bluuebunny/crossref_metadata_2025_split huggingface dataset:
Compressing Deep Learning Model for Agile Moving Target Defense
Authors: Xu Xiaoyu , Hu Hao , Zhu Xianwei 
Published: January 2022

Abstract
The moving target defense achieves the effect of defending against network attacks by constantly changing the attack surface. IP hopping defense is a typical representative of network layer moving target defense technology. It has been verified to show considerable defense effect against DDoS attacks and scanning attacks. Aiming at the problems that the system resource overhead of the existing IP hopping defense technology is too large, an agile IP hopping defense technology based on compressed neural network is proposed in this paper. A convolutional neural network (CNN) is deployed to sense the attack. In the training, the CNN uses techniques of clipping and quantizing to make the trained model show low storage occupation and high processing efficiency. The lightweight CNN determines the current attack situation according to the flow table data uploaded regularly by each switch in the data plane. Then configure and trigger two different levels of IP hopping according to the judgment results. Experimental results show that compared with the current typical IP hopping defense methods, the proposed method can significantly reduce the system overhead, including storage occupation, channel occupation and so on. In terms of security, the performance of the proposed method is equivalent to the existing state-of-art method against DDoS attacks and scanning attacks.
Combining Imputation Method and Feature Weighting Algorithms to Improve the Classification Accuracy of Incomplete Data
Authors: Wang Yue , Guo Cong , Xiao Chunjing , Yang Wei 
Published: January 2022

Abstract
It is a common problem that datasets in pattern classification tasks contain missing values. In order to deal with missing values, the K-Nearest Neighbor Imputation method with Euclidean distance is often used to find K nearest neighbors, and then the mean of these samples is considered as the filling value. Although this method can deal with the problem of missing values well, it cannot effectively deal with the classification task with noise and redundant features because it ignores the importance of features. In order to do this, the paper proposes a novel imputation method. In our method, missing values are firstly filled by using the K-Nearest Neighbor Imputation method based on Euclidean distance, then a feature weighting vector can be obtained by using a feature weighting algorithm trained on the initially filled data, and finally the K-Nearest Neighbor Imputation with weighted Euclidean distance is used to fill missing values. The experimental results on six datasets show that the proposed method can improve the classification accuracy of incomplete data.
Road Aerial Object Detection Based on Improved YOLOv5
Authors: Li Zhenzhe 
Published: January 2022

Abstract
In this paper, the target detection technology based on deep learning is applied to the process of object detection in highway aerial photography. By detecting road objects such as vehicles or crosswalk, it lays the foundation for digitalization and informationization of roads. Firstly, the unmanned aerial vehicle is used to collect road images. Then based on YOLOv5 network, aiming at the problem of small detection target, attention mechanism is introduced to weigh different channels of feature graph, and SoftPool is introduced in SPP module to improve pooling operation and retain more detailed feature information. The experimental results show that the improved YOLOv5 network can identify and locate objects on aerial roads more accurately and effectively.
YOLOv5-based Defect Detection Model for Hot Rolled Strip Steel
Authors: Li Shun , Wang Xiaoqiang 
Published: January 2022

Abstract
In the defect detection of hot-rolled strip steel, there are often problems of too small target size and unclear features that lead to wrong detection and missed detection, for which a YOLOv5-based defect detection method for hot-rolled strip steel is proposed in this paper. Firstly, the overall architecture of the method is proposed, and then the algorithm implementation process is highlighted. Experimental analysis shows that the average detection accuracy using YOLOv5 is improved by 11.9% compared to YOLOv4 improved, with stronger generalization capability, faster detection speed, and lower error and miss detection rate.
NOTAM Text Analysis and Classification Based on Attention Mechanism
Authors: Mi Baigang , Fan Yi , Sun Yu 
Published: January 2022

Abstract
As one of the important carriers, Notice to Air Men (NOTAM) provides key aeronautical security information during flight operation. However, a large number of NOTAM texts lack systematic utilization and organization. To improve the application of NOTAM texts, the Natural language processing can be used to classify and analyze NOTAM texts, and their effective processing attaches significance to monitor the air security. In this paper, a corpus set of NOTAM by web crawler technology has been built to generate raw data. Based on the aeronautical intelligence knowledge system, the corpus set is systematically pre-processed and analyzed, while the key information in NOTAM and corpus features are also extracted. Considering the high-dimensional and sparse of corpus set, the traditional bi-directional Recurrent Neural Network (Bi-RNN) architecture is improved by adding an attention layer which not only allows the Bi-RNN to capture hidden dependency to improve sparse features, but also allows the attention mechanism to weigh the key information base on their perceived importance to optimize text representation. Experiments show that that the Attention-based Bi-RNN network outperforms the other four models, achieving a precision of 94.17% and an F1-Score of 93.66%. The model rapidly increases the utilization of text features meanwhile reduces the loss, which demonstrates it is a useful tool for the task of NOTAM texts classification and air security surveillance.
A K-means Optimization Algorithm Suitable for Fast Clustering of WebGIS Massive Data
Authors: He Honglei , Sun Bo , Yang Yan , Chen Jun 
Published: January 2022

Abstract
K-means has the advantage of fast speed and is suitable for clustering large-scale data of WebGIS geographic information. However, due to the random selection of K-means initial clustering centers, the clustering results are unstable and the clustering accuracy is poor. Some current research documents have solved the problems of clustering accuracy and stability, but the clustering time has been greatly increased. The article proposes a grid-based K-means improved algorithm GBK-means, which is based on an adaptive grid method to obtain initial clustering centers. Firstly, the parameters of the grid division are obtained by judging the distribution state of the sample data; then, the interconnected areas of each dense grid are obtained and the cluster centers are obtained, and on this basis, the initial cluster centers are obtained. The experimental results on the real data set of WebGIS show that GBK-means has better clustering effect and faster clustering speed than K-means, K-means++, literature [2], and literature [3]. The average value of its F value, accuracy rate and adjusted Rand coefficient (ARI) is 10.9%, 11% and 11.2% higher than that of K-means. The average clustering time is 75.4%, 52.3%, 85.1%, 91.1% faster than K-means, K-means++, literature [2], and literature [3].
Research and Implementation of Robot Path Planning Based on Ant Colony Algorithm
Authors: Ji Yalong , Liu Baichuan 
Published: January 2022

Abstract
Intelligent mobile objects (mobile robots) are gradually integrated into People’s Daily life, and path planning is the core of this kind of robots. In this article, ant colony algorithm is adopted to plan a global path through all points in the global space based on pheromone changes, so as to solve the practical problem that a robot needs to walk n points at a time and cannot repeat, and its distance is the shortest. Finally, the shortest path is solved based on MATLAB simulation platform.
Directed Association-based User Identification Algorithm
Authors: Jiang Qiuyan , Gong Daofu , Liu Fenlin 
Published: January 2022

Abstract
This paper studies the social network with directed association semantics, and proposes an unsupervised user identification algorithm (DAUM-P). The algorithm construct a user associations graph based on multiple types of directed user behaviors, and define directed associations; then, walk based on directed associations to obtain a walking sequence, and then combine the network embedding model to learn user characteristics vector representation; finally, the identification result is given based on the representation vector distance. Finally, the experiments show that the user identification effect is better than that of the baseline method.
Simulation of hydropower at subcontinental to global scales: a state-of-the-art review
Authors: Turner Sean W D , Voisin Nathalie 
Published: January 2022

AbstractHydroelectric power is playing a new and often expanded role in the world’s major power grids, offering low carbon generating capacity in industrializing, dam-building economies while providing reserve and flexibility to co-manage fledgling wind and solar resources in high income countries. Driven by river flows, conventional hydropower is exposed to the vagaries of weather and climate, motivating drought and climate change hydropower impact studies at large spatial scales. Here we review methods of climate-driven hydropower simulation at large spatial scales, specifically multi-basin regions to global. We identify four types of approach based on complexity of tools and richness of data applied to the problem. Since the earliest attempts to model climate-driven hydropower at continental scale almost two decades ago, the field has transitioned from one of scientific curiosity to practical application, with studies increasingly motivated by the need to inform power grid expansion planning and operation. As the hydrological and water management models used in large-scale hydropower studies become more sophisticated, new opportunities will emerge to study the impacts of changing hydropower on power system reliability and performance at large power grid scale. To grasp these opportunities, the water resources community must continue to enhance data and models for representing river flows and anthropogenic water use and management at subcontinental to global scales.
The core zone decisive of marine conservation area in Southeast Sulawesi using marxan
Authors: Wijayanto C , Yulianda F , Imran Z 
Published: January 2022

Abstract
The Southeast Sulawesi Marine Conservation Area is one of the marines protected areas, namely Aquatic Tourism Park type, appointed by The Governor’s decree of Southeast Sulawesi Number 98 the Year 2016. This area is located in The Konawe Regency, Kendari City and The South Konawe Regency with 21,785.14 ha. This area was still in initiation, so it has not marine spatial planning. This study aims to formulate and determine the core zone. Marxan was used to assign the core zone and solve the marine spatial planning and utilization conflict. Three scenarios were used to analyze the critical habitat of level protection at 30%, 50%, and combinations. These results described that scenario A has 751 ha, scenario B has 1008 ha, and combinations scenario have 1498 ha. The core zone area is under 1 % of the total area conservation. So, all scenarios do not qualify the criteria required by the International Union for Conservation of Nature (IUCN). Besides, all scenarios have qualified the thirty percents of critical habitat protection. Managers and stakeholders could use these findings to decide the core zone, spatial planning, and sustainable developments.
Length frequency distribution and length-weight relationships of Euthynnus sp. in North Sumatera, Indonesia
Authors: Pramesthy T D , Kelana P P , Siregar A A E 
Published: January 2022

Abstract
North Sumatra is one of the provinces that has a large fishery potential. The total catch of in North Sumatra reached 380,349 tons in 2016. This research to determine the growth pattern of Euthynnus sp. that caught in the waters of Nias Island, North Sumatra. Sampling was carried out in July 2020. The study was conducted by following fishing operations on purse seine vessels start from Sibolga City. Sample of 59 fish were taken randomly during the operation of the fishing gear in one trip. Length of fish was measured using a ruler (nearest: 1 mm) and weight of fish was measured using a digital scale (nearest: 1 g). The result of this research was the total length of the fish about 350–530 mm. There were 7 classes Length Distribution of fish that caught in July 2020. The highest frequency of total length was 401-427 mm. The growth pattern of Euthynnus sp. was positive allometric growth (b > 3). The Formula for Length-Weight Relationships is W = 0.06L3.2611 (r = 0.97). The length-weight relationship can describe the condition of fish population growth and the symptoms of fishing in nature. This is necessary to support the management of fishery resources.
Diversity of reef fish on Lembeh Island as an indicator of the coral reef health condition
Authors: Dwita N P M , Idris  , Widjoyo N S 
Published: January 2022

Abstract
Lembeh Strait in North Sulawesi is one of the areas included in the world’s coral triangle. Coral reef structures provide a habitat for reef fish. Herbivorous and invertivorous fish were essential to determine the direction of coral reef succession. This study aims to examine the health of coral reefs based on the presence of reef fish. Observations were conducted on January 16-19, 2019, with a total of 22 observation points. Observation of reef fish communities using the underwater visual census (UVCs) and belt transect method. At the observation site, it was found that there were 260 species of reef fish. The resilience of coral reefs based on the presence of reef fish has a high value on the parameters of the abundance of herbivorous fish, taxonomic diversity, and abundance of coral reef fish.
Diversity and fluctuation of cultivable Vibrio bacteria populations in an integrated multi-trophic aquaculture (IMTA) system of Holothuria scabra, Chanos chanos and Gracillaria sp
Authors: Anggorowati D A , Munandar H 
Published: January 2022

Abstract
Sea cucumber is one of the vital aquaculture commodities in the global market. Progressive demand and limiting the supply of sea cucumber from natural sources drove sea cucumber aquaculture development. An integrated multi-trophic aquaculture system (IMTA) was a polyculture system in aquaculture to improve production by promoting nutrient utilisation through different tropical levels. This system combined sea cucumber (Holothuria scabra), milkfish (Chanos chanos), and seaweed (Gracillaria sp.) in a rearing tank system. Several factors affect the success of IMTA processes, including microorganisms. Microorganisms in the aquaculture environment play a crucial role in elements cycling, energy flow and farmed-species health. Diseases caused by the bacteria, mainly from the Vibrionaceae family, were often chronic than acute and may cause a high mortality percentage. This study aimed to investigate the Vibrio bacterial diversity and fluctuation in the water of IMTA rearing tanks. The result indicated that the Vibrio bacterial diversity from the polyculture system (IMTA) was generally higher than the monoculture system. Vibrio bacteria populations from different culture systems have been found to consist of varied bacterial species. However, the predominant species was the same. The polyculture system is suggested as a sustainable and eco-friendly culture system.
Applying risk assessment approach to evaluate small island status in Kepulauan Seribu
Authors: Ambo S W , Yonvitner  , Samosir A M 
Published: January 2022

AbstractKepulauan Seribu with all potential need to be realized in an integrated management of coastal and ocean areas for sustainable development. The process of developing small islands in an integrated manner in the three islands needs to consider the risks that will occur. The purpose of this study is to analyze the level of risk in small islands and estimate the appropriate management of small islands for the Thousand Islands area. The method used in this study is a survey and observation method with an analysis of the IPCC (2014) model. The type of hazard that has the most potential to cause a disaster is a hurricane. The level of vulnerability in Harapan Island, Kelapa Island, and Kelapa Dua Island is relatively low, because there is only one hazard that has the potential to be a disaster, namely a tornado with a large enough magnitude and loss. The level of capacity owned by the three islands is quite good, so that the risk value in Harapan Island is 0.69, Kelapa Island is 0.68, and Kelapa Dua Island is 0.62 which is included in the low category.
Eight natural treasures of Aceh Jaya, Province of Aceh
Authors: Christian Y , Afandy A , Desmiwati  
Published: January 2022

Abstract
The coastal regency of Aceh Jaya has great potential resources in marine and fisheries, agriculture-plantation-animal farming, forestry, minerals-mining, tourism, processing industry, and renewable energy. However, significant challenges arise regarding selecting these potentials with the principle of sustainability: encouraging economic development, being accountable and socially accepted, and having an ecological perspective as a short to medium plan to accelerate economic growth. This study has identified the leading sectors with the most potential resources for the basis of development priority of Aceh Jaya nearly two decades after the 2004’s tsunami. The research was conducted in nine districts in Aceh Jaya Regency. Data is processed through Market Analysis, Gap Analysis, Stakeholder and Institutional Analysis, and Sectoral Analysis. These analyses identified eight sectors with each superior product for the development acceleration of Aceh Jaya. Those sectors and the products are agriculture (rice), capture fisheries (tuna, skipjack, mackerel tuna, and crustacean), aquaculture (giant-tiger prawn, tilapia, and lobster), animal farming (cattle, buffalo, goat, duck), forestry (agarwood, dragonblood, and rattan), tourism (Geureutee, Reusam Island), mineral (coal), industry (prawn cracker, shredded catfish, soybean, patchouli oil, and biogas).
Assessment of marine debris in seagrass beds of Pramuka Island, Kepulauan Seribu
Authors: Rasyid N , Munir  , Andryan D , Bengen D G , Subhan B 
Published: January 2022

Abstract
Indonesia is referred as the second largest contributor of marine debris in the world after China, with an estimated 0.48-1.29 million metric tons per year. High anthropogenic activities from locals and tourists can produce large marine debris and impact the seagrass ecosystem. This research aimed to identify marine debris in the habitat of seagrass beds on Pramuka Island. Extensive surveys include observing seagrass community structures, the measurement of chemical and physical parameters of the water, and marine debris inventory at three stations in Pramuka Island. Observation results found six seagrass species, with coverage ranged from 1.67-47.32% while the density 28-112.76 stand/m2. Marine debris can be classified into six types: plastic, metal, rubber, glass, organic matter, and others. The weight of marine debris for each type ranges from 0.03–2.38 kg. In addition, microplastic found consisted of fiber, film, and fragment with a unit weight of 20–440 particles/kg. In conclusion, the seagrass conditions of each station are classified as damaged. The marine debris that has the most impact on the seagrass beds is plastic. Fiber type microplastic has the most abundance. this can interfere with respiration and the photosynthesis process of seagrass.
Nutrition of wet noodles with mangrove fruit flour during the shelf life by adding catechins as a source of antioxidants
Authors: Sumartini  , Ratrinia P W 
Published: January 2022

Abstract
Wet noodles are foods that are very popular with the public, but basically, noodles do not contain many important nutrients. Catechins are a class of antioxidant compounds that can be extracted from various plant sources. This goal from this research is making of noodles from mangrove fruit flour with the addition of catechins is carried out to increase the nutritional and nutritional value and improve the quality of wet noodles during the shelf life. The research method used an experimental design with a factorial Completely Randomized Design (CRD) with three factors (K = Control, S = T. Mangrove fruit S. caseolaris). A (T. Mangrove fruit A.marina) and 3 test levels, namely storage time (0.3 and 5 days). The results were processed using SPSS version 22 software with one-way ANOVA. The results showed the value of water content in the range of 46.33-56.82%, protein content 3.88-6.83%, fat content 1.76-2.82%, ash content 0.04-0.18%, levels of carbohydrates 39.08-48.79%, fiber content 3.09-8.81%, antioxidant activity 5.11-47.74%. The results showed that seaweed fruit flour wet noodles with catechins as a source of antioxidants were able to improve the quality and nutrition of wet noodles during the shelf life. The results showed that the manufacture of wet noodles from mangrove fruit flour with the addition of 7% catechins as a source of antioxidants was able to significantly improve the nutritional quality and nutrition of wet noodles during the shelf life compared to control (K) wet noodles with wheat flour as raw material without 7% catechins as a source of antioxidants
Antibacterial activity of functional bioactive peptides derived from fish protein hydrolysate
Authors: Baco N , Oslan S N H , Shapawi R , Mohhtar R A M , Noordin W N M , Huda N 
Published: January 2022

Abstract
By-product removal in fish processing is estimated to be between 25 and 70% due to improper fish production handling and significant problems in the fish industry today. Therefore, one of the ways to manage the raw material of by-product is through protein hydrolysis. However, one of the most effective methods for managing this raw material, which includes skin, bones, heads, and viscera, is to convert their protein into peptides via hydrolysis methods, resulting in fish protein hydrolysate (FPH). FPH has been shown to have bioactive properties such as antibacterial, antihypertensive, antioxidative, anticancer, and anticoagulant properties. Bioactivity could be fully utilised in the future in both the nutraceutical and food industries. Numerous studies have been published on the acceptability of FPH in obtaining bioactive properties from various fish, particularly antibacterial activity. For example, the antibacterial peptide was identified as FPIGMGHGSRPA, consisting of 12 amino acids. Its antibacterial activity was tested against B. subtilis using 800 g/mL ampicillin. The inhibition zone increased with peptide concentration. This review discusses functional bioactive peptides derived from fish protein hydrolysate that can be used as antibacterial agents by inhibit Gram-positive and Gram-negative bacterial growth. It also covers fish species, parts, and hydrolysis methods to maximise yields.