Basic Observation Research Articles

Lightweight Channel Attention and Multiscale Feature Fusion Discrimination for Remote Sensing Scene Classification

High-resolution remote sensing image scene classification has attracted widespread attention as a basic earth observation task. Remote sensing scene classification aims to assign specific semantic labels to remote sensing scene images to serve specified applications. Convolutional neural networks are widely used for remote sensing image classification due to their powerful feature extraction capabilities. However, the existing methods have not overcome the difficulties of large-scene remote sensing images of large intraclass diversity and high interclass similarity, resulting in low performance. Therefore, we propose a new remote sensing scene classification method that combines lightweight channel attention and multiscale feature fusion discrimination, called LmNet. First, ResNeXt is used as the backbone; second, a new lightweight channel attention mechanism is constructed to quickly and adaptively learn the salient features of important channels. Furthermore, we designed a multiscale feature fusion discrimination framework, which fully integrates shallow edge feature information and deep semantic information to enhance feature representation capabilities and uses multiscale features for joint discrimination. Finally, a cross-entropy loss function based on label smoothing is built to reduce the influence of interclass similarity on feature representation. In particular, our lightweight channel attention and multiscale feature fusion mechanism can be flexibly embedded in any advanced backbone as a functional module. The experimental results on three large-scale remote sensing scene classification datasets show that compared with the existing advanced methods, our proposed high-efficiency end-to-end scene classification method has reached state-of-the-art. Moreover, our method has a weaker dependence on labeled data and provided better generalization performance.

Development and Application of the Sample Support in Transmission Electron Microscopy

Cryogenic electron microscopy is becoming an increasingly popular technology that allows us to observe the molecules in high-resolution details. With this refined way to study the structures in scientific researches, the observation of the molecules will be expected to make improvements. The conventional methods, such as the X-ray crystallography and the nuclear magnetic resonance spectroscopy, provide the basic observation of ground-state molecules and the measurement of various small molecules. But both of them contain flaws discovered in the continuing development process. Therefore, the application of cryo-EM becomes a broader area to explore. In this review, we will give an overall understanding of the cryogenic electron microscopy. We will discuss the intention behind the invention of the cryo-EM and introduce the main workflow of the experiments. In addition, we will discuss the methods to prepare the sample in a well-condition and compare them among different groups of experiments. More importantly, we will discuss the application of the graphene in cryo-EM and evaluate possible improvements in future development.

点群ベースの測定基準による埴輪の三次元顔類似性に関する研究

The Haniwa are a type of terracotta figurines from ancient Japan, which have been scanned and saved as three-dimensional models composed of point cloud and triangular meshes for archaeological research. Although these three-dimensional models can be used to analyze the production technique of the Haniwa, there are several cases where archaeologists subjectively classify the Haniwa using only visual and qualitative observation approaches based on the Haniwa features, i.e., the face, clothes, etc. Here, the need for a computer-aided and quantitative evaluation method, using three-dimensionally measured point cloud, becomes evident. For a quantitative evaluation of the Haniwa, the evaluation of face similarity is considered an important issue. As the face is mainly composed of nose, mouth, and eyes, the face similarity of the Haniwa can be evaluated by comparing the corresponding facial parts between individuals. However, shapes and placements of the same facial parts for each pair of Haniwa have individual differences. Therefore, the face alignment to precisely localise the facial parts and recoginize their shapes should be required. To achieve the aforementioned precise alignment, a hybrid method combining ellipsoid-fitting-based segmentation and topological hole detection is proposed, to extract the point cloud of the nose and locate the contours of the eyes and mouth. Besides the face alignment, the quantitative evaluation essentially contains a process of comparing the faces by analyzing the relationships between the facial parts. For the face comparison, when the facial parts are aligned, the point clouds of the nose for each pair of Haniwa are registered through a scaling iterative closest point algorithm to achieve a value for scale alignment. After the point clouds of all the facial parts for each pair of Haniwa are aligned on the same scale to suppress scale error generated in production, their difference is calculated using the standard iterative closest point algorithm to obtain point-based dissimilarity for each pair of Haniwa. Moreover, owing to basic visual observation, the difference in the relative positions of the eyes and mouths with respect to those of the noses was manually measured as another dissimilarity for face comparison. Our experimental results demonstrate that the proposed method is effective for the similarity evaluation of the Haniwa through the three-dimensional point cloud.

Crises of the communist and neoliberal orders 30 years later: A structural comparison between 1975 and 2019 Poland

This article proposes to look at the current moment in the recent history of the so-called Central-European countries, with Poland as a critical case study, through a structural comparison with an earlier historical cycle, that is one of the first three decades of the communist rule in the region. Thus, I propose to compare the social and economic situation in Poland of circa 1975 with that of 2019, so 30 years after the establishment of a new given political order (30 years after 1945 and 1989 respectively). The paper will offer a general overview of the trajectory of Poland in the post-war era, based primarily on the perspective of the world-system theory and that of the critical sociology of elites, one which will also point to the essential structural contexts of the post-communist dynamics of society. This paper will be based on a basic observation: even if both the 1970s and late 2010s can be considered as periods of relative political stabilization and economic growth for the region as such, and Poland in particular, these countries are, at the same time, subjected to a considerable and even increasing economic dependence on the Western core. In the conclusions, it is argued that the proposed comparative approach, taking into account both an earlier historical cycle and the broader structural dependency of the region, may allow to cast a new light on the nature of current dynamics in Polish politics as well as on the possible future trajectories of the country.

Activity-based unplugged coding during the preschool period

The aim of this pilot study is to support the activity-based unplugged coding and robotic coding skills of children during their preschool period. A significant sample was chosen for this quantitative research. The study group consisted of 24 5-year-old children being educated in a State kindergarten under the Gaziantep Provincial Directorate of National Education. The children had never received any coding or robotic coding lessons before. Eight basic coding and robotic coding activities were organized for preschoolers. The activities provided 60–90 min of daily training over the course of 8 days. The goal of these activities was to develop basic coding and robotic coding skills. The activities were integrated with the current preschool education curriculum. A Basic Coding Skills Observation Form and a Robotic Coding Basic Skills Observation Form were used in order to evaluate the coding and robotic coding skills of the children before and after training. The validity of these forms was assessed by a professional coder. The forms were initially applied to a small group. The data were recorded by the trainer and an observer. Inter-rater reliability was calculated using the kappa statistic, and X2 was calculated as .73. For the analysis of the study, a McNemar test was used for dependent groups in order to test the significance between two connected percentages. The results showed that activity-based unplugged coding and robotic coding training, integrated with the preschool education curriculum, enhanced the basic coding and robotic coding skills of this group of preschoolers.

Experiences and outcomes of craft skill learning with a 360° virtual learning environment and a head-mounted display

Virtual reality environments (VLEs) such as 360° videos have been introduced as educational tools over the last few years, although the pedagogical value of these media has not been widely examined, especially in the context of craft skill learning. Moreover, emotions and competences have a great impact on the usability and adoption of ICT – and on learning. In this paper, mixed-method strategies were used to address these pedagogical and emotional needs in the context of craft learning and 360° VLE. Furthermore, a quasi-experimental design was used to compare learning outcomes of 360° VLE and traditional groups. Findings based on quantitative analysis suggest that negative or positive ICT-attitude did not affect how students experienced traditional or 360° lessons emotionally. However, ICT- and craft-competences had significant correlations with the described emotions. No significant differences in terms of learning outcomes were observed between the traditional and 360° teaching methods. According to the thematic analysis of the interviews, the 1st-person-view 360° VLE could be used for basic skill observation and visualization to support traditional hands-on learning. Moreover, a head-mounted display was considered to help with focusing on the demonstration. However, more interaction with the interface and opportunities for direct interaction with the instructor were seen as necessary in 360° VLEs for skill learning in the future.

Direct Visualization of Perm-Selective Ion Transportation

Perm-selective ion transportation in a nanoscale structure such as nanochannel, nanoporous membrane or nanojunction has been extensively studied with aids of nanofabrication technology for a decade. While theoretical and experimental advances pushed the phenomenon to seminal innovative applications, its basic observation has relied only on an indirect analysis such as current-voltage relation or fluorescent imaging adjacent to the nanostructures. Here we experimentally, for the first time, demonstrated a direct visualization of perm-selective ion transportation through the nanoscale space using an ionic plasma generation. A micro/nanofluidic device was employed for a micro bubble formation, plasma negation and penetration of the plasma along the nanojunction. The direct observation provided a keen evidence of perm-selectivity, i.e. allowing cationic species and rejecting anionic species. Furthermore, we can capture the plasma of lithium, which has lower mobility than sodium in aqueous state, passed the nanojunction faster than sodium due to the absence of hydrated shells around lithium. This simple, but essential visualization technique would be effective means not only for advancing the fundamental nanoscale electrokinetic study as well as interfacial ion transportation between liquid and plasma but also for providing the insight of new innovative engineering applications.

Sustainable Conservation of the Coal Mining Town: Ombilin Sawahlunto West Sumatra Indonesia Context

Sawahlunto is a small town located 116 km from the West Sumatra city of Padang. It was the second coal-mining town which was opened by the Netherlands after North Borneo. The discovery of this coal deposit interest to embed the Netherlands Colonial investment. At the end of the 19th century they initiated three major projects in West Sumatra. The third major project is the construction of Railway Infrastructure along the 155 km between Sawahlunto towards port in Padang city, the construction of the Teluk Bayur harbour and the construction of the mining town of Sawahlunto. The presence of the whole infrastructure has made a new history for the people of Indonesia at that time. Nevertheless the whole infrastructure is still survives and has been a witness to the struggle of the nation.Historical heritage attracts the Government town of Sawahlunto, observer preservation and historians. These stakeholders are then shared with the public the city declared to still preserve the historical heritage of this evidence. This commitment has resulted in the preservation of program implementation is running very well. So the whole infrastructure has in the mining town of conservation and is enabled to support government programs especially in the field of historical tourism and culture. This preservation program has been bearing the name of the town of Sawahlunto and has become one of the tourist destinations in West Sumatra. This success became a passion for the City Government to propose Sawahlunto being one to UNESCO World Heritage sites. As evidence of the extraordinary diusulukan of the Ombilin coal mine is a city with an infrastructure of railway and warehousing coal in Teluk Bayur Harbour.The methodology used is Qualitative Observation from a current state to make future development plans. The basic observation will be taken from the process of preservation that has been done before especially for the town of Sawahlunto. Because of the town of Sawahlunto as a pioneer against the initiative. This article aims to identify sustainable development plan for the development of the heritage site. This management plan will affect property and maintenance as well as the development of new functions as a historical and cultural tourism destinations. The study will be made in the form of a framework for the management of the world heritage site and development guidelines for the world heritage site. The end of the research will produce guidelines for sustainability development historic district and the world heritage site management plan.

Screening and the pinch point paradox in spin ice

A pinch point singularity in the structure factor characterizes an important class of condensed matter that is a counterpoint to the paradigm of broken symmetry. This class includes water ice, charge ice and spin ice. Of these, dipolar spin ice affords the the pre-eminent model system because it has a well-established Hamiltonian, is simple enough to allow analytical theory and numerical simulation, and is well represented in experiment by Dy$_{2}$Ti$_{2}$O$_{7}$ and Ho$_{2}$Ti$_{2}$O$_{7}$. Nevertheless it is a considerable challenge to resolve the pinch points in simulation or experiment as they represent a very long range correlation. Here we present very high resolution simulations of the polarized neutron scattering structure factor of dipolar spin ice and new analytical theory of the pinch point profiles. We compare these with existing theory and experiment. We find that our simulations are consistent with theories that reveal the pinch points to be infinitely sharp, as a result of unscreened dipolar fields. However, neither simulation nor these theories are consistent with experiments, which instead is quantitatively captured by a theory that allows for screening of the dipolar fields and consequent strong broadening of the pinch points. This striking paradox is not easily resolved: broadening of the pinch points by random disorder seems to have been ruled out by existing theory, while deficiencies in the Hamiltonian description are not relevant. Intriguingly, we are left to consider the role of quantum fluctuations or the possibility of a fundamental correction to either the standard method of simulating dipolar systems, or the theory of polarized neutron scattering. More generally, our results may have relevance far beyond ice systems. For example, spin ice is a model Debye-H\"uckel (magnetic) electrolyte, so our basic observation that the screening length may diverge while...

Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T

Multiband (MB) or Simultaneous multi-slice (SMS) acquisition schemes allow the acquisition of MRI signals from more than one spatial coordinate at a time. Commercial availability has brought this technique within the reach of many neuroscientists and psychologists. Most early evaluation of the performance of MB acquisition employed resting state fMRI or the most basic tasks. In this study, we tested whether the advantages of using MB acquisition schemes generalize to group analyses using a cognitive task more representative of typical cognitive neuroscience applications. Twenty-three subjects were scanned on a Philips 3 ​T scanner using five sequences, up to eight-fold acceleration with MB-factors 1 to 4, SENSE factors up to 2 and corresponding TRs of 2.45s down to 0.63s, while they viewed (i) movie blocks showing complex actions with hand object interactions and (ii) control movie blocks without hand object interaction. Data were processed using a widely used analysis pipeline implemented in SPM12 including the unified segmentation and canonical HRF modelling. Using random effects group-level, voxel-wise analysis we found that all sequences were able to detect the basic action observation network known to be recruited by our task. The highest t-values were found for sequences with MB4 acceleration. For the MB1 sequence, a 50% bigger voxel volume was needed to reach comparable t-statistics. The group-level t-values for resting state networks (RSNs) were also highest for MB4 sequences. Here the MB1 sequence with larger voxel size did not perform comparable to the MB4 sequence. Altogether, we can thus recommend the use of MB4 (and SENSE 1.5 or 2) on a Philips scanner when aiming to perform group-level analyses using cognitive block design fMRI tasks and voxel sizes in the range of cortical thickness (e.g. 2.7 ​mm isotropic). While results will not be dramatically changed by the use of multiband, our results suggest that MB will bring a moderate but significant benefit.

Change Detection of RSSI Fingerprint Pattern for Indoor Positioning System

A set of Wi-Fi RSSI (Received Signal Strength Indicator) measurements is one of basic sensory observation available for indoor localization. One major drawback of the RSSI based localization is maintenance of the RSSI fingerprint database, which should be periodically updated against measurement pattern changes caused by relocation, removal and malfunction of Wi-Fi APs (access points). To address this problem, a new change detection method is proposed in this paper. First, by machine learning techniques, the RSSI database is reconstructed to a probabilistic feature database by the implementations of PCA (Principal Component Analysis) and GP (Gaussian Process). Then, KL (Kullback-Leibler) divergence is used as a metric to measure the similarity of the existing database and a newly arrived test sets. The proposed method is evaluated by a real experiment at a multi-storey building. For experimental study, different cases that provoke changes of RSSI patterns are considered, and the positioning accuracy is examined by the k-NN (Nearest Neighbor) method. From the experimental results, it is found that the bigger the RSSI pattern changes, the large the KL divergences become. Also, when a modified change detection algorithm as the benchmark, which does not implement the PCA feature extraction, is compared, the proposed algorithm yields accurate and fast computing performances. In addition, the required number of survey points is empirically found associated with the threshold value to trigger the detection alarm.

Advances and Practices on the Research, Prevention and Control of Land Subsidence in Coastal Cities

AbstractLand subsidence severely threatens most of the coastal plains around the world where high productive industrial and agricultural activities and urban centers are concentrated. Coastal subsidence damages infrastructures and exacerbates the effect of the sea‐level rise at regional scale. Although it is a well‐known process, there is still much more to be improved on the monitoring, mapping and modeling of ground movements, as well as the understanding of controlling mechanisms. The International Geoscience Programme recently approved an international project (IGCP 663) aiming to bring together worldwide researchers to share expertise on subsidence processes typically occurring in coastal areas and cities, including basic research, monitoring and observation, modelling and management. In this paper, we provide the research communities and potential stakeholders with the basic information to join the participating teams in developing this project. Specifically, major advances on coastal subsidence studies and information on well‐known and new case studies of land subsidence in China, Italy, The Netherlands, Indonesia, Vietnam and Thailand are highlighted and summarized. Meanwhile, the networking, dissemination, annual meeting and field trip are briefly introduced.

3-D Modeling of Dehydration Kinetics and Shrinkage of Ellipsoidal Fermented Amazonian Cocoa Beans

A recently proposed moving-boundary model for food isothermal dehydration was applied to analyze the dehydration kinetics of ellipsoidal cocoa beans, characterized by a moderate shrinkage and a non-uniform initial distribution of water content between the core and the shell of the bean. The aim is to predict the influence of air velocity and non-uniformity of the initial water distribution on the dehydration rates, as well as the temporal evolution of the water content in the core and in the shell and of the characteristic lengths of the ellipsoidal bean. The model proved capable of accurately describing the two-phases dehydration process: an initial fast dehydration of the shell, characterized by higher dehydration rates, followed by a slower dehydration of the core, characterized by a linear relationship j d = δ ( T ) X r between the dehydration rate j d and the moisture ratio X r . A shortcut method to estimate the effective water diffusivity D is also proposed, deriving from the basic observation that the asymptotic exponential behaviour of the dehydration curve X r ( t ) for an ellipsoidal bean coincides with that of an equivalent sphere, with the same surface-to-volume ratio.

How Could the Use of Game Elements Help Students' Affective and Cognitive Engagement During Game Play?

Researchers have posited different types of engagement, distinguishing between behavioral, cognitive, and affective engagement and theoretical frameworks have helped explain the psychological aspects of engagement. However, game researchers should examine all types of engagement using multiple methodologies as a means to understand what students are learning from educational games during game play. Conclusive results require psychological aspects and learning characteristics to be considered, but also require a deeper understanding of the intricate links between learning and game mechanics for engagement. This article presents the findings from a qualitative study with thirty participants that focuses on the importance of affective and cognitive engagement during game play with educational games. To do this, the researchers used Ferran Alsina, a game that would help to develop learning competences of primary education skills. Researchers obtained the experiences of students through a game play session, basic game metrics, think-aloud protocol, observation and focus groups. Results shows that the game provided participants an active participation associated with both affective and cognitive engagement. Without attention to cognition the atuhors risk losing valuable data that relate to a student's learning. Researchers should consider multiple qualitative methodologies and game play experience analysis as student experiences are qualitative.

Unsupervised representation learning with Laplacian pyramid auto-encoders

Scale-space representation has been popular in computer vision community due to its theoretical foundation. The motivation for generating a scale-space representation of a given data set originates from the basic observation that real-world objects are composed of different structures at different scales. Hence, it is reasonable to consider learning features with image pyramids generated by smoothing and down-sampling operations. In this paper we propose Laplacian pyramid auto-encoders, a straightforward modification of the auto-encoder framework, for unsupervised representation learning. The method uses multiple encoding–decoding sub-networks within a Laplacian pyramid framework to reconstruct the original image and the low pass filtered images. The last layer of each encoding sub-network also connects to an encoding layer of the sub-network in the next level, which aims to reverse the process of Laplacian pyramid generation. Experimental results showed that Laplacian pyramid leaded to a more stable and efficient training procedure and improved the performance of the learned representation with scale information.

Pengaruh Pembelajaran Demonstrasi Interaktif terhadap Keterampilan Proses Sains Dasar Siswa SMA pada Materi Perubahan Lingkungan

The achievement of students science process skills in Indonesia is relatively low, this is partly because learning has not yet explored and facilitated students science process skills. This study aims to identify the effect of interactive demonstrations to basic science process skills of senior high school students in environmental change concept, with global warming sub concept. The subjects of this study were X grade of science in second semester, academic year 2017/2018. The method used in this research was quasi experiment with non equivalent pre-test post-test control group design. The research data was collected by using basic science process skills test, observation form, and questionnaire. The results of data analysis using the Mann Whitney test with a significance level of 0,05 to the value of the post-test of basic science process skills showed a significant difference in basic science process skills of students between experimental group and control group. N-gain of basic science process skills in the experimental group is 0,56, while in the control group is 0,43. Improved basic science process skills in the experimental group and control group are in the medium category. Neverthless, the average of N-gain in the experimental group is higher than the control group. The results of this study indicate that 97,5% of learning activities performed well. Based on the results of the research, it can be concluded that the interactive demonstrations learning trains to improve students basic science process skills.

Autonomous digital seismic stations SV

Seismic exploration is one of the most informative geophysical methods. It gives thorough information on deep and spatial structure of the Earth using features of seismic waves propagation in geological layers with different physical properties. Wave field excited with seismic source propagates in space and time, therefore for its registration we need availability of many observation sites simultaneously resulting in considerable rise in prices cost of seismic information. In turn, absence of numerical seismic data renders impossible development of basic seismicity, seismic monitoring and long-term observation of seismically dangerous processes in big areas of man-made objects. The paper presents autonomous seismic stations developed at the Institute of Geophysics NAS of Ukraine. Universality of seismic stations allows their use for a wide range of seismic and seismological problems. Small weight and size make their transportation easier as well as their mounting in unequipped observation sites in boggy hard-to-reach areas. Long-continued registration of seismic information and big capacity of operative internal memory makes possible their use for passive long-term observations. Several variants of wireless connection have been realized in seismic stations for control of technical condition of the station, inspection of seismic record quality in real time and remote programming for alternation its working regime. Likewise historical review has been presented on development of autonomous seismic stations the most popular in Europe and North America used in large-scale international projects on studies of deep structure of the Earth during the latest 50 years. In addition up-to date passive and active seismic stations used in economic seismicity have been described.

A Neural Probabilistic outlier detection method for categorical data

Unsupervised outlier detection for categorical data is important and essential for broad applications in various domains. The complex interactions between attributes and the relevance of attributes make it a stem challenge. Existing methods, including patterns-based and couplings-based methods, either fail to capture the complex interactions or cannot handle the diverse attributes well. In this paper, we propose a novel Neural Probabilistic Outlier Detection method for categorical data, called NPOD. We present a new log-bilinear neural model to learn the categorical distributions, and we observe that the inliers and the outliers can be well separated according to learning loss. Based on this basic observation, we give both empirical and theoretical analysis and present a new neural network architecture that captures the interactions of attributes. Moreover, the discriminative information is used in the proposed bias training process to make the inliers and the outliers more separable. Lastly, to distinguish relevance of attributes, two indicators are proposed for computing ensemble outlier score to get a reliable result. Experimental results show that NPOD significantly outperforms the state-of-the-art competitors on 12 real-world data sets in terms of AUC and P@k.

APPLICATION OF LATENT GROWTH MODELING ON MOTHER-REPORTED MONITORING

One of the basic observation in the social and behavioral sciences is that things are changed over the time. Longitudinal data analysis can yield valuable information about this change. Although many techniques have been developed to capitalize on these desirable features of longitudinal data, the structural equation modeling approach of building latent growth models (LGMs) has become one of the commonly used statistical models. A subset of data is taken from the National Longitudinal Survey 97, prepared by the Bureau of Labor Statistics, U.S. Four waves of mother monitoring reported by youth in the year 1997 to the year 2000 are used for the analysis. A total of 2675 adult respondents are used in our analysis. Mother monitoring scores reported by youth are used as a dependent variable. There are 52% male and 48% female in the data. Different linear, quadratic, autoregressive and moving average LGMs with gender as a covariate are used and compared to study the effects of mother monitoring over a 4 year period of time. It is found mom monitoring is increasing slowly over the period of time. An association was found between slop and intercept of fitted latent growth model and female has a significant effect on slop but not on the intercept of the fitted growth model. Five fit indices Chi-square, GFI, CFI, RMSEA, and AIC are used to select an appropriate model.

Developmental profiles of SUMOylation pathway proteins in rat cerebrum and cerebellum.

Protein SUMOylation regulates multiple processes involved in the differentiation and maturation of cells and tissues during development. Despite this, relatively little is known about the spatial and temporal regulation of proteins that mediate SUMOylation and deSUMOylation in the CNS. Here we monitor the expression of key SUMO pathway proteins and levels of substrate protein SUMOylation in the forebrain and cerebellum of Wistar rats during development. Overall, the SUMOylation machinery is more highly-expressed at E18 and decreases thereafter, as previously described. All of the proteins investigated are less abundant in adult than in embryonic brain. Furthermore, we show for first time that the profiles differ between cerebellum and cerebrum, indicating differential regional regulation of some of the proteins analysed. These data provide further basic observation that may open a new perspective of research about the role of SUMOylation in the development of different brain regions.