Information systems in geotechnics

The article considers the information modeling of buildings together with the foundation within the information system and the stages of its implementation. The workflow for building a 3D geotechnical model includes surface relief data, field and laboratory test data, soil lithology, geometric characteristics of the foundation structure and load. Automated systems with processing and interpretation of test data are used to determine the characteristics of soils. Mathematical modeling of the behavior of the foundations of the foundations with various input data is performed using analytical solutions and numerical methods. The natural heterogeneity of soil properties and its impact on the behavior of buildings is estimated by the sensitivity indicator of the foundation-foundation system by introducing virtual workings between the existing normative ones and the subsequent calculation of the precipitation and roll of the foundation.

Applying Machine Learning to the Development of Prediction Models for Bank Deposit Subscription

It is not easy for banks to sell their term-deposit products to new clients because many factors will affect customers’ purchasing decision and because banks may have difficulties to identify their target customers. To address this issue, we use different supervised machine learning algorithms to predict if a customer will subscribe a bank term deposit and then compare the performance of these prediction models. Specifically, the current paper employs these five algorithms: Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine and Neural Network. This paper thus contributes to the artificial intelligence and Big Data field with an important evidence of the best performed model for predicting bank term deposit subscription.

An Improved Backscattering Theoretical Model for Snow Area

Remote sensing has been studied for a long time to monitor the earth terrain. Remote sensing technology has been used globally in many different fields and one of the most popular area of study that uses remote sensing technology is snow monitoring. In previous researches, remote sensing has been modelled on snow area to study the scattering mechanisms of various scattering processes. In this paper, surface volume second order term that was dropped in previous study is derived, included and studied to observe the improvement in the surface volume backscattering coefficient. This new model is applied on snow layer above ground and the snow layer is modelled as a volume of ice particles as the Mie scatterers that are closely packed and bounded by irregular boundaries. Various parameters are used to investigate the improvement of adding the new term. Results show improvement in cross-polarized return, for all the range of parameters studied. Comparison is made with the field measurement result from U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) in 1990. Close agreement is shown between developed model and data field backscattering coefficient result.

Incremental autoencoders for text streams clustering in social networks

Clustering data streams in order to detect trending topic on social networks is a chal- lenging task that interests the researchers in the big data field. In fact, analyzing such data needs several requirements to be addressed due to their large amount and evolving nature. For this purpose, we propose, in this paper, a new evolving clustering method which can take into account the incremental nature of the data and meet with its principal requirements. Our method explores a deep learning technique to learn incrementally from unlabelled examples generated at high speed which need to be clustered instantly. To evaluate the performance of our method, we have conducted several experiments using the Sanders, HCR and Terr-Attacks datasets.

Identifikasi Tingkat Kekumuhan Pada Kabupaten Langkat Dengan Metode AHP (Analytical Hierarcy Process)

<p><em>Problems that occur in an urban level of uneven service facilities and infrastructure especially in the urban suburbs. This is also the case in Langkat Regency. The existence of these settlements is classified into squatters or slums that grow unplanned on unlicensed state land. The purpose of the research is to identify the slums, using the AHP method, starting from the collection of primary and secondary data, field observations, interviews, and documentation, which are then assessed against the criteria that have been set. The final result of the weighting resulted in the classification of the level of slums in the village. It is hoped that the results of this study can be useful for other research. </em><em></em></p>

A MODULE OF A GEOINFORMATION SYSTEM BASED ON NUMERICAL MODELING OF INVERSE PROBLEMS OF GEOCHEMISTRY BY REGULARIZING ALGORITHMS

Currently, due to the rapid development of computer technology in geology, methods and approaches of scientific visualization based on additional data analysis are being intensively developed. The general concept is that the main data field on the daily surface and additional conditions are set at the input. Further, methods of mathematical geophysics are used for their analysis and processing, as a result of which new information is obtained for deep surveys. Then, in the information system, visualization tools are applied to the new information received and to the main data field. Thus, the information system is based on the synthesis of visual representation methods and methods of mathematical geophysics, computational mathematics from different branches of knowledge. This paper presents a description of the software module of the geoinformation system, based on the methods of intelligent detection of anomalies of hidden deposits, for deep predictive and search modeling of deposits. The functioning of the software module is based on the application of the theory of inverse problems of mathematical geophysics with elements of artificial intelligence using geological data on the earth's surface, geophysical measurements and geochemical analyses as input data. The program module for the inverse problem of the continuation of potential fields in the direction of disturbing masses is used for real data of a specific mineral deposit.

PROSES BONGKAR MUATAN CURAH CAIR DARI KAPAL MT.SUNRISE HOPE DI PELABUHAN KABIL PADA PT.PASADA ARTHA CARGO BATAM

Abstrak. Proses Bongkar Muatan curah cair di pelabuhan Batam ini bertujuan mengenai Peran Perusahaan Bongkar Muat (PBM) dalam Proses Bongkar Muatan Kapal Asing di pelabuhan Kabil pada PT. Pasada Artha Cargo Batam. Proses penanganan Bongkar Muat dan persiapan penyediaan dokumen bongkar muat kapal serta kegiatan instansi yang berhubungan dengan kegiatan bongkar muat kapal di pelabuhan Batam. Dengan adanya hubungan yang baik dengan instansi pemerintah di pelabuhan maupun pemilik barang (owner) yang dilakukan oleh PT. Pasada Artha Cargo Batam merupakan salah satu kelancaran kegiatan bongkar muat yang dilakukan PT. Pasada Artha Cargo Batam. Sehingga perusahaan leluasa menyampaikan informasi baik itu tentang kegiatan bongkar muat, kebutuhan bongkar muat, dan lainnya. Kegiatan ini sangat membatu dalam kegiatan Ekspor dan Impor barang muatan yang di angkut oleh kapal. Oleh karana itu Perusahaan Bongkar Muat PT. Pasada Artha Cargo Batam sangat berusaha melakukan pelayanan baik agar dapat berjalan lancar sehingga tidak menghambat proses kegitan Bongkar Muat kapal. Hal tersebut akan berjalan lancar apabila karyawan perusahaan bekerja sangat teliti agar dokumen sesuai dengan prosedur yang ada di wilayah pelabuhan Batam. Salah satu bentuk contoh dokumen seperti Manisfest inward dan Manifest Outward akan di ajukan kepada kantor Bea dan Cukai agar kegiatan bisa segera dapat di proses. Alasan saya memilih judul makalah tentang “Proses Bongkar Muatan Curah Cair Dari Kapal MT. SUNRISE HOPE Di Pelabuhan Kabil Pada PT. Pasada Artha Cargo Batam” merupakah salah satu upaya agar bisa memberitahu kepada pembaca yang akan membaca makalah ini dan bisa memberikan sedikit ilmu tentang proses bongkar muat pada kapal curah cair. Berdasarkan pengamatan pada waktu Praktek Darat (PRADA) penulis melakukan dengan menggunakan data Field Research dan Library Reseacrh.

Error propagation dynamics of velocimetry-based pressure field calculations (2): on the error profile

This work investigates the propagation of error in a Velocimetry-based Pressure field reconstruction (VPressure) problem to determine and explain the effects of error profile of the data on the error propagation. The results discussed are an extension to those found in Pan et al. (2016). We first show how to determine the upper bound of the error in the pressure field, and that this worst scenario for error in the data field is unique and depends on the characteristics of the domain. We then show that the error propagation for a V-Pressure problem is analogous to elastic deformation in, for example, a Euler-Bernoulli beam or Kirchhoff-Love plate for one- and two-dimensional problems, respectively. Finally, we discuss the difference in error propagation near Dirichlet and Neumann boundary conditions, and explain the behavior using Green’s function and the solid mechanics analogy. The methods discussed in this paper will benefit the community in two ways: i) to give experimentalists intuitive and quantitative insights to design tests that minimize error propagation for a V-pressure problem, and ii) to create tests with significant error propagation for the benchmarking of V-Pressure solvers or algorithms. This paper is intended as a summary of recent research conducted by the authors, whereas the full work has been recently published (Faiella et al., 2021).