Huge Scale Research Articles

RT-RCT: an online tool for real-time retrieval of connected things

In recent years, internet of things (IoT) represents a giant and a promoter area in innovation and engineering fields. IoT devices are spread in various fields and offer advanced services which assist their users to monitor and control objects remotely. IoT has a set of special characteristics such as dynamic, variety of data and huge scale which introduces a great challenge in the field of retrieval technologies, more precisely real-time retrieval. This paper addresses the issue of real-time retrieval of connected things and tries to propose an innovative solution which allows the retrieval of these things and their descriptive data. The paper proposes an on-line tool for real-time retrieval of connected things and their descriptive data based on network port scanning technique. The performance of this tool proves to be powerful under normal conditions, however more tests must be implemented in the aim to improve the proposed solution. The tool resulted from this work appears to be promising and can be used as a reference by network administrators and IT security managers for the development of new security mechanisms and security reinforcement.

Measuring total‐factor energy environment efficiency, energy‐saving and carbon emission‐reduction potential in China's food industry: Based on a meta‐frontier slacks‐based measure model

AbstractChina's food industry is a large energy consumer and carbon emitter due to its huge scale, so it cannot be ignored if China wants to achieve the goals of energy conservation, emission reduction, and clean production. It is necessary to conduct an in‐depth analysis of the energy environment efficiency of the industry. This paper measures the total‐factor energy environment efficiency (TFEEE) of China's food industry and calculates its energy‐saving and CO2 emission‐reduction potential. A method that combines the slacks‐based measure (SBM) model with meta‐frontier technology is adopted, which considers the heterogeneity of production between regions while dealing with the undesirable output (CO2 emissions). This method is used to calculate the energy environment efficiency of each province based on the group frontier (GTFEEE) and the meta‐frontier (MTFEEE). Through the difference between these two efficiencies, the energy‐saving potential is further decomposed into energy saving from management efficiency improvement and energy saving from technology catch‐up. The results show that, overall, the energy environment efficiency of China's food industry is low, and there are obvious technology gaps between regions. In 2013, the energy‐saving potential of China's food industry reached 49.28 million tce, accounting for 60.7% of the industry's energy consumption that year. Among them, 76% came from the improvement of management efficiency. And the CO2 emission‐reduction potential was 154.6 million tons. Finally, targeted energy saving and emission reduction recommendations were put forward.

Solution Blow Spinning (SBS): A Promising Spinning System for Submicron/Nanofibre Production

Submicron/nanofibres possess great potential for application in different areas because of their amazingly high surface area-to-weight ratio. The demand for fabrication of such fibres on a huge scale is increasing with the fast improvement of nanotechnology. Traditionally, nanofibre fabrication methods have intrinsic faults, limiting their application in industry. Solution blow spinning (SBS) is a viable option for producing adaptable and conformable submicron/nanofibre mats on a variety of surfaces. The technique can be employed to produce submicron/ nanofibres with only a simple commercial airbrush, a concentrated polymer solution, and a compressed gas source. It depends on the high velocity of decompressed air that allows the rapid stretching and evaporation of the solvent from a polymeric solution jet at the outlet of the concentric nozzles system. Along with recent advancements, the importance and drawbacks of the solution blow spinning system in comparison to other methods, such as electrospinning and melt blowing, are briefly discussed. Furthermore, the mechanisms of co-axial SBS spinning and micro SBS spinning system for submicron/nanofibre fabrication are also described. Drawbacks and research challenges of SBS are also addressed in this paper.

Efficiency of the wild plant market in modern economic conditions

At the present stage of economic development in a market economy, the most urgent problem is the rational using the economic potential of the regions to meet the needs of the population in food, as well as other goods and services. The implementation of the food program should be carried out not only through the growth of agricultural production, the efficient operation of food and processing enterprises, the expansion of personal subsidiary farms, but also through the using other sources of food resources, in particular, for example forest products. The severity of this problem is determined by the huge scale of the Russian economy, on the one hand, and the constant increase in prices for food raw materials, on the other.

A characteristic time-based heat input model for simulating selective laser melting

The residual stress induced by rapid temperature cycling in a component during a selective laser melting (SLM) process has a significant detrimental effect on the component’s quality and may cause component failure during or after the printing process. Predicting and therefore actively controlling the residual stress are important research topics in SLM. Numerical simulation is an effective tool to predict the residual stress and distortion throughout the printing process. Goldak heat input model has been commonly used to model the heat source in an SLM process. However, it incurs an unpractically high computational cost when simulating building a part with dimensions in centimetres due to the huge scale gap between the component size and the laser spot size. In the present work, a characteristic time-based heat input (CTI) model has been developed and implemented in a finite-element thermal-mechanical model to significantly reduce the process simulation time while satisfactorily predicting the temperature and residual stress state of SLMed parts. This characteristic time-based heat input model speeds up the computation by applying the integrated energy along the scan path over a characteristic heating time, which is defined as the ratio of the axis of the ellipsoidal heat source in the laser scanning direction to the scanning speed. The characteristic heating time ensures that the peak temperature and subsequent heat transfer of each deposited track can be satisfactorily captured in just one numerical step, respectively. The present model was calibrated and validated by identified isothermal curves on the cross section of a printed Ti-6Al-4V track. Case studies demonstrate that the simulated temperature profile and stress field are in a good agreement with Goldak model. The maximum distortion of a 32 mm single-track sample predicted by CTI model is within 6% of that predicted by Goldak heat input model while CTI’s computational time is just 0.4% of Goldak’s. • A characteristic time-based heat input (CTI) model was developed by integrating Goldak model over a characteristic time. • The characteristic heating time was defined as a ratio of the axis of the heat source to the laser scanning speed. • Residual stress and displacement predicted by CTI model agreed well with those by Goldak model. • CTI model can greatly reduce the simulation time and it is only 0.4% of Goldak model in simulating a 32 mm single-track.

Analysis of Low Power and High Speed Double Tail Comparator Using Gnrfet Technology

Moore’s guideline has been a fundamental benchmark for patterns in the locale of microelectronics and measurements preparing. It has played an instrumental position in driving the part financial aspects and downsizing of the component time frame has been the major system for improving the general execution of the gadget. in any case, as we hold to diminish, close to the nanometre routine, various elements like line region unpleasantness, burrowing outcomes, arbitrary dopant changes, fast channel results, and numerous others have a tendency to impact its working and thereupon, its rise as of intense quintessence to investigate other open door substances that may help intensify the soaking Moore’s guideline. some of the research is as of now going inside the zone and numerous open door advances like CNFETs, FINFETs, GNRFETs. Region sway transistors the utilization of Graphene Nano-Ribbons (GNRFETs) has developed as promising innovation as a result of their stunning supplier transport homes and capacity for huge scale preparing and creation. This paper investigates the GNRFETs inverter generally speaking execution with CMOS inverter at 32nm time hub. Reproductions recommend about 2.5x upgrades inside the proliferation dispense with and 2x enhancements inside the quality put-off item (PDP). what’s more improvement of results was gotten through different the kind of Nano-Ribbons together with the convey voltage. On different the broad kind of nano-ribbons, it has turned out to be set that, spread put off reductions, at the indistinguishable time as powerful power utilization will increment. principally based definitely at the derivation, the upgraded outcome altered into chose to be 15 nano-ribbon. The outcomes imply that that GNRFET is a promising open door for Si-CMOS, making it a splendid recommendation to help intensify soaking Moore’s law. Graphene is an exciting new fabric with radiant electric properties, for the most part inside the state of graphene nanoribbons. on this educational document, we inspect steel-oxide-semiconductor and graphene nanoribbon discipline- impact transistors and recommend the proceeded with utilization of MOSFETs through 2023. This archive fills in as a top-notch initial texture for people with a legacy in semiconductors who want to find out about graphene and GNRFETs.

BIDIRECTIONAL MULTI-SCALE ATTENTION NETWORKS FOR SEMANTIC SEGMENTATION OF OBLIQUE UAV IMAGERY

Abstract. Semantic segmentation for aerial platforms has been one of the fundamental scene understanding task for the earth observation. Most of the semantic segmentation research focused on scenes captured in nadir view, in which objects have relatively smaller scale variation compared with scenes captured in oblique view. The huge scale variation of objects in oblique images limits the performance of deep neural networks (DNN) that process images in a single scale fashion. In order to tackle the scale variation issue, in this paper, we propose the novel bidirectional multi-scale attention networks, which fuse features from multiple scales bidirectionally for more adaptive and effective feature extraction. The experiments are conducted on the UAVid2020 dataset and have shown the effectiveness of our method. Our model achieved the state-of-the-art (SOTA) result with a mean intersection over union (mIoU) score of 70.80%.

Корекція монетарної політики під впливом коронакризи та довгострокових чинників

The article shows the modification of monetary policy and modification of its interaction with fiscal policy in response to the challenges of the global financial crisis and the corona crisis, as well as reveals potential macroeconomic policy adjustments in response to long-term structural changes in the global economy. The specificity of the global financial and economic crisis, which was caused by financial intermediaries, and the belief in markets efficiency led to the dominance of monetary instruments in combating this crisis. However, purely monetary stimulus does not solve structural problems, and, acting with a very low degree of targeting, but on a huge scale, leads to the debt accumulation and financial crises. The corona crisis forced to resort to budget incentives to ensure targeted support for people and businesses and provided an impetus to discuss the ways to make better use of fiscal policy capacity to increase potential GDP and reduce inequality. The following potential long-term adjustments of macroeconomic policy are revealed: 1) increasing the emphasis on the interests of employees; 2) increasing the inclusiveness of monetary and fiscal policy; 3) the growing role of fiscal policy as an instrument of macroeconomic stabilization; 4) revision of the theory of monetary and fiscal policy interaction; 5) revision of the pre-emptive approach to anti-inflation policy, which means the reaction of monetary policy to deviations of the inflation forecast from the target, and the emergence of alternatives: response to the actual achievement and maintenance the inflation target for some time and compensation for the previous deviations from the inflation target; 6) modification of the optimal anti-inflationary policy in response to demand-pull inflation and cost-push inflation; 7) adjustment of the monetary policy in response to rising inflation due to the exhaustion of long-standing global disinflationary forces that have been in effect since the 1980s; 8) more active monetary and fiscal stimulus in emerging market economies.

User defined weight based budget and deadline constrained workflow scheduling in cloud

AbstractCloud computing is a technology that is being used by scientists for the execution of huge scale workflows as it has various features such as availability, faster, cheaper, elasticity, and high accessibility. In addition, the users are charged on a pay per use basis which makes it more efficient to be used by various clients. Scheduling workflows in the cloud is a difficult task as it takes into account the dependencies of workflows along with quality of service (QoS) demands. The problem becomes more challenging when there are multiple QoS objectives which are often disagreeing to each other. A lot of research has been done to minimize makespan and execution cost under deadline and budget constraints. This article presents a workflow scheduling algorithm based on Jaya to minimize them both and returns solutions according to the weights a user gives. The algorithm has been compared with Min‐Min, Max‐Min, Round Robin, heterogeneous earliest finish time first, first come first serve, minimum completion time, dynamic heterogeneous earliest finish time first in WorkflowSim. The results are compared based on both cost and time. In the end, a trade‐off between the objectives has been shown. Results show that Jaya performs much better than other algorithms when averaged over several iterations.

Fast Implementation of Genetic Algorithm Based on Software/Hardware Co-design Method

Genetic algorithm (GA) has been widely used since it was proposed. However, due to the complexity of the algorithm itself, the fact that the actual problems have huge data and scale, and that it needs to meet certain real-time requirements, the acceleration of genetic algorithm has become a hot spot in both academia and industry field. Previous work have been done on the acceleration of GA, which primarily focuses on the software aspect, while the existing work in hardware aspect lacks adaptability for different industrial scenarios. Therefore, this paper puts forward a novel architecture based on software/hardware co-design method, in which the software produces random numbers, and the hardware, taking full account of the characteristics of sequential circuit, is implemented in a hierarchical pipeline architecture. This architecture accelerates the algorithm while providing certain flexibility. This paper completes the simulation on MATLAB and Vivado, and the total running time is 987.4.u. Compared with the pure software implementation, the speed is increased by 73.9 times.

Characteristics, challenges and countermeasures of giant karst cave: A case study of Yujingshan tunnel in high-speed railway

Karst landforms were widely distributed all over the world, and they were mainly distributed in the Southwest and Southeast regions in China. However, tunnel construction in giant karst caves was rarely studied. In recent years, Yujingshan tunnel of Chengdu-Guiyang high-speed railway in Yunnan Province had encountered the largest karst cave in history of Chinese railway construction. This paper reported the hydrological and geological conditions of this case, as well as relationship between karst cave and tunnel, and compared it with the other three giant karst caves encountered in railway construction, and systematically analyzed the challenges it brought to tunnel construction, and put forward the corresponding countermeasures. Furthermore, in-situ monitoring results of the layered settlement of tunnel bottom and the crown settlement and horizontal convergence of tunnel in giant karst cave were analyzed. The results showed that the challenges mainly included: (a) huge scale of karst cave, (b) poor stability of cave wall, (c) poor stability and complex composition of filling content, (d) complex underground river and channels; the countermeasures mainly included: (a) backfill of cave, (b) roof reinforcement of cave, (c) both sides and the bottom reinforcement of tunnel, (d) diversion and closure of underground river, (e) bridge in the tunnel, (f) bench cut method. The feedback of in-situ monitoring results demonstrated the effectiveness of countermeasures. This case study can provide experience for construction of similar tunnels in giant karst caves.

The COVID-19-Led Reverse Migration on Labour Supply in Rural Economy: Challenges, Opportunities and Road Ahead in Odisha

Migration is a bigger option for earning and livelihood in Odisha either for push factors or pull factors, for which people move to other states in search of work and better wages. But COVID-19 emerged as a crippling blow for which huge reverse migration is being noticed in the state. So the study tried to investigate labour supply and employment opportunity in rural areas due to COVID-19-led reverse migration and to examine the impact of COVID-19 on employment status, income profile and livelihood of returned migrants in Odisha. The study also discusses the possible measures to create alternative livelihood by rebuilding the rural economy after COVID-19. Both secondary and primary data are used in the study. Descriptive statistics and regression model are used in the study to examine the vulnerability of migrants during the period of COVID-19. The study found a sudden rise in labour supply with a huge scale is catch sight of the rural economy of Odisha. Job loss is the biggest problem faced by migrants followed by income loss. The study found that income of migrants, household income excluding migrants and nature of work have significant impact on the vulnerability of migrants. JEL Classification Codes: J21, J22, J46

Formula omitted] model-driven recursive multi-scale denoising network for image super-resolution

Most existing deep learning based single-image super-resolution (SISR) methods mainly improve the reconstruction performances from the perspective of data-driven, i.e., widening or deepening the networks according to the huge scale of the training data. However, it will bring a huge amount of weights and biases, and cost the expensive computations. Recently, some people have proposed a new frame for designing the deep networks according to the algorithms deduced from the ℓ2-optimization problem. But they did not consider the case with outliers. Since ℓ1-norm can describe the sparsity of the outliers better than ℓ2-norm, we propose an effective deep network designed according to the new algorithm deduced from the ℓ1-optimization problem. In our proposed method, an effective iterative algorithm for the ℓ1 reconstructed optimization problem is deduced based on the split Bregman algorithm, majorization–minimization algorithm, and soft thresholding operator. Then according to the deduced iterative algorithm, an effective deep network, named ℓ1 Model-Driven Recursive Multi-Scale Denoising Network (ℓ1-MRMDN), is designed. Due to the iteration form of the deduced algorithm, the proposed ℓ1-MRMDN contains an inner recursion and an outer recursion. Therefore, our proposed method can not only relieve its sensitiveness to the outliers because of the ℓ1 data fidelity term, but also avoid designing the deep network blindly via the guidance of prior knowledge. Extensive experimental results illustrate that our proposed method is superior to some related popular SISR methods.

Technology Focus: Deepwater Fields (May 2021)

I cannot overstate that 2020 was one of the toughest years on our industry’s ecosystem. The huge scale of the crisis wreaked by the COVID-19 pandemic has affected us all in such an unprecedented way and added a hard-hitting dimension to our industry’s fragile outlook. The prolonged periods of lockdown and the hiatus mandated in several countries, including some of the high-consuming ones, resulted in the largest oil glut ever, which exacerbated the economics severely. The flat oil-supply curve erased almost all the growth of the last decade and has put our endurance, agility, and resilience to a hard test. The offshore segment, from which approximately 33% of global oil production comes, was confronted by this turmoil, and escalating challenges surrounded the viability and sustainability of deepwater developments like never before. Unlike previous downturns experienced by our industry, the record plunge in oil demand has put the effectiveness of previous measures of recovery, such as deferral of investments or waiting for an upturn in oil prices, under the microscope. As the headwinds of the pandemic continue reshaping the global economy, our industry, and the deepwater segment in particular, have no time to lose to rock the boat and upend assumptions in the post-COVID-19 world. Imminent substantive changes within the industry are inevitable to reduce uncertainty and risk and to prepare for the new decade and beyond of delivery in light of the rapid evolution of renewables. Major deepwater operators have made remarkable achievements in lowering the average breakeven price to around $50 per barrel from around $70 per barrel in the past 5 years. Increasing cost savings are vital, and innovative money-saving engineering notions are an essential tactic to achieve a lower breakeven price. Additional proportionate, strategic, and reinventive initiatives are needed for the deepwater sector to adapt to the new energy landscape and search for new areas of growth. They will govern the future of the sector and differentiate the pioneers from followers. I am in no doubt that redefining fundamental strategies toward the development of partnerships in joint deepwater projects, embracing cutting-edge fit-for-purpose and cross technologies, and prioritizing net-zero emissions are keys to unlocking transformational gains and leveraging the opportunity to promote a sustainable future for the deepwater sector. Recommended additional reading at OnePetro: www.onepetro.org. SPE 200522 - A Novel Deepwater Kick-Control Strategy for Handling Riser Gas Unloading With Data-Driven Parameter Estimation by Qifan Gu, The University of Texas at Austin, et al. SPE 200429 - Investigation of Permeability Impairment Caused by Asphaltene Precipitation During Gas-Injection EOR in a Major Gulf of Mexico Field by M.R. Fassihi, BHP, et al. SPE 202296 - Analyzing Critical Elements in Openhole Gravel-Pack-Treatment Design Cycle: Case Study in Indian Ultradeep Water by Vaibhav Gupta, Schlumberger, et al.

On the flood paradigm of aqua-geological arrangement of the future rural architecture

High waters systematically flood large areas and villages with their agricultural lands. People, livestock and crops perish on a huge scale. This situation should be accepted as a living condition, not an emergency. For this we need to radically reconstruct the buildings and architectural landscapes so that the floods stop being destructive. A variant of floating villages and their buildings, structures, and roads based on pontoon-pile systems and the creation of modular pontoon parks is proposed in this paper. The scale of the phenomenon requires the introduction of an appropriate national project.

Ceramics in architecture

The article analyzes the role of decorative ceramics in solving architectural problems of the traditional “architecture - painting - sculpture” triad and organizing the architectural and spatial environment. Ceramists use ceramics in unusual ways. Their solutions are crucial for the synthesis of arts. In the current architectural space, ceramics should not be considered as a building material or an element of the decorative or monumental arts. Its applications in the architectural spatial environment require studies of fundamental problems of the synthesis of arts. A literature review has identified an unusual pace of ceramics development. It penetrates into adjacent areas and shows a trend towards “omnipresence”. Therefore, a deep analysis of the ongoing processes is required. The appearance of a modern city is determined by the huge scale of construction. At the same time, the issues of emotional enrichment and individualization of the architectural space are acute. Irkutsk is famous for its rich historical experience in using ceramics as a building material. It is necessary to preserve the individual appearance of the city with a rich historical heritage. New applications of the ancient material are determined by its remarkable plasticity, color and texture properties. Combining plasticity and color, ceramics can be used as a material for monumental sculpture and jewelry modeling. It is cheap and possess good artistic and utilitarian qualities.

Generations of Stateless People: Many Years of The Rohingya’s Personal Security at Risk and the Support of the EU

The Rohingya is an ethnic-religious Muslim minority that has struggled with serious human rights violations for decades. Indian migration to Burma, stimulated by British colonial rule, is pointed to as the main cause of the Muslim-Buddhist conflict. Although Indians in Burma currently constitute a fraction of the population (2.3%), resentment remained. The aim of the article is to analyze the threats to many aspects of the personal security of the Rohingya population. It is one of the most populous groups of stateless persons in the world; moreover, since the 1960s, this ethnic group has experienced oppression on a huge scale: from restrictions related to work and movement as well as difficult access to health care and education, through deprivation of civil rights , to physical violence and even death. All this is happening in the 21st century in front of the world. In order to better understand the Rohingya conflict with the Burmese army, the historical context and the course of the conflict were presented. The assistance activities of the European Union and possible solutions to this humanitarian crisis were also indicated.

An efficient reasoning method on logic programming using partial evaluation in vector spaces

Abstract In this paper, we introduce methods of encoding propositional logic programs in vector spaces. Interpretations are represented by vectors and programs are represented by matrices. The least model of a definite program is computed by multiplying an interpretation vector and a program matrix. To optimize computation in vector spaces, we provide a method of partial evaluation of programs using linear algebra. Partial evaluation is done by unfolding rules in a program, and it is realized in a vector space by multiplying program matrices. We perform experiments using artificial data and real data, and show that partial evaluation has the potential for realizing efficient computation of huge scale of programs in vector spaces.

Research and Exploration of Steel Structure Deepening Design Based on Multi User Mode

Steel structure with its high strength, light weight, good seismic performance, high degree of industrialization, short construction period, strong plasticity, energy conservation and environmental protection and other comprehensive advantages, has been widely used in machinery, construction and many other fields. But because of its huge scale, increasingly complex structure, project management is facing many problems. Based on the multi-user mode of steel structure in-depth design, the technology of product modelling, structural analysis, in-depth design, engineering calculation, processing and manufacturing and cost control are studied, especially the advantages in model creation and component manufacturing bring more possibilities for the mechanical industry. Based on the multi-user mode, the steel structure deepening design technology integrates the technical requirements of the project, provides clear information for the owner, designer, raw material supplier, manufacturer, construction party, etc., promotes the implementation of the project, improves the achievement degree of the project, and improves the control ability of the engineering personnel. A number of foreign large-scale bulk material conveying systems have obtained good benefits by using the steel structure deepening design technology based on the multiuser mode, which improves the industrialization degree of steel structure component design and manufacturing, so that the research results have good practicability and operability. The research results have positive guiding significance for the practice of steel structure deepening design.

Determining Optimum Productivity of a Ball Drum Mill When Milling Brown Coals

Ball drum mills (BDM) are one of the main types of coal-grinding equipment in Russia. A significant drawback of BDM is high power consumption (a significant part of the TPP’s own needs). With a huge scale of production, reducing these costs even by a few percent gives a significant economic effect. The problem of minimizing the specific energy consumption for grinding and transporting Azean coal in an ShK-32 ball drum mill is considered. For moist brown coals, the efficiency of grinding and transport of coal dust is usually achieved in the mode of equality of the grinding and drying capacities of the mill. The implementation of this regime is a necessary but insufficient condition. A system of equations is obtained that describe the processes of grinding and transport of coal dust. The analysis of the equations shows that the specific energy consumption for grinding is inversely proportional to the air consumption, and the specific costs for the transport of the dust and gas flow are proportional to the square of the air consumption. This fact ensures the presence of a minimum specific energy consumption for pulverization. A comparison is made of the estimated consumption of specific energy for pulverizing in an ShK-32 ball drum mill with experimental results obtained during routine commissioning tests of the dust system of the Irkutsk CHPP-9. The average deviations of the calculation results from the experimental data are in the range of ±10%. Comparison of the calculated and experimental data indicates that the mathematical model of the mode of equality of the grinding and drying capacities of the BDM adequately describes the processes occurring during the preparation of fuel for combustion. It is shown that an increase in the efficiency of dust systems with BDM can be achieved only after a detailed study of the transport of coal dust. In the proposed method for determining the optimal performance of the ball mill, the effect of the polydispersity of coal dust on the aerodynamic resistance of the mill is consistently taken into account.