Search results for: sparse reconstruction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 772

Search results for: sparse reconstruction

502 Study of Geological Structure for Potential Fresh-Groundwater Aquifer Determination around Cidaun Beach, Cianjur Regency, West Java Province, Indonesia

Authors: Ilham Aji Dermawan, M. Sapari Dwi Hadian, R. Irvan Sophian, Iyan Haryanto

Abstract:

The study of the geological structure in the surrounding area of Cidaun, Cianjur Regency, West Java Province, Indonesia was conducted around the southern coast of Java Island. This study aims to determine the potentially structural trap deposits of freshwater resources in the study area, according to that the study area is an area directly adjacent to the beach, where the water around it did not seem fresh and brackish due to the exposure of sea water intrusion. This study uses the method of geomorphological analysis and geological mapping by taking the data directly in the field within 10x10 km of the research area. Geomorphological analysis was done by calculating the watershed drainage density value and roundness of watershed value ratio. The goal is to determine the permeability of the sub-soil conditions, rock constituent, and the flow of surface water. While the field geological mapping aims to take the geological structure data and then will do the reconstruction to determine the geological conditions of research area. The result, from geomorphology aspects, that the considered area of potential groundwater consisted of permeable surface material, permeable sub-soil, and low of water run-off flow. It is very good for groundwater recharge area. While the results of geological reconstruction after conducted of geological mapping is joints that present were initiated for the Cipandak Fault that cuts Cipandak River. That fault across until the Cibako Syncline fold through the Cibako River. This syncline is expected to place of influent groundwater aquifer. The tip of Cibako River then united with Cipandak River, where the Cipandak River extends through Cipandak Syncline fold axis in the southern regions close to its estuary. This syncline is expected to place of influent groundwater aquifer too.

Keywords: geological structure, groundwater, hydrogeology, influent aquifer, structural trap

Procedia PDF Downloads 185
501 The Nature of the Complicated Fabric Textures: How to Represent in Primary Visual Cortex

Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

Abstract:

Fabric textures are very common in our daily life. However, we never explore the representation of fabric textures from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. Experimental results based on 140 classical fabric images indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency, and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: fabric texture, receptive filed, simple cell, spare coding

Procedia PDF Downloads 448
500 Electric Field Analysis of XLPE, Cross-Linked Polyethylene Covered Aerial Line and Insulator Lashing

Authors: Jyh-Cherng Gu, Ming-Ta Yang, Dai-Ling Tsai

Abstract:

Both sparse lashing and dense lashing are applied to secure overhead XLPE (cross-linked polyethylene) covered power lines on ceramic insulators or HDPE polymer insulators. The distribution of electric field in and among the lashing wires, the XLPE power lines and insulators in normal clean condition and when conducting materials such as salt, metal particles, dust, smoke or acidic smog are present is studied in this paper. The ANSYS Maxwell commercial software is used in this study for electric field analysis. Although the simulation analysis is performed assuming ideal conditions due to the constraints of the simulation software, the result may not be the same as in real situation but still be of sufficient practical values.

Keywords: electric field intensity, insulator, XLPE covered aerial line, empty

Procedia PDF Downloads 244
499 Heat Transfer Enhancement through Hybrid Metallic Nanofluids Flow with Viscous Dissipation and Joule Heating Effect

Authors: Khawar Ali

Abstract:

We present the numerical study of unsteady hydromagnetic (MHD) flow and heat transfer characteristics of a viscous incompressible electrically conducting water-based hybrid metallic nanofluid (containing Cu-Au/ H₂O nanoparticles) between two orthogonally moving porous coaxial disks with suction. Different from the classical shooting methodology, we employ a combination of a direct and an iterative method (SOR with optimal relaxation parameter) for solving the sparse systems of linear algebraic equations arising from the FD discretization of the linearized self similar nonlinear ODEs. Effects of the governing parameters on the flow and heat transfer are discussed and presented through tables and graphs. The findings of the present investigation may be beneficial for the electronic industry in maintaining the electronic components under effectiveand safe operational conditions.

Keywords: heat transfer enhancement, hybrid metallic nanofluid, viscous dissipation and joule heating effect , Two dimensional flow

Procedia PDF Downloads 207
498 Enhanced Tensor Tomographic Reconstruction: Integrating Absorption, Refraction and Temporal Effects

Authors: Lukas Vierus, Thomas Schuster

Abstract:

A general framework is examined for dynamic tensor field tomography within an inhomogeneous medium characterized by refraction and absorption, treated as an inverse source problem concerning the associated transport equation. Guided by Fermat’s principle, the Riemannian metric within the specified domain is determined by the medium's refractive index. While considerable literature exists on the inverse problem of reconstructing a tensor field from its longitudinal ray transform within a static Euclidean environment, limited inversion formulas and algorithms are available for general Riemannian metrics and time-varying tensor fields. It is established that tensor field tomography, akin to an inverse source problem for a transport equation, persists in dynamic scenarios. Framing dynamic tensor tomography as an inverse source problem embodies a comprehensive perspective within this domain. Ensuring well-defined forward mappings necessitates establishing existence and uniqueness for the underlying transport equations. However, the bilinear forms of the associated weak formulations fail to meet the coercivity condition. Consequently, recourse to viscosity solutions is taken, demonstrating their unique existence within suitable Sobolev spaces (in the static case) and Sobolev-Bochner spaces (in the dynamic case), under a specific assumption restricting variations in the refractive index. Notably, the adjoint problem can also be reformulated as a transport equation, with analogous results regarding uniqueness. Analytical solutions are expressed as integrals over geodesics, facilitating more efficient evaluation of forward and adjoint operators compared to solving partial differential equations. Certainly, here's the revised sentence in English: Numerical experiments are conducted using a Nesterov-accelerated Landweber method, encompassing various fields, absorption coefficients, and refractive indices, thereby illustrating the enhanced reconstruction achieved through this holistic modeling approach.

Keywords: attenuated refractive dynamic ray transform of tensor fields, geodesics, transport equation, viscosity solutions

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497 Application of Compressed Sensing Method for Compression of Quantum Data

Authors: M. Kowalski, M. Życzkowski, M. Karol

Abstract:

Current quantum key distribution systems (QKD) offer low bit rate of up to single MHz. Compared to conventional optical fiber links with multiple GHz bitrates, parameters of recent QKD systems are significantly lower. In the article we present the conception of application of the Compressed Sensing method for compression of quantum information. The compression methodology as well as the signal reconstruction method and initial results of improving the throughput of quantum information link are presented.

Keywords: quantum key distribution systems, fiber optic system, compressed sensing

Procedia PDF Downloads 662
496 Modern Machine Learning Conniptions for Automatic Speech Recognition

Authors: S. Jagadeesh Kumar

Abstract:

This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

Procedia PDF Downloads 418
495 Free Fibular Flaps in Management of Sternal Dehiscence

Authors: H. N. Alyaseen, S. E. Alalawi, T. Cordoba, É. Delisle, C. Cordoba, A. Odobescu

Abstract:

Sternal dehiscence is defined as the persistent separation of sternal bones that are often complicated with mediastinitis. Etiologies that lead to sternal dehiscence vary, with cardiovascular and thoracic surgeries being the most common. Early diagnosis in susceptible patients is crucial to the management of such cases, as they are associated with high mortality rates. A recent meta-analysis of more than four hundred thousand patients concluded that deep sternal wound infections were the leading cause of mortality and morbidity in patients undergoing cardiac procedures. Long-term complications associated with sternal dehiscence include increased hospitalizations, cardiac infarctions, and renal and respiratory failures. Numerous osteosynthesis methods have been described in the literature. Surgical materials offer enough rigidity to support the sternum and can be flexible enough to allow physiological breathing movements of the chest; however, these materials fall short when managing patients with extensive bone loss, osteopenia, or general poor bone quality, for such cases, flaps offer a better closure system. Early utilization of flaps yields better survival rates compared to delayed closure or to patients treated with sternal rewiring and closed drainage. The utilization of pectoralis major flaps, rectus abdominus, and latissimus muscle flaps have all been described in the literature as great alternatives. Flap selection depends on a variety of factors, mainly the size of the sternal defect, infection, and the availability of local tissues. Free fibular flaps are commonly harvested flaps utilized in reconstruction around the body. In cases regarding sternal reconstruction with free fibular flaps, the literature exclusively discussed the flap applied vertically to the chest wall. We present a different technique applying the free fibular triple barrel flap oriented in a transverse manner, in parallel to the ribs. In our experience, this method could have enhanced results and improved prognosis as it contributes to the normal circumferential shape of the chest wall.

Keywords: sternal dehiscence, management, free fibular flaps, novel surgical techniques

Procedia PDF Downloads 74
494 VANETs Geographic Routing Protocols: A survey

Authors: Ramin Karimi

Abstract:

One of common highly mobile wireless ad hoc networks is Vehicular Ad Hoc Networks. Hence routing in vehicular ad hoc network (VANET) has attracted much attention during the last few years. VANET is characterized by its high mobility of nodes and specific topology patterns. Moreover these networks encounter a significant loss rate and a very short duration of communication. In vehicular ad hoc networks, one of challenging is routing of data due to high speed mobility and changing topology of vehicles. Geographic routing protocols are becoming popular due to advancement and availability of GPS devices. Delay Tolerant Networks (DTNs) are a class of networks that enable communication where connectivity issues like sparse connectivity, intermittent connectivity; high latency, long delay, high error rates, asymmetric data rate, and even no end-to-end connectivity exist. In this paper, we review the existing Geographic Routing Protocols for VANETs and also provide a qualitative comparison of them.

Keywords: vehicular ad hoc networks, mobility, geographic routing, delay tolerant networks

Procedia PDF Downloads 488
493 A Study of Anthropometric Correlation between Upper and Lower Limb Dimensions in Sudanese Population

Authors: Altayeb Abdalla Ahmed

Abstract:

Skeletal phenotype is a product of a balanced interaction between genetics and environmental factors throughout different life stages. Therefore, interlimb proportions are variable between populations. Although interlimb proportion indices have been used in anthropology in assessing the influence of various environmental factors on limbs, an extensive literature review revealed that there is a paucity of published research assessing interlimb part correlations and possibility of reconstruction. Hence, this study aims to assess the relationships between upper and lower limb parts and develop regression formulae to reconstruct the parts from one another. The left upper arm length, ulnar length, wrist breadth, hand length, hand breadth, tibial length, bimalleolar breadth, foot length, and foot breadth of 376 right-handed subjects, comprising 187 males and 189 females (aged 25-35 years), were measured. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then sex-specific simple and multiple linear regression models were used to estimate upper limb parts from lower limb parts and vice-versa. The results of this study indicated significant sexual dimorphism for all variables. The results indicated a significant correlation between the upper and lower limbs parts (p < 0.01). Linear and multiple (stepwise) regression equations were developed to reconstruct the limb parts in the presence of a single or multiple dimension(s) from the other limb. Multiple stepwise regression equations generated better reconstructions than simple equations. These results are significant in forensics as it can aid in identification of multiple isolated limb parts particularly during mass disasters and criminal dismemberment. Although a DNA analysis is the most reliable tool for identification, its usage has multiple limitations in undeveloped countries, e.g., cost, facility availability, and trained personnel. Furthermore, it has important implication in plastic and orthopedic reconstructive surgeries. This study is the only reported study assessing the correlation and prediction capabilities between many of the upper and lower dimensions. The present study demonstrates a significant correlation between the interlimb parts in both sexes, which indicates a possibility to reconstruction using regression equations.

Keywords: anthropometry, correlation, limb, Sudanese

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492 Recognition of Tifinagh Characters with Missing Parts Using Neural Network

Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

Abstract:

In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

Procedia PDF Downloads 309
491 Inverse Problem Method for Microwave Intrabody Medical Imaging

Authors: J. Chamorro-Servent, S. Tassani, M. A. Gonzalez-Ballester, L. J. Roca, J. Romeu, O. Camara

Abstract:

Electromagnetic and microwave imaging (MWI) have been used in medical imaging in the last years, being the most common applications of breast cancer and stroke detection or monitoring. In those applications, the subject or zone to observe is surrounded by a number of antennas, and the Nyquist criterium can be satisfied. Additionally, the space between the antennas (transmitting and receiving the electromagnetic fields) and the zone to study can be prepared in a homogeneous scenario. However, this may differ in other cases as could be intracardiac catheters, stomach monitoring devices, pelvic organ systems, liver ablation monitoring devices, or uterine fibroids’ ablation systems. In this work, we analyzed different MWI algorithms to find the most suitable method for dealing with an intrabody scenario. Due to the space limitations usually confronted on those applications, the device would have a cylindrical configuration of a maximum of eight transmitters and eight receiver antennas. This together with the positioning of the supposed device inside a body tract impose additional constraints in order to choose a reconstruction method; for instance, it inhabitants the use of well-known algorithms such as filtered backpropagation for diffraction tomography (due to the unusual configuration with probes enclosed by the imaging region). Finally, the difficulty of simulating a realistic non-homogeneous background inside the body (due to the incomplete knowledge of the dielectric properties of other tissues between the antennas’ position and the zone to observe), also prevents the use of Born and Rytov algorithms due to their limitations with a heterogeneous background. Instead, we decided to use a time-reversed algorithm (mostly used in geophysics) due to its characteristics of ignoring heterogeneities in the background medium, and of focusing its generated field onto the scatters. Therefore, a 2D time-reversed finite difference time domain was developed based on the time-reversed approach for microwave breast cancer detection. Simultaneously an in-silico testbed was also developed to compare ground-truth dielectric properties with corresponding microwave imaging reconstruction. Forward and inverse problems were computed varying: the frequency used related to a small zone to observe (7, 7.5 and 8 GHz); a small polyp diameter (5, 7 and 10 mm); two polyp positions with respect to the closest antenna (aligned or disaligned); and the (transmitters-to-receivers) antenna combination used for the reconstruction (1-1, 8-1, 8-8 or 8-3). Results indicate that when using the existent time-reversed method for breast cancer here for the different combinations of transmitters and receivers, we found false positives due to the high degrees of freedom and unusual configuration (and the possible violation of Nyquist criterium). Those false positives founded in 8-1 and 8-8 combinations, highly reduced with the 1-1 and 8-3 combination, being the 8-3 configuration de most suitable (three neighboring receivers at each time). The 8-3 configuration creates a region-of-interest reduced problem, decreasing the ill-posedness of the inverse problem. To conclude, the proposed algorithm solves the main limitations of the described intrabody application, successfully detecting the angular position of targets inside the body tract.

Keywords: FDTD, time-reversed, medical imaging, microwave imaging

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490 Last ca 2500 Yr History of the Harmful Algal Blooms in South China Reconstructed on Organic-Walled Dinoflagellate Cysts

Authors: Anastasia Poliakova

Abstract:

Harmful algal bloom (HAB) is a known negative phenomenon that is caused both by natural factors and anthropogenic influence. HABs can result in a series of deleterious effects, such as beach fouling, paralytic shellfish poisoning, mass mortality of marine species, and a threat to human health, especially if toxins pollute drinking water or occur nearby public resorts. In South China, the problem of HABs has an ultimately important meaning. For this study, we used a 1.5 m sediment core LAX-2018-2 collected in 2018 from the Zhanjiang Mangrove National Nature Reserve (109°03´E, 20°30´N), Guangdong Province, South China. High-resolution coastal environment reconstruction with a specific focus on the HABs history during the last ca 2500 yrs was attempted. Age control was performed with five radiocarbon dates obtained from benthic foraminifera. A total number of 71 dinoflagellate cyst types was recorded. The most common types found consistently throughout the sediment sequence were autotrophic Spiniferites spp., Spiniferites hyperacanthus and S. mirabilis, S. ramosus, Operculodinium centrocarpum sensu Wall and Dale 1966, Polysphaeridium zoharyi, and heterotrophic Brigantedinium ssp., cyst of Gymnodinium catenatum and cysts mixture of Protoperidinium. Three local dinoflagellate zones LAX-1 to LAX-3 were established based on the results of the constrained cluster analysis and data ordination; additionally, the middle zone LAX-2 was derived into two subzones, LAX-2a and LAX-2b based on the dynamics of toxic and heterotrophic cysts as well as on the significant changes (probability, P=0.89) in percentages of eutrophic indicators. The total cyst count varied from 106 to 410 dinocysts per slide, with 177 cyst types on average. Dinocyst assemblages are characterized by high values of the dost-depositional degradation index (kt) that varies between 3.6 and 7.6 (averaging 5.4), which is relatively high and is very typical for the areas with selective dinoflagellate cyst preservation that is related to bottom-water oxygen concentrations.

Keywords: reconstruction of palaeoenvironment, harmful algal blooms, anthropogenic influence on coastal zones, South China Sea

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489 Traditional and New Residential Architecture in the Approach of Sustainability in the Countryside after the Earthquake

Authors: Zeynep Tanriverdi̇

Abstract:

Sustainable architecture is a design approach that provides healthy, comfortable, safe, clean space production as well as utilizes minimum resources for efficient and economical use of natural resources and energy. Traditional houses located in rural areas are sustainable structures built at the design and implementation stage in accordance with the climatic environmental data of the region and also effectively using natural energy resources. The fact that these structures are located in an earthquake geography like Türkiye brings their earthquake resistance to the agenda. Since the construction of these structures, which contain the architectural and technological cultural knowledge of the past, is shaped according to the characteristics of the regions where they are located, their resistance to earthquakes also differs. Analyses in rural areas after the earthquake show that there are light-damaged structures that can survive, severely damaged structures, and completely destroyed structures. In this regard, experts can implement repair, consolidation, and reconstruction applications, respectively. While simple repair interventions are carried out in accordance with the original data in traditional houses that have shown great resistance to earthquakes, reinforcement work blended with new technologies can be applied in damaged structures. In reconstruction work, a wide variety of applications can be seen with the possibilities of modern technologies. In rural areas experiencing earthquakes around the world, there are experimental new housing applications that are renewable, environmentally friendly, and sustainable with modern construction techniques in the light of scientific data. With these new residences, it is aimed to create earthquake-resistant, economical, healthy, and pain-relieving therapy spaces for people whose daily lives have been interrupted by disasters. In this study, the preservation of high earthquake-prone rural areas will be discussed through the knowledge transfer of traditional architecture and also permanent housing practices using new sustainable technologies to improve the area. In this way, it will be possible to keep losses to a minimum with sustainable, reliable applications prepared for the worst aspects of the disaster situation and to establish a link between the knowledge of the past and the new technologies of the future.

Keywords: sustainability, conservation, traditional construction systems and materials, new technologies, earthquake resistance

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488 Deep Learning for SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 45
487 Deep Learning Based Polarimetric SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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486 Research on the Landscape Reconstruction of Old Industrial Plant Area from the Perspective of Communication Studies

Authors: Minghao Liu

Abstract:

This paper uses the theory of communication in the context of mass communication, from the construction of communication symbols, communication flow organization, communication experience perception of the three levels of the old industrial factory landscape transformation research and analysis, summarizes the old industrial factory landscape in the communication process to create strategies and design methods for the old industrial factories carried by the urban culture of how to enter the public's life more widely in the existing environment and be familiar with the significance of the exploration, to provide a new idea for the renewal of the urban stock, and ultimately to achieve the sustainable development of the city.

Keywords: communication, old industrial factor, urban renewal, landscape design

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485 Renovation of Dilapidated Areas and Sustainable Reconstruction of Various Parts of Tehran, Iran

Authors: Alireza Rahpeyma

Abstract:

One of the most significant challenges faced by cities is inefficient and deteriorated urban fabric. Deteriorated areas bring about numerous issues, including economic, social, physical, and infrastructural problems, sewage management, environmental concerns, and security issues. One of the crucial necessities of modern urban life is the revitalization and renovation of these urban fabrics. Another important aspect is preserving a cohesive cultural and social identity during the urban renewal process. Urban renovation and upgrading are not a one-time occurrence but rather an ongoing process that ultimately needs to become ingrained in the system. This process is not swift; it involves sensitive and intricate stages that require well-designed plans within short, medium, and long-term timeframes. To revitalize dilapidated areas, a comprehensive understanding of the urban region's sustainability is essential. The goal of this study is to provide a suitable model for the upgrading and renewal of areas 2, 4, 5, 7, 8, and 10 in Tehran, preserving the heritage within these urban fabrics (urban assets), including the valuable morphologies of these areas, to prevent financial wastage. This study was conducted descriptively and analytically using the SWOT technique and GIS software. The research results regarding urban upgrading and renewal bring about the following points: 1) Urban upgrading and renewal ensure satisfactory efficiency, justice, environmental quality, safety and security, hygiene, sewage management, and the comfort and aesthetics of urban spaces. 2) Employing the above processes in old city centers re-establishes the historical and cultural connection between people and their past, a past that is evolving and improving and will not repeat itself. 3) Despite the expansion and growth of Iranian cities, cultural and national identity can be preserved by adhering to healthy urban revitalization principles. 4) Proper urban upgrading and renewal prevent social fragmentation, deviant behavioral patterns, psychological and occupational disorders, and financial losses. In general, preserving the identity and urban life in renovation and upgrading must be comprehensive, encompassing various dimensions, including physical, social, economic, political, and administrative aspects.

Keywords: dilapidated areas, renovation, sustainable reconstruction, Tehran-Iran

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484 Quality of Life after Damage Control Laparotomy for Trauma

Authors: Noman Shahzad, Amyn Pardhan, Hasnain Zafar

Abstract:

Introduction: Though short term survival advantage of damage control laparotomy in management of critically ill trauma patients is established, there is little known about the long-term quality of life of these patients. Facial closure rate after damage control laparotomy is reported to be 20-70 percent. Abdominal wall reconstruction in those who failed to achieve facial closure is challenging and can potentially affect quality of life of these patients. Methodology: We conducted retrospective matched cohort study. Adult patients who underwent damage control laparotomy from Jan 2007 till Jun 2013 were identified through medical record. Patients who had concomitant disabling brain injury or limb injuries requiring amputation were excluded. Age, gender and presentation time matched non exposure group of patients who underwent laparotomy for trauma but no damage control were identified for each damage control laparotomy patient. Quality of life assessment was done via telephonic interview at least one year after the operation, using Urdu version of EuroQol Group Quality of Life (QOL) questionnaire EQ5D after permission. Wilcoxon signed rank test was used to compare QOL scores and McNemar test was used to compare individual parameters of QOL questionnaire. Study was approved by institutional ethical review committee. Results: Out of 32 patients who underwent damage control laparotomy during study period, 20 fulfilled the selection criteria for which 20 matched controls were selected. Median age of patients (IQ Range) was 33 (26-40) years. Facial closure rate in damage control laparotomy group was 40% (8/20). One third of those who did not achieve facial closure (4/12) underwent abdominal wall reconstruction. Self-reported QOL score of damage control laparotomy patients was significantly worse than non-damage control group (p = 0.032). There was no statistically significant difference in two groups regarding individual QOL measures. Significantly, more patients in damage control group were requiring use of abdominal binder, and more patients in damage control group had to either change their job or had limitations in continuing previous job. Our study was not adequately powered to detect factors responsible for worse QOL in damage control group. Conclusion: Quality of life of damage control patients is worse than their age and gender matched patients who underwent trauma laparotomy but not damage control. Adequately powered studies need to be conducted to explore factors responsible for this finding for potential improvement.

Keywords: damage control laparotomy, laparostomy, quality of life

Procedia PDF Downloads 250
483 Land Use Change Detection Using Remote Sensing and GIS

Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

Abstract:

In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: Haraz basin, change detection, land-use, satellite data

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482 Analyzing Social and Political Constraints in Development Aid Projects in Post Conflict Region of SWAT, Pakistan

Authors: Faizan Sultan

Abstract:

Non-government organizations (NGOs) in Pakistan have the potential to deliver services such as health, education, and rural development through targeting the most vulnerable communities of society. Having this significant importance, NGOs are facing numerous challenges in service delivery. So, there is a need to identify the challenges NGOs face in community development, particularly post-conflict development. The current study has analyzed the social and political constraints in development projects in the post-conflict region of the Swat district of Khyber Pakhtunkhwa. The objectives of this study are “What are the social and political constraints faced by the nongovernmental organizations in the implementation of development aid Projects in post-conflict development of Swat and to examine the challenges in coordination mechanism between government departments, NGOs, and community in reconstruction activities”. This research is based upon both the quantitative and qualitative data that is being gathered from the NGO representatives, government officials, and community members who were involved in post-conflict development interventions in the Swat region. A purposive sampling technique was used to select respondents from the community members/activists (25 in number) and government and NGO officials (10 in number). Based on analysis against our objectives, NGOs have faced numerous constraints such as Insecurity, Negative Perceptions about NGOs, restrictions on women's mobility, government policies and regulations, lack of coordination and networking, trust deficit, and political interference while implementing their project interventions. These findings concluded that constraints have affected project implementation to a greater extent, including women's participation, involvement of marginalized populations, and equal distribution of resources. In the Swat region, NGOs cannot openly discuss sensitive projects such as human rights, gender-based projects, or women empowerment as these issues are very sensitive to the local community due to their cultural values. The community may not allow their females to go outside their homes as this region is a male-dominated society. Similarly, lack of communication and poor networking for the arrangements of the project meetings were also the major constraints.

Keywords: national disaster management authority, millennium development goals, provincial disaster management authority, provincial reconstruction, rehabilitation and settlement authority

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481 Educaton for Social Reconstruction: Impact of Social Terrorism on Women Education in Nigeria

Authors: Theresa Chinyere ONU

Abstract:

This paper examines the effect of social terrorism on education in Nigeria. The article looked into some prevailing conditions of international political unrest and insecurity. The fear and risk of these conditions to national security and the struggle for power establishment which has further intensified and taken the shape of terrorism has imposed devastating effects on the growth and prosperity of Nigeria; as traffic patterns get disturbed, hospitals and schools get dysfunctional. This has also affected the educational standard in Nigeria as parents are no longer comfortable in sending their children to schools in some states for the fear of terrorist attacks. The study emphasized the integrated the effort of the government management institutions.

Keywords: education, social terrorism, women, Nigeria

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480 Underwater Image Enhancement and Reconstruction Using CNN and the MultiUNet Model

Authors: Snehal G. Teli, R. J. Shelke

Abstract:

CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.

Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images

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479 Margin-Based Feed-Forward Neural Network Classifiers

Authors: Xiaohan Bookman, Xiaoyan Zhu

Abstract:

Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

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478 FlexPoints: Efficient Algorithm for Detection of Electrocardiogram Characteristic Points

Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

Abstract:

The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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477 An Accurate Method for Phylogeny Tree Reconstruction Based on a Modified Wild Dog Algorithm

Authors: Essam Al Daoud

Abstract:

This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: least square, neighbor joining, phylogenetic tree, wild dog pack

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476 Sparsity-Based Unsupervised Unmixing of Hyperspectral Imaging Data Using Basis Pursuit

Authors: Ahmed Elrewainy

Abstract:

Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l1-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l1-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets

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475 Over the Air Programming Method for Learning Wireless Sensor Networks

Authors: K. Sangeeth, P. Rekha, P. Preeja, P. Divya, R. Arya, R. Maneesha

Abstract:

Wireless sensor networks (WSN) are small or tiny devices that consists of different sensors to sense physical parameters like air pressure, temperature, vibrations, movement etc., process these data and sends it to the central data center to take decisions. The WSN domain, has wide range of applications such as monitoring and detecting natural hazards like landslides, forest fire, avalanche, flood monitoring and also in healthcare applications. With such different applications, it is being taught in undergraduate/post graduate level in many universities under department of computer science. But the cost and infrastructure required to purchase WSN nodes for having the students getting hands on expertise on these devices is expensive. This paper gives overview about the remote triggered lab that consists of more than 100 WSN nodes that helps the students to remotely login from anywhere in the world using the World Wide Web, configure the nodes and learn the WSN concepts in intuitive way. It proposes new way called over the air programming (OTAP) and its internals that program the 100 nodes simultaneously and view the results without the nodes being physical connected to the computer system, thereby allowing for sparse deployment.

Keywords: WSN, over the air programming, virtual lab, AT45DB

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474 Building Scalable and Accurate Hybrid Kernel Mapping Recommender

Authors: Hina Iqbal, Mustansar Ali Ghazanfar, Sandor Szedmak

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Recommender systems uses artificial intelligence practices for filtering obscure information and can predict if a user likes a specified item. Kernel mapping Recommender systems have been proposed which are accurate and state-of-the-art algorithms and resolve recommender system’s design objectives such as; long tail, cold-start, and sparsity. The aim of research is to propose hybrid framework that can efficiently integrate different versions— namely item-based and user-based KMR— of KMR algorithm. We have proposed various heuristic algorithms that integrate different versions of KMR (into a unified framework) resulting in improved accuracy and elimination of problems associated with conventional recommender system. We have tested our system on publically available movies dataset and benchmark with KMR. The results (in terms of accuracy, precision, recall, F1 measure and ROC metrics) reveal that the proposed algorithm is quite accurate especially under cold-start and sparse scenarios.

Keywords: Kernel Mapping Recommender Systems, hybrid recommender systems, cold start, sparsity, long tail

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473 Reconsidering the Palaeo-Environmental Reconstruction of the Wet Zone of Sri Lanka: A Zooarchaeological Perspective

Authors: Kelum N. Manamendra-Arachchi, Kalangi Rodrigo

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Bones, teeth, and shells have been acknowledged over the last two centuries as evidence of chronology, Palaeo-environment, and human activity. Faunal traces are valid evidence of past situations because they have properties that have not changed over long periods of time. Sri Lanka has been known as an Island, which has a diverse variation of prehistoric occupation among ecological zones. Defining the Paleoecology of the past societies has been an archaeological thought developed in the 1960s. It is mainly concerned with the reconstruction from available geological and biological evidence of past biota, populations, communities, landscapes, environments, and ecosystems. Sri Lanka has dealt with this subject and considerable research has been already undertaken. The fossil and material record of Sri Lanka’s Wet Zone tropical forests continues from c. 38,000–34,000 ybp. This early and persistent human fossil, technical, and cultural florescence, as well as a collection of well-preserved tropical-forest rock shelters with associated ' on-site ' Palaeoenvironmental records, makes Sri Lanka a central and unusual case study to determine the extent and strength of early human tropical forest encounters. Excavations carried out in prehistoric caves in the low country wet zone has shown that in the last 50,000 years, the temperature in the lowland rainforests has not exceeded 5 degrees. Based on Semnopithecus Priam (Gray Langur) remains unearned from wet zone prehistoric caves, it has been argued that periods of momentous climate changes during the LGM and Terminal Pleistocene/Early Holocene boundary, with a recognizable preference for semi-open ‘Intermediate’ rainforest or edges. Continuous Genus Acavus and Oligospira occupation along with uninterrupted horizontal pervasive of Canarium sp. (‘kekuna’ nut) have proven that temperatures in the lowland rain forests have not changed by at least 5 oC over the last 50,000 years. Site Catchment or Territorial analysis cannot be no longer defensible, due to time-distance based factors as well as optimal foraging theory failed as a consequences of prehistoric people were aware of the decrease in cost-benefit ratio and located sites, and generally played out a settlement strategy that minimized the ratio of energy expanded to energy produced.

Keywords: palaeo-environment, prehistory, palaeo-ecology, zooarchaeology

Procedia PDF Downloads 101