bluuebunny/crossref_metadata_2025_split huggingface dataset:
Escrevivências Decoloniais: o Movimento do Feminismo Agroecológico como um Modelo de Educação Informal no Vale do Ribeira (SP)
Authors: Busko Paula Simone 
Published: November 2019

O feminismo agroecológico evidencia a presença da mulher nos espaços agrícolas. O objetivo deste artigo é evidenciar as narrativas de mulheres a partir do campo. Pela história oral e na interação de redes de apoio um novo modelo de educação informal poderá ser proposto. Visibilizar estudos em agroecologia é destacar a ação de diversos agentes, que formam uma rede de interação social e de educação, partindo do princípio de que a agroecologia é uma ciência, que orienta a adoção de práticas agroecológicas com o uso de novas ferramentas tecnológicas dentro de determinados sistemas de produção. A pedagogia decolonial convoca conhecimentos subordinados pela colonialidade do saber e do poder, além de dialogar com as experiências críticas e políticas muito presentes nos movimentos sociais e nos trabalhos de redes de interação, que colaboram para a derrubada de estruturas e pensamentos hegemônicos. A educação informal, que ocorre no Vale do Ribeira, dá destaque às narrativas de mulheres que constituem os sujeitos dos discursos, que configuram um feminismo agroecológico. Em relação às práticas educativas e ao material utilizado para o aprendizado, cartilhas e impressos se tornam importantes por valorizarem a formação profissional rural e a promoção social. Ressalta-se as escrevivências decoloniais daquelas mulheres, enquanto personagens, que caminham para a busca da alteridade. Palavras-chave: Educação Informal. Práticas Educativas. Feminismo Agroecológico. Decolonialidade. AbstractThe agroecological feminism evidences the woman’s presence in the agricultural spaces. The purpose of this article is to evidence the countryside women’s narratives. Through oral history and in the interaction of support networks a new model of informal education may be proposed. Studies visibility in agroecology is to highlight the actions of several agents that form a network of social interaction and education, based on the principle that agroecology is a science that guides the adoption of agroecological practices with the use of new technological tools within certain production systems. Decolonial pedagogy calls for subordinate knowledge for the knowledge and power coloniality, as well as dialogue with the critical and political experiences that are very much present in social movements and in the work of interaction networks that collaborate in the overthrow of hegemonic structures and thoughts. The informal education that takes place in Ribeira Valley highlights the women’s narratives who constitute the subjects of the discourses that constitute an agroecological feminism. In relation to educational practices and the material used for learning, booklets and printed matter become important because they value rural vocational training and social promotion. It is emphasized the decolonial writings of those women as characters who are moving towards the search for otherness. Keywords: Informal Education. Educational Practices. Agroecological Feminism. Decoloniality. Interculturality.
CORPORATE GOVERNANCE IN THE STATE-OWNED BANKS
Authors: Smovzhenko T. S. , Lyutyy I. O. , Denys O. B. 
Published: November 2019

In the article, based on application of agency theory, the specifics of corporate governance in state-owned banks are highlighted. It is determined that the key distinction of state-owned banks is the fact that a state simultaneously can act as an owner, manager, creditor and regulator. The differences of corporate relations in state-owned banks such as the more complicated multilevel system of agency relations, the higher level of information asymmetry and risk of agent’s opportunism, the another character of trust manifestation are substantiated. It is highlighted that the presence of complicated corporate relations causes the following risks: the state as an agent of population may be ineffective and use the state-owned banks not so for ensuring of socio-economic development, as for financing the state’s projects or state-owned enterprises; in the case of certain political forces’ impact on the formation of the government the state-owned banks activities may be subordinated by motives of certain politicians, interested in using of state-owned banks for achieving their own political goals; the ineffective multi-level delegation of management, monitoring and regulation functions can lead to inefficiencies of state-owned banks in general; the lobbying of state-owned banks’ interests may lead to the breach of competitive environment of financial market, manipulation of movement of credit and investment resources etc. The hypotheses, regarding to the factors that can be decisive for the effective corporate governance in the state-owned banks, are formulated. As main factors which may determine the efficiency of corporate governance in the state-owned banks are considered follow: the structure and composition of agency contracts of management in the state-owned banks, level of banking regulator independence and character of its relations with state-owned banks and other government structures; the formation of supervisory boards, taking into account the absence of political engagement of supervisory boards, the appropriate level of professionalism and reputation, the presence of independent members, the application other procedures for the selection of state-owned banks managers, based on the balance of all stakeholders’ interests; the appropriate balanced level of transparency.
Fertilizer Production Planning Optimization Using Particle Swarm Optimization-Genetic Algorithm
Authors: Rahmalia Dinita , Herlambang Teguh , Saputro Thomy Eko 
Published: November 2019

Background: The applications of constrained optimization have been developed in many problems. One of them is production planning. Production planning is the important part for controlling the cost spent by the company.Objective: This research identifies about production planning optimization and algorithm to solve it in approaching. Production planning model is linear programming model with constraints : production, worker, and inventory.Methods: In this paper, we use heurisitic Particle Swarm Optimization-Genetic Algorithm (PSOGA) for solving production planning optimization. PSOGA is the algorithm combining Particle Swarm Optimization (PSO) and mutation operator of Genetic Algorithm (GA) to improve optimal solution resulted by PSO. Three simulations using three different mutation probabilies : 0, 0.01 and 0.7 are applied to PSOGA. Futhermore, some mutation probabilities in PSOGA will be simulated and percent of improvement will be computed.Results: From the simulations, PSOGA can improve optimal solution of PSO and the position of improvement is also determined by mutation probability. The small mutation probability gives smaller chance to the particle to explore and form new solution so that the position of improvement of small mutation probability is in middle of iteration. The large mutation probability gives larger chance to the particle to explore and form new solution so that the position of improvement of large mutation probability is in early of iteration.Conclusion: Overall, the simulations show that PSOGA can improve optimal solution resulted by PSO and therefore it can give optimal cost spent by the company for the planning.Keywords: Constrained Optimization, Genetic Algorithm, Linear Programming, Particle Swarm Optimization, Production Planning
One-Pot Synthesis of Requirements Elicitation for Operational BI (OBI) System: in the Context of the Modern Business Environment
Authors: Sarma A.D.N. 
Published: November 2019

Background: Requirement elicitation is the first step for any project. The available BI requirement elicitation approaches are focused more towards: the top pyramid of the management, less focus on the business aspect of an organization, historical in nature, emphasis on data mining and data warehousing aspects, no clear separation between requirements, and lack of proper linkage between the requirements. The demand of BI shifts towards the operational front for last couple of years. The use of Operational BI is gaining more popularity among industry and business communities because of increased demand of real time BI. It provides a powerful analysis of both operational and business information in current time for all levels of the users in the organization.Objective: In the modern business environment, the business operates on networks that demands multi-level decision-making capabilities as compared to the traditional business approaches. Operational BI is one of the business information systems that support the modern business environment and provides timely decision-making information to all the users in the organization. The requirement elicitation methodology for Operational BI system is found open for research. A new approach for requirement elicitation for an Operational BI system is presented in this paper, which highly suits to the organizations in the modern business environment.Methods: A top down technique is employed in the proposed requirements methodology that focuses on the business context of an organization. The proposed requirement elicitation approach is highly suited for the organizations that operate in the modern business environment. This approach overcomes several limitations in the existing BI requirement approaches. A case study is presented to support the proposed requirement elicitation approach for OBI system.Conclusion: This approach has several advantages like fast development, clear definition, classification of various types of requirements and proper linkage between the requirements without any loss or missing of gathering requirements. Finally, it is to conclude that the proposed approach acts as a one-pot synthesis of requirements elicitation for Operational BI system.Keywords: Business Context, Business, Intelligence, Business Networks, Protocols, Modern Business, Environment, Operational Business, Intelligence Requirement, Elicitation, Requirement, Methodology
Untethering the Queue based on Multi Channel Access (MCA) Technology at Hospital Radiology Section
Authors: Dyatmika Dharma , Sudana Oka , Putri Gusti Agung A. 
Published: November 2019

Background: Information technology is developing rapidly over time, but there are many companies do not make use of it to support their operational activities. One example is the queue system in the Radiology Section of Sanglah Hospital, which operates the conventional queue system.Objective: The problem occurs in this queue system is inefficient waiting time because the patients must come early and wait in line in the hospital waiting rooms. Many patients thereafter decide going home first or doing other activities. Another problem is it triggers double costs of transportation. The purpose of this study is to improve patients comfort while waiting in queue by applying untethering the queue. Untethering the queue is a service that allows people to be in a queue even though they are not in the waiting room.Methods: The system applies the FCFS (First Come First Serve) algorithm to manage patients’ queue and integrates this queue system with Telegram and SMS gateway. It makes patients easier to take queue numbers and receive notification of health service time from the Radiology Section of Sanglah Hospital.Result: As a result of this study is an untethering the queue application which is web-based queue system integrated to Telegram and SMS gateway. The daily queue services in the Radiology Section of Hospital can be improved through this application.Conclusion: Patients can only come to the hospital when the queue numbers obtained nearly the health service time so that it leads to time efficient and comfort while waiting in queue.Keywords:First Come First Serve, Multi Channel Access, SMS, Telegram, Untethering the Queue
PEMANFAATAN PISANG KEPOK (MUSAPARADISIACA FORMATYPICA) DAN TERUNG BELANDA (SOLANUM BETACEUM CAV.) PADA PEMBUATAN FRUIT LEATHER
Authors: Tahir Mulyati M. , Tawali Abu Bakar , Andriana Ferty Desy 
Published: November 2019

Kepok banana (Musaparadisiaca formatypica) is one fruit that contains enough digestive fiber for the body. Kepok banana (Musaparadisiaca formatypica) is usually processed by frying or steaming, bananas have a short shelf life and easily damaged. Therefore, to extend the shelf life of bananas, fruit will be processed into fruit leather products. However, because the color of bananas are less attractive, the color addition will make the product preferred by consumers. Terung belanda (Solanum betaceum cav. has a bright color and has enough fiber content so well processed into fruit leather. The objective of this research was to find the best treatment combination between kepok banana (Musaparadisiaca formatypica) and terung belanda (Solanum betaceum cav.) sugar concentration to produce a good physical and chemical properties and favored by consumers. The research was also to find out the effect of sugar concentration addition to physical, chemical and organoleptic fruit leather banana and terung belanda (Solanum betaceum cav.). Treatment applied was A1: kepok banana (Musaparadisiaca formatypica) mashed 50%: terung belanda ((Solanum betaceum cav) mashed 45%: sugar 5%; A2: 45%: 40%: 15%; A3: 40%: 35%: 25%. Fruit leather is then tested organoleptically including color, flavor, taste and texture and was chemically tested including moisture content, total acid, pH, anthocyanin and fiber. The result of the research shows that A1 treatment: 50% banana porridge: terung belanda porridge 45%: 5% sugar produces the best fruit leather product in terms of water content, total acid, pH, anthocyanin, fiber, aroma, taste, and texture.
A Primer on Clinically Important Outcome Values
Authors: Cepeda Nicholas A. , Polascik Breanna A. , Ling Daphne I. 
Published: November 2019

➤ Clinically important outcome values allow physicians to provide patients with more realistic expectations regarding their treatment that are based on their specific demographics.➤ Clinically important outcome values can vary for the same procedure or population depending on the method of calculation used, which raises the need for uniform ways to calculate and compare these values across populations and procedures.➤ A shift in approach from focusing solely on significant outcomes, or p values, to considering both clinically important and significant outcomes will allow clinicians to provide more efficient care, in line with recent trends toward a value-based health-care system.
A New Design of Low Salinity-CO2-Different Chemical Matters
Authors: Al-Saedi Hasan N. , Al-Jaberi Soura K. , Flori Ralph E. , Al-Bazzaz Waleed , Long Yifu 
Published: November 2019

Abstract
In this study, we proposed a new EOR method by combining low salinity (LS) water, alkaline, Surfactant, and CO2. Generally, injecting CO2 into oil reservoirs is a fruitful EOR technique that improves oil recovery, but injecting CO2 accompanied with technical in situ problems such as early breakthrough, viscous fingering, and gravity override. This prompted to find a solution to improve the gas sweep efficiency to prevent the mentioned problems from happening. Water was proposed to be alternated with CO2 for this purpose, and the outcome was promising. LS water was used instead of the regular water, which resulted in higher oil recoveries than the regular water. We proposed to inject surfactant-CO2 and LS water with foam which provided the most top results (28.35% OOIP). In this work, we presented a new method to inject Alkaline-Surfactant-CO2-LS water successively. The tertiary oil recovery can reach ~34% of the OOIP for all the cores in this study. The new process can improve the sweep efficiency as well as increasing oil recovery up to 20.1% OOIP. The oil recovery due to this new method is higher than mixing alkaline and foam together by a factor of 2 and more than this factor for WAG and CO2 injection. Coupling LS water with alkaline, Surfactant, and CO2 is a novel idea which takes advantage of the relative strengths of all processes and prevents the precipitation that could affect the performance of alkaline-foam EOR process. We proposed a new procedure to avoid this surfactant precipitation by injecting an LS water slug in between alkaline and foam flooding.
Compressor Package: Failure Analysis & Reliability Enhancement
Authors: Khalaf Adel , Barsoum Imad , Kobbia Ibrahim , Toubar Ashraf 
Published: November 2019

Abstract
Instrument Air (IA) compression system is a critical utility system that is responsible to deliver filtered and dry air to various process stations within the plant. The compressed air is used to manipulate valves that are crucial for plant control and emergency shutdown systems. Inadequate operation of the IA compression package leads to reduced system availability, which introduces safety hazard and leads to serious operational interruption. This paper analyzes a case study of frequent system tripping due to hot air recirculation phenomenon (HAR), using actual field measurements and computational fluid dynamics (CFD) simulations, to propose solutions for maximized system reliability.
This research work presents a case study of HAR at oil and gas offshore plant that reduced the performance of an air-cooled IA compression package. This in turn caused the system to experience repeated and frequent trips due to increased temperature within the package. Therefore, the need for exhaust hot air dispersion analysis of discharged air from air-cooled heat exchangers is becoming of great importance. A detailed three-dimensional CFD model, that represents different installation arrangements of the compressor unit area, was built to simulate the HAR and its influence on the overall performance of the compressor unit. Actual site measurements were collected, analyzed and compared to CFD predictions. The effect of wind speed and direction with relative to the compressor package installation location on the platform was analyzed and discussed. Recommendations and mitigation measures to avoid frequent system outings and exhaust HAR are provided based on CFD outcomes.
The results of the analysis showed that HAR was the main reason of the frequent system tripping which is directly associated with the installation location of the compressor package. The CFD predictions calculated the flow and temperature distribution in the compressor area, and results were compared with actual site measurements, taking the site weather conditions, wind speed and direction into account. Excellent agreement between CFD results and field measurements was observed. In order to prevent system break-offs from happening, a short-term mitigation of installing a ventilation blower inside the package while introducing additional suction louvers in the enclosure was made to enhance heat transfer. Moreover, a long-term solution to install exhaust ducting to route the exhaust hot air away from the air-cooler intake of the compression package is proposed. Both mitigation measures were implemented and the frequent tripping was eliminated.
The influence of HAR on air-cooled compression packages is not well recognized in oil and gas industry. This study utilizes in-depth engineering analysis techniques to enhance the air compression system reliability using advanced engineering simulations.
Predicting Horizontal Shear Slowness- A Machine Learning Approach
Authors: Hussain Syed Aaquib , Chatterjee Chandreyi , Sarkar Sujit Kumar , Reyes Allan , Majumdar Chandan , Das Ritwika 
Published: November 2019

Abstract
The Spraberry trend area is part of a larger oil-producing region within the Midland basin in United States. The main targets, Spraberry, Dean and Wolfcamp, are reservoirs of shales interbedded with clastic formations. Thus, the reservoirs exhibit TIV (transverse isotropy vertical) anisotropy due to thin laminations. A pilot well was drilled vertically in the complex lithology and logged with the advanced acoustics measurements. Shallow penetration of Stoneley energy into the formation raised concerns about the depth resolution of the inverted shear slowness derived from it. It is very difficult to get a reliable horizontal shear slowness from Stoneley when the borehole condition is rugose, there is a complex mud rheology and gas influx inside the borehole.
A machine learning based approach integrating the advanced acoustics measurements and petrophysical interpretation is adopted to provide the solution to get the lithology-based horizontal shear slowness. To eliminate the variability of getting the horizontal shear slowness from Stoneley wave, to process for an advanced geomechanics product like for TIV anisotropy analysis, two machine learning algorithms are used. First one is a very commonly used linear supervised learning algorithm multi-linear regression (MLR) and second is random forest (RF) a nonlinear supervised learning algorithm. These algorithms take inputs from formation evaluation and advanced acoustics to predict the horizontal shear slowness. The random forest algorithm being an ensemble learning method have greater predictive capabilities compared with any linear supervised learning models and many of the non-linear supervised learning algorithms. The inputs for RF and MLR regressions are values of dry weight fractions of calcite, dolomite, quartz, illite, total porosity, permeability, gamma ray, compressional slowness and fast shear slowness. These values are obtained for the entire depth of interest from advance logging tools and interpretation techniques. To check the performance of the model, standard machine learning techniques such as the error evaluation metrics of the mean squared error and the coefficient of determination (R-squared or R2) were considered. The model has been trained over 90% of data and 10% of the data was used to cross-validate the model.
Hyperparameter tuning of the RF model has been done to improve upon the prediction accuracy. After the parameters are tuned, the mean squared error and R2 value of the training dataset are 1.77 and 0.98; while that for the testing dataset, they are 13.26 and 0.89 respectively. The closeness of the R2 value for both the training and testing dataset to 1, implies that the RF model is successfully able to explain the variance of the given data.