scholarly journals An Expert Artificial Intelligence Model for Discriminating Microseismic Events and Mine Blasts

2021 ◽  
Vol 11 (14) ◽  
pp. 6474
Author(s):  
Dijun Rao ◽  
Xiuzhi Shi ◽  
Jian Zhou ◽  
Zhi Yu ◽  
Yonggang Gou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Discrimination Performance ◽  
Pso Algorithm ◽  
Microseismic Monitoring ◽  
Model Parameters ◽  
Research Results ◽  
Microseismic Events ◽  
The Difference ◽  
Learning Machine ◽  
Mine Blasts

To reduce the workload and misjudgment of manually discriminating microseismic events and blasts in mines, an artificial intelligence model called PSO-ELM, based on the extreme learning machine (ELM) optimized by the particle swarm optimization (PSO) algorithm, was applied in this study. Firstly, based on the difference between microseismic events and mine blasts and previous research results, 22 seismic parameters were selected as the discrimination feature parameters and their correlation was analyzed. Secondly, 1600 events were randomly selected from the database of the microseismic monitoring system in Fankou Lead-Zinc Mine to form a sample dataset. Then, the optimal discrimination model was established by investigating the model parameters. Finally, the performance of the model was tested using the sample dataset, and it was compared with the performance of the original ELM model and other commonly used intelligent discrimination models. The results indicate that the discrimination performance of PSO-ELM is the best. The values of the six evaluation indicators are close to the optimal value, which shows that PSO-ELM has great potential for discriminating microseismic events and blasts. The research results obtained can provide a new method for discriminating microseismic events and blasts, and it is of great significance to ensure the safe and smooth operation of mines.

scholarly journals A novel tree-based algorithm for real-time prediction of rockburst risk using field microseismic monitoring

2021 ◽  
Author(s):  
Xin Yin ◽  
Quansheng Liu ◽  
Yucong Pan ◽  
Xing Huang
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Clustering Algorithm ◽  
Microseismic Monitoring ◽  
Engineering Practice ◽  
Minority Class ◽  
The Real ◽  
Time Prediction ◽  
Microseismic Events ◽  
Validation Set

Abstract Rockburst is a kind of complex and catastrophic dynamic geological disaster in the development and utilization of underground space, which seriously threatens the safety of personnel and environment. Due to the suddenness in time and randomness in space, the prediction of rockburst becomes a great challenge. Microseismic monitoring is capable to continuously capture rock microfracture signals in real time, which offers an effective means for rockburst prediction. With the explosive growth of monitoring data, the conventional manual forecasting methods are laborious and time-consuming. Therefore, artificial intelligence was introduced to improve the prediction efficiency. A novel tree-based algorithm was proposed. Its basic idea was to automatically recognize precursory microseismic sequences for the real-time prediction of rockburst intensity. The database consisting of 1500 microseismic events was analyzed. In order to establish precursory microseismic sequences, dimensionality reduction of the database was first implemented by t-SNE algorithm. Then, k-means clustering algorithm was employed for labelling 1500 microseismic events. Before that, canopy algorithm was adopted to determine the number of clusters. Finally, 300 precursory microseismic sequences were formed by grouping rule. They were further partitioned into two parts through stratified sampling: 70% for training and 30% for validation. The validation results indicated that the precursor tree with pruning achieved higher prediction accuracy of 98.9% than one without pruning on the validation set. And the increase was separately 12.2%, 9.2% and 28.6% on the whole validation set and each classes (low/moderate rockburst). In comparison with low rockburst, moderate rockburst was minority class. The improved accuracy on moderate rockburst suggested that pruning can enhance the recognition ability of precursor tree for minority class. Additionally, two extra rockburst cases were collected from a diversion tunnel in northwestern China, which provided a complete workflow about how to apply the built precursor tree model to achieve field rockburst warning in engineering practice. The tree-based algorithm served as a new and promising way for the real-time rockburst prediction, which successfully integrated field microseismic monitoring and artificial intelligence.

POLIGAMI DALAM PERSPEKTIF AL-QUR’AN

2016 ◽  
Vol 1 (2) ◽  
pp. 35-50
Author(s):  
Makrum Makrum
Keyword(s):  
Qualitative Research ◽  
Islamic Law ◽  
Qualitative Approach ◽  
Comprehensive Understanding ◽  
Research Results ◽  
Library Research ◽  
Difference Of Opinion ◽  
Controversial Problem ◽  
The Difference ◽  
Interpretation Method

This paper is discusion the polygamy is still a controversial problem, although much discussed and examined. The difference of opinion among scholars make this problem continues to potentially raises the agree and disagree. Even though it has been regulated in Act Number 1 of 1974 concerning marriage and the compilation of Islamic law (KHI), this does not necessarily make the problem of polygamy is complete. Not a few perpetrators of polygamy choose married under the hand or by sirri. This research uses qualitative approach by implementing thematic interpretation method (maudhu'i) to obtain a comprehensive understanding about polygamy in the Qur'an. The Data obtained through the study of a library research by sharing the data that comes from the various verse of the Qur'an, hadith, book fiqh, research results, books and the news in various media outlets in order to complete the interpretation of the verses of polygamy. Based on the results of this research it is known that the verses of the Qur'an gives a very tight restrictions for those who want to in polygamy. Justice that the conditions of polygamy is not only were quantitative but also qualitative research. In the context of historical-socio, the command of polygamy is intended as a form of the solution to avoid injustice to orphans women. Even if polygamy still want to do, should the husband marrying the widows who have lighten the orphan.

Analysis of compliance of box sizes to comfortable housing of highly productive cows

2020 ◽  
pp. 42-50
Author(s):  
V. Turlyun
Keyword(s):  
Free Movement ◽  
Research Results ◽  
Total Length ◽  
Genetic Potential ◽  
Productive Potential ◽  
The Difference

The analysis of some herds of imported cattle under the conditions of Russian farms had been shown that the genetic potential of imported cattle in many farms has being realized only by 57 %, with the output of up to 50 % of the cattle during the first 2 years. The reason for this is the discrepancy between the conditions of the biological needs of animals. In this regard, the study of factors that affect the provision of comfortable conditions for animals plays an important role. This is especially true for Holstein animals, which are more susceptible to various diseases. In accordance with the technological solutions used in modern large complexes, the loose housing method of maintenance is mainly used. This method allows the animal to move freely, providing access to the consumption of water and feed, as well as timely rest. This determines the importance of the requirements for the size of the boxes for the rest of animals, which should ensure dryness and cleanliness in the process of resting cows, prevent damage to animals, as well as the ability of other animals to displace each other. The crossbars should not interfere with the free movement of the cow in the process of lowering to the floor and getting up due to their flexibility. The dimensions of the boxes should be made taking into account the measurements of the animals’ torso, as well as the amplitude of movement in the process of lowering and rising. The purpose of the research was to study the size of boxes and their compliance with the biological needs of highly productive imported cattle. An analysis of the compliance of conditions for housing highly productive cattle of Canadian and Australian origin with their biological needs under the conditions of a mega farm has been presented in the paper. Calculation on the basis of measurements of animals has been shown that animals of the Canadian selection require boxes with a total length of at least 279 cm, Australian – 271 cm. The difference with the required width of the box has been also established. For the group of cows of Canadian selection it should be at least 120 cm, for the Australian – 114 cm. Research results have been shown that the discrepancy in the design of boxes for comfortable rest of animals is a deterrent to the realization of their genetic productive potential.

PENGAKUAN CALABAI: SEBUAH ANALISIS INTERTEKSTUAL NOVEL PASUNG JIWA KARYA OKKY MADASARI DAN NOVEL CALABAI KARYA PEPI AL-BAYQUNIE

Jurnal KATA ◽  
2018 ◽  
Vol 2 (1) ◽  
pp. 50
Author(s):  
Krisna Aji Kusuma ◽  
Herman J Waluyo ◽  
Nugraheni Eko Wardani
Keyword(s):  
Content Analysis ◽  
Analysis Data ◽  
Qualitative Approach ◽  
The Novel ◽  
Research Results ◽  
Self Actualization ◽  
Similarities And Differences ◽  
The Difference ◽  
Descriptive Qualitative

<p><em>This study aims to describe the intertextuality relationship between the novel Pasung Jiwa by Okky Madasari and Calabai by Pepi Al-Bayqunie. The type of research is descriptive qualitative approach using content analysis. Data are collected by inventorying events that are similarities and differences, specifications on the characters, settings, plots, and themes of both text. The research results indicate that there are similar themes on the two novels, the theme of self actualization in addition with the theme of family and friendship. The same characterization are also used by both author, masculine figures with feminine soul characters. The difference between the two novels lies on the plot and setting. Pasung Jiwa uses progressive plot and Calabai uses a flash-back plot.. Okky Madasari takes Java Island as the background in the novel Pasung Jiwa, while the novel Calabai, Pepi Al-Bayqunie using the setting of Sulawesi Island. The basis of the similarity of theme and characterization supported by the similirity of events in the story shows the existence of intertextual relationship between the two novels. As a previously published work, the novel Pasung Jiwa by Okky Madasari is a hipogram and novel Calabai by Pepi A-Bayqunie as a transformational text. On the theme and characterization, the transformation of Calabai forward the hypogram, while in the plot and setting deviates his hypogram, Pasung Jiwa.</em></p><p>Penelitian ini bertujuan untuk mendeskripsikan hubungan intertekstualitas antara novel Pasung Jiwa karya Okky Madasari dan novel Calabai karya Pepi Al-Bayqunie. Jenis penelitian ini adalah deskriptif kualitatif dengan pendekatan konten analisis. Data dikumpulkan dengan menginventariskan peristiwa yang merupakan persamaan dan perbedaan, spesifikasi pada tokoh, latar, alur, dan tema dari kedua teks. Hasil penelitian ini menunjukkan bahwa terdapat kesamaan tema pada kedua novel, yaitu tema aktualisasi diri, ditambah dengan tema keluarga dan persahabatan. Penokohan yang sama juga digunakan oleh kedua penulis, yaitu tokoh maskulin dengan karakter jiwa feminin. Perbedaan kedua novel terletak pada alur dan latar. Pasung Jiwa menggunakan alur maju dan Calabai menggunakan alur campuran. Latar dalam novel Pasung Jiwa, Okky Madasari mengambil latar Pulau Jawa, sedangkan novel Calabai, Pepi Al-Bayqunie menggunakan latar Pulau Sulawesi. Dasar kesamaan tema dan penokohan didukung kesamaan peristiwa-peristiwa dalam cerita menunjukkan adanya hubungan intertekstual antara kedua novel. Sebagai karya yang terbit terlebih dahulu menjadikan novel Pasung Jiwa karya Okky Madasari adalah hipogram dan novel Calabai karya Pepi Al-Bayqunie sebagai teks transformasi. Pada tema dan penokohan, transformasi Calabai meneruskan hipogram, sedangkan pada alur dan latar menyimpangi hipogramnya, Pasung Jiwa.</p>

scholarly journals Investigation on performance of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) in a combination of CFD modeling for prediction of fluid flow

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Meisam Babanezhad ◽  
Iman Behroyan ◽  
Ali Taghvaie Nakhjiri ◽  
Azam Marjani ◽  
Mashallah Rezakazemi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Particle Swarm Optimization ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Bubble Column ◽  
Pso Algorithm ◽  
Cfd Modeling ◽  
Swarm Optimization ◽  
Inference System ◽  
Mesh Density

AbstractHerein, a reactor of bubble column type with non-equilibrium thermal condition between air and water is mechanistically modeled and simulated by the CFD technique. Moreover, the combination of the adaptive network (AN) trainer with the fuzzy inference system (FIS) as the artificial intelligence method calling ANFIS has already shown potential in the optimization of CFD approach. Although the artificial intelligence method of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) has a good background for optimizing the other fields of research, there are not any investigations on the cooperation of this method with the CFD. The PSOFIS can reduce all the difficulties and simplify the investigation by elimination of the additional CFD simulations. In fact, after achieving the best intelligence, all the predictions can be done by the PSOFIS instead of the massive computational efforts needed for CFD modeling. The first aim of this study is to develop the PSOFIS for use in the CFD approach application. The second one is to make a comparison between the PSOFIS and ANFIS for the accurate prediction of the CFD results. In the present study, the CFD data are learned by the PSOFIS for prediction of the water velocity inside the bubble column. The values of input numbers, swarm sizes, and inertia weights are investigated for the best intelligence. Once the best intelligence is achieved, there is no need to mesh refinement in the CFD domain. The mesh density can be increased, and the newer predictions can be done in an easier way by the PSOFIS with much less computational efforts. For a strong verification, the results of the PSOFIS in the prediction of the liquid velocity are compared with those of the ANFIS. It was shown that for the same fuzzy set parameters, the PSOFIS predictions are closer to the CFD in comparison with the ANFIS. The regression number (R) of the PSOFIS (0.98) was a little more than that of the ANFIS (0.97). The PSOFIS showed a powerful potential in mesh density increment from 9477 to 774,468 and accurate predictions for the new nodes independent of the CFD modeling.

scholarly journals On the Juridical Relevance of the Phenomenological Notion of Person in Max Scheler and Edith Stein

2021 ◽  
Author(s):  
Francesco Galofaro
Keyword(s):  
Artificial Intelligence ◽  
Edmund Husserl ◽  
Phenomenological Analysis ◽  
Machine Learning Algorithms ◽  
Decision Makers ◽  
Edith Stein ◽  
Max Scheler ◽  
Human Decision ◽  
The Difference ◽  
Social Units

AbstractThe paper presents a semiotic interpretation of the phenomenological debate on the notion of person, focusing in particular on Edmund Husserl, Max Scheler, and Edith Stein. The semiotic interpretation lets us identify the categories that orient the debate: collective/individual and subject/object. As we will see, the phenomenological analysis of the relation between person and social units such as the community, the association, and the mass shows similarities to contemporary socio-semiotic models. The difference between community, association, and mass provides an explanation for the establishment of legal systems. The notion of person we inherit from phenomenology can also be useful in facing juridical problems raised by the use of non-human decision-makers such as machine learning algorithms and artificial intelligence applications.

scholarly journals Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications

2020 ◽  
Vol 17 (10) ◽  
pp. 3730 ◽  
Author(s):  
Sina Shaffiee Haghshenas ◽  
Behrouz Pirouz ◽  
Sami Shaffiee Haghshenas ◽  
Behzad Pirouz ◽  
Patrizia Piro ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Infectious Disease ◽  
Relative Humidity ◽  
Cost Function ◽  
Selection Process ◽  
Environmental Parameters ◽  
Pso Algorithm ◽  
Data Set ◽  
De Algorithm

Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmental, and economic impacts, and leads to serious challenges and threats. Additionally, investigating the prioritization parameters is of vital importance to reducing the negative impacts of this global crisis. Hence, the main aim of this study is to prioritize and analyze the role of certain environmental parameters. For this purpose, four cities in Italy were selected as a case study and some notable climate parameters—such as daily average temperature, relative humidity, wind speed—and an urban parameter, population density, were considered as input data set, with confirmed cases of COVID-19 being the output dataset. In this paper, two artificial intelligence techniques, including an artificial neural network (ANN) based on particle swarm optimization (PSO) algorithm and differential evolution (DE) algorithm, were used for prioritizing climate and urban parameters. The analysis is based on the feature selection process and then the obtained results from the proposed models compared to select the best one. Finally, the difference in cost function was about 0.0001 between the performances of the two models, hence, the two methods were not different in cost function, however, ANN-PSO was found to be better, because it reached to the desired precision level in lesser iterations than ANN-DE. In addition, the priority of two variables, urban parameter, and relative humidity, were the highest to predict the confirmed cases of COVID-19.

Estimation of Internal Surface Roughness of Additively Manufactured Components Under Complex Conditions Using Artificial Intelligence and Measurements of Ultrasonic Backscatter

2021 ◽  
Author(s):  
Mohamed Subair Syed Akbar Ali ◽  
Mato Pavlovic ◽  
Prabhu Rajagopal
Keyword(s):  
Artificial Intelligence ◽  
Surface Roughness ◽  
Internal Surface ◽  
Side Surface ◽  
Ultrasonic Waves ◽  
Model Parameters ◽  
Ultrasonic Measurements ◽  
Neural Network Algorithm ◽  
X Ray Computed ◽  
Pulse Echo

Abstract Additive Manufacturing (AM) is increasingly being considered for fabrication of components with complex geometries in various industries such as aerospace and healthcare. Control of surface roughness of components is thus a crucial aspect for more widespread adoption of AM techniques. However, estimating the internal (or ‘far-side’) surface roughness of components is a challenge, and often requires sophisticated techniques such as X-ray computed tomography, which are difficult to implement online. Although ultrasound could potentially offer a solution, grain noise and inspection surface conditions complicate the process. This paper studies the feasibility of using Artificial Intelligence (AI) in conjunction with ultrasonic measurements for rapid estimation of internal surface roughness in AM components, using numerical simulations. In the first models reported here, a pulse-echo configuration is assumed, whereby a specimen sample with rough surfaces is insonified with bulk ultrasonic waves and the backscatter is used to generate A-scans. Simulations are carried out for various combinations of the model parameters, yielding a large number of such A-scans. A neural network algorithm is then created and trained on a subset of the datasets so generated using simulations, and later used to predict the roughness from the rest. The results demonstrate the immense potential of this approach in inspection automation for rapid roughness assessments in AM components, based on ultrasonic measurements.

scholarly journals A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions

2018 ◽  
Vol 15 (9) ◽  
pp. 2909-2930 ◽  
Author(s):  
Sebastian Lienert ◽  
Fortunat Joos
Keyword(s):  
Land Use ◽  
Carbon Emissions ◽  
Latin Hypercube Sampling ◽  
Historical Period ◽  
Model Parameters ◽  
Dynamic Global Vegetation Model ◽  
Order Of Magnitude ◽  
The Difference ◽  
Wood Harvest ◽  
Global Vegetation

Abstract. A dynamic global vegetation model (DGVM) is applied in a probabilistic framework and benchmarking system to constrain uncertain model parameters by observations and to quantify carbon emissions from land-use and land-cover change (LULCC). Processes featured in DGVMs include parameters which are prone to substantial uncertainty. To cope with these uncertainties Latin hypercube sampling (LHS) is used to create a 1000-member perturbed parameter ensemble, which is then evaluated with a diverse set of global and spatiotemporally resolved observational constraints. We discuss the performance of the constrained ensemble and use it to formulate a new best-guess version of the model (LPX-Bern v1.4). The observationally constrained ensemble is used to investigate historical emissions due to LULCC (ELUC) and their sensitivity to model parametrization. We find a global ELUC estimate of 158 (108, 211) PgC (median and 90 % confidence interval) between 1800 and 2016. We compare ELUC to other estimates both globally and regionally. Spatial patterns are investigated and estimates of ELUC of the 10 countries with the largest contribution to the flux over the historical period are reported. We consider model versions with and without additional land-use processes (shifting cultivation and wood harvest) and find that the difference in global ELUC is on the same order of magnitude as parameter-induced uncertainty and in some cases could potentially even be offset with appropriate parameter choice.

scholarly journals Study of Multimedia Delivery over Software Defined Networks

2016 ◽  
Vol 7 (4) ◽  
pp. 37 ◽  
Author(s):  
Jose Miguel Jimenez ◽  
Oscar Romero ◽  
Albert Rego ◽  
Avinash Dilendra ◽  
Jaime Lloret
Keyword(s):  
Artificial Intelligence ◽  
Personal Computer ◽  
Network Protocols ◽  
Performance Comparison ◽  
Distributed Artificial Intelligence ◽  
Software Defined Networks ◽  
Multimedia Delivery ◽  
Real Network ◽  
Multimedia Streams ◽  
The Difference

Software Defined Networks (SDN) have become a new way to make dynamic topologies. They have great potential in both the creation and development of new network protocols and the inclusion of distributed artificial intelligence in the network. There are few emulators, like Mininet, that allow emulating a SDN in a single personal computer, but there is lack of works showing its performance and how it performs compared with real cases. This paper shows a performance comparison between Mininet and a real network when multimedia streams are being delivered. We are going to compare them in terms of consumed bandwidth (throughput), delay and jitter. Our study shows that there are some important differences when these parameters are compared. We hope that this research will be the basis to show the difference with real deployments when Mininet is used.

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