Gathering System Research Articles

Review of Semantic Importance and Role of using Ontologies in Web Information Retrieval Techniques

The Web contains an enormous amount of information, which is managed to accumulate, researched, and regularly used by many users. The nature of the Web is multilingual and growing very fast with its diverse nature of data including unstructured or semi-structured data such as Websites, texts, journals, and files. Obtaining critical relevant data from such vast data with its diverse nature has been a monotonous and challenging task. Simple key phrase data gathering systems rely heavily on statistics, resulting in a word incompatibility problem related to a specific word's inescapable semantic and situation variants. As a result, there is an urgent need to arrange such colossal data systematically to find out the relevant information that can be quickly analyzed and fulfill the users' needs in the relevant context. Over the years ontologies are widely used in the semantic Web to contain unorganized information systematic and structured manner. Still, they have also significantly enhanced the efficiency of various information recovery approaches. Ontological information gathering systems recover files focused on the semantic relation of the search request and the searchable information. This paper examines contemporary ontology-based information extraction techniques for texts, interactive media, and multilingual data types. Moreover, the study tried to compare and classify the most significant developments utilized in the search and retrieval techniques and their major disadvantages and benefits.

An Investigation of the Policies and Crucial Sectors of Smart Cities Based on IoT Application

As smart cities (SCs) emerge, the Internet of Things (IoT) is able to simplify more sophisticated and ubiquitous applications employed within these cities. In this regard, we investigate seven predominant sectors including the environment, public transport, utilities, street lighting, waste management, public safety, and smart parking that have a great effect on SC development. Our findings show that for the environment sector, cleaner air and water systems connected to IoT-driven sensors are used to detect the amount of CO2, sulfur oxides, and nitrogen to monitor air quality and to detect water leakage and pH levels. For public transport, IoT systems help traffic management and prevent train delays, for the utilities sector IoT systems are used for reducing overall bills and related costs as well as electricity consumption management. For the street-lighting sector, IoT systems are used for better control of streetlamps and saving energy associated with urban street lighting. For waste management, IoT systems for waste collection and gathering of data regarding the level of waste in the container are effective. In addition, for public safety these systems are important in order to prevent vehicle theft and smartphone loss and to enhance public safety. Finally, IoT systems are effective in reducing congestion in cities and helping drivers to find vacant parking spots using intelligent smart parking.

“Improvement in Power Quality of Grid Connected PV & Wind Power Generation System”

Abstract: Power structure is really extraordinary and future one system. In this structure, there is wind system with neighboring planetary gathering and diesel generator system, which is limit in one spot that is reserves (Batteries) and yield, gives age sources, little turbines system used in hybrid, infers relationship with battery, diesel-generator and photovoltaic system. The breeze is a wellspring of free-energy, which has been used since bygone era. It is used of wind stream through wind turbine to provide the mechanical ability to change into electrical power this structure for used by a wide margin off and off-network system in like manner, that marvel called hybrid power system. Now and again, this blend power system in any case called Green Energy. Mix of something like two economical power sources is more convincing than single. This is called as blend system. 'Hybrid' connotes unite harmless to the ecosystem power sources headways. This advancements yield gives electric deftly gets at home, on-network and so forth Numerous combination system sources, which worked off-grid structure, not related with an appropriated structure from this system, we set aside the energy power stream in batteries. A mix of somewhere around two supportable power sources is more effective than a singular is brought with respect to cost, capability and reliability. Energy is the main element for both present day and agribusiness progression of any country. Keywords: Charging station, DC grid, Electric vehicle, MATLAB Simulink

Damage Classification Using Supervised Self-Organizing Maps in Structural Health Monitoring.

Improvements in computing capacity have allowed computers today to execute increasingly complex tasks. One of the main benefits of these improvements is the possibility of developing machine learning algorithms, of which the fields of application are extensive and varied. However, an area in which this type of algorithms acquires an increasing relevance is structural health monitoring (SHM), where inspection strategies and guided wave-based approaches make the evaluation of the structural conditions of an aircraft, vessel or building among others possible, by detecting and classifying existing damages. The use of sensors, data acquisition systems (DAQ) and computation has also allowed these damage detection and classification tasks to be carried out automatically. Despite today’s advances, it is still necessary to continue with the development of more robust, reliable, and low-cost structural health monitoring systems. For this reason, this work contemplates three key points: (i) the configuration of a data acquisition system for signal gathering from an an active piezoelectric (PZT) sensor network; (ii) the development of a damage classification methodology based on signal processing techniques (normalization and PCA), from which the models that describe the structural conditions of the plate are built; and (iii) the use of machine learning algorithms, more specifically, three variants of the self-organizing maps called CPANN (counterpropagation artificial neural network), SKN (supervised Kohonen) and XYF (X–Y fused Kohonen). The data obtained allowed one to carry out an experimental validation of the damage classification methodology, to determine the presence of damages in two aluminum plates of different sizes, where masses were added to change the vibrational responses captured by the sensor network and a composite (CFRP) plate with real damages, such as delamination and cracks. This classification methodology allowed one to obtain excellent results by validating the usefulness of the SKN and XYF networks in damage classification tasks, showing overall accuracies of 73.75% and 72.5%, respectively, according to the cross-validation process. These percentages are higher than those obtained in comparison with other neural networks such as: kNN, discriminant analysis, classification trees, partial least square discriminant analysis, and backpropagation neural networks, when the cross-validation process was applied.

Impact of Integration of the Production Systems and Reservoir of a Benchmark Based on Carbonate Fields

AbstractIntegrating production system and reservoir is used in several studies of offshore oilfield development and management for improved production forecasts through more realistic boundary conditions. This study evaluates the influence of the parameters in a production strategy of a reference model (carbonate oil reservoir) on financial and production performance. We first considered nonintegrated system (NI) with the reservoir and fixed boundary conditions for well and gathering system. We then considered integrated system (I) with the variable boundary conditions for the wells and gathering system. Finally, we compared both systems. Our analysis involved several steps to define the best production strategy for both systems based on net present value (NPV) and how integrated modeling helps define production strategy. For NI, three stages were considered: number of wells, placement of wells, and platform capacity. For I, five stages were evaluated (all NI parameters) with diameters and gas lift evaluation, and platform placement. The results are similar, but the simplifications (NI) may affect financial performance. The cross analysis indicated (in the hypothesis that the integrated system is closer to reality) that integrating the NI case resulted in considerable financial and production differences and may be useful in simplified systems. Since the main aspects of the object-function financial return were related to reservoir model behavior, one can first apply the nonintegrated optimization cycles, then add the integrated cycles, obtaining an intermediate time of the integrated model optimization in similar cases.

When Mediators Need Machines (and Vice Versa): Towards a Research Agenda on Hybrid Peacemaking Intelligence

Abstract The growing use of artificial intelligence (AI) in peace processes challenges the ways in which mediators conventionally generate and use knowledge to facilitate a convergence of conflict party positions. Mediators are increasingly unable to maintain their role as information brokers without the support of automated information gathering and analysis systems. However, the effectiveness of such AI-tools is likewise hampered by their limited autonomy across peacemaking contexts, by the paradigmatic nature of knowledge that is used to design AI-systems, and the influence of subjective factors that are difficult to measure. These challenges may be overcome by hybrid human-machine systems in support of peacemaking. This article formulates a research agenda for hybrid peacemaking intelligence that is concerned with the increasing interdependence of humans and machines. It suggests studying how agency is distributed in mediator-machine networks, the hermeneutics of machine-supported participatory approaches, and how hybrid arrangements change power relations in peacemaking.

New Design and Optimization of a Jet Pump to Boost Heavy Oil Production

In the Oil and Gas industry, installing pipe loops is a well-known hydraulic practice to increase oil pipeline capacities. Nevertheless, pipe loops could promote an unfavorable phenomenon known as fouling. That means that in a heavy oil-water mixture gathering system with low flow velocities, an oil-water stratified flow pattern will appear. In consequence, due to high viscosity, the oil stick on the pipe, causing a reduction of the effective diameter, reducing handled fluids production, and increasing energy consumption. As jet pumps increase total handled flow, increase the fluid velocities, and promote the homogenous mixture of oil and water, this type of pump could result attractive compared to other multiphase pump systems in reactivating heavy crude oil transport lines. Jet pumps are highly reliable, robust equipment with modest maintenance, ideal for many applications, mainly in the oil and gas industry. Nevertheless, their design method and performance analysis are rarely known in the literature and keep a high experimental component similar to most pumping equipment. This paper proposes a numerical study and the optimization of a booster multiphase jet pump system installed in a heavy oil conventional loop of a gathering system. First, the optimization of a traditionally designed jet pump, combining CFD simulation and optimization algorithms using commercials software (ANSYS CFX® and PIPEIT® tool), has been carried out. This method allowed evaluating the effect of multiple geometrical and operational variables that influence the global performance of the pump to run more than 400 geometries automatically in a reduced time frame. The optimized pump offers a substantial improvement over the original concerning total flow capacity (+17%), energy, and flow distribution. Then, the effect of the three jet pump plugin configurations in a heavy oil conventional trunkline loop was analyzed. Simulations were carried out for different driving fluid pressures and compared against a traditional pipeline loop’s performance. Optimum plugin connection increases fluid production by 30%. Finally, a new eccentric jet pump geometry has been proposed to improve exit velocities and pressure fields. This eccentric jet pump with the best connection was analyzed over the same conditions as the concentric optimized one. An improvement of 2% on handled fluid was achieved consistently with the observed uniform velocity field at the exit of the pump. A better total fluid distribution between the main and the loop line is obtained, handling around half of the complete fluid each.

Exergy Analysis of Energy Comprehensive Utilization in Oil Field Gathering and Transportation System

Exergy Analysis of Energy Comprehensive Utilization in Oil Field Gathering and Transportation System

Theoretical and Conceptual Approaches to Defining the Concept of Economic Intelligence in the Ukrainian Scientific Practice

This contribution is dedicated to the study of theoretical and conceptual aspects of economic intelligence. The goal of the research is to theoretically define the notion of economic intelligence and categorize the forms of its implementation with regard to the wide range of tools used to obtain, process and analyze information. Since economic intelligence is a separate analytical phenomenon, the author focuses on a series of relevant research tasks that disclose the theoretical essence of such notions as “economic intelligence”, “competitive intelligence” and “industrial espionage” as well as elaborate on their distinctive features in the context of data management process. Moreover, the author singles out the principles of information security within the context of intelligence activities and scientifically substantiates the forms of economic intelligence implementation with respect to the use of data acquisition methods. In the course of the research on economic intelligence, the author emphasizes the existence of various methods to acquire information necessary for the effective functioning of a state, organization or enterprise, which facilitates the successful solving of strategic and operational issues in the policy-making process. Furthermore, the economic intelligence data helps to identify new market opportunities as well as potential risks, and, subsequently, modify economic activities and plans on the development of an enterprise environment. Having studied theoretical aspects and forms of economic intelligence, the author reaches conclusions regarding the notion of economic intelligence as well as its forms – competitive intelligence and industrial espionage. It is determined that economic intelligence represents a system of covert search, gathering, compilation, analysis and goal-oriented use of strategic intelligence. The author notes that economic intelligence can be studied within the contexts of its separate forms, namely the competitive intelligence (as a lawful method to acquire data) and industrial espionage (as an unlawful method of acquiring data). The comparative analysis reveals that the notions of economic and business intelligence can be considered synonyms, although business intelligence in less associated with the illegal gathering of information. The author states that business intelligence is not synonymous with industrial espionage. Even being forms of economic intelligence, the notions of competitive intelligence and industrial espionage cannot be interpreted as one phenomenon, for they differ in the characteristic methods of data acquisition.

Adaptive analysis of multistage down-hole throttling and optimization design of process parameters in Sulige gas field

The Sulige Gas Field mainly adopts down-hole throttling production technology. For gas Wells with high bottom-hole pressure and productivity and low pressure drop in the testing process, it is difficult to reduce the wellhead pressure to the ideal value by installing a single-stage down-hole throttle, which cannot meet the needs of existing middle and low-pressure gas gathering technology in Sulige Gas field. Therefore, it is proposed to adopt down-hole multi-stage throttling technology, which not only makes full use of the residual pressure and heat of the well bore, but also ensures the safety of the surface gathering and transportation process system and the normal production of gas wells. In this paper, the optimization design method and theory for the technological parameters of the down-hole multi-stage throttling system of gas wells are established. According to the constraint of low-pressure gas collection mode in a temperature and pressure of wellhead safety to determine the number of down-hole choke and the process parameters. Discuss the applied conditions of down-hole multi-stage throttling, and provide theoretical support for the selection of the down-hole choke technology of the Sulige gas well and the safe and stable production of the gas well. It has important guiding significance for gas field quality and efficiency improvement and fine management.

Concept and Proof of the Lifelog Bigdata Platform for Digital Healthcare and Precision Medicine on the Cloud.

PurposeWe propose the Lifelog Bigdata Platform as a sustainable digital healthcare system based on individual-centric lifelog datasets and describe the standardization of lifelog and clinical data in its full-cycle management system.Materials and MethodsThe Lifelog Bigdata Platform was developed by Yonsei Wonju Health System on the cloud to support digital healthcare and precision medicine. It consists of five core components: data acquisition system, de-identification of individual information, lifelog integration, analyzer, and service. We designed a gathering system into a dedicated virtual machine to save lifelog or clinical outcomes and established standard guidelines for maintaining the quality of gathering procedures. We used standard integration keys to integrate the lifelog and clinical data. Metadata were generated from the data warehouse after loading combined or fragmented data on it. We analyzed the de-identified lifelog and clinical data using the lifelog analyzer to prevent and manage acute and chronic diseases through providing results of statistics on analysis.ResultsThe big data centers were built in four hospitals and seven companies for integrating lifelog and clinical data to develop the Lifelog Bigdata Platform. We integrated and loaded lifelog big data and clinical data for 3 years. In the first year, we uploaded 94 types of data on the platform with a total capacity of 221 GB.ConclusionThe Lifelog Bigdata Platform is the first to combine lifelog and clinical data. The proposed standardization guidelines can be used for future platforms to achieve a virtuous cycle structure of lifelogging big data and an industrial ecosystem.

Cloud computing rising in the field of big data and artificial intelligence

Cloud Computing is a strong, large-scale and complex Computing technology. It lessens the need to maintain an expensive, specialized computer hardware area, as well as expensive software and software. Cloud computing has shown a significant increase in data quality or the production of large amounts of data. Big data processing is a difficult and time-consuming operation that necessitates the use of a large computer system in order to ensure performance. Knowledge creation and analysis are two intertwined activities and this paper investigates the rise of Big Data and Artificial Intelligence (AI) in Cloud Computing research. As data storage and mining methods advance, the preservation of expanding data quantities is characterized by a change in the core of structured results. This shift is reflected in the evolution of structured results. However, one major barrier is that this rate of growth surpasses the ability of data gathering systems and cloud infrastructure platforms to be upgraded. Workloads are really heavy and it is possible that certain cloud computing disputes will be created, which will include the description, characteristics, and categorization of huge data. In addition, analysis problems based on data integrity, heterogeneity and protection.

Effectiveness of a digital data gathering system to manage the first pandemic wave among healthcare workers in a main European coronavirus disease 2019 (COVID-19) tertiary-care hospital.

To evaluate the information collected from workers infected with severe acute respiratory coronavirus virus 2 (SARS-CoV-2) or close contacts using a digital data gathering system (DDGS) developed at the onset of the coronavirus disease 2019 (COVID-19) pandemic to better manage the spread of infection at our hospital. Observational retrospective study. Tertiary University Hospital "Spedali Civili" Hospital, Brescia, Italy. Workers (most of whom are healthcare workers) employed at the hospital. The information collected by the DDGS was transferred to the IBM SPSS statistical software package and then statistically analyzed. Overall, ∼16% of the hospital workforce was infected by SARS-CoV-2 in the first pandemic wave. Nurses were the professional category with the highest infection rate (∼15%). The asymptomatic rate of infection was between 31% and 62%. Positive molecular swabs were significantly more frequent in workers undergoing the test after sending a signaling form to our DDGS. Among workers sending the signaling forms, the information about symptoms was more predictive in terms of risk, compared to the close-contact information. The concordance between molecular swabs and subsequent serological testing was significantly higher in workers signaling their at-risk condition through the DDGS. Overall, our data demonstrate the advantages of a digital system to gather information from workers, which is useful for managing emergencies such as the COVID-19 pandemic. This holds particularly true for large organizations such as hospitals.

Understanding Domestic Food Safety: An Investigation into Self-Reported Food Safety Practice and Associated Factors in Southern Ethiopian Households.

Background:According to available studies, 12%-20% of reported foodborne outbreaks start in the household. It is projected that 1 out of every 10 persons will become ill as a result of consuming tainted food. Poor food handling practices cause 600 million foodborne illnesses each year. In a given year, this leads to 420 000 deaths. In Ethiopia, there is a scarcity of studies on home-food-safety practices and the factors that affect them. This has resulted in a shortage of relevant information on the status of home-food-related illnesses in the country.Methods:A community-based cross-sectional study was carried out from May to June 23, 2021. A standardized and pre-tested questionnaire was used to collect data from 622 households. The total plate count method was used to analyze bacteria on cleaned plates. Epi data version 3.1 was used to enter data, while SPSS version 25 was used to analyze the data. Descriptive statistics and multivariable regression were used to characterize the data and identify factors associated with food safety practices.Result:51.1% of the study participants had a safe food handling practice. The mean total plate count was 2.34 CFU/cm2. In the multivariable regression, Household wealth (AOR = 2.05, 95% CI [1.01-3.16]), Education (AOR = 3.33, 95% CI [1.41-6.31]), Training (AOR = 2.85, 95% CI: [1.31–3.19]), Knowledge of safe practices (AOR = 1.95, 95% CI [1.23-3.08], and Attitude (AOR = 2.04, 95% CI [1.09, 3.82]) were associated with safe food handling practices.Conclusion:Although data gathering systems for food-borne diseases typically overlook a large number of home-based outbreaks of sporadic infection, it is now widely understood that many episodes of food-borne sicknesses are caused by individuals’ inappropriate food handling and preparation in their kitchens. In the current study, educational status, household wealth, food safety training, attitude, and knowledge about FBDs were found to be strongly associated with safe practices. This implies that public education is a key factor in improving food safety practices at home.

KONTRIBUSI ARISAN ONLINE DALAM MEMENUHI GAYA HIDUP MAHASISWA MENURUT SUDUT PANDANG EKONOMI ISLAM (Studi Kasus Pada Kelompok Arisan Mahasiswa Fakultas Ekonomi Dan Bisnis Islam Universitas Islam Negeri Sumatera Utara)

<em><span style="font-size: 11pt; line-height: 152%; font-family: 'Times New Roman', 'serif';" lang="IN">The progress of the development of life in Indonesia affects the lifestyle, especially students. Student, someone who demands education at higher education, has many necessities of life to fulfill his studies and daily life. Online arisan is an alternative for students to save money to fulfill their daily needs. This study aims to see how to see members who are online arisan, see which ones contribute to online arisan in fulfilling student lifestyles, and see a review of Islamic economics on online social gathering activities in the Islamic economics faculty of the State Islamic University of North Sumatra. The research method used a qualitative approach with data techniques, namely primary data and secondary data. Research subjects, the owner of the arisan and (9) members of the online arisan. Data techniques are premier data and secondary data. The data analysis methods used in the study were data reduction, data presentation, and conclusion drawing. The results of this study indicate that the lifestyle of students who take part in an online social gathering is classified as hedonistic, the contribution of online arisan to the arisan group is that there are many benefits obtained by members and an Islamic economic review of the online social gathering system is not allowed because it contains elements of usury in it.</span></em><p class="MsoNormal" style="margin-top: 0cm; margin-right: 0cm; margin-bottom: .0001pt; margin-left: 13.55pt; text-align: center; text-indent: -13.55pt; line-height: 112%;" align="center"><strong><span style="mso-bidi-font-size: 12.0pt; line-height: 112%; font-family: 'Garamond','serif';" lang="IN">KONTRIBUSI ARISAN ONLINE DALAM MEMENUHI GAYA HIDUP MAHASISWA MENURUT SUDUT PANDANG EKONOMI ISLAM</span></strong></p><h1 style="margin-top: 0cm; margin-right: 0cm; margin-bottom: 10.0pt; margin-left: .5pt; text-align: center;" align="center"><span style="mso-bidi-font-size: 12.0pt; line-height: 107%; font-family: 'Garamond','serif';" lang="IN">(Studi Kasus Pada Kelompok Arisan Mahasiswa Fakultas Ekonomi Dan Bisnis Islam Universitas Islam Negeri Sumatera Utara)</span></h1>

Measurement project interoperability for real-time data gathering systems

The Internet-of-Things devices have allowed the increment of the Spatiotemporal resolution in the Real-time Data Gathering Systems. However, this has increased the complexity due to the heterogeneity of sensors. Thus, it is important to know how data can be understood aware of its context at the edge. Also, a transversal perspective is expected for aligning and reusing as many sensors as possible (based on an experimental design). Because of the hardware limitations, the experimental design should be communicated as simple, integrated, and consistent as possible under single content fostering the projects’ complementarity. This work describes a strategy for defining and communicating a set of measurement projects, following a conceptual hierarchy derived from a measurement ontology. Every project definition is obtained from the user requirements following a well-established strategy. BriefPD is introduced as a data interchange format that is self-contained, partially verifiable (through a Merkle tree insight), consistent, and does not require the use of tags to determine the content meaning. BriefPD generates a project definition in 6.27 ms (1.9 times quicker than JSON-equivalent), consuming 20.39% of JSON’s size. A Github library is provided with the reference implementation jointly with a ‘Code Ocean’ capsule for reproducing the simulation results.

General models for topology layout of oil and gas star-tree pipeline network

Oil&gas gathering pipeline network structure is a significant part of oil&gas field construction, and the rational construction of pipeline network is directly related to the efficiency and benefits of oil&gas field production. Therefore, optimizing the gathering and transportation system of oil and gas fields is the key to reducing development costs. The star-tree type pipe network is widely used in the gathering and transportation system. In order to optimize the star-tree pipe networks (STPNs) that has restrictions on the processing capacity and gathering radius of the station as a whole, this paper establishes four models of pipe network layout with specific constraints. They are Mixed-Integer Linear Programming Models with a large number of discrete variables. We take two virtual fields as examples, use CPLEX solver to solve the above four models as a whole, to obtain the optimal scheme, and also figure out the investment of the pipeline network. We further optimize the hierarchical optimization of the pipeline network with special constraints, then compare and analyze results obtained by the overall optimization. Finally, models are applied to an actual oil field and an actual gas field as examples to optimize the layout, which verifies the validity and feasibility of the models.

Influence of water cut and rates of cooling on oil flow

Oils with anomalous properties are characterized by large values of density, viscosity, high content of paraffinic hydrocarbons and asphaltene-resinous substances (up to 30%), high pour point (3538C), which increases the likelihood of complications in the processes of production, field gathering and oil treatment. Therefore, for many countries with cold climatic conditions, the problem of improving the low-temperature properties of oils is one of the most pressing problems in the production and transportation of hard-to-recover oils. Recent studies show that the rates of heating / cooling processes have a great influence on the rheological properties of natural oil mixtures during heat treatment. The experience of operating oil fields shows that in oil gathering and transportation systems, due to the water cut of oils and the aggressiveness of formation waters, persistent oil emulsions are often formed, which complicate the commercial preparation of oils.
 The article presents the results of studies of the influence of the water cut factor on the transportation of well products, as well as the effect of the cooling rate on the pour point of oil emulsions. Laboratory studies have shown that an increase in the water content in emulsions of more than 40% leads to a significant increase in viscosity over the entire temperature range. It is also shown that an increase in water cut increases the pour point of oil by 7-14С.

Regulatory oversight on the use of experimental therapies during a pandemic: The case of early access to convalescent plasma therapy in three LMICs

Clinicians, especially in low- and middle-income countries (LMICs), contend with limited economic and healthcare resources in deciding appropriate and feasible care for their patients. Some of the LMICs affected by COVID-19 implemented convalescent plasma therapy without sufficient regulatory guidance. Based on this experience, there are several requirements going forward, including: the need for an immediately accessible data gathering and processing system; the necessity of establishing regulatory pathways for early access to experimental treatment during emergency situations; and the accompanying reporting and monitoring requirements must be set. The different stakeholders must also be properly incorporated in the system that such a pathway will create, without neglecting to properly inform the public of the patient rights especially during an emergency situation.

Improvement and Application of Segmented Pigging Process for Gathering and Transportation System in Puguang Gas Field, China

AbstractGathering-transferring Pipeline 1 of the Puguang Gas Field employs a procedure that mixes gas and liquid for transportation. The inner wall of the pipeline is coated with a 0.1-mm-thick cor...