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Journal articles on the topic 'Automatic Identification System'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 March 2023

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1

Johannsen, K. G. "Automatic transmitter identification system." IEEE Transactions on Broadcasting 38, no. 2 (June 1992): 127–32. http://dx.doi.org/10.1109/11.142664.

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2

Li, Kung-Pu. "Automatic language identification/verification system." Journal of the Acoustical Society of America 104, no. 1 (July 1998): 31. http://dx.doi.org/10.1121/1.424049.

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3

Komarov, V. V., and S. A. Garagan. "Functional Requirements for the Automatic System of Vehicle Accident Identification." Izvestiya MGTU MAMI 5, no. 2 (January 20, 2011): 15–23. http://dx.doi.org/10.17816/2074-0530-69824.

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There is a necessity to develop the functional requirements to the automatic system for vehicle accident identification in the automated systems of emergency response to the accident. The list of accident types, which are subject to automatic identification is substantiated. Proposals on the design and use of some sensors, in particular, vehicle element deformation sensors are presented.
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4

Pech-Pacheco, José Luis. "Automatic system for phytoplanktonic algae identification." Limnetica 20, no. 1 (June 15, 2001): 143–58. http://dx.doi.org/10.23818/limn.20.14.

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5

Poo, Danny C. C., Shaojiang Cai, and James T. L. Mah. "UASIS: Universal Automatic SNP Identification System." BMC Genomics 12, Suppl 3 (2011): S9. http://dx.doi.org/10.1186/1471-2164-12-s3-s9.

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6

Steinholtz, B., and K. Walden. "Automatic Identification of Software System Differences." IEEE Transactions on Software Engineering SE-13, no. 4 (April 1987): 493–97. http://dx.doi.org/10.1109/tse.1987.233186.

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7

Schumann-Bischoff, Jan, Stefan Luther, and Ulrich Parlitz. "Nonlinear system identification employing automatic differentiation." Communications in Nonlinear Science and Numerical Simulation 18, no. 10 (October 2013): 2733–42. http://dx.doi.org/10.1016/j.cnsns.2013.02.017.

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8

Dahana, U., and R. O. S. Gurning. "Maritime Aerial Surveillance: Integration Manual Identification System to Automatic Identification System." IOP Conference Series: Earth and Environmental Science 557 (September 15, 2020): 012014. http://dx.doi.org/10.1088/1755-1315/557/1/012014.

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9

Jin, Zuo Tao, and Yun Wang. "Research of a Novel Automatic Management System for Material Storages." Advanced Materials Research 977 (June 2014): 476–79. http://dx.doi.org/10.4028/www.scientific.net/amr.977.476.

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According to the management efficiency of material storages, a design scheme of automatic management system is designed based on radio frequency identification devices. The hardware platform of the system is realized based on nRF2401 and embedded computer technology. The software design of each subsystem is achieved by using the middleware technology of radio frequency identification devices and embedded software development and database programming technology. The field trial experiments and the laboratory testing results indicate that the system can realize effectively the automatic identification and management of material storages. It can improve the operation efficiency and greatly enhance the automation level of material storages management and save the cost of management.
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10

Hussein, Enas. "Fingerprint Identification using Multiwavelet Transform." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 2 (October 26, 2021): 131–38. http://dx.doi.org/10.55562/jrucs.v23i2.485.

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identification systems have been developed to achieve automatic identification of a person based on his physiological or behavioral characteristics. Biometric systems are critical in a wide range of applications such as banking system, E-commerce, smart cards, and access control to secure system. Automatic fingerprint identification is one of the most reliable biometric system, which is used for identifying persons. This study, aim is to design a fingerprint identification system, which is capable of identifying a fingerprint with high level of accuracy. Therefore, this system can be applied to a wide range of forensic applications. The proposed algorithm based upon multiwavelet transform (one level) as feature extraction and minimum distance classifier ( Euclidean distance) to make automatic fingerprint identification . The identification accuracy of this algorithm has been found to be 72%.
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MARIN, Florin-Bogdan, Mihaela MARIN, and Gheorghe GURĂU. "Material Recognition Using CNN Approach for Garbage Collection System." Annals of “Dunarea de Jos” University of Galati. Fascicle IX, Metallurgy and Materials Science 45, no. 4 (December 15, 2022): 126–29. http://dx.doi.org/10.35219/mms.2022.4.20.

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Material identification has been proved to be of important interest for different fields such as industrial automation, autonomous robots The autonomous robots for garbage collection, such as aquatic-cleaning [3] or garbage gathering [6] need the algorithm for identification of materials. Automatic conveyer identification for garbage collection and segregation also use algorithm for material identification. In this paper is proposed an algorithm based on Convolutional Neural Network.
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12

Li and, C. James, and Tung-Yung Huang. "Nonlinear Continuous Dynamic System Identification by Automatic Localized Modeling." Journal of Dynamic Systems, Measurement, and Control 122, no. 2 (July 3, 1997): 354–58. http://dx.doi.org/10.1115/1.482471.

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This paper describes an automated localized modeling method to identify continuous nonlinear dynamic systems from their operating data. Using a method similar to finite element method’s automatic mesh generation, the input space is partitioned into overlapped regions that are small enough that a local model, such as a simple neural network, can approximate the data well in each region. Subsequently, adjacent regions are inspected to see if they can be represented well by a single local model to minimize the number of regions and local models needed to approximate a system. A nonlinear oscillator is used to test the proposed method, and the method was able to generate models that can simulate the system well. [S0022-0434(00)01902-X]
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13

Zhang, Rui, and Feng Wang. "Research on Cogent Automatic Fingerprint Identification System." Advanced Materials Research 605-607 (December 2012): 1741–47. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.1741.

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Cogent Automatic Fingerprint Identification System (CAFIS) was researched by Cogent Co. Ltd. This system filtrated and matched fingerprints feathers automatically by computer to search for similar fingerprints, which are identified by specialists finally. It can provide help for criminal cases. About CAFIS, this paper introduces the principle, fingerprint identification process and the system workflow. Then, it researches five functions modules; they are image acquisition, screening, feathers matching, scoring and sorting; and introduce the algorithm of feather matching briefly. Experimental results show that it has many advantages, such as the big capacity of database, quick matching speed, high accuracy, etc.
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14

Kolarovszki, Peter, and Juraj Vaculík. "Intelligent Storage System Based on Automatic Identification." Transport and Telecommunication Journal 15, no. 3 (September 1, 2014): 185–95. http://dx.doi.org/10.2478/ttj-2014-0016.

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Abstract This article describes RFID technology in conjunction with warehouse management systems. Article also deals with automatic identification and data capture technologies and each processes, which are used in warehouse management system. It describes processes from entering goods into production to identification of goods and also palletizing, storing, bin transferring and removing goods from warehouse. Article focuses on utilizing AMP middleware in WMS processes in Nowadays, the identification of goods in most warehouses is carried through barcodes. In this article we want to specify, how can be processes described above identified through RFID technology. All results are verified by measurement in our AIDC laboratory, which is located at the University of Žilina, and also in Laboratory of Automatic Identification Goods and Services located in GS1 Slovakia. The results of our research bring the new point of view and indicate the ways using of RFID technology in warehouse management system.
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Botani, Dilshad, and Wasfi Saalih. "Automatic Fingerprint Identification System Using Robust Distance." TANMIYAT AL-RAFIDAIN 28, no. 83 (September 1, 2006): 27–38. http://dx.doi.org/10.33899/tanra.2006.161638.

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16

Gorban, Igor I. "Crime automatic speaker verification and identification system." Journal of the Acoustical Society of America 102, no. 5 (November 1997): 3165. http://dx.doi.org/10.1121/1.420769.

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17

Tawfik, Said Lamey. "Automatic Identification System (AIS): Notes and Impacts." Maritime Studies 2005, no. 145 (November 2005): 14–20. http://dx.doi.org/10.1080/07266472.2005.10878797.

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18

Goudossis, Athanassios, and Sokratis K. Katsikas. "Towards a secure automatic identification system (AIS)." Journal of Marine Science and Technology 24, no. 2 (May 30, 2018): 410–23. http://dx.doi.org/10.1007/s00773-018-0561-3.

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19

KHASHMAN, ADNAN. "AUTOMATIC IDENTIFICATION SYSTEM FOR RAW POULTRY PORTIONS." Journal of Food Process Engineering 35, no. 5 (July 12, 2011): 727–34. http://dx.doi.org/10.1111/j.1745-4530.2010.00621.x.

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20

Il-heung, Choi, Oh Sang-heon, Choi Dae-soo, Park Chan-sik, Hwang Dong-hwan, and Lee Sang-jeong. "Time synchronization module for automatic identification system." Wuhan University Journal of Natural Sciences 8, no. 2 (June 2003): 725–30. http://dx.doi.org/10.1007/bf02899841.

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21

Hu, Qing, Yi Jiang, Jingbo Zhang, Xiaowen Sun, and Shufang Zhang. "Development of an Automatic Identification System Autonomous Positioning System." Sensors 15, no. 11 (November 11, 2015): 28574–91. http://dx.doi.org/10.3390/s151128574.

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22

Du, Dong, Jun Ying Zhao, Jian Yuan Lu, Cheng Sheng Wang, and Feng Chuang Yu. "The Design of Industrial Robot Sorting and Pallet System." Applied Mechanics and Materials 536-537 (April 2014): 1009–14. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.1009.

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industrial assembly line development in the direction of automation and flexibility. Not only more and more automated machinery and more industrial manipulator into the production line. Manipulator instead of artificial heavy labor, realize mechanization, automation and flexibility production process. But in the process of production, first of all to the parts, then is all kinds of processing actions. So, will the application of automatic identification in combination with manipulator is very necessary. This paper introduces a can demonstrate the technology training equipment, from the development of the technology are integrated into the software are introduced. Hope that this technology can be widely used in industrial production.
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23

B S, Mrs Nanda. "Identification of Teacher Interaction in Online Class." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 1029–32. http://dx.doi.org/10.22214/ijraset.2022.45430.

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Abstract: The system investigate teacher’s instructional activities from live audio of online class. The system is trained using python to identify the occurrences of eight key instructional activities from teacher audio. The system was able to identify eight key instructional activities using speech recognition techniques with an eye towards providing automatic feedback to teachers. One advancement in the field of automation is the Automated Attendance system replacing the old and traditional attendance marking. This system is based on the face detection and face recognition algorithms. The concept of this paper is to provide real time teacher attendance to the faculty’s data base. Automatically detects the teacher face using the web camera and detect the facial part using Haar cascade algorithm and the image undergoes the various techniques and will compare with reference image, Later the attendance of the teacher is updated .Thus with the help of this system time will be saved and it is so convenient to record the attendance at any time throughout the day.
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24

Jin, Lai Chong, Azrul Azim Abdullah Hashim, Salmiah Ahmad, and Nor Maniha Abdul Ghani. "System Identification and Control of Automatic Car Pedal Pressing System." Journal of Intelligent Systems and Control 1, no. 1 (October 30, 2022): 78–89. http://dx.doi.org/10.56578/jisc010108.

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This paper mainly explores the system identification and control of an automatic car pedal pressing system. Specifically, the system identification was achieved using an artificial neural network, with the help of MATLAB’s System Identification Toolbox. The proportional-integral-derivative (PID) controller and fuzzy logic controller were designed, and normalized with membership functions. These functions were scaled with a gain as a scaling factor. The controller gains were tuned by a metaheuristic algorithm named particle swarm optimization (PSO). On this basis, the two controllers were compared with a number of performance indices, including integral squared error (ISE), integral absolute error (IAE), integral time absolute error (ITAE), and mean squared error (MSE). The car pedal pressing performance was measured at different speed levels for each controller.
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25

Wang, Lu, and Lihong Cui. "Automatic Recognition and Detection System Based on Machine Vision." Journal of Control Science and Engineering 2022 (July 6, 2022): 1–7. http://dx.doi.org/10.1155/2022/7318374.

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In order to realize the automation of part identification and detection and the intellectualization of part production, this paper proposes a method of automatic identification and detection of parts based on machine vision (overall method). This paper combines machine vision with motion control theory and uses pulse coupled neural network (PCNN) edge detection and recognition algorithms to preliminarily design a set of machine vision automatic recognition and detection systems and carry out detection and recognition experiments on small parts such as relay covers. The experimental results show that the whole process of part size detection and recognition, including part feeding, image acquisition, size recognition, part screening, and reset of the experimental platform, can be completed within 5 s and can carry out high-precision dynamic recognition and detection when the part moves at a speed of 1 m/s. Through the correction and compensation of dynamic error, the detection accuracy of small rectangular parts with a length of 28.87 mm and a width of 12.36 mm can reach 0.04 mm. The visual inspection and recognition automation system improves the automation degree of parts inspection, improves the dimensional accuracy, optimizes the robustness of the system, and finally realizes the real-time screening and classification of parts and the efficient production of parts.
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26

Bai, Zhen Lin, Qin Run Wen, and Mei Yang. "A Pearl Automatic Sorting System Based on Image Identification." Applied Mechanics and Materials 496-500 (January 2014): 1574–77. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1574.

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This paper introduces a pearl automatic sorting system. The design conforms to the national condition of our country. With the use of pearl automatic sorting system, automatic sorting instead of the cumbersome manual sorting workers. It uses computer image processing technology and numerical control technology. It has a positive effect to guarantee product quality. And it can improve the market competitiveness of enterprises.
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27

Huang, Jie, Yong Jun Zheng, Wei Bai, and Jia Jun Ding. "Electronic Scale Automatic Calibration System with Image Identification." Advanced Materials Research 468-471 (February 2012): 1609–12. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.1609.

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A new automatic calibration system for electronic scale with image identification is developed. The system is composed with mechanical part, pneumatic components, PLC, USB camera and computer. Labview is the developing platform with user interface, PLC is controlled by Labview via OPC configuration to load or unload the standard weights, image machine vision technology is used to automatic recognize the LED char displayed on electronic scale.
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28

Feng, Xiaozhen, Yiping Cao, Kuang Peng, and Cheng Chen. "An online identity authentication method for blood smear." Journal of Innovative Optical Health Sciences 09, no. 06 (August 2016): 1550039. http://dx.doi.org/10.1142/s179354581550039x.

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Blood smear test is the basic method of blood cytology and is also a standard medical test that can help diagnose various conditions and diseases. Morphological examination is the gold standard to determine pathological changes in blood cell morphology. In the biology and medicine automation trend, blood smears' automated management and analysis is very necessary. An online blood smear automatic microscopic image detection system has been constructed. It includes an online blood smear automatic producing part and a blood smear automatic microscopic image detection part. Online identity authentication is at the core of the system. The identifiers printed online always present dot matrix digit code (DMDC) whose stroke is not continuous. Considering the particularities of DMDC and the complexities of online application environment, an online identity authentication method for blood smear with heterological theory is proposed. By synthesizing the certain regional features according to the heterological theory, high identification accuracy and high speed have been guaranteed with few features required. In the experiment, the sufficient correct matches between the tube barcode and the identification result verified its feasibility and validity.
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Kim, Hankil, Jaehyun Park, and Hoekyung Jung. "Automatic control system based on iot data identification." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 3 (September 1, 2020): 1525. http://dx.doi.org/10.11591/ijeecs.v19.i3.pp1525-1532.

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<p>Recently, as the Internet of Things (IoT) technology has developed, researches are rigorously conducted to construct smart environments such as smart home, smart grid, and industrial IoT. However, currently existing systems consists of a series of events, and even if an existing task is running, unnecessary work still occurs as both works happen simultaneously. In this paper, we propose an automatic work control system to solve this problem. The proposed system transmits the data measured by the sensor to the server and identifies non - real - time tasks such as real - time work which is related to the dangerous situations, ventilation and temperature control. In addition, priority among the tasks is set in a way that existing tasks are stopped when high priority tasks occur. Accordingly, this can reduce the unnecessary waste of power, and the user is able to receive a proactive service.</p>
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A. Shawkat, Shihab, Khalid Saeed Lateef Al-badri, and Ahmed Ibrahim Turki. "The new hand geometry system and automatic identification." Periodicals of Engineering and Natural Sciences (PEN) 7, no. 3 (August 9, 2019): 996. http://dx.doi.org/10.21533/pen.v7i3.632.

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Zhao, Yue, Lin Zhou, Aocheng Zhou, and Yao Xiao. "Automatic insect identification system based on SE-ResNeXt." International Journal of Systems, Control and Communications 1, no. 1 (2022): 1. http://dx.doi.org/10.1504/ijscc.2022.10049960.

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32

Jiang, Yi, Shufang Zhang, and Dongkai Yang. "Accuracy Analysis of Automatic Identification System Position Estimation." Information Technology Journal 12, no. 22 (November 1, 2013): 6849–51. http://dx.doi.org/10.3923/itj.2013.6849.6851.

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33

Srivastava, Priyank, Rahul Sindhwani, Bhupendra Prakash Sharma, Aditya Vikram Singla, Raghav Gupta, and Aditya Goyal. "Development of Automatic Waste Identification and Segregation System." Materials Today: Proceedings 47 (2021): 3943–46. http://dx.doi.org/10.1016/j.matpr.2021.03.648.

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34

Fadlil, Abdul. "An Automatic Identification System of Human Skin Irritation." TELKOMNIKA (Telecommunication Computing Electronics and Control) 8, no. 3 (December 1, 2010): 255. http://dx.doi.org/10.12928/telkomnika.v8i3.627.

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35

Ma, Nan, Xin Hao Chen, Xiang Ming Liu, and Yun Bai. "Automatic System for Identification and Analysis of Burst." Advanced Materials Research 590 (November 2012): 451–58. http://dx.doi.org/10.4028/www.scientific.net/amr.590.451.

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Although there are complex patterns of discharges exist in neurons, which are often clustered in bursts, the pattern of the burst discharge can substantially change with the alternation of the living environment of the neurons. Furthermore, there is a big difference in the physiological and pharmacological characteristics of various types of burst discharges. So it is necessary to analyze the information contained in various types of burst discharges. Here, an automatic system for identification and analysis of the neuron discharge based on plotting histograms of the logarithm of the interspike interval was designed. The system consists of neuron discharge collecting unit, neuron discharge processing unit, battery monitoring, real-time charging unit and bursts processing software. The system can identify the burst discharge from the neuron discharge without any omission and make statistical analysis. By using this device, the electrophysiological experiment that the spontaneous and evoked discharges of wide dynamic range neurons in spinal dorsal horn of rats were recorded was smoothly completed. The result of statistical analysis indicated that the device can give the corresponding interspike interval aimed at various types of burst discharges and respectively identify the burst discharges in the different amplitude spikes, which provide a tool for further research on the biosensor and the neural communication.
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Mitchell, Kenneth N., and Brandan Scully. "Waterway Performance Monitoring with Automatic Identification System Data." Transportation Research Record: Journal of the Transportation Research Board 2426, no. 1 (January 2014): 20–26. http://dx.doi.org/10.3141/2426-03.

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37

Shirali-Shahreza, Sajad, Hassan Abolhassani, and M. Hassan Shirali-shahreza. "Fast and scalable system for automatic artist identification." IEEE Transactions on Consumer Electronics 55, no. 3 (August 2009): 1731–37. http://dx.doi.org/10.1109/tce.2009.5278049.

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Shao, Yuanyuan, Guantao Xuan, Yangyan Zhu, Yanling Zhang, Hongxing Peng, Zhongzheng Liu, and Jialin Hou. "Research on automatic identification system of tobacco diseases." Imaging Science Journal 65, no. 4 (May 4, 2017): 252–59. http://dx.doi.org/10.1080/13682199.2017.1319609.

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Kim, Kyung-Wha, Byung-Min So, and Ha-Jin Yu. "Forensic Automatic Speaker Identification System for Korean Speakers." Phonetics and Speech Sciences 4, no. 3 (September 30, 2012): 95–101. http://dx.doi.org/10.13064/ksss.2012.4.3.095.

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Singh Lehal, Gurpreet, Tejinder Singh, and Saini Pretpal Kaur Buttar. "Automatic Bilingual Legacy-Fonts Identification and Conversion System." Research in Computing Science 86, no. 1 (December 31, 2014): 9–23. http://dx.doi.org/10.13053/rcs-86-1-1.

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Lanitis, A., CJ Taylor, and TF Cootes. "Automatic face identification system using flexible appearance models." Image and Vision Computing 13, no. 5 (June 1995): 393–401. http://dx.doi.org/10.1016/0262-8856(95)99726-h.

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., Vishnu K. B. "AUTOMATIC NUMBER PLATE RECOGNITION SYSTEM FOR VEHICLE IDENTIFICATION." International Journal of Research in Engineering and Technology 04, no. 15 (April 25, 2015): 1–4. http://dx.doi.org/10.15623/ijret.2015.0415001.

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Cabrera, F., N. Molina, M. Tichavska, and V. Araña. "Automatic Identification System modular receiver for academic purposes." Radio Science 51, no. 7 (July 2016): 1038–47. http://dx.doi.org/10.1002/2015rs005895.

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Sang-heon, Oh, Kim Seung-pum, Hwang Dong-hwan, Park Chan-sik, and Lee Sang-jeong. "Channel access algorithm design for automatic identification system." Wuhan University Journal of Natural Sciences 8, no. 2 (June 2003): 712–18. http://dx.doi.org/10.1007/bf02899839.

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Xiao, Yao, Aocheng Zhou, Lin Zhou, and Yue Zhao. "Automatic insect identification system based on SE-ResNeXt." International Journal of Systems, Control and Communications 14, no. 1 (2023): 81. http://dx.doi.org/10.1504/ijscc.2023.127487.

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Lee, Han Soo, Su Dae Kim, Yong Hyun Kim, Jung Min Kim, and Sung Shin Kim. "Automated Precipitate Identification for Sludge Volume Indicator." Advanced Materials Research 488-489 (March 2012): 1636–40. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.1636.

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Nowadays, since sewage disposal plant monitoring system is changed to combine automating control system tendency, automatic measurement method is widely applicable water temperature, pH, BOD, COD, suspended solid, etc. And its tendency is accumulated objective data. However, in the case of leaking suspended solid concentration measurement, it is literally not a long way from managing settling procedure. Because it has an effect on SS concentration of leaked water only when settled ability is disturbed. In other words, it means that research about solid-liquid separation activated sludge on automated monitoring system currently lacks, and needs research in this field. Considering that sedimentation process in the biological treatment process is one of the most important part, currently performed way, namely, SVI measured and judged by experienced specialists in standard procedure has weaknesses which objectivity cannot be guaranteed. Therefore, for maintaining the consistency of judging criteria and ensuring continuity of knowledge, objectified in the settling process is needed to build diagnostic systems. This paper proposed the method using image processing techniques over time due to settling of the sludge is analyzed for changes in height, also due to changes in sedimentation rate by analyzing the performance of the sludge settling, then send administrator for the system to pass the current state of the sludge.
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Bai, Zhen Long, and Xiang Li. "Dial Instrument Calibration by both Automatic and Half-Automatic Methods." Applied Mechanics and Materials 157-158 (February 2012): 581–88. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.581.

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This paper presents a calibration system by video processing technique. The system can calibrate large number of different types of dial instruments. The system is composed of an automatic recog-nition approach and a half-automatic approach. Both the automatic calibration and half-automatic calibration include four steps: 1st, dial plane circle edge extraction and center identification; 2nd, pointer extraction; 3rd, scale start and end position identification; 4th, result reading. For half-automatic method, the 1st step and 3rd step are manually indentified. By experiments and practical application in industry, it proves that our calibration system is effective for more than hundreds of different types of dial instruments.
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Zhong, Bo Cheng, and Yi Jun Shen. "Remote Attendance System Based on RFID." Applied Mechanics and Materials 380-384 (August 2013): 4080–83. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.4080.

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Radio Frequency Identification (RFID) is an automatic identification technology that can identify the objects at a distance.This paper presents the design of remote attenance system based RFID. The system is implemented for the automation of time and attenance using a new mode of barrer-free channel. With a simple setting, the attendance system is capable of recording real time attendance, counting attendance and attenance statistics analysis. Reports and charts will be provided for the top management to make decision, annual review, and planning on man power. The applied result of the system shows that it is simple and effective.
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Dai, Hong Wei. "Automatic Recognition of Undersea Target Detection." Applied Mechanics and Materials 329 (June 2013): 457–60. http://dx.doi.org/10.4028/www.scientific.net/amm.329.457.

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In order to solve the problem of undersea detection target identification systems low recognition rate, this article introduces the momentum item and uses the invariable length of stride in the undersea detection system's neural network. Through computer simulation, results show that: improved identification system has been greatly improved in the recognition time. This is extremely advantageous to realize real-time automatic target detection undersea identification.
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Zhang, Ming Hui, and Yao Yu Zhang. "The Application of Biometric Identification Technology in ATM System." Applied Mechanics and Materials 347-350 (August 2013): 3419–21. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3419.

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Abstract:
Biometric identification technology deals with the identification of individuals based on their biological or human behavioral characteristics. Biometric identification method is reliable, anti-counterfeit, convenient and safe. At present there are some insecurity factors in the ATM (automatic teller machine) in bank system. Methods such as combining biological recognition with the ATM machine, adding the face recognition technology, fingerprint recognition, second generation ID card recognition, enhancing automatic identification are developed to improve the security of ATM.
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