bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of MUDRA in Promoting SMEs/MSE, MSMEs, and allied Agriculture Sector in the rural and urban area - To Achieve 5 Trillion Economy
Authors: K. M. Mahesh , Aithal P. S. , K. R. S. Sharma
Published: May 2022

Purpose: Pradhan Mantri MUDRA Yojana(PMMY) will offer loans up to 10 lakh to Non- Corporate, Non-farm micro-enterprises to generate income and employment in manufacturing services, retail MSME, SMEs and Agriculture related occupations like beekeeping, horticulture, pisciculture, Poultry, agro-industries, diary, agriclinics, agribusiness, to add to the national wealth with the support of SIDBI, NABARD in providing working capital. The Economic Survey-2020-21 recently tabled in Parliament, has stated that about 54.6 % of the workforce in the country is still engaged in agricultural and allied sector activities(Census2011)as well as Micro, small and medium businesses (MSMEs) have played a major role in India’s economic expansion and Women Empowerment, More than 40 per cent of the nation’s GDP comes from the MSME sector, which is a major source of employment and in the Budge emphasizes MSME and agriculture allied activities. MUDRA act as a refinancing institution to Commercial banks, NBFCs, MFIs, RRBs, SFBs through Shishu, Kishor, Tarun schemes in credit outreach model of delivery is SHGs/JLGs, women entrepreneur and in agriculture allied sectors agripreneurship with development and promotion support to enhance employment opportunities in small and medium-sized enterprises /Micro Small Enterprises (SMEs/MSE) in non –farm activities to achieve US$5 trillion economies microfinance plays a vital role.
Design/Methodology/approach: The Research paper is based on secondary statistics collected from different sources such as websites, and published articles. After the literature review and their area gap in the literature and prospect to analyze the role of MUDRA in promoting MSME, SMEs/MSE and Agri. allied sector's funding needs to create a 5 trillion Economy with an ABCD listing framework.
Findings/Result: The study discloses that the MUDRA maximum limit for the Schemes is to be enhanced and more awareness is to be created about the MUDRA loan for Agri. allied activity, Agriclinics, and lack of clarity relating to the role in refinancing schemes for Banks by MUDRA, and NABARD to promote SHGs and Agri allied activity.
Originality/Value: The Research study was undertaken on the contribution of MUDRA funding needs in terms of working capital to Agri. entrepreneurship in agricultural allied sector activities to enhance employment opportunities in rural and urban areas in India.
Paper type: Conceptual Research.
Effect of Teaching Programme regarding Home Care on Knowledge and Practice of Informal Caregivers of CVA Patients in a Selected Hospital in Dehradun (Uttarakhand)
Authors: Sharma Shweta , Prakash Kamli
Published: May 2022

Objectives of the study were to determine the effectiveness of a teaching programme regarding home care of CVA patients on knowledge and practice of informal caregivers, to find association between pre-test knowledge and practice scores of informal caregivers with their selected demographic variables, and to find correlation between post-test knowledge score and post-test practice score of informal caregivers of CVA patients. Quantitative research approach and pre-experimental one group pre-test and post-test design was adopted. Total sample were 45 informal caregivers of CVA patients; purposive sampling technique was used. The findings showed the mean of pre-test knowledge score of 13.24 and mean of post-test knowledge score as 25.96 with calculated ‘t’ value 28.96, which was more than tabulated ‘t’ value at p
Knowledge of Antenatal Women Regarding Breastfeeding: A Descriptive Cross-sectional Study
Authors: D’Sa Juliana Linnette , C. Koshy Akash , Baby Bimi , Asok Jesmi , D’Souza Nileema , D’Souza Sweety Theresa
Published: May 2022

This descriptive cross-sectional study was conducted among antenatal women in a hospital in Mangalore, India. This study aimed at exploring the knowledge of antenatal women regarding breastfeeding and finding association with selected socio-demographic factors. Fifty primigravidae who were either admitted to the antenatal ward or were attending the Outpatient Department of a tertiary care hospital were selected for the study using convenience sampling. Data were collected using a Breastfeeding Knowledge Questionnaire (BKQ) that had 20 multiple choice questions, developed by the authors. The average mean score (M=12), with an overall mean percentage of 60, indicated that the women had average overall knowledge but lacked knowledge in specific content areas of breastfeeding. It ranged from 18 percent in the area ‘nutritional requirements’ to 89 percent in the area ‘general aspects’. The area duration of breastfeeding had a mean percentage of 44.43 percent, with the least in the area of nutritional requirements (18%). Only 58 percent of the women knew that the duration of exclusive breastfeeding is six months. The knowledge of the women was independent of age, religion, education, occupation, type of family and monthly income. Determining the existing knowledge on breastfeeding will provide a basis for developing effective health education programmes.
Effect of Structured Teaching Programme regarding Breast SelfExamination Among Adolescent Girls of Selected College at Guwahati (Assam)
Authors: Jenita Khwairakpam , Himakshi Kalita , Jennifer Pando , Jones Gracia Thabah , Chanu K Leishembi , Devi L Monika , Romabati L , Wegara Marak
Published: May 2022

A pre-experimental study was conducted to assess the effectiveness of structured teaching programme (STP) regarding breast self-examination among the adolescent girls of selected college of Narengi, Guwahati. A total of 35 students were selected using purposive sampling technique. A structured questionnaire was used to collect the data. The results revealed that the pretest mean was 8.2 which increased to 15 in the post-test and there is significant association between the knowledge and demographic variables such as age and religion. The study concludes that STP was significantly effective in increasing the knowledge regarding breast selfexamination among the adolescent girls.
Assessing the Post-Traumatic Stress Among Survivors of Motor Vehicle Accidents in Hoshiarpur (Punjab)
Authors: Kaur Gurpreet
Published: May 2022

Motor vehicle accidents are one of the leading causes of deaths, disabilities and hospitalisations. The present non-experimental descriptive research study, undertaken to assess post-traumatic stress among survivors of motor vehicle accidents, had sample size of 60 survivors of motor vehicle accidents after one month of accident attending OPD on follow-up basis. Assessment of posttraumatic stress was done with the help of standardised rating scale Impact Event Scale- Revised (IES-R) and assessment of severity of injury was done with Abbreviated Injury Scale (AIS) and Injury Severity Score (ISS). Analysis showed that subjects had mild level of post-traumatic stress and as per subscales of post-traumatic stress, patients had highest mean percentage of posttraumatic stress score in hyper arousal subscale.
Effectiveness of Planned Teaching Programme PTP on Knowledge and Practice about Self-care of Diabetes Mellitus Type-II Patients
Authors: Arora Jyoti , Hooda Santosh , Gahlaut PS
Published: May 2022

An evaluative study was conducted to assess the effect of Planned Teaching Programme (PTP) in terms of knowledge and practice about self-care of Type-II diabetes mellitus patients in Pt BD Sharma, PGIMS, Rohtak. A total 100 patients were selected using simple random sampling technique. A quasi experimental one group pre-test and post-test research design was used to assess the knowledge and practice of self-care activities in diabetic patients. A structured knowledge questionnaire was used to collect the data. The results revealed that the mean pre-test knowledge score was 15.36 which increased to 22.77 in post-test. The Mean post-test practice score 14.51 was also higher than the mean pre-test practice score of 10.72. The mean difference between the post-test and pre-test knowledge and practice scores of diabetic patients was found to be highly significant. The study concludes that a planned teaching programme was significantly effective in increasing the knowledge and improving the practice of diabetic patients regarding self-care of the disease.
Patients’ and Care-givers’ Knowledge and Practice regarding Prevention of Complications of Immobilisation with a View to Develop an Information Booklet
Authors: Gandhi Priya , Shaiju Bindu , Tamang Eke Lama
Published: May 2022

This study was conducted at a tertiary care hospital with the objectives to assess the knowledge and practice of immobilised orthopaedic patients and their care-givers regarding prevention of complications of immobilisation and to seek relationship between knowledge and practice scores with the selected demographic variables. A quantitative approach with descriptive survey design was used. A semi structured questionnaire, to assess the knowledge and a checklist to assess the practice of both patients and their care-givers were used for data collection. Purposive sampling technique was employed to select 50 patients admitted in the orthopaedic ward and their 50 care-givers. The study showed that most of the subjects (both patients and care-givers) were in the age group of 20-30 years and married and spending more than 12 hours with their patient to care for them. There was no significant relationship between the knowledge scores of study subjects (patients as well as care-givers) with their practice scores. There was a significant relationship between the knowledge scores of patient and care-givers in specific areas showing consistent knowledge deficit in both patient and care-givers in those areas. There was no significant relationship between the knowledge and practice scores with the selected demographic variables in both patients and their care-givers. An Information Booklet on prevention of complications of immobilisation was developed and disseminated.
Food Calories Estimation Using Image Processing
Authors: Kundan Kumar  , Abhishek Pachpole  , Akshay Shelke  , Rutuja Mandapmalvi  , Prof. Ankita Kotalwar
Published: May 2022

One of the most difficult aspects of obesity therapy is determining how much food obese individuals consume on a daily basis. A computer vision-based approach is used in this study to estimate calorie consumption from food photographs. Propose a Food Recognition System (FRS) for the calculation of calories and nutrient values. The system next analyses and categorises the photos to determine the type of food and portion size, and then uses that information to calculate the calories in the food. In today's food identification applications, emerging food categorization methods are critical. A new food recognition algorithm is provided for this purpose, taking into account the shape, colour, size, and texture features of the item. A better classification will be attained by using various combinations of these features. Dietitians can use this food calorie and nutrition assessment method to track and control their daily food intake. The texture, shape, and size properties of the food image are then retrieved using the CNN. The better the classification, the more accurately the calories of the food may be estimated..
Electricity Generation for Small Scale Industry by Using Exhaust Air
Authors: Eliza Sheikh  , Samiksha Tiwaskar  , Rakhi Bagde  , Nikita Nitnaware  , Dr. Jagdish Chaudhari
Published: May 2022

The energy demand of the world has become unbridled in the past years and is augmenting by leaps and bounds. With increase in energy demand, the conventional sources of energy (fossil fuels, nuclear) are encumbered with monumental pressure and hence, the unremitting use of it, leads to dearth of fossil fuels. This has provoked an extensive research into the area of non-conventional energy sources like hydro, wind, thermal energy, etc. Out of these, the wind energy is being discussed in this paper. Wind energy has a lot of potential and advantages but its utilization is restricted due to its irregularity, geographical conditions and its availability. Our primary goal is to suggest an idea that can surmount these conundrums and utilize the wind energy to its maximum extent. This paper deals with the wind energy that can be derived from the wasted wind energy from industrial exhaust fans. The wind force from an exhaust fan can drive a small windmill and the energy generated from it will be stored in energy storage unit. The power stored in the battery can be transmuted into ac with the help of an inverter and then it can be supplied to the load and hence, this wasted power from exhaust fan can be utilized to meet the growing energy demand. Abstract - The energy demand of the world has become unbridled in the past years and is augmenting by leaps and bounds. With increase in energy demand, the conventional sources of energy (fossil fuels, nuclear) are encumbered with monumental pressure and hence, the unremitting use of it, leads to dearth of fossil fuels. This has provoked an extensive research into the area of non-conventional energy sources like hydro, wind, thermal energy, etc. Out of these, the wind energy is being discussed in this paper. Wind energy has a lot of potential and advantages but its utilization is restricted due to its irregularity, geographical conditions and its availability. Our primary goal is to suggest an idea that can surmount these conundrums and utilize the wind energy to its maximum extent. This paper deals with the wind energy that can be derived from the wasted wind energy from industrial exhaust fans. The wind force from an exhaust fan can drive a small windmill and the energy generated from it will be stored in energy storage unit. The power stored in the battery can be transmuted into ac with the help of an inverter and then it can be supplied to the load and hence, this wasted power from exhaust fan can be utilized to meet the growing energy demand.
2022 Systemic lupus erythematosus remission in clinical practice. Message for Polish rheumatologists
Authors: Pawlak-Buś Katarzyna , Leszczyński Piotr
Published: May 2022

Systemic lupus erythematosus (SLE) is a complicated multiorgan disease and can lead to organ damage and increased risk of morbidity and mortality. The strategy of management while avoiding complications, especially caused by chronic glucocorticoid therapy, improves outcomes. Different definitions of the treatment goal in different configurations of lupus activity indexes have appeared over the years. In 2021 the definition of remission and recommendations for its achievement were published and it become a way to implement a treat-to-target strategy. The main goal of treatment has become DORIS (definition of remission in SLE) remission and the alternative LLDAS (low lupus disease activity state).

Prolonging remission with clinical and immunological lupus activity restrictions and minimizing or stopping steroid doses reduced flares and damage accrual. The analysis and neutralization of poor prognosis predictive factors in lupus could be the most beneficial for less morbidity and mortality and better quality of life.
Opening report of the Polish National Consultant
in the field of rheumatology
Authors: Kwiatkowska Brygida
Published: May 2022

In Poland the National Consultants for the Ministry of Health operate in the fields of health care associated with medical specialties they represent. They are appointed by the Minister of Health from among specialists in the fields of medicine, pharmaceutics and other disciplines which find application in health management [1].
EVALUATION OF VIRUS DISEASE STATUS ON SUGARCANE GERMPLASM IN WESTERN CAMEROON
Authors: Arrey Doris Besem , Essomo Etanke Sylvie , Neculina Anyinkeng , Afanga Afanga Yannick
Published: May 2022

Sugarcane cultivation is hindered by several biotic constraints of which viral disease plays a major disaster. This study was carried out to evaluate the virus disease situation of sugarcane germplasm in western Cameroon, consisting of three regions (Southwest, Northwest and West region). A survey was carried out in 66 villages in these regions. Landraces identified included SMU58, SBK36, SNC16, NBfPc48 and NBfAg53. Representative samples of the landraces were collected and grown in an experimental field in the Department of Plant Science, University of Buea. Canes were observed for virus disease symptoms eleven months after planting. Single leaf samples of the symptomatic plants were collected from 10 randomly selected plants constituted a batch sample. A total of 66 and 15 batch samples collected from the field and experimental plot respectively were tested for the detection of Sugarcane Mosaic Virus (SCMV) and Maize Streak Virus (MSV) by direct Double Antibody Sandwich ELISA (DAS-ELISA). Of the 66 composite samples tested for SCMV and MSV, 54 samples tested positive for at least one virus. Maize streak virus was the most prevalent, with an incidence of 11.25%. Mixed infection was also recorded. Sugarcane in western Cameroon is infected with some virus diseases though the prevalence is low. This is a course of concern.
SEMANTIC SEGMENTATION OF URBAN TEXTURED MESHES THROUGH POINT SAMPLING
Authors: Grzeczkowicz G. , Vallet B.
Published: May 2022

Abstract. Textured meshes are becoming an increasingly popular representation combining the 3D geometry and radiometry of real scenes. However, semantic segmentation algorithms for urban mesh have been little investigated and do not exploit all radiometric information. To address this problem, we adopt an approach consisting in sampling a point cloud from the textured mesh, then using a point cloud semantic segmentation algorithm on this cloud, and finally using the obtained semantic to segment the initial mesh. In this paper, we study the influence of different parameters such as the sampling method, the density of the extracted cloud, the features selected (color, normal, elevation) as well as the number of points used at each training period. Our result outperforms the state-of-the-art on the SUM dataset, earning about 4 points in OA and 18 points in mIoU.
IMPROVED EDGE DETECTION FOR SATELLITE IMAGES
Authors: Mapurisa W. , Sithole G.
Published: May 2022

Abstract. Edges are a key feature employed in various computer vision applications namely segmentation, object recognition, feature tracking and 3D reconstruction. Edges provide key information with regards to object presence, shape, form and detail which aid in many computer vision tasks. While there are various edge detection techniques in literature, challenges in edge detection remain. Varying image contrast due to non uniform scene illumination and imaging resolution affects the edge information obtained from any given image. The edge detection results are characterised by missing edges, edge fragmentation and some false positive edges. Gradient based edge detectors are the most commonly used detectors. These detectors all suffer from aforementioned challenges. In this, paper we present an edge detection framework that aims to recover long unfragmented edges from satellite images. This is achieved by using an edge accumulator that operates on the entire edge detection parameter space. Gradient based edge detectors rely on thresholding to retrieve salient edges. This usually results in missed or noisy edges. To counter this, the accumulator is run over a wide parameter space, growing edges at each accumulator level while maintaining edge position using a localisation filter. The results are longer unbroken edges that are detected for most objects, even in shadowy regions and low contrast areas. The results show improved edge detection that preserves the form and detail of objects when compared to current gradient based detectors.
A NOVEL DATA AUGMENTATION METHOD TO ENHANCE THE TRAINING DATASET FOR ROAD EXTRACTION FROM SWISS HISTORICAL MAPS
Authors: Jiao C. , Heitzler M. , Hurni L.
Published: May 2022

Abstract. Long-term retrospective road data are required for various analyses (e.g., investigation of urban sprawl, analysis of road network evolution). Yet, it is challenging to extract roads from scanned historical maps due to their dissatisfying quality. Although deep learning has been exerting its superiority in image segmentation, its application to road extraction from historical maps is rarely seen in existing studies. Deep learning usually requires quite large amounts of training data, which is time-consuming and tedious to label. Data augmentation can to some extent solve this issue. The existing data augmentation techniques vary each training sample as a whole (e.g., rotation, flipping). But some features or symbols on maps will never occur in practice when they are rotated or flipped (e.g., numbers, labels). To solve this problem and to further improve the diversity of training samples, we propose a novel data augmentation method, which varies the target features instead of the whole training sample. The method is validated by applying it to road extraction from the historical Swiss Siegfried map. The experiment results show the effectiveness of the proposed method.
RUNOFF ESTIMATION BASED ON HYBRID-PHYSICS-DATA MODEL
Authors: Zhang C. , Xue H. , Dong G. , Jing H. , He S.
Published: May 2022

Abstract. Runoff estimations play an important role in water resource planning and management. Existing hydrological models can be divided into physical models and data-driven models. Although the physical model contains certain physical knowledge and can be well generalized to new scenarios, the application of physical models is limited by the high professional knowledge requirements, difficulty in obtaining data and high computational costs. The data-driven model can fit the observed data well, but the estimation may not be physically consistent. In this letter, we propose a hybrid physical data (HPD) model combining physical model and deep learning model for runoff estimation. The model uses the output of a physical hydrological model together with the driving factors as another input of the neural network to estimate the monthly runoff of the upper Heihe River Basin in China. We show that the use of the HPD model improves the quality of runoff estimation, and results in high R2, NSE values of 0.969, and a low RMSE value of 9.645. It is indicated that the new model had an excellent learning capability to simulate runoff and flexible ability to extract complex relevant information; At the same time, the estimation capacity of peak runoff is optimized.
HISTORIC LAND COVER CHANGE ASSESSMENT OF CHILEAN MEDITERRANEAN COAST: DID FOREST PLANTATIONS REALLY CAUSED FRAGMENTATION?
Authors: Cortés L. , Hernández H. J. , Silva P.
Published: May 2022

Abstract. Currently, the Mediterranean coast of Chile has large areas of commercial pine and eucalyptus plantations. Several authors have reported habitat loss and fragmentation of the original “Maulino” native forest due to the expansion of plantations. However, in the Maule coast took place a previous process that affected the native forest. This is the extensive use of forestlands with a moderate slope for the cultivation of wheat. The peak of this process occurred in the second half of the 19th century and meant a great degradation of the soil in the area. In this work, we first look for whether the overexploitation of wheat is the primary cause of the fragmentation of the Maulino forest in the study area. Secondly, we wanted to determine what proportion of the area currently occupied by plantations was previously used for growing wheat. First, using the community of Constitución as a representative area of the central coast we use Species Distribution Modelling to identify the potential original extent of the Maulino forest. Secondly, we created a spatial model to estimate the extension of wheat production using historical data. Finally, we used Landsat-8 images to assess the actual extension of forest plantation. By comparing the three former results, we were able to quantify the effects of wheat production and forest plantation separately, for the first time. The results indicate that 41% of the original native forest was first affected by wheat production and that only 34 % was later replaced by forest plantations. Therefore, the rest of the plantations were installed in places where the forest had previously been cut down for use in wheat production. The main cause of deforestation and forest fragmentation in this landscape was originally the wheat extensive production boosted by the gold rush in California and Australia. Forest commercial plantations further augmented the Maulino forest fragmentation process by significantly reducing its mean patch size and increasing the number of patches.
MULTITEMPORAL SEGMENTATION OF SENTINEL-2 IMAGES IN AN AGRICULTURAL INTENSIFICATION REGION IN BRAZIL
Authors: Dos Santos L. T. , Werner J. P. S. , Dos Reis A. A. , Toro A. P. G. , Antunes J. F. G. , Coutinho A. C. , Lamparelli R. A. C. , Magalhães P. S. G. , Esquerdo J. C. D. M. , Figueiredo G. K. D. A.
Published: May 2022

Abstract. With the recent evolution in the sensor's spatial resolution, such as the MultiSpectral Imager (MSI) of the Sentinel-2 mission, the need to use segmentation techniques in satellite images has increased. Although the advantages of image segmentation to delineate agricultural fields in images are already known, the literature shows that it is rarely used to consider temporal changes in highly managed regions with the intensification of agricultural activities. Therefore, this work aimed to evaluate a multitemporal segmentation method based on the coefficient of variation of spectral bands and vegetation indices obtained from Sentinel-2 images, considering two agricultural years (2018–2019 and 2019–2020) in an area with agricultural intensification. Images of the coefficient of variation represented the spectro-temporal dynamics within the study area. These images were also used to apply an edge detection filter (Sobel) to verify their performance. The region-based algorithm Watershed Segmentation (WS) was used in the segmentation process. Subsequently, to assess the quality of the segmentation results produced, the metrics Potential Segmentation Error (PSE), Number-of-Segments Ratio (NSR), and Euclidean Distance 2 (ED2) were calculated from manually delineated reference objects. The segmentation achieved its best performance when applied to the unfiltered coefficient of variation images of spectral bands with an ED2 equal to 7.289 and 2.529 for 2018–2019 and 2019–2020, respectively. There was a tendency for the WS algorithm to produce over-segmentation in the study area; however, its use proved to be effective in identifying objects in a dynamic area with the intensification of agricultural activities.
THE EFFECT OF SPECTRAL MIXTURES ON WEED SPECIES CLASSIFICATION
Authors: Ronay I. , Kizel F. , Lati R.
Published: May 2022

Abstract. Site-specific weed management (SSWM) is a precise and resource-efficient approach that can result in more productive and sustainable agricultural practices. SSWM requires weed maps, in which the vegetation-related pixels are segmented from the soil and other substances and then classified into crops and different weed species. Such classification with a high spatial resolution is significant for SSWM since preventing economic losses due to weeds requires making management decisions at meter scales. In this regard, hyperspectral sensors can capture leaf anatomy and biochemistry variations, suggesting many advantages for weed classification. However, the typical tradeoff between spectral and spatial resolution poses a challenge for applying hyperspectral imaging in large scales and scenarios of high densities and tiny seedlings at early growth due to mixed pixels. Mixture analysis methods were previously demonstrated to offer opportunities for dealing with mixed pixels in vegetation ecology and agriculture. Nonetheless, they were not widely utilized for weed classification. This study aims to reveal the impact of the spectral mixture on classification results using supervised classification, spectral unmixing, and spatial analysis. We attempted to characterize how the spectral mixture of different weed species and soil at different growth stages affects classification results. Our results suggest that spectral mixtures are probably a significant factor driving misclassifications when classifying weed species. Their effect can be characterized by spatial analysis and fractions obtained by spectral unmixing. We assume that the subpixel information provided by the fraction maps may add information about the spectral mixture that can assist in interpreting misclassification pixels alongside the widely used confusion matrix. This contribution is highly relevant at coarser spatial resolutions.
SUPER RESOLUTION FOR SINGLE SATELLITE IMAGE USING A GENERATIVE ADVERSARIAL NETWORK
Authors: Li R. , Liu W. , Gong W. , Zhu X. , Wang X.
Published: May 2022

Abstract. Inspired by the immense success of deep neural network in image processing and object recognition, learning-based image super resolution (SR) methods have been highly valued and have become the mainstream direction of super resolution research. Base on the recent proposed state-of-art convolution neural network (CNN) super-resolution methods, this paper proposed a generative adversarial network for single satellite image Super Resolution reconstruction. It built on a trained deep residual network to generate preliminary SR images, combined with a discriminative network learns to differentiate preliminary SR images and High resolution samples. The experiments results show that our method can use existing model parameters to refine SR image performance.
CLIFF CHANGE DETECTION USING SIAMESE KPCONV DEEP NETWORK ON 3D POINT CLOUDS
Authors: de Gélis I. , Bessin Z. , Letortu P. , Jaud M. , Delacourt C. , Costa S. , Maquaire O. , Davidson R. , Corpetti T. , Lefèvre S.
Published: May 2022

Abstract. Mainly depending on their lithology, coastal cliffs are prone to changes due to erosion. This erosion could increase due to climate change leading to potential threats for coastal users, assets, or infrastructure. Thus, it is important to be able to understand and characterize cliff face changes at fine scale. Usually, monitoring is conducted thanks to distance computation and manual analysis of each cliff face over 3D point clouds to be able to study 3D dynamics of cliffs. This is time consuming and inclined to each one judgment in particular when dealing with 3D point clouds data. Indeed, 3D point clouds characteristics (sparsity, impossibility of working on a classical top view representation, volume of data, …) make their processing harder than 2D images. Last decades, an increase of performance of machine learning methods for earth observation purposes has been performed. To the best of our knowledge, deep learning has never been used for 3D change detection and categorization in coastal cliffs. Lately, Siamese KPConv brings successful results for change detection and categorization into 3D point clouds in urban area. Although the case study is different by its more random characteristics and its complex geometry, we demonstrate here that this method also allows to extract and categorize changes on coastal cliff face. Results over the study area of Petit Ailly cliffs in Varengeville-sur-Mer (France) are very promising qualitatively as well as quantitatively: erosion is retrieved with an intersection over union score of 83.86 %.
MASNET: IMPROVE PERFORMANCE OF SIAMESE NETWORKS WITH MUTUAL-ATTENTION FOR REMOTE SENSING CHANGE DETECTION TASKS
Authors: Zhou H. , Ren Y. , Li Q. , Yin J. , Lin Y.
Published: May 2022

Abstract. Siamese networks are widely used for remote sensing change detection tasks. A vanilla siamese network has two identical feature extraction branches which share weights, these two branches work independently and the feature maps are not fused until about to be sent to a decoder head. However we find that it is critical to exchange information between two feature extraction branches at early stage for change detection task. In this work we present Mutual-Attention Siamese Network (MASNet), a general siamese network with mutual-attention plug-in, so to exchange information between the two feature extraction branches. We show that our modification improve the performance of siamese networks on multi change detection datasets, and it works for both convolutional neural network and visual transformer.
MULTISCALE SPATIAL RELATION EXTRACTION OF A REMOTELY SENSED WATERLINE IN A MUDDY COASTAL ZONE WITH CHONGMING DONGTAN AS AN EXAMPLE
Authors: Yang L. , Li M. , Li J. , Jiang Y. , Yang H.
Published: May 2022

Abstract. To address the difficulty of waterline extraction in areas with gentle slopes in the muddy coastal zone, Chongming Dongtan in the Yangtze River estuary is selected as the research object. This paper analyzes the spatial relationship of the waterline in Landsat images at three spatial scales, gives a method for numerically calculating the spatial relationship characteristics at different spatial scales and the application means in waterline extraction, and constructs a model for waterline extraction from Landsat images using the multiscale spatial relationship. Finally, the execution efficiency and positioning accuracy of the multiscale spatial relationship waterline extraction model are quantitatively evaluated. The results show that the spatial relationship is effectively used to solve the problem of discontinuous extraction of a weak waterline in the muddy coastal zone, and the waterline recognition ability for remote sensing images is significantly improved. The position accuracy of waterlines obtained by the improved method can reach 12.4 meters. Compared with other methods, this method shows great advantages in terms of automation, waterline continuity, and positioning accuracy and provides technical support for the use of remote sensing technology to study the dynamic changes in coastal zones.
VISUALLY ANNOTATED RESPONSIVE DIGITAL TWINS FOR REMOTE COLLABORATION IN MIXED REALITY ENVIRONMENTS
Authors: Baumgartner L. , Brägger L. , Koebel K. , Scheidegger J. , Çöltekin A.
Published: May 2022

Abstract. Various forms of extended reality might empower remote collaboration in ways that the current de facto standards cannot facilitate. Especially when combined by a digital twin of the remote physical object, mixed reality (MR) opens up interesting new ways to support spatial communication. In this study, we explore the use of a digital twin to facilitate visuospatial communication in an expert-guided repair and maintenance operation scenario, supported by visual annotations. We developed two MR prototypes, one with a digital twin of the object of interest, and another where a first-person camera view was shown additionally. We tested these prototypes in a study with 19 participants (9 pairs) against a state-of-the art solution as a baseline and measured their usability, and obtained qualitative user feedback. Our findings suggest that digital twin supported mixed reality enriched with real time visual annotations can potentially improve remote collaboration tasks.
VIRTUALLY THROWING BENCHMARKS INTO THE OCEAN FOR DEEP SEA PHOTOGRAMMETRY AND IMAGE PROCESSING EVALUATION
Authors: Song Y. , She M. , Köser K.
Published: May 2022

Abstract. Vision in the deep sea is acquiring increasing interest from many fields as the deep seafloor represents the largest surface portion on Earth. Unlike common shallow underwater imaging, deep sea imaging requires artificial lighting to illuminate the scene in perpetual darkness. Deep sea images suffer from degradation caused by scattering, attenuation and effects of artificial light sources and have a very different appearance to images in shallow water or on land. This impairs transferring current vision methods to deep sea applications. Development of adequate algorithms requires some data with ground truth in order to evaluate the methods. However, it is practically impossible to capture a deep sea scene also without water or artificial lighting effects. This situation impairs progress in deep sea vision research, where already synthesized images with ground truth could be a good solution. Most current methods either render a virtual 3D model, or use atmospheric image formation models to convert real world scenes to appear as in shallow water appearance illuminated by sunlight. Currently, there is a lack of image datasets dedicated to deep sea vision evaluation. This paper introduces a pipeline to synthesize deep sea images using existing real world RGB-D benchmarks, and exemplarily generates the deep sea twin datasets for the well known Middlebury stereo benchmarks. They can be used both for testing underwater stereo matching methods and for training and evaluating underwater image processing algorithms. This work aims towards establishing an image benchmark, which is intended particularly for deep sea vision developments.
Tsunami hazard in Lombok and Bali, Indonesia, due to the Flores back-arc thrust
Authors: Felix Raquel P. , Hubbard Judith A. , Bradley Kyle E. , Lythgoe Karen H. , Li Linlin , Switzer Adam D.
Published: May 2022

Abstract. The tsunami hazard posed by the Flores back-arc thrust, which runs
along the northern coast of the islands of Bali and Lombok, Indonesia, is
poorly studied compared to the Sunda Megathrust, situated ∼250 km to the south of the islands. However, the 2018 Lombok earthquake
sequence demonstrated the seismic potential of the western Flores Thrust
when a fault ramp beneath the island of Lombok ruptured in two Mw 6.9
earthquakes. Although the uplift in these events mostly occurred below land,
the sequence still generated local tsunamis along the northern coast of
Lombok. Historical records show that the Flores fault system in the Lombok
and Bali region has generated at least six ≥Ms 6.5 tsunamigenic
earthquakes since 1800 CE. Hence, it is important to assess the possible
tsunami hazard represented by this fault system. Here, we focus on the
submarine fault segment located between the islands of Lombok and Bali
(below the Lombok Strait). We assess modeled tsunami patterns generated by
fault slip in six earthquake scenarios (slip of 1–5 m, representing Mw 7.2–7.9+) using deterministic modeling, with a focus on impacts on the
capital cities of Mataram, Lombok, and Denpasar, Bali, which lie on the
coasts facing the strait. We use a geologically constrained earthquake model
informed by the Lombok earthquake sequence, together with a high-resolution
bathymetry dataset developed by combining direct measurements from the General Bathymetric Chart of the
Oceans (GEBCO)
with sounding measurements from the official nautical charts for Indonesia.
Our results show that fault rupture in this region could trigger a tsunami
reaching Mataram in <9 min and Denpasar in ∼ 23–27 min, with multiple waves. For an earthquake with 3–5 m of
coseismic slip, Mataram and Denpasar experience maximum wave heights of
∼ 1.6–2.7 and ∼ 0.6–1.4 m, respectively.
Furthermore, our earthquake models indicate that both cities would
experience coseismic subsidence of 20–40 cm, exacerbating their exposure to
both the tsunami and other coastal hazards. Overall, Mataram is more
exposed than Denpasar to high tsunami waves arriving quickly from the fault
source. To understand how a tsunami would affect Mataram, we model the
associated inundation using the 5 m slip model and show that Mataram is
inundated ∼ 55–140 m inland along the northern coast and
∼230 m along the southern coast, with maximum flow depths of
∼ 2–3 m. Our study highlights that the early tsunami arrival
in Mataram, Lombok, gives little time for residents to evacuate. Raising
their awareness about the potential for locally generated tsunamis and the
need for evacuation plans is important to help them respond immediately
after experiencing strong ground shaking.
О СПОСОБАХ ОБРАЗОВАНИЯ РУССКО-АРМЯНСКИХ МЕДИЦИНСКИХ ТЕРМИНОВ
Authors: МКРТЧЯН ГОАР
Published: May 2022

Статья посвящена изучению способов образования русско-армянских медицинских терминов. Была поставлена задача выявить наиболее распространенные в данных языках способы образования новой медицинской терминологии. В процессе работы был проведен сравнительно-сопоставительный анализ медицинской терминологии в армянском и русском языках. Как известно, медицина пользовалась и пользуется латинскими и греческими терминами. Однако синхронный лексико-семантический анализ собранных терминов показал, что на фоне греческих и латинских появляются новые термины, обозначающие новые вирусы, болезни, новые медицинские специальности, а также новую медицинскую аппаратуру. Это объясняется стремительным развитием медицины. Как показал анализ терминообразующих единиц, в процессе создания новых терминов часто используются элементы латинского и греческого языков. Это объясняется тем, что такая форма легко воспринимается представителями медицинской науки. Были выявлены также новые термины, образованные путем калькирования терминов с английского языка или других языков. В данном случае доминантный язык определяется тем, в какой стране было сделано то или иное медицинское открытие и какой язык первым дал этому открытию название. Проведенный анализ дает возможность сделать выводы о том, что самыми распространенными способами образования новых терминов в указанных языках являются калькирование, описательный или поэлементный перевод, транслитерация и заимствование.
ԱՐՑԱԽԻ ՀԱՆՐԱՊԵՏՈՒԹՅԱՆ ՊԱՏՄԱՄՇԱԿՈՒԹԱՅԻՆ ԿՈԹՈՂՆԵՐԻ ՈՒՍՈՒՄՆԱՍԻՐՈՒՄԸ «ԶՐՈՒՅՑՆԵՐ ԱՐՎԵՍՏԻ ՄԱՍԻՆ» ԹԵՄԱՏԻԿ ԴԱՍԸՆԹԱՑՆԵՐԻ ՇՐՋԱՆԱԿՈՒՄ
Authors: ԱՎԵՏԻՍՅԱՆ ԳԱԳԻԿ
Published: May 2022

2020 թվականի աղետալի պատերազմի արդյունքում, Արցախի Հանրապետության հարյուրավոր բնակավայրերից զատ, բազմաթիվ հայրենի պատմական նշանակության հուշարձաններ ևս հայտնվել են Բաքվի ռեժիմի ներքո: Վերջինս պետական ամենաբարձր մակարդակով իրագործում է մշակութային ցեղասպանություն՝ վերացնելով հայկականության քարակերտ հետքերը՝ կոթողները ներկայացնելով երբեմնի աղվանական մշակութային ժառանգություն: Ուստի չհանդուրժելով բռնազավթված մեր հայրենիքում վանդալիստական գործողությունները՝ հարկ է նաև ռուսական խաղաղապահ և ՊԲ ուժերի կողմից վերահսկվող Արցախի մնացյալ տարածքներում վերաարժևորել առկա կոթողային անգին հուշարձաններն ու պետական մակարդակով ձևավորել հայրենաճանաչ ու հայրենատեր քաղաքացու կերպարը:
Այս համատեքստում սույն հոդվածի նպատակն է հիմնավորել սովորողների կողմից Արցախի Հանրապետության հսկողության ներքո գտնվող տարածքների պատմամշակութային կոթողների նորովի ուսումնասիրման և ապագա հայրենասեր քաղաքացիների ձևավորման հիմքերը: Խնդիրներն են վերլուծել համապատասխան մանկավարժական մոտեցումներն ու հիմնավորել պատմամշակութային կոթողների վերաբերյալ սովորողների հետաքրքրությունների առկայությունը: Գիտական նորույթն ընդհանուր մասնագիտական պատրաստվածության մեջ պատմամշակութային կոթողների ներկայացման գործընթացում սովորողներին նպաստող ուսուցման դերն ու տեղը բացահայտելն է:
Վերոնշյալ խնդրի լուծմանը գործուն քայլեր ձեռնարկելու նպատակային միջոց ենք համարում տեղի ուսումնական հաստատություններում 7-րդ դասարանի Կերպարվեստ առարկայի «Զրույցներ արվեստի մասին» թեմատիկ դասընթացների շրջանակում (հին հայկական ճարտարապետությունը, կոթողային հուշարձանները) ներառելու նաև սովորողների կողմից պատմամշակութային կոթողների ծանոթացմանն ու պլեներային պատկերագրմանը միտված գործընթացը, որի արդյունքում վերջիններիս մոտ կարժևորվի հայրենաճանաչությունը, կձևավորվի գեղարվեստական ընկալունակություն, ու միջազգային հարթակներում ցուցադրությունների միջոցով կամրապնդվի Արցախի՝ որպես հայոց հնամենի բնօրրան լինելու անառարկելի փաստը:
Սույն հոդվածում Արցախի Հանրապետության պատմամշակութային կարևորագույն կոթողների շարքում անդրադառնում ենք Գանձասարի, Դադիվանքի և Ամարասի ճարտարապետական ընդհանուր նկարագրին, պատմությանն ու պատկերագրմանը միտված հիմնական առանձնահատկություններին: Աշխատանքը շարադրված է համապատասխան փաստերի համադիր քննությամբ, մանկավարժամեթոդական վերլուծությամբ։ Մանրամասն ուսումնասիրելով խնդրո առարկան՝ հանգել ենք այն եզրակացության, որ թեմայի արդիականությունից ելնելով՝ սովորողների կողմից պատմամշակութային կոթողների ծանոթացման ու պատկերագրման գործընթացը կնպաստի վերջիններիս մոտ հայրենատիրության գաղափարախոսության ամրապնդմանն ու հայրենիքի վերաազատագրման սրբազան առաքելությանը:
ՆՈՐԱՐԱՐԱԿԱՆ ԳՈՐԾՈՒՆԵՈՒԹՅԱՆ ՀԱՐԿԱՅԻՆ ԽԹԱՆՄԱՆ ՄԻՋԱԶԳԱՅԻՆ ՓՈՐՁԸ ԵՎ ՀԱՅԱՍՏԱՆԻ ՀԱՆՐԱՊԵՏՈՒԹՅՈՒՆՈՒՄ ԴՐԱ ՏԵՂԱՅՆԱՑՄԱՆ ՀՆԱՐԱՎՈՐՈՒԹՅՈՒՆՆԵՐԸ
Authors: ՄԱՐԳԱՐՅԱՆ ԱՏՈՄ , ԳՐԻԳՈՐՅԱՆ ԷՄԻԼ
Published: May 2022

Վերջին տասնամյակներին տնտեսագետների կողմից բազմիցս նշվել է նորարարության դրական ազդեցությունների մասին: Ազգային նորարարական համակարգի ձևավորման գործընթացում նորարարական գործունեությանը նպաստելու պետական ինստիտուցիոնալ լծակներից է նաև հարկային քաղաքականությունը: Հոդվածում նպատակ է սահմանվել ուսումնասիրել Հայաստանի, ԵՄ երկրների, Մեծ Բրիտանիայի հետազոտությունների և մշակումների հարկային խթանումը և նորարարությունը բնութագրող ցուցանիշները, մասնավորապես՝ R&D անուղղակի հարկային խթանների տեսակարար կշիռը ՀՆԱ-ում և նորարարական արդյունքի ենթահամաթիվը, իսկ խնդիրը տվյալ ցուցանիշների դինամիկայի, արդի միտումների, ինչպես նաև Հայաստանում նորարարական գործունեության հարկային խթանման ինստիտուցիոնալ հիմքերի ուսումնասիրությունն է: Հոդվածում կիրառվել են հետազոտության վերլուծության, համադրության, համեմատության, գրաֆիկական և նկարագրության մեթոդները: Դրված խնդրի համատեքստում դիտարկվել են 2000 և 2019 թթ. նորարարական գործունեության ուղղակի և անուղղակի խթանման և 2019 թ. նորարարական արդյունքի ցուցանիշները, որի հիման վրա կատարվել են որոշ եզրահանգումներ: Տարիների ընթացքում ավելացել է հարկային խթանների գործիքակազմն օգտագործող երկրների թիվը: Այլ հարց է՝ ինչպիսի կառուցվածք պետք է ունենա տվյալ գործիքակազմը՝ առավելագույն արդյունավետություն ապահովելու նպատակով: Հայաստանում ներկայումս չի կիրառվում հետազոտությունների և մշակումների հարկային խթանման միջազգայնորեն ընդունված մեխանիզմ: Այնուհանդերձ, Հայաստանում նորարարական գործունեությանը մեծապես կարող է նպաստել ոլորտում հարկային քաղաքականության առաջավոր փորձի ներդրումը հատկապես ազգային նորարարական քաղաքականության գործիքակազմի այլ բաղադրիչների հետ ներդաշնակ ներազդման պարագայում:
Арзуманян Ашот Мартиросович. «Тайна булата», «Советакан грох», 1976г., 536 с.
Authors: Варданян Анна
Published: May 2022

«Тяжёлый путь остался позади. Мальчик из Шуши с двумя сёстрами и маленьким братом оказался в Баку». Так начинается глава «Ованес из Шуши» из книги под названием «Тайна Булата», написанной Ашотом Арзуманяном. Он годами собирал ценные материалы, сведения, проводил встречи с современниками — с теми, кто дольше и ближе знал Ованеса Тевадросовича, которого на русский лад называли Иваном Фёдоровичом, с теми, кто работал с ним и в мирные дни, и в грозовые военные годы в СССР и за рубежом.
Membangun Guru Agama Katolik yang Kreatif, Inovatif, dan Motivatif di Masa Pandemi
Authors: Leba Katarina , Watunglawar Balthasar
Published: May 2022

The purpose of this study is to describe and analyze the substantive perspectives of teacher creativity, innovation, and motivation as well as the characteristics of creative, innovative, and motivational Catholic teachers. This study uses a qualitative method. The data technique is done through literature review, observation, and documentation. Data were analyzed using descriptive qualitative. The results of the analysis were in the form of real conditions in the field which were obtained from opinions, including the perspective of the teaching of Jesus Christ. Perspective research was carried out by means of reflection, analysis, and comparison of each view and theory to find the advantages and disadvantages. Furthermore, it was drawn as the final report of this research. These results informed that creativity and intellectual initiative helped humans to solve research problems and answer goals. The power of innovation can be seen through the teacher's creations in making it easier for students to absorb the knowledge being taught. The teaching of Jesus is a major factor for creative, innovative, and motivational Catholic teachers. A creative, innovative, and motivational Catholic teacher must prioritize his essential duties; find students and answer their needs; using contextual media according to the needs of students or learners; always strives to be a person or a teacher with integrity, role model, and disregard.