scholarly journals Analyzing the Effectiveness of Touch Keystroke Dynamic Authentication for the Arabic Language

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Suliman A. Alsuhibany ◽  
Afnan S. Almuqbil
Keyword(s):  
Arabic Language ◽  
Error Rates ◽  
Free Text ◽  
Classification Methods ◽  
Traditional Methods ◽  
Digital Devices ◽  
Android Platform ◽  
Authentication Technique ◽  
Keystroke Dynamic ◽  
Dynamic Authentication

The keystroke dynamic authentication (KDA) technique was proposed in the literature to develop a more effective authentication technique than traditional methods. KDA analyzes the rhythmic typing of the owner on a keypad or keyboard as a source of verification. In this study, we extend the findings of the system by analyzing the existing literature and validating its effectiveness in Arabic. In particular, we examined the effectiveness of the KDA system in Arabic for touchscreen-based digital devices using two KDA classes: fixed and free text. To this end, a KDA system was developed and applied to a selected device operating on the Android platform, and various classification methods were used to assess the similarity between log-in and enrolment sessions. The developed system was experimentally evaluated. The results showed that using Arabic KDA on touchscreen devices is possible and can enhance security. It attains a higher accuracy with average equal error rates of 0.0% and 0.08% by using the free text and fixed text classes, respectively, implying that free text is more secure than fixed text.

scholarly journals Classification of Pneumonia Cell Images Using Improved ResNet50 Model

2021 ◽  
Vol 38 (1) ◽  
pp. 165-173
Author(s):  
Ahmet Çınar ◽  
Muhammed Yıldırım ◽  
Yeşim Eroğlu
Keyword(s):  
Error Rates ◽  
Lung Imaging ◽  
Imaging Method ◽  
Data Sets ◽  
Accuracy Rate ◽  
Traditional Methods ◽  
X Ray ◽  
Qualified Personnel ◽  
Patient Will

Pneumonia is a disease caused by inflammation of the lung tissue that is transmitted by various means, primarily bacteria. Early and accurate diagnosis is important in reducing the morbidity and mortality of the disease. The primary imaging method used for the diagnosis of pneumonia is lung x-ray. While typical imaging findings of pneumonia may be present on lung imaging, nonspecific images may be present. In addition, many health units may not have qualified personnel to perform this procedure or there may be errors in diagnoses made by traditional methods. For this reason, computer systems can be used to prevent error rates that may occur in traditional methods. Many methods have been developed to train data sets. In this article, a new model has been developed based on the layers of the ResNet50. The developed model was compared with the architectures InceptionV3, AlexNet, GoogleNet, ResNet50 and DenseNet201. In the developed model, the maximum accuracy rate was achieved as 97.22%. The model developed was followed by DenseNet201, ResNet50, InceptionV3, GoogleNet and AlexNet, respectively, according to their accuracy. With these developed models, the diagnosis of pneumonia can be made early and accurately, and the treatment management of the patient will be determined quickly.

scholarly journals 2507 A novel multi-photon microscopy method for neuronavigation in deep brain stimulation surgery

2018 ◽  
Vol 2 (S1) ◽  
pp. 2-3
Author(s):  
Nicholas M. George ◽  
Arianna G. Polese ◽  
Greg Futia ◽  
Baris Ozbay ◽  
Wendy Macklin ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Second Harmonic Generation ◽  
Image Classification ◽  
Blood Vessels ◽  
Harmonic Generation ◽  
Calcium Binding ◽  
Second Harmonic ◽  
Brain Regions ◽  
Classification Methods ◽  
Traditional Methods

OBJECTIVES/SPECIFIC AIMS: The goal for this project is to determine the feasibility of using a novel multi-photon fiber-coupled microscope to aid surgeons in localizing STN during surgeries. In order to accomplish this goal, we needed to identify the source of a strong autofluorescent signal in the STN and determine whether we could use image classification methods to automatically distinguish STN from surrounding brain regions. METHODS/STUDY POPULATION: We acquired 3 cadaveric brains from the University of Colorado Anschutz Medical Campus, Department of Pathology. Two of these brains were non-PD controls whereas 1 was diagnosed with PD. We dissected a 10 square centimeter region of midbrain surrounding STN, then prepared this tissue for slicing on a vibratome or cryostat. Samples were immuno-labeled for various cellular markers for identification, or left unlabeled in order to observe the autofluorescence for image classification. RESULTS/ANTICIPATED RESULTS: The border of STN is clearly visible based on the density of a strong autofluorescent signal. The autofluorescent signal is visible using 2-photon (850–1040 nm excitation) and conventional confocal microscopy (488–647 nm excitation). We were also able to visualize blood vessels with second harmonic generation. The autofluorescent signal is quenched by high concentrations of Sudan-black B (0.5%–5%), and is primarily localized in microtubule-associated protein-2 (MAP2)+ cells, indicating that it is likely lipofuscin accumulation in neurons. Smaller lipofuscin particles also accumulate in microglia, identified based on ionized calcium binding adopter 1 (Iba1)+ labeling. We anticipate that colocalization analysis will confirm these qualitative observations. Using 2-photon images of the endogenous autofluorescent signal in these samples, we trained a logistic regression-based image classifier using features derived from gray-level co-occurrence matrices. Preliminary testing indicates that our classifier performed well, with a mean accuracy of 0.89 (standard deviation of 0.11) and a Cohen’s Kappa value of 0.76 (standard deviation of 0.24). We are currently using coherent anti-Stokes Raman scattering and third harmonic imaging to identify different features of myelin that can be used to distinguish between these regions and expect similar results. DISCUSSION/SIGNIFICANCE OF IMPACT: Traditional methods for localizing STN during DBS surgery include the use of stereotactic coordinates and multi-electrode recording (MER) during implantation. MERs are incredibly useful in DBS surgeries, but require penetration of brain structures in order to infer location. Using multi-photon microscopy techniques to aid identification of STN during DBS surgeries offers a number of advantages over traditional methods. For example, blood vessels can be clearly identified with second harmonic generation, something that is not possible with MER. Multi-photon microscopy also allows visualization deep into tissue without actually penetrating it. This ability to look within a depth of field is useful for detection of STN borders based on autofluorescent cell density. When combined with traditional stereotactic information, our preliminary image classification methods are a fast, reliable way to provide surgeons with extra information concerning their location in the midbrain. We anticipate that future advancements and refinements to our image classifier will only increase accuracy and the potential applications and value. In summary, these preliminary data support the feasibility of multi-photon microscopy to aid in the identification of target brain regions during DBS surgeries. The techniques described here complement and enhance current stereotactic and electrophysiological methods for DBS surgeries.

scholarly journals Free‐text keystroke dynamics authentication for Arabic language

2016 ◽  
Vol 5 (3) ◽  
pp. 164-169 ◽  
Author(s):  
Arwa Alsultan ◽  
Kevin Warwick ◽  
Hong Wei
Keyword(s):  
Arabic Language ◽  
Free Text ◽  
Keystroke Dynamics

scholarly journals Keystroke Dynamic Authentication Using Combined MHR (Mean of Horner’s Rules) and Standard Deviation

2018 ◽  
pp. 13-18 ◽  
Author(s):  
Didih Rizki Chandranegara ◽  
Fauzi Dwi Setiawan Sumadi
Keyword(s):  
Standard Deviation ◽  
High Accuracy ◽  
Previous Method ◽  
Acceptance Rate ◽  
Biometric Authentication ◽  
False Acceptance Rate ◽  
False Acceptance ◽  
Keystroke Dynamic ◽  
Dynamic Authentication

Keystroke Dynamic Authentication used a behavior to authenticate the user and one of biometric authentication. The behavior used a typing speed a character on the keyboard and every user had a unique behavior in typing. To improve classification between user and attacker of Keystroke Dynamic Authentication in this research, we proposed a combination of MHR (Mean of Horner’s Rules) and standard deviation. The results of this research showed that our proposed method gave a high accuracy (93.872%) than the previous method (75.388% and 75.156%). This research gave an opportunity to implemented in real login system because our method gave the best results with False Acceptance Rate (FAR) is 0.113. The user can be used as a simple password and ignore a worrying about an account hacking in the system.

The impact of using different keyboards on free-text keystroke dynamics authentication for Arabic language

2019 ◽  
Vol 27 (2) ◽  
pp. 221-232
Author(s):  
Suliman A. Alsuhibany ◽  
Muna Almushyti ◽  
Noorah Alghasham ◽  
Fatimah Alkhudhayr
Keyword(s):  
Recognition Accuracy ◽  
Rejection Rate ◽  
Arabic Language ◽  
Free Text ◽  
Keystroke Dynamics ◽  
Content Type ◽  
High Level ◽  
Traditional Approaches ◽  
The Impact ◽  
Keyboard Layout

Purpose Nowadays, there is a high demand for online services and applications. However, there is a challenge to keep these applications secured by applying different methods rather than using the traditional approaches such as passwords and usernames. Keystroke dynamics is one of the alternative authentication methods that provide high level of security in which the used keyboard plays an important role in the recognition accuracy. To guarantee the robustness of a system in different practical situations, there is a need to examine how much the performance of the system is affected by changing the keyboard layout. This paper aims to investigate the impact of using different keyboards on the recognition accuracy for Arabic free-text typing. Design/methodology/approach To evaluate how much the performance of the system is affected by changing the keyboard layout, an experimental study is conducted by using two different keyboards which are a Mac’s keyboard and an HP’s keyboard. Findings By using the Mac’s keyboard, the results showed that the false rejection rate (FRR) was 0.20, whilst the false acceptance rate (FAR) was 0.44. However, these values have changed when using the HP’s keyboard where the FRR was equal to 0.08 and the FAR was equal to 0.60. Research limitations/implications The number of participants in the experiment, as the authors were targeting much more participants. Originality/value These results showed for the first time the impact of the keyboards on the system’s performance regarding the recognition accuracy when using Arabic free-text.

A Novel Method for Classifying Function of Spatial Regions Based on Two Sets of Characteristics Indicated by Trajectories

2020 ◽  
Vol 16 (3) ◽  
pp. 1-19
Author(s):  
Haitao Zhang ◽  
Chenguang Yu ◽  
Yan Jin
Keyword(s):  
Classification Performance ◽  
Classification Methods ◽  
Traditional Methods ◽  
Urban Settings ◽  
Spatial Classification ◽  
Spatiotemporal Characteristics ◽  
Novel Method ◽  
Single Set ◽  
F Measure ◽  
Global Connection

Trajectory is a significant factor for classifying functions of spatial regions. Many spatial classification methods use trajectories to detect buildings and districts in urban settings. However, methods that only take into consideration the local spatiotemporal characteristics indicated by trajectories may generate inaccurate results. In this article, a novel method for classifying function of spatial regions based on two sets of characteristics indicated by trajectories is proposed, in which the local spatiotemporal characteristics as well as the global connection characteristics are obtained through two sets of calculations. The method was evaluated in two experiments: one that measured changes in the classification metric through a splits ratio factor, and one that compared the classification performance between the proposed method and methods based on a single set of characteristics. The results showed that the proposed method is more accurate than the two traditional methods, with a precision value of 0.93, a recall value of 0.77, and an F-Measure value of 0.84.

scholarly journals Communication through the electronic health record: frequency and implications of free text orders

JAMIA Open ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 154-159
Author(s):  
Swaminathan Kandaswamy ◽  
Aaron Z Hettinger ◽  
Daniel J Hoffman ◽  
Raj M Ratwani ◽  
Jenna Marquard
Keyword(s):  
Data Entry ◽  
Clinical Decision ◽  
Error Rates ◽  
Asynchronous Communication ◽  
Free Text ◽  
Future Studies ◽  
Safety Issues ◽  
Inaccurate Information ◽  
Related Information ◽  
Medication Information

Abstract Communication for non-medication order (CNMO) is a type of free text communication order providers use for asynchronous communication about patient care. The objective of this study was to understand the extent to which non-medication orders are being used for medication-related communication. We analyzed a sample of 26 524 CNMOs placed in 6 hospitals. A total of 42% of non-medication orders contained medication information. There was large variation in the usage of CNMOs across hospitals, provider settings, and provider types. The use of CNMOs for communicating medication-related information may result in delayed or missed medications, receiving medications that should have been discontinued, or important clinical decision being made based on inaccurate information. Future studies should quantify the implications of these data entry patterns on actual medication error rates and resultant safety issues.

scholarly journals Evaluation of sensory panels of consumers of specialty coffee beverages using the boosting method in discriminant analysis

2015 ◽  
Vol 36 (6) ◽  
pp. 3671 ◽  
Author(s):  
Gilberto Rodrigues Liska ◽  
Fortunato Silva de Menezes ◽  
Marcelo Angelo Cirillo ◽  
Flávio Meira Borém ◽  
Ricardo Miguel Cortez ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
False Negative ◽  
False Negative Rate ◽  
Error Rates ◽  
Training Data ◽  
Classification Rule ◽  
Classification Methods ◽  
Training Set ◽  
Linear Discriminant ◽  
Boosting Method

Automatic classification methods have been widely used in numerous situations and the boosting method has become known for use of a classification algorithm, which considers a set of training data and, from that set, constructs a classifier with reweighted versions of the training set. Given this characteristic, the aim of this study is to assess a sensory experiment related to acceptance tests with specialty coffees, with reference to both trained and untrained consumer groups. For the consumer group, four sensory characteristics were evaluated, such as aroma, body, sweetness, and final score, attributed to four types of specialty coffees. In order to obtain a classification rule that discriminates trained and untrained tasters, we used the conventional Fisher’s Linear Discriminant Analysis (LDA) and discriminant analysis via boosting algorithm (AdaBoost). The criteria used in the comparison of the two approaches were sensitivity, specificity, false positive rate, false negative rate, and accuracy of classification methods. Additionally, to evaluate the performance of the classifiers, the success rates and error rates were obtained by Monte Carlo simulation, considering 100 replicas of a random partition of 70% for the training set, and the remaining for the test set. It was concluded that the boosting method applied to discriminant analysis yielded a higher sensitivity rate in regard to the trained panel, at a value of 80.63% and, hence, reduction in the rate of false negatives, at 19.37%. Thus, the boosting method may be used as a means of improving the LDA classifier for discrimination of trained tasters.

Design and Implementation of the Marine Disaster Real-Time Evacuation Path on Android Platform

2013 ◽  
Vol 336-338 ◽  
pp. 2091-2094
Author(s):  
Dong Mei Huang ◽  
Yan Ling Du ◽  
Sheng Qi He
Keyword(s):  
Decision Support ◽  
Real Time ◽  
High Availability ◽  
Location Information ◽  
Traditional Methods ◽  
Design And Implementation ◽  
Android Platform ◽  
Information Delay ◽  
Marine Disaster ◽  
Dynamic Path

Evacuation path is an important part of the marine disaster decision support. It can provide evacuation paths quickly for the affected people to ensure life safety. The application is developed based on android platform. Take advantages of GPS to obtain real-time location information in order to achieve dynamic path of the affected personnel evacuation. It has solved problems of information delay, inability to obtain or update the data in real time caused by traditional methods. Thus, the application has high availability.

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