Shape Moments Research Articles

The rise of artificial intelligence as the future of Korean culture diplomacy

The COVID-19 pandemic ushered in a new era of technology, pushing everything online and necessitating human adaptation to computers. Industry 4.0 proved invaluable during this pandemic, with Artificial Intelligence (AI) emerging as a key player, particularly in the beloved South Korean music industry, which enjoys international acclaim. The pandemic played a significant role in the increased use of AI within the K-POP industry, with the emergence of the Aespa Girl Group being a pivotal moment in shaping a futuristic concept. This research aims to investigate the recent surge in AI usage as a futuristic K-Pop concept through a qualitative literature study method. This paper contends that AI has the potential to profoundly impact Korean cultural diplomacy, serving as a game-changing element in the realm of digital diplomacy. While AI has traditionally been applied in high-context scenarios, such as search engines or high-tech automotive control systems, its application in cultural contexts could propel South Korea's cultural diplomacy to unprecedented heights, rendering the concept difficult for other nations to replicate.

BUNG KARNO’s POLITICAL THOUGHT ACCORDING TO PANCASILA: A Study of Bung Karno’s Speech on June 1, 1945, and the President Soekarno/Bung Karno’s Pancasila Course Throughout 1958-1959

This paper examines the evolution of Bung Karno’s Pancasila concept, tracing its origins from his pivotal June 1, 1945 speech and the comprehensive elucidation of Pancasila during the 1958 Pancasila Course, a crucial moment in shaping its official formulation. Pancasila has become an enduring cornerstone of Indonesian ideology. This prompts a closer examination of Sukarno’s political ideals. This study scrutinizes Bung Karno’s Pancasila ideology within the context of his political philosophy. Methodologically, this article employs a Qualitative-Descriptive approach, primarily drawing on literature and documentary sources. The concept of deconstruction has also used in this article. The findings underscore how Sukarno’s political convictions found expression in Pancasila. His political thought was deeply influenced by Indonesia’s social and political landscape, emphasizing the nation’s diverse yet interconnected destiny and history. Sukarno ingeniously infused this diversity with spiritual unity, encapsulated in the five principles known as “Pancasila.” For Sukarno, Pancasila wasn’t theoretical; it was his practical political tool to manage diversity and avert polarization among Indonesian citizens. The first principle, “Believe in One Supreme God,” was particularly pivotal, serving as the foundation on which the others relied to maintain their integrity. This study sheds light on how Pancasila became more than just a concept; it was Sukarno’s practical response to the complexities of Indonesia’s socio-political landscape, emphasizing unity amidst diversity.

The 2-Orthogonal and Orthogonal Radial Shape Moments for Image Representation and Recognition

The 2-Orthogonal and Orthogonal Radial Shape Moments for Image Representation and Recognition

Multiscale Modeling for Texture and Grain Topology of Polycrystalline Microstructures Under Uncertainty

The present work addresses multiscale modeling for grain topology of polycrystalline microstructures under the effects of the microstructural uncertainties. The special focus is on the titanium-7wt%-aluminum alloy (Ti-7Al), which is a candidate material for many aerospace systems owing to its outstanding mechanical performance in elevated temperatures. The electron backscatter diffraction samples of Ti-7Al in small-scales are used to reconstruct the alloy microstructures in larger domains. The reconstruction provides a statistically equivalent synthetic representation to the small-scale test samples while introducing epistemic uncertainty on microstructural features. Here, the grain topology of the polycrystalline microstructures is quantified using shape moment invariants. These invariant parameters can capture the shapes of physical objects with a numerical representation, and they are invariant to shape transformations. To quantify the effects of the uncertainties on the homogenized properties of the microstructures, a surrogate model is developed as a function of shape moment invariants with Gaussian process regression by utilizing the experiments and crystal plasticity simulations for training data.

A modified similarity measurement for image retrieval scheme using fusion of color, texture and shape moments

A modified similarity measurement for image retrieval scheme using fusion of color, texture and shape moments

Application of Shape Moments for Cloudiness Assessment in Marine Environmental Research

The search for clouds in satellite images is a challenging subject which still attracts a lot of attention due to the amount and quality of data, which is growing at a tremendous pace, the development of satellite techniques and methods, inexpensive equipment, and automation of satellite imaging processes. This paper presents a new approach to the assessment of cloudiness based on the use of the theory of moments with invariants. The values of moments with invariants, determined on the basis of the available cloudiness maps, create a new, valuable set of data, which are the geometrical parameters of the scene representing the cloud cover. In further research, the obtained data sets will be used in machine learning methods, deep machine learning methods, etc. The method is used for different conditions, including different angular positions of the Sun and time periods. The effectiveness of the method is checked on the basis of comparing the entropy results of the input maps after subtracting clouds masked by various methods. The obtained results additionally indicate the potential of the moments method as a support for the existing methods of estimating cloudiness over the sea surface.

On Identifying Terrorists Using Their Victory Signs

In certain cases, the only evidence to identify terrorists, who are seen in digital images or videos is their hands’ shapes, particularly, the victory sign as performed by many of them when they intentionally hide their faces, and/or distort their voices. This paper proposes new methods to identify those persons for the first time from their victory sign. These methods are based on features extracted from the fingers areas using shape moments in addition to other features related to fingers contours. To evaluate the proposed methods and to show the feasibility of this study we have created a victory sign database for 400 volunteers using a mobile phone camera. The experimental results using different classifiers show encouraging identification results; as the best precision/recall were achieved by merging normalized features from both methods using linear discriminate analysis classifier with 96.6% precision and 96.3 recall. Such a high performance achieved by the proposed methods shows their great potential to be applied for terrorists’ identification from their victory sign.

Direct parameter estimation for generalised balanced power diagrams

ABSTRACTThe statistical characterisation and synthetic reproduction of a polycrystalline material's microstructure is assisted by mathematically representing its morphology by a tessellation model. The generalised balanced power diagram (GBPD) is a tessellation model that was shown in previous studies to accurately reproduce the microstructure morphology of various materials by closely matching micrographs obtained through electron microscopy. These studies employed costly optimisation procedures to determine the best-fit model parameters, limiting the scalability of the model. In this work, it is shown that setting the tessellation cell parameters to values such that the shape moments of the corresponding grains are matched results in a quality of fit that is commensurate with optimisation procedures. This fitting approach decouples the interaction among grains when fitting the tessellation parameters and, most notably, provides analytical, closed-form expressions for all the model parameters. The performance of this parameter fitting approach is demonstrated on multiple micrographs of various materials, and it compares similarly to the performance of optimisation procedures reported in recently published literature. As the fitted parameter values are obtained through trivial computations, this approach enables extensive scalability of the GBPD model such that it can be used to represent extremely large characterisation data sets.

2-D Object Recognition Approach using Wavelet Transform

Humans have supernatural ability to observe, analyze, and tell about the layout of the 3D world with the help of their natural visual system. But contrary to machine vision system, it remains a most difficult task to recognize various objects from images being captured by cameras. This paper presents 2-D image object recognition approach using Daubechies (Db10) wavelet transform. Firstly, an edge detection is carried out to delineate objects from the images. Secondly, shape moments have been used for object recognition. For testing purpose, different geometrical shapes such as rectangle, circle, triangle and pattern have been selected for image analysis. Simulation has been performed using MATLAB, and obtained results showed that it accurately identifies the objects. The research goal was to test 2-D images for object recognition.

HUMAN ACTIVITIES RECOGNITION USING SHAPE MOMENTS AND HISTOGRAM OF NORMALIZED DISTANCES “HND”

this paper presents an algorithm for human activities recognition in videos based on a combination of two different feature types The first feature type concerns the shape and is called the Shape moments. The second feature type concerns the contour boundary coordinates and the feature is called Histogram of Normalized Distances from Center of gravity of the object Shape “COG” and it’s Contour points “HND”. Combining these features leads to the formation of a strong complementary feature vector that captures effective discriminate details of human action videos. We use two classifiers; the first is Multi-class Support Vector Machine and the second is Naive Bayes classifier. The Recognition rate by using Multi-class SVM classifier is up to 95.6 % but by using Naive Bayes classifier is 97.2%.

Machine-learning-based real–bogus system for the HSC-SSP moving object detection pipeline

Abstract Machine-learning techniques are widely applied in many modern optical sky surveys, e.g., Pan-STARRS1, PTF/iPTF, and the Subaru/Hyper Suprime-Cam survey, to reduce human intervention in data verification. In this study, we have established a machine-learning-based real–bogus system to reject false detections in the Subaru/Hyper-Suprime-Cam Strategic Survey Program (HSC-SSP) source catalog. Therefore, the HSC-SSP moving object detection pipeline can operate more effectively due to the reduction of false positives. To train the real–bogus system, we use stationary sources as the real training set and “flagged” data as the bogus set. The training set contains 47 features, most of which are photometric measurements and shape moments generated from the HSC image reduction pipeline (hscPipe). Our system can reach a true positive rate (tpr) ∼96% with a false positive rate (fpr) ∼1% or tpr ∼99% at fpr ∼5%. Therefore, we conclude that stationary sources are decent real training samples, and using photometry measurements and shape moments can reject false positives effectively.

Problems using ratios of galaxy shape moments in requirements for weak lensing surveys

Context. The shapes of galaxies are typically quantified by ratios of their quadrupole moments. Knowledge of these ratios (i.e. their measured standard deviation) is commonly used to assess the efficiency of weak gravitational lensing surveys. For faint galaxies, observational noise can make the denominator close to zero, so the ratios become ill-defined. Aims. Since the requirements cannot be formally tested for faint galaxies, we explore two complementary mitigation strategies. In many weak lensing contexts, the most problematic sources can be removed by a cut in measured size. This first technique is applied frequently. As our second strategy, we propose requirements directly on the quadrupole moments rather than their ratio. Methods. As an example of the first strategy, we have investigated how a size cut affects the required precision of the charge transfer inefficiency model for two shape measurement settings. For the second strategy, we analysed the joint likelihood distribution of the image quadrupole moments measured from simulated galaxies, and propagate their (correlated) uncertainties into ellipticities. Results. Using a size cut, we find slightly wider tolerance margins for the charge transfer inefficiency parameters compared to the full size distribution. However, subtle biases in the data analysis chain may be introduced. These can be avoided using the second strategy. To optimally exploit a Stage-IV dark energy survey, we find that the mean and standard deviation of a population of galaxies' quadrupole moments must to be known to better than 1:4 x 10(-3) arcsec(2), or the Stokes parameters to 1:9 x 10(-3) arcsec(2). Conclusions. Cuts in measured size remove sources that otherwise make ellipticity statistics of weak lensing galaxy samples diverge. However, size cuts bias the source population non-trivially. Assessing weak lensing data quality directly on the quadrupole moments instead mitigates the need for size cuts. Such testable requirements can form the basis for performance validation of future instruments.

DUSR (Distributed Ultrafast Shape Recognition): a Hadoop Based Tool to Identify Similar Shaped Ligand Molecules

Abstract: Background: Identifying potential drug candidates through Ligand-based virtual screening is often associated with processing of huge amount of data and hence is a computational intensive task. Ultrafast Shape Recognition (USR) algorithm has been reported as a faster alternative for molecular shape comparison which maps the chemical structure of query ligand into its shape moment vector to find novel chemical scaffolds in chemical compound libraries. The USR algorithm however was devoid of the ability to discriminate ligand molecules according to their pharmacokinetic features. Methods: To overcome this discrepancy, a modification in the existing USR algorithm called DUSR (Distributed Ultrafast Shape Recognition) was carried out where chemical compounds were screened on the basis of their drug-likeliness properties prior to the molecular shape comparison followed by shape complementarity momentum measure. The DUSR due to its Hadoop implementation acts as a faster approach than the existing standalone tools, utilizing the MapReduce algorithm supporting the high throughput screening of million conformers in a much reduced time span. We further demonstrated the utility of DUSR on dataset of 2 million ligand molecules by running shape comparison based searching job on standalone and multisystem Hadoop platforms. Results: The result suggested that DUSR completed its job in 1h 15 m 41s, 0 h 23 m 41s and 0h13m 22s sec for 2038924 molecules on Hadoop standalone mode, 3-nodes cluster & 5-nodes cluster of distributed commodity hardware respectively. Key words: DUSR (Distributed Ultrafast Shape Recognition), High throughput Screening, Hadoop, MapReduce, Virtual Screening.

Women as Symbols of National Honour and Masculinity in Crisis in Chaman Nahal's Azadi

The simultaneous Independence and Partition of India is considered to be the single most traumatic experience, a cataclysm that forever changed the contours of the country and the lives of the people. In the Punjab it resulted in a mass migration that dislocated millions. In the large-scale insensate, communal violence that followed Partition became a defining moment in shaping and strengthening a communitarian consciousness wherein religion became the prime explanatory category of nationhood. While Independence in India and Pakistan is celebrated, there has been a collective amnesia about the event despite the harrowing experiences the refugees testified to. Accompanying the official Indian erasure of the violence has been the historiographical lacuna on the moment until recently. Historical debates centre round the causes and the high politics of Partition but are unable to deal with violence. Moreover, this does not deal with the narrative of popular history. To deal with history from below and to recover marginal voices, history has become revisionist. Subaltern studies and Feminist research have focused on recording the oral testimonies of Partition survivors and witnesses. Revisionist feminist historiographers have investigated women's experiences of the violence and have shown how it became a gendered narrative of displacement which led to the realignment of family, community and national identities. They have also investigated the violence women were subjected to by men of their own as well as the other community and within their own families as they became symbols of national honour. Similarly, men too experienced violence during the Partition but questions like what happens to men's roles, male bodies and conceptions of masculinity remain unanswered and hidden. Ashuman voices are silent on the violence, historians have observed that literature has stepped in to supplement the lacuna. Based on his personal experiences of the Partition, Chaman Nahal's Azadi deals with the gendered, sexual violence women faced while on the move in kafilas or foot convoys. The other, embedded in the narrative, is about a little dealt aspect of Partition violence: violence committed on male bodies. This paper will show how both women and men faced violence from the perspective of a male writer and whether Nahal has succeeded in his enterprise or not.

‘Joburg has its own momentum’: Towards a vernacular theorisation of urban change

This article demonstrates and advocates the importance of theoretical frameworks which allow for nuance and complexity. Moving away from fixed ways of reading and analysing processes of urban renewal (such as gentrification, revanchism, neoliberal urbanism), it seeks to show how a diversity of imperatives and agendas are present and shape moments of urban change and the practices of actors involved in these. Drawing on research conducted in inner-city Johannesburg which focussed on private-sector-led regeneration, housing provision and security, it demonstrates that the process underway is characterised by a multiplicity of goals and practices. Regeneration is formulated within a neoliberal paradigm, yet through creative strategies and interventions is also achieving developmental goals and expanding the provision of affordable, centrally-located housing. The article details the strategies adopted by organisations specialising in financing social and affordable housing and demonstrates the ways in which these emphasise and are helping to achieve the expansion of housing provision to low-income households. It further discusses the habitus of housing providers in the inner-city and shows how these have been influenced by and respond to the developmental challenges and racial transformation which characterise the area. It thus demonstrates that local contexts, concerns and agendas influence the regeneration process and that putatively global processes such as gentrification, revanchism and neoliberal urbanism, whilst still relevant, need to be used in ways which allow for alternative, vernacular narratives and explanations to emerge too.

Speculating on London's housing future

London's housing crisis is rooted in a neo-liberal urban project to recommodify and financialise housing and land in a global city. But where exactly is the crisis heading? What future is being prepared for London's urban dwellers? How can we learn from other country and city contexts to usefully speculate about London's housing future? In this paper, we bring together recent evidence and insights from the rise of what we call ‘global corporate landlords’ (GCLs) in ‘post-crisis’ urban landscapes in North America and Europe to argue that London's housing crisis—and the policies and processes impelling and intervening in it—could represent a key moment in shaping the city's long-term housing future. We trace the variegated ways in which private equity firms and institutional investors have exploited distressed housing markets and the new profitable opportunities created by states and supra-national bodies in coming to the rescue of capitalism in the USA, Spain, Ireland and Greece in response to the global financial crisis of 2007–2008. We then apply that analysis to emerging developments in the political economy of London's housing system, arguing that despite having a very low presence in the London residential property market and facing major entry barriers, GCLs are starting to position themselves in preparation for potential entry points such as the new privatisation threat to public and social rented housing.

Shape registration using characteristic functions

This study presents a fast algorithm for the registration of shapes implicitly represented by their characteristic functions. The algorithm proposed here aims to recover the registration parameters (scaling, rotation and translation) by minimising a dissimilarity term between the two shapes. The proposed algorithm is based on phase correlation and statistical shape moments to compute the registration parameters individually. The registration method proposed here is applied to various registration problems, to address issues such as the registration of shapes with various topologies and registration of complex shapes containing various numbers of sub-shapes. The method proposed here is characterised with a better accuracy, a higher convergence speed, robustness at the presence of excessive noise and a better performance for registration over large databases of shapes, in comparison with other state-of-the-art shape registration techniques in the literature.

Error analysis of moment-based modal wavefront sensing

The shape of a focus-modulated point spread function (PSF) is used as a quick visual assessment tool of aberration modes in the PSF. Further analysis in terms of shape moments can permit quantifying the modal coefficients with an accuracy comparable to that of typical wavefront sensors. In this Letter, the error of the moment-based wavefront sensing is analytically described in terms of the pixelation and photon/readout noise. All components highly depend on the (unknown) PSF shape but can be estimated from the measured PSF sampled at a reasonable spatial resolution and photon count. Numerical simulations verified that the models consistently predicted the behavior of the modal estimation error of the moment-based wavefront sensing.

Measurement of Strong Coupling Constant by Using Event Shape Moments in Perturbative Theory

We measure the strong coupling constant at NNLO corrections. We do this analysis with moments of event shape variables: thrust, C parameter, heavy jet mass, wide and total jet broadening, by fitting the L3 and DELPHI data with NNLO model. Our real data are consistent with NNLO calculations, because it involves higher order terms in QCD calculations.

Study on Test Scheme of Shield Tunnel Prestressed Segment Joint

Mechanical property of the segment joint for fabricated shield tunnel lining is the key factor for segment lining design and research. Based on the test prototype of shield tunnel segment lining with about 6m diameter, the test scheme of prestressed segment joint has been studied. On account for the influencing factors of prestressing force, prestressed reinforcement shape, joint shape and bending moment, the test structure and test conditions were designed. And the test content and methods were brought out, the test procedure and notes were discussed.