bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Simulation of Underwater Acoustic Spread Spectrum Communication Based on LDPC Code
Authors: Wei Xiao Fei , Chen Jin
Published: April 2021

As we all know, the underwater acoustic channel is a time-varying, space-changing, and frequency-varying fading channel with limited bandwidth and severe noise interference. This paper studies and analyzes the main factors restricting the transmission of underwater acoustic channels, and establishes an underwater acoustic multipath time-varying fading channel. The channel coding adopts Quasi-Cyslic Low-Density Parity-Check Codes (QC-LDPC), combined with spread spectrum technology and high-order modulation technology, and utilizes Log-likelihood Ratios Belief Propagation (LLR-BP) is decoded, the simulation results show that LDPC codes have stronger error correction capabilities in underwater acoustic spread spectrum communication systems, ensuring that the system can operate reliably under low SNR conditions.
IYOLO: Multi-scale infrared target detection method based on bidirectional feature fusion
Authors: Zhao Xiaofeng , Xu Yebin , Wu Fei , Cai Wei , Zhang Zhili
Published: April 2021

Convolutional neural networks are advanced computer vision solution for various tasks, and have made considerable progress. In order to detect infrared targets with details and texture features, we propose a detection method based on YOLOv3. First, we propose a bidirectional feature fusion structure called Improve-FPN(Im-FPN), which allows fast and efficient multi-scale feature fusion. Second, we use the Focal Loss(FL) loss function to balance the problem of sample imbalance. Based on these optimizations, an Infrared-YOLO (IYOLO) target detection model for infrared target is constructed. On the self-constructed infrared dataset: Infrared-VOC, the mAP of IYOLO can achieve 77.1%, which is 4.0% higher than YOLOv3, and the detection speed can reach 55.6FPS. Experimental results show that this method can improve the overall accuracy of detection while ensuring real-time detection.
122km single-end phase-sensitive optical time domain reflectometer based on post signal processing method
Authors: Song Muping , Wang Yixuan , Chen Ge , Zhang Yuxin
Published: April 2021

Phase sensitive optical time domain reflectometer is able to detect vibration information. However, when it comes to ultra-long distance detection, the vibration signal is overwhelmed due to noise level and polarization fading. In this paper, a method is used to compensate noise and fading phenomenon based on post signal processing scheme, including sectional amplification, amplitude demodulation and adaptive matched filtering. On the basis of the theoretical analyzation of the detection method, the feasibility is verified by experiment. Vibration information from 122km can be detected.
Design of automatic generation system of equipment protection common sense pocket book content based on power big data
Authors: Gu Hailin , Hu Pan , Qi Jun , Bai Liang , Xia Yu
Published: April 2021

In order to improve the power system and process, strengthen personnel training and guidance, this paper proposes a new automatic generation system of equipment protection knowledge pocket book content based on power big data. Firstly, the architecture of each level of the system is designed. Secondly, according to the architecture design results, the main hardware and software of the system are designed. The hardware mainly includes pocket book content naming module, user management module and pocket book content automatic generation module. In the software part, K-mean clustering algorithm is used to cluster the power big data, and the main content of equipment protection knowledge in power big data is extracted. The above hardware and software are combined to complete the design of automatic generation system for the contents of power equipment protection pocket book. The experimental results show that the performance of the system is greatly improved.
Noise reduction optimization of sound sensor based on a Conditional Generation Adversarial Network
Authors: Lin Xiongwei , Yang Dongru , Mao Yadong , Zhou Lei , Zhao Xiaobo , Lu Shengguo
Published: April 2021

To address the problems in the traditional speech signal noise elimination methods, such as the residual noise, poor real-time performance and narrow applications a new method is proposed to eliminate network voice noise based on deep learning of conditional generation adversarial network. In terms of the perceptual evaluation of speech quality (PESQ) and shorttime objective intelligibility measure (STOI) functions used as the loss function in the neural network, which were used as the loss function in the neural network, the flexibility of the whole network was optimized, and the training process of the model simplified. The experimental results indicate that, under the noisy environment, especially in a restaurant, the proposed noise reduction scheme improves the STOI score by 26.23% and PESQ score by 17.18%, respectively, compared with the traditional Wiener noise reduction algorithm. Therefore, the sound sensor’s noise reduction scheme through our approach has achieved a remarkable noise reduction effect, more useful information transmission, and stronger practicability.
Research on Physical Fitness Classification of Traditional Chinese Medicine Based on Human Infrared Heat Map
Authors: Zhang YanYang , Hu GuangQin , Zhang XinFeng
Published: April 2021

The infrared heat map reflects the overall temperature distribution of the human body, which coincides with the theory of traditional Chinese medicine, as an important indicator of human sub-health status identification in the field of traditional Chinese medicine, the physical fitness of traditional Chinese medicine has attracted more and more attention from the medical field and the general public. Because the infrared heat map of the human body has rich color distribution characteristics, this paper uses color feature extraction and texture feature extraction algorithms combined with SVM classifiers and convolutional neural networks to perform classification experiments. The results show that the accuracy of deep learning algorithms is higher than that of traditional machine learning algorithms, Deep learning can be combined with local subtle features for further research.
Simulation analysis on motion stability of smart wheelchair
Authors: An Yi , Han Tianqi , Zhao Hongyu , Qiu Sen
Published: April 2021

Electric wheelchairs sometimes are used in complex terrain, such as slopes, stairs, ravines, etc. If there is no rapid and accurate judgment and decision-making for the current situation, the wheelchair may lose control and become unstable, which may will lead to serious consequences. The intelligent electric wheelchair studied in this paper can conduct stability analysis when moving on different terrains based on its own motion state. This paper uses ADAMS simulation software to build a wheelchair model according to the size of an existing wheelchair. The stability pyramid technique used in this paper has a good judgment on the tip-over stability of the object. This paper also has a more comprehensive judgment for slippage instability. In the simulation and experiment, the slippage and tip-over instability are verified. Theoretical analysis and actual simulation demonstrated that the developed smart wheelchair has high reliability for stability analysis in different environments.
Design and Application of Early Warning Model for Electric Vehicle Charging Safety
Authors: Zhang Yang , Yuan Jun , Li Liang , Zhan Yanjiao
Published: April 2021

In order to improve the charging safety of electric vehicles, it is necessary to design the early warning model of charging safety, so as to overcome the overload defects in the charging process of electric vehicles. An electric vehicle charging safety warning model was proposed based on contactless charging design. The electromagnetic induction coil and electromagnetic coupler installed on the charging pile are used to design the electromagnetic coupling induction with the driving electric vehicle tire wire, and the electromagnetic coupling control and charging stability adjustment of the electric vehicle are carried out by using the inductive power transmission technology. According to the overload regulation of electric vehicle during charging, the overload interruption control of electric vehicle charging is carried out by mutual inductance coupling method, and the parameters such as resonance frequency, mutual inductance coefficient and coil internal resistance during charging are analyzed. The parameter steady-state regulation method is used for non-contact charging, and the electric vehicle charging safety early warning control is realized, and the parameter optimization design of electric power transmission system in the process of electric vehicle charging is carried out. According to the parameter optimization result, the electric vehicle charging safety early warning test is realized. The test results show that the proposed method has good control performance and can effectively realize the wireless energy transmission of 100W in 100cm, the charging efficiency and the charging safety are improved.
A concatenated approach based on transfer learning and PCA for classifying bees and wasps
Authors: Zhang Jiahong , Guo Hongxiang , Chen Zekai
Published: April 2021

Convolutional neural networks (CNNs) are a type of deep model that can accomplish image classification tasks resulting in outstanding performances. From recognizing handwritten numbers to tachyarrhythmia, researchers and engineers have used CNNs for classification tasks in various domains. However, there lacks a comparison and analysis of the performances of different models in classifying insects. Previous methods are currently limited to using only one particular type of network in finishing one specific task. This approach fails to use the strengths of different models. In this paper, a concatenated model is developed, which is able to take advantage of the strengths of multiple CNNs. The performances of VGG, ResNet, XceptionNet, and EfficienNet in classifying bees and wasps are firstly compared. Then, outputs of the penultimate layers in the four networks are merged, which is similar to encoding. In addition, we use principal component analysis (PCA) to decrease computation cost and increase explanatory. Finally, to achieve the final classification, a deep neural network (DNN), which takes the concatenated outputs and four labels separately as input data and output, is structured. In comparison to the traditional classification methods, the proposed model achieves high-level performance and better explanation. Furthermore, it is worth remarking that this paper discovers the encoding characteristics of VGG, ResNet, XceptionNet, and EfficientNet.
The upgrade of applied talents cultivation in the background of AI
Authors: Liu Wenhua
Published: April 2021

In the AI age, a series of high technology, like AI technology and information technology, trigger deep reform in industry field. To meet the talents requirements of AI, colleges should promote the mission of talents cultivation. A few forward steps should carry on. They are pedagogy remodeling replacement of teaching technology, arrangement of education resources and extension of learning space.
Yolo-tiny-MSC: A tiny neural network for object detection
Authors: Li Dongsheng , Zhang Yujie , Xiang Junping , Li Jianfei , Zou Yu
Published: April 2021

Object detection is an important and active area of computer vision. However, the expensive computational cost and memory requirement are big challenges for deploying object detection networks in resource constraints embedded devices. To address this problem, we designed the multi-stage cascade module to reduce the computational cost of object detection networks. The proposed structure is used to build a compact and efficient object detection neural network. Experiments show that our multi-stage cascade module could significantly reduce the computational and parameter budgets meanwhile achieve outstanding object detection accuracy.
Study on Influencing Factors of Major Incidents in Petrochemical Parks Based on Bayesian Networks
Authors: Hu Haoran , Shao Bowen , Guo Jian , Hong Bingyuan
Published: April 2021

With the rapid development of the petrochemical industry, the scale of the petrochemical park is gradually expanding. Safety incidents that occur from time to time and their serious consequences cannot be ignored. Based on the systematic summary of chemical incidents in the last 15 years, the main types of incidents are explosion, poisoning and suffocation, and fire. Thus, it is necessary to prevent major incidents from critical events. The incident tree model of major and extraordinarily large explosion incident in petrochemical park is constructed, and it is mapped to a Bayesian network for incident cause analysis and influence analysis. Consequently, it is concluded that illegal command and illegal operations are the main factors leading to the incident. The method of adding a protective layer is proposed to improve its overall safety. It can provide theoretical and technical support for accident risk identification, evaluation, and control in petrochemical park in the future.
Research on Multi-party Cooperative Secure Identity Authentication Mechanism Based on Blockchain
Authors: Liu Nianzu , Guo Bing
Published: April 2021

With the continuous development of information society, block chain technology can play an extremely important role in many fields. However, with the increasing degree of communication in the information society, a huge amount of data is generated. How to protect the information data generated in the process of communication has become a more serious problem at present. In its earliest stages, blockchain technology was used only for cryptocurrency transactions. Under the general directory, there are a lot of sub-accounts, and these sub-accounts are all valuable accounts, and the data is stored in different blocks in different chains. Judging from the current application of blockchain technology, the application of this technology can guarantee the security of data storage. Data storage is extremely secure in terms of security, so there will be no individual or group to destroy or tamper with the data. In blockchain technology, all data is stored in a Mosaic form in many blocks, which means that a single block does not have the function of storing information data. When making a large transaction, due to the uniqueness of blockchain technology, each member of the chain needs to authorize the data, which means all members of the chain must agree to the transaction before the transaction can be completed. Starting from the application of block chain technology, this paper analyzes the most common identity authentication mechanism in our daily life, and analyzes the application of block chain technology in daily life from multiple aspects.
Urine red blood cell classification based on Siamese Network
Authors: Zhao Xue , Xiang Jianhong , Ji Qingbo
Published: April 2021

Urine examination is an important examination commonly used in medical in vitro examination. The morphological classification of red blood cells in urine plays an important role in the diagnosis of hematuria and renal diseases. In order to improve the accuracy and efficiency of urine red blood cell classification, a urinary red blood cell classification algorithm based on Siamese Network of dual-mode contrastive loss function was proposed. In the dual-mode contrastive loss function, the Cosine Similarity measure and a weight factor were added as the constraint of Euclidean distance in the Contrastive Loss function, which improves the similarity judgment ability of the Contrastive Loss function for the two input eigenvectors. The experimental results show that the Cosine Similarity measure has a positive effect on the Contrastive Loss function, and can effectively improve the accuracy of the whole classification model.
Knotting spectrum of polygonal knots in extreme confinement
Authors: Ernst Claus , Rawdon Eric J , Ziegler Uta
Published: April 2021

Random knot models are often used to measure the types of entanglements one would expect to observe in an unbiased system with some given physical property or set of properties. In nature, macromolecular chains often exist in extreme confinement. Current techniques for sampling random polygons in confinement are limited. In this paper, we gain insight into the knotting behavior of random polygons in extreme confinement by studying random polygons restricted to cylinders, where each edge connects the top and bottom disks of the cylinder. The knot spectrum generated by this model is compared to the knot spectrum of rooted equilateral random polygons in spherical confinement. Due to the rooting, such polygons require a radius of confinement R ⩾ 1. We present numerical evidence that the polygons generated by this simple cylindrical model generate knot probabilities that are equivalent to spherical confinement at a radius of R ≈ 0.62. We then show how knot complexity and the relative probability of different classes of knot types change as the length of the polygon increases in the cylindrical polygons.
Mechanical Properties Effect of Wood-plastic Composite by Basalt Fiber and MAPE
Authors: Wang Yong
Published: April 2021

In order to protect biological resources, this article explores the use of tensile and bending tests and Thermogravimetry (TG), thermal differential scanning (DSC) and other experimental studies. The compatibilizer maleic anhydride grafted high-density polyethylene (MAPE) improves the mechanical properties of chopped basalt fiber (SBF, 20% by mass) and reinforces wood-plastic composites (WPC). The results show that: 1) WPC with a length of 6mmSBF, when the MAPE content is 5∼6%, its tensile breaking strength and bending strength achieve the best results, of which the breaking strength is increased by about 90% compared with pure wood plastic; (2) Since the tensile and bending strength of MAPE itself is roughly similar to HDPE, when the content of MAPE is greater than 9%, it acts as a matrix HDPE. In addition to the plasticity continues to be improved, its strength index is gradually decreasing. 3) When the MAPE content is 6%, the TG curve has the slowest thermal weight loss and the DSC has the highest melting peak temperature, which means that the composite material is difficult to melt, and the bonding between the components in the material is firm, thereby having better mechanics. The performance also confirmed the results of mechanical testing.
Numerical Simulation of Catenary Effect of (RC) Frame Structure Based on MSC.Marc
Authors: Yang Jiahao , Zhao Jizhi
Published: April 2021

Since the collapse of Ronan point apartment in 1960s, progressive collapse has become a research hotspot in civil engineering. In order to study and verify the catenary effect on the resistance of the reinforced concrete frame structure to the progressive collapse. Based on MSC.Marc software, a single-story plane frame structure of reinforced concrete frame structure was selected to establish a finite element model for numerical simulation, and the numerical simulation results was compared with the experimental data.
Assessment of typhoon prevention level at fishing port
Authors: Kong Congying , Lu Yingxue , Han Tao
Published: April 2021

Due to the need of typhoon grade evaluation in the construction plan of fishing port, the wave height distribution in the fishing port of typhoon 10 and typhoon 12 under adverse path was calculated, and the berthing area of the fishing port was counted. According to the theoretical formula, the wind force and anchor-holding force of the fishing boat are calculated, and the anti-typhoon grade of the anchorage is analyzed, which provides technical support for the construction of the port area.
Analysis of the elements of the LNG terminal’s location in Dalian Port under the background of carbon neutrality in China
Authors: Yao Haiyuan , Wang Dachuan , Wu Hongyu , Fang Zhuo , Ding Wentao
Published: April 2021

As the issue of climate change is always attracting widespread attention and China had fulfilled its commitment on emission reduction, the proportion of traditional energy consumption such as coal in China’s energy consumption structure will gradually decrease in the future, and the use of clean energy such as LNG will become the latest trend to replace the use of traditional resources, and the future increment of LNG would be mainly borne by sea transportation. Dalian City has a single source of natural gas by sea, which is highly dependent on offshore imports. In addition, it is predicted that the LNG throughput of Dalian Port will reach 8-12 billion m3by 2050, so it urgently needs to build new LNG terminals to ensure the safety of natural gas supply. This paper statistically analyzed not only the operation status and construction progress of LNG terminals in northern China, but also the characteristics of natural gas consumption in the three North-Eastern Provinces of China and Dalian City. Based on the above situation, the principle and preliminary scheme of LNG terminal site selection were proposed.
Change detection of built-up areas based on ensemble learning
Authors: Chen Lei , Li Yingcheng , Geng Zhongyuan , Li Xilin , Xue Yanli , Wang Guangliang , Wang Yanhui
Published: April 2021

The paper presents a new method for the change detection of built-up areas based on ensemble learning. The method selects the feature generation part of VGG network to replace the encoder of UNet network, and makes full use of the advantages of VGG network in feature interpretation to construct a new network VGG-UNet, so as to improve the information extraction accuracy of built-up areas. First, the slice sample sets containing built-up areas and non-built-up areas were established. Secondly, the model was trained and tested to obtain several optimal models with high precision. Thirdly, these optimal models were used to extract the change information of built-up areas in the experimental area. Finally, the results were ensemble optimized and the accuracy was verified by comparing with the field measurements. The experimental results in Xinjiang demonstrate the advantages, feasibility and reliability of the proposed method. Moreover, the ensemble optimization of multiple model results can further improve the change detection accuracy of built-up areas.
CBS-GAN: A Band Selection Based Generative Adversarial Net for Hyperspectral Sample Generation
Authors: Qiao Yulin , Mohammad Mostofa Zaman , Li Yi , Liu Xiaobo , Cai Zhihua
Published: April 2021

Sample generation is an effective method to improve the performance of hyperspectral image classification by generating virtual samples for training sample expansion in the training process of classification. However, there are some defects existing in the previous sample generation methods including the lack of spatial information, the redundant generation and the damage of the original spectral components. In this paper, we propose conditional band selection generative adversarial net, named CBS-GAN, to handle this problem. Firstly, the band selection net of CBS-GAN is utilized to avoid redundant bands and keep original spectral information, then the generation net of CBS-GAN generates the spatial-spectral data blocks by selected bands for sample generation. The experiments of classification are also used to demonstrate the availability of virtual samples generated by our method.
Propagation characteristics of low-frequency acoustic wave in full waveguide of shallow water based on time-domain finite element method
Authors: Wang Qile , Zhu Hanhao , Tang Yunfeng , Xiao Rui , Xue Yangyang
Published: April 2021

In order to clarify the propagation mechanism and characteristics of low-frequency sound signals in shallow sea with elastic bottom, using the Time-domain Finite Element Method (TDFEM), a time-domain numerical calculation model of the low-frequency sound field in shallow sea full-waveguide under the action of a point sound source is established. With this model, The influence of seabed acoustic parameters’ and seabed topography’ changes on the sound propagation characteristics in full-waveguide is simulated and analyzed. The results show that when there is a shear wave effect on the seabed, low-frequency sound waves will excite the Scholte wave propagating on the bottom boundary of the seabed. The greater the seabed acoustic impedance, the faster the excited Scholte wave velocity and the large the amplitude. At the same time, there will be acoustic energy leakage phenomenon in the inclined seabed.
Green architecture approach in waste management building design concept
Authors: Fachrudin H T , Zafira Khairuz
Published: April 2021

Medan City has 2 landfill sites, Namo Bintang and Terjun. However, Namo Bintang Landfill was closed in 2013 by the Medan City Government. Namo Bintang Landfill is planned to be reopened to receive Medan City waste. The waste management will focus on the solid waste in the Namo Bintang Landfill that applies the Green Architecture which is focused on the Principles of Energy Efficiency and Conservation. The design method starts from a direct site survey, then data collection by observation, documentation, literature review, and comparative studies of similar projects that will be analyzed to produce a concept of design of waste to energy management area at the Namo Bintang Landfill. Combustion of waste into alternative electrical energy that can meet the electricity needs of the community. The process of waste to energy starts by burning waste at very high temperatures, then transfer the heat, and by used turbin, transformed it into the energy. The steam which drives the turbines - creates surplus heat which can be used for district cooling and heating, electricity, also recovered clean water, construction material, and valuable metals from the waste. This is the approachable solution in the field of energy, ecology, and sustainable environment.
Study of slum settlement infrastructure in Pulonas Village, Babussalam Sub-district, South East Aceh Regency
Authors: Ariarma Nazmy , Marpaung B O Y , Nirfalini Aulia Dwira
Published: April 2021

In 2015 the population of Babussalam District was 2,758 people per km2 with an area of 9.42 km2 or a density of up to 293 inhabitants per km2. With this population density, Babussalam District can be classified into areas with high density. Babussalam Subdistrict which consists of 27 villages. Pulonas Village which is indicated as slums and are predicted to continue to deteriorate. The condition of settlement infrastructure in Pulonas Village are very poor, such as narrow and damaged roads with infeasible clean water and infeasible waste collection. High building density with limited area and the number of occupants in a dense building is a big problem that occurs in Pulonas Village today. The research method used in this study is a Qualitative Descriptive Methodology, in which researchers interpret the data obtained through direct observation in the field. The data are interpreted and the method of data collection is based on theoretical basis. The results of the study were recommendations and directions for the management of slums in Pulonas Village Babussalam Sub-district, Southeast Aceh Regency, beneficial for local government and stakeholders in determining the direction of local government policy.
Unconfined compressive strength and California Bearing Ratio test on clay stabilization using silica sand
Authors: Hastuty Ika Puji , Hartawan Agung
Published: April 2021

Clay is a soil with certain particles which has plastic properties when it is mixed with water, so that clay needs to be stabilized before it is ready to be used. In this study, the stabilizing agent used was silica sand, which is a mineral commonly found and has a hexagonal crystal structure (SiO2). The purpose of this study was to determine the effect of adding silica sand to the properties index, Unconfined Compressive Strength (UCT), and California Bearing Ratio (CBR) value of clay soil. The result showed that according to AASHTO this soil was classified as A-7-6 (9) and according to USCS it was classified as CL (Clay - Low Plasticity). The original soil sample has a moisture content of 34.43%; specific weight of 2.65%; liquid limit of 47.33%; plastic limit of 17.45%; and plasticity index of 29.88%. The values of unsoaked design CBR and UCT for the original soil were 6.29% and 1.42 kg/cm2. Among all the variations, the mixture of 30% silica sand reached the optimum value of soaked California Bearing Ratio which is 14.86%, meanwhile, the mixture of 12% silica sand reached the optimum value of free compressive strength in Unconfined Compression Test which was 2.90 kg/cm2.
Classification and effect of compaction on soil shear strength by direct shear test on peat soil of Tapanuli Utara Regency, North Sumatera Province
Authors: Roesyanto  , Tarigan T
Published: April 2021

Planning for development on peat soil requires an understanding of the behavior of peat soil because of the large potential damage that can occur to buildings on peat. The points of this study were to determine the index properties, to classify the peat soil classifications, and to determine the effect of compaction on internal friction angles and cohesion values. The water content of Pohan Tonga peat soil was 729.33% and the specific gravity was 1.302. Based on ASTM D442-84, the sample of peat soil was classified as medium ash peat because it had ash content of 8.260%, and was classified as moderately acidic because of its pH value of 5.5. From Standard Proctor test, the optimum moisture content obtained was 98% and maximum dry unit weight was 0.419 gr/cm3. The effect of compaction increased the dry unit weight value of the undisturbed sample from 0.126 g/cm3 to 0.454 gr/cm3 of 108% sample. The highest value of internal friction angle in peat was obtained from 108% sample, namely 5.391° with a cohesion of 0.024 MPa compared to undisturbed sample which had internal friction angle of 0.375° with a cohesion of 0.019 MPa.
The influence of Chinese architecture on the development of architecture in Medan City
Authors: Pane I F , Fachrudin H T , Pane P S
Published: April 2021

This paper aims to trace the development of Chinese architecture in Medan. Chinese architecture is architecture that was brought by traders and plantation workers during the Dutch colonial period and collaborated with local architecture. This collaboration has colored the development of modern / postmodern architecture that developed until now. For this reason, this article notes the harmonious collaboration between Chinese architecture and local architecture. The research location is in the city of Medan because this area has had a long history of the entry of Chinese influence through plantation workers during the colonial period. The object of study is building in the city of Medan with Chinese architectural characteristics. The method used is a descriptive qualitative approach in order to elaborate and examine the facts on the field and analyze them with the theory used. The results showed that Chinese architecture plays a role in forming the architecture which developed in the city of Medan and the existing spaces are the result of culture from generation to generation that present the meaning according to their needs.
Industry 4.0: Data science perspective
Authors: Nasution Mahyuddin K M
Published: April 2021

Industry 4.0 is a shift from the previous industry shape. Automation is as a result of technology involving electrical energy. Changes occur and lead to paperless and humanless, but these changes require preparation both in the industrial world and in other supporting worlds. Data is a different side of technology. Data involves many different concepts from the industrial world, even though either data of the industrial world involve the same technology. Specifically, data management is different than industry management. This paper reviews integrated management based on data science, a science that studies the behavior of data. As a result, integration requires data structuring steps from Industry 4.0 and structuring data for Industry 4.0.
Analysis delay factor distribution of ready–mix concrete PT. Kreasibeton Nusapersada
Authors: Nasution Andri , Hidayati Juliza , Buchari  , Syarifah Yolanda Putri
Published: April 2021

PT Kreasibeton Nusapersada must be able to provide the best service to meet customer needs, one of which is in terms of timely delivery of goods safely to the destination. The process of sending goods with different locations still often occurs, such as delays in shipping goods caused by various factors to find the cause of the delay in the shipment of Ready-mix on PT Kreasibeton Nusapersada then the data analysis technique used the writer is a fishbone diagram or a causal diagram. From the analysis of activities carried out by PT Kreasibeton Nusapersada, it has been going well. However, based on data in the field, it turns out, there is still a delay. Of the twelve (12) factors, it turns out, there are four (4) factors that cause delays, 84.37% of congestion factor is stating that congestion are the most cause of late distribution of Ready-mix Concrete products, 68.75% is state the number of projects or Demand for Ready-mix Concrete causes the product distribution constraints, 43.75% the Batching Plant machine was damaged so that the process of making Ready-mix Concrete was disturbed, and for product delivery was delayed and 75% is state the availability of raw materials affected the distribution delay.
Application of reliability engineering method in machine maintenance
Authors: Sembiring Nurhayati , Buchari  , Hermansah
Published: April 2021

This study was conducted in an industry resin from block rubber with the quality specifications of the SIR (Standard Indonesian Rubber)-10. Problems occurred because the company is still doing corrective maintenance and do not have a planned machine maintenance schedule. It disrupted of the exhibition process. This study’s purpose is designing a preventive maintenance machine system with reliability engineering method. Data needed in study is machine breakdown and downtime, damaged frequency, and interval damaged of machine details. The critical details on the machine were Reactors with its details, namely packing valve Codogno, packing main-hole, and propeller. Determining the distribution of failure, reliability, Mean Time to Failure, the study results show the interval of replaced part packing valve Codogno is a 109-day with reliability value the of details 0.5007; packing main-hole is 120 days with reliability 0.5070; propeller details is 172 days with reliability 0.5028.
Proposed improvement of production floor layout using urban algorithm in minimizing the cost of material handling (Case study of rubber wood processing factory)
Authors: Tarigan U , Ishak A , Fabiola N A , Sembiring N , Syahputri K , Tarigan U P P
Published: April 2021

The design of the layout of the production floor facilities in this study aims to solve the problem on the production floor, namely that there is an irregular material flow pattern due to alternating flow and crossing paths with high frequency resulting in total material transfer moment which is directly proportional to high material handling cost. To solve the problem is used Urban Algorithm and WinQSB Software. This method was chosen because it can exchange between departments and move departments so that distant parts can be re-adjacent. In addition, this method uses from to chart which is then inputted to produce alternative layout proposals. The results obtained after repairing the production floor layout using the Urban algorithm and WinQSB software in XYZ Company of wood processing factory shows that the total displacement moment is 546,745 times/month. This has decreased compared to the total moment of displacement of the initial layout of 1,211,335 times/month. The total OMH in the initial layout was IDR 1,321,902 after improvements and adjustments were made using the Urban algorithm, the total OMH was IDR 574,083. The results showed that the layout improvement with the Urban algorithm has an efficiency of 56.57% and the best alternative is layout II.
Big data analysis for product design
Authors: Hidayati Juliza , Gusrina Shelvy Riry , Matondang Nazaruddin
Published: April 2021

Currently all industries have the same challenges, namely the challenges facing disruptive technology, including the telecommunications industry. Disruptive Technology is a form of industrial revolution 4.0 as a result of robotic technology, machine learning and artificial intelligence. The company’s innovation capacity will be one of the best indicators for the company. So that to face disruptive technology in the industrial era 4.0, companies must design a technology with sustainable market needs in order to survive in the industrial market. Accordingly, a literature review is conducted to explore values of big data in the perspective of product designers. Product features and sentiment polarities would be the first identification of consumer opinion data. Some methods is discussed in this study such Kalman filter which used to forecast the trends of customer requirements (CR) and Bayesian method to compare products. This study aimed to help designers their advantages and understanding every possibilities of changes customer requirements (CR). And by exploring valuable information from big data the designers may decide kind of product based on customer needs and market driven product design.
The correlation of ultimate analysis and calorific value on palm oil briquettes using durian seed adhesives
Authors: Maulina Seri , Sarah M. , Misran E. , Anita M. F.
Published: April 2021

Palm fronds are one of the wastes produced from oil palm plantations that have high potential and are suitable for use as raw material for biomass as renewable energy through carbonization and briquetting processes. Durian seeds contain amylose and amylopectin which can be used as an adhesive to improve the physical quality of the briquettes produced. Palm fronds are carbonized at 300°C for 90 minutes. The charcoal produced is mashed with a ball mill. The gluing process is carried out using an adhesive from durian seeds with a concentration of 5%, 15% and 25% with a char: adhesive ratio of 30:70, 50:50, and 70:30 and compressed at a pressure of 100 kg/m2. Ultimate analysis and calorific value are carried out to test the performance and quality of bio-charcoal briquettes.
Utilization of wood biomass as a renewable energy source using gasification technology
Authors: Maisyarah L , Siregar Y
Published: April 2021

One of the potential uses of biomass is gasification. Therefore, various breakthroughs need to utilizing biomass. One of the possible services of biomass is gasification. The best method for producing woody biomass is gasification conversion technology. The principle of biomass gasification uses incomplete combustion in a room withstand high temperatures called a gasifier. Burning order imperfect can occur, then the air with a small amount of stochiometric needs of explosion flowed into the reactor to supply oxygen needs using a fan/blower. The combustion process that occurs causes a thermo-chemical reaction that produces CO, H2, and methane gas (CH4). The Downdraft gasifier, where the combustible gas had passed to the oxidation part of the combustion by being pulled down so that the resulting gas will be cleaner because the oil will burn when it passes through the oxidation part of the explosion. Gasification of wood sawdust can produce gas fuel. Where more biomass is classified, it will increase the amount of gas delivered to become fuel.
Turpentine oil extraction from pine resin by microwave assisted hydro-distillation (MAHD) technique
Authors: Sarah M , Juwairiah S
Published: April 2021

Turpentine oil obtained from pine resin plant consists ofα-pineneutilized to synthesize organic compound used to produce paint and disinfectant for example. This project aims to study extraction of turpentine oil byMicrowave Assisted Hydro-Distillation(MAHD). This study evaluates effect of time, power and volume of pine resin_to turpentine oil characteristic. Variables observed in this study are time (30 to 90 min), power (300 to 600 Watt) and material (150 to 250 mL). Turpentine oil quality such as color, density and refractive index are identified with respect to SNI 7633-2011 whileα-pineneconcentration determined using GCMS. Highest yield is 27.31% obtained from extraction of 150 mL pine resin using 600 Watt of microwave power for about 60 min. Chemical composition of turpentine oil at that certain condition are α-pinene of 68,53%, 3-carene of 14,31% and β-pinene of 5,23% respectively. Turpentine oil product has characteristic of clear color with refractive index of 1.467 and density of 0.853 g/cm3. This study concludes microwave energy very potential to be utilized as source of energy to extract turpentine oil from pine resin as it proceeding very rapidly.
The effect of fibre loading on characterization and mechanical properties of polyurethane foam composites derived waste cooking oil, polyol and toluene diisocyanate with adding filler sugar palm (Arenga pinnata) fibre
Authors: Lubis Maulida , Prayogo Muhammad A. , Harahap Mara B. , Iriany  , Ginting Muhammad Hendra S. , Lazuardi Iqbal N. , Akbar Rievaldi
Published: April 2021

In the study, sugar palm (Arenga pinnata) fibre reinforced polyurethane foam was prepared by compounding waste cooking oil, polyol and toluene diisocyanate. The composites foam were prepared with different fibre loading: 10%, 20%, 30% and 40% (by weight), with the process conditions : ambient temperature, 1 min stirring and fast stirring. Four samples were cut from polyurethane foam composite and tested according to ASTM standard. Effect of fibre loading on mechanical included tensile strength, FT-IR, and SEM. From the analysis, highest condition of polyurethane foam composites tensile strength was 0.978 MPa.
Minimizing inventory cost of dried food materials availability: An analyzing in teaching hospital
Authors: Sari R M , Firiza S Y , Erwin  , Syahputri K , Rizkya I , Siregar I
Published: April 2021

Excess stock of dried food materials directly proportional to the increase in inventory cost. Average overstock in Teaching Hospital during February 2019 - April 2019 is 39,3% with total capital invested of the overstock of IDR 13.702.247. In addition, an overstock caused by an average total damage of 18,31% which is resulted in a loss of 29,73% of the capital invested in dried food material overstocked. Dried food material excess stock is caused by the absence of a reference limit for orders and the optimal number of orders. The number of orders are not optimal will cause the order frequency to increase and make order costs also increase. The purpose of this research is to prove whether there is a cost minimization of the cost of dried food material which is higher than the Economic Order Quantity (EOQ) model when compared to the actual dried food inventory model. EOQ was used to calculate the optimal number of orders for dried food, safety stock and reorder points calculation. In the total cost of inventory calculation based on actual conditions when compared with the total cost of inventories using the EOQ method for dried food, a saving efficiency of 44,22% is obtained.
Statistical Measures for Trending Video Analysis using knowledge pre-processing and preliminary knowledge Analysis
Authors: Pradhan Rahul , Saxena Akansha , Bansal Divyanshi , Jain Ananya
Published: April 2021

YouTube has an algorithm that decides which videos will appear in the Trending Videos List. Some are more likely to be on the trending list but some videos which were never estimated to be on-trend are seen, it targets viewers’ attention over a short span. On Youtube, trending video lists are not personalized according to a person’s views, likes, or dislikes just like what the recommendation system does, rather its algorithm targets a collective group of people, the same Trending video page is displayed to everyone in a country. In India, the Trending page of. Like various recommendation systems, YouTube also gives you suggestions on your Home page based on your previously watched content. Recommendation systems are so common that we are using it without even knowing it, it makes the user experience much better. Common Examples are Amazon, NetFlix, and now Spotify uses it to suggest to us the music we might love to listen to. The trending videos page updates itself every few minutes (15 minutes). After every update, videos may move up, down, or stay in the same position in the list. Here in this Paper, we used statistical skills to analyze what are the reasons for a video to be on trends. In this paper, we have worked on a dataset for the year 2020. For data collection, we used a Web Scraper script, that’s not part of our work. Based on EDA we can say what is the exact reason for a video to appear on the trending page.
A Pun Identification Framework for Retrieving Equivocation Terms based on HLSTM Learning Model
Authors: Shekhar Shashi , Sharma Rishabh
Published: April 2021

The artificial intelligence system is made linguistically intelligent through HLSTM model to identify pun expressions from code mixed text. The text available on social media domain is written in mixed script format and from these content puns word identification is a challenging task in this scenario. The retrieval of pun and its corresponding equivocation terms is very hard to retrieve from the transliterated text. The pun retrieval and its equivocation representation are widely used to present the opinions over the network applications. The work described in the paper gives the comparative view of different learning models and techniques applied in the area of transliteration for pun word retrieval. The rule framed approach is presented which accepts the roman form text as input and as per the defined rules the system is developed to give the equivocation words available in the sentence. The evaluation measures used here to validate the hypothesis is based on statistical measures along with HLSTM learning model. Further the result is validated using the voting technique that can choose appropriate equivocation label which are not identifies by the learning model. The use of voting technique here is to provide an extra edge when the proposed approaches suggest incorrect tag against the pun word. The voting approach enhances the overall result accuracy with high precision value.
A dataset to evaluate Hindi Word Embeddings
Authors: Soni Vimal Kumar , Gopalani Dinesh , Govil M C
Published: April 2021

The current trend to solve different challenges of Natural Language Processing utilizes various online crawling methods to fetch the data and applying different shallow or deep learning methods to develop models for the respective tasks on this data. Word vectors generated using such methods are being applied for several NLP challenges and such vectors are being evaluated on word similarity task. Not only huge data is available but also multiple datasets are available for the English language to evaluate the performance of the developed models. However, the scenario is not the same for Indian languages specifically for Hindi. Focusing this challenge, we propose a dataset to check word similarity in Hindi. The construction process and afterwards annotation process are described in details. To construct this dataset, first, 353 word-pairs from the most popular English dataset are selected and translated. Their translations are verified by Hindi Experts. These word pairs are finally annotated independently by 11 native Hindi speakers. Multiple criteria have been set to select the annotators for this task. The final dataset has been evaluated on CBOW and Skip-gram models.