Human Identification Research Articles

Optimizing service encounters through mascot-like robot with a politeness strategy

Mascot-like service robots embody anthropomorphic features, fostering affinity, and cultural representation. It is unknown whether they have politeness strategies that are more effective compared to humanoid robots. Drawing on politeness, uncanny valley, and mind perception theories, this study investigates the interaction effect of service robot appearance types (humanoid and mascot-like) and politeness strategies on customers’ service encounter evaluation, as well as the psychological mechanisms and boundary conditions of this effect. The findings reveal the superiority of mascot-like robots over humanoid robots in positive politeness contexts; human identity threat mediated this effect. Sense of power plays a moderating role; specifically, mascot robots with positive politeness strategies are more appealing to customers with low sense of power. This research significantly contributes to our understanding of service robot appearance and communication within the framework of mind perception and politeness theories in human–robot interaction. Moreover, it offers valuable guidance for companies enhancing consumer experiences through service robots.

Spatial genomics: mapping human steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as non-alcoholic fatty liver disease) is a leading cause of chronic liver disease worldwide. MASLD can progress to metabolic dysfunction-associated steatohepatitis (MASH, formerly known as non-alcoholic steatohepatitis) with subsequent liver cirrhosis and hepatocellular carcinoma formation. The advent of current technologies such as single-cell and single-nuclei RNA sequencing have transformed our understanding of the liver in homeostasis and disease. The next frontier is contextualizing this single-cell information in its native spatial orientation. This understanding will markedly accelerate discovery science in hepatology, resulting in a further step-change in our knowledge of liver biology and pathobiology. In this Review, we discuss up-to-date knowledge of MASLD development and progression and how the burgeoning field of spatial genomics is driving exciting new developments in our understanding of human liver disease pathogenesis and therapeutic target identification.

Legal behavior and human identity in the debate paradigm of the philosophy of law

This article analyzes the peculiarities of the reflection of a person’s legal behavior in the light of various philosophical and legal scientific discourses. In general, the analysis of a person’s legal behavior in the debatable paradigm of the philosophy of law in the context of studying the problem of establishing legal cooperation illuminates the deep aspects of the interaction between the individual and the legal system. Philosophical concepts help to consider this topic on a metaphysical level, revealing the fundamental principles and moral aspects of legal behavior.
 It was established that the primary springboard for considering behavior in the context of legal reality is its consideration through the ideological paradigm of human rights, since the concept recognizes the inalienability and inalienability of the rights of each person, justifying their fundamentality due to the presence of dignity inherent to each person. The main idea is that these rights are not only legal norms, but also a key element that forms personal dignity and freedom and express the personal identity of a person, and in evaluating human behavior, the role of the state and society in ensuring and protecting rights as an unconditional axiological determinants.
 It is proved that a valid paradigm of reflection is the need to analyze behavior in the prism of a social contract, since the mutual agreement of people involves the exchange of a part of individual freedom for common order and security, ensured by the adoption of rules and obligations, which forms the basis for the creation of the state and the legal order. Thus, a person’s behavior is evaluated for its compliance with established rules and the ability to interact with other members of society in peace and mutual understanding.
 It is motivated that the philosophical analysis of ethical-philosophical concepts in the context of human behavior defines two key areas - deontology and consequentology. Deontology, focusing on duties and rules, determines the morality of actions regardless of their consequences, indicating the obligation of ethical norms, and consequentology focuses on the consequences of actions as the main criterion for their moral evaluation, emphasizing the importance of positive results.

Genetic diagnosis of endocrine disorders in Cyprus through the Cyprus Institute of Neurology and Genetics: an ENDO-ERN Reference Center

The report covers the current and past activities of the department Molecular Genetics-Function and Therapy (MGFT) at the Cyprus Institute of Neurology and Genetics (CING), an affiliated Reference Center for the European Reference Network on Rare Endocrine Conditions (Endo-ERN).The presented data is the outcome of > 15 years long standing collaboration between MGFT and endocrine specialists from the local government hospitals and the private sector. Up-to-date > 2000 genetic tests have been performed for the diagnosis of inherited rare endocrine disorders. The major clinical entities included Congenital Adrenal Hyperplasia (CAH) due to pathogenic variants in CYP21A2 gene and Multiple Endocrine Neoplasia (MEN) type 2 due to pathogenic variants in the RET proto-oncogene. Other rare and novel pathogenic variants in ANOS1, WDR11, FGFR1, RNF216, and CHD7 genes were also found in patients with Congenital Hypogonadotropic Hypogonadism. Interestingly, a few patients with Disorders of Sexual Differentiation (DSD) shared rare pathogenic variants in the SRD5A2, HSD17B3 and HSD3B2 while patients with Glucose and Insulin Homeostasis carried theirs in GCK and HNF1A genes. Lastly, MGFT over the last few years has established an esteemed diagnostic and research program on premature puberty with emphasis on the implication of MKRN3 gene on the onset of the disease and the identification of other prognosis biomarkers.As an Endo-ERN member MGFT department belongs to this large European network and holds the same humanistic ideals which aim toward the improvements of health care for patients with rare endocrine conditions in respect to improved and faster diagnosis.

GAITBOOST: Boosting gait recognition performance with BAT-extreme learning machines algorithm

Gait analysis is a widely used technique for passive human identification and tracking, with potential applications in security and surveillance systems. However, existing gait recognition methods face challenges in handling changing angles and uncertain features. In this paper, we propose a novel gait recognition approach that leverages real-time spatio-temporal gait features, including step length, gait cycle, height, cadence, swing ratio, and foot length. We apply the Extreme Learning Machines (ELM) algorithm for classification, which has been shown to be effective in various applications due to its fast-learning speed and good generalization performance. To further enhance the recognition rate, we introduce an evolutionary BAT-optimized ELM algorithm that addresses the instability issue in ELM. The proposed BAT-ELM algorithm can optimize the hidden nodes and weights of ELM, which leads to improved efficiency in recognizing gait from multiple view angles ranging from 0° to 180°. Our comprehensive analysis of the proposed approach indicates that it outperforms other reported algorithms in terms of recognition rate and efficiency. Our work demonstrates the effectiveness of combining real-time spatio-temporal gait features with the BAT-ELM algorithm for gait recognition. The proposed approach has potential applications in various fields, including security and surveillance systems, healthcare, and robotics. Our findings highlight the importance of leveraging evolutionary algorithms to optimize machine learning models and achieve better performance in complex recognition tasks.

Multipoint ECG Signal Extraction on Palms and Figures for Human Identification System

The ECG signal contain vital information for cardiac disease which is one of main cause of catastrophic mortality. In conventional technique, the signals are extracted through different points located on the limbs and surface of the chest. The biological impedance of human body eliminates any practical means of making fake copies of the relevant physiological traits. Moreover, this method needs the complex data acquisition system and apparatus as well as inconvenience way of acquisition of signal at the chest. Hence, there is a demand to find out the promising alternative technique to extract the ECG signals in more convenient way with high accuracy. In this paper, the real-time ECG monitor has been developed to extract the signals from the multipoint on the hands and fingers. Placement of the electrodes are done based on the acupressure point on palms and fingers. A total of 120 volunteers were investigated to develop the ECG database as the development dataset. This work uses the template matching algorithm and distance classification method to analyze and to find the best similarities between the developed dataset of ECG biometric signals to improve the identification rate. In order to lessen the noise that was recorded with the ECG signals, signal averaging was used to create ECG databases and templates. The recognition rate rose to 98% accuracy on the development dataset when the prescreening procedure was introduced to create a combined system model. ECG biometric model was created by combining the two models and using the development dataset's results. The algorithm was applied on the entire developed ECG dataset and 96% of accuracy rate was achieved in identification.

Loss of the Y Chromosome: A Review of Molecular Mechanisms, Age Inference, and Implications for Men's Health.

Until a few years ago, it was believed that the gradual mosaic loss of the Y chromosome (mLOY) was a normal age-related process. However, it is now known that mLOY is associated with a wide variety of pathologies in men, such as cardiovascular diseases, neurodegenerative disorders, and many types of cancer. Nevertheless, the mechanisms that generate mLOY in men have not been studied so far. This task is of great importance because it will allow focusing on possible methods of prophylaxis or therapy for diseases associated with mLOY. On the other hand, it would allow better understanding of mLOY as a possible marker for inferring the age of male samples in cases of human identification. Due to the above, in this work, a comprehensive review of the literature was conducted, presenting the most relevant information on the possible molecular mechanisms by which mLOY is generated, as well as its implications for men's health and its possible use as a marker to infer age.

Technological Bodies: Artificial Intelligence as Friday in Portal and Halo Infinite

Artificial intelligence characters provide a unique perspective on the discussion of Friday figures and issues of Otherness and Othering as they relate to the body. With their technological, inherently inhuman physicality, AI Fridays shed light on the differentiation between ‘being human’ as an inner state of being, on the one hand, and as having a biologically human body, on the other. These characters thus shift some of the central questions about culture in many Robinsonades towards questions of humanity and physical identity, especially when reading the AI body as a metaphorical stand-in for the colonised body. They reflect on the question of how far our bodies determine who we are, how they relate to and are shaped by the groups we belong to, and what it means to be human.

Micro-Doppler based Human Activity Recognition using ABOA based Dual Spatial Convolution with Gated Recurrent Unit

The through-wall capability, device-free detection of radar-based human activity recognition are drawing a lot of interest from both academics and industry. The majority of radar-based systems do not yet combine signal analysis and feature extraction in the frequency domain and the time domain. Applications like smart homes, assisted living, and monitoring rely on human identification and activity recognition (HIAR). Radar has a number of advantages over other sensing modalities, such as the ability to shield users' privacy and conduct contactless sensing. The article introduces a new human tracking system that uses radar and a classifier called Dual Spatial Convolution Gated Recurrent Unit (DSC-GRU) to identify the subject and their behavior. The system follows the person and identifies the type of motion whenever it detects movement. One important feature is the integration of the GRU with the DSC unit, which allows the model to simultaneously capture the spatiotemporal dependence. Present prediction models just take into account spatial features that are immediately adjacent to each other, disregarding or just superimposing global spatial features when taking spatial correlation into account. A new dependency graph is created by calculating the correlation among nodes using the correlation coefficient; this graph represents the global spatial dependence, while the classic static graph represents the neighboring spatial dependence in the DSC unit. The DSC unit goes a step further by using a modified gated mechanism to quantify the various contributions of both local and global spatial correlation. While previous models performed worse, the suggested model outperformed them with an accuracy of 99.45 percent and a precision of 97.15 percent.

Empowering artificial intelligence-based multi-biometric image sensor for human identification

Artificial intelligence (AI) and sensor technology developments have sparked revolutionary shifts in a number of fields, including biometric Identification. In order to improve human identification processes, this research offers a novel method that integrates AI and many biometric image sensors. The accuracy, robustness, and susceptibility to spoofing assaults of conventional single-modal biometric systems are among their many drawbacks. To overcome these challenges, we introduce a secure multi-biometric system that relies on feature-level fusion to identify users. In the preprocessing step, fingerprint images undergo Min-Max normalization to mitigate variations in image quality. In order to extract high-level features from both raw Electrocardiogram (ECG) signals and Min-Max normalized fingerprint images, ResNet50, a deep convolutional neural network, is used. These extracted feature vectors are able to distinguish between the two modalities. We proposed boosted Xgboost as a classifier for authentication in the identification steps to improve performance. The proposed approach is simulated using Python. A comparison study for improved Xgboost is presented using measures for accuracy, precision-recall, and F1-Score. Across all comparative metrics, the technique achieves much better performance. According to experimental findings, the suggested multi-biometric systems are more effective, dependable, and robust than the existing multi-biometric authentication systems.

Ear Biometry: Protection Safeguarding Ear Acknowledgment Framework utilizing Transfer Learning in Industry 4.0

Human-Recognition using biometric features proposes a noble way of uniquely identifying individuals considering they do not require people to keep loads of passwords in mind to prove their identity. Biometrics have aided in people unable to render other’s identity as well and have advanced over the years. Identification using ear biometric technique is considered to outrun other features since passive human involvement and ease-of-access are its strong set of attributes, not seen in any other biometric techniques. It has managed to identify criminals in the Crime Branch and has various helpful applications in the industry. Even in times of pandemic, it can serve its purpose in identifying individuals due to its feasibility. Models for Ear Image Identification have been proposed by various researchers over time utilizing Deep Learning and its Networks achieving high accuracy results, presenting faster and accurate identification models, boosting Ear Biometry as a secure Human Identification Tool. The learnings of this study on the AMI Ear Dataset and the OCEar dataset prove Ear Uniqueness of individuals demonstrating the identification of individuals, introducing passive identification into play, as well as computes on another dataset OCEar to study the similarity of both ears for identifying an individual.

Reliable human authentication using AI-based multibiometric image sensor fusion: Assessment of performance in information security

Reliable human authentication is essential for assuring the availability, confidentiality, and integrity of sensitive data and resources in the field of information security. Due to the vulnerabilities of conventional authentication techniques like passwords and PINs, interest in biometric-based authentication systems has developed. To get over this, we suggest an efficient voice and iris recognition-based multimodal biometric verification strategy for human authenticating tools. We first collect the voice and iris datasets from 150 people. Then, we used a median filter and high pass filter to preprocess the voice and iris data. The features of voice identification are extracted using the shifted delta cepstral coefficient (SDCC) and the Mel frequency discrete wavelet coefficient (MFCC), and these two coefficients are evaluated. The outcomes of the extraction of iris identification features using Local binary pattern (LBP) and Speeded robust features (SURF) are evaluated. The classifier Fine Tuned Cuckoo Search Optimized Convolutional Neural Network (FCSO-CNN) performs voice and iris recognition modalities. Voice and iris biometric systems may be combined into a single multimodal biometric system by fusing their respective feature sets and scoring algorithms. The results of the computer simulation demonstrate that for speech recognition, using the SDC and MFC coefficients produces better results, while for iris recognition, using the LBP and FCSO-CNN experiment produces superior outcomes. Additionally, the scores fusion works superior to other scenarios in the proposed multimodal biometrics system. The suggested system provides a dependable and strong solution for human identification, assisting in the improvement of security measures across a variety of industries, including financial institutions, governmental agencies, and the defense of key infrastructure.

The Subject of Human Rights: From the Unencumbered Self to the Relational Self

ABSTRACT The divisive character of a large part of identity politics creates enormous challenges which have yet to be satisfactorily engaged with from within human rights circles. This article addresses an area of human rights theory and practice that is in urgent need of critical attention: the prevailing human-rights-based response to identity politics, namely recognition rights that eschew social class. I shall argue that human rights has vitally important contributions to make to protecting those who are vulnerable because of their self-affirmed or imposed identities. However, I shall also argue that human rights’ engagement with identity politics is significantly limited in key areas. Human rights remains deeply influenced by an overly individualist ideal of the individual rights holder, which limits its ability to effectively engage with what I see as a key challenge of our age: identity politics wielded in divisive ways. I shall argue that what is largely missing from human rights’ engagement with identity politics is an understanding of the subject of rights as relational. I will consider specific aspects of this failure to engage with the constitutive relationality of human agency and identity, before proceeding to outline three areas in which an acknowledgement of relationality can contribute to human rights incorporating identity politics in a more effective way. My article asks the human rights community to radically rethink and begin to reshape its efforts to engage with the challenge of identity.

Reflection of Aesthetic Concepts of Russian Realism in Chinese Visual Art

This paper examines the impact of Russian realism on Chinese visual art, focusing on how Chinese artists have adapted and reinterpreted Russian aesthetic concepts. The study highlights the role of cross-cultural exchanges in enriching both traditional Chinese art and the broader understanding of realism. Through a detailed analysis, the author explores the reflection of Russian realism's social criticism and humanistic ideals in Chinese artistic practices, and how these influences have fostered new artistic forms and themes within China.The research employs comparative analysis of artworks and artistic traditions alongside historical and cultural contexts of both Russia and China. This approach underscores the importance of international artistic exchanges in creating a more diverse and multicultural art world. The study's novelty lies in uncovering the mechanisms of cultural integration and innovation through artistic exchanges between the two countries, detailing how Russian realism has not only shaped Chinese art but also spurred the creation of unique forms that reflect contemporary societal and cultural demands.Significantly, the fusion of Russian realism and traditional Chinese aesthetics has led to a new artistic direction in China that melds global artistic trends with local cultural values. This synthesis has facilitated deeper cultural dialogues and mutual understanding, enriching the artistic traditions of both Russia and China. Artists have been provided with new opportunities to explore innovative ideas and forms, thus strengthening cross-cultural ties and expanding the boundaries of artistic interaction. The paper emphasizes the transformative power of this artistic merger in enriching the global art space and fostering a more inclusive and varied artistic milieu.

Head rotation and the perception of eyelid height and contour

PurposeEffective visual perceptual processing is one of the many components of surgical competence. Human face identification is most efficient when viewed upright. However, it is not yet clear how this...

Estimation of Sex From the Buccolingual Dimension of Tooth Among the North Indian Population.

Identification is an important aspect of forensic medicine. Identification plays an imperative role, especially in highly decomposed bodies, mutilated bodies, and undisclosed and fragmentary human remains. The estimation of sex is an essential parameter of human identification. In forensic anthropometry, sex determination is related to morphometric characteristics of skeletal bones, such as the skull and mandible, clavicle, sternum, scapula, humerus, pelvic bone, sternum, and femur. Since teeth are decay-resistant, conscientious analysis of teeth can accredit reliable sex estimation of an individual, especially when other determinants are fragmented or destroyed. The aim of the study was to explore the association between sex and buccolingual crown dimensions of teeth. The study sample consists of 100 volunteer subjects (50 male subjects and 50 female subjects) aged between 20 and 35 years. Alginate was used to take impressions of the teeth and the cast was prepared using pouring by dental stone. Measurements of buccolingual parameters of all the teeth (except the third molars) of both jaws were done on dental casts by using a digital caliper. Collected data were analyzed using SPSS software (IBM Corp., Armonk, NY) and were outlined as mean and standard deviation (SD). The male and female groups were compared using an independent Student's t-test or unpaired test. The results of this study revealed that 16 out of 28 odontometric parameters (except third molar) of the two groups (male and female) were higher in the male group as compared to the female group (p < 0.05). Buccolingual odontometric parameters can be used for sex estimation in the North Indian population.

Dynamic Process of International Student’s Identity Development and Multiplicity of Linguistic Selves

The current paper examines the concept and characteristics of human identity and how those have been historically discussed by theorists from diverse fields, focusing particularly on international students who study abroad. The aim of this report is to investigate how international students shape their multiple selves during their time overseas by drawing on social and cultural factors. Relevant empirical studies are reviewed from the standpoint of sociological, socio-cultural, and dialogical theories. Reviewing the literature allowed this study to arrive at some conclusions. First, international students construct their identity through complex, dynamic, and constant processes, and this identity is subject to continually change as per social interactions and circumstances rather than being acquired as biological determinants. Second, language is a crucial factor in the process of identity construction. Implications and limitations are discussed as well.

Book Review: Gender as love: A theological account of human identity embodied desire and our social worlds by Felipe do Vale

Book Review: <i>Gender as love: A theological account of human identity embodied desire and our social worlds</i> by Felipe do Vale

A Postmodern Eco-Critical Study of Identity Crisis in "The Winter of Our Discontent"

This paper examines the theme of identity crisis in John Steinbeck's novel "The Winter of Our Discontent" through the lens of ecocriticism theory. The novel is set in the postmodern era and explores the moral decay of American society, particularly the loss of traditional values and the rise of materialism. Through the analysis of the novel, this paper explores the relationship between human identity and the natural world and how the destruction of the environment can lead to a crisis of identity. It starts with theoretical background, introduction, theory, discussion and analysis and ends with a conclusion.

The Perception of Malaysian Undergraduates towards Bilingualism and Multilingualism in Language Learning

Language is essential to human communication and identity. Individuals may have different language abilities in one or more languages. Bilingualism refers to the ability to use two languages proficiently, whereas multilingualism is characterised by the ability to use more than two languages. Cultural background, societal views, and personal experiences can significantly impact perceptions. Bilingualism and multilingualism may be viewed positively by some students while negatively by others. In today's globalised society, language diversity is growing, yet there is little research on students' perceptions of bilingualism and multilingualism in higher education in the Malaysian context. The study seeks to identify Malaysian undergraduates' perceptions towards bilingualism and multilingualism in language learning. Conducted among 51 undergraduate students at an engineering university in Malaysia, this quantitative study employed a survey-based approach. The result revealed positive perceptions of bilingualism and multilingualism in language learning influenced by the bilingual education system in Malaysia and globalisation. The present research has proved that students favour bilingualism and multilingualism, enhancing their motivation to acquire additional languages. This inclination stems from the belief that having proficiency in more than two languages confers a more excellent knowledge upon individuals.