Relevant bibliographies by topics / Automated pin setter machine

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  1. Journal articles
  2. Dissertations / Theses

Academic literature on the topic 'Automated pin setter machine'

Author: Grafiati
Published: 28 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Automated pin setter machine"

1

Wang, Y., Z. Wang, N. Gindy, R. Tang, and X. J. Gu. "Automated discrete-pin adjustment for reconfigurable moulding machine." International Journal of Computer Integrated Manufacturing 23, no. 3 (March 2010): 229–36. http://dx.doi.org/10.1080/09511920903527853.

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2

Nwankwo, C., G. Oletu, and O. B. Longe. "Security Enhancement of an Automated Teller Machine Using Fingerprint and Password." advances in multidisciplinary & scientific research journal publication 26, no. 1 (December 11, 2020): 45–50. http://dx.doi.org/10.22624/isteams/v26p5-ieee-ng-ts.

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This paper focuses on how to enhanced security of Transactions in Automatic Teller Machine system using a multi-factor authentication system (Password and Fingerprint). In order to achieve security and to overcome illegal activities, shortcoming of piracy in money transactions, we propose the idea of using fingerprints of customers and password instead of traditional use of PIN number. After authorized verification, the customer will be able to proceed for transaction else after four successive wrong attempts, the ATM card will be ejected automatically and a message will be sent to the registered mobile number. The proposed system is developed to provide better security to the ATMs. Keywords— ATM, Fingerprint, PIN, Biometric.
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3

Pradeep Kumar, S., and N. Shanmugasundaram. "Pin number theft recognition and cash transaction using sixth sense technology in ATM/CDM." International Journal of Engineering & Technology 7, no. 2.31 (May 29, 2018): 178. http://dx.doi.org/10.14419/ijet.v7i2.31.13435.

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Nowadays peoples using credit/debit card for cash transaction for their daily needs. Meanwhile for deposit and withdrawal of huge amount the consumers use the automated teller machine or cash deposit machine. Due to this the crime related to ATM like pin number theft, fraud calls etc increasing day by day. This paper aim to reduce the risk related to pin number theft. We proposed a sixth sense technology which can access by our gestural interface to do the normal operation for cash transaction rather than touching the pin number plate which will be helpful for eliminating the theft related with pin number tracking. The experimental prototype model is designed and the results are verified and presented in this paper.
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4

Oladimeji, Ismaila W., Omidiora E. Olusayo, Ismaila Folasade M., and Falohun Adeleye S.. "Multi-Level Access Control System in Automated Teller Machines." International Journal of Computer Science and Mobile Computing 10, no. 4 (April 30, 2021): 146–55. http://dx.doi.org/10.47760/ijcsmc.2021.v10i04.020.

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E-commerce theft involves using lost/stolen debit/credit cards, forging checks, misleading accounting practices, etc. Due to carelessness of cardholders and criminality activities of fraudsters, the personal identification number (PIN) and using account level based fraud detection techniques methods are inadequate to cub the activities of fraudsters. In recent times, researchers have made efforts of improving cyber-security by employing biometrics traits based security system for authentication. This paper proposed a multi-level fraud detection system in automated teller machine (ATM) operations. The system included PIN level, account-level and biometric level. Acquired RealScan-F scanner was used to capture liveness fingers. Transactional data were generated for each individual fingerprint with unique PIN. The results of the simulation showed that (i) the classification at account level only yielded averages 84.3% precision, 94.5% accuracy and 5.25% false alarm rate; (ii) matching at biometric level using liveness fingerprints samples yielded 0% APCER , 0% NPCER and 100% accuracy better than using fingerprints samples that produced 4.25% APCER , 2.33% NPCER and 93.42% accuracy; (iii) combining the three levels with the condition that all the levels must be positive produced 87.5% precision,84.9% accuracy and 2.65% false alarm rate; (iv) while the classification using voting technique yielded 99.15% precision, 97.35% accuracy and 0.47% false alarm.
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5

Liu, Qing Li, Lei Shen, Albert Tsai, Su Fen Yao, and Edmund Wang. "The Parametric Simulation Design Method of Conjugate Cams of Automatic Pin Insertion Machine Based on Creo Parametric Software." Applied Mechanics and Materials 236-237 (November 2012): 1201–4. http://dx.doi.org/10.4028/www.scientific.net/amm.236-237.1201.

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Cam mechanisms are widely used in automated machines. Conjugate cams have become popular for its eminent kinematics and dynamic performance in research and in industry. As a commonly used cam mechanism in industry, especially in automatic pin insertion machines, conjugate cams have the advantages of being highly efficient, highly accurate and relatively cheap. A parametric simulation method was used to create a conjugate cam profile. This paper describes the steps used to create 3D models of the conjugate cam and the basic principles used to simulate the motion of cam mechanisms. The motion simulations were done with the parametric 3D modeling method using Creo Parametric Software.
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6

Ghozali, Mohammad Shiddiq. "PEMBUATAN PENDETEKSI OBYEK DENGAN METODE YOU ONLY LOOK ONCE (YOLO) UNTUK AUTOMATED TELLER MACHINE (ATM)." Majalah Ilmiah UNIKOM 17, no. 1 (September 30, 2019): 69–76. http://dx.doi.org/10.34010/miu.v17i1.2225.

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Perkembangan Teknologi Informasi dan Komunikasi begitu pesat di zaman sekarang ini. Diikuti pula dengan perkembangan di bidang Artificial Intelligence (AI) atau Kecerdasan Buatan. Di Indonesia sendiri masih belum begitu populer dikalangan masyarakat akan tetapi perusahaan-perusahaan IT berlomba-lomba menciptakan inovasi dibidang Kecerdasan Buatan dan penerapan Kecerdasan Buatan disegala aspek kehidupan. Contoh kasus di Automated Teller Machine (ATM), seringkali terjadi kejahatan di ATM seperti pengintaian nomor pin, skimming, lebanese loop dan kejahatan lainnya. Walaupun di ATM sudah terdapat CCTV akan tetapi penjahat menggunakan alat bantu untuk menutupi wajahnya seperti helm, topi, masker dan kacamata hitam. Biasanya didepan pintu masuk ATM terpampang larangan untuk tidak menggunakan helm, topi, masker dan kacamata hitam serta tidak membawa rokok. Akan tetapi larangan itu masih tetap ada yang melanggar, dikarenakan tidak ada tindak lanjut ketika seseorang menggunakan benda-benda yang dilarang dibawa kedalam ATM. Oleh karena itu penulis membuat sistem pendeteksi obyek di bidang Kecerdasan Buatan untuk mendeteksi benda-benda yang dilarang digunakan ketika berada di ATM. Salah satu metode yang digunakan untuk menciptakan Object Detection yaitu You Only Look Once (YOLO). Implementasi ide ini tersedia pada DARKNET (open source neural network). Cara kerja YOLO yaitu dengan melihat seluruh gambar sekali, kemudian melewati jaringan saraf sekali langsung mendeteksi object yang ada. Oleh karena itu disebut You Only Look Once (YOLO). Pada penelitian ini, penulis membuat sistem yang masih dalam bentuk pengembangan, sehingga menjalankannya masih menggunakan command prompt. Keywords : Automated Teller Machine (ATM), Kecerdasan Buatan, Pendeteksi Obyek, You Only Look Once (YOLO)
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7

Wasril, Abi Rachman, Mohammad Shiddiq Ghozali, and M. Banu Mustafa. "PEMBUATAN PENDETEKSI OBYEK DENGAN METODE YOU ONLY LOOK ONCE (YOLO) UNTUK AUTOMATED TELLER MACHINE (ATM)." Majalah Ilmiah UNIKOM 17, no. 1 (September 30, 2019): 69–76. http://dx.doi.org/10.34010/miu.v17i1.2240.

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Perkembangan Teknologi Informasi dan Komunikasi begitu pesat di zaman sekarang ini. Diikuti pula dengan perkembangan di bidang Artificial Intelligence (AI) atau Kecerdasan Buatan. Di Indonesia sendiri masih belum begitu populer dikalangan masyarakat akan tetapi perusahaan-perusahaan IT berlomba-lomba menciptakan inovasi dibidang Kecerdasan Buatan dan penerapan Kecerdasan Buatan disegala aspek kehidupan. Contoh kasus di Automated Teller Machine (ATM), seringkali terjadi kejahatan di ATM seperti pengintaian nomor pin, skimming, lebanese loop dan kejahatan lainnya. Walaupun di ATM sudah terdapat CCTV akan tetapi penjahat menggunakan alat bantu untuk menutupi wajahnya seperti helm, topi, masker dan kacamata hitam. Biasanya didepan pintu masuk ATM terpampang larangan untuk tidak menggunakan helm, topi, masker dan kacamata hitam serta tidak membawa rokok. Akan tetapi larangan itu masih tetap ada yang melanggar, dikarenakan tidak ada tindak lanjut ketika seseorang menggunakan benda-benda yang dilarang dibawa kedalam ATM. Oleh karena itu penulis membuat sistem pendeteksi obyek di bidang Kecerdasan Buatan untuk mendeteksi benda-benda yang dilarang digunakan ketika berada di ATM. Salah satu metode yang digunakan untuk menciptakan Object Detection yaitu You Only Look Once (YOLO). Implementasi ide ini tersedia pada DARKNET (open source neural network). Cara kerja YOLO yaitu dengan melihat seluruh gambar sekali, kemudian melewati jaringan saraf sekali langsung mendeteksi object yang ada. Oleh karena itu disebut You Only Look Once (YOLO). Pada penelitian ini, penulis membuat sistem yang masih dalam bentuk pengembangan, sehingga menjalankannya masih menggunakan command prompt. Keywords : Automated Teller Machine (ATM), Kecerdasan Buatan, Pendeteksi Obyek, You Only Look Once (YOLO)
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8

Che, Chenggang, and Jun Ni. "Modeling and Calibration of a Structured-light Optical CMM via Skewed Frame Representation." Journal of Manufacturing Science and Engineering 118, no. 4 (November 1, 1996): 595–603. http://dx.doi.org/10.1115/1.2831072.

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A new tetrahedron-target-based approach is presented for the extrinsic calibration of a non-contact “light-striping” (structured light) optical coordinate measuring machine (CMM). The procedure makes automated on-line calibration possible. The system modeling is based on a unique skewed frame representation without the use of pin-hole camera model assumption. It is demonstrated that the extrinsic calibration matrix can be decomposed into two classes of transformations, one homogeneous and the other nonhomogeneous. The nonhomogeneous transformation between a Cartesian world frame and the non-Cartesian skewed sensor frame is studied. The sensitivity of the dimensional deformation on the two skew angles is simulated. Experimental studies show that a micron level calibration accuracy can be achieved.
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Ji, Ling. "Equipment Modification for Friction Stir Joining Based on PLC." Applied Mechanics and Materials 596 (July 2014): 52–55. http://dx.doi.org/10.4028/www.scientific.net/amm.596.52.

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In order to achieve the common drilling and milling machine for friction stir joining (FSJ) , A model ZXTM-40 equipment is modified., it’s workstation transmission mode and axial direction press mode are mechanical transmission, through the modification, install stepper motors and drives , write program code ,PLC control the motor ,it can work to achieve Longitudinal automatic movement . the speed of workstation can input through the Interactive panel, the control system operate parameters to achieve semi-automated operation of equipment and overtravel protection.. In the vertical direction,install a sleeve on the handle, the sleeve has scale and recesses, it can control the pressure measurement of friction stir pin. weights hanged on the sleeve, research proves the optimum parameters are 3KG weights and 40CM away from the center, Workbench moving speed of 125mm/min, rotation speed of 730r/min, it can join 1mm thick 2024 aluminum by FSJ, appearance of bead is good.
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10

Singh, Abhilash, Kumar Gaurav, Atul Kumar Rai, and Zafar Beg. "Machine Learning to Estimate Surface Roughness from Satellite Images." Remote Sensing 13, no. 19 (September 22, 2021): 3794. http://dx.doi.org/10.3390/rs13193794.

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We apply the Support Vector Regression (SVR) machine learning model to estimate surface roughness on a large alluvial fan of the Kosi River in the Himalayan Foreland from satellite images. To train the model, we used input features such as radar backscatter values in Vertical–Vertical (VV) and Vertical–Horizontal (VH) polarisation, incidence angle from Sentinel-1, Normalised Difference Vegetation Index (NDVI) from Sentinel-2, and surface elevation from Shuttle Radar Topographic Mission (SRTM). We generated additional features (VH/VV and VH–VV) through a linear data fusion of the existing features. For the training and validation of our model, we conducted a field campaign during 11–20 December 2019. We measured surface roughness at 78 different locations over the entire fan surface using an in-house-developed mechanical pin-profiler. We used the regression tree ensemble approach to assess the relative importance of individual input feature to predict the surface soil roughness from SVR model. We eliminated the irrelevant input features using an iterative backward elimination approach. We then performed feature sensitivity to evaluate the riskiness of the selected features. Finally, we applied the dimension reduction and scaling to minimise the data redundancy and bring them to a similar level. Based on these, we proposed five SVR methods (PCA-NS-SVR, PCA-CM-SVR, PCA-ZM-SVR, PCA-MM-SVR, and PCA-S-SVR). We trained and evaluated the performance of all variants of SVR with a 60:40 ratio using the input features and the in-situ surface roughness. We compared the performance of SVR models with six different benchmark machine learning models (i.e., Gaussian Process Regression (GPR), Generalised Regression Neural Network (GRNN), Binary Decision Tree (BDT), Bragging Ensemble Learning, Boosting Ensemble Learning, and Automated Machine Learning (AutoML)). We observed that the PCA-MM-SVR perform better with a coefficient of correlation (R = 0.74), Root Mean Square Error (RMSE = 0.16 cm), and Mean Square Error (MSE = 0.025 cm2). To ensure a fair selection of the machine learning model, we evaluated the Akaike’s Information Criterion (AIC), corrected AIC (AICc), and Bayesian Information Criterion (BIC). We observed that SVR exhibits the lowest values of AIC, corrected AIC, and BIC of all the other methods; this indicates the best goodness-of-fit. Eventually, we also compared the result of PCA-MM-SVR with the surface roughness estimated from different empirical and semi-empirical radar backscatter models. The accuracy of the PCA-MM-SVR model is better than the backscatter models. This study provides a robust approach to measure surface roughness at high spatial and temporal resolutions solely from the satellite data.
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Dissertations / Theses on the topic "Automated pin setter machine"

1

Nevoral, Tomáš. "Automatický stavěč kuželek – separace a transport kuželek." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-443022.

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This thesis deals with the design of an automatic non-string pinsetter machine for nine-pin bowling. Firstly, a summary of rules and technical standards important for constructing an automatic pinsetter machine was created. The next part of the thesis contains market research and verification of patent safety. The final part of this thesis is focused on the conceptual design and construction of an automated pinsetter machine. Complete construction and technological design of the sweep wagon, horizontal and vertical elevator of skittles and their practical implementation. Design of (AC) drives for the motorized assembled parts.
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2

Robota, Jakub. "Automatický stavěč kuželek – výtah a metač koule." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-443023.

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The goal of this master’s thesis was to design and construct ninepin ball elevator for automated pin setter machine and ninepin ball launcher to simulate load and to verify correct function of the setter machine. Also, a ball track was designed as a means of transport for the ball from elevator to launcher. Theoretical part of thesis contains research into ninepin bowling, its rules and analysis of different applicable solutions found on the market that deal with automated pin setters and their ball elevators. Furthermore, a separate research into ball launchers was conducted. Practical part of thesis was comprised of own solution to design and construction of elevator, which extended already designed pin setter machine. After this, track for ball was designed and constructed together with ball launcher which imitates load that would the machine experience during usual game.
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