An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Biometric Recognition - Security and Privacy Concerns.

The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called “dynamic features (DFs).” This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be “fraud-proof,” because these DFs can only be extracted from living irises.

Dynamic Features for Iris Recognition

There is a growing demand for 5G applications in all fields of knowledge. Current applications, such as the Internet of Things, smart homes, and clean energy, require sophisticated forms of 5G waveforms. Researchers and developers are investigating the requirements of 5G networks for better waveform types, which will result in high spectrum efficiency and lower latency with less complexity in systems. This paper proposes an assessment of various 5G waveform candidates [filtered orthogonal frequency-division multiplexing (OFDM), universal filtered multicarrier (UFMC), filter bank multicarrier (FBMC), and generalized frequency-division multiplexing] under the key performance indicators (KPIs). This paper assesses the main KPI factors (computational complexity, peak-to-average-power ratio, spectral efficiency, filter length, and latency). Moreover, this paper compares and evaluates all KPI factors in various 5G waveforms. Finally, this paper highlights the strengths and weaknesses of each waveform candidate based on the KPI factors for better outcomes in the industry. In conclusion, the current review suggests the use of optimized waveforms (FBMC and UFMC) for better flexibility to overcome the drawbacks encountered by previous works. Regarding coexistence, FBMC and UFMC showed better coexistence with CP-OFDM in 4G networks with a new radio spectrum. The rapprochement between the above-mentioned waveforms has been called green coexistence and is due to the mix between one waveform in 4G networks and two waveforms in 5G networks based on the subcarrier and subband shaping (FBMC and UFMC).

Green Coexistence for 5G Waveform Candidates: A Review

Ageism is the most invisible form of discrimination While there is some awareness of gender, racial, and socioeconomic discrimination on digital platforms, ageism has received less attention This article analyzes some tools that are frequently embedded on digital platforms from an old-age perspective, in order to increase awareness of the different ways in which ageism works We will firstly look at how innovation teams, following homophilic patterns, disregard older people Secondly, we will show how ageism tends to be amplified by the methods often used on digital platforms And thirdly, we will show how corporate values contradict the usability issues that mainly affect people with a low level of (digital) skills, which is more common among older people Counterbalancing the abusive power control of the corporations behind digital platforms and compensating for the underrepresentation of groups in less favorable situations could help to tackle such discrimination

https://journals.sagepub.com/doi/pdf/10.1177/1354856520930905

Ageism in the era of digital platforms

With an increasing emphasis on security, automated personal identification and verification based biometrics has been receiving extensive attention over the past decade. The iris images captured from the same person or different persons differ in size due to illumination variations and other factors. The iris recognition system is composed of many steps. Namely, capturing the iris patterns; determining the location of the iris boundaries; converting the iris boundary to the polar coordinate system; extracting the iris code based on wavelet transforms; and classification of the iris code. There are many methods proposed for iris recognition by many researchers. The proposed system based on dual tree complex wavelet transform for iris recognition system with high performance and acceptance/rejection capabilities is described.

An iris recognition based on dual tree complex wavelet transform

Segmentation is of vital importance in iris based identification. This paper presents a straightforward approach for segmenting the iris. The method determines an automated threshold for binarising and determining the pupil center, based on a histogram of gray scale image and after which the iris is segmented. To access the methods efficacy, this method is applied to a database of 756 images. After segmentation, 160-byte code is extracted from normalized image, which is used for identification.

An Automated Segmentation Method For Iris Recognition

Frauds attacking the automated teller machine has increased over the decade which has motivated us to use the biometrics for personal identification to procure high level of security and accuracy This paper describes a system that replaces the ATM cards and PINs by the physiological biometric fingerprint and iris authentication. Moreover, the feature of one time password (OTP) imparts privacy to the users and emancipates him/her from recalling PINs. Additionally the system provides protection to the ATM terminal from fire and thief attacks by making provisions of pump motor and a DC motor for rolling the shutter. In this system during enrollment the genuine user's fingerprint and iris samples of are retained in the database. The process of transaction begins by capturing and matching fingerprints and iris patterns. The system will automatically distinguish between real legitimate trait and fake samples. A GSM module connected to the ARM7 LPC2148 will message a 3-digit code generated by the system to the registered mobile number. After the valid OTP is entered the user can either withdraw or deposit cash or check his/her balance. In any kind of fake access attempts the account is blocked. In this paper the experimental results are obtained on the data set of fingerprint and iris in real time using fingerprint module with a minutiae matching algorithm and a GUI based of Circular Hough Transform respectively.

Fingerprint and iris biometric controlled smart banking machine embedded with GSM technology for OTP

Facial expression analysis plays pivotal role for all the applications which are based on emotion recognition. Some of the significant applications are driver alert system, animation, pain monitoring for patients and clinical practices. Emotion recognition is carried out in diverse ways and facial expressions based method is one of the most prominent in non verbal category of emotion recognition. The paper presents detection of all the six universal emotions based on statistical moments i.e. Zernike moments. The features extracted by Zernike moments are further classified through Naive Bayesian classifier. Rotation Invariance is one of the important properties of Zernike moments which is also experimented. The simulation based experimentation provides average detection accuracy as 81.66% and recognition time less than 2 seconds for frontal face images. The average precision with respect to positives is 81.85 and average sensitivity is obtained as 80.60%. Robustness of system is verified against rotation of images till 360 degrees with step size as 45 degrees. The detection accuracy varies with reference to emotion under consideration but the average accuracy and detection time remains at par with frontal face images.

Statistical moments based facial expression analysis

The concept of dielectric constant measurement has been extended and applied in agriculture, pharmaceutical and food industry for quality control of liquids. Dielectric analysis of material at microwave frequencies can be done using novel shielded stacked multi-ring resonator (SMRR). The dielectric constant of liquids and paste has been calculated using SMRR with greater accuracy than the planar resonator, boxed resonator and stacked resonator. SMRR contains a ring resonator with fed patch and parasitic patch with different numbers and sizes of rings. The dimensions of rings on the parasitic patch are optimized to achieve Quality factor Q greater than 100 and return loss less than −2 dB. Due to dual resonance in novel SMRR, structure losses are reduced by 50% than planar resonator structure. The behavior of SMRR structure at the 2.45 GHz frequency is studied with E field and H field. 3D model is designed in Computer Simulation Technology Microwave Studio (CST MWS) using TLM (Transmission Line Modeling) solver. Electromagnetic field analysis as well as impedance bandwidth of SMRR using CST MWS 3D model prove that electromagnetic coupling in SMRR structure increases thus improves quality factor. In SMRR quality factor increases and losses reduce help us to predict the complex permittivity of material for quality analysis.

/pdf/dielectric-constant-measurement-of-low-loss-liquids-using-23lecfs1uz.pdf

A. N. Gaikwad

Papers

An iris recognition based on dual tree complex wavelet transform

An Automated Segmentation Method For Iris Recognition

Fingerprint and iris biometric controlled smart banking machine embedded with GSM technology for OTP

Statistical moments based facial expression analysis

Dielectric constant measurement of low loss liquids using stacked multi ring resonator