Search results for: ambiguity resolution

Authors: Robin V. Cupido

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Online dispute resolution has been identified in many countries as a viable alternative for resolving conflicts which have arisen in the so-called digital age. This system of dispute resolution is developing alongside the Internet, and as new types of transactions are made possible by our increased connectivity, new ways of resolving disputes must be explored. Developed nations, such as the United States of America and the European Union, have been involved in creating these online dispute resolution mechanisms from the outset, and currently have sophisticated systems in place to deal with conflicts arising in a number of different fields, such as e-commerce, domain name disputes, labour disputes and conflicts arising from family law. Specifically, in the field of e-commerce, the Internet’s borderless nature has served as a way to promote cross-border trade, and has created a global marketplace. Participation in this marketplace boosts a country’s economy, as new markets are now available, and consumers can transact from anywhere in the world. It would be especially advantageous for developing nations to be a part of this global marketplace, as it could stimulate much-needed investment in these nations, and encourage international co-operation and trade. However, for these types of transactions to proliferate, an effective system for resolving the inevitable disputes arising from such an increase in e-commerce is needed. Online dispute resolution scholarship and practice is flourishing in developed nations, and it is clear that the gap is widening between developed and developing nations in this regard. The potential for implementing online dispute resolution in developing countries has been discussed, but there are a number of obstacles that have thus far prevented its continued development. This paper aims to evaluate the various political, infrastructural and socio-economic challenges faced in developing nations, and to question how these have impacted the acceptance and development of online dispute resolution, scholarship and training of online dispute resolution practitioners and, ultimately, developing nations’ readiness to participate in cross-border e-commerce.

Keywords: developing countries, feasibility, online dispute resolution, progress

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Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

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Authors: F. R. Chen, C. Kisielowski, D. Van Dyck

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In principle, the latest generation aberration-corrected transmission electron microscopes (TEMs) could achieve sub-Å resolution, but there is bottleneck that hinders the final step towards revealing 3D structure. Firstly, in order to achieve a resolution around 1 Å with single atom sensitivity, the electron dose rate needs to be sufficiently large (10⁴-10⁵eÅ⁻² s⁻¹). With such large dose rate, the electron beam can induce surfaces alterations or even bulk modifications, in particular, for electron beam sensitive (soft) materials such as nm size particles, organic materials, proteins or macro-molecules. We will demonstrate methodology of low dose electron holography for observing 3D structure for soft materials such as single Oleic acid molecules at atomic resolution. The main improvement of this new type of electron holography is based on two concepts. Firstly, the total electron dose is distributed over many images obtained at different defocus values from which the electron hologram is then reconstructed. Secondly, in contrast to the current tomographic methods that require projections from several directions, the 3D structural information of the nano-object is then extracted from this one hologram obtained from only one viewing direction.

Keywords: low dose electron microscopy, in-line electron holography, atomic resolution tomography, soft materials

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Authors: Roy Alex, Dr. Shampa I Dev

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Abstract Nine out of twenty-eight states in India have enacted anti-conversion laws to regulate religious conversions by use of force, allurement, inducement, or fraudulent means. The vagueness of the definitions of the terms used in these laws makes them inconsistent with the provisions of the right to freedom of religion guaranteed by the Constitution. It is a critical question whether these laws protect the religious freedom of groups that are “vulnerable” to missionary inducements, or are they restricting the freedom of citizens to propagate their religion to others or change their religious identity? This article looks into the constitutionality of the anti-conversion laws passed in the Indian States and argues that these laws limit the freedom of religion guaranteed under Article 25 of the Constitution of India. The ambiguity in the anti-conversion laws passed in various states of India is brought out by critically analyzing multiple cases charged under anti-conversion laws.

Keywords: Freedom of Religion, Anti-conversion Laws, allurement, inducement, and fraudulent means.

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Authors: Yuchen Yang, Zhenming Wang, Jun Zhu, Ning Zhao

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An easy-to-implement and robust finite volume multi-resolution Weighted Essentially Non-Oscillatory (WENO) scheme is proposed on adaptive cartesian grids in this paper. Such a multi-resolution WENO scheme is combined with the ghost cell immersed boundary method (IBM) and wall-function technique to solve Navier-Stokes equations. Unlike the k-exact finite volume WENO schemes which involve large amounts of extra storage, repeatedly solving the matrix generated in a least-square method or the process of calculating optimal linear weights on adaptive cartesian grids, the present methodology only adds very small overhead and can be easily implemented in existing edge-based computational fluid dynamics (CFD) codes with minor modifications. Also, the linear weights of this adaptive finite volume multi-resolution WENO scheme can be any positive numbers on condition that their sum is one. It is a way of bypassing the calculation of the optimal linear weights and such a multi-resolution WENO scheme avoids dealing with the negative linear weights on adaptive cartesian grids. Some benchmark viscous problems are numerical solved to show the efficiency and good performance of this adaptive multi-resolution WENO scheme. Compared with a second-order edge-based method, the presented method can be implemented into an adaptive cartesian grid with slight modification for big Reynolds number problems.

Keywords: adaptive mesh refinement method, finite volume multi-resolution WENO scheme, immersed boundary method, wall-function technique.

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Authors: Krzysztof Malczewski

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Magnetic Resonance Imaging (MRI) reconstruction algorithm using compressed sensing is presented in this paper. It is exhibited that the offered approach improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were conventionally assumed necessary. Magnetic Resonance Imaging (MRI) is a fundamental medical imaging method struggles with an inherently slow data acquisition process. The use of CS to MRI has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the objective is to combine super-resolution image enhancement algorithm with CS framework benefits to achieve high resolution MR output image. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. The presented algorithm considers the cardiac and respiratory movements.

Keywords: super-resolution, MRI, compressed sensing, sparse-sense, image enhancement

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Authors: W. M. M. Weerasooriya, K. T. N. P. Abeywickrama

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There has been some research on stress in the hotel industry in Sri Lanka and elsewhere. Still, the amount is not proportionate to the severity of the issue. This paper examined the effect of stress on job performance of frontline employees of Sri Lankan hotel context. Duly completed 70 self-administered questionnaires filled by frontline employees of star class hotels in North Central Province in Sri Lanka were used for the purpose with a response rate of 70%. The researcher employed empirical analysis using statistical tools such as regression analysis of Pearson’s correlation of coefficient. It was found that there is a high level of workload and role ambiguity existing among the frontline employees of hotels located in North Central Province and existing role ambiguity significantly reduce the job performance of the frontline employees of star class hotels while the existing low level of physical work environment also leads to a low level of job performance.

Keywords: hotel front line employees, job stress, job performance, Sri Lanka

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Authors: Oluwole Enoch Adeniran

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Peace studies and conflict resolution; though a relatively new discipline had attracted scholars from far and near. It had enhanced a purposeful training of mind of young adult among other categories of learners. It provides a platform through which university under-graduates and post-graduates students are exposed to the rudiments of peace building, peacemaking and peace keeping towards a successful conflict resolution. The paper historicizes peace education as most desirable in any human society that desired development. It aims at educating children and young adults in the dynamics of peaceful conflicts resolution at home, in school and communities (states) throughout the world for a purposeful technological development. It also aims at exposing students to the nature of conflict and how to manage and resolve conflicts in order to promote national unity for meaningful development. The paper argues that, for a state to record any meaningful socio-economic, political and technological development; a conducive and peaceful atmosphere must be put in place. This theoretical paper emerged in the context of historical specificities of conflict resolution from a general conceptual framework. It then concludes with suggestions on the modes of conflict prevention, conflict management and conflict resolution for an ideal technologically advanced society.

Keywords: history, education, peace, unity, technology and development

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Authors: Hiroyuki Aoki

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The physical properties of polymer materials are dependent on the conformation and molecular motion of a polymer chain. Therefore, the structure and dynamic behavior of the single polymer chain have been the most important concerns in the field of polymer physics. However, it has been impossible to directly observe the conformation of the single polymer chain in a bulk medium. In the current work, the novel techniques to study the conformation and dynamics of a single polymer chain are proposed. Since a fluorescence method is extremely sensitive, the fluorescence microscopy enables the direct detection of a single molecule. However, the structure of the polymer chain as large as 100 nm cannot be resolved by conventional fluorescence methods because of the diffraction limit of light. In order to observe the single chains, we developed the labeling method of polymer materials with a photo-switchable dye and the super-resolution microscopy. The real-space conformational analysis of single polymer chains with the spatial resolution of 15-20 nm was achieved. The super-resolution microscopy enables us to obtain the three-dimensional coordinates; therefore, we succeeded the conformational analysis in three dimensions. The direct observation by the nanometric optical microscopy would reveal the detailed information on the molecular processes in the various polymer systems.

Keywords: polymer materials, single molecule, super-resolution techniques, conformation

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: N. Dahraoui, M. Boulakroune, D. Benatia

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In this paper, the improvement by deconvolution of the depth resolution in Secondary Ion Mass Spectrometry (SIMS) analysis is considered. Indeed, we have developed a new Tikhonov-Miller deconvolution algorithm where a priori model of the solution is included. This is a denoisy and pre-deconvoluted signal obtained from: firstly, by the application of wavelet shrinkage algorithm, secondly by the introduction of the obtained denoisy signal in an iterative deconvolution algorithm. In particular, we have focused the light on the effect of the iterations number on the evolution of the deconvoluted signals. The SIMS profiles are multilayers of Boron in Silicon matrix.

Keywords: DRF, in-depth resolution, multiresolution deconvolution, SIMS, wavelet shrinkage

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Authors: Retno Supriyanti, Teguh Budiono, Yogi Ramadhani, Haris B. Widodo, Arwita Mulyawati

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Cervical cancer is the leading cause of mortality in cancer-related diseases. In this diagnosis doctors usually perform several tests to determine the presence of cervical cancer in a patient. However, these checks require support equipment to get the results in more detail. One is by using ultrasonography. However, for the developing countries most of the existing ultrasonography has a low resolution. The goal of this research is to obtain abnormalities on low-resolution ultrasound images especially for cervical cancer case. In this paper, we emphasize our work to use Image Enhancement for pre-processing image quality improvement. The result shows that pre-processing stage is promising to support further analysis.

Keywords: cervical cancer, mortality, low-resolution, image enhancement.

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Authors: Jagna Mucha, Anna Kańciak

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The concept of good governance constitutes a wide perspective for academic discussion, because it provides a substantial theoretical background for settling many practical problems faced contemporarily by the EU. The basic assumptions of good governance have basically remained unchanged since the 90’s, when the concept was introduced by the World Bank, although the scholarly discussions reveal new facets of the said concept, when related to specific domains. The paper discusses the application of the specific elements of the concept of good governance in the field of the international investment law. Specifically, it seeks to demonstrate that the concept of good governance regulates the issue of international investments in that, among others, it requires the application of the alternative dispute resolution in order to make the investment law enforceable in the best possible way.

Keywords: dispute resolution, european union, investments, good governance

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Authors: Siddharth Sarma, Ayush Majumdar, Nidhi Sabu, Mufaddal Jiruwaala, Shilpa Paygude

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Digital Elevation Models (DEMs) are digital representations of the Earth’s topography, which include information about the elevation, slope, aspect, and other terrain attributes. DEMs play a crucial role in various applications, including terrain analysis, urban planning, and environmental modeling. In this paper, TerraEnhance is proposed, a distinct approach for high-resolution DEM generation using Generative Adversarial Networks (GANs) combined with Real-ESRGANs. By learning from a dataset of low-resolution DEMs, the GANs are trained to upscale the data by 10 times, resulting in significantly enhanced DEMs with improved resolution and finer details. The integration of Real-ESRGANs further enhances visual quality, leading to more accurate representations of the terrain. A post-processing layer is introduced, employing high-pass filtering to refine the generated DEMs, preserving important details while reducing noise and artifacts. The results demonstrate that TerraEnhance outperforms existing methods, producing high-fidelity DEMs with intricate terrain features and exceptional accuracy. These advancements make TerraEnhance suitable for various applications, such as terrain analysis and precise environmental modeling.

Keywords: DEM, ESRGAN, image upscaling, super resolution, computer vision

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Authors: Muslim Khan, Kenneth B. Jensen, Kevin A. Francesconi

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Trace amounts (ca 1 µg/L, 13 nM) of arsenic are present in sea water mostly as the oxyanion arsenate. In contrast, arsenic is present in marine biota (animals and algae) at very high levels (up to100,000 µg/kg) a significant portion of which is present as lipid-soluble compounds collectively termed arsenolipids. The complex nature of sea water presents an analytical challenge to detect trace compounds and monitor their environmental path. We developed a simple method using liquid-liquid extraction combined with HPLC-High Resolution Mass Spectrometer capable of detecting trace of arsenolipids (99 % of the sample matrix while recovering > 80 % of the six target arsenolipids with limit of detection of 0.003 µg/L.)

Keywords: arsenolipids, sea water, HPLC-high resolution mass spectrometry

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Authors: Antigoni Panagiotopoulou, Lemonia Ragia

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High-resolution satellite images can provide detailed information about change detection on the earth. In the present work, QuickBird images of spatial resolution 60 cm/pixel and WorldView images of resolution 30 cm/pixel are utilized to perform automatic change detection in urban and suburban areas of Crete, Greece. There is a relative time difference of 13 years among the satellite images. Multiindex scene representation is applied on the images to classify the scene into buildings, vegetation, water and ground. Then, automatic change detection is made possible by pixel-per-pixel comparison of the classified multi-temporal images. The vegetation index and the water index which have been developed in this study prove effective. Furthermore, the proposed change detection approach not only indicates whether changes have taken place or not but also provides specific information relative to the types of changes. Experimentations with other different scenes in the future could help optimize the proposed spectral indices as well as the entire change detection methodology.

Keywords: change detection, multiindex scene representation, spectral index, QuickBird, WorldView

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Authors: Keyao Li, Sai On Cheung

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Incorporation of alternative dispute resolution (ADR) mechanism has been the main feature of current trend of construction project dispute resolution (CPDR). ADR approaches have been identified as efficient mechanisms and are suitable alternatives to litigation and arbitration. Moreover, the use of ADR in this multi-tiered dispute resolution process often leads to repeated evaluations of a same dispute. Multi-tiered CPDR may become a breeding ground for cognitive biases. When completed knowledge is not available at the early tier of construction dispute resolution, disputing parties may form preconception of the dispute matter or the counterpart. This preconception would influence their information processing in the subsequent tier. Disputing parties tend to search and interpret further information in a self-defensive way to confirm their early positions. Their imbalanced information collection would boost their confidence in the held assessments. Their attitudes would be hardened and difficult to compromise. The occurrence of cognitive bias, therefore, impedes efficient dispute settlement. This study aims to explore ways to minimize bias in CPDR. Based on a comprehensive literature review, three types of bias minimizing approaches were collected: strategy-based, attitude-based and process-based. These approaches were further operationalized into bias minimizing measures. To verify the usefulness and practicability of these bias minimizing measures, semi-structured interviews were conducted with ten CPDR third party neutral professionals. All of the interviewees have at least twenty years of experience in facilitating settlement of construction dispute. The usefulness, as well as the implications of the bias minimizing measures, were validated and suggested by these experts. There are few studies on cognitive bias in construction management in general and in CPDR in particular. This study would be the first of its type to enhance the efficiency of construction dispute resolution by highlighting strategies to minimize the biases therein.

Keywords: bias, construction project dispute resolution, minimization, multi-tiered, semi-structured interview

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Authors: Adejoke Yemisi Ige

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This study presents a conceptual analysis and investigation into the development of a systematic framework required for better understanding of the social process of Alternative Dispute Resolution (ADR) and collective conciliation. The critical examination presented in this study is significant because; it draws on insight from ADR, negotiation and collective bargaining literature and applies it in our advancement of a methodical outline which gives an insight into the influence of the key actors and other stakeholder strategies and behaviours during dispute resolution in relation to the outcomes which is novel. This study is qualitative and essentially inductive in nature. One of the findings of the study confirms the need to consider ADR and collective conciliation within the context of the characteristic conditions; which focus on the need for some agreement to be reached. Another finding of the study shows the extent which information-sharing, willingness of the parties to negotiate and make concession assist both parties to attain resolution. This paper recommends that in order to overcome deadlock and attain acceptable outcomes at the end of ADR and collective conciliation, the importance of information exchange and sustenance of trade union and management relationship cannot be understated. The need for trade unions and management, the representatives to achieve their expectations in order to build the confidence and assurance of their respective constituents is essential. In conclusion, the analysis presented in this study points towards a set of factors that together can be called the social process of collective conciliation nevertheless; it acknowledges that its application to collective conciliation is new.

Keywords: alternative dispute resolution, collective conciliation, social process, theoretical framework, unveiling

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Authors: Manoj Kumar Dutta

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Wavelength division multiplexing (WDM) technology is the most promising technology for the proper utilization of huge raw bandwidth provided by an optical fiber. One of the key problems in implementing the all-optical WDM network is the packet contention. This problem can be solved by several different techniques. In time domain approach the packet contention can be reduced by incorporating fiber delay lines (FDLs) as optical buffer in the switch architecture. Different types of buffering architectures are reported in literatures. In the present paper a comparative performance analysis of three most popular FDL architectures are presented in order to obtain the best contention resolution performance. The analysis is further extended to consider the effect of different fiber non-linearities on the network performance.

Keywords: WDM network, contention resolution, optical buffering, non-linearity, throughput

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Authors: Rashmi Yadawad, Disha Narayanan, Ravi Gautam

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Through Wall Radar Imaging is gaining increasing importance now a days in the field of Defense and one of the most important criteria that forms the basis for the image quality obtained is the Cross-Range resolution of the image. In this research paper, the Bilateral Back projection algorithm has been implemented for Through Wall Radar Imaging. The sole purpose is to enhance the resolution in the cross range direction of the obtained Back projection image. Synthetic Data is generated for two targets which are placed at various locations in a room of dimensions 8 m by 6m. Two algorithms namely, simple back projection and Bilateral Back projection have been implemented, images are obtained and the obtained images are compared. Numerical simulations have been coded in MATLAB and experimental results of the two algorithms have been shown. Based on the comparison between the two images, it can be clearly seen that the ringing effect and chess board effect have been heavily reduced in the bilaterally back projected image and hence promising results are obtained giving a relatively sharper image with relatively well defined edges.

Keywords: through wall radar imaging, bilateral back projection, cross range resolution, synthetic data

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Authors: Salehi Zahabi Saleh, Rajabi Hosaien, Rasaneh Samira

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Yttrium-90 (90Y) radioembolisation(RE) is increasingly used for the treatment of patients with unresectable primary or metastatic liver tumours. Image-based approaches to assess microsphere distribution after RE have gained interest but are mostly hampered by the limited imaging possibilities of the Isotope 90Y. Quantitative 90Y-SPECT imaging has limited spatial resolution because it is based on 90Y Bremsstrahlung whereas 90Y-PET has better spatial resolution but low sensitivity. As a consequence, new alternative methods of visualizing the microspheres have been investigated, such as MR imaging of iron-labelled microspheres. It was also shown that MRI combines high sensitivity with high spatial and temporal resolution and with superior soft tissue contrast and thus can be used to cover a broad range of clinically interesting imaging parameters.The aim of the study in this article was to investigate the capability of MRI to measure the intrahepatic microsphere distribution in order to quantify the absorbed radiation dose in RE.

Keywords: radioembolisation, MRI, imaging, dosimetry

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Authors: Joyce Onoromhenre Agofure

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Research has shown how fictional work and films reflect the destruction of the environment due to the exploitation of oil, gas, gold, and forest products by multinational companies for profits but overlook discussions on conflict resolution and peacebuilding. However, this paper examines the manner art forms project peace and conflict resolution, thereby contributing to mediation and stability geared towards changing appalling situations in the resource extraction regions of Nigeria. This paper draws from selected Nigerian films- Blood and Oil (2019), directed by Curtis Graham, Black November (2012), directed by Jeta Amata, and a novel- Death of Eternity (2007), by Adamu Kyuka Usman. The study seeks to show that the disruptions caused in the natural resource regions of Nigeria have not only left adverse effects on the social well-being of the people but require resolutions through means of peacebuilding. By adopting the theoretical insights of Social Conflict, this paper focuses on artistic processes that enhance peacebuilding and conflict resolution in non-violent ways by using scenes, visual effects, themes, and images that can educate by shaping opinions, influencing attitudes, and changing ideas and behavioral patterns of individuals and communities. Put together; the research will open up critical perceptions brought about by the artists of study to shed light on the dire need to sustain peace and actively participate in conflict resolution in natural resource extraction spaces.

Keywords: natural resource, extraction, conflict resolution, peace building

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Authors: Odoh Ben Uruchi

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Access to Justice implies access to social and distributive Justice. Access to social justice in Nigeria remains an illusion where cases last in courts for unduly long period of time, as is currently the situation in the country. As the popular saying goes– justice delayed is justice denied. It is, however, important to underscore the point that these perspectives are not necessarily disconnected since the extent to which one can have distributive justice in any system is largely determined by the level and effectiveness of social justice in the country. Generally, Alternative Dispute Resolution (ADR) Processes are increasingly being accepted in Nigeria as appropriate mechanisms for resolving disputes. While some jurisdictions have institutionalized ADR through the concept of a Multidoor Courthouse, many other are at different stages of doing same. With these developments, it is obvious that stakeholders in the administration of justice in Nigeria, can no longer be indifferent about understanding and fully mainstreaming ADR into their various activities and professional practice. Any framework for promoting social justice in Nigeria should therefore of necessity include provision of avenues for use of ADR in the protection and enforcement of citizen’s rights. The constitutional and other legal provisions that guarantee various rights of citizens cannot of itself ensure the enjoyment of the rights in the absence of an effective framework for dispute resolution. Excessive reliance on litigation and other adversarial approaches will also fail to ensure a sound regime of social justice. There should be structured mainstreaming of alternative dispute resolution mechanisms in justice delivery if the society must provide and guarantee social justice to the citizens. This paper seeks to address some of the fundamental issues affecting the perception, knowledge and skills of ADR in the provision of social justice. In doing this, the paper proposes to unlock the full enormous potentials of Alternative Dispute Resolution (ADR) in promoting access to justice in Nigeria.

Keywords: aspects, dimensions, alternative dispute resolution, social justice

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Authors: Wang Zhaoming, Shao Shegang, Chen Xiaorong, Qi Yanan, Tian Lei, Wang Jian

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This study conducts a comparative analysis of the spectral curves of asphalt pavements at various aging stages to improve road information extraction from high-resolution remote sensing imagery. By examining the distinguishing capabilities and spectral characteristics, the research aims to establish a pavement information extraction methodology based on China's high-resolution satellite images. The process begins by analyzing the spectral features of asphalt pavements to construct a spectral assessment model suitable for evaluating pavement health. This model is then tested at a national highway traffic testing site in China, validating its effectiveness in distinguishing different pavement aging levels. The study's findings demonstrate that the proposed model can accurately assess road health, offering a valuable tool for road maintenance planning and infrastructure management.

Keywords: spectral analysis, asphalt pavement aging, high-resolution remote sensing, pavement health assessment

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Hardi Alunaza, Mauidhotu Rofiq

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This research is attempted to describe the role of KontraS as track-6 on multi track diplomacy for conflict resolution in Myanmar in 2015. The researcher took the specific interest on multi track diplomacy and transnational advocacy concepts to analyze the phenomena. Furthermore, this essay is using the descriptive method with a qualitative approach. The data collection technique is literature study consisting of books, journals, and including data from the reliable website in supporting the explanation of this research. The result of this research is divided into two important points in explaining the role of KontraS in cases of human rights crisis in Myanmar. First, KontraS as human rights NGO in Indonesia was able to advocate against human rights violence that occurred in other countries by encouraging Indonesian Government to take part in the resolution of human rights issues affecting the Rohingya people in Burma. Also, KontraS take advantages of transnational advocacy networks as a form of politics and accountabilities responsibility of Non-Governmental Organization against human rights crisis in other countries.

Keywords: conflict resolution, human rights crisis, multi track diplomacy, transnational advocacy

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Hussain Sajid, Jung-Hun Shin, Kum-Won Cho

Abstract:

Image super-resolution is the most common computer vision problem with many important applications. Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory requirements of GAN-based SR (mainly generators) lead to performance degradation and increased energy consumption, making it difficult to implement it onto resource-constricted devices. To relieve such a problem, In this paper, we introduce an optimized and highly efficient architecture for SR-GAN (generator) model by utilizing model compression techniques such as Knowledge Distillation and pruning, which work together to reduce the storage requirement of the model also increase in their performance. Our method begins with distilling the knowledge from a large pre-trained model to a lightweight model using different loss functions. Then, iterative weight pruning is applied to the distilled model to remove less significant weights based on their magnitude, resulting in a sparser network. Knowledge Distillation reduces the model size by 40%; pruning then reduces it further by 18%. To accelerate the learning process, we employ the Horovod framework for distributed training on a cluster of 2 nodes, each with 8 GPUs, resulting in improved training performance and faster convergence. Experimental results on various benchmarks demonstrate that the proposed compressed model significantly outperforms state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and image quality for x4 super-resolution tasks.

Keywords: single-image super-resolution, generative adversarial networks, knowledge distillation, pruning

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Authors: Nihad Karim Chowdhury, Mohammad Sanaullah Chowdhury, Muhammed Jamshed Alam Patwary, Rubel Biswas

Abstract:

In content-based 3D shape retrieval system, achieving high search performance has become an important research problem. A challenging aspect of this problem is to find an effective shape descriptor which can discriminate similar shapes adequately. To address this problem, we propose a new shape descriptor for 3D shape models by combining multi-resolution with multi-block center-symmetric local binary pattern operator. Given an arbitrary 3D shape, we first apply pose normalization, and generate a set of multi-viewed 2D rendered images. Second, we apply Gaussian multi-resolution filter to generate several levels of images from each of 2D rendered image. Then, overlapped sub-images are computed for each image level of a multi-resolution image. Our unique multi-block CS-LBP comes next. It allows the center to be composed of m-by-n rectangular pixels, instead of a single pixel. This process is repeated for all the 2D rendered images, derived from both ‘depth-buffer’ and ‘silhouette’ rendering. Finally, we concatenate all the features vectors into one dimensional histogram as our proposed 3D shape descriptor. Through several experiments, we demonstrate that our proposed 3D shape descriptor outperform the previous methods by using a benchmark dataset.

Keywords: 3D shape retrieval, 3D shape descriptor, CS-LBP, overlapped sub-images

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Authors: Khadija Bouzaachane, El Mahdi El Guarmah

Abstract:

The classification of low-resolution satellite images has been a worthwhile and fertile field that attracts plenty of researchers due to its importance in monitoring geographical areas. It could be used for several purposes such as disaster management, military surveillance, agricultural monitoring. The main objective of this work is to classify efficiently and accurately low-resolution satellite images by using novel technics of deep learning and reinforcement learning. The images include roads, residential areas, industrial areas, rivers, sea lakes, and vegetation. To achieve that goal, we carried out experiments on the sentinel-2 images considering both high accuracy and efficiency classification. Our proposed model achieved a 91% accuracy on the testing dataset besides a good classification for land cover. Focus on the parameter precision; we have obtained 93% for the river, 92% for residential, 97% for residential, 96% for the forest, 87% for annual crop, 84% for herbaceous vegetation, 85% for pasture, 78% highway and 100% for Sea Lake.

Keywords: classification, deep learning, reinforcement learning, satellite imagery

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