bluuebunny/crossref_metadata_2025_split huggingface dataset:
Asynchronous Federated Learning for Elephant Flow Detection in Software Defined Networking Systems
Authors: Ma Xiaohang , Liao Ling Xia , Li Zhi , Chao Han-Chieh 
Published: April 2022

Abstract
This paper introduces an Asynchronous Federated Learning (AFL) approach to train an elephant flow model over Software Defined Networking (SDN) systems with distributed controllers. The AFL addresses the issues of data privacy and communication overhead in collecting network statistics over large-scaled SDN systems. It allows each local controller to train a local model based on its local statistics using Decision Tree and upload the local model to the root in an asynchronous manner, so that the root controller can aggregate each local model into a global model once a local model is received to improve its time efficiency. The AFL proposes to weight the performance of each local model to form the global model. The evaluation based on 5 real packet traces demonstrates the accuracy of the AFL is better than any local models and two classical federated learning approaches.
Loop Closure Detection for SLAM Based on Siamese Convolutional Neural Network
Authors: Li Xiang , Xu Gang , Zhang Xingyu , Yu Ze , Zhu Zhimin 
Published: April 2022

Abstract
Loop closure detection is an indispensable part of the SLAM system, which can reduce the cumulative error of mobile robots in positioning and mapping. This paper proposes a supervised learning method, which combines the Siamese network and the VGG16 network in deep learning to handle loop closure detection. The Siamese network method and the traditional method are contrasted in the New College and City Centre data sets to prove the method’s usefulness in this research. The experiment’s findings reveal that the method of this paper ensures precision and recall rate while reducing the time necessary to assess similarities compared to the traditional method. It has a better chance of achieving real-time SLAM.
Channel Attention Module for Efficient Action Recognition
Authors: Cheng Xianpeng , Lu Fei , Han Xiangzu , Yuan Ying , Tian Guohui , Wu Hao 
Published: April 2022

AbstractFor action recognition, 3D CNNs can achieve satisfactory performance, but they are parameter-rich and computationally intensive. Although conventional 2D CNNs have a small computational burden, they do not capture the channel relationships well. To mitigate this issue, we propose a plug-and-play channel attention module that is simple yet effective. Our CA module can perform adaptive refinement of the feature for the given input feature map by capturing channel-wise dependencies. Since the CA module is generic and lightweight, it can be easily integrated into regular convolutional neural networks. We embedded the CA module into TSM and evaluated it by conducting extensive experiments on the commonly used action recognition dataset: Kinetics-400 and gesture recognition dataset: Jester. For Kinetics-400, our CA module was able to improve the top-1 accuracy by 1.24%, 1.46%, 1.43% and 1.53% when using one crop, three crops, five crops and ten crops, respectively. Our experimental results showed that the CA module brings consistent performance improvements, proving the effectiveness of the CA module.
Droplet Image Reconstruction Based on Generative Adversarial Network
Authors: Zhang Jinsong , Chen Haiyan , Wang Zhiliang 
Published: April 2022

Abstract
In the digital microfluidic experiments, the improper adjustments of the camera focus and background illumination lead to the phenomena of low illumination and blurred edges in the droplet image, which seriously interferes with information acquisition. Removing these blurred factors is an essential pretreatment step before information extraction. In this paper, a generative adversarial network model combining multi-scale convolution and attention mechanism is proposed to reconstruct the droplet image. The feature reconstruction module in generator can reconstruct the image feature maps from multiple scales. The fusion module is used to fuse the multi-scale feature maps into a reconstructed sharp image. The new model was trained on the data set which was made by the Style Transfer. Experimental results show that the proposed model can significantly improve the visual quality of images, effectively reduce the blur and improve the background illumination.
An Elderly Indoor Behavior Recognition Method Based on Improved SlowFast Network*
Authors: He Junping , Xiang Min , Zhao Xiaoxiang 
Published: April 2022

Abstract
Due to the limited resources of home-based elderly care monitoring equipment, how to accurately identify the elderly behavior is a hot issue concerned by many equipment manufacturers. A behavior recognition method suitable for embedded equipment is proposed. This method first introduces the TPN module in the SlowFast network to capture the visual action tempo of the elderly and uses Faster-CNN to detect the elderly and objects in the video frames. Then in the AIA module, the accuracy of the elderly indoor behavior recognition is improved by strengthening the correlation between the elderly and the objects. Experiments show that the improved network can run stably at 18FPS on Jetson Xavier NX. The indoor behavior recognition accuracy for the elderly reaches 90.61%, which is 8.25% higher than the original SlowFast network.
Multi-label Image Classification Model via Label Correlation Matrix
Authors: Huang Tianxi , Wu Dongdong , Duan Guiduo , Huang Hao 
Published: April 2022

AbstractMulti-label classification is one of the most essential tasks of computer vision. In the multi-label image classification model, using the correlation between labels is a powerful method for improving the classification effectiveness of the model. However, common methods ignore the interrelationship between the label pairs. On the other hand, introducing a spatial attention mechanism into the model could also improve the classification effectiveness of the model. However, most methods that use the attention mechanism module do not use the correlation information between labels. To solve these issues, we propose a novel multi-label image classification model using the label correlation in the paper. Our model generates label word vectors based on the BERT model that can describe the potential relationship between labels. And then we combine these vectors with static statistics information on labels to construct a new label correlation matrix. Moreover, we introduce label semantic information into the spatial attention mechanism. With the semantic information, the generated spatial attention map could focus on the image feature regions with label correlation, and complete the accurate classification of the model. On the Microsoft COCO data set, this model achieves the best score of 84.3% on mAP, which shows the effectiveness of our model.
Design of an Internet of Things — based multi-channel temperature monitoring system
Authors: Clerbaux B. , Gómez de Gracia D. , Petitjean P. , Yang Y. 
Published: April 2022

Abstract
In the scope of the Jiangmen Underground Neutrino Observatory (JUNO) project, 6 back-end card (BEC) mezzanines connected to one BEC base board are in charge of compensating the attenuated incoming data from 48 front-end channels over 48 100-meter-long Ethernet cables. Each of the mezzanines has 16 equalizers that may be subject to overheating. It is important therefore to monitor their temperature in real time. However, collecting data from a relatively large (1080) number of mezzanines is not a trivial task. In this work we propose a solution based on Wi-Fi mesh. Both the technical details and the first test results performed are reported.
Study of the spatiotemporal structure of extensive air showers at high energies
Authors: Kalikulov O.A. , Saduyev N.O. , Shaulov S.B. , Zhukov V.V. , Beznosko D. , Mukhamejanov Y.S. , Yerezhep N.O. , Baktoraz A.Y. , Shinbulatov S.K. , Utey Sh. , Zhumabayev A.I. , Sedov A.N. , Oskomov V.V. 
Published: April 2022

Abstract
In a series of works carried out at the Tien-Shan High Altitude Science Station (TSHASS), a penetrating component of extensive air showers (EAS) caused by cosmic rays (CR) with energy of the primary particle above 1 PeV was discovered. The local increase in the energy of secondary hadrons in the EAS cores in the region of the CR spectrum slope change around energy of 3 PeV, the so-called “knee”. The problem of knee formation currently is one of the currently still open mysteries in astrophysics. The studies carried out at the TSHASS show that more information on the knee region can be obtained by studying the characteristics of the EAS cores. At present, a large installation with an area of several hundred square meters is being constructed at the station to study the EAS cores in the “knee” region. The installation is located at an altitude of 3330 meters above sea level near the city of Almaty, Kazakhstan.
Save our soil from heavy metals (Pb and Cd) accumulation for rice growth
Authors: Budianta D , Napoleon A , Merismon  , Habi M L 
Published: April 2022

AbstractRice intensification has been very successful in Indonesia and was even appreciated by FAO in 1985. However, despite the success, paddy soils are frequently polluted with Pb and Cd which are mostly derived from phosphate (P) fertilizers. Considering that the soils have been used for the long-term cultivation, Pb and Cd contents both in the soil and rice have exceeded the tolerance level in food as defined by WHO namely 2 and 0.24 mg kg-1, respectively. The highest Pb and Cd were found in soils cultivated for 80 years in Musi Rawas, Indonesia with values of 20.56 mg kg-1and 0.72 mg kg-1for soil and 3.11 mg kg-1and 0.29 mg kg-1for rice, while the lowest was found at 20 years with values of 17.82 mg kg-1and 0.26 mg kg-1. Furthermore, the highest rice Pb and Cd were obtained at 80 years of cultivation with values of 3.11 and 0.29 mg kg-1, respectively, while the lowest was found at 20 years with values of 2.35 mg kg-1Pb and 0.15 mg kg-1Cd. Therefore, these metals need to be managed immediately. One of the methods to detoxify heavy metals is by application of organic material. Through a chelating process, heavy metals are immobilized and not absorbed by rice. Based on the results, rice straw biochar and compost at a rate of 10 tons ha-1separately reduced Pb and Cd in soil from 13.60 to 3.00 mg kg-1and 13.60 to 5.98 mg kg-1for Pb and 0.62 down to 0.29 mg kg-1and 0.64 down to 0.42 mg kg-1for Cd, respectively.
Effect of combination of inorganic fertilizer and biochar-coastal sediment on nutrient availability and growth of corn plants in alluvial soil
Authors: Sulakhudin  , Manurung R , Abdurrahman T , Karpriana A P 
Published: April 2022

Abstract
Fertilizer is one of the inputs in plant cultivation that requires high costs. However, unfavourable soil conditions so that most of the nutrients contained in fertilizers cannot be absorbed by plant roots. The purpose of this study was to increase the availability of nutrients and plant growth by applying a mixture of biochar – coastal sediment with inorganic fertilizers on alluvial soil. The study was a single factor experiment arranged in a completely randomized design with five replications. Treatment consisted of A: without giving fertilizer, treatment B: giving inorganic fertilizer 100% of the recommended dosage, treatment C: inorganic fertilizer mixed with biochar and coastal sediment 75% + 25% fertilizer recommended dosage, treatment D: inorganic fertilizer mixed with biochar and coastal sediment 50% + 50% fertilizer recommended dosage and treatment, E: inorganic fertilizer mixed with biochar and coastal sediment 25% + 75% fertilizer recommended dosage and treatment F: inorganic fertilizer mixed with biochar and coastal sediment 100% recommended dosage. The application of inorganic fertilizer mixed with biochar and coastal sediment 100% recommended dosage was able to increase the availability of nutrients P, K, Mg and growth of corn plants in Alluvial.
Can application of organic matter, cover crops and tree planting improve infiltration rate of soil covered by pyroclastic materials?
Authors: Agustina C. , Utami S.R. , Kusuma Z. 
Published: April 2022

Abstract
Pyroclastic materials from volcanic eruption is easily compacted and may develop surface crust, which potentially decreases water infiltration. We conducted research in Ngantang, regularly affected by Mt. Kelud eruption, as an attempt to improve water infiltration using organic matter and cover crop. The organic matter (20 Mg.ha-1) used was sweet potato leaves (Bsp) and Tithonia diversifolia leaves (Btd). Cover crops (Arachis pintoi (Tap) and Tithonia diversifolia (Ttd)) and tree (Paraserianthes falcataria (P1)) were planted. Ring infiltrometer was used to measure infiltration rate on initial soil, on soils covered by pyroclastics after 3 months organic matter and cover crops application, and after one year tree planting. The result showed that infiltration rate of initial soil was significantly decreased with time, when covered by eruption materials. After 3 months application of organic matter and cover crops, infiltration rate was significantly higher than untreated soil covered by volcanic materials. Planting tree increased infiltration rate with the highest infiltration rate occurred in combination with organic matter Tithonia diversifolia leaves and Tithonia diversifolia cover crops. Infiltration rate increased with increasing total pores, but decreased with increasing of meso-pores, especially 12 months after application organic matter, together with planting cover crops and tree.
Characteristics of peat functional group in Padang Island, Indonesia
Authors: Devangsari I M , Nurudin M , Sartohadi J , Karmila Y A 
Published: April 2022

Abstract
Peat is composed of a diverse range of polar and nonpolar groups. Nonpolar groups, particularly those composed of aliphatic structures, tend to associate with one another and are therefore water-repellent (hydrophobic), a property that increases with the length of the chain of bonds. The drying process causes the nonpolar groups to interact with each other and form a long chain of bonds, reducing the ability of peatlands to bind water. As a result, it is vital to understand the chemical characteristics and functional groups associated with hydrophilicity and hydrophobicity. The chemical analysis comprises the following: ash content (500°C combustion method), C-org using the combustion method, N-total by Kjeldahl method, actual pH with soil water ratio of 1:5, and cation exchange capacity with NH4Oac pH 4.0. Additionally, the pelletized peat was examined for its constituent groups using an FTIR spectra and the Flaig et al., method (1975). Soil pH values on Padang Island ranged from 3.61 to 4.35 and the content of bases Ca, Mg, K, and Na in oligotrophic peat is very low, especially in thick peat (0-5 m). C-organic levels on Padang Island peat ranged from 4.42 to 53.32 percent, according to the results of the analysis. Peat with a thickness 0-5 m has functional groups dominated by C-O from ester, eter, fenol, while peat with a thickness 5-7 m, 7-9 m, >9 m is dominated with H OH group bonds, free OH.
The Effect of Food Consumption Management on the Reduction of Food Waste in Indonesia
Authors: Mulyo J.H. , Widada A.W. , Perwitasari H. , Sugiyarto  , Rohmah F. 
Published: April 2022

Abstract
Food waste is one of the important problems faced by households because it is related to the availability of food in the community. In addition, food wastage is suspected to be closely related to the ineffective and inefficient of food consumption management. This study aims to determine food consumption management, food waste and the effect of food consumption management on food waste in four major cities in Indonesia, namely Yogyakarta, Surabaya, Medan and Denpasar. The latent variable of food consumption management is reflected by four indicators, they are food planning, processing and storage, and food waste disposal. Meanwhile, the latent variable of food waste is reflected by three indicators, including opportunities for food wastage, knowledge about food wastage, and skills in managing food. Indicators in each latent variable is measured using a Likert scale. The data collection method is convenient sampling to get 150 households’ sample from the four big cities. Food consumption management and food waste were analysed descriptive qualitatively, while the effect of food consumption management on food waste was analysed using the Structural Equation Model (SEM). The results showed that the food planning indicators on the latent variable of food consumption management were in the very good category, while the other three indicators, namely food processing, food storage and food waste disposal, were in good category. The three indicators on the latent variable of food waste consisting of opportunities for food waste, knowledge about food waste and food management skills are included in good category. Furthermore, the results of the study show that good management of food consumption has a positive and significant effect on the efforts to reduce food waste at the household level in four major cities in Indonesia.
Factors Influenced Farmer’s Willingness to Continue Semi Organic Shallot Farming In Bantul District, Daerah Istimewa Yogyakarta
Authors: Torani D V , Suryantini A , Irham  
Published: April 2022

Abstract
The agricultural sector is a strategic sector and have an important role in the national economy and the survival of the community, especially in its contribution to GDP, providing employment and providing domestic food. For sustainable agriculture to protect the environment, overuse of pesticides has its drawbacks and its misuse can have serious health implications therefore immediately switch to eco-friendly agriculture with reduced chemicals. So it is important to know the factors that make farmers willingness to continue semi organic shallot farming. The purpose of this study was to find out how the level of willingness of farmers to continue semi-organic shallot farming in Bantul Regency, Yogyakarta and the factors that influence it. The study was conducted on 153 shallot farmers the members of Lestari Mulyo and Srunggo Farmer Group in Bantul District, D.I Yogyakarta. Data obtained by surveyechniques and processed using quantitative analysis. The results showed that the sustainability level of shallot farming willingness to continue by the economic, ecological and social aspect are quite sustainable. . To increase the willingness of farmers to continue their farming, it is necessary to optimize the role of farmer groups by involving government participation in farming training, marketing and economic benefits in semi-organic shallot farming.
Impacts of agricultural waste and NPK fertilizers on soil chemical properties, production and phosphorus uptake of sweet corn plants on ultisol soil
Authors: Panjaitan E , Sidauruk L , Manalu C J , Pratiwi S , Saragih M , Sianturi P 
Published: April 2022

Abstract
Ultisol soil is classified as a marginal terrain with a low productivity level. Thus, this research aims to determine the most fitting biochar material and the effects of NPK fertilizer regarding the chemical properties of Ultisol soil that are analyzed on the production and phosphorus uptake of sweet corn plants. The materials used for the biochar consist of agricultural waste. This research utilized factorial randomized block design which was repeated three times. Factor number one consisted of three types of biochar: rice husk, corncob, and coconut shell. Factor number two was made up of NPK fertilizer which consisted of three dosages: without NPK, 2 g pot-1, and 4 g pot-1. This research was conducted on December 2019 up to March 2020. Research shows that there was no interaction between biochar types and NPK fertilizer, whether on the chemical properties of Ultisol soil, growth parameter, and production nor phosphorus uptake of the sweet corn plants. Corncob biochar was better than other types in affecting the chemical properties of Ultisol soil, production, root dry weight and phosphorus uptake by the sweet corn plants. Application of 4 g pot-1 NPK fertilizer was the best for almost all observation parameters.
Satellite Remote Sensing Using Earth Observing System in Environmental Monitoring for Hydropower & Floating Photovoltaic Reservoir (Case Study: Algae Blooming on Cirata Reservoir, West Java-Indonesia)
Authors: Sibuea R T , Pratna R , Hapsari A , Kristi Y W 
Published: April 2022

Abstract
This paper describes the application remote sensing satellite for vegetation in the management of the Cirata Reservoir. This reservoir is a provider of raw water for the Cirata hydropower plant, which is the largest hydropower plant in Indonesia. In the next 2 years, the largest floating solar power plant in Indonesia and Southeast Asia will also be built here. The results of monitoring using Earth Observing System, the area of water hyacinth in the Cirata Reservoir is in the range of 100 to 400 hectares. Cleaning of water hyacinth per month is in the range of 25 to 75 hectares per month. This has not been able to compensate for the water hyacinth area cover that can develop, especially during the rainy season which has an impact on increasing the Water Level. Therefore, this paper also presents several management strategies that have been carried out. In Indonesia in particular, there are many reservoirs that have the potential for algae blooming disturbances and the potential for floating solar power plants in the future. The experiment conducted in Cirata can be an alternative in best practice management.
Systematic Review of the Efficiency of Aquatic Plants in the Wastewater Treatment
Authors: Palomino Seguil Y. , Vilchez Garay L. , Matencios Cortez C. , Cornejo Tueros J. , Camargo Hinostroza S. , Canales Guerra V. 
Published: April 2022

Abstract
Wastewater treatment uses a phytoremediation strategy that sets significant trends according to recent research from the 2019-2021 period, being one of the most efficient strategies regarding the removal of pollutants using artificial wetlands with aquatic plants. Therefore, the objective of the review article is to determine the efficiency of the aquatic plant in the phytoremediation process for the treatment of industrial, domestic, and municipal wastewater through a systematic mapping method that allows us to summarize the theoretical framework avoiding. The exclusions also have a comparative descriptive design for the study variables where it has been found that Eichhornia Crassipes is an aquatic weed that removed NO2- and NO3- up to 93% of industrial wastewater, in Pistia stratiotes it removed Turbidity (98.5%), N total (100%), P total (100%) and COD (79.18%) in household wastewater in 60 days. Finally, Azolla Filiculoides removed SO4
2- (83%), Cl (76%), PO4
3- (84%), NO3- (76%), COD (79%), BOD (63%) and EC (49%) from municipal wastewater in 21 days.
Polyethylene Terephthalate Waste as a Mobilizer for Heavy Metals in Gold Mine Tailings
Authors: Mashifana Tebogo 
Published: April 2022

Abstract
The accumulation of gold mine tailings (GMT) and polyethylene terephthalate plastic waste (PW) continue to impact the ecosystem negatively, and strategies are required to counteract these issues to maintain a sustainable environment. This study investigated the use of PW as a binder to mobilize heavy metals in GMT. Plastic was used as a binder to develop specimens. were developed using plastic as a binder, the geotechnical and geochemical properties of the specimens were studied. The leachability of heavy metals from developed specimens was also studied. GMT and PW ratios of 80:20; 70:30, and 60:40 were investigated. The mineralogy and elemental composition of GMT and developed specimens showed that was quartz and silicon oxide were the predominant constituent in the materials. The specimen with the highest unconfined compressive strength yielded the lowest water absorption. The concentration of heavy metals in the PW-based specimens was lower than in the raw GMT. Waste plastic can be used as a sustainable binder to mobilize contaminants in GMT. The proposed solution can solve and prevent environmental pollution caused by GMT and WP.