when the threshold is exceeded by 9.01, 5.31, 2.13 and 2.55 times, respectively. It is shown that the method of early detection of fires, which is based on the detection of significant differences in sample dispersions of data from the relevant general populations
Aplikasi Algoritma Viterbi dalam Hidden Markov Model untuk Menganalisis Trend Pasar Saham di Bursa Efek (Studi Kasus di PT. Bank Central Asia, Tbk.)
Authors: Lina P Eligia Helvianti Tri , Yundari Yundari , Huda Nur’ainul Miftahul 
Published: March 2024

This study aims to analyze and apply the Viterbi algorithm in the Hidden Markov Model on stock market trend movement data at PT Bank Central Asia, Tbk in 2022. At the initial stage, the closing stock price data of PT Bank Central Asia, Tbk for the next fifteen days is predicted using the ARIMA method. Then, the second stage is classifying closing stock data as a result of predictions. The third stage is to determine the parameters of the Hidden Markov Model. The fourth stage is to determine the Hidden State sequence with the Viterbi Algorithm, and the last stage is to analyze the application of the Viterbi Algorithm to the movement of the stock market trend. The results show that the Viterbi algorithm is used to determine the most optimal Hidden State sequence from a sequence of observed states. The right time for an investor to make a decision to sell shares is when the stock price is rising and the stock market trend is in a bullish position, namely on the March 4th, 10th, 16th, 17th and 21th 2022. Meanwhile, buying shares is when the stock price is down and the stock market trend is in a bearish position, namely on the March 3rd, 9th, 14th, 18th and 23th 2022.Keywords: Hidden Markov Model, Stock Market Trends, Viterbi Algorithm. AbstrakPenelitian ini bertujuan untuk menganalisis dan mengaplikasikan algoritma Viterbi dalam Hidden Markov Model pada data pergerakan trend pasar saham di PT. Bank Central Asia, Tbk tahun 2022. Pada tahap awal dilakukan prediksi data harga saham penutupan PT Bank Central Asia, Tbk selama lima belas hari ke depan menggunakan metode ARIMA. Tahap kedua adalah mengklasifikasi data hasil dari prediksi. Tahapan ketiga adalah menentukan parameter-parameter Hidden Markov Model. Tahapan keempat menentukan barisan Hidden State dengan Algoritma Viterbi, dan tahap terakhir adalah menganalisis pengaplikasian Algoritma Viterbi pada pergerakan trend pasar saham. Hasil dari penelitian ini adalah bahwa algoritma Viterbi digunakan untuk menentukan barisan Hidden State yang paling optimal dari suatu barisan observed state. Waktu yang tepat seorang investor mengambil keputusan untuk menjual saham adalah ketika harga saham dalam keadaan naik dan trend pasar saham dalam posisi bullish yaitu pada tanggal 4, 10, 16, 17, dan 21 Maret 2022. Sedangkan untuk membeli saham adalah ketika harga saham dalam keadaan turun dan trend pasar saham dalam posisi bearish yaitu tanggal 3,9, 14, 18, dan 23 Maret 2022.
Application Bootstrap to Estimate the Confidence Intervals of NO2 Levels in the Kriging Method
Authors: Fitriyati Nina , Irene Yanne , Benita Azzahra 
Published: March 2024

NO2 levels must be monitored continuously to minimize negative environmental impacts. In general, the estimation of NO2 levels using the Kriging method produces point estimates. In this study, we developed an interval estimate for NO2 levels by applying the quasi-random Bootstrap resampling method. We used data on NO2 levels in 14 areas in South Tangerang City in 2021. The data is stationary, so the appropriate estimation method is ordinary kriging. To develop the 95% confidence interval, we applied 1000 resamplings to the Bootstrap. The estimation results show that the lowest 95% confidence interval for NO2 levels is in the range of 25.23123 – 27.82351 μgr/m3 in Pamulang Timur Village, and the highest 95% confidence interval for NO2 levels is in the range of 45.59886 – 46.08371 μgr/m3 in the Ciater Village.Keywords: Bootstrap, Confidence Interval, Kriging, Quasi-Random. AbstrakKadar NO2 perlu dipantau secara terus menerus untuk meminimalisir dampak negatif terhadap lingkungan. Pada umumnya, estimasi kadar NO2 menggunakan metode kriging menghasilkan estimasi titik. Pada penelitian ini akan dikembangkan estimasi selang untuk kadar NO2 dengan mengaplikasikan metode resampling quasi-random bootstrap. Data yang digunakan adalah kadar NO2 pada 14 wilayah di Kota Tangerang Selatan tahun 2021. Data tersebut stasioner sehingga metode estimasi yang digunakan adalah ordinary kriging. Untuk pembentukan selang kepercayaan 95% diaplikasikan 1000 resampling pada metode bootstrap. Hasil estimasi menunjukkan bahwa selang kepercayaan kadar NO2 terkecil berada pada rentang nilai 25,23123 – 27,82351 yang berlokasi di Kelurahan Pamulang Timur dan selang kepercayaan kadar NO2 terbesar berada pada rentang 45,59886 – 46,08371 yang berlokasi di Kelurahan Ciater.
ANALISIS TINGKAT KERUSAKAN BANGUNAN GEDUNG RUSUNAWA IAIN AMBON
Authors: Ali Alfianty Mase , Sangadji Fauzan A. , Kempa Meidy 
Published: March 2024

Damage to the building of the building often occurs, one of the factors is the age of the building and also the lack of maintenance and maintenance. Like one of the buildings of the IAIN Ambon rusunawa building. The purpose of this study is to calculate the volume of damage that occurs in the IAIN Ambon rusunawa building and determine the level of damage to the IAIN Ambon rusunawa building. The research method used by the author is a survey method and quantitative method, the survey method is used to see what damage to the building elements of the IAIN Ambon Rusunawa building, which then uses quantitative methods to determine the level of damage to the IAIN Ambon rusunawa building. The results showed total damage to building elements with a volume of wall damage 295.88 m2, ceramic floor 30x30 38.25 m2, concrete deck floor 162 m2, unit door 5 pieces, door KM / WC 20 pieces, windows 13 pieces, ceiling km / wc 1.5 m2, conclusions obtained the category of damage level for building elements of the IAIN Ambon rusunawa building including the level of minor damage, with a damage weight analysis value of 10.58%. Where according to the Regulation of the Minister of Public Works 30% damage including minor damage.
Jugulotympanic paraganglioma: A cause of sequential cranial nerve fallout and obstructive hydrocephalus
Authors: Hirachund Kiara , Khuzwayo Nhlalenhle , Beringer Craig , Hoffman Deidre , Mahomed Zeyn , Colloty J , Dewey G 
Published: March 2024

Abstract
A 46-year-old male presented with a longstanding history of a sequential cranial nerve fallout. Following extensive imaging which included contrast enhanced computed tomography, computed tomography angiography, and diagnostic digital subtraction angiography, a diagnosis of jugulotympanic paraganglioma was made. The tumour was found to be locally invasive, encapsulating major neurovascular structures and ultimately inaccessible. Furthermore, the clinical presentation was complicated by acute obstructive hydrocephalus secondary to tumour mass effect. Given the rarity of the condition and unusually extensive presentation, neurosurgery alongside a multidisciplinary team collaborated to formulate a management plan aimed at maximizing functional outcome and minimizing intraoperative morbidity. A decision was made to perform palliative surgical debulking procedure followed by multidisciplinary care and rehabilitation. The patient demised in the care of his family prior to any further intervention.