bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning Prediction of Formation Evaluation Logs in the Gulf of Mexico
Authors: LeCompte Brian , Majekodunmi Tosin , Staines Mike , Taylor Gareth , Zhang Barry , Evans Randy , Chang Nathan
Published: August 2021

The objective of the paper is to describe the application of artificial intelligence software to predict formation evaluation logs (compressional sonic, shear sonic and density) using only gamma ray, and resistivity log data and drilling dynamics data as received by the electronic drilling recorder (EDR). The software was applied real-time as a well was being drilled in deepwater Gulf of Mexico.

Thorough examination and conditioning of EDR and wireline data give way to a training model construction for the artificial neural network (ANN) using full suites of log-data in offset wells. Next, a neural network architecture and associated hyperparameters are chosen and tested. The fully trained and validated model is applied to the gamma ray, resistivity and EDR of the target well while drilling. Real-time EDR and wireline data flow via WITSML from rig to cloud and data is delivered to the client. The results of the study indicate the simulated log data were comparable to those measured from conventional logging tools over the study area. In both blind well tests the density agreed with the conventional log results within 1.1 % and the compressional within 2.51 % (Figure 1). Each of these is well within the range of variance expected of repeat runs of a conventional logging tool. A primary driver for near real-time logs was to confirm structural depth of the target sands along the well bore. There was a depleted sand below the expected TD of the well that, if encountered, could have led to total losses and possible loss of the wellbore. It was critical to have real-time logs to characterize the sands above the depleted sand, using every possible petrophysical and geologic character to refine the log correlation. This integration of all the logs provided the best interpretation of the sand quality and led toward the completion decision. AI-based logs are a highly cost-effective alternative to LWD logging. It presents an environmentally friendly approach as there is no logging personnel on-site and no expensive and potentially dangerous nuclear sources in the hole

The deployment of this patented, machine learning-driven, real-time simulation of formation evaluation logs is unique in using only gamma ray, resistivity and drilling data. It is particularly useful in the overburden section where formation evaluation tools are often not run for cost reasons, in side-tracks, in HP/HT settings and operational risk mitigation. It provides additive data for other petrophysical/QI/rock property analyses including seismic inversion, shale content, porosity, log QC/editing, real-time LWD, drilling optimization, etc.
3D Stress Field Modeling for Wellbore Stability Analysis
Authors: Li Shaoxuan , Liu Lei , Han Zhilei , Wu Rui , Guo Naichuan
Published: August 2021

Borehole collapse is one of the difficult problems in offshore oilfield drilling, which is directly related to regional geostress field. Seismic inversion is widely used to construct 3D stress field, and the accuracy of seismic inversion results depends heavily on the quality of seismic data. Therefore, in the development oilfield with poor seismic data quality, we use attribute modeling method to construct high-precision 3D geostress field to help analyze the wellbore stability of oilfield development wells. First, 3D structural model is created by using seismic interpretation horizon and fault. Then, the 3D stress body is constructed by filling the vertical and horizontal attributes according to certain constraints by using the known geostress values at the wellbore of the drilled development wells.

P oilfield is a large Neogene oilfield located in Bohai Bay. The serious expansion of the wellbore in the shallow unconsolidated sandstone in the oilfield area leads to high engineering risks. Moreover, due to the influence of large-scale gas cloud area, the effective wave energy on seismic profile is submerged. Through the above attribute modeling method, the high-precision 3D geostress field of P oilfield is successfully constructed. Practical application shows this method is suitable for the evaluation of geostress and wellbore stability analysis in areas with high well control in the middle and late stages of oilfield development. Especially in the area where the seismic data is not reliable enough, the 3D modeling results of this method has higher accuracy than the seismic inversion results.
Offshore LNG and Gas Monetization
Authors: Alabi Femi Adeoye
Published: August 2021

Objectives/Scope

In recent years, there has exceptional expansion of the liquefied natural gas industry (LNG), which is largely attributed to rising demands in various parts of the world and triggered the emergence of Floating LNG (FLNG) as a faster and more cost-effective strategy for exploitation of gas resources with a huge competitive advantage in the business activities. However, the introduction of new technologies comes with new requirements for tax related issues.

Methods, Procedures, Process

It is a testament to the resilience and adaptableness of the LNG business to check the hypothesis that FLNG provides a method by that stranded gas discoveries will be monetized and essentially within a shorter time, lower fabrication execution risk and the entrepreneurial vibrancy that comes from competitive suppliers and approaches on FLNG. On FLNG plant cost, Brian Songhurst gives a review review of the state of the performance of FLNG after commissioning. The need for the FLNG industry to address both cost base and contractual price formation mechanisms as a viable channel for the delivery of gas is key.

Results, Observations, Conclusions

The impact of Independent Power Projects (IPP) in the third World nations act as game-changer in the monetization, new gas markets discoveries and increasing impact on the global gas economy. FLNG has potentials to transform the phase transition business from technical and business stand points within the economic development of remote offshore oil fields. The opportunity provided by the contractors to lease the FLNG vessel enables the smaller independent energy companies to avoid arranging project finance and carrying the asset on their balance sheet. However, it could also assist the major energy companies where current low oil prices are restricting capital investment to lease their FLNGs. Given the high level of interest in the researcher's two previous papers, this update will prove equally interesting and useful to analysts and participants in the gas sector, as floating technology continues to open new opportunities. Cost Comparison of the FLNG offerings are following a more industry standard design approach based on functional specifications and vendor standard equipment rather than client standards and design methods as used by the energy companies. The reason for the quality style approach is to position the FLNG facilities to be hired and reused by energy company.

Novel/Additive Information

The price of producing LNG from offshore gas reserves through the FLNG ought to be less than from onshore plants thanks to the lower CAPEX, albeit this will be somewhat offset by higher OPEX. This paper provides an update on the floating LNG sector (both floating liquefaction and regas terminals) over the past few years looking into some of the publication of the floating liquefaction (FLNG) contribution from the Oxford Institute for Energy Studies.
Design Considerations for Polyester Construction Stretch Removal and its Impact on Mooring System Design
Authors: Moideen Hisham , Le-Guennec Stephane , Mansour Alaa M. , Peng Cheng , Huntley Mark
Published: August 2021

Polyester based mooring systems offer unique challenges from design, analysis and installation perspective. Non-linear elongation behavior of the fiber is key to these challenges. A good understanding of the fiber elongation characteristics is critical to the design of a robust and efficient mooring system. Mooring systems are one of the primary contributors to the CAPEX of the Floating Production Units (FPU) and the drive to develop cost effective systems has led to improvements/changes to mooring systems. Off-vessel tensioning has been in use for several years, but the option has recently received more in-depth consideration. Off-vessel tensioning is becoming the standard for floating systems with the elimination of on-vessel tensioning systems. The elimination of on-vessel tensioning system brings upon new challenges in terms of mooring line installation and tensioning. A key driver for these systems is the polyester rope pre-load criteria primarily used to remove construction stretch and jump the creep curve that the system may experience. The challenges to each project are unique, however, understanding and assessing the key design impacts will be beneficial to the industry.

This paper focuses on the design of a polyester based mooring system with focus on polyester fiber elongation characteristics and its impact on the design and installation. A polyester test program is established to understand the rope elongation behavior and impact of various pre-load levels. Installation assessment is also performed to understand the installation vessel requirements to achieve various pre-loads. Based on the studies, design updates are made to the mooring system and a novel two tension regime mooring system is proposed. Design impact of the two pre-tension system on various design criterions are evaluated and presented in this paper. The paper also makes recommendations on target pre-load and elongation to be considered in systems that do not plan to re-tension their system post installation. Authors appreciate that recommendations and observations reported may not be applicable for all types of floaters and mooring system.
AI Based Water-in-Oil Emulsions Rheology Model for Value Creation in Deepwater Fields Production Management
Authors: Silva Thiago Geraldo , Miyatake Luis Kin , Barbosa Rafael Madeira , Medeiros Andre Goncalves , Borges Otavio Ciribelli , Oliveira Marcia Cristina , Cardoso Felipe Mauro
Published: August 2021

This work aims to present a new paradigm in the Exploration & Production (E&P) segment using Artificial Intelligence for rheological mapping of produced fluids and forecasting their properties throughout the production life cycle. The expected gain is to accelerate the process of prioritizing target fields for application of flow improvers and, as a consequence, to generate anticipation of revenue and value creation.

Rheological data from laboratory analyses of water-in-oil emulsions from different production fields collected over the years are used in a machine learning framework, which enables a modeling based on supervised learning. The Artificial Intelligence infers the emulsion viscosity as a function of input parameters, such as API gravity, water cut and dehydrated oil viscosity.

The modeling of emulsified fluids uses correlations that, in general, do not represent the viscosity emulsion suitably. Currently, an improvement over empirical correlations can be achieved via rheological characterization using tests from onshore laboratories, which have been generating a database for different Petrobras reservoirs over the years.

The dataset used in the artificial intelligence framework results in a machine learning model with generalization ability, showing a good match between experimental and calculated data in both training and test datasets. This model is tested with a great deal of oils from different reservoirs, in an extensive range of API gravity, presenting a suitable mean absolute percentage error. In addition to that, the result preserves the expected physical behavior for the emulsion viscosity curve. Consequently, this approach eliminates frequent sampling requirements, which means lower logistical costs and faster actions in the decision making process with respect to flow improvers injection. Moreover, by embedding the AI model into a numerical flow simulation software, the overall flow model can estimate more reliably production curves due to better representation of the rheological fluid characteristics.
Water Disposal Wells Injectivity Enhanced by Well Treatment Optimization
Authors: Mei Wenrong , Al-Anazi Ammal F. , Yateem Karam S.
Published: August 2021

Produced water is always an unwanted by-product for any hydrocarbon producing process. Underground disposal of the produced formation water has many benefits such as minimum or no damage to the environment. However, formation damage arising from injection of water containing impurities is usually of great concerns and poses challenges for maintaining good injectivity of disposal wells. Well stimulation is probably one of the most effective treatment to restore the injection of impaired wells. Therefore, well treatment and optimization always play an important role in cost saving and injectivity improvement.

Although many treatments such as acidizing and mutual solvent have been developed as a standard practice and are widely employed in the oil and gas industry, there is no universal treatment recipe which may be used to effectively stimulate a well without doing any well specific studies. To effectively tackle the injection rate decline issue in water disposal wells, understanding the process, quality of injection water and the nature of the in-situ properties of the formation is vitally important. Therefore, analysis of the formation minerals and lithology, produced water, well performance and field stimulation histories had been thoroughly reviewed and examined to understand the root causes and the mechanisms underlying the rate reduction and how to improve the injectivity. Laboratory experiments had then been organized and conducted for evaluating and optimizing the treatment. Fit-for-purpose well treatments were finally designed and executed for field evaluation. Once the field treatment was done, a thorough review and benchmarking of the treatment job had been performed to capture the lessons learned. More laboratory evaluation may be necessarily carried out for further improvement in the next well treatment.

Applying the above process to the treatment of water disposal wells, a new well specific matrix stimulation treatment had been developed and applied to a few water disposal wells over the last few years. When compared with the outcomes of other types of treatment in history, the injection gain from this type of treatment was significant with a maximum 400% injection increase. Moreover, the improved injectivity had longer effective duration up to 26 months so far. Still a few wells have no signs of injection rate drop. The benefits are obviously enormous in terms of cost saving and injection gain.

Effectiveness of a well specific treatment is rooted into the thorough understanding of the physical and chemical interaction between alien fluids and the in-situ formation. Laboratory evaluation is an important key to the development of a successful treatment recipe, which was showcased by the work presented in this paper. This would enrich the expertise of petroleum professionals in the limited stimulation practice of the water disposal wells.
Potential of Synthetic Weather Radar for Squall Identification and Prediction
Authors: Fulton Ryan , Luffman James
Published: August 2021

Squall event impacts are a long-standing problem offshore, especially in regions where radar imagery and reliable nowcasts are unavailable. Existing methodologies for monitoring and advising of impacts have been near-stagnant for decades. In this paper, initial results of using machine learning tools paired with advancements in weather satellite imagery processing are presented. The approach is based on a novel method of processing satellite, lightning, radar, and numerical weather model datasets trained against observed weather radar as truth to create gridded synthetic radar and short-term forecast. The capability has demonstrated to be an effective system in simulating and predicting the high precipitation rates that are associated with squall activity in real-time. The resulting output provides precipitation rates among other attributes at 1-km resolution, updated every five minutes, and gridded extrapolative nowcasts produced to four hours ahead. Initial results over multiple geographic domains of the system have performed exceptionally well at identifying and tracking strong thunderstorm activity, with and without ground radar, including detection rates over 90% and false alarm rates near 20%. As the technique is improved and deployed more broadly on a global scale, the objective is to provide a consistent, high-fidelity dataset that enables squall risk identification and advisories within a minimum two-hour planning horizon. The primary visualization for situational awareness is a commonly used format: weather radar. New levels of productivity and safety are possible with the global expansion and application of this system. This work was completed as a collaboration between Solcast, WeatherZone, and DTN.
Experimental Investigation of FPSO Roll Motion Response Coupled with Sloshing in a Pair of Two Row Cargo Tanks
Authors: Igbadumhe Jane-Frances , Furth Mirjam , Bonoli Jack , Dzielski John
Published: August 2021

Floating Production Storage and Offloading Units (FPSOs) will continue to be in high demand because of their numerous advantages; such as, their ability to offer early production and operate in ultra-deep water locations, while remaining easy to relocate to meet changing needs. By design, slack cargo tanks are almost always present in FPSOs due to continuous loading and offloading operations; however, the presence of slack cargo impacts the seakeeping stability abilities of FPSOs. There are limited published experimental data on coupled sloshing with seakeeping of stationary vessels, and existing studies on this have focused on single row cargo tanks which is seldom the case in FPSOs. The aim of this paper is to study roll motion coupled with sloshing in partially-filled pair of two-row tanks of a stationary FPSO model exposed to regular beam waves. The model tests was performed in the Davidson Laboratory towing tank at Stevens Institute of Technology. The FPSO model response in roll was measured, and the time histories of sloshing oscillation were measured on the starboard and port side of one of the stern cargo tanks. The results show that varying internal cargo sloshing leads to unpredictable motion response of floating vessels that should be accounted for in the design and offloading operations of FPSO.
Innovation to Reduce Operation Downtime in Sulfate Removal Offshore Applications
Authors: Cuenca Yolanda , Tejero Àngels , Das Supriyo , Brooke-Peig Daniel , Martin Philip , Bechir Flavio
Published: August 2021

Sulfate removal in injection water is standard practice to prevent scaling and souring in subsea oil reservoirs. Nanofiltration membranes have been used to this purpose since 1987, when FilmTec™ SR90-400 elements were installed in an offshore platform in the North Sea. The most pressing concern in this type of systems is membrane fouling, with the associated reduction in effective plant operation time and shorten element lifespan caused by the standard Clean-in-Place (CIP) protocols. The object of this research has been to test the latest developments in biofouling-resistant sulfate removal membranes to achieve oil and gas (O&G) industry requirements. Improved chemistry and improved module engineering have enabled the production of new membrane elements that represent the next-generation in sulfate removal nanofiltration. Next-generation sulfate removal membranes have been trial-tested. In pilot testing, target performance was validated in terms of productivity, permeate quality and fouling resistance. The results of this testing indicate that improvements in membrane chemistry and module engineering have resulted in a 63% decrease in pressure drop and a much slower fouling trend over the total of 6 elements. This significant improvement should allow an important reduction in the number of cleanings, which the authors have estimated to be of 50%. Moreover, sulfate rejection values are in the range of 99.9% (below 1 ppm of sulfate in the permeate), providing great injection- quality water. Full-scale testing in a production site in the Atlantic Ocean was done to validate pilot testing results, showing a continued operation of 100 days without any need for a clean-in-place (CIP) procedure. The results obtained in the extensive testing carried out on these new antifouling elements, show that the improvements implemented in its design have the ability to improve the operation of Sulfate Removal Units (SRU). These improvements are the results of reducing maintenance costs and downtime on offshore platforms, resulting in increased operation and improved productivity.
Offshore Platform Topsides Structural Design: Using Topology Optimization to Generate Novel Design Concept
Authors: Li Zhongwei , Wang Aimin , Wang Jonathan , Dasilva Otto
Published: August 2021

The paper presents topology optimization performed for the concept study of a semi-submersible platform topsides structure. The topsides truss system consisting of I beams carries the equipment payload and the environment loads. The structural weight needs to be reduced in order to maximize the allowable equipment weight, and the structural strength criterion must be satisfied for the harsh ocean environment. Topology optimization is a powerful tool to generate designs that optimally distribute the structural material for the balance between structural weight and strength. A finite-element-based topology optimization method assigns a density value to each structural element and updates this density value using topology optimization algorithms during each design iteration. Elements in the load-transferring path retain high density value at the end cycle and form an efficient structural shape under the given design load conditions and constraints. The topology optimization generated novel and optimal geometric arrangements for the topsides structure. Two corresponding innovative topsides truss concepts were developed. The new topsides designs were compared with an existing benchmark design for the structural weight and strength to demonstrates the advantages of topology optimization over conventional empirical approach for offshore platform topsides structural design. At the same strength level, the novel designs reduced the structural weight significantly. One novel design was selected for practical semi-submersible designs at Exmar Offshore Company.
Near-Wellbore Hydraulic Fracture Non-Planar Propagation and Torturous Morphology in Tight Sandstone Formation
Authors: Zhang Ruxin , Shan Qinglin , Cheng Wan
Published: August 2021

In this paper, a 3D near-wellbore fracture propagation model is established, integrating five parts: formation stress balance, drilling, casing and cementing, perforating, and fracturing, in order to investigate fracture initiation characteristics, near-wellbore fracture non-planar propagation behavior, and torturous hydraulic fracture morphology for cased and perforated horizontal wellbores in tight sandstone formation.

The method is based on the combination of finite element method and post-failure damage mechanism. Finite element method is used to determine the coupling behavior between the pore fluid seepage and rock stress distribution. Post-failure damage mechanism is adopted to test the evolution of hydraulic fractures through simulating rock damage process. Moreover, a user subroutine is introduced to establish the relation between rock strength, permeability, and damage, in order to solve the model. This model could simulate the interaction between fractures during their propagation process because of the stress shadow.

The simulation results indicate that each operation could cause redistribution and reorientation of near-wellbore stress. Therefore, it is important to know the real near-wellbore stress distribution that affects near-wellbore fracture initiation and propagation. Initially, hydraulic fractures initiate independently from each perforation and propagate along the direction of maximum horizontal stress. However, hydraulic fractures divert from original direction gradually to interconnect and overlap with each other, because of stress shadow, resulting in non-planar propagation behavior. Individual fractures coalesce into a spiral-shaped fracture morphology. In addition, a longitudinal fracture could be observed because of wellbore effect, which is a result of weak cementing strength or near-wellbore weak plane. Finally, the complex and torturous fracture morphologies are created near the wellbore, incorporating Multi-spiral shaped fracture and horizontal-vertical crossing shaped fracture. However, the propagation behavior of fracture far away from wellbore is controlled by in-situ stress, forming a planar fracture.

The highlights of this 3D near-wellbore fracture propagation model are following: 1) it considers near-wellbore stress change caused by each construction to ensure the accuracy of near-wellbore stress distribution; 2) it achieves 3D simulation of fracture initiation and near-wellbore propagation from perforations; 3) the interaction between fractures is involved, resulting in complex and torturous morphology. This model provides the theoretical basis for fracture initiation and propagation, which also could be applied into heterogenous formations considering the effect of discontinuities.
Automatic Detection and Tracking of Marker Seeds Implanted in Prostate Cancer Patients using a Deep Learning Algorithm
Authors: Amarsee Keya , Ramachandran Prabhakar , Fielding Andrew , Lehman Margot , Noble Christopher , Perrett Ben , Ning Daryl
Published: August 2021

Purpose:

Fiducial marker seeds are often used as a surrogate to identify and track the positioning of prostate volume in the treatment of prostate cancer. Tracking the movement of prostate seeds aids in minimizing the prescription dose spillage outside the target volume to reduce normal tissue complications. In this study, You Only Look Once (YOLO) v2™ (MathWorks™) convolutional neural network was employed to train ground truth datasets and develop a program in MATLAB that can visualize and detect the seeds on projection images obtained from kilovoltage (kV) X-ray volume imaging (XVI) panel (Elekta™).

Methods:

As a proof of concept, a wax phantom containing three gold marker seeds was imaged, and kV XVI seed images were labeled and used as ground truth to train the model. The projection images were corrected for any panel shift using flex map data. Upon successful testing, labeled marker seeds and projection images of three patients were used to train a model to detect fiducial marker seeds. A software program was developed to display the projection images in real-time and predict the seeds using YOLO v2 and determine the centers of the marker seeds on each image.

Results:

The fiducial marker seeds were successfully detected in 98% of images from all gantry angles; the variation in the position of the seed center was within ± 1 mm. The percentage difference between the ground truth and the detected seeds was within 3%.

Conclusion:

Our study shows that deep learning can be used to detect fiducial marker seeds in kV images in real time. This is an ongoing study, and work is underway to extend it to other sites for tracking moving structures with minimal effort.
Is Maximum Intensity Projection an Optimal Approach for Internal Target Volume Delineation in Lung Cancer?
Authors: Tibdewal Anil , Bushra Sabheen , Mummudi Naveen , Kinhikar Rajesh , Ghadi Yogesh , Agrawal Jai Prakash
Published: August 2021

Purpose:

Respiratory-induced tumor motion is a major challenge in lung cancer (LC) radiotherapy. Four-dimensional computed tomography (4D-CT) using a maximum intensity projection (MIP) dataset is a commonly used and time-efficient method to generate internal target volume (ITV). This study compared ITV delineation using MIP or tumor delineation on all phases of the respiratory cycle.

Materials and Methods:

Thirty consecutive patients of LC who underwent 4D-CT from January 2014 to March 2017 were included. ITV delineation was done using MIP (ITVMIP) and all ten phases of the respiratory cycle (ITV10Phases). Both volumes were analyzed using matching index (MI). It is the ratio of the intersection of two volumes to the union of two volumes. A paired sample t-test was used for statistical analysis, and P < 0.05 was considered statistically significant.

Results:

The mean ± standard deviation volume of ITV10Phases was significantly larger compared to ITVMIP (134 cc ± 39.1 vs. 113 cc ± 124.2, P = 0.000). The mean MI was 0.75 (range 0.57–0.88). The mean volume of ITV10Phases not covered by ITVMIP was 26.33 cc (23.5%) and vice versa was 5.51 cc (6.1%). The mean MI was 0.73 for tumors close to the mediastinum, chest wall, and diaphragm. MI was not different between tumors ≤5 cm and >5 cm. The average time required for delineation was 9 and 96 min, respectively. The center of mass of two ITVs differed by 0.01 cm.

Conclusion:

ITV using MIP is significantly smaller and may miss a tumor compared to ITV delineation in 10 phases of 4D-CT. However, the time required is significantly less with MIP. Caution should be exercised in tumors proximity to the mediastinum, chest wall, and diaphragm.
Customization of a Model For Knowledge-Based Planning to Achieve Ideal Dose Distributions in Volume Modulated arc Therapy for Pancreatic Cancers
Authors: Nitta Yuya , Ueda Yoshihiro , Isono Masaru , Ohira Shingo , Masaoka Akira , Karino Tsukasa , Inui Shoki , Miyazaki Masayoshi , Teshima Teruki
Published: August 2021

Purpose:

To evaluate customizing a knowledge-based planning (KBP) model using dosimetric analysis for volumetric modulated arc therapy for pancreatic cancer.

Materials and Methods:

The first model (M1) using 56 plans and the second model (M2) using 31 plans were created in the first 7 months of the study. The ratios of volume of both kidneys overlapping the expanded planning target volume to the total volume of both kidneys (Voverlap/Vwhole) were calculated in all cases to customize M1. Regression lines were derived from Voverlap/Vwhole and mean dose to both kidneys. The third model (M3) was created using 30 plans which data put them below the regression line. For validation, KBP was performed with the three models on 21 patients.

Results:

V18 of the left kidney for M1 plans was 7.3% greater than for clinical plans. Dmean of the left kidney for M2 plans was 2.2% greater than for clinical plans. There was no significant difference between all kidney doses in M3 and clinical plans. Dmean of the left kidney for M2 plans was 2.2% greater than for clinical plans. Dmean to both kidneys did not differ significantly between the three models in validation plans with Voverlap/Vwhole lower than average. In plans with larger than average volumes, the Dmean of validation plans created by M3 was significantly lower for both kidneys by 1.7 and 0.9 Gy than with M1 and M2, respectively.

Conclusions:

Selecting plans to register in a model by analyzing dosimetry and geometry is an effective means of improving the KBP model.
Reduction of CLABSI in Telemetry Patients through Limiting Central Line Blood Draw
Authors:   , Lok Caselyn
Published: August 2021

CLABSI is known to be one of the many healthcare-associated infections that has led to an increase in health complications, length of hospital stays, and increased in healthcare cost. There is about 25000 bloodstream infection that occurs annually (Haddadin, Annamaraju, & Regunath, 2020). The PICOT question that guided this project was “How does limiting blood-draw from central venous catheter lines influence the rate of central-line associated bloodstream infections (CLABSI) post-implementation compared to rate of CLABSI pre-implementation after eight weeks?” CLABSI prevention bundles were already being used to guide healthcare providers in handling CVC access. There were 15 scholarly articles that supports the use of bundle programs in CVC access and addressing CLABSI. The reduction in handling and manipulation of the CVC access leads to lesser risks of infection. The intervention in this project is the reduction of the CVC access through the limiting of blood draws from central lines with rare exceptions. CVC is primarily used only for the administration of intravenous fluids, antibiotic, parenteral nutrition, and blood products. The intervention utilized a structured decision-making framework to follow during blood draws to avoid using the central line. The project resulted to a reduction of CLABSI rate from 7.9% pre-implementation rate to 0% post-implementation. The limiting of CVC access led to reduced CLABSI episode in the telemetry unit compared to the national average of 5.94%. The project has proven how the intervention implemented can be used in CLABSI prevention bundles to address healthcare associated infections.
İNSANSIZ KARA ARAÇLARI İÇİN LIDAR TEKNOLOJİSİ KULLANILARAK 3B ORTAM HARİTALAMA SİSTEMİ
Authors: TOPAL Ali , YİĞİT Tuncay
Published: August 2021

Günümüz dünyasında teknolojik gelişmeler sonucunda insansız kara araçlarının kullanımı ve uzaktan algılama tekniklerinin önemi artmıştır. Bu teknolojiler doğal afetlerlerden savunma sanayisine kadar birçok farklı alanda kullanılmaktadır. İnsansız kara aracının algılayıcılar sayesinde çevresini tanımasıyla ilgili kişi veya kurumlara ortam hakkında doğru verileri aktarması olası kötü senaryoları önlemektedir. Bu çalışmada, otonom robotların gönderilmesi planlanan ortamlara kullanılacak olan algılayıcı teknikler sayesinde ulaşımının kolaylıkla sağlanması ve ilgili ortamı tanıyarak görevini daha etkin bir şekilde gerçekleştirmesi ve düşük maliyetli olması amaçlanmıştır. Geliştirilen sistemde insansız kara aracının bulunduğu ortamı modelleyebilmesi için LIDAR lazer tarayıcı sensör kullanılmıştır. Sistem tasarımında görüntü işleme tekniği ile gece görüşlü kamera kulanılarak, ortam tanımlaması zenginleştirilmiştir. İnsansız kara aracının motor sürme işlemleri ve çeşitli çevre birimlerinin kontrolü Arduino mikrodenetleyicisi ile sağlanmıştır. LIDAR ve kamera ise Raspberry Pi gömülü sistem bilgisayarı üzerinde çalışmaktadır. Gerçekleştirilen çalışma sonucunda, ilgili kuruluşların çevre algılama sistemleri için ayırmış oldukları mali kaynakları azaltacak ergonomik, güvenli, kullanıcının tehlikeli ortamları uzaktan takip ederek ilgili ortamı tanıyabileceği tümleşik bir robot tasarımı oluşturulmuştur.
Identifikasi Telur Cacing pada Saluran Pencernaan Satwa Liar yang Dipelihara Masyarakat di Manokwari, Papua Barat
Authors: Nurhayati Dwi , Baaka Alnita , Pattiselanno Freddy
Published: August 2021

Investment of parasitic worms of captive wildlife was an impact on their health condition. This study was conducted to determine the intensity of parasitic worm infection in wild animals kept by communities in Manokwari, West Papua. The Natif method was used, by centrifuge of 20 birds and 20 mammals (Kangaroo and Deer) faeces collected from the sites. Sampling was carried out from October to November 2016. The analysis of collected faecal samples showed that bird species were not indicated (negatively infected by worm). In mammals, Nematodes and cestodes were found. Identification of existing findings showed that 3 (three) types of worm eggs were found, namely Taenia sp in kangaroos (Macropodidae), Ascaris sp (berembrio), and stronyle sp in deer (Cervus timorensis). The highest parasites intensity was stronyle sp (10 worm eggs) and the lowest intensity was Ascaris sp (3 worm eggs) .The rate of infection and investment of parasitic worm eggs in wild animals in Manokwari was categorised relatively low.
Heritabilitas Produki Telur Ayam Lokal Papua Berbeda Genotip dari Lokus 24- bp Insertion-Deletion dalam Promotor Gen Prolaktin
Authors: Mu'in Muhammad Affan , Lumatauw Sintje
Published: August 2021

The heritability (h2) of a trait shows phenotypes variance of the trait caused by additive genetic variance. The h2 value is used to estimate the quantitative trait breeding value of livestock in order to improve these traits through selection. This study aims to estimate the h2 of egg production characteristics in Papua local chickens with different genotypes from the 24-bp InDel (Insertion-Deletion) locus in the prolactin gene promoter region (24-bp InDel/cPRLp locus). A total of 13 pairs of Papua local chickens consisting of 3 pairs of II genotypes (♂II x ♀II) and 11 female offspring, 5 pairs of ID genotypes (♂ID x ♂ID) and 19 female offspring, and 5 pairs of DD genotypes (DD x ♀DD) and 17 female offspring were used in this study. Observations were made on the characteristics of egg production in female offspring of each genotype group. The variance component for h2 estimation is obtained by the one-way analysis of variance method and the separation of the variance components for single pairs. The results showed that the h2 at first laying of eggs in all genotype groups was moderate (0.10 to 0.30); the h2 of the number of eggs produced from the time they first laid eggs until the age of 240 days in II and ID genotype groups was high (> 0.3), while in the DD genotype group was classified as moderate (0.10 to 0.30); and the h2 of egg weight in all genotype groups was moderate (0.10 to 0.30). The high h2 of a trait indicates that the trait is more dominated by additive genes and is more responsive to the selection treatment.
É POSSÍVEL TRANSFORMAR O ENSINO NA ENFERMAGEM? USO DE METODOLOGIAS ATIVAS NA FORMAÇÃO DO ENFERMEIRO
Authors: Barros de Souza Jeane , Tamara Tomasi Yaná , Silvana Faganello Madureira Valéria
Published: August 2021

Objetivo: compartilhar experiências sobre a utilização de metodologias ativas na graduação em Enfermagem, como forma de qualificar o processo ensino-aprendizagem. Descrição da experiência no primeiro semestre de 2019, docentes de dois componentes curriculares da primeira e da quinta fases do curso de graduação em Enfermagem de uma Universidade Federal do Sul do Brasil, organizaram dinâmicas interativas e lúdicas para abordagem de conteúdos programáticos das disciplinas. Discussão: as atividades despertaram nos estudantes criatividade, ampliação do conhecimento, diálogo, reflexão, desenvolvimento do trabalho em equipe, pois se colocaram como protagonistas no processo ensino-aprendizagem, proporcionando maior satisfação para educador e educando, bem como estímulo na continuidade do uso de metodologias ativas no ensino da Enfermagem. Conclusão: a incorporação de metodologias ativas na formação em enfermagem fomenta o protagonismo do estudante e a formação de enfermeiros condizentes com as demandas da sociedade e do Sistema Único de Saúde.
Thermodynamic Optimization of an Air bottoming Cycle for Waste Heat Recovery from Preheater Tower in a Cement Industry
Authors:   LGPDDPS Laboratory, Department of Process Engineering, National Polytechnic School of Constantine, Constantine, Algeria, Redjeb Youcef , Kaabeche-Djerafi Khatima ,   LGPDDPS Laboratory, Department of Process Engineering, National Polytechnic School of Constantine, Constantine, Algeria
Published: August 2021

This work evaluated the air bottoming cycles(ABC) as a technology for waste heat recovery (WHR) at the level of the preheater tower in a cement industry. An optimization code has been developed in MATLAB environment and linked with REFPROP database as a way to design and calculate the different parameters and points of the cycle. The theory of power maximization is adopted and the genetic algorithm is employedasa way to maximize the net power output of the cycle, while a case study of a real cement plant has been taken into consideration for the examination purpose. Results showed that the integration of the ABC cycle for energy valorization contributes to covering around 8.5% of the industry need for electrical energy, by generating an amount of power that can achieve 1.07 MW.In addition, although the cycle has shown a low efficiency, it can be a practical WHR solution especially in case of water deficiency.
Modeling the concentration of carbonyl of ethylene propylene diene monomer during the thermal aging using artificial neural network
Authors:   Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Médéa, Ain D’Heb 26000, Médéa, Algeria, Maouz Hadjira , Adda Asma ,   Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Médéa, Ain D’Heb 26000, Médéa, Algeria, Hanini Salah ,   Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Médéa, Ain D’Heb 26000, Médéa, Algeria
Published: August 2021

The concentration of carbonyl is one of the most important properties contributing to the detection of the thermal aging of polymer ethylene propylene diene monomer (EPDM). In this publication, an artificial neural network (ANN) model was developed to predict concentration of carbenyl during the thermal aging of EPDM using a database consisting of seven input variables. The best fitting training data was obtained with the architecture of (7 inputs neurons, 10 hidden neurons and 1 output neuron). A Levenberg Marquardt learning (LM) algorithm, hyperbolic tangent transfer function were used at the hidden and output layer respectively. The optimal ANN was obtained with a high correlation coefficient R= 0.995 and a very low root mean square error RMSE = 0.0148 mol/l during the generalization phase. The comparison between the experimental and calculated results show that the ANN model is able of predicted the concentration of carbonyl during the thermal aging of ethylene propylene diene monomer
Energy Recovery by Production of Electricity from Anaerobic Digestion of Organic Waste in the Saharan Environment
Authors:   Research unit in Renewable energies in Saharan Medium URERMS, Renewable Energies Development Center, CDER, 01000, Adrar, Algeria, TAHRI Ahmed , KALLOUM Slimane ,   Energy, Environment and Information Systems Laboratory, Université Ahmed Draia, Adrar 01000, Algérie
Published: August 2021

Anaerobic digestion is a natural process of transforming organic matter into energy by methanogenic bacteria. This process is performed in the digesters in the absence of oxygen, they produce biogas composed mainly of methane (CH4) which is a combustible natural gas we can used in everyday life. In this work, we produced biogas using a continuous digester with a capacity of 4m3 and after the biogas purification; we used methane produced to run the generator to produce electricity. The results are very encouraging, where we have to produce electricity and cover the daily needs of the Algerian individual in electricity using 1m3 of biogas from our digester
OPTIMASI MESIN PENCARI BUKU FIKSI BERDASARKAN PADA SEMANTIK IMPRESI
Authors:   Politeknik Elektronika Negeri Surabaya, Asmara Rengga , Mubtadai Nur Rasyid , Bimantara Varidh
Published: August 2021

Fiction books are one of the most popular types of books in Indonesia. There are five most popular genres in fiction books, namely fantasy, mystery, romance, sci-fi, and thriller. Each genre gives a different impression and special interest for readers. It has become a common habit when people choose a fiction book based on the title, author, or publisher of the book. However, it does not provide precise search results. In this final project, an application system was developed to find out fiction books based on semantic impressions on the cover of the fiction book. The impression on each book cover is obtained through a survey of fiction book lovers in Indonesia. To get the results of the closeness between the user search and the impression survey data obtained through text mining, as well as the cosine similarity algorithm to calculate the most precise proximity value to the impression the user expects. The results of this system display a fiction book that has a closeness value with an error rate of 3.93% based on the impression expected by the user.
IMPLEMENTASI CONTEXT AWARE PADA SISTEM TRAVEL PLANNER BERBASIS MOBILE
Authors:   Politeknik Elektronika Negeri Surabaya, Darmawan Viery , Asmara Rengga , Prasetyaningrum Ira
Published: August 2021

In the era of technological advances, tourists will first seek information about the tourist object to be addressed, even tourists often don't have a destination, so they have to search one by one via the internet. In determining travel plans, it is often to see one by one the review of tourist attractions and conclude the results will take a long time, while tourists need actual and fast information to determine the travel plans. In this study, the authors take a new approach, namely by creating a mobile-based travel planner system that compiles travel plans automatically by considering contextual information related to tourist location points, whether of tourist locations during travel days, travel opening and closing hours, so that it will increase travel efficiency without having to do the research manually which takes a long time. The system can also provide travel recommendations based on visitor comments sentiment on Google Places and is equipped with a trip route that will be generated automatically. This research is useful for helping tourists plan their trip actually because of the consideration of contextual information so that it will make it easier and save tourists time.
SISTEM CUSTOMER SERVICE PT KERETA API INDONESIA (PERSERO) BERBASIS CHATBOT MENGGUNAKAN KOMPUTASI BAHASA
Authors:   Politeknik Elektronika Negeri Surabaya, Shafira Nia , Martiana Etin , Asmara Rengga
Published: August 2021

As the main train service provider company in Indonesia, PT Kereta Api Indonesia (PT KAI) has many customers who need information. In order to maintain customer loyalty, PT KAI must respond quickly and be adaptive to technology to provide the best service to customers. Limited human resources make PT KAI unable to serve customers simultaneously, so customers often have to wait for a response. In order to provide the best service, automatic messages are needed in order to help customer service performance respond quickly and at the same time with no cost, access anytime and anywhere. This study proposes a new approach with chatbots as a medium for conveying automatic information quickly and simultaneously. This chatbot is made with a computational language that focuses on natural language modeling and cosine similarity as a method for calculating the proximity of inputs and databases. This research can help PT KAI's customer service workers to answer customer needs automatically.
DETEKSI KEMIRIPAN ARTIKEL MELALUI KEYWORDS DENGAN METODE FUZZY STRING MATCHING DALAM NATURAL LANGUAGE PROCESSING
Authors:   Universitas Methodist Indonesia, Rumapea Humuntal
Published: August 2021

Natural Language Processing (NLP) is part of artificial intelligence that focuses on natural language processing. That is the language commonly used by humans in communicating with each other. In writing, articles can also be applied. To find out the similarity of the contents of a scientific article to another will make it easier for readers to make selections and make it easier to collect similar documents. Likewise with differences in article content even though they use the same keywords. Measurements are made using the keywords contained in the abstract which consists of several words and the number of keywords. The method used is to use fuzzy string matching to get the number of keywords used in an article. Then the calculation will be done for each keyword used and will be sorted by priority according to the position of the keyword. The search will be carried out starting from the title, abstract, keywords, content, and references. The number of keywords found in each article is shared across all keywords found to generate a similarity percentage level. If the results found are the same in number from one article to another, it can even be categorized that the contents of the article have similar content. The testing process is carried out by counting the number of keywords in the source then comparing all the source keys to the destination articles in the database by searching and comparing each word.