bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of FAST’ Best Working Paraboloid
Authors: Xiao Haitao , Wang Hanyun , Li Wenzhi , Yang Shanshan
Published: June 2022

FAST consists of an active reflector, a signal receiving system (feedback source cabin) and other devices, where the reflector is an adjustable sphere composed of a main cable net, reflective panel, actuator and other main parts. It obtains an ideal paraboloid for operation in line with the position of the heavenly bodies, and meanwhile, a reflective panel regulating model by fitting the paraboloid as much as possible based on this ideal paraboloid, and calculates the absorptance of the cable according to the reflection model of electromagnetic waves.
Offloading Strategy in Satellite-Ground Network
Authors: Li Yang , Wei-dong Ma , De-bin Wei
Published: June 2022

Subject to other constraints such as economic costs, limited ground network coverage and insufficient network service capabilities in remote areas have resulted in some unloading requests being rejected. In this paper, the satellite network is used as the supplement of the terrestrial network, and the satellite-ground fusion multi-layer MEC network is constructed to study the offloading strategy and resource allocation for multi-type tasks. Firstly, the priority of task unloading is divided, and then the optimization function is constructed with the goal of minimizing the system overhead, and the improved tabu search algorithm is used to solve the problem. Finally, the feasibility and superiority of the algorithm are verified by experimental simulation.
A Hybrid Particle Swarm Optimization and Single-Objective Slap Swarm Optimization Algorithm Based MPPT Strategy
Authors: Huang Ronggeng
Published: June 2022

Under inhomogeneous irradiance conditions, multiple peak characteristic of P-V curve reduces the efficiency of conventional trackers like incremental conductance control. A hybrid particle swarm optimization and single-objective slap swarm optimization algorithm (PSO-SOSSOA) based which is applied to maximum power point tracking (MPPT) strategy is presented. The PSO-SOSSOA adopts the particle swarm optimization algorithm in the early period of the algorithm operation and a modified single-objective slap swarm optimization algorithm (SOSSOA) in the remaining period. The simulation results reveal that the PSO-SOSSOA can successfully deal with global MPPT and exhibits performance advantages in terms of efficiency, search speed, and power oscillation compared with the SOSSOA.
Acoustic modeling of transformer combined with multi physical field coupling
Authors: Wu Zhengyang
Published: June 2022

To realize the state diagnosis of transformer by detecting the running sound signal of transformer, it is necessary to obtain the sound pressure distribution of transformer in normal state. Because the amplitude of the sound signal changes obviously during the operation of the transformer, this paper studies the overall operation noise of the transformer and verifies it with the sound signal collected on site. The multi physical field coupling analysis software COMSOL multiphysics is selected to solve the vibration acceleration and sound pressure distribution of dry-type transformer under rated state. By comparing the solution with the field data, the sound pressure law of the transformer under normal operation is studied.
A Group Learning based Optimization Algorithm Applied to UWB Positioning
Authors: Zhang XiuWei , Zheng WenYi , chen Yong
Published: June 2022

In dealing with optimization problems, metaheuristic algorithms have attracted much attention due to their simple structure and flexible characteristics. Inspired by the principle of teaching students in accordance with their aptitude, this paper proposed a novel metaheuristic algorithm——Group Learning based Optimization (GLBO) Algorithm, this algorithm is suitable for continuous optimization problems. The main idea of this method is to divide a class into three study groups according to their scores, and formulate different study strategies for them according to the characteristics of each group, so as to improve the scores of the whole class. To verify the performance of the algorithm, it is tested on the CEC21 Benchmark suit and applied to UWB positioning. The results show that the proposed method has excellent performance when dealing with continuous optimization problems.
Research on graph classification based on improved metric learning
Authors: Dai Miaomiao , Zhang Xiaohui , Chen Wenxia
Published: June 2022

Few-shot graph classification is to learn valuable information from limited labelled graph data for graph classification. However, although the traditional graph neural networks (GNNs) have been widely used in graph classification tasks, the problem of insufficient graph sample of many domains is ignored. At present, using meta learning method can greatly solve the problem of low data in many fields. However, when facing the new few-shot graph classification task, there are still fundamental difficulties in using the existing methods. In this paper, a novel loss function compared with prototype networks is proposed which takes both inter-class and intra-class distance into account, is applied to solve the problem of graph classification under the condition of few samples. In addition, combined with the existing idea of considering the structural features of graphs, using this idea can extract a more accurate representation of graph sample features, so as to improve the classification accuracy of the model. Extensive experiments on two data sets Chembl and TRIANGLES verify the effectiveness of our proposed method.
A New Black Widow Algorithm for Discontinuous Optimization in Cloud Task Environment
Authors: You Die , Zheng WenYi , Chen Yong
Published: June 2022

Task scheduling in cloud environment has received extensive attention due to its complex characteristics, and most of the previous methods ignore the discontinuity problem of workflow scheduling. Therefore, a new black widow optimization algorithm (NBWO) is proposed. NBWO proposed a new reproductive strategy to select excellent male individuals and female individuals to obtain better offspring. In NBWO, the number of female individuals is fixed, and males obtain mating rights through competition; NBWO improves the mutation strategy, which makes the exploration ability and development ability of the algorithm more balanced. Applying NBWO to cloud computing task scheduling, the experimental results show that NBWO has excellent performance in dealing with discontinuous optimization problems.
Development and application of data mining method for synthetic aperture radar image ship inspection based on big data application technology
Authors: Chang Ruili
Published: June 2022

Synthetic aperture radar belongs to the radar signal working in microwave band, which has the characteristics of strong penetrating performance, large area imaging, all-weather and so on, and is widely used in the civil field and military field. Especially in the background of the information era, synthetic aperture radar imaging technology has developed to different degrees, and the resolution of synthetic aperture radar images has been significantly improved, which is highly valued by the target detection field, and the detection of naval targets through the reasonable use of synthetic aperture radar images has become an important application direction in the field of marine remote sensing. Based on this, this paper analyzes the characteristics of ship targets in SAR images, analyzes the differences between them and optical images from different aspects, and then concentrates on the most common statistical models and prediction methods of clutter analysis in SAR images, proposes the most reasonable way of clutter distribution simulation, and then uses the experimental way to accurately evaluate the complex sea clutter in SAR images, so as to propose the similar characteristics of the ship detection method‥
Design of low-power CIC decimation filter based on nibble serial arithmetic
Authors: Gao Min , Yu Zongguang , Wan Shuqin , Shao Jie
Published: June 2022

Aiming at the problem of large area and high power consumption of traditional CIC (Cascade Integral Comb Filter) decimation filter, a folded multistage cascade CIC decimation filter is designed. The nibble-serial arithmetic and multiplexing technology are used to reduce the operation and storage logic unit, lower the cost and improve the utilization efficiency of system resources. The folded multistage cascade CIC decimation filter has a programmable structure of down sampling factor and can dynamically realize 1∼16 times extraction. It is suitable for communication systems with multiple channel bandwidths. In addition, the designed truncation module can optimize the effective accuracy of the final stage output.
Power Grid Multi-protocol Network Topology Based on Data Exchange Strategy
Authors: Qian Kejun , Li Yafei , Liu Yi , Zheng Zhong
Published: June 2022

With the combination of Internet of Things technology and smart grid, there are more and more application scenarios of Internet of Things in power system, which makes the whole power system more informationized and intelligent. In this paper, an intelligent data switching technology for power communication network based on multi-protocol label is proposed. The link structure model of mobile core network is constructed, and the TDMA protocol of the multi-protocol intelligent data switching node is designed by using route detection method. The dynamic routing decision and node rotation scheduling of the mobile core network are realized, and the intelligent data exchange performance is improved. Finally, the simulation experiment of the intelligent data exchange protocol is carried out, and the comparative experiment between the proposed method and other methods is carried out, which shows the superior performance of the proposed method in improving the intelligent data exchange capability of the mobile core network.
NL2SQL Generation with Noise Labels based on Multi-task Learning
Authors: Long Lingli , Zhu Yongjin , Shao Jun , Kong Zheng , Li Jian , Xiang Yanzheng , Zhang Xu
Published: June 2022

With the rapid development of artificial intelligence technology, semantic recognition technology is becoming more and more mature, providing the preconditions for the development of natural language to SQL (NL2SQL) technology. In the latest research on NL2SQL, the use of pre-trained models as feature extractors for natural language and table schema has led to a very significant improvement in the effectiveness of the models. However, the current models do not take into account the degradation of the noisy labels on the overall SQL statement generation. It is crucial to reduce the impact of noisy labels on the overall SQL generation task and to maximize the return of accurate answers. To address this issue, we propose a restrictive constraint-based approach to mitigate the impact of noise-labeled labels on other tasks. In addition, parameter sharing approach is used in noiseless-labeled labels to capture each part’s correlations and improve the robustness of the model. In addition, we propose to use Kullback-Leibler divergence to constrain the discrepancy between hard and soft constrained coding of noisy labels. Our model is compared with some recent state-of-the-art methods, and experimental results show a significant improvement over the approach in this paper.
A Compressed Sensing Reconstruction Algorithm Based on Hyperbolic Function
Authors: Wang Hui
Published: June 2022

The accuracy of the compressed sensing theory reconstruction algorithm is important for signal recovery. Sparsity Adaptive Matching Pursuit (SAMP) has a fixed step size in each iterative process of reconstruction, which has a significant impact on accuracy in actual use, often leading to overestimation and underestimation. In order to solve this problem, combined with the advantages of regular backtracking and variable step size, the article introduces the idea of retrospective in the atom selection stage. Then, the atoms are inspected using backtracking and re-screened. The algorithm uses regularization at the beginning to select atoms with higher energy and reduce the number of atoms in the candidate set at the threshold stage. During reconstruction, because the energy difference of the reconstructed signal decreases rapidly at the initial stage, and then the energy difference decreases slowly. This algorithm takes advantage of the large change rate of the hyperbolic function at the beginning and the slower change rate at the later stage. At first, a large step size is used. When the energy difference reaches a certain threshold, a small step size is used instead. After the actual simulation, the improved algorithm improves the reconstruction accuracy and the effect is better.
Self-Knowledge Distillation For the Object Segmentation Based on Atrous Spatial Pyramid
Authors: Wang Xiaobing , Zheng Yunfei , Zhang Xiongwei , Cao Tieyong , Li Chenming , Wang Xiulai , Wang Yong , Fang Zheng , Wang Yang
Published: June 2022

This paper presents an effective Self-Knowledge Distillation (SKD) framework via Atrous Spatial Pyramid Structure (ASPS), which is able to enhance the performance of the object segmentation network without increasing network parameters. In the framework, a lightweight object segmentation network is constructed to achieve the pixel-level object segmentation efficiently. A SKD learning model, including the SKD representation structure based on ASPS and loss function, is proposed to transfer the knowledge in the ASPS into our object segmentation network and improve its generalization ability. The experimental results confirm that compared with recent typical object segmentation networks, our object segmentation network contains the fewest parameters but achieves better performance. Moreover, the proposed SKD method achieves the best performance-boosting compared with recent SKD methods
Modeling and Research on Route Planning
Authors: Liu Ying
Published: June 2022

In view of the problem of fixed and mobile threat areas in the navigation of reconnaissance aircraft, this paper proposes to connect the position information with the time information, and build a distance matrix based on the ant colony algorithm to model and solve the optimal navigation route.This article is based on the problem of the threat area in the area where the reconnaissance aircraft is sailing, since the distance between two target points is no longer a straight line distance but a curve distance, so consider building a distance matrix.The simulation experiment results show that the algorithm proposed in this paper can select the optimal path faster and has good accuracy when traversing each target point.
A Hierarchical Intrusion Detection System Based on Machine Learning
Authors: Kong Dehua , Peng Sicheng , Zhai Yihong , Liu Zhangyuan , Zhang Luming , Wan Zixuan
Published: June 2022

The Intrusion detection system (IDS) is one of the most important tools for defending against abnormal flow and attack messages. Most of the existing IDSs use detection technology based on security policies, and there is a risk that it cannot be accurately analyzed and evaluated. Therefore, machine learning techniques provide a new direction for solving this problem. This paper uses and analyzes the CIC-IDS series datasets, but there is a data imbalance in this dataset. In order to solve the problem of data imbalance and reduce the accuracy of the model, this paper proposes a hierarchical detection model. Experiments have shown that the stratified detection module has good classification accuracy for attack types with a small sample size.
A simple implement of Q-learning in robot path planning
Authors: Gao Haoran , Liu Yujie , Su Shiqi , Yao Wetao
Published: June 2022

This paper firstly gives an introduction of robot path planning problem, which includes the brief definition of path planning, some representative methods and previous applications of Q-learning. Secondly, the paper compares some typical methods, like Breadth First Search and Depth-First-Search, A* and deep learning, with corresponding pseudo codes in detail. Their advantages and disadvantages are also listed in this part. Thirdly, we carry out a simple simulation experiment by applying Q-learning method. The experiment is clearly presented in several parts which includes environment establishment, realizing the Q-learning, simulation experiment and interpretation of the Q-table. In the end, a short conclusion summarizes the achievement of our results.
Research on mathematical modeling of order and transshipment optimal distribution
Authors: Cui Lin , Liu Yin , Liu Zhi
Published: June 2022

Aiming at the problems of production arrangement and ordering, this paper conducts quantitative analysis, overall analysis and individual analysis on the supply characteristics of 402 suppliers, and constructs a ratio ranking model of 402 suppliers in the past five years, which reflects the important mathematical model to ensure the production of enterprises. And multi-index evaluation model, comprehensive use of Matlab, Excel and other software programming to solve, to determine the 50 most important suppliers. On the basis of mathematical modeling, a control scheme is given, and further analysis is completed, so as to optimize the ordering and transportation of raw materials in the production enterprise.
Research on multi-motor coordinated control under load disturbance
Authors: Hu J S , Zhou Z Y
Published: June 2022

With the iterative development of industrialization and automation, more and more mechanical and electrical equipment rely on the joint operation of multiple motors, and the efficient operation of mechanical and electrical equipment benefits from the reliable cooperative control of multiple motors. Therefore, to ensure the stability of multi-motor coordination control and improve the precision of multi-motor coordination control has important practical significance. In this paper, the multi-motor master-slave controls structure and ring-coupling control structure with random disturbance are simulated and analyzed, and it is verified that the annular coupling control structure has stronger anti-interference ability and higher control accuracy under random load disturbance in the case of four-motor coordinated control.
Hybrid institution vacuum circuit breaker action time prediction
Authors: Dong Enyuan , Hou Peng , Wang Yongxing , Zhang Liyan , Tian Yu , Liu Geyang , Zhuang Ruida
Published: June 2022

Phase-control technology requires a sufficiently small dispersion of switching operation times, however, even though the switch itself is sufficiently stable, action time dispersion is still a key issue in phase-control technology due to various factors. In this paper, by building a simulation and test model of the hybrid mechanism, the action time variation caused by influencing factors such as fast switching temperature, capacitance voltage, capacitance degradation are investigated, and the test and simulation data are collated and analysed form a database. The Generalized Regression neural network has excellent prediction, self-learning, non-linear mapping and tolerance capabilities, and the prediction error of the GRNN algorithm is verified to be less than 0.2ms for the closing time.
Research on rolling bearing fault diagnosis based onTVFEMD-SVD and random forest algorithm
Authors: YANG Cheng
Published: June 2022

In order to solve the problem that it is difficult to extract the early fault of rolling bearing under the background noise, a rolling bearing fault diagnosis method based on TVFEMD-SVD and random forest algorithm is proposed. In this method, the original vibration signal of the bearing is decomposed into a series of eigenmode components with physical significance by using time-varying filtering empirical mode decomposition. The components with higher fault information are selected according to the kurtosis, and SVD decomposition is carried out. The singular values obtained by decomposition are input into the random forest as eigenvalues for bearing fault diagnosis. Experiments show that this method can effectively diagnose the fault of rolling bearing.
Transformer vibration fault detection based on spectrum analysis
Authors: Hu Yuan , Wu Peng , Li Yan , Zhao Penghui , Wang Ning , Zhang Shuai , Zheng Junguan , Hao Jianliang
Published: June 2022

Measuring the vibration signal of transformer is one of the ways to verify whether the transformer is faulty. In this paper, taking the vibration detection of transformer as the technical starting point, the signals before and after the vibration fault of transformer are compared by frequency spectrum analysis, and the vibration fault detection of transformer is realized. The vibration test system is constructed and tested in the field. The results show that the non-contact vibration sensor can be used to detect the uninterruptible power failure of the transformer through spectrum analysis and processing, which is simple, safe and reliable, and has good application value.
An optimization method for the inverted pendulum problem based on deep reinforcement learning
Authors: Zhu Shenghan , Liu Song , Feng Siling , Huang Mengxing , Sun Bo
Published: June 2022

The inverted pendulum problem is a classical problem. The inverted pendulum starting at a random position keeps moving upwards and aims to reach an upright position. The problem has been solved through some methods based on deep reinforcement learning (DRL) such as Deep Deterministic Policy Gradient (DDPG). However, DDPG also has disadvantages. Deterministic policy is not conducive to action exploration. Moreover, the Q value needs to be estimated reasonably accurately for the policy to be accurate. Nevertheless, at the beginning of the learning, there is a certain difference in the Q value estimation, and the parameters learned at this time are easy to deviate. Therefore, this paper combining AdaBound with DDPG algorithm proposes an optimization method for the inverted pendulum problem, and compares the performance with that of four published baselines. The experimental results show that for the inverted pendulum problem, the proposed method outperforms the above four baselines to a certain extent.
LVF-based FBG interrogation simulation calculation
Authors: Liu Zhaoyi
Published: June 2022

We propose a miniature FBG(Fiber Bragg Grating) interrogation based on the LVF(Linear Variable Fliter ), which is very suitable for measurements in aircraft because of its small size, light weight and vibration insensitivity compared to conventional interrogation. We analyzed the relationship between the performance of the interrogation and the optical properties of the LVF by simulating the light passing through the LVF demodulator by means of theoretical simulations before the actual construction of the instrument, and we also find that the inhomogeneous illumination of the incident light can impair the performance of the interrogation.
Optimization and Design of Key Expansion of SM4 Algorithm Based on ZYNQ
Authors: Feng YeJi , Liu XiaoDong , Jing Shuai , Yang XiaoTing , Hao FuQing , Mao YueJian , Yang ZiHeng
Published: June 2022

As the application of "China Intelligent Manufacturing" in the field of production becomes more and more extensive, it becomes crucial to ensure the security of information interaction between production equipment. China's domestic encryption algorithm - SM4 block encryption algorithm came into being. The algorithm consists of a key expansion function and an encryption and decryption function. The key expansion function collects 128-bit keys at a time, and generates thirty-two 32-bit encryption keys after XOR operation, nonlinear permutation operation (S-box) and linear shift operation.The XOR operation parameter CK of the original key expansion function is obtained by the modulo method, which is similar to the system parameter FK and is a fixed value. In order to reduce the risk of deciphering caused by fixed parameters, the lightweight two-dimensional chaos algorithm Hemon is introduced for optimization design. The system parameters used in the SM4 algorithm are randomly generated with the change of the key, which improves the security of the algorithm. And use the hardware encryption platform ZYNQ-7000 series model xc7z100ffv900-1 FPGA side design and implementation, relying on the hard to decipher of hardware encryption to complete the optimization of SM4 algorithm key exchange.
A Fault Tolerant Method Based on LQR for the Electric Motor Servo System
Authors: LIU Zhiyong , Jing Lei , Wang Xiaohong
Published: June 2022

In the paper, a PI fault tolerant method based on LQR (Linear Quadratic Regulator, LQR) is proposed for the coal mine motor servo system. In the proposed strategy, the proportional part is arranged in the feedback loop of the control system firstly, so that the PI control law can be described in the form of system state feedback. And then the PI fault-tolerant control law is obtained based on the PI control law, the parameters are adjusted adaptively with the LQR control method Finally, the proposed method was applied to an electric motor, the simulation illustrates the effectiveness of the proposed method.
Study of Full Composite Pole-Aluminum Conductor Composite Core System Ice-Shedding Response
Authors: An Liqiang , Zhang Luojia , Wang Zhixu
Published: June 2022

Full composite pole-aluminum conductor composite core system is gradually used in the 10kV distribution network. In order to study the different ice-shedding forms of the dynamic response of this distribution system, the author established a conductor-insulator and pole-conductor system with two finite element models to study the linear section and corner section of the line in different forms of ice-shedding and ice-shedding rate under the influence of the line ice-shedding response degree. The results show that the pole-conductor model is a good model for the design of distribution lines with carbon fiber cores. The results also show that the ice jump height of the pole-conductor model is smaller than that of the conductor-insulator model, which is related to the coupling relationship between the composite pole and aluminum conductor composite core. The stay wire of the corner pole will absorb most of the energy generated by ice-shedding. In addition, when non-uniform ice-shedding, the line vibration is more violent, the jump height is higher, and the maximum axial force generated after ice-shedding is greater, which has certain safety risks.
Defect Analysis and Process Improvement of Metal-Oxide Arrester
Authors: Wu Liwei , Guo Caihong , Wu Jinping , Xie Zhenzhen
Published: June 2022

Metal-Oxide Arresters are important equipment to ensure the reliable operation of power systems. An experimental protocol for judging the nature of MOA defects accurately is introduced in this paper and applied to engineering practice. Through diagnostic tests and dismantling inspections, it is determined that a certain batch of 110kV line MOA has a familial defect of poor sealing. Then, the reasons for dampness are analyzed, and other defects except the dampness of the varistor are discovered. Besides, the improvement of manufacturing process is proposed from aspects of terminal structure and the coating material on the side of varistor;the actual data proves that adding fillers such as quartz sand or silica gel inside the MOA can reduce the failure rate effectively. This article provides a certain technical reference for the manufacture and defect disposal of MOAs.
Design of Control System for a new Intelligent Tree-climbing and Pruning Robot
Authors: Yang Xi , Gan Tuanjie , Zheng Hai , Cai Quishen , Chen Yan
Published: June 2022

This paper designed the control system of a new intelligent tree-climbing and pruning robot which included the control of remote control mobile terminal and intelligent control terminal. Remote control module, power circuit, motor drive, automatic holding detection, height detection, side branch detection and other modules were designed, Then the main program based on STM32 embedded MCU, interrupt program and communication program were designed. The control system could enable the tree climbing robot to climb automatically, detect the side branches in the climbing process, trim the side branches automatically, and saw the top branch after climbing to a certain height. The robot also had the function of image monitoring. Through image monitoring, the working process of the robot could be adjusted remotely. Finally, the prototype was tested. The test results showed that the selection of controller and sensors were appropriate, the design of remote control circuit, motor driving circuit and detection circuit was reasonable, and the structure and algorithm of the program were reasonable. The development of the prototype laid a foundation for the popularization of fast-growing forest pruning robot.
A novel contour error evaluation index of the five-axis machine tools
Authors: Fu Meng , Wang Liping , Guan Liwen , Chen Yanyu
Published: June 2022

The accuracy of high speed five-axis machine tool is mainly determined by the contour accuracy of machine tools. The contour accuracy evaluation and improvement of 5-axis machine tools have always been concerned. In order to simplify the calculation of five-axis contour error considering the synchronization between tool tip position and tool orientation, a novel five-axis contour evaluation index TCCE(Two-point Cutter location Contour Error) is proposed in this paper, which is based on the tool axis trajectory surface. The calculating method of the proposed index by NC servo encoder input from 5-axis machine tools is introduced. Finally, the experiment is performed to evaluate the trajectory accuracy and servo matching performance of the machine tool with the proposed contour error evaluation index and the calculating method.
Biomimicked large-area anisotropic grooves from Dracaena sanderiana leaf enhances cellular alignment and subsequent differentiation
Authors: Yadav Shital , Majumder Abhijit
Published: June 2022

Cellular alignment is important for the proper functioning of different tissues such as muscles or blood vessel walls. Hence, in tissue engineering, sufficient effort has been made to control cellular orientation and alignment. It has been shown that micro-and nanoscale anisotropic topological features on cell culture substrates can control cellular orientation. Such substrates are fabricated using various lithography techniques such as photolithography and soft lithography. Although such techniques are suitable for creating patterns in small areas to establish a proof-of-concept, patterning large areas with intricate features is an unsolved problem. In this work, we report that a replica of the groove-like anisotropic patterns of the abaxial side of a Dracaena sanderiana (bamboo) leaf can be used for large-area patterning of cells. We imprinted the leaf on polydimethylsiloxane (PDMS) and characterised its surface topography using scanning electron microscopy. We further cultured bone marrow human mesenchymal cells (BM-hMSCs), skeletal muscle cells (C2C12), and neuroblastoma cells (SHSY5Y) on the patterned PDMS on which the cells orient along the direction of the grooved pattern. Further, we observed enhanced neuronal differentiation of SHSY5Y cells on biomimicked pattern compared to flat PDMS as measured by percentage of cells with neurites, neurite length and the expression of neuronal differentiation marker beta-III tubulin (TUJ1). This process is simple, frugal, and can be adopted by laboratories with resource constraints. This one-step technique to fabricate large-area anisotropic surface patterns from bamboo leaves can be used as a platform to study cellular alignment and its effect on various cellular functions, including differentiation.
Detection of passageways in natural foliage using biomimetic sonar
Authors: Wang Ruihao , Liu Yimeng , Müller Rolf
Published: June 2022

The ability of certain bat species to navigate in dense vegetation based on trains of short biosonar echoes could provide for an alternative parsimonious approach to obtaining the sensory information that is needed to achieve autonomy in complex natural environments. Although bat biosonar has much lower data rates and spatial (angular) resolution than commonly used human-made sensing systems such as LiDAR or stereo cameras, bat species that live in dense habitats have the ability to reliably detect narrow passageways in foliage. To study the sensory information that the animals may have available to accomplish this, we have used a biomimetic sonar system that was combined with a camera to record echoes and synchronized images from 10 different field sites that featured narrow passageways in foliage. The synchronized camera and sonar data allowed us to create a large data set (130 000 samples) of labeled echoes using a teacher–student approach that used class labels derived from the images to provide training data for echo-based classifiers. The performance achieved in detecting passageways based on the field data closely matched previous results obtained for gaps in an artificial foliage setup in the laboratory. With a deep feature extraction neural network (VGG16) a foliage-versus-passageway classification accuracy of 96.64% was obtained. A transparent artificial intelligence approach (class-activation mapping) indicated that the classifier network relied heavily on the initial rising flank of the echoes. This finding could be exploited with a neuromorphic echo representation that consisted of times where the echo envelope crossed a certain amplitude threshold in a given frequency channel. Whereas a single amplitude threshold was sufficient for this in the previous laboratory study, multiple thresholds were needed to achieve an accuracy of 92.23%. These findings indicate that despite many sources of variability that shape clutter echoes from natural environments, these signals contain sufficient sensory information to enable the detection of passageways in foliage.
Past and projected climate change impacts on heat-related child mortality in Africa
Authors: Chapman Sarah , Birch Cathryn E , Marsham John H , Part Chérie , Hajat Shakoor , Chersich Matthew F , Ebi Kristie L , Luchters Stanley , Nakstad Britt , Kovats Sari
Published: June 2022

Children (<5 years) are highly vulnerable during hot weather due to their reduced ability to thermoregulate. There has been limited quantification of the burden of climate change on health in sub-Saharan Africa, in part due to a lack of evidence on the impacts of weather extremes on mortality and morbidity. Using a linear threshold model of the relationship between daily temperature and child mortality, we estimated the impact of climate change on annual heat-related child deaths for the current (1995–2020) and future time periods (2020–2050). By 2009, heat-related child mortality was double what it would have been without climate change; this outweighed reductions in heat mortality from improvements associated with development. We estimated future burdens of child mortality for three emission scenarios (SSP119, SSP245 and SSP585), and a single scenario of population growth. Under the high emission scenario (SSP585), including changes to population and mortality rates, heat-related child mortality is projected to double by 2049 compared to 2005–2014. If 2050 temperature increases were kept within the Paris target of 1.5 °C (SSP119 scenario), approximately 4000–6000 child deaths per year could be avoided in Africa. The estimates of future heat-related mortality include the assumption of the significant population growth projected for Africa, and declines in child mortality consistent with Global Burden of Disease estimates of health improvement. Our findings support the need for urgent mitigation and adaptation measures that are focussed on the health of children.
Plant Distance Effect on Rice Cultivation System of Rice Intensification (SRI) Method on Tillers and Yield Numbers in East Sumba Regency
Authors: Nugroho B D A , Arif C , Nihayah B , Hapsari U , Suryandika F
Published: June 2022

SRI is known as a set of methods to increase the productivity of paddy fields by changing the management of yields, soil, and fertilizers/nutrients. The main components of using the SRI method include: transferring young seedlings, planting one seed per hole, wide spacing, keeping the soil moist and not stagnant, controlling weeds by manual weeding, and adding soil organic matter. The study aims to determine the number of SRI rice tillers based on different spacing treatments and their effect on yield productivity. The results of the two treatments of plant spacing, namely 30 x 30 cm (A) and 20 x 10 cm (B) based on statistical tests using the T-Test, showed no significant difference between the two treatments on the number of tillers produced. While the yield showed that treatment A produced 4.27 tons/ha and treatment B was 4.7 tons/ha, so it concludes that spacing (A) had higher crops than spacing (B).
Exploring the effect of different number of periods in Thailand natural rubber supply forecasting models
Authors: Pumkaesorn P , Paoprasert N H
Published: June 2022

To dates, many studies attempted to forecast the price of natural rubber while many others also attempted to forecast the amount. The objective of this study was to explore the effect of different number of periods used in various forecasting models for the amount of natural rubber in Thailand. Monthly data from the Office of Agricultural Economics in the years 2007-2019 were obtained. Then the data were classified into 12 data sets; each of which had different number of periods including 12, 24, 36, 48, 60, 72, 84, 96, 108, 120, 132 and 144 months. Decomposition forecasting methods consisted of the addition divide and the multiplicative divide methods were adopted. Model accuracy indicators were the mean absolute deviation, the mean square error and the mean absolute percentage error. The results showed that the amount of natural rubber and time were positively correlated at 99% confidence level. The most suitable model for forecasting the amount of natural rubber in Thailand found in our study was the multiplicative divide method by using the number of periods at 36 months yielding the mean absolute deviation of 66,264.61, the mean square error of 7,988,871,007.41 and the mean absolute percentage error of 24.66%.
Effect of Production Technique on Corncob Biochar Quality
Authors: Anika Nova , Mahardika Melbi , Panjaitan Jabosar Ronggur Hamonangan , Achmad Feerzet , Bindar Yazid , Azizah Intan N. , Anggraini Riska , Ramadhani Dhiya A.
Published: June 2022

Lampung Selatan Regency is one of the centers of corn production in Lampung, Indonesia. Along with the increase in corn production, the resulting corn biomass waste also increases. Corn biomass waste such as cobs can be utilized into more useful products such as biochar which is useful as a soil amendment. The purpose of this research was to evaluate the quality of biochar based on its production technique. The three biochar production techniques used were traditional soil pit, closed drum kilns, and open drum kilns.. The quality of biochar was determined by the temperature and period of the pyrolysis process, which was greatly influenced by the selected production technique. The results showed that the closed drum kiln technique produces biochar with better properties for increasing soil fertility because it produces the biochar with the highest fixed carbon and CEC.
Development Software to Evaluate Environmental Impact for Palm Oil (Elaeis guineensis Jacq) Industry using Life Cycle Assessment Approach in Indonesia
Authors: Siregar Kiman , Supriyanto  , Susanto Dwi , Setiawan Arief AR. , Sofiah Intan , Solihati
Published: June 2022

Palm oil in Indonesia are producing the Crude Palm Oil (CPO) with the highest export in the world. CPO production in Indonesia are increasing from 17,77 million to 31,49 million tons from 2013 to 2013 and still increases. Currently Indonesian government projected to use palm oil as source to produce biodiesel to replace the fossil fuel. However, to evaluate the production of biodiesel from palm oil should consider the environmental aspect. Life cycle assessment are appropriate tools to evaluate the overall productions environmental impact in palm oil industry. In this research, we proposed a software to life cycle assessment application in palm oil industry in Indonesia. The method was used in this study are prototyping that consist of the iteration analysis, design, coding and testing. The result of this study was the software to evaluate the environmental impact using life cycle assessment approach. Software was able to perform life cycle assessment activity such as goal scope definition, inventory data, life cycle impact assessment and interpretations.
Artificial Neural Network Models to Estimate Growth of Melon (Cucumis melo L.) at Vegetative Phase in Greenhouse with Evaporative Cooling
Authors: Erniati  , Suhardiyanto Herry , Hasbullah Rokhani , Supriyanto
Published: June 2022

Currently, melon is a high economic value product in Indonesia. To optimize the production of melon, cultivation in greenhouses equipped with evaporative cooling system is implemented in some locations. However, growth of melon in greenhouse with evaporative cooling is characterized by complexity in its relation with environmental parameters inside the greenhouse. Therefore, it is important to establish stochastic model to explain the relation between the growth of melon with environmental parameters inside the greenhouse. This paper presents an Artificial Neural Network (ANN) model to predict the growth of melon during vegetative stage of melon in a greenhouse with evaporative cooling in Bogor, Indonesia. Data was collected from October to December 2020 during vegetative stage of melon. The ANN model was developed using six input parameters that are air temperature (°C), air relative humidity (%), radiometric intensity of sunlight (watt/m2), plant age (day), leaf area (cm2), plant height (cm) to predict leaf area (cm2) and plant height (cm) for the next two days. The results showed that the designed seven hidden nodes-ANN model achieved a high prediction accuracy with R2 of 0.9 for leaf area validation and plant height validation.
Coconut shell bio-oil distillation: Its characteristic and product distribution
Authors: Amrullah Apip , Eko Teguh S.
Published: June 2022

The properties of bio-oil distillation and product distribution are critical for parameter optimization and reaction conditions. In this work, low-reaction temperature of 96, 97, 98, 99, and 100 °C was conducted. The slow pyrolysis process at 500 °C with a 1 hour holding period yielded the coconut shell bio-oil employed in this research. The characteristic components of bio-oil were thoroughly evaluated using gas chromatography-mass spectrometry (GC-MS). The research founded that during the distillation reaction process, a similar critical point was thoroughly established, which might be attributed to the steady system created by the hydroxyl group. As a result, bio-oil distillation might be divided into 3 stages: steady, explosive, and heating. The content of acetic acid, 2-Furancarboxaldehyde, and phenol are dominated. Acetic acid yield showed an increase, followed by the distillation reaction temperature. Phenol yield was also observed as a dominant product in the bio-oil. The higher phenol yield was observed at a temperature of 98 °C is 38 %. The observed phenomena could be related to the oxidation of hemicellulose, cellulose, and lignin to form phenol, the bio-major oil component. The specific distillation properties and product distribution provide a great look at the reaction process and component enrichment patterns, which can aid formulation and parameter adjustment.
Delignification of Cassava Peel as Bioethanol Raw Material using Combined Alkali and Microwave Heating Methods
Authors: Hartulistiyoso Edy , Farobie Obie , Zaky M
Published: June 2022

Indonesia is ranked fourth as the largest cassava producing country with a total production of around 20 million tons per year. As much as 15-20% per kilogram of cassava is waste in the form of cassava peel which contains starch and allows it to be converted into alternative energy such as bioethanol. The bioethanol production process is carried out through the stages of pretreatment (delignification) to obtain cellulose used in the hydrolysis process, hydrolysis, fermentation, and purification. This paper discussed the use of combined alkali and microwave heating methods to increase the cellulose content and reduce the lignin content of cassava peel. Delignification was carried out by varying the NaOH concentration of 0.5, 0.75, and 1 M and microwave exposure of 5, 10, and 15 min. The data of the pretreatment variation were statistically tested using a completely randomized design. The results shows that combined alkali and microwave heating methods was able to increase cellulose content from 39.78 to 59.01 %, decrease hemicellulose content from 24.75 to 12.79 %, and decrease lignin content from 23.28 to 14.66 %. The combination of 1 M NaOH and 15 min microwave exposure showed the best results.
Design and performance test of biodiesel reactor using hellical screw agitator and baffles
Authors: Wulandani D , Ibrahim Z A
Published: June 2022

Biodiesel reactor model using hellical screw agitator and baffles have been designed. The hellical screw type is chosen based on the agitation ability on viscous liquid with low energy, while baffles is purposed to generate homogeneous mixing. The objectives of the research was to obtained biodiesel reactor model and determined the best operation of reactor in producing biodiesel. Performance test of biodiesel reactor was done at 10 rotation speed levels of agitator, at range of 100 rpm until 1000 rpm. Biodiesel was produced by catalytical method, with 1.5 % w/w KOH catalyst at temperature ranging from 60 °C to 65 °C, for 60 minutes. The research obtained the model of cylindrical biodiesel reactor with the height of 300 mm and 168 mm diameter. The helical screw agitator has 4 screws and is equipped 4 baffles installed at the reactor wall. Based on the saponification value analysis, the biodiesel contained 99 % w/w methyl ester. The best operation of biodiesel production is resulted at 100 rpm which fulfil the quality standard of biodiesel and has the lowest energy consumption.
Comparison of engine performance and emissions for fuels of diesel-biodiesel blends and pure biodiesel
Authors: Firdaus NK , Aunillah A , Wardiana E , Pranowo D , Herman M , Syafaruddin
Published: June 2022

Biodiesel is a substitute or replacement petroleum diesel fuel used to reduce pollution without modifying engines. This study aimed to investigate the engine performance and emissions characteristics of a passenger car engine (Hilux 2.4G Double cabin (4x4) M/T) fuelled by two different fuels, which is biodiesel (B100) and diesel-biodiesel fuel blend (B20). The study was conducted at the Bioenergy Laboratory of Balittri, the Thermodynamics and Propulsion Engine Research Center of BPPT, and the Research Center for Oil and Gas Technology Development (LEMIGAS), from November 2019 to February 2020. The result showed that the traction and power for diesel-biodiesel fuel blends were obtained slightly higher than biodiesel. Biodiesel has marginally higher fuel consumption than diesel-biodiesel fuel blends. According to the emission analysis, biodiesel produces lower exhaust emissions of unburned fuel emissions, carbon monoxide, and carbon dioxide content in the exhaust gas than diesel-biodiesel fuel blends.