scholarly journals Quality Controlled Region-Based Partial Fingerprint Recognition

2018 ◽  
Author(s):  
Omid Zanganeh ◽  
Komal Komal ◽  
Nandita Bhattacharjee ◽  
David Albrecht ◽  
Bala Srinivasan
Keyword(s):  
Reference Points ◽  
Fingerprint Recognition ◽  
Sufficient Information ◽  
New Paradigm ◽  
Ridge Structure ◽  
Matching Process ◽  
Computationally Intensive ◽  
Partial Fingerprint ◽  
Global Similarity

The conventional method of fingerprint alignment using reference points does not work well for partial fingerprints due to the limited or non-availability of reference points. Moreover, matching of partial fingerprints using existing techniques is challenging as partial fingerprints lack enough distinguishing information. Even if fingerprints consists of sufficient information, the varying quality of different parts of fingerprint affects recognition process. In this paper, a new paradigm in the form of region-based approach that uses all available fingerprint ridge structure for aligning the fingerprints is proposed. Additionally, a new metric to compute individual local region similarity based on region’s quality, size and consistency of its neighbouring regions is proposed and used in deriving the global similarity for matching process. Although the proposed approach is computationally intensive, yet, the error rate is close to zero as the experimental results shows. The method is most suitable in applications where perfect identification is required such as forensic investigations.  

scholarly journals Improving of Fingerprint Segmentation Images Based on K-MEANS and DBSCAN Clustering

2019 ◽  
Vol 9 (4) ◽  
pp. 2425 ◽  
Author(s):  
El mehdi Cherrat ◽  
Rachid Alaoui ◽  
Hassane Bouzahir
Keyword(s):  
Computing Time ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Identification System ◽  
Fingerprint Image ◽  
Local Variance ◽  
Dbscan Clustering ◽  
Matching Process ◽  
Fingerprint Segmentation

<span lang="EN-US">Nowadays, the fingerprint identification system is the most exploited sector of biometric. Fingerprint image segmentation is considered one of its first processing stage. Thus, this stage affects typically the feature extraction and matching process which leads to fingerprint recognition system with high accuracy. In this paper, three major steps are proposed. First, Soble and TopHat filtering method have been used to improve the quality of the fingerprint images. Then, for each local block in fingerprint image, an accurate separation of the foreground and background region is obtained by K-means clustering for combining 5-dimensional characteristics vector (variance, difference of mean, gradient coherence, ridge direction and energy spectrum). Additionally, in our approach, the local variance thresholding is used to reduce computing time for segmentation. Finally, we are combined to our system DBSCAN clustering which has been performed in order to overcome the drawbacks of K-means classification in fingerprint images segmentation. The proposed algorithm is tested on four different databases. Experimental results demonstrate that our approach is significantly efficacy against some recently published techniques in terms of separation between the ridge and non-ridge region.</span>

scholarly journals An Increasing Performance of Fingerprint Image Segmentation Based on Clustering and Algorithms

2019 ◽  
Vol 8 (12) ◽  
pp. 4572-4577
Keyword(s):  
Computing Time ◽  
Fingerprint Recognition ◽  
Identification System ◽  
Background Region ◽  
Fingerprint Image ◽  
Local Variance ◽  
Dbscan Clustering ◽  
Matching Process ◽  
Local Block

The fingerprint identification system is nowadays the biometric sector that is most exploited. Segmentation of the fingerprint image is considered as one of its first stage of processing.This stage thus typically affects the extraction and matching process of the feature, resulting in a high accuracy fingerprint recognition system.Three important steps are proposed in this paper. First, to improve the quality of the fingerprint images, Soble and TopHat filtering method were used.K-means clustering for combining 5-dimensional vector characteristics (variance, mean difference, gradient coherence, ridge direction, and energy spectrum) then accurately separates the foreground and background region for each local block in a fingerprint image.Also, local variance thresholding is used in our approach to reducing computing time for segmentation. Finally, we are combined with our DBSCAN clustering system that was performed to overcome the disadvantages of classifying K-means in the segmentation of fingerprint images.In four different databases, the proposed algorithm is tested. Experimental results show that our approach is significantly effective in the separation between the ridge and non-ridge region against some recently published techniques.

scholarly journals Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 894-918
Author(s):  
Luís Rosa ◽  
Fábio Silva ◽  
Cesar Analide
Keyword(s):  
Internet Of Things ◽  
Mobile Networks ◽  
Smart Cities ◽  
Human Mobility ◽  
Rapid Development ◽  
Disruptive Technology ◽  
New Paradigm ◽  
Design And Optimization ◽  
High Level

The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches.

scholarly journals Private and rateless adaptive coded matrix-vector multiplication

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rawad Bitar ◽  
Yuxuan Xing ◽  
Yasaman Keshtkarjahromi ◽  
Venkat Dasari ◽  
Salim El Rouayheb ◽  
...  
Keyword(s):  
Computing Methods ◽  
Erasure Codes ◽  
Time Varying ◽  
New Paradigm ◽  
Matrix Vector Multiplication ◽  
Processing Data ◽  
Computationally Intensive ◽  
Matrix Vector ◽  
Monitoring Devices ◽  
Theoretical Results

AbstractEdge computing is emerging as a new paradigm to allow processing data near the edge of the network, where the data is typically generated and collected. This enables critical computations at the edge in applications such as Internet of Things (IoT), in which an increasing number of devices (sensors, cameras, health monitoring devices, etc.) collect data that needs to be processed through computationally intensive algorithms with stringent reliability, security and latency constraints. Our key tool is the theory of coded computation, which advocates mixing data in computationally intensive tasks by employing erasure codes and offloading these tasks to other devices for computation. Coded computation is recently gaining interest, thanks to its higher reliability, smaller delay, and lower communication costs. In this paper, we develop a private and rateless adaptive coded computation (PRAC) algorithm for distributed matrix-vector multiplication by taking into account (1) the privacy requirements of IoT applications and devices, and (2) the heterogeneous and time-varying resources of edge devices. We show that PRAC outperforms known secure coded computing methods when resources are heterogeneous. We provide theoretical guarantees on the performance of PRAC and its comparison to baselines. Moreover, we confirm our theoretical results through simulations and implementations on Android-based smartphones.

Rivigo

2017 ◽  
pp. 1-35
Author(s):  
G. Raghuram ◽  
Pooja Sanghani
Keyword(s):  
Quality Of Service ◽  
Professional Organizations ◽  
New Paradigm ◽  
Market Segments ◽  
Logistics Industry ◽  
Iot Platform ◽  
The Future

Rivigo, a new entrant in the trucking business in India, believed that a new paradigm in the trucking/logistics industry could be brought about that would not only improve the quality of service dramatically, but also upgrade a truck driver's lifestyle. While the industry faced driver shortage largely due to long stays away from home, Rivigo hoped to attract drivers by offering them roles which would bring them back home in 24 hours. Drivers would be part of a relay, handing over the truck at pit stops. Further, they leveraged an IT-enabled IoT platform on a fleet of owned trucks. All this revolutionized most of the traditions then followed in the industry. The entrepreneur and his core team comprised professionals from premium institutes of the country, with experience in professional organizations in related domains. By offering services like assured delivery at half the time and full shipment visibility, Rivigo had to charge a premium to market segments that would value this. The case raises the question of sustainability in the future.

II. General practitioner and patient satisfaction with psychiatric outpatient provision in the Eastern Health Board Region

2000 ◽  
Vol 17 (1) ◽  
pp. 14-16
Keyword(s):  
Patient Satisfaction ◽  
General Practitioners ◽  
Waiting Times ◽  
Health Centre ◽  
Health Board ◽  
Sufficient Information ◽  
Eastern Health ◽  
Advocacy Groups ◽  
Self Administered Questionnaire

AbstractObjectives: The aim of this study was to undertake a satisfaction survey of users of psychiatric OPD clinics.Method: Attenders were surveyed at two clinics A&B, situated in different socio-economic areas by using a self administered questionnaire. General practitioners who refer patients to these clinics were also surveyed.Results: Patient satisfaction with psychiatric OPD clinics is high, (90%). Satisfaction is significantly affected by waiting times and receiving sufficient information on treatment. The local pharmacist would seem to be preferable to the majority of patients to dispense their medication. Patients attending Clinic A were critical of facilities in Clinic A Health Centre. The majority of general practitioners considered that their patients' needs were being met by OPD but would welcome more frequent communication. They were also in favour of shared care.Conclusions: The establishment of Advisory/Advocacy Groups or user forum would provide a monitor for quality of service for psychiatric OPD clinics.

scholarly journals The Journal Impact Factor and its discontents: steps toward responsible metrics and better research assessment

2016 ◽  
Vol 1 ◽  
Author(s):  
J. Roberto F. Arruda ◽  
Robin Champieux ◽  
Colleen Cook ◽  
Mary Ellen K. Davis ◽  
Richard Gedye ◽  
...  
Keyword(s):  
Impact Factor ◽  
San Francisco ◽  
Journal Impact Factor ◽  
Impact Factors ◽  
Research Assessment ◽  
Sufficient Information ◽  
Alternative System ◽  
Practical Support ◽  
Journal Impact

A small, self-selected discussion group was convened to consider issues surrounding impact factors at the first meeting of the Open Scholarship Initiative in Fairfax, Virginia, USA, in April 2016, and focused on the uses and misuses of the Journal Impact Factor (JIF), with a particular focus on research assessment. The group’s report notes that the widespread use, or perceived use, of the JIF in research assessment processes lends the metric a degree of influence that is not justified on the basis of its validity for those purposes, and retards moves to open scholarship in a number of ways. The report concludes that indicators, including those based on citation counts, can be combined with peer review to inform research assessment, but that the JIF is not one of those indicators. It also concludes that there is already sufficient information about the shortcomings of the JIF, and that instead actions should be pursued to build broad momentum away from its use in research assessment. These actions include practical support for the San Francisco Declaration on Research Assessment (DORA) by research funders, higher education institutions, national academies, publishers and learned societies. They also include the creation of an international “metrics lab” to explore the potential of new indicators, and the wide sharing of information on this topic among stakeholders. Finally, the report acknowledges that the JIF may continue to be used as one indicator of the quality of journals, and makes recommendations how this should be improved.OSI2016 Workshop Question: Impact FactorsTracking the metrics of a more open publishing world will be key to selling “open” and encouraging broader adoption of open solutions. Will more openness mean lower impact, though (for whatever reason—less visibility, less readability, less press, etc.)? Why or why not? Perhaps more fundamentally, how useful are impact factors anyway? What are they really tracking, and what do they mean? What are the pros and cons of our current reliance on these measures? Would faculty be satisfied with an alternative system as long as it is recognized as reflecting meaningfully on the quality of their scholarship? What might such an alternative system look like?

scholarly journals Positive and negative incentive contrasts lead to relative value perception in ants

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Stephanie Wendt ◽  
Kim S Strunk ◽  
Jürgen Heinze ◽  
Andreas Roider ◽  
Tomer J Czaczkes
Keyword(s):  
Reference Points ◽  
Contrast Effects ◽  
High Expectations ◽  
Absolute Income ◽  
Value Perception ◽  
Quality Food ◽  
Relative Value ◽  
Medium Quality ◽  
Quality Of Food

Humans usually assess things not according to their absolute value, but relative to reference points – a main tenant of Prospect Theory. For example, people rate a new salary relative to previous salaries and salaries of their peers, rather than absolute income. We demonstrate a similar effect in an insect: ants expecting to find low-quality food showed higher acceptance of medium-quality food than ants expecting medium quality, and vice versa for high expectations. Further experiments demonstrate that these contrast effects arise from cognitive rather than mere sensory or pre-cognitive perceptual causes. Social information gained inside the nest can also serve as a reference point: the quality of food received from other ants affected the perceived value of food found later. Value judgement is a key element in decision making, and thus relative value perception strongly influences which option is chosen and ultimately how all animals make decisions.

scholarly journals Towards adaptive method for peak migration time correction: discretization period in electropherograms

Chemija ◽  
2020 ◽  
Vol 31 (3) ◽  
Author(s):  
Tomas Drevinskas ◽  
Audrius Maruška ◽  
Gintarė Naujokaitytė ◽  
Laimutis Telksnys ◽  
Mihkel Kaljurand ◽  
...  
Keyword(s):  
Capillary Electrophoresis ◽  
Adaptive Method ◽  
Reference Points ◽  
Migration Time ◽  
Time Shift ◽  
Internal Standards ◽  
Relative Standard ◽  
Adaptive Peak ◽  
Time Correction ◽  
Computationally Intensive

Capillary electrophoresis often causes unrepeatable peak migration times in the electropherogram due to changes of electroosmosis, yet in some cases this separation technique does not have a replacement alternative. Some attempts to overcome this issue have been performed introducing internal standards into the sample and compensating peak shifting in time. However, existing vector calculation-based methods are computationally intensive for portable instrumentation and usually limited to post-processing applications with 1 or 2 markers. In this work, an original approach of compensating peak migration time shift via signal discretization period correction is proposed. Using the proposed method, the number of reference points or markers that are used for compensation is extended. This method is effective in compensating migration time of peaks in real samples, where high sample injection volumes are used. Using 4 reference peaks in compensation, the method was capable of reducing the relative standard deviation of migration time of the peaks in the electropherograms more than 15 times. Corrected signal discretization periods indicated very high correlations with recorded separation currents, what can be perspective developing an adaptive peak migration time compensation method in capillary electrophoresis.

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