Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution characteristics of elemental grade and mineralization grade of Jiama copper deposit

The change of metallogenic element grade in borehole has strong randomness and nonlinearity. Quantitative analysis of metallogenic element grade distribution is one of the important ways to reveal the degree of mineralization enrichment. Taking Jiama porphyry copper deposit as an example, the distribution structure of Cu grade series in exploration lines 32 and 36 is analyzed by lacunarity method, and this paper discusses the relationship between lacunarity index and mineralization intensity. It is found that both the lacunarity index and parameters of Cu element in different boreholes exist distinction, the higher the mineralization intensity, the smaller the lacunarity index and the smoother the curve, pointing that the high-grade Cu element is more enriched and uniform. The size of lacunarity index and the variation trend of lacunarity curve have a certain indicative effect on mineralization grade.
Retraction Retraction: Intelligent Transaction System for Fraud Detection using Deep Learning Networks

Detecting online transaction fraud is a basic study of the new era of electronic transactions. Because the payment patterns of customers and the fraud behaviour of offenders are continually changing, improving the consistency of the fraud detection model and ensuring its stability is exceedingly challenging. In this report, we will look at We concentrate on acquiring deep feature representations of legal and fraud transactions from the perspective of a deep neural network's loss function in this report. Our aim is to increase the separability and discrimination of features in order to boost the efficiency and stability of our fraud detection platform, with the rapid evolution of the technology, the world is turning to use online transaction instead of cash in their daily life, which opens the door to many new ways for fraudsters to use these cards in a nefarious manner. Global losses are projected to reach $35 billion by 2020, according to the Nilson report. To guarantee that users of these credit cards are secure, the credit card issuer should provide a program that protects them from any threats they can experience. As a result, we illustrate our framework for predicting whether transactions are genuine or illegitimate using Kaggel's IEEE-CIS Fraud Detection dataset. BiLSTMMaxPooling-BiGRUM is the name of our model. Long bi-directional gated repeated unit and long bi-directional memory term (BiLSTM) are used in axPooling (BiGRU).
Analysis of Image Generation by different Generator in GANs

GAN is very useful in the field of image generation. Many related GANs have been proposed for generating images from the description. However, the research about analysis of image generation by different Generator in GANs is still insufficient. In this paper, different methods such as CNN and Resnet are used as the Generator in GANs for image generation. The subjective evaluation is used to analyze the performance of different generators of GAN. The result shows that the CNN-based generator performs better than the Resnet-based generator. And the increase of the number of parameters in the model will change the image quality. The analysis of different methods as the generator in GAN has a great referential significance in the field of image generation.
Levels of Heavy Metal and Trace Element Among Children with Autism Spectrum Disorders

The aim of this study was estimation the concentration of heavy and trace element in blood samples for autism spectrum disorder material and method: sixty patients with autism participated in the present study, all of these patients are registered in an autism center in Basrah province( Iraq). At the same time, 30 healthy children contributed in the study as a control group. The heavy levels were estimated and trace elements (chromium, zinc, selenium, copper, lead, mercury and iron) in the patient and control groups by used energy dispersive X-ray spectroscopy (EDS). The basic principle should appear in the X-rays emitted by the different energies coming from the sample at the same time as a beam of an electron is moving its factors. Conclusion: The results showed that there was no significant difference between patients and the control group in all trace elements except zinc. On the other hand, the study showed that there was no significant change between male and female in all levels of trace elements except selenium.
Modelling and optimizing sensor wireless network systems

This paper is connected with the necessity of problem modelling and optimizing sensor wireless network systems. The general scheme of a multi-step process of making the optimal decision in sensor wireless network systems is given. The main steps of the computational scheme of the dynamic programming method are given. It is shown how to increase the efficiency of the wireless sensor network. All possible variants of optimal strategies are demonstrated that ensure obtaining the maximum value of a generalized performance indicator. The results of the paper can be useful in the development of wireless sensor networks with high performance indicators.
Classification of Damaged Road Types Using Multiclass Support Vector Machine (SVM)

Damage roads had been disturbed by social activities and involved in traffic accidents. Identification and classification of the types of defected road are required to minimize its impact and before repairs. Digital image processing technology can identify and classify the type of damaged roads automatically. In this study, the classification of defected roads is automatic with a multiclass Support Vector Machine(SVM). There are three classes in the classification process, namely, alligators, potholes, and cracks. The process of recognizing defected roads uses a multiclass SVM classification model with polynomial and Gaussian kernel function and One Vs. All strategy and uses a cell size of 16 × 16 pixels during the Histogram of Oriented Gradients (HOG) feature extraction process. and produces an accuracy value of 78,85%.
A comprehensive index model for real estate convenience based on multi-source data

The description information of the convenience of real estate is often qualitative and simple, and lacks comprehensive evaluation, so it is difficult to make horizontal comparison of the convenience of different real estate. Therefore, this paper proposes a comprehensive index model which uses multi-source data to measure the real estate convenience quantitatively. Based on the walking index, the model adds vector road network data, poi (point of interest) data and other multi-source data, and introduces the concept of walking score. Combined with the practical application of real estate, the model classifies the convenience facilities and calculates the walking distance between the convenience facilities and real estate quantitatively, so as to obtain a real number index to comprehensively measure the convenience of real estate. Finally, the experimental results based on Amap data prove the accuracy and effectiveness of the proposed model.
Optimizing Channel Profit in a Retail Dual-channel Supply Chain When Considering Delivery Lead Time

With the development of e-commerce, more and more consumers are shopping Online, which has led several traditional retailers to redesign their sales strategy to include an Online sales channel. Their Online and offline channels form dual-channel supply chains. However, consumers have to wait before receiving the products they buy. The time elapsed is called delivery lead time which is an important index in consumer’s channel choice. There are few studies in this new field with studies in dual-channel supply chain being more common. In this paper, a dual-channel supply chain in which there are one manufacturer and one retailer is studied, and the retailer has an Online and an offline channel at the same time. The supply chain is considered as a retailer-dominant Stackelberg game. The delivery lead time is introduced into the operation of the supply chain. The impact of the delivery lead time on the operation of the supply chain is analyzed in this paper. The two-part tariff contract is used to coordinate the supply chain when making the decentralized decision. Finally, the optimal decisions of the supply chain members when the delivery lead time is different are shown using numerical examples.
Small-scale fishing families and their daily multiple-stressor on climate change and COVID-19: Preliminary findings

The COVID-19 pandemic situation is still ongoing in many countries in the world, including Indonesia. The positive case continues to increase every day and impacts our life, including the fisheries’ family. The fishery is a vulnerable sector to climate change, and this day worsened by a pandemic situation. This paper aims to understand the resources attached to fishing families facing various pressures and risks, forms of response, and adaptation within the fishing families. During COVID-19 pandemic situation, we have to carried out an online ethnographic approach by online-focused group discussion (FGD) to fisherman group and fisherman wives. Purworejo village was selected as a research site because it is the one with the largest number of small-scale fishing families in Java’s northern coastal area. The results show that various pressures and risks faced by fishery families, not only related to climate change and COVID-19 such as fishing season, limited resources, capital, and access, but also a risk on their internal family. In the context of fishery family resilience, each family member has a role in dealing with stressors, especially economic stressors. Fathers look for fish in the sea almost eight hours a day; children also go to sea when economic conditions continue to deteriorate; even a fisherman’s wife has the same responsibilities as her husband.
Channel Power Allocation Optimization Based on Water-filling Algorithm in 5G

Since entering the information age, the popularity of mobile communication has become higher and higher, and people’s requirements for communication quality are also increasing, but the channel resources that people can control are limited. This paper proposes an optimization algorithm for channel resource allocation based on water-filling algorithm. Some improvements have been made on the basis of the original water-filling algorithm. The sgn function is used to optimize the transmit interference temperature limit (Sk), so that the screening result is not completely dependent on Sk, which improves the flexibility of channel screening and effectively optimizes the capacity of the communication network.
Effects of 10 MeV Al4+ ions irradiation on fluorine-doped tin oxide substrates for photovoltaic device applications

The effects of 10 MeV Al4+ ions irradiation on structural, surface morphological, optical and electrical properties of fluorine-doped tin oxide (FTO) substrates are presented for solar cell applications. The ions irradiation changes the surface morphology, average roughness, interface width, roughness exponent, and several other fractal parameters of the FTO surfaces. The UV–visible transmittance measurement shows an enhancement of transmittance in the ions irradiated substrates up to 95%. The electrical properties such as mobility, work-function, sheet resistance, and resistivity are also modified due to ions irradiation. In order to have functional applications of these ions irradiated substrates, we fabricated organic solar cells on these ions irradiated and pristine FTO substrates. The device performances are significantly improved for the case of ions irradiated FTO substrate in comparison to the pristine one. Thus, better device performance due to effective changes in physical properties suggests that the ions irradiated FTO substrates can be used as better electrodes for organic and hybrid photovoltaic device applications.
Facial Expression Recognition Algorithm Based on Convolution Neural Network and Multi-Feature Fusion

Facial expression recognition is a hot topic in the field of computer vision. The related research results show high application value in many fields, such as human-computer interaction, intelligent emotional robot, fatigue driving detection, medical health, safety prevention and control, teaching evaluation and so on. However, the huge difference within the expression class still has a prominent impact on the expression recognition, and it is difficult to solve this problem by single feature and traditional feature fusion methods. Therefore, this paper uses neural network and feature fusion strategy to further characterize and classify the constructed features. Experiments show that this method can effectively overcome the interference caused by the differences within the expression class, and achieve ideal expression recognition results.
Landscape structure of the territory of the state nature complex reserve Ichalkovsky Bor (Nizhny Novgorod region, Russia)

The article presents the results of landscape differentiation of the territory of the state nature complex reserve “Ichalkovsky Bor” (Nizhny Novgorod region), performed at the hierarchical level of landscapes and stows. The research territory lies in the forest-steppe zone, and characterized by a rugged karst topography relief, high biological diversity, which determined its complicated landscape structure and great environmental and recreational importance. In 2020 it was decided to organize a geopark, based on the state nature complex reserve Ichalkovsky Bor. All these circumstances determine the high demand for the landscape zoning scheme, which is necessary for the effective organization of environmental and recreational activities. In the course of the research, 4 landscapes were identified, which included 33 kinds of stows. The work was carried out on the basis of field researches, conducted in 2015-2020, materials of remote sensing of the Earth, thematic maps, literature data, processed using GIS.
Deep learning based Food Recognition using Tensorflow

Cutting edge profound learning models for food acknowledgment don’t permit information steady taking in and frequently experience the ill effects of cataclysmic impedance issues during the class gradual learning. This is a significant issue in food acknowledgment since certifiable food datasets are open-finished and dynamic, including a persistent expansion in food tests and food classes. Model retraining is frequently done to adapt to the powerful idea of the information, yet this requests very good quality computational assets and critical time. This paper proposes another open-finished ceaseless learning system by utilizing move learning on profound models for include extraction, Relief F for highlight determination, and a novel versatile decreased class steady portion extraordinary learning machine (ARCIKELM) for characterization. Move learning is gainful because of the great speculation capacity of profound learning highlights. Alleviation F lessens computational intricacy by positioning and choosing the extricated highlights. The tale ARCIKELM classifier progressively changes network design to decrease calamitous neglect. It tends to space variation issues when new examples of the current class show up. To direct complete analyses, we thought about the model in contrast to four standard food benchmarks and an as of late gathered Pakistani food dataset. Test results show that the proposed structure learns new classes steadily with less calamitous induction and adjusts space changes while having serious characterization execution.
Evaluation for User’s Safety Through Psychological Perception and Walkable Path Physical Design

Safety is one of the four basic needs of pedestrians. It must be met before other pedestrian paths are met, namely: function, comfort, and aesthetics. The DKI Jakarta government has improved the quality of the walkable path infrastructure in the Thamrin Sudirman area. Which the areas are trade and service centers and primary activity centers, as well as a strategic area (Integrated Commerce Center and Upper Hamlet area are exchanges of mass public transport ( TOD) (Spatial Planning for DKI Jakarta Province in 2010-2030). It is to improve pedestrian convenience and safety. This study aims to explore the safety problems of the pedestrian in the Thamrin Sudirman area. The research methodology used is qualitative by observing the perception of psychological parameters and physical design parameters for pedestrian safety. The results will show a physical parameter design: an open design and a transparent façade that gives a high perception of safety for pedestrians. Then it can be a role model for the design of other walkable paths design.
Migrant Workers Role in Rural-Urban Linkage, Case Study: Industrial Growth in Semarang Regency, Indonesia

Rural-urban linkages are part of regional development concern, providing a regional network strategy to deal with the rural-urban divide issue. Industrial growth in the peri-urban area is an important activity that could bridge the linkage of rural and urban. The recent growth of the industrial sector in Semarang Regency, Indonesia, has fostered the surrounding region workers to migrate into the area that promoted the rural-urban linkage. This paper presents a research result of the industrial migrant workers role in rural-urban linkage of the peri-urban region. The research approach was carried out by descriptive analysis to understand the role of migrant workers in the rural-urban linkage. The research collected data from a sample of migrant workers in the regency. The study found that the rural migrant workers as people movement are the main component of rural-urban linkage, which fosters the other linkage components. The workers bring rural social capital from the origin area to support migration and working activity in the urban area. In general, the growth of migrant workers in the industrial sector in the Semarang Regency has a significant impact on promoting rural-urban linkage, especially regarding the contemporary flow of workers to the urban area and spreading remittance income and information surrounding rural areas. Despite the opportunities, the current rural-urban linkages were not yet effectively realized and utilized by the government to deal with the rural-urban divide issue.
Development of system information of building code checking in planning and permitting phase to improve building code compliance based on work breakdown structure (WBS) using building information modeling (BIM)

Purpose: Audit of the requirements for construction project regulations in DKI Jakarta is still conducted conventionally (paper and CAD based) which requires a long time, resource intensive, different interpretations of the regulations, the process of revised repetitive, the process of tracking difficult requirements, inaccurate and not transparent, and has significant time and cost implications. Examination of conventional requirements causes that there are still many buildings in DKI Jakarta that have not yet met the technical requirements requested for building completion and public dissatisfaction. Automatic requirements checking is possible when the computer representation of the product data model (Product Data Model (PDM)) is integrated with the Legal Knowledge Model (LKM) as input for data processing systems or machines with algorithmic procedures as Compliant Design Processes (CDP) to produce an accurate automatic regulatory check report. Methodology: The Building Model developed in Building Information Making (BIM) is made as a building representation. The scope of building technical requirements based on BIM is managed dynamically using Work Breakdown Structure (WBS) in one database that is validated by the Government and can be applied by planners in any planning. This research uses the BIM model and develops a WBS-based Information System with a BIM application. Results: The scope of requirements can be managed by decomposition of work known as Work Breakdown Structure to produce a BIM component that will be subject to regulatory requirements checking. The ability of the BIM can produce building models that can be subject to audit of regulatory requirements. Examination of regulatory requirements can be carried out at each stage of developing the BIM model according to the level of detail of the BIM object. Examination of regulatory requirements can be carried out independently by planners at each stage by using a Web-based Information System developed in the BIM format that has been validated by the Government. Applications/Originality/Value: By grouping requirements based on the stages of development of the BIM model, it will maximize the fulfillment of the requirements at each stage so as to reduce the risk of redesign while at the same time increasing the fulfillment of the technical requirements of the building.
Text Mining by Social Network Data towards Developing Attractiveness of Urban Park. Case Study: Thematic Parks in Bandung City, Indonesia

The existence of a thematic green open space in Bandung is one of the pioneers in the urban landscape of Indonesian cities. In addition, the thematic park in Bandung is also one of the efforts to realize the concept of a green city besides its function as a medium of channelling citizens’ aspirations. Furthermore, the thematic park concept is to make a difference between one park and other parks and to define its own uniqueness. As public spaces, such as parks, can also be functioned as a place to express an opinion, visitor’s opinion plays an important role. Recently, the online reviews data particularly has been considered as an important factor to influence consumers’ decision and are valued as assets based on valued information. In this research, we used the online reviews method from google maps to collect all information from reviewers about the thematic parks and to analyse the attractiveness of the thematic parks in Bandung City. Our approach is to evaluate visitor’s perceptions by identifying sentences from opinions or reviews regarding the fulfilment of thematic park functions based on its user or visitor, facilities, community activities, and atmosphere of the park. Social network data towards developing urban park attractiveness. The result shows the dominant factor attractiveness of thematic parks is the user or community factor. Moreover, user-oriented thematic park concept generates a special attraction for visitors to visit thematic parks.
The Thermal Reprocessing of Reflected Radiation in the AGN Accretion Disk

We present a reflected reprocessing model to study the thermal lag–wavelength relationship in the AGN accretion disk. The main radiation produced from the corona assumed with the lamppost geometry on the axis of the black hole irradiates the accretion disk to affect the temperature structure via reflection processes. Considering the thermal emission of the disk responded to coronal irradiation, we obtain the lag–wavelength relationship of the disk emission by calculating the response function. We then fit the observed data of four Seyfert 1–1.5 galaxies, NGC4151 , Mrk509, NGC5548, and NGC4593, to test the reflected reprocessing model compared with the X-ray spectrum fitting, and the main results present as follows: (I) The actual geometry of the disk corona is more complex than the lamppost. (II) The option of the reference band is sensitive to fitting the observed time lags. (III) The intrinsic bolometric luminosity is larger than the observed luminosity.