Parcel Map Research Articles

Existence of Functional Connectome Fingerprint during Infancy and Its Stability over Months.

The functional connectome fingerprint is a cluster of individualized brain functional connectivity patterns that are capable of distinguishing one individual from others. Although its existence has been demonstrated in adolescents and adults, whether such individualized patterns exist during infancy is barely investigated despite its importance in identifying the origin of the intrinsic connectome patterns that potentially mirror distinct behavioral phenotypes. To fill this knowledge gap, capitalizing on a longitudinal high-resolution structural and resting-state functional MRI dataset with 104 human infants (53 females) with 806 longitudinal scans (age, 16-876 d) and infant-specific functional parcellation maps, we observe that the brain functional connectome fingerprint may exist since infancy and keeps stable over months during early brain development. Specifically, we achieve an ∼78% individual identification rate by using ∼5% selected functional connections, compared with the best identification rate of 60% without connection selection. The frontoparietal networks recognized as the most contributive networks in adult functional connectome fingerprinting retain their superiority in infants despite being widely acknowledged as rapidly developing systems during childhood. The existence and stability of the functional connectome fingerprint are further validated on adjacent age groups. Moreover, we show that the infant frontoparietal networks can reach similar accuracy in predicting individual early learning composite scores as the whole-brain connectome, again resembling the observations in adults and highlighting the relevance of functional connectome fingerprint to cognitive performance. For the first time, these results suggest that each individual may retain a unique and stable marker of functional connectome during early brain development.SIGNIFICANCE STATEMENT Functional connectome fingerprinting during infancy featuring rapid brain development remains almost uninvestigated even though it is essential for understanding the early individual-level intrinsic pattern of functional organization and its relationship with distinct behavioral phenotypes. With an infant-tailored functional connection selection and validation strategy, we strive to provide the delineation of the infant functional connectome fingerprint by examining its existence, stability, and relationship with early cognitive performance. We observe that the brain functional connectome fingerprint may exist since early infancy and remains stable over months during the first 2 years. The identified key contributive functional connections and networks for fingerprinting are also verified to be highly predictive for cognitive score prediction, which reveals the association between infant connectome fingerprint and cognitive performance.

Inter-species cortical registration between macaques and humans using a functional network property under a spherical demons framework.

Systematic evaluation of cortical differences between humans and macaques calls for inter-species registration of the cortex that matches homologous regions across species. For establishing homology across brains, structural landmarks and biological features have been used without paying sufficient attention to functional homology. The present study aimed to determine functional homology between the human and macaque cortices, defined in terms of functional network properties, by proposing an iterative functional network-based registration scheme using surface-based spherical demons. The functional connectivity matrix of resting-state functional magnetic resonance imaging (rs-fMRI) among cortical parcellations was iteratively calculated for humans and macaques. From the functional connectivity matrix, the functional network properties such as principal network components were derived to estimate a deformation field between the human and macaque cortices. The iterative registration procedure updates the parcellation map of macaques, corresponding to the human connectome project’s multimodal parcellation atlas, which was used to derive the macaque’s functional connectivity matrix. To test the plausibility of the functional network-based registration, we compared cortical registration using structural versus functional features in terms of cortical regional areal change. We also evaluated the interhemispheric asymmetry of regional area and its inter-subject variability in humans and macaques as an indirect validation of the proposed method. Higher inter-subject variability and interhemispheric asymmetry were found in functional homology than in structural homology, and the assessed asymmetry and variations were higher in humans than in macaques. The results emphasize the significance of functional network-based cortical registration across individuals within a species and across species.

Unified framework for early stage status prediction of autism based on infant structural magnetic resonance imaging.

Autism, or autism spectrum disorder (ASD), is a developmental disability that is diagnosed at about 2 years of age based on abnormal behaviors. Existing neuroimaging‐based methods for the prediction of ASD typically focus on functional magnetic resonance imaging (fMRI); however, most of these fMRI‐based studies include subjects older than 5 years of age. Due to challenges in the application of fMRI for infants, structural magnetic resonance imaging (sMRI) has increasingly received attention in the field for early status prediction of ASD. In this study, we propose an automated prediction framework based on infant sMRI at about 24 months of age. Specifically, by leveraging an infant‐dedicated pipeline, iBEAT V2.0 Cloud, we derived segmentation and parcellation maps from infant sMRI. We employed a convolutional neural network to extract features from pairwise maps and a Siamese network to distinguish whether paired subjects were from the same or different classes. As compared to T1w imaging without segmentation and parcellation maps, our proposed approach with segmentation and parcellation maps yielded greater sensitivity, specificity, and accuracy of ASD prediction, which was validated using two datasets with different imaging protocols/scanners and was confirmed by receiver operating characteristic analysis. Furthermore, comparison with state‐of‐the‐art methods demonstrated the superior effectiveness and robustness of the proposed method. Finally, attention maps were generated to identify subject‐specific autism effects, supporting the reasonability of the predictive results. Collectively, these findings demonstrate the utility of our unified framework for the early‐stage status prediction of ASD by sMRI.Lay SummaryThe status prediction of autism spectrum disorder (ASD) at an early age is highly desirable, as early intervention may significantly reduce autism symptoms. However, current methods for diagnosing young children are limited to behavioral assays. In this study, we propose an automated method for ASD status prediction at the age of 24 months that uses infant structural magnetic resonance imaging to identify neural features.

HybraPD atlas: Towards precise subcortical nuclei segmentation using multimodality medical images in patients with Parkinson disease.

Human brain atlases are essential for research and surgical treatment of Parkinson's disease (PD). For example, deep brain stimulation for PD often requires human brain atlases for brain structure identification. However, few atlases can provide disease‐specific subcortical structures for PD, and most of them are based on T1w and T2w images. In this work, we construct a HybraPD atlas using fused quantitative susceptibility mapping (QSM) and T1w images from 87 patients with PD. The constructed HybraPD atlas provides a series of templates, that is, T1w, GRE magnitude, QSM, R2*, and brain tissue probabilistic maps. Then, we manually delineate a parcellation map with 12 bilateral subcortical nuclei, which are highly related to PD pathology, such as sub‐regions in globus pallidus and substantia nigra. Furthermore, we build a whole‐brain parcellation map by combining existing cortical parcellation and white‐matter segmentation with the proposed subcortical nuclei map. Considering the multimodality of the HybraPD atlas, the segmentation accuracy of each nucleus is evaluated using T1w and QSM templates, respectively. The results show that the HybraPD atlas provides more accurate segmentation than existing atlases. Moreover, we analyze the metabolic difference in subcortical nuclei between PD patients and healthy control subjects by applying the HybraPD atlas to calculate uptake values of contrast agents on positron emission tomography (PET) images. The atlas‐based analysis generates accurate disease‐related brain nuclei segmentation on PET images. The newly developed HybraPD atlas could serve as an efficient template to study brain pathological alterations in subcortical regions for PD research.

Guidelines and pitfalls of refraction microtremor surveys

The geotechnical industry has widely adopted the refraction microtremor shear-wave velocity measurement technique, which is accepted by building authorities for evaluation of seismic site class around the world. Clark County and the City of Henderson, Nevada, populated their Earthquake Parcel Map with over 10,000 site measurements for building code enforcement, made over a 3-year period. 2D refraction microtremor analysis now allows engineers to image lateral shear-wave velocity variations and do passive subsurface imaging. Along with experience at a basic level, the ability to identify the “no energy area” and the “minimum-velocity envelope” on the slowness-frequency (p-f) image helps practitioners to assess the quality of their ReMi data and analysis. Guides for grading (p-f) image quality, and for estimating depth sensitivity, velocity-depth tradeoffs, and depth and velocity resolution also assist practitioners in deciding whether their refraction microtremor data will meet their investigation objectives. Commercial refraction microtremor surveys use linear arrays, and a new criterion of 2.2% minimum microtremor energy in the array direction allows users to assess the likelihood of correct results. Unfortunately, any useful and popular measurement technique can be abused. Practitioners must follow correct data collection, analysis, interpretation, and measurement procedures, or the results cannot be labeled “refraction microtremor” or “ReMi” results. We present some of the common mistakes and provide solutions with the objective of establishing a “best practices” template for getting consistent, reliable models from refraction microtremor measurements.

Application of Geoinformatics for Site Assessment of Large Scale Organic Agriculture Plot

To enhance organic agriculture promoted by the Governmental policy, Nong Wang Sok Phra Sub-district, Phon District, Khon Kaen Province, Thailand has designated an organic agriculture plot covering the area of 681.50 hectare. It is, however, necessary to identify the suitable organic agriculture in conjunction with large scale by integrating Geoinformatics and Unmanned Aerial Vehicle. The study process consisted of creating a boundary study area map by topography, georeferencing and Land use classification, validating the study area to verify Land use by video record and field observation, assessing the validated study area/Land use map plot by vector analysis through QGIS to create the potential suitable large scale organic agriculture categorizing as the moderate and the least suitable area 151.82 hectare, 89.93 hectare and 34.05 hectare, being equivalent to 55.05%, 32.61% and 12.35% of total suitable area, respectively; validating the potential suitable large scale organic agriculture plot by focus group interview based on the most suitable area, processing UAV imagery and parcel maps. The output was the suitable organic agriculture plot accepted by the organic agriculture members, located at Ban Kok Lam Village no.3, covering the area of 20.64 hectare, where was only 13.60 %of the most suitable agriculture area. The large scale criteria could not be attained due to the accepted organic agriculture area was lower than the large scale standard of 48 hectare. By the mean of this study, the most suitable organic agriculture plot of151.82 hectare was available for the large scale organic agriculture plot. That would enable Nong Wang Sok Phra Sub-district to carry on for enhancement of the large scale organic agriculture plot.

Open-air grape classification and its application in parcel-level risk assessment of late frost in the eastern Helan Mountains

The eastern Helan Mountains are one of the most important plantings and production bases for high-quality grapes in China. In winter, grape root is prone to freezing damage owing to natural phenomenon such as early and late frost, and methods to assess disaster risk at the grape parcel level is one of the current research hotspots. However, there are two problems at present; first is the lack of grape parcel maps and second is that scale of disaster risk assessment is limited to the level of administrative divisions and grid systems. Therefore, according to the perennial characteristics of the grapes and clear texture of the open-air grape parcels based on public data sets (Sentinel-2A/B) and high-quality winery address information, combined with Google Earth engine (GEE) platform, Google Earth, and Ovitalmap, this study designs a collection scheme of open-air grape parcel samples and non-grape parcel samples, analyzes the environmental characteristics of the distribution of high-quality wineries, constructs a classification feature database in three aspects (time, terrain, and vegetation), uses the random forest classification method to classify open-air grape parcels in the eastern Helan Mountains in 2019, and conducts a late frost disaster risk assessment of the open-air grape parcel. The results show that: (1) The high-quality wineries are mainly distributed in the elevation of 1106–1240 m, with the average slope of 0.82°, the organic matter content of 10.79–14.27 g/kg, the P content of 24.87–37.58 mg/kg, the K content of 116–166 mg/kg, the pH 8.38–8.55, N content of 0.65–0.98 g/kg, annual average active accumulated temperature ≥10 °C of 3490–3590 °C, annual average rainfall of 189–201 mm, the annual average sunshine duration of 7.3–7.6 h, annual average air temperature of 8.8–9.4 °C, annual average temperature difference of 12.7–13.2 °C, annual average frost-free period at 263–270 d and annual average relative air Humidity of 50–54%. (2) The overall classification accuracy of open-air grape parcels reached 98.96% and the verification accuracy of ground truth parcel samples reached 87.89%. The open-air grape parcels in the eastern Helan Mountains are mainly distributed in Helan County, Xixia District, Yongning County, and Qingtongxia City. (3) The highest risk of late frost was found in Xixia District and the lowest risk in Yongning County. Helan County was higher than Qingtongxia City in the medium risk of late frost. The typical small area high risk includes Liangtian Town, the experimental field of Ningxia Academy of Agricultural and Forestry Sciences in Zhenbeibao Town, Yuhuang Winery in Ganchengzi Village, and the State-run Warm Spring Farm in Helan County. Thus, the sample collection and augmentation scheme are feasible, the open-air grape classification accuracy is high and its result is consistent with field investigation, which can provide accurate parcel-level disaster risk assessment and provide decision support for agricultural departments and farmers.

A Deep Network for Joint Registration and Parcellation of Cortical Surfaces.

Cortical surface registration and parcellation are two essential steps in neuroimaging analysis. Conventionally, they are performed independently as two tasks, ignoring the inherent connections of these two closely-related tasks. Essentially, both tasks rely on meaningful cortical feature representations, so they can be jointly optimized by learning shared useful cortical features. To this end, we propose a deep learning framework for joint cortical surface registration and parcellation. Specifically, our approach leverages the spherical topology of cortical surfaces and uses a spherical network as the shared encoder to first learn shared features for both tasks. Then we train two task-specific decoders for registration and parcellation, respectively. We further exploit the more explicit connection between them by incorporating the novel parcellation map similarity loss to enforce the boundary consistency of regions, thereby providing extra supervision for the registration task. Conversely, parcellation network training also benefits from the registration, which provides a large amount of augmented data by warping one surface with manual parcellation map to another surface, especially when only few manually-labeled surfaces are available. Experiments on a dataset with more than 600 cortical surfaces show that our approach achieves large improvements on both parcellation and registration accuracy (over separately trained networks) and enables training high-quality parcellation and registration models using much fewer labeled data.

Penerapan Sistem Informasi (Komputerisasi Kegiatan Pertanahan) Dalam Mencapai Good Governance Pada Kementerian Agraria dan Tata Ruang/ Badan Pertanahan Kota Magelang

Management of data and information in an institution can support national development, but some are still less effective and efficient. This study aims to determine the application of information systems to achieve Good Governance in the Ministry of Agrarian Affairs and Spatial Planning / Land Agency of Magelang City. The method used in this study was interviews with staff at the Magelang City Land Agency. The results find that the development of information technology and supporting infrastructure created opportunities to develop a more reliable, efficient, and timely computerized application for land activities (KKP) within the National Land Agency (BPN). The growing need for more accessible land information demanded by the community (policy recipients) and the government (policymakers) has increased higher than before. However, on the other hand, there are obstacles, such as the unfinished mapping of land parcels. The implication of this research is the Land Office needs to guide operators to better service quality.

Farmland Parcel Mapping in Mountain Areas Using Time-Series SAR Data and VHR Optical Images

Accurate, timely, and reliable farmland mapping is a prerequisite for agricultural management and environmental assessment in mountainous areas. However, in these areas, high spatial heterogeneity and diversified planting structures together generate various small farmland parcels with irregular shapes that are difficult to accurately delineate. In addition, the absence of optical data caused by the cloudy and rainy climate impedes the use of time-series optical data to distinguish farmland from other land use types. Automatic delineation of farmland parcels in mountain areas is still a very difficult task. This paper proposes an innovative precise farmland parcel extraction approach supported by very high resolution(VHR) optical image and time series synthetic aperture radar(SAR) data. Firstly, Google satellite imagery with a spatial resolution of 0.55 m was used for delineating the boundaries of ground parcel objects in mountainous areas by a hierarchical extraction scheme. This scheme divides farmland into four types based on the morphological features presented in optical imagery, and designs different extraction models to produce each farmland type, respectively. The potential farmland parcel distribution map is then obtained by the layered recombination of these four farmland types. Subsequently, the time profile of each parcel in this map was constructed by five radar variables from the Sentinel-1A dataset, and the time-series classification method was used to distinguish farmland parcels from other types. An experiment was carried out in the north of Guiyang City, Guizhou Province, Southwest China. The result shows that, the producer’s accuracy of farmland parcels obtained by the hierarchical scheme is increased by 7.39% to 96.38% compared with that without this scheme, and the time-series classification method produces an accuracy of 80.83% to further obtain the final overall accuracy of 96.05% for the farmland parcel maps, showing a good performance. In addition, through visual inspection, this method has a better suppression effect on background noise in mountainous areas, and the extracted farmland parcels are closer to the actual distribution of the ground farmland.

Automated Tax Mapping from UAV Multispectral Imagery

Tax mapping is an essential element for efficient management of real estate property and tax management, paving the way for effective implementation of g-governance practices in India. Conventional mapping of individual buildings and their attributes involves large effort and is time-consuming. The use of high-resolution UAV imagery facilitates the process of automatic extraction of land parcel, roof area and height by providing accurate and latest building and landuse information for improved tax assessment and collection. Image segmentation has been performed on UAV imagery applied to differentiate rooftop surfaces from other features such as roads and vegetation using gray level thresholding. An example-based feature extraction algorithm was adopted to extract the land parcel and rooftop surfaces from the segmented image. Further, DSM and DTM derived from UAV imagery were used to determine the height of the buildings by extraction of terrain points and rooftop points. The extracted building height was used to estimate the numbers of floors in the building using thresholding. The number of floors and rooftop area were used to derive the total floor area of each building. The property tax to be levied for each building was calculated automatically using total floor area in efficient and scientific manner. The UAV imagery used in the study enabled rapid mapping of buildings parcels for tax assessment compared to conventional mapping methods.

Cerebello-basal ganglia connectivity fingerprints related to motor/cognitive performance in Parkinson's disease

IntroductionThe role of the cerebellum in Parkinson's disease (PD) has attracted increasing attention; however, the role of functional connectivity (FC) between the basal ganglia and particular cerebellar subregions remains to be elucidated. We aimed to clarify the FC and its contribution to motor and cognitive performances in patients with PD. MethodsWe included 99 patients with PD and 99 age- and sex-matched healthy controls in this study. We created a cerebellar functional parcellation by performing cerebellum-only independent component analysis. Using the functional parcellation map, we performed seed-based connectivity analysis using each region as a seed and extracted the mean correlation coefficients within the thalamus and basal ganglia, including the caudate, pallidum, putamen and subthalamic nucleus. We examined the group differences and correlations with the motor and general cognitive scores. In addition, we conducted a mediation analysis to clarify the relationship among FC, motor severity, and cognition. ResultsThe PD group showed decreased FC between a wide range of cerebellar subregions and the basal ganglia. Motor severity was correlated with FC between the subthalamic nucleus and posterior Crus I/II, and general cognitive performance scores correlated with FC between the caudate nucleus and medial-posterior part of the Crus I/II (p < 0.05, corrected for multiple comparisons). The cerebello-caudate network had a direct effect on cognitive performance (p = 9.0 × 10−3), although partially mediated by motor performance (p = 8.2 × 10−3). ConclusionFC between cerebellar Crus I/II and divergent basal ganglia related to motor and cognitive performance in PD.

Evaluasi Pemanfaatan Citra Tegak Satelit Resolusi Tinggi untuk Percepatan Pembuatan Peta Blok Pajak Bumi dan Bangunan (PBB-P2) secara Partisipatif di Desa Triharjo, Kabupaten Bantul, DIY

The recent advances of remote sensing technology development can support government needs including cadastral related purposes. One of the purposes is to supply geospatial data especially land parcel maps for land and tax value inventory. This research tries to evaluate the utilization of Quickbird Satellite image for updating land and building (PBB-P2) block maps in Bantul Regency, Yogyakarta Province of Indonesia. The image was recorded in 2014 with resolution of 0.6 meter and has been ortho-rectified. Evaluation is conducted by analyzing the utilization of the image as the base map for deriving land parcel maps according to the Decree of Tax Director General number: KEP-533/PJ/2000. The process was firstly done by digitizing land parcel boundaries on Quickbird image to produce block maps. The process was done by the community through participatory mapping. The resulting block maps then were compared with land registration map from National Land Agency. The evaluation was focused on the accuracy of land parcel position as well as the resulting land areas. For this purpose the land registration map is regarded as the reference data. By focusing on the 51 sample data in Triharjo Village, statistical test was conducted to evaluate the accuracy of the resulting areas of the digitized land parcel map. The results show that 47 samples comply with a tolerance requirement of 10% according to the Decree of Tax Directorate number KEP-533/PJ/2000’. In addition, the t-test analysis with a significant level of 5% indicates that there is no significant difference of area between the digitized land parcel data with land registration map. Based on the results, it is concluded that ortho-rectified QuickBird image is sufficient for producing of land and building tax (PBB-P2) block maps.

Admissible relative errors of the parcel area while creating a land parcel map base using an orthoimage as a reference

Currently the official land parcel map of Uruguay does not allow a suitable interoperability with other available geographic information. We are considering using a national high accuracy and high resolution orthomosaic in two ways: either to support the creation of a brand new land parcel map or to allow amending the existing one. In particular, the present work is part of a set of experiments which considers different techniques to amend the existing land parcel map. In order to perform a fair comparison it is necessary to have test cases produced with a reference procedure properly and objectively evaluated. The metric of success will be used as attainable goal for any other alternative. Using the orthomosaic in order to identify the apparent limits of parcels in the land parcel map we were able to modify its location, thus making the map interoperable with the image. In order to measure the accuracy of the fit, we used the relative difference between the area declared at the parcel map (taken as the reference value) respect to the one computed from the GIS. We found that the discrepancy between the areas computed from the initial and the final dataset w.r.t. the declared area decreases, but not up to expected level. Once filtered for outliers the remaining discrepancies follow a normal distribution, where its bias and standard deviation varies from (-0.65%, 11.24%) before editing to (‑1.72%, 8.59%) later. Despite the drastic change in planimetric accuracy the improvement of the area accuracy is marginal. Considering the admissibility criteria of the Uruguayan National Cadastral Office, for the legacy dataset only 39.4% parcel maps could be accepted, a value which improves up to 49.7% after the manual edition. It is still far from the goal of 100%, and the reasons for such pessimistic finding will be discussed.

Admissible relative errors of the parcel area while creating a land parcel map base using an orthoimage as a reference

Currently the official land parcel map of Uruguay does not allow a suitable interoperability with other available geographic information. We are considering using a national high accuracy and high resolution orthomosaic in two ways: either to support the creation of a brand new land parcel map or to allow amending the existing one. In particular, the present work is part of a set of experiments which considers different techniques to amend the existing land parcel map. In order to perform a fair comparison it is necessary to have test cases produced with a reference procedure properly and objectively evaluated. The metric of success will be used as attainable goal for any other alternative. Using the orthomosaic in order to identify the apparent limits of parcels in the land parcel map we were able to modify its location, thus making the map interoperable with the image. In order to measure the accuracy of the fit, we used the relative difference between the area declared at the parcel map (taken as the reference value) respect to the one computed from the GIS. We found that the discrepancy between the areas computed from the initial and the final dataset w.r.t. the declared area decreases, but not up to expected level. Once filtered for outliers the remaining discrepancies follow a normal distribution, where its bias and standard deviation varies from (-0.65%, 11.24%) before editing to (‑1.72%, 8.59%) later. Despite the drastic change in planimetric accuracy the improvement of the area accuracy is marginal. Considering the admissibility criteria of the Uruguayan National Cadastral Office, for the legacy dataset only 39.4% parcel maps could be accepted, a value which improves up to 49.7% after the manual edition. It is still far from the goal of 100%, and the reasons for such pessimistic finding will be discussed.

EVALUASI BERJALAN TERHADAP PROGRAM PENDAFTARAN TANAH SISTEMATIS LENGKAP (PTSL) DI KOTA PADANG

Abstract&#x0D; The complete systematic land registration program (PTSL) is one of the programs to accelerate registration, measurement and mapping of land parcels so that maps of their fields are known and certificates can be given as proof of land ownership rights by the community. This program implementation has been regulated in The Ministry of Agrarian Affairs and Spatial Planning/National Land Agency No.6 of 2018 concerning Complete Systematic Land Registration. The problem in this study is that there are still many lands that have not yet been registered in the city of Padang and do not have land certificates. And the purpose of this study is to find out the implementation of the PTSL Program in the City of Padang and to find out the factors that influence the implementation of the PTSL Program in the City of Padang. This research is a qualitative research with descriptive method, the research was conducted at the National Land Agency (BPN) of Padang City.Determination of research informants by purposive sampling, which is related to the PTSL Program, namely Head of Legal and Land Relations (BPN) Padang City , and the village officials as PTSL executive members and community registrants in the PTSL program in Padang City. This study discusses on going evaluation a program because the program is still being implemented in the City of Padang. So that it refers to the evaluation theory which consists of 6 (six)aspects the effectiveness, efficiency, adequacy, equity, responsiveness and accuracy. The results of the study show how to implement the PTSL program in the city of Padang, this can be seen from several aspects that have not been maximized because there are several problems in the field, such as lack of human resources as executors and the status of customary land which is an obstacle in registering land because many get less approval from their people.&#x0D; Keywords : On going evaluation, The complete systematic land registration program (PTSL) ,land registration, land certificate.

Informative Feature-Guided Siamese Network for Early Diagnosis of Autism.

Autism, or autism spectrum disorder (ASD), is a complex developmental disability, and usually diagnosed with observations at around 3-4 years old based on behaviors. Studies have indicated that the early treatment, especially during early brain development in the first two years of life, can significantly improve the symptoms, therefore, it is important to identify ASD as early as possible. Most previous works employed imaging-based biomarkers for the early diagnosis of ASD. However, they only focused on extracting features from the intensity images, ignoring the more informative guidance from segmentation and parcellation maps. Moreover, since the number of autistic subjects is always much smaller than that of normal subjects, this class-imbalance issue makes the ASD diagnosis more challenging. In this work, we propose an end-to-end informative feature-guided Siamese network for the early ASD diagnosis. Specifically, besides T1w and T2w images, the discriminative features from segmentation and parcellation maps are also employed to train the model. To alleviate the class-imbalance issue, the Siamese network is utilized to effectively learn what makes the pair of inputs belong to the same class or different classes. Furthermore, the subject-specific attention module is incorporated to identify the ASD-related regions in an end-to-end fully automatic learning manner. Both ablation study and comparisons demonstrate the effectiveness of the proposed method, achieving an overall accuracy of 85.4%, sensitivity of 80.8%, and specificity of 86.7%.

Nature Through The Potential Development of Tourism to Increase Economic And Social Village Sepakung

Sepakung tourist village is a village that has a pretty good tourism potential and is a sector thatspur the economy in Sub Banyubiru, excellence Sepakung the village is a tourist village that isstill very beautiful area that makes a very natural tourism potential of local tourist interest.Sepakung travel planning in the village can spur other sectors such as transport, food stalls orsouvenirs, and others so that the local governments will benefit in the areas associated withtourism. Sepakung tourist village located in the district Banyubiru, Semarang regency which hasan opportunity to improve the life of village communities Sepakung, with the development ofrural tourism is expected to make villagers sepakung to get a good progress of the economy,which notaben sepakung native village are farmers who have an average primary schooleducation. But this can happen if the development and management of tourist villages sepakungcan be done well. The method used is descriptive qualitative method. Respondents in this studyincluded 302 respondents using as a reference parcel map data retrieval and two tours as a tourmanager in the capture of data collection techniques include, observations, interviews,questionnaires, study the documentation. Data were analyzed using, percentage and SWOTanalysis. The results showed that (1) Village tour sepakung did little to change people'slivelihood Sepakung village. The majority of people work as farmers and laborers (2) Revenuecommunity work in the village Sepakung average of less than one million rupiah (3)Development of a tourist village in Sepakung pretty good (4) The appeal in the village Sepakungto attract tourists is a tourist attraction (5) Measures for the development of tourist villages inSepakung quite. The contribution made by local authorities make people more enthusiastic todevelop the potential of the village.

Combining Satellite Images and Cadastral Information for Outdoor Autonomous Mapping and Navigation: A Proof-of-Concept Study in Citric Groves

The development of robotic applications for agricultural environments has several problems which are not present in the robotic systems used for indoor environments. Some of these problems can be solved with an efficient navigation system. In this paper, a new system is introduced to improve the navigation tasks for those robots which operate in agricultural environments. Concretely, the paper focuses on the problem related to the autonomous mapping of agricultural parcels (i.e., an orange grove). The map created by the system will be used to help the robots navigate into the parcel to perform maintenance tasks such as weed removal, harvest, or pest inspection. The proposed system connects to a satellite positioning service to obtain the real coordinates where the robotic system is placed. With these coordinates, the parcel information is downloaded from an online map service in order to autonomously obtain a map of the parcel in a readable format for the robot. Finally, path planning is performed by means of Fast Marching techniques using the robot or a team of two robots. This paper introduces the proof-of-concept and describes all the necessary steps and algorithms to obtain the path planning just from the initial coordinates of the robot.

Large Scale Mapping Using Unmanned Aerial Vehicle (UAV)-Photogrammetry To Accelerate Complete Systematic Land Registration (PTSL) (Case Study: Ciwidey Village, Bandung Regency, Indonesia)

Technical Guidance for Complete Systematic Land Registration (PTSL) describes that implementation of PTSL requires a land registration base map for mapping of land parcels. The land registration base map uses aerial photo maps, high-resolution imagery maps, and vector maps. A PTSL was undertaken to solve overlapping problems. Currently, UAV can be used to accelerate mapping because the UAV system is able to observe the earth’s surface at low altitude and still fulfill the accuracy requirements of land mapping. To support the PTSL, a large scale land registration base map is needed, in this case will be done using UAV. Case study is located in Ciwidey Village, Bandung regency, which does not have base map of land registration, has hilly terrain, and ± 332 ha area. The method of making land registration base map is using UAV-photogrammetry method and Ground Control Point (GCP) measurement is done by using GPS-static method for base point measurement and using real-time-kinematic method (RTK) for GCP measurement. The analysis of the results of this large-scale mapping is using the standard of accuracy as recommended by American Society for Photogrammetry and Remote Sensing (ASPRS) 2014. The horizontal accuracy obtained from ortho-photo processing has fulfilled the ASPRS standard for 1: 1000 scale photo maps.