bluuebunny/crossref_metadata_2025 huggingface dataset:
ANALISIS SISTEM INFORMASI AKUNTANSI PENERIMAAN DAN PENGELUARAN KAS PADA RSIA “ KASIH SAYANG IBU-BATAM”
Authors: Ompusunggu Hermaya
Published: August 2020

Artikel ini menganalisis bagaimana penerapan, efektivitas dan efisiensi Sistem Informasi Akuntansi (SIA) Penerimaan dan Pengeluaran Kas pada RSIA “Kasih Sayang Ibu-Batam”. Jenis dan pendekatan dalam penelitian ini deskriptif kualitatif dengan menggunakan data primer dan sekunder. Tehnik pengumpulan datanya dengan observasi yaitu wawancara dan dokumentasi serta studi kepustakaan. Tehnik analisis datanya menggunakan tehnik deskriptif dengan uji kredibilitas data menggunakan triangulasi. Tehnik pengambilan sampel dengan metode snowball. Variabel operasional pada penelitian ini meliputi: Sistem Informasi Akuntansi Penerimaan dan Sistem Informasi Akuntansi Pengeluaran Kas pada RSIA “Kasih Sayang Ibu-Batam”. Hasil penelitian menunjukkan bahwa penerapan Sistem Informasi Akuntansi (SIA) Penerimaan dan Pengeluaran Kas pada RSIA “Kasih Sayang Ibu-Batam” sudah efektif dan efisien. Tetapi perlu disempurnakan lagi jaringan yang membentuk sistem informasi akuntansi pada RSIA “Kasih Sayang Ibu-Batam” dengan dilakukannya penambahan beberapa fungsi/ bagian di struktur organisasinya serta membentuk tim pengawasan internal (tim auditor) guna melakukan audit baik secara berkala maupun insidental untuk pencegahan, koreksi dan penanggulangan masalah perusahaan untuk menyempurnakan jaringan sistem dan meningkatkan pelayanan kesehatan terhadap masyarakat (customer) pada RSIA “Kasih Sayang Ibu-Batam”. Serta perlu diadakannya kebijakan penggunaan cek atas nama perusahaan client/ supplier yang bekerjasama dengan RSIA “Kasih Sayang Ibu-Batam” dalam transaksi baik penerimaan maupun pengeluaran kas yang bernilai besar selain pemindahbukuan supaya lebih aman sehingga penggunaan uang tunai untuk transaksi yang bernilai besar seharusnya ditiadakan untuk menghindari resiko perusahaan.
VENTRICULAR SEPTAL DEFECT WITH SEVERE AORTIC REGURGITATION, SUB AORTIC STENOSIS, AORTIC AND PULMONARY ROOTS DILATION IN AN ADULT: A CASE REPORT
Authors: Nadeem Deebaj , Mueed Abdul , Akhtar Parveen
Published: August 2020

A case of 30 years’ male, a farmer by occupation who was a diagnosed case of a ventricular septal defect (VSD) since the age of seven, but refused for surgical closure back then, came in the emergency room (ER) with decompensated congestive cardiac failure and peripheral edema. After initial stabilization, he underwent transthoracic echocardiography (TTE) that showed small perimembranous VSD with the left to right shunt, a subaortic membrane with severe left ventricular outflow tract (LVOT) obstruction and moderate aortic and mitral regurgitation. TTE was followed by Computed Tomography (CT) thoracic aortogram that revealed small VSD with significant aortic regurgitation (AR). Subaortic membrane, aneurysmal dilated aortic root and ascending aorta and aneurysmal dilated pulmonary arteries. Cardiac surgeons were taken onboard and advised for VSD closure with aortic valve replacement, subaortic membrane resection and aortic root replacement. Patient and family were counseled regarding the procedure but refused again for surgical closure. Key Words: ​Ventricular Septal Defect, Aortic Regurgitation, Subaortic Membrane, Pulmonary Roots Dilation, Adult
SPECKLE TRACKING ECHOCARDIOGRAPHY:BASIC CONCEPTS AND CLINICAL APPLICATIONS
Authors: Hameed Imran
Published: August 2020

Assessment of the mechanical performance of heart usually means evaluation of left ventricular function and this can be done most easily by echocardiography by measuring ‘ejection fraction’. However, ejection fraction tells us the story of myocardium as a whole. Deeper understanding of cardiac mechanics has shown that this is a multi-layered phenomenon, as LV wall is composed of three layers of fibers. A deterioration in the function of one layer is compensated by others so the numerical value of ejection fraction is not compromised in the beginning. Speckles are produced due to ultrasound scattering and movement of these can be recorded by 2D imaging, frame to frame. This tracking of speckles is done in three directions viz. longitudinal, radial and circumferential, so that drop in global longitudinal strain is ascertained much before any change in ejection fraction is noted, “subclinical LV dysfunction”. In this review, the basics of speckle tracking, acquisition of echocardiographic data and the clinical applications of this new modality have been discussed. Key words: Echocardiography, Speckle tracking, Deformation, Sub-clinical LV dysfunction, Global longitudinal strain
OPEN HEART SURGERY AT A NEWLY DEVELOPED CARDIAC CENTER IN KARACHI: A STEP TOWARDS AFFORDABLE CARDIAC CARE IN PAKISTAN
Authors: Musharaf Muhammad , Ali Taimur Asif , Naeem Syed Saad , Jawad Muhammad , Salahuddin Urooj , Shirazi Zara , Karim Musa
Published: August 2020

Objective: To evaluate the outcomes and cost-effectiveness of cardiac surgery performed in a newly developed center providing affordable surgical care. Methods: This descriptive study was conducted at the Medicare Hospital Karachi, from January 2016 to October 2017. Patients undergoing open-heart surgery with cardiopulmonary bypass were enrolled, and those presenting with cardiogenic shock and off-pump cardiac surgeries were excluded. Data were prospectively collected on the designed questionnaire. Results: A 127 consecutive patients, predominantly male, 72%, with an overall median age of 58±15 years were identified. Ninety percent had CABG, 5.5% had MVR, 1.6% had AVR, 0.8% had CABG+MVR, and 1.6% had CABG+AVR. A majority, 50.4%, had 1+2+3 grafts. Sixty percent had a CPB time between 60-90 minutes and ventilation of less than six hours in 88% patients. Peri-operatively 97% of patients received transfusion, 2.4% developed renal dysfunction, 1.6% sepsis, 3.2% arrhythmia, and 71% received inotropes. In-hospital mortality was 1.8%, ICU stay >5 days and hospital stay >8 days was found each in 1.6% of patients respectively. Conclusion: We demonstrated impressive results compared with strong Western standards. Further comparative studies with greater sample size are required to assess the outcomes, survival, and cost-effectiveness in this region. Key words: Coronary artery bypass grafting (CABG), Outcomes, Cost-effectiveness
ASSESSING PACEMAKER PATIENTS' PERCEPTION OF LIFESTYLE: AFTER AN EDUCATIONAL INTERVENTION
Authors: Khaliq Ghulam Kubra , Rehan Fariha Hasan , Qadir Faisal , Mueed Abdul , Mumtaz Zubair , Irfan Ghazala , Shafquat Azam
Published: August 2020

Objectives: Misconceptions regarding various physical activities after pacemaker implantation can severely limit a patient's lifestyle and very little in terms of patient education has been done to correct it. This study; by means of both verbal, and provision of brochure for education of patients; at the time of discharge and then reinforcing by questioning again at subsequent visit, aims to correct it. Methodology: A Quasi- experimental design of study carried out on consecutive patients implanted permanent pacemaker at electrophysiology department NICVD Karachi. Patients were discharged with an educational brochure and practical application of various daily life activities after assessment of related knowledge at baseline with reassessment at 1st visit. A questionnaire of 25 daily activities was developed and tested. Patients perception of safety of various daily activities both at baseline and at 1 week follow up were noted along with socio- demographic data of the patient. Results: A total of128 patients were interviewed at baseline, out of which 115 showed up for follow-up after one week. Male patients were 59.4% (76) of the sample and 47.7% were illiterate. Mean age of the patient was 60.31 ± 12.81 years. Only 11/128 at baseline, and 59/115 after intervention, answered all questions correctly. The percentages at baseline and 1 week follow up for: driving (82% vs. 99.1%; p=0.005), climbing stairs (75% vs. 97.4%; p<0.001), sleeping on the side of pacemaker (60.2% vs. 91.3%; p=0.001), usage of mobile phone (28.1% vs. 96.5%; p<0.001), for electric iron (54.7% vs. 94.8%; p<0.001), electrical switches (16.4% vs. 96.5%; p<0.001), microwave ovens (54.7% vs. 84.3%; p<0.001), electrical sewing machines (58.6% vs. 93.0%; p=0.106), UPS and electricity generators (52.3% vs. 87.8%; p=0.003), electric motors (63.3% vs. 91.3%; p<0.001), undergoing X-Ray irradiation (68% vs. 96.5%; p<0.001), and ultrasound imaging (65.6% vs. 93.9%; p=0.005). Conclusion: Many pacemaker patients' misperception leading to unnecessarily restricted lifestyle can be corrected by simple measures such as distribution of brochures and in hospital implementation of those activities which can be resumed with in hospital stay thereby benefitting the patient more than just with implantation. Distribution of these brochures and counseling with practical application should therefore be standardized and made as part of routine for all pacemaker patients. Keywords: mobile phone usage 1, MRI scanning 2, patient education 3, permanent pacemaker 4.
Palavras ao vento: voz, corpo e melodrama no cinema sonoro
Authors: Ferro Rodrigues Felipe
Published: August 2020

Neste artigo nos debruçamos sobre o melodrama cinematográfico, tradicionalmente tido como modo de representação predominantemente visual, em que embates morais se manifestam em signos visíveis. Dentro da literatura que fundamenta a pesquisa no campo, diz-se que constitui um drama da mudez: a voz não oferece recursos suficientes para expressar adequadamente a emoção avassaladora. Essa definição, porém, torna-se frágil sob escrutínio mais cuidadoso no que tange às ideias de voz, corpo e logos. Informados por autores que versam sobre som e voz, propomos uma reformulação desse enunciado: libertando a voz do jugo da língua podemos verificar que ela persiste em sua materialidade mais natural, na forma de grito, choro, suspiro e canto. A limitação não seria, assim, da voz, mas da palavra, da capacidade da língua de expressar o inefável, e a voz corpórea, sonora, triunfaria sobre a fala, tornando o melodrama não um drama da falha da voz, mas da vitória do vocal sobre o verbal, do triunfo da voz sobre o logos.
Uma odisseia em nove atos: configurações estéticas e dimensões performáticas do álbum visual na cultura digital
Authors: Dalla Vecchia Leonam , Dos Santos Dornelles Wagner
Published: August 2020

O presente artigo tem como objetivo principal analisar o formato álbum visual, tendo como corpus empírico de observação a obra How Big, How Blue, How Beautiful, da banda britânica Florence + The Machine. Partindo-se do pressuposto de que as características estéticas do álbum visual são derivadas do cruzamento entre o álbum fonográfico, o videoclipe e as narrativas cinematográficas, o artigo empreenderá uma análise micro contextual do formato na cultura digital, procurando investigar as estratégias de mercado utilizadas na promoção da obra, bem como a sua dimensão estética e o seu impacto cultural no contemporâneo. A hipótese central deste trabalho é a de que o álbum visual materializa a convergência midiática entre os três produtos supramencionados, instaurando um modelo de fruição estética pautado pela específica linguagem audiovisual do formato.
Um vocalise nordestino na Amazônia: considerações sobre a Mãe D'água em Canticum Naturale, de Edino Krieger
Authors: Damaceno Julio Cesar , Piedade Acácio
Published: August 2020

Este trabalho apresenta a discussão de uma seção do poema sinfônico Canticum naturale (1972), de Edino Krieger (1928), a partir do conceito de intertextualidade e da teoria das tópicas. A referida seção consiste em um solo para voz feminina soprano em forma de vocalise que traz, dentro do contexto da peça, uma alusão programática ao canto do personagem folclórico da Mãe d’Água. Serão abordadas as relações intertextuais entre a peça de Krieger e exemplos diversos do repertório de concerto, como a tradição francesa de vocalises e peças programáticas que trazem representações sonoras das águas, tendo como ponto central o diálogo entre o vocalise presente em Canticum naturale e a peça Mãe d’Água (1969), de Guerra-Peixe (1914-1993). Acreditamos que uma perspectiva comparativa pode contribuir para uma melhor compreensão das estruturas e significados de Canticum naturale.
Estudos de contraponto e fuga de Carlos Gomes
Authors: Silva Paulo
Published: August 2020

Republicação do artigo da Revista Brasileira de Música, v. 3, n. 2, p. 168-176, nov. 1936.
Quarteto de cordas n.o 3, 1.o. mov. (primeira versão)
Authors: Nepomuceno Alberto
Published: August 2020

Partitura do Quarteto de cordas n.o 3, 1.o. mov. (primeira versão), de Alberto Nepomuceno.
Numerical Investigation of Heat and Mass Transfer Processes while the Desorption of Hydrogen Gas Stored in MmNi4.6Fe0.4-H6
Authors: Boukhari Ali
Published: August 2020

This work presents a numerical investigation of two-dimensional coupled heat and mass transfer processes in a unit disc of an annulus-disc reactor filled with the intermetallic (Mischmetal) compound MmNi4.6Fe0.4, during the hydrogen gas desorption using the finite volume method. Temperature and amount of desorbed hydrogen and their time-averaged quantities inside the metal hydride bed are presented for different heat transfer fluid temperatures, and different metal thermal conductivities. Impacts of both effects on the metal hydride reactor performance in terms of discharging time are examined by means of a set of numerical simulations. Thus, the dehydriding time minimization relates to the adjustment of the amount of heat addition to the packed bed reactor. A good agreement was found between the present computational results and the experimental data reported in the literature.
CFD simulation of natural convection and heat transfer in a flat solar thermal collector with fins on the glazing - horizontal case
Authors: Laaraba Adel
Published: August 2020

This study is based on a CFD simulation of a flat horizontal solar thermal collector containing fins on its inner face of the glazing. The walls of the solar collector with insulation are considered adiabatic and the rest of the walls are at constant different temperatures. The principal objective of this work is to study the effects of the number of fins that changed from 0 to 30, as well as their length varied from 0 to 0.8 on the air flow and heat transfer characteristics. It has been observed that the heat transfer rate is strongly affected by the number of fins and the length of the fins. The obtained result showed that the increase of the fins reduces the heat loss by convection by 54 %.
Economic Perspective in the Production of Copper Nanowire using Amino Acids as Capping Agent
Authors: Dewi Puspa Sari , Nandiyanto Asep Bayu Dani
Published: August 2020

The purpose of this study is to evaluate the economic feasibility of making copper nanowire using amino acids as a capping agent. The evaluation was conducted from two perspectives, namely engineering analysis and economic evaluation using parameters such as gross profit margin, payback period, breakeven points, and net present value. An economic evaluation was also carried out comparing the use of amino acids Glycine, Lysine, Proline, and Alanine to find out which amino acids were more profitable in the production of copper nanowire. Furthermore, the evaluation is done by estimating the ideal situation and several other state assumptions such as changes in raw material prices, labor costs, and also income tax. From the results of this study, Glycine is known as the most profitable amino acid to be used in this process. In addition, by using Glycine as an ideal condition, based on the results of the evaluation of all parameters, this project is classified as prospective to do. Although further studies must be carried out to develop this project, this study can be the basis for developing new methods of making copper nanowire on a large scale.
Enhancing of CH3NH3SnI3 based solar cell efficiency by ETL engineering
Authors: Hima Abdelkader
Published: August 2020

Solar cells based on organic-inorganic perovskites (PVK) are the subject of several researches in laboratories around the world. One of the most promising hybrid perovskite is the methylammonium lead tri-iodide MAPbI3 that is suitable for sun light harvesting. But the MAPbI3 is a toxic material, so in this paper is proposed another nature friendly candidate which is the methylammonium tin tri-iodide MASnI3. The proposed material is inserted into an n-i-p heterojunction solar cell which structure is electron transport layer (ETL)/PVK/hole transport layer (HTL). The used HTL is the PEDOT: PSS in combination with one of two ETLs which are the PCBM and the IGZO. Simulation efforts using 1D SCAPS was carried. It is found that IGZO ETL based solar cell yields a higher power conversion efficiency (PCE) compared with PCBM ETL based solar cell in the same thickness.
Studying sediment transport dynamics by using the Smart sphere
Authors: Alhusban Zaid
Published: August 2020

A new method is introduced by using high precision accelerometer and gyroscope micro-electromechanical sensors (MEMS), which can record Lagrangian observations of sediments and shed light into the dynamics of sediment transport processes at above threshold conditions. The sensor can be used under a range of well-controlled flow conditions and can record measurements at high frequency (200 Hz), which can be used at the field. The smart sphere performance was evaluated by comparing its rotation and acceleration readings from the sensors to the video recordings of both top and underwater high-speed camera for a range of flow rates and sphere densities. Furthermore, an initial attempt to compare the smart-sphere’s velocity is achieved, by transforming the particle’s velocity from the Lagrangian frame of reference, obtained from the inertial sensor, to its velocity at the Eularian frame, obtained from the top camera.
Relative importance analysis with multivariate models: Shifting the focus from independent variables to parameter estimates
Authors: Luchman Joseph N. , Lei Xue , Kaplan Seth
Published: August 2020

Conclusions regarding the relative importance of different independent variables in a statistical model have meaningful implications for theory and practice. However, methods for determining relative importance have yet to extend beyond statistical models with a single dependent variable and a limited set of multivariate models. To accommodate multivariate models, the current work proposes shifting away from the concept of independent variable relative importance toward that of parameter estimate relative importance (PERI). This paper illustrates the PERI approach by comparing it to the evaluation of regression slopes and independent variable relative importance (IVRI) statistics to show the interpretive and methodological advantages of the new concept and associated methods. PERI’s advantages above standardized slopes stem from the same fit metric that is used to compute PERI statistics; this makes them more comparable to one another than standardized slopes. PERI’s advantages over IVRI stem from situations where independent variables do not predict all dependent variables; hence, PERI permits importance determination in situations where independent variables are nested in dependent variables they predict. We also provide recommendations for implementing PERI using dominance analysis with statistical models that can be estimated with maximum likelihood estimation combined with a series of model constraints using two examples.
Safety-specific transformational leadership, safety climate and occupational accidents
Authors: Mirza Muhammad Zeeshan , Isha Ahmad Shahrul Nizam
Published: August 2020

Despite the fact that safety-specific transformational leadership had been reported to have favorable outcomes on workplace safety, there is limited work on identifying its role in decreasing occupational accidents at workplace. The current study looks to fill this void by proposing safety-specific leadership approach to combat occupational accidents via safety climate. Data were collected from 270 production workers of Oil and Gas Industry across four states of Malaysia. Results showed strong support for our suppositions. Safety climate mediated the relationship between safety-specific leadership and occupational accidents. The supposition linking safety-specific transformational leadership to safety climate and safety climate to occupational accidents also found considerable support. The results are discussed in the light of previous literature and the contributions made by the study.
Observations of sunlit N2+ aurora at high altitudes during the RENU2 flight
Authors: Ellingsen Pål Gunnar , Lorentzen Dag , Kenward David , Hecht Jams H. , Evans J. Scott , Sigernes Fred , Lessard Marc
Published: August 2020

Abstract. We present measurements of sunlit aurora during the launch of the Rocket Experiment for Neutral Upwelling 2 (RENU2) on the 13th of December 2015 at 07:34 UT. The in situ auroral conditions coincide with those of sunlit aurora, and were characterised by the 391.4 nm and 427.8 nm N2+ emissions. A correlation between several auroral wavelengths, as measured by a meridian scanning photometer was used to detect sunlit aurora and indirectly neutral upwelling. These results, based on ground data, agree well with the RENU2 measurements recorded during its pass through the sunlit polar cusp. Using data from RENU2 and the solar photon flux, it was found that sunlit aurora was a major part (≈ 40 %) of the observed 427.8 nm emission.
Chemical characterization of Punta de Fuencaliente CO2 seeps system (La Palma Island, NE Atlantic Ocean): a new natural laboratory for ocean acidification studies
Authors: González-Delgado Sara , González-Santana David , Santana-Casiano Magdalena , González-Dávila Melchor , Hernández Celso A. , Sangil Carlos , Hernández José Carlos
Published: August 2020

Abstract. We present a new natural carbon dioxide (CO2) system located off the southern coast of La Palma Island (Canary Islands, Spain). Like others CO2 seeps, these seeps can be used as an analogue to study the effects of ocean acidification (OA) on the marine realm. With this aim, we present an accurate chemical characterization of the seeps system carbon emissions, describing the carbon system dynamics, by measuring pH, AT and CT, as well as, Ω aragonite and calcite. Our explorations on the area have found several emission points with similar chemical features. Here, the CO2 emission flux varies between 2.8 kg CO2 d−1 to 28 kg CO2 d−1, becoming a significant source of carbon. CO2 seeps are of volcanic origin and the alteration of local ocean chemistry is due to acid brackish water discharges. Although this kind of acidified system is not a perfect image of future oceans, this area of La Palma island is an exceptional spot to perform studies aimed to understand the effect of different levels of OA on the functioning of marine ecosystems. These studies can then be used to comprehend how life has persisted through past Eras, with higher atmospheric CO2, or to predict the consequences of present fossil fuel usage on the marine ecosystem of the future oceans.
THE INFLUENCE OF GROUND CONTROL POINTS CONFIGURATION AND CAMERA CALIBRATION FOR DTM AND ORTHOMOSAIC GENERATION USING IMAGERY OBTAINED FROM A LOW-COST UAV
Authors: Garcia M. V. Y. , Oliveira H. C.
Published: August 2020

Abstract. Technological improvement of Unmanned Aerial Vehicles (UAVs) and computer vision algorithms, such as Structured-from-Motion (SfM) and Multi-view Stereo (MVS) have provided the possibility for high-resolution mapping and high-density point cloud generation using low-cost equipment and sensors. Orthomosaics and Digital Terrain Model (DTM) are the main digital products considering mapping purposes. Their quality is directly related to the sensors boarded on the UAV and data processing. Ground Control Points (GCPs) are used in the process of indirect georeferencing and also to model the lens distortions. The number of GCPs used in this process affects the positional accuracy of the final products. This study aims to determine the optimum number of GCPs to achieve high accuracy orthomosaics and DTM. To obtain this optimum number, an area of 3.85 ha was mapped with a low-cost UAV DJI Phantom 4 Advanced at 31 m flying height, lateral and longitudinal overlap of 90% and 80%, respectively, and using 22 checkpoints for quality assessment. For the experiments, different configuration were used both for the number of GCPs and for the use of self-calibration process or pre-calibrated camera IOP (Interior Orientation Parameters). The results show that for the flight configuration used in this work and for the mentioned UAV, a total of 5 GCPs, with pre-calibrated camera IOP, yields an accuracy of 0.023 m for X, 0.031 m for Y and 0.033 m for Z.
ANALYSIS OF SYSTEMATIC ERRORS OF MOBILE LiDAR SYSTEMS: A SIMULATION APPROACH
Authors: Shahraji M. H. , Larouche C. , Cocard M.
Published: August 2020

Abstract. The systematic error analysis of the mobile LiDAR system (MLS) is always a challenging task in real-world situations. This challenge is mainly due to the mixture of systematic errors with non-systematic errors. To tackle this issue, in this paper, we introduce a conceptual model of an MLS simulator. The main advantage of the simulation-based approach is the full control over the erroneous systematic and non-systematic parameters that affect an MLS’s output. In the proposed simulation approach, we only take into account systematic errors that affect the simulated georeferenced point cloud. These systematic errors are as follows, POS-LiDAR boresight angles, POS-LiDAR leverarms, range offset, and scan angle offset. To simplify our analysis, we concentrate only on modeling the effects of systematic errors on planar targets and we focus solely on the terrestrial platform. Based on an independent analysis performed on each of the eight systematic errors of an MLS, to obtain strong visibility over systematic errors of an MLS, we suggest two planar targets of 1m x 1m dimensions with vertical and inclined orientations and a five-line pattern for MLS, two parallel and three side-looking passages. The proposed configuration generates an ideal input point cloud for the detection of systematic errors (except for the Z-Leverarm error) and ultimately it will lead to the proper input data for calibration of a terrestrial MLS. To validate our methodology, with an in-house assembled terrestrial MLS, we scanned a set of planar targets with three different orientations (vertical, inclined, and horizontal). This real-data validation test illustrated that with only two out of three planar targets (vertical and inclined) and with five out of six passages (two parallel to the planar targets and three side-looking passages), we will obtain expected visibility over the systematic errors of a terrestrial MLS, which approves the results with the simulation data.
PRELIMINARY INVESTIGATION ON POSSIBILITY OF SUPER RESOLUTION OF UAV ORTHOIMAGES
Authors: Matsuoka R. , Fukue K.
Published: August 2020

Abstract. Since inspection of infrastructures using UAV images seems to be efficient, many systems for infrastructure maintenance using UAV images have been developed recently. For the purpose of more efficient image acquisition, we started an investigation on the possibility of super resolution (SR) of UAV images to obtain high-resolution (HR) orthoimages suitable for infrastructure maintenance. This paper reports an preliminary investigation using existing UAV images acquired for 3D measurement that were not be intended to be utilized for SR. We produced HR orthoimages by three SR methods: image interpolation of a single low-resolution (LR) image by cubic convolution, SR by resampling, and SR based on observation equations. Both SR by resampling and SR based on observation equations utilize multiple overlapping LR images. Results of the investigation demonstrate that SR based on observation equations using multiple overlapping images would be able to provide higher resolution orthoimages than those produced by an ordinary method. The results show that an inaccurate DSM utilized in SR processing degrades the quality of SR results as well. Furthermore, the results illustrate that the quality of the result of SR processing depends rather upon the characteristic of a lens utilized in image acquisition. We think that further investigations on SR using UAV images would be necessary in order to put SR to practical use.
MULTILATERATION UNDER FLIP AMBIGUITY FOR UAV POSITIONING USING ULTRAWIDE-BAND
Authors: Park K. , Kang J. , Arjmandi Z. , Shahbazi M. , Sohn G.
Published: August 2020

Abstract. Ultrawide-band (UWB) ranging technology and multilateration techniques have recently been emerging solutions for positioning unmanned aerial vehicles (UAVs) in GNSS-denied environments. This solution offers cm-level ranging accuracy and considerable robustness to multipath receptions. UWB modules are commonly used in an anchor-based configuration; i.e., one UWB tag is mounted on the UAV, and several UWB anchors are installed on the ground. In real-world operational conditions, anchors can form a planar or a near-planar surface. This causes a geometric ambiguity, called flip ambiguity, in position estimation. Flip ambiguity can lead to considerable errors in the estimated position by multilateration. In this paper, we present a multilateration approach, which automatically resolves the flip ambiguity for UAV-positioning using UWB ranging. The proposed multilateration method first computes an algebraic solution through recursive least squares. If the initially estimated position is found to be flipped, then it is corrected by a symmetric reflection with respect to the anchor plane. Finally, the estimated position is refined by non-linear optimization. Extensive experiments in a real environment show that the proposed algorithm can effectively tackle the issue of flip ambiguity in multilateration, leading to a significant improvement in positioning accuracy.
A COMPOSITE MODEL FOR REFLECTANCE AND POLARISATION OF LIGHT FROM GRANULATE MATERIALS
Authors: Peltoniemi J. I. , Gritsevich M. , Markkanen J. , Hakala T. , Suomalainen J. , Zubko N. , Wilkman O. , Muinonen K.
Published: August 2020

Abstract. Many natural land surfaces, such as sand or snow, consist of densely packed grains, often covered by dust, water droplets, contaminated with other materials such as possible oil leaks, hoar frost, and can also be internally cracked, porous, and heterogeneous. Most scattering models ignore these complications, but here a more detailed approach is taken to test all these effects. The current model is composed of three techniques: 1) Monte Carlo-based electromagnetic volume integral equation technique for non-spherical wavelength scale dust particles, 2) Monte Carlo ray tracing for stochastic-shaped grains much larger than the wavelength, with optional point scattering from dust cover, internal inclusions, and liquid surface layer, in a layer of an optical depths of few units, and 3) adding-doubling to combine smaller layers into an arbitrary, thick and vertically inhomogeneous medium. The model allows the medium to be built in a modular way, and after initialisation, rather complicated layered structures can be computed quickly and flexibly. The computed results are compared against experimental measurements of snow and sand. The model agrees with measurements usually within the measurement accuracy (∼ 0:05). The scattering is observed to depend significantly on grain size, shape, orientation, composition, fine structures, dust, and some other properties that need to be defined. Both, measurement and modelling, require much deeper attention to these properties.
ROBUST AND ACCURATE PLANE SEGMENTATION FROM POINT CLOUDS OF STRUCTURED SCENES
Authors: Hu P. , Liu Y. , Tian M. , Hou M.
Published: August 2020

Abstract. Plane segmentation from the point cloud is an important step in various types of geo-information related to human activities. In this paper, we present a new approach to accurate segment planar primitives simultaneously by transforming it into the best matching issue between the over-segmented super-voxels and the 3D plane models. The super-voxels and its adjacent topological graph are firstly derived from the input point cloud as over-segmented small patches. Such initial 3D plane models are then enriched by fitting centroids of randomly sampled super-voxels, and translating these grouped planar super-voxels by structured scene prior (e.g. orthogonality, parallelism), while the generated adjacent graph will be updated along with planar clustering. To achieve the final super-voxels to planes assignment problem, an energy minimization framework is constructed using the productions of candidate planes, initial super-voxels, and the improved adjacent graph, and optimized to segment multiple consistent planar surfaces in the scenes simultaneously. The proposed algorithms are implemented, and three types of point clouds differing in feature characteristics (e.g. point density, complexity) are mainly tested to validate the efficiency and effectiveness of our segmentation method.
GEOMETRY-BASED POINT CLOUD CLASSIFICATION USING HEIGHT DISTRIBUTIONS
Authors: Politz F. , Sester M. , Brenner C.
Published: August 2020

Abstract. Semantic segmentation is one of the main steps in the processing chain for Airborne Laser Scanning (ALS) point clouds, but it is also one of the most labour intensive steps, as it requires many labelled examples to train a classifier. National mapping agencies (NMAs) have to acquire nationwide ALS data every couple of years for their duties. Having point clouds cover different terrains such as flat or mountainous regions, a classifier often requires a refinement using additional data from those specific terrains. In this study, we present an algorithm, which is able to classify point clouds of similar terrain types without requiring any additional training data and which is still able to achieve overall F1-Scores of over 90% in most setups. Our algorithm uses up to two height distributions within a single cell in a rasterized point cloud. For each distribution, the empirical mean and standard deviation are calculated, which are the input for a Convolutional Neural Network (CNN) classifier. Consequently, our approach only requires the geometry of point clouds, which enables also the usage of the same network structure for point clouds from other sensor systems such as Dense Image Matching. Since the mean ground level varies with the observed area, we also examined five different normalisation methods for our input in order to reduce the ground influence on the point clouds and thus increase its transferability towards other datasets. We test our trained networks on four different tests sets with the classes’ ground, building, water, non-ground and bridge.
OBJECT DETECTION AND CLASSIFICATION FROM CLUTTERED LARGE-SCALE INDOOR SCENE VIA ANCHOR-BASED GRAPH
Authors: Su F. , Liang Y. , Gang Z. , Zuo X. , Yang F. , Zhu H. , Li L.
Published: August 2020

Abstract. Indoor object detection and classification from scanned point clouds has recently attracted considerable research interest. However, detecting and classifying objects with arbitrary upward orientation has emerged as a substantial challenge. This paper presents an anchor-based graph method via geometric and topological similarity among indoor objects. With this method, the misclassification that usually occurs in the objects placed non-vertical with the floor is overcome by extracting anchor in each graph via nodes’ geometric attribute and by matching graph via topological relationship between nodes and anchor, rather than the features along the upward orientation. A region growing-based method along the anchor’s upward orientation is proposed for classifying the unlabeled over-segmentation parts. Such an anchor-based method ensures both the accuracy of object classification and the geometric integrity of object. A series of experimental tests using three real-world 3D scans of indoor environments show the effectiveness and feasibility of the proposed method.
EXTRACTION OF ROAD-CROSSING POWER AND COMMUNICATION LINES FROM MOBILE MAPPING DATA
Authors: Tajima K. , Masuda H.
Published: August 2020

Abstract. In residential areas, maintenance of power and communication lines is an important issue. In recent years, the frequency and power of typhoons and storms have significantly increased. If utility poles incline due to strong winds, slack cables may contact with large vehicles. For automatically detecting loose road-crossing cables in wide areas, the MMS is very promising. However, when roadcrossing cables are measured using the MMS, large portions of points on cables may be lost, because the directions of laser beams are nearly parallel to the directions of road-crossing cables, and therefore, the laser beams cross road-crossing cables only a small number of times. In this paper, we propose a new method for reconstructing cables crossing roads. In our method, road-crossing cables are reconstructed using both point clouds and camera images. While point clouds of road-crossing cables may be partly missing, their camera images can be captured with little occlusion. Missing portions are recovered using lines extracted from camera images. First, points of each cable are extracted from a point cloud, and the 3D vertical plane on which the cable exists are calculated. From camera images, 2D line segments are extracted as candidates of cable lines. 2D line segments are projected onto the 3D vertical plane using the pinhole camera model. Finally, 3D cable lines are reconstructed on the 3D vertical plane from the merged points. In our experiments, road-crossing cables could be sufficiently extracted using our method.
AUTOMATIC EXTRACTION AND RECOGNITION OF ROAD MARKINGS BASED ON VEHICLE LASER POINT CLOUD
Authors: Yao L. , Qin C. , Chen Q. , Wu H. , Zhang S.
Published: August 2020

Abstract. At present, automatic driving technology has become one of the development direction of the future intelligent transportation system. The high high-precision map, which is an important supplement of the on on-board sensors under the condition of shielding or the restriction of observation distance, provides a priori information for high high-precision positioning and path planning of the automatic driving with the level of L3 and above. The position and semantic information of the road markings, such as the absolute coordinates of th e solid line and the bro ken line, are the basic components of the high high-precision map. At present, point cloud data are still one of the most important data source of the high high-precision map. So, how to get road markings information from original point clouds automatically deserve study. In this paper, point cloud is sliced by the mileage of the road, then each slice is projected onto respective vertical section section. Random Sample Consensus (RANSAC) algorithm is applied to establish road surface buffer area . Finally, moving window filtering is used to extract road surface point cloud from road surface buffer area area. On this basis, the road surface point cloud image is transformed into raster image with a certain resolution by using the method of inverse distance weighted interpolation , and the grid image is converted into binary image by using the method of adaptive threshold segmentation based on the integral graph. Then the method of the Euclidean clustering is used to extract the road markings point cloud from the binary image. Characteristic attribute detection is applied to recognize solid line marking from all clusters. Deep learning network framework pointnet++ is applied to recognize remain road markings including guideline, broken line, straight arrow, and right turn arrow.
FAST AND REGULARIZED RECONSTRUCTION OF BUILDING FAÇADES FROM STREET-VIEW IMAGES USING BINARY INTEGER PROGRAMMING
Authors: Hu H. , Wang L. , Zhang M. , Ding Y. , Zhu Q.
Published: August 2020

Abstract. Regularized arrangement of primitives on building façades to aligned locations and consistent sizes is important towards structured reconstruction of urban environment. Mixed integer linear programing was used to solve the problem, however, it is extremely time consuming even for state-of-the-art commercial solvers. Aiming to alleviate this issue, we cast the problem into binary integer programming, which omits the requirements for real value parameters and is more efficient to be solved. Firstly, the bounding boxes of the primitives are detected using the YOLOv3 architecture in real-time. Secondly, the coordinates of the upper left corners and the sizes of the bounding boxes are automatically clustered in a binary integer programming optimization, which jointly considers the geometric fitness, regularity and additional constraints; this step does not require a priori knowledge, such as the number of clusters or pre-defined grammars. Finally, the regularized bounding boxes can be directly used to guide the façade reconstruction in an interactive environment. Experimental evaluations have revealed that the accuracies for the extraction of primitives are above 0.82, which is sufficient for the following 3D reconstruction. The proposed approach only takes about 10% to 20% of the runtime than previous approach and reduces the diversity of the bounding boxes to about 20% to 50%.
DEEP CASCADED NEURAL NETWORKS FOR AUTOMATIC DETECTION OF STRUCTURAL DAMAGE AND CRACKS FROM IMAGES
Authors: Bai Y. , Zha B. , Sezen H. , Yilmaz A.
Published: August 2020

Abstract. In this paper, two different convolutional neural networks (CNNs) are applied on images for automated structural damage detection (SDD) in earthquake damaged structures and cracking localization (e.g., detection of cracks, their widths and distributions) at various scales, such as pixel level, object level, and structural level. The proposed method has two main steps: 1) diagnosis, and 2) localization of cracking or other damage. At first a residual CNN with transfer learning is employed to classify the damage in the structures and structural components. This step performs damage detection using two public datasets. The second step uses another CNN with U-Net structure to locate the cracking on low resolution images. The implementations using public and self-collected datasets show promising performance for a problem that had remained a challenge in the structure engineering field for a long time and indicate that the proposed approach can perform detection and localization of structural damage with an acceptable accuracy.
STOCKPILE MONITORING USING LINEAR SHAPE-FROM-SHADING ON PLANETSCOPE IMAGERY
Authors: d’Autume M. , Perry A. , Morel J.-M. , Meinhardt-Llopis E. , Facciolo G.
Published: August 2020

Abstract. The storage and management of stockpiles of materials is a fundamental process in large scale activities such as mining, civil engineering, and in the management of waste landfill sites. Following the evolution of stocks has always been important, and advancements in remote sensing technology are not only facilitating this, but also making it possible in near real-time. Nowadays, this monitoring appears to be performed almost exclusively using UAV based techniques. This paper proposes to apply a simple Shape-from-Shading method on low resolution satellite images provided by PlanetScope to monitor the evolution of the volume of stockpiles. The proposed Shape-from-Shading formulation makes it possible to handle occluding objects in the scene. The loss in accuracy due to the low resolution of PlanetScope images is well compensated by the daily revisit frequency and by the fact that spaceborne acquisitions require no human supervision. With satellites it is also easy to follow simultaneously several stocking sites all over the world. We test our method on two coal storage sites and demonstrate that the stockpiles are well detected.
BUILDING CHANGE DETECTION FROM BITEMPORAL AERIAL IMAGES USING DEEP LEARNING
Authors: Su S. , Nawata T. , Fuse T.
Published: August 2020

Abstract. Automatic building change detection has become a topical issue owing to its wide range of applications, such as updating building maps. However, accurate building change detection remains challenging, particularly in urban areas. Thus far, there has been limited research on the use of the outdated building map (the building map before the update, referred to herein as the old-map) to increase the accuracy of building change detection. This paper presents a novel deep-learning-based method for building change detection using bitemporal aerial images containing RGB bands, bitemporal digital surface models (DSMs), and an old-map. The aerial images have two types of spatial resolutions, 12.5 cm or 16 cm, and the cell size of the DSMs is 50 cm × 50 cm. The bitemporal aerial images, the height variations calculated using the differences between the bitemporal DSMs, and the old-map were fed into a network architecture to build an automatic building change detection model. The performance of the model was quantitatively and qualitatively evaluated for an urban area that covered approximately 10 km2 and contained over 21,000 buildings. The results indicate that it can detect the building changes with optimum accuracy as compared to other methods that use inputs such as i) bitemporal aerial images only, ii) bitemporal aerial images and bitemporal DSMs, and iii) bitemporal aerial images and an old-map. The proposed method achieved recall rates of 89.3%, 88.8%, and 99.5% for new, demolished, and other buildings, respectively. The results also demonstrate that the old-map is an effective data source for increasing building change detection accuracy.
BOUNDARY REGULARIZED BUILDING FOOTPRINT EXTRACTION FROM SATELLITE IMAGES USING DEEP NEURAL NETWORKS
Authors: Zhao K. , Kamran M. , Sohn G.
Published: August 2020

Abstract. In recent years, an ever-increasing number of remote satellites are orbiting the Earth which streams vast amount of visual data to support a wide range of civil, public and military applications. One of the key information obtained from satellite imagery is to produce and update spatial maps of built environment due to its wide coverage with high resolution data. However, reconstructing spatial maps from satellite imagery is not a trivial vision task as it requires reconstructing a scene or object with high-level representation such as primitives. For the last decade, significant advancement in object detection and representation using visual data has been achieved, but the primitive-based object representation still remains as a challenging vision task. Thus, a high-quality spatial map is mainly produced through complex labour-intensive processes. In this paper, we propose a novel deep neural network, which enables to jointly detect building instance and regularize noisy building boundary shapes from a single satellite imagery. The proposed deep learning method consists of a two-stage object detection network to produce region of interest (RoI) features and a building boundary extraction network using graph models to learn geometric information of the polygon shapes. Extensive experiments show that our model can accomplish multi-tasks of object localization, recognition, semantic labelling and geometric shape extraction simultaneously. In terms of building extraction accuracy, computation efficiency and boundary regularization performance, our model outperforms the state-of-the-art baseline models.
COMPARISON OF SUBAQUATIC DIGITAL ELEVATION MODELS FROM AIRBORNE LASER SCANNING AND IMAGERY
Authors: Mulsow C. , Mandlburger G. , Maas H.-G.
Published: August 2020

Abstract. The paper describes and compares the workflows and results of generating digital elevation models (DEMs) of underwater areas from airborne laser scanning and aerial stereo images. Based on a combined laser scanning/image data set of an artificial lake, both methods are described and pros/cons are highlighted. The authors focus on the final results, especially on accuracy, completeness and spatial resolution of the underwater DEM’s. Further, practical aspects of processing and complexity of both methods are highlighted too.