bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of fabric properties on the performance of a textile based ferroelectret generator toward human body energy harvesting
Authors: Shi Junjie , Beeby Steve P 
Published: February 2022

AbstractThis paper reports the lamination of two thin fluorinated ethylene propylene (FEP) films onto the back and front surfaces of a conventional textile forming a sandwich structure which creates a textile-based ferroelectret. In this work, we study the effect of the physical properties and dimensions of the textile on the piezoelectric properties and energy harvesting performance of the ferroelectret. Five different fabrics with different thicknesses and Young’s modulus were used to form textile based ferroelectret harvesters. Thinner textiles result in increased piezoelectric properties of the fabricated FEP textile ferroelectret. The highest measured stable maximum piezoelectric coefficientd33of 987 pC N−1was achieved by the thinnest silk textile FEP ferroelectret. The energy harvester based on the FEP-silk textile ferroelectret generates a peak output power density of 2.26µW cm−2. The textile ferroelectret can charge a 10µF capacitor used to store the harvested energy to 3.2 V in 40 s. This corresponds to an average output power of 1.07µW when subjected to compressive pressures of 30 kPa applied at a frequency of 1 Hz with a 90 MΩ loading resistance.
Active Extrinsic Calibration of Encoder and LIDAR for Robot
Authors: Yi Tong , Lan Bin , Wang Xueqian , Liang Bin 
Published: February 2022

Abstract
Robotic extrinsic calibration is a prerequisite for multi-sensor data fusion, which provides a transformation between coordinate systems of different sensors. For wheeled robots equipped with encoder and other sensors, the existing usual calibration process is completed by professional calibration engineers, or just randomly, which is not efficient and may cause motion degradation or unknown uncertainty. In this paper, we propose an active extrinsic calibration algorithm for encoder and 2D LIDAR. The trajectory in the calibration process is planned in belief space, which is optimized to get the calibration value with the minimized uncertainty. Our method doesn’t rely on maximum-likelihood observations assumption, and can also work in discontinuous sensing domain. The simulation is conducted to validate the method.
Path Planning for Mobile Robots Based on an Improved Ant Colony Algorithm with Gaussian Distribution
Authors: Li Chenyang , Liu Qianjie , Song Shuang , Huang Tengchao , Zhu Qingyuan 
Published: February 2022

Abstract
Optimal path planning for mobile robots in complex environments has the problem of tangential collision with obstacles. This paper proposed an ant colony algorithm based on Gaussian distributed pheromone volatile mechanism (GD-ACO). The algorithm can reduce the collision probability with obstacles during the search navigation, and it increased the search efficiency and avoidance capability of mobile robot in complex environment path planning. Firstly, we established a grid environment model and introduced a Gaussian distribution pheromone volatility mechanism to perform optimal path planning. Secondly, we introduced right triangle constraints to eliminate the unqualified paths and reduce the complexity of the algorithm through a pheromone reward mechanism. Finally, by improving the heuristic information function distribution of the ant colony algorithm, it solved the algorithm cannot effectively converge to the optimal solution when encountering special obstacle distribution and achieved more efficient obstacle avoidance. Compared with other path planning algorithms, it can effectively generate a collision-free path. The simulation experiments show the improved ant colony algorithm has better obstacle avoidance capability and faster performance, and the proposed method can effectively find the optimal collision-free path through experimental verification.
The System Design and Robotic Manipulation Skills of Dualarm Autonomous Mobile Robot for Bomb Removing
Authors: Zhao Dan , Sun Fuchun , Li Linxiang 
Published: February 2022

Abstract
Bomb removing is a very challenging but valuable task in urban anti-terrorist or military applications. With the rapid development of technologies of intelligent robots in these years, the intelligence and security level of bomb removing process can be largely improved by using the autonomous mobile robotic systems. In this paper, a dual-arm autonomous mobile robot for bomb removing is proposed which is designed by Tsinghua University. The system design is introduced which mainly consists of the structure and multimodal perception module of the designed system. Besides, manipulation performance is one of the most important functional attributes in bomb removing. Therefore, the manipulation skills for the bomb removing applications are analyzed which adopt the idea of primitives, and skill decomposition and synthesis. Moreover, a knowledge graph for bomb removing is established in the paper and a knowledge based method for the manipulation skills learning is presented. Finally, simulations and experiments have been carried out in the platform to validate the proposed method in the paper and designed bomb removing mobile robot.
SemEAGAT: A Novel Approach by Incorporating Semantic Dependency Graph in Event Detection
Authors: Xi Yuqi , Lu Jiamin , Hang Tingting , Zhang Yunfei , Wang Zhongyi , Feng Jun 
Published: February 2022

AbstractEvent detection (ED) is a task that requires capturing deep semantic information in text to correctly identify specific types of events. Semantic dependency graph aims to recover sentence-internal predicate-argument relationships. However, recent ED researches often use syntactic dependency tree in GNNs, while we believe that the semantic dependency graph can further improve the ED task’s effectiveness since it has already been used in many other NLP tasks such as relation extraction, machine translation and abstractive summarization to provide effective semantic information, which is exactly required for event detection. In this paper, we propose a novel semantic dependency edges aware graph attention network (SemEAGAT). It incorporates the semantic dependency graph with an additional multi-head attention in an edge-aware way. Experiments on ACE2005 show our proposed method can achieve better effectiveness by comparing with the state-of-the-art methods.
Joint Dilated Convolution and Self-attention for Cross-domain Sentiment Analysis
Authors: Gu Tong , Xu Guoliang , Liu Xuemei , Luo Jiangtao 
Published: February 2022

Abstract
Cross-domain sentiment analysis aims to use source domain resources or models to serve the sentiment analysis tasks in the target domain, and it can effectively alleviate the problem of insufficient tagged data in the target domain. In this paper, we investigate deep transfer learning for text sentiment analysis, and focus on customer reviews for different domains. Given the shortcomings of the conventional deep neural network, such as convolutional neural network (CNN) cannot obtain the long-term dependence between features, recurrent neural network (RNN) cannot achieve parallel computing, we propose a novel neural network which joint dilated convolution and self-attention (ADC). The ADC takes residual learning as its basic framework, which can capture more distant information by introducing a dilation rate in the convolution. Self-attention is used to make the ADC pay more attention to important sentiment information. First, the ADC is pre-trained with the data of the source domain, and the weight of the pre-training is frozen. Then, the model is fine-tuned by the method of gradual unfreezing, and the weight is updated through the data of the target domain. Finally, the updated model can be utilized for the target domain sentiment analysis. By using customer review datasets, we carry out extensive experiments to demonstrate that this method has superior performance and can better achieve cross-domain sentiment analysis.
Research on Effective Path Planning Algorithm Based on Improved A* Algorithm
Authors: Zhang Jing , Liu Zengyuan , Wang Yi , Zhang Fan , Li Yunsong 
Published: February 2022

Abstract
In recent years, with the rapid development of technology, mobile robots are being applied in all aspects of production and life. The A* algorithm can be used for global path planning of mobile robots. Aimed at the problem of the traditional A* algorithm planning path having many turning points and do not satisfying the global optimality, an A* algorithm based on the adaptive neighborhood search and steering cost has been proposed. Based on the information of the surrounding obstacles, the algorithm adaptively selects the appropriate neighborhood to search for the optimal child node. By establishing the steering cost model of the mobile robot, the steering cost is joined into the evaluation function of the A* algorithm. Based on the adaptive neighborhood search, the A* algorithm with steering cost breaks through the constraint of eight neighborhood search nodes, shortens the path length, and uses the steering cost to search for the global optimal path with fewer turning points. The simulation results show that compared to the traditional A* algorithm, the total path cost of the A* algorithm based on adaptive neighborhood search and steering cost is reduced by 19.3%, and the number of turning points is reduced by 44.4%.
The effect of adding impurities to the high density fuel matrix on the reactivity of the RSG-GAS core
Authors: Tukiran S , Surian P , Endiah PH 
Published: February 2022

Abstract
The safety calculation of the RSG-GAS reactor core needs to be done if new high-density fuel is used in the RSG-GAS core. The use of new high-density fuels is very much needed in the RSG-GAS core so that it is necessary to calculate its safety. When using high density fuel there will be a “bottle neck” effect where there is a problem with the fuel and cladding interaction. According to previous researchers this can be overcome by adding metal elements Si, Ni or Ti to fuel. However, with the addition of metal elements Si, Ni or Ti to the fuel, it needs to be analyzed in the RSG-GAS core. The analysis was carried out calculations using a computer program by simulating the Si metal used 1%, 2%, 3% 4% and 5% in the fuel. The calculation of the additional metal element in the high-density fuel effect on the reactivity of the RSG-GAS core was carried out with the WIMSD-5B and Batan-FUEL programs. The WIMSD-5B program is a computer program consisting of several modules including the transport module which is used for the calculation of the generation of macroscopic constants for the 19.75% enriched uranium silicide fuel and the density of 4.8 gU/cc as a function of degree of burn. Core calculations were performed using a neutron diffusion program, namely Batan-FUEL. By calculating the core criticality at operating temperature, the core neutronic parameter values are obtained. The results of the analysis show that the amount of Si 5% in the high density fuel matrix can solve the bottle neck problem and the neutronic parameters are still within the safety limit. This value will determine how much the value of the fuel burn up and control rods are in accordance with the acceptance criteria so that the safety analysis can be carried out on the RSG-GAS core using high density. From the analysis, it was found that the addition of the element Si in the high-density fuel matrix did not find any significant changes in core reactivity and neutronic parameter.
Effect of N2 carbonization temperature on porous activated carbon derived from jicama (Pachyrhizus erosus L.) peel as electrode material for supercapacitor
Authors: Taer Erman , Riccahd G Arnold , Apriwandi  , Taslim Rika 
Published: February 2022

Abstract
This study presents the different effects of nitrogen carbonization temperature of porous carbon as electrode material based for supercapacitor applications. The precursor origin material as a carbon source is focused on the bio-waste of jicama peel. The precursor is directly chemically activated ZnCl2 followed by high-temperature pyrolysis. This work has been performed with three different carbonization temperatures of 550 °C, 600 °C, and 650 °C. Experimental results show that carbonization at different temperatures causes the formation of different material properties to support the performance of the supercapacitor. The dimensions of the carbon coins display different density values with data trends being degraded after the high-temperature pyrolysis process. In addition, microcrystalline properties were also evaluated by means of the X-ray diffraction technique. The supercapacitor cells were evaluated in two-electrode configurations with an organic membrane as a separator. Electrochemical properties such as specific capacitance, energy density, and power density were thoroughly evaluated through cyclic voltammetry and galvanostatic charge-discharge techniques. The highest specific capacitance was confirmed at 179 F g−1 in a constant current density of 1.0 A g−1. Furthermore, the maximum energy density was found as high as 12.60 Wh kg−1 at the optimum power density of 105.86 Wh kg−1. These results confirm that the carbonization temperature needs to be considered to obtain high-porous activated carbon derived from bio-waste jicama peel for supercapacitor electrode materials.
High potential of yellow potato (Solanum Tuberosum L.) peel waste as porous carbon source for supercapacitor electrodes
Authors: Pertiwi Dinda , Yanti Novi , Taslim Rika 
Published: February 2022

Abstract
Yellow potato peel contains chemical components such as protein, fiber, starch and sugar which is composed atom carbon chains bonding. Heating potato peel at high temperatures can disrupt the bonding of the carbon atoms of the constituents, vaporizing volatile compounds, thereby producing high carbon fixed. This study preparation yellow potato peel-based carbon electrodes through a single-stage integrated pyrolysis with carbonization from room temperature to 600 °C in N2 gas atmosphere followed by physical activation to a temperature of 850°C in CO2 gas environment. The impregnation of ZnCl2 at different concentrations was optimized as an independent variable precursor to produce porous activated carbon for energy storage devices. The difference in concentration of 0.1M, 0.3M and 0.5M ZnCl2 can increase the porosity, structure of amorphous carbon and the resulting high electrochemical performance. Electrochemical properties were characterized using cyclic voltammetry and galvanostatic charge discharge methods in an aqueous electrolyte of 1M H2SO4 at a voltage of 0-1000 mV and a scanning rate of 1 mV s−1. Furthermore, the resulting specific capacitance increased from 82.82 F g−1, 195.66 F g−1 and 147.03 F g−1 based on the effect of the concentration of the chemical activator ZnCl2. While the specific capacitance obtained using the GCD method shows higher numbers, namely 145.13 F g−1, 223.25 F g−1 and 174.08 F g−1. Energy density 27.18 Wh kg−1 and power density 97.93 W kg−1 from cv method. The simple approach of activated carbon from potato peel waste is expected to produce an economical and simple porous carbon electrode for high performance energy storage application.
Development of an ADVICE training model for radiotherapy medical physicists in North Sumatera-Indonesia
Authors: Nasution Ikhsan Bagatondi , Napitupulu Efendi , Sitompul Harun 
Published: February 2022

Abstract
Radiotherapy is a fundamental part of effective cancer treatment. Medical physicists are one of the personnel who play a major role in radiation planning for cancer patients, but in North Sumatra, there are still 71.4% who do not have competency certificates due to limitations in accessing appropriate training. The type of study is a research and development study. Data obtained directly from respondents to validate research products and their feasibility. The resulting training model is the ADVICE training model which consists of six syntaxes, namely: analyze, design, verify, implement, control and evaluate. The development of the ADVICE training model was developed from the ADDIE learning model. The products produced are in the form of model books, textbooks, training manuals for instructors and training manuals for training participants and videos of the results of making 3D FIF radiation planning techniques for nasopharyngeal cancer. The validity of the model development is measured with several tools. The validation sheet tool is used to assess the quality of the content, construction and syntax of the ADVICE training model and its feasibility is measured based on the results of the review by design experts, material experts and media. The results of due diligence on the product from the results of research on the development of the ADVICE training model are declared feasible by the user. The educational impact that occurs when using the ADVICE model is the formation of a simple, creative and flexible training concept. Participants create training products.
Structure evolution due to heat treatment of aluminum nanoparticle with different sizes: a molecular dynamics study
Authors: Fahdiran Riser , Sugihartono Iwan , Delina Mutia , Prayitno Teguh Budi , Sunaryo  , Nasbey Hadi 
Published: February 2022

Abstract
In this study, we performed Molecular Dynamics (MD) Simulation to investigate the significance of diameter during heat treatment of Aluminum nanoparticle. Structure information along with thermodynamics evolution is analyzed to explain the significance. Different sizes of nanoparticle diameter, i.e., 5 nm, 10 nm, and 15 nm, were investigated with same heating rate. The results show that smallest diameter is suffered for total melting, while for larger nanoparticle small fractions remains. Thermodynamics information indicated the relation that smaller diameter will experience faster pressure oscillations period. While for larger system, the period is longer, but the pressure value become stronger. Structure analysis confirmed that the nanoparticles are melted at the end of the simulation.
Comparative study of mineral element content in fishes from the south and north seas of java island using neutron activation analysis
Authors: As’ari A H , Mulyaningsih T R , Yusuf S 
Published: February 2022

Abstract
Fish is an environmental bioindicator and a contributor to the daily intake of mineral elements. The content of mineral elements in fish is influenced by what it eats and its environment. Moreover, based on location, around the north coast of Java there are denser residential and industrial areas compared to around the south coast of Java. In this study, we analyzed the mineral content of fish of the same species originating from the southern and northern seas of Java using neutron activation analysis. Fish samples of the same 11 species were each collected from fish auctions in Pemalang and Garut districts. The samples were washed, and then the meat was taken and dried by the freeze-drying method. The samples were irradiated in the G.A. Siwabessy multi-purpose reactor through the rabbit system then counted using gamma spectrometry. The results obtained as many as 17 mineral elements in fish: Na, K, Mg, Cl, Ca, Br, Fe, Zn, Sr, Al, Cr, Se, Rb, Mn, Co, Hg, and Cs. Statistical test results show that there are various differences (positive covariance on 14 elements, negative covariance on 3 elements) for each element between fish from the South Java Sea and North Sea, which indicates that marine environmental conditions have contributed significantly to changes in mineral content on fish.
Forecasting of salt demand using ARIMA model to prevent the bullwhip effect in salt supply chain
Authors: Novianti Trisita , Utami Issa Dyah , Prima Dania Wike Agustin 
Published: February 2022

Abstract
The volume of imported salt contributed roughly up to 50.29 percent in Indonesia. However, until the end of 2020, salt from domestic farmers reached 2.89 million tons. Based on these conditions, it is necessary to plan how to expand the distribution of local salt. Not only does distribute the salt to the domestic market, but also exports it, so the stock of salt does not accumulate in the warehouse. The work demonstrated in this article constituted to predict the demand of salt especially exported salt. This research utilized the historical demand data from 2014 to 2019 to predict the market of exported salt in Indonesia. The historical data were used to develop several models of autoregressive integrated moving average (ARIMA). This method was used to analysed how the forecast affected to supply chain and to prevent the bullwhip effect on it. The bullwhip effect could be known as the small fluctuations in retail demand level which could cause progressively larger fluctuation in demand at the distributor and supplier levels. The selected model corresponded to the ARIMA (1,0,1) of the tentative models with the smallest RSME value of 9.566. These results will provide to the manager of salt manufacturing to make decisions related to expand the salt market by exporting it rather than only distributing in domestic market.
Performance analysis and microstructure of brake shoe composite material made of pecan, aluminum, and pineapple leaf fiber
Authors: Mulia  , Supriadi  , Gunawan Safri 
Published: February 2022

Abstract
This research develops natural composite such as pecan, aluminum, and pineapple leaf fiber and polyurethane as matrix filler. The objective of this study is to get brake shoe performance in braking wheel and its micro structure. The ability in braking wheel rotation of 200 rpm and pedal load 2 kg, 200 rpm and pedal load 3 kg, 400 rpm and pedal load 2 kg, and 400 rpm and pedal load 3 kg for Honda Genuine Part (HGP) are 15.59m, 15.13m, 28.44m, and 27.85, respectively, and for composite brake shoe are 15.61m, 15.35m, 28.47m, and 27.99m, respectively. Microstructure tests with variation 200 rpm and pedal load 3 kg resulting carbon, oxygen, chlore, calcium, zirconium, aluminum with composition 68.06%, 24.56%, 0.82%, 0.51%, 0.16%, 0.33%, respectively on its surface. The conclusion shows that the motorbike brake shoe composite material is recommended as new material for brake shoe based on the experiment data.
Developing a measurement tool for assessing situation awareness of operator in the MCR of SMR
Authors: Suryono T J , Santoso S , Maerani R 
Published: February 2022

Abstract
Automated action is one of the main features in the modern main control room (MCR) of nuclear power plants including small and modular reactors (SMR). The automated systems can increase the safe operation of the plants and can make it easier for operators to monitor and control the plant. However, it can reduce the awareness of operators about the current status of the plant. This paper discusses a tool to measure the situation awareness of operators of MCR of Nuscale, one of SMR type reactor. The tool is developed based on the National Aeronautics and Space Administration Task Load Index (NASA-TLX) that measures operator workload that affects the situation awareness based on the 6 subscales: mental demand, physical demand, temporal demand, frustration, effort, and performance. The types of workloads of the operator are investigated and some questioners related to the 6 subscales are made. The result shows that the tool is suitable for assessing the situation awareness of the operator of MCR of Nuscale.