Search results for: biometric

Authors: Patrick O. Bobbie, Prince S. Attrams

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In recent times, the rapid change in new technologies has spurred up the way and manner records are handled in educational institutions. Also, there is a need for reliable access and ease-of use to these records, resulting in increased productivity in organizations. In academic institutions, such benefits help in quality assessments, institutional performance, and assessments of teaching and evaluation methods. Students in educational institutions benefit the most when advanced technologies are deployed in accessing records. This research paper discusses the use of biometric technologies coupled with smartcard technologies to provide a unique way of identifying students and matching their data to financial records to grant them access to restricted areas such as examination halls. The system developed in this paper, has an identity verification component as part of its main functionalities. A systematic software development cycle of analysis, design, coding, testing and support was used. The system provides a secured way of verifying student’s identity and real time verification of financial records. An advanced prototype version of the system has been developed for testing purposes.

Keywords: biometrics, smartcards, identity-verification, fingerprints

Procedia PDF Downloads 379

Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

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The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

Procedia PDF Downloads 360

Authors: Hachemi Nouria

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The olive tree is a Mediterranean tree, which belongs to the family Oleaceae. The Olea genus contains various species and subspecies, and the only species bearing edible fruit is Olea europaea. The desired issue in this study is to provide the current status of plant cover and especially the training in Olea europaea currently existing in the major centers of the region of Tlemcen. While based on the flora and biometric aspect of this plant germplasm. In order to make an assessment of the phytomass, we made measurements of the four parameters of the aerial part of the taxon: height, diameter, and canopy density to ten feet of the olive tree per station. The floristic analysis shows a certain floristic difference between the different stations. The vegetal formations reflect the biotic and abiotic conditions including climate affecting the ecosystem. Biometric study on the feet of Olea in the six study sites, has led us to conclude that the four measured parameters provides insight on the development or degradation of Olea feet depending on the layout of the stations and the factors environmental. We find that the terrains are havens for these assets. Also the local microclimate (Oued Thalweg) promotes the healthy development of this species.

Keywords: olivier, ecology, biometrics, Tlemcen, Algeria

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Authors: Ibrahim Rabiu Darazo

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The research has been conducted on the impact of E-banking on the operational efficiency of Banks in Nigeria, A case of some selected banks (Diamond Bank Plc, GTBankPlc, and Fidelity Bank Plc) in Nigeria. The research is a quantitative research which uses both primary and secondary sources of data collection. Questionnaire were used to obtained accurate data, where 150 Questionnaire were distributed among staff and customers of the three Banks , and the data collected where analysed using chi-square, whereas the secondary data where obtained from relevant text books, journals and relevant web sites. It is clear from the findings that, the use of e-banking by the banks has improved the efficiency of these banks, in terms of providing efficient services to customers electronically, using Internet Banking, Telephone Banking ATMs, reducing time taking to serve customers, e-banking allow new customers to open an account online, customers have access to their account at all the time 24/7.E-banking provide access to customers information from the data base and cost of check and postage were eliminated using e-banking. The recommendation at the end of the research include; the Banks should try to update their electronic gadgets, e-fraud(internal & external) should also be controlled, Banks shall employ qualified man power, Biometric ATMs shall be introduce to reduce fraud using ATM Cards, as it is use in other countries like USA.

Keywords: banks, electronic banking, operational efficiency of banks, biometric ATMs

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Authors: Behnam Zahednejad, Saeed Kosari

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Widespread deployment of Internet of Things (IoT) has raised security and privacy issues in this environment. Designing a secure two-factor authentication scheme between the user and server is still a challenging task. In this paper, we focus on Cancelable Biometric (CB) as an authentication factor in IoT. We show that previous CB-based scheme fail to provide real two-factor security, Perfect Forward Secrecy (PFS) and suffer database attacks and traceability of the user. Then we propose our improved scheme based on CB and Physically Unclonable Functions (PUF), which can provide real two-factor security, PFS, user’s unlinkability, and resistance to database attack. In addition, Key Compromise Impersonation (KCI) resilience is achieved in our scheme. We also prove the security of our proposed scheme formally using both Real-Or-Random (RoR) model and the ProVerif analysis tool. For the usability of our scheme, we conducted a performance analysis and showed that our scheme has the least communication cost compared to the previous CB-based scheme. The computational cost of our scheme is also acceptable for the IoT environment.

Keywords: IoT, two-factor security, cancelable biometric, key compromise impersonation resilience, perfect forward secrecy, database attack, real-or-random model, ProVerif

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Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

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Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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Authors: Mai Anh Tuan, Wenlong Liu, Meng Li

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Despite warnings and concerns about the use of fast food that has health effects, the fast-food industry is actually a source of profit for the global food industry. Obviously, in the face of such huge economic benefits, investors will not hesitate to continuously add recipes, processing methods, menu diversity, etc., to improve and apply information technology in enhancing the diners' experience; the ultimate goal is still to attract diners to find their brand and give them the fastest, most convenient and enjoyable service. In China, as the achievements of the industrial revolution 4.0, big data and artificial intelligence are reaching new heights day by day, now fast-food diners can instantly pay the bills only by identifying the biometric signature available on the self-ordering kiosk, using their own face without any additional form of confirmation. In this study, the author will evaluate the acceptance level of customers with this new form of payment through a survey of customers who have used and witnessed the use of smart kiosks and biometric payments within the city of Nanjing, China. A total of 200 valid volunteers were collected in order to test the customers' intentions and feelings when choosing and experiencing payment through AI services. 55% think that it bothers them because of the need for personal information, but more than 70% think that smart kiosk brings out many benefits and convenience. According to the data analysis findings, perceived innovativeness has a positive influence on satisfaction which in turn affects behavioral intentions, including reuse and word-of-mouth intentions.

Keywords: artificial intelligence, catering industry, smart kiosks, technology acceptance

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Authors: A. Smaï, H. Idouhar-Saadi, S. Zenia, F. Haddadj, A. Aboun, S.Doumandji

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The quail is the smallest member of the order fowl. His captive breeding has been practiced for centuries by the Japanese. Knowing that in the literature, it is mentioned that the end of lay is noted for the age of 6 months, our work has revealed a good egg production by females aged up to 35 weeks of age. In the same vein, our study focused on various parameters such as weight, diet and the number of eggs laid and this in order to better know the potential production and reproduction of domestic quail. Egg production has started from the 8th week of age of breeding, crop them and their counts are conducted daily basis until the age of 35 weeks. Indeed, biometric parameters are studied such as weight, length, and the largest diameter, the shape index, the index of shell, in order to analyze the physical condition of eggs by females of age. Until the age of 22 weeks, the eggs have maintained good biometric features. Japanese quail are best producing eggs. Hatchability is also considered. They are excellent poultry yields, since they begin laying eggs in two months and can provide abundant nesting with females over 8 months in our study. Other farms results reveal conclusions. Indeed, one aspect remains to be developed; it is the analysis of nutritional and therapeutic values of eggs over the age of females. The latter, given their wealth is a dietary supplement of animal origin with dietary value (it contains 0 cholesterol) that characterizes the quail eggs. Raising quail among other reproduction requires minimal when compared to other domestic birds space, this is the second breeding, in terms of importance after the chicken. Therefore, in the case of a farm that works exclusively in the production of eggs, requires minimal work and free space, as well as reduced costs.

Keywords: Japanese quail, reproduction, eggs, biometrics, reproductive age

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Authors: Jianfeng Hu

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Personal authentication based on electroencephalography (EEG) signals is one of the important field for the biometric technology. More and more researchers have used EEG signals as data source for biometric. However, there are some disadvantages for biometrics based on EEG signals. The proposed method employs entropy measures for feature extraction from EEG signals. Four type of entropies measures, sample entropy (SE), fuzzy entropy (FE), approximate entropy (AE) and spectral entropy (PE), were deployed as feature set. In a silhouettes calculation, the distance from each data point in a cluster to all another point within the same cluster and to all other data points in the closest cluster are determined. Thus silhouettes provide a measure of how well a data point was classified when it was assigned to a cluster and the separation between them. This feature renders silhouettes potentially well suited for assessing cluster quality in personal authentication methods. In this study, “silhouettes scores” was used for assessing the cluster quality of k-means clustering algorithm is well suited for comparing the performance of each EEG dataset. The main goals of this study are: (1) to represent each target as a tuple of multiple feature sets, (2) to assign a suitable measure to each feature set, (3) to combine different feature sets, (4) to determine the optimal feature weighting. Using precision/recall evaluations, the effectiveness of feature weighting in clustering was analyzed. EEG data from 22 subjects were collected. Results showed that: (1) It is possible to use fewer electrodes (3-4) for personal authentication. (2) There was the difference between each electrode for personal authentication (p<0.01). (3) There is no significant difference for authentication performance among feature sets (except feature PE). Conclusion: The combination of k-means clustering algorithm and silhouette approach proved to be an accurate method for personal authentication based on EEG signals.

Keywords: personal authentication, K-mean clustering, electroencephalogram, EEG, silhouettes

Procedia PDF Downloads 248

Authors: Amina Smaï, Habiba Idouhar-Saadi, Safia Zenia, Fairouz Haddadj, Salaheddine Doumandji

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The poultry industry (chicken and egg consumption) has become important in Algeria, but that does not prevent other farms from beginning to position themselves on the ground like the turkey, guinea fowl, partridge and quail Japanese. The breeding importance of this last, reside, also in game meat, egg quality and their therapeutic role without forgetting its growth performance. To the same effect, a study was held at the center of Zeralda hunting on various parameters such as the weight and number of eggs laid and this in order to know better the potential of production and reproduction of domestic quail. Egg laying has started from the 8th week of reproductive age, their harvest and their counts are performed daily up to 32 weeks of age and more. We have given the biometrics of incubated eggs and unhatched eggs. The parameters studied were the weight, large and small diameter, density, volume, shell index and the shape index. The work revealed that the maximum weight in males is reached in the 11th week, against the female, he reached the 13th week of age. Indeed, there is a good correlation (R = 0.79) between the weight of females and egg production. The rate of unhatched eggs varies between 11 and 43%, these values are recorded respectively in breeding under the age of 25 and 43 weeks. Furthermore, the biometric parameters of hatched and unhatched eggs have differences that are marked, especially during the beginning and end of lay. Further results will be subsequently exploited. Indeed, rearing Japanese quail is easy in technical terms and does not require big investment but its practical application vigilance and daily presence of the breeder within the farm who oversees the hygiene and well-being of its poultry.

Keywords: Japanese quail, biometrics, eggs, unhatching eggs, reproduction

Procedia PDF Downloads 157

Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran

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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.

Keywords: access control, multimodal biometrics, pattern recognition, security safe

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Authors: Mokopane Charles Marakalala

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Research shows that mobile fraud has grown exponentially in South Africa during the lockdown caused by the COVID-19 pandemic. According to the South African Banking Risk Information Centre (SABRIC), fraudulent online banking and transactions resulted in a sharp increase in cybercrime since the beginning of the lockdown, resulting in a huge loss to the banking industry in South Africa. While the Financial Intelligence Centre Act, 38 of 2001, regulate financial transactions, it is evident that criminals are making use of technology to their advantage. Money-laundering ranks among the major crimes, not only in South Africa but worldwide. This paper focuses on the impact of biometric-based solutions in combatting mobile fraud at the South African Risk Information. SABRIC had the challenges of a successful mobile fraud; cybercriminals could hijack a mobile device and use it to gain access to sensitive personal data and accounts. Cybercriminals are constantly looting the depths of cyberspace in search of victims to attack. Millions of people worldwide use online banking to do their regular bank-related transactions quickly and conveniently. This was supported by the SABRIC, who regularly highlighted incidents of mobile fraud, corruption, and maladministration in SABRIC, resulting in a lack of secure their banking online; they are vulnerable to falling prey to fraud scams such as mobile fraud. Criminals have made use of digital platforms since the development of technology. In 2017, 13 438 instances involving banking apps, internet banking, and mobile banking caused the sector to suffer gross losses of more than R250,000,000. The final three parties are forced to point fingers at one another while the fraudster makes off with the money. A non-probability sampling (purposive sampling) was used in selecting these participants. These included telephone calls and virtual interviews. The results indicate that there is a relationship between remote online banking and the increase in money-laundering as the system allows transactions to take place with limited verification processes. This paper highlights the significance of considering the development of prevention mechanisms, capacity development, and strategies for both financial institutions as well as law enforcement agencies in South Africa to reduce crime such as money-laundering. The researcher recommends that strategies to increase awareness for bank staff must be harnessed through the provision of requisite training and to be provided adequate training.

Keywords: biometric-based solution, investigation, cybercrime, forensic investigation, fraud, combatting

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Authors: Kevin V. Bui, Richard A. Claytor, Elizabeth M. Priolo, Weihui Li

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Oxygen deprivation masks operate through the use of restricting valves as a means to reduce respiratory flow where flow is inversely proportional to the resistance applied. This produces the same effect as higher altitudes where lower pressure leads to reduced respiratory flow. Both increased resistance with restricting valves and reduce the pressure of higher altitudes make breathing difficultier and force breathing muscles (diaphragm and intercostal muscles) working harder. The process exercises these muscles, improves their strength and results in overall better breathing efficiency. Currently, these oxygen deprivation masks are purely mechanical devices without any electronic sensor to monitor the breathing condition, thus not be able to provide feedback on the breathing effort nor to evaluate the lung function. That is part of the reason that these masks are mainly used for high-level athletes to mimic training in higher altitude conditions, not suitable for patients or customers. The design aims to improve the current method of oxygen deprivation mask to include a larger scope of patients and customers while providing quantitative biometric data that the current design lacks. This will be accomplished by integrating sensors into the mask’s breathing valves along with data acquisition and Bluetooth modules for signal processing and transmission. Early stages of the sensor mask will measure breathing rate as a function of changing the air pressure in the mask, with later iterations providing feedback on flow rate. Data regarding breathing rate will be prudent in determining whether training or therapy is improving breathing function and quantify this improvement.

Keywords: oxygen deprivation mask, lung function, spirometer, Bluetooth

Procedia PDF Downloads 193

Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: B. S. Akhmetov, S. T. Akhmetova, A. I. Ivanov, T. S. Kartbayev, A. Y. Malygin

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The problem of training of a network of artificial neurons in biometric appendices is that this process has to be completely automatic, i.e. the person operator should not participate in it. Therefore, this article discusses the issues of training the network of artificial neurons and the description of the non-iterative learning algorithm of artificial neuron.

Keywords: artificial neuron, biometrics, biometrical applications, learning of neuron, non-iterative algorithm

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Authors: Prakash, Vikash Kumar, Vinay Bansal, L. N. Das

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Dual biometrics is a subpart of multimodal biometrics, which refers to the use of a variety of modalities to identify and authenticate persons rather than just one. We limit the risks of mistakes by mixing several modals, and hackers have a tiny possibility of collecting information. Our goal is to collect the precise characteristics of iris and palmprint, produce a fusion of both methodologies, and ensure that authentication is only successful when the biometrics match a particular user. After combining different modalities, we created an effective strategy with a mean DI and EER of 2.41 and 5.21, respectively. A biometric system has been proposed.

Keywords: multimodal, fusion, palmprint, Iris, EER, DI

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Authors: Mohammad A. Alia, Abdelfatah Aref Tamimi, Omaima N. A. Al-Allaf

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This paper reviews a comparison study on the most common used authentication methods. Some of these methods are actually based on cryptography. In this study, we show the main cryptographic services. Also, this study presents a specific discussion about authentication service, since the authentication service is classified into several categorizes according to their methods. However, this study gives more about the real life example for each of the authentication methods. It talks about the simplest authentication methods as well about the available biometric authentication methods such as voice, iris, fingerprint, and face authentication.

Keywords: information security, cryptography, system access control, authentication, network security

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Authors: Soheir El-Shazly, Gouda Abdel-Gawad, Yasser Salama, Dina Sayed

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Twelve species belonging to genus Carolia Cantraine, 1838 were recorded from nine localities in the Tertiary rocks of the Tethys, Atlantic and Eastern Pacific Provinces. During The Eocene two species were collected from Indian-Pakistani region, two from North Africa (Libya, Tunis and Algeria), one from Jamaica and two from Peru. The Oligocene shows its appearance in North America (Florida) and Argentina. The genus showed its last occurrence in the Miocene rocks of North America (Florida) before its extinction. In Egypt, the genus was diversified in the Eocene rocks and was represented by four species and two subspecies. The paleobiogeographic distribution of Genus Carolia Cantraine, 1838 indicates that it appeared in the Lower Eocene of West Indian Ocean and migrated westward flowing circumtropical Tethys Current to the central Tethyan province, where it appeared in North Africa and continued its dispersal westward to the Atlantic Ocean and arrived Jamaica in the Middle Eocene. It persisted in the Caribbean Sea and appeared later in the Oligocene and Miocene rocks of North America (Florida). Crossing Panama corridor, the genus migrated to the south Eastern Pacific Ocean and was collected from the Middle Eocene of Peru. The appearance of the genus in the Oligocene of the South Atlantic Coast of Argentina may be via South America Seaway or its southward migration from Central America to Austral Basin. The thickening of the upper valve of the genus, after the loss of its byssus to withstand the current action, caused inability of the animal to carry on its vital activity and caused its extinction. The biometric study of Carolia placunoides Cantraine, 1938 from thhe Eocene of Egypt, indicates that the distance between the muscle scars in the upper valve increases with the closure of the byssal notch.

Keywords: Atlantic, carolia, paleobiogeography, tethys

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Authors: Kleche Myriam, Ziane Nadia, Berrebbah Houria, Djebar Mohammed Reda

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The Phytoremediation has now become a necessity. Thus, in our work, we are interested in the biological wastewater treatment of Oued Meboudja. The physicochemical analysis of water after treatment showed a significant reduction of suspended matter, COD and BOD5 and rate of metals in roots for example iron and zinc. We also highlighted some significant changes in biometric and physiological parameters such as increasing the number of roots and increased respiratory metabolism through the oxygen consumption in isolated roots of Phragmites australis, placed in a polluted environment.

Keywords: phragmites australis, roots, phytoremediation, iron, zinc

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

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Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

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Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: biometrics, deep learning, handwriting, signature forgery

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Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik

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Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.

Keywords: biometrics, face recognition, facial landmarks, image processing

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Authors: Andrew Lock, Alastair Allen

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Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance of investigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: biometrics, iris recognition, reversible watermarking, vision engineering

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Authors: Emmanuel Ogala

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Cloud computing has been envisioned as the next-generation architecture of Information Technology (IT) enterprise. In contrast to traditional solutions where IT services are under physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centres, where the management of the data and services may not be fully trustworthy. This is due to the fact that the systems are opened to the whole world and as people tries to have access into the system, many people also are there trying day-in day-out on having unauthorized access into the system. This research contributes to the improvement of cloud computing security for better operation. The work is motivated by two problems: first, the observed easy access to cloud computing resources and complexity of attacks to vital cloud computing data system NIC requires that dynamic security mechanism evolves to stay capable of preventing illegitimate access. Second; lack of good methodology for performance test and evaluation of biometric security algorithms for securing records in cloud computing environment. The aim of this research was to evaluate the performance of an integrated security system (ISS) for securing exams records in cloud computing environment. In this research, we designed and implemented an ISS consisting of three security mechanisms of biometric (fingerprint), auto-PIN and password into one stream of access control and used for securing examination records in Kogi State University, Anyigba. Conclusively, the system we built has been able to overcome guessing abilities of hackers who guesses people password or pin. We are certain about this because the added security system (fingerprint) needs the presence of the user of the software before a login access can be granted. This is based on the placement of his finger on the fingerprint biometrics scanner for capturing and verification purpose for user’s authenticity confirmation. The study adopted the conceptual of quantitative design. Object oriented and design methodology was adopted. In the analysis and design, PHP, HTML5, CSS, Visual Studio Java Script, and web 2.0 technologies were used to implement the model of ISS for cloud computing environment. Note; PHP, HTML5, CSS were used in conjunction with visual Studio front end engine design tools and MySQL + Access 7.0 were used for the backend engine and Java Script was used for object arrangement and also validation of user input for security check. Finally, the performance of the developed framework was evaluated by comparing with two other existing security systems (Auto-PIN and password) within the school and the results showed that the developed approach (fingerprint) allows overcoming the two main weaknesses of the existing systems and will work perfectly well if fully implemented.

Keywords: performance evaluation, fingerprint, auto-pin, password-based, security systems, cloud computing environment

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Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

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Authors: Bing Gu

Abstract:

Abstract—Most of Conventional facial recognition systems are based on image features, such as LBP, SIFT. Recently some DBN-based 2D facial recognition systems have been proposed. However, we find there are few DBN-based 3D facial recognition system and relative researches. 3D facial images include all the individual biometric information. We can use these information to build more accurate features, So we present our DBN-based face recognition system using Light Field. We can see Light Field as another presentation of 3D image, and Light Field Camera show us a way to receive a Light Field. We use the commercially available Light Field Camera to act as the collector of our face recognition system, and the system receive a state-of-art performance as convenient as conventional 2D face recognition system.

Keywords: DBN, face recognition, light field, Lytro

Procedia PDF Downloads 425

Authors: S. Zenia, A. Menasseria, A. E. Kheidous, F. Lariouna, A. Smai, H. Saadi, F. Haddadj, A. Milla, F. Marniche

Abstract:

The objective of this study was to estimate the correlation ship between different pheasant external egg quality traits. A total of 938 eggs were collected. Egg weight (g), egg length (mm), egg width (mm), volume (cm3), shape index egg, surface area and water loss were measured. The overall mean values obtained for the different variables are respectively 29.2 ± 2,24, 43.01 ± 1,84, 34.05 ± 1,44, 25.63 ± 2.88 cm3, 79.00 ± 3%, 68% and 13%. Concerning studied regressions, it was considered only the most important regressions. Those that show significant links between the different parameters studied. The ANOVA procedure was applied to estimate correlations for the examined traits. The weights of the eggs being observed before incubation and before hatching are linearly correlated with a positive correlation coefficient of order 0.75. Egg length and the weight before incubation had a good and positive correlation with a coefficient r = 0.6. However, density had high and negative correlations with egg height r = -0.78. Shape index had a good linear and negative r= - 0.71 correlation with water loss.

Keywords: correlation, egg, morphometry of eggs, analysis of variance

Procedia PDF Downloads 417

Authors: Nougrara Zineb

Abstract:

The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.

Keywords: fovea, optic disc, registration, retinal images

Procedia PDF Downloads 228

Authors: Ali Safaeianpour, Nima Shamandi

Abstract:

As air traffic expands, many airports have evolved into transit centers for people, information, and commerce, and technology implementation is an absolute part of airport development. Several challenges are in the way of implementing technology in an airport. Airport 4.0 proposes the "Smart Airport" concept, which focuses on using modern technologies such as Big Data, the Internet of Things (IoT), advanced biometric systems, blockchain, and cloud computing to alter and enhance passengers' journeys. Several common IoT concrete topics as partial keys to smart airports are discussed and introduced, ranging from automated check-in systems to exterior tracking processes, with the goal of enlightening more and more insightful ideas and proposals about smart airport solutions. IoT will dramatically alter people's lives by infusing intelligence, boosting the quality of life, and assembling it smarter. This paper reviews the approaches to transforming an airport into a smart airport and describes several enabling components of IoT and challenges that can hinder the implementation of a smart airport's function, which require to be addressed.

Keywords: airport 4.0, digital airport, smart airport, IoT

Procedia PDF Downloads 79

Authors: Salmi-Laouar Sihem, Aouissi Riadh

Abstract:

The Cenomanian formations of the Bellezma-Batna Range are yielding very diversified fossiliferous beds. Among the abundant and well-preserved fossils stands out Aspidiscus cristatus (Lamarck). This taxon is assigned to the Family Latomeandridae (Alloiteau) for the presence of six symmetry axes. The outer morphology of sampled specimens documents a low-energy environment with a high sedimentary rate and a mud-supported bottom. Its provincialism evidences some characteristic thermal gradients of the marked Tethysian climatic areas. Biometric measurements are given. Coral size increases from the North towards the southeastern Tethysian margin where waters are supposed warmer; this feature is also underlined by a frequent bio-erosion of sampled specimens. Its limited stratigraphic range makes it a good candidate for an index species for the Middle Cenomanian.

Keywords: Aspidiscus cristatus, coral, Middle Cenomanian, Batna, Bellezma, Algeria

Procedia PDF Downloads 136