bluuebunny/crossref_metadata_2025_split huggingface dataset:
High Quality Al-Ga-In-N Heterostructures Fabricated by MOVPE Growth in Multiwafer Reactors
Authors: Schmitz D. , Beccard R. , Schoen O. , Niebuhr R. , Wachtendorf B. , Juergensen Holger 
Published: August 2016

We present results on the growth of Al-Ga-In-N films in multiwafer reactors with 7×2″ wafer capacity. The design of these reactors allows the combination of high efficiency (TMGa efficiency for GaN around 30%) and excellent uniformity. Results on the growth of all materials from the Al-Ga-In-Nitride family are presented in detail. GaN is grown with an excellent optical quality and very good thickness uniformity below 2% across 2″ wafers. The material quality is shown by electron mobility of more than 500 cm2/Vs at an intentional Si-doping of approximately 1×1017 cm−3. Controlled acceptor doping with Mg yields carrier concentrations between 5×1016 and 1018 cm−3. The layer thickness uniformity of the films are better than 2% over a 2″ wafer area. GaInN is grown with PL emission wavelengths in the visible blue region showing a uniformity better than 1.5 nm standard deviation. The film thickness uniformity represents the same figures as obtained for the binary. The compositional uniformity of AlGaN is in the sub 1% range corresponding to a wavelength variation below 1 nm.The fabrication of heterostructures from these binary and ternary materials is described as well as results from the characterization of these structures. The results show that reliable and efficient production of Al-Ga-In-Nitride based optoelectronic devices can be performed in multiwafer reactors.
MOCVD Equipment for Recent Developments towards the Blue and Green Solid State Laser
Authors: Jürgensen H. , Schmitz D. , Strauch G. , Woelk E. , Dauelsberg M. , Kadinski L. , Makarov Yu.N. 
Published: August 2016

For the growth of an electrically pumped lasing nitride emitter, the development of the MOCVD equipment and the process are mutually dependent. Most important is the implementation of the rapid temperature changes that are required between the growth of the different layers of a device structure. Equally important is to provide a reaction chamber that develops a stable gas phase at all growth temperatures used in the process. In this paper we will give insight in the technology and the relationship between processes and equipment. The development of the reation chamber was supported by mathematical modeling that formed the basis for the selection of appropriate process parameters for growth of group-III nitrides. The modeling consists of the numerical solution of the Navier-Stokes equations coupled with heat transfer and mass transport of the chemical species. The modeling of radiative heat transfer takes into account the effect of changing surface radiative properties. These changes result from the coating of the reactor inner surfaces during the growth run. Coupled flow dynamics and chemistry including homogeneous and heterogeneous reactions play an important role for predicting growth rate distributions on the susceptor area. At the practically used high temperatures, group-III metalorganics turn out to be almost entirely decomposed and it is the mass transport of these decomposition products to the growing layer that is assumed to control the growth rate in accordance with experimental observations.AIXTRON GmbH
Correlation between surface morphologies and crystallographic structures of GaN layers grown by MOCVD on sapphire
Authors: Rouviere J. L. , Arlery M. , Niebuhr R. , Bachem K. H. , Briot Olivier 
Published: August 2016

GaN layers deposited by MOCVD on sapphire have been characterized by Transmission Electron Microscopy (TEM). Two substrate orientations were used, (0 0 0 1) and(2 0).We determine the crystallographic structures (defect content and layer polarity) of three different types of GaN layers with different surface morphologies. Convergent Beam Electron Diffraction studies were particularly important to determine the polarity of the GaN layers. We find that polarity and surface diffusion are the factors that control the different growth modes. Unipolarity is obtained thanks to the annealing of the low temperature buffer layer or/and thanks to the nitridation of the sapphire substrate.Hexagonal pyramids and flat tops are formed when the material has a dominant N-polarity. The pyramids contain many tiny hexagonal columnar Inversion Domains (IDs). These pyramids are formed when the tiny Ga-polar IDs grow faster than the surrounding N-polar matrix. Flat GaN layers are unipolar, with a Ga polarity. Rough grainy layers which are unipolar (Ga-polarity) are obtained when surface diffusion is not high enough.
Cleidocranial Dysplasia with 6p21.1-p12.3 Microdeletion
Authors: Puvabanditsin Surasak , February Melissa , Mayne Julia , McConnell Jennifer , Mehta Rajeev 
Published: August 2016

Objective: The aim of this article is to publish a literature review and report on a new case of cleidocranial dysplasia syndrome with 6p21.1-p12.3 microdeletion. Design: A PubMed search using “cleidocranial dysplasia syndrome (CCD)” or “6p microdeletion” was performed. Articles with information relevant to our case were obtained for review. A new case of cleidocranial dysplasia syndrome is presented to describe and discuss clinical manifestations, pathogenesis, clinical progression of cleidocranial dysplasia syndrome, and management. Results: There were 22 articles with reports of cleidocranial dysplasia syndrome or 6p microdeletion. Cleidocranial dysplasia syndrome, a rare genetic disorder, documented to have an autosomal dominant inheritance pattern and caused by caused by mutations of the transcription factor RUNX2. RUNX2 has been mapped to chromosome 6p21. The anomalies in cleidocranial dysplasia syndrome can involve not only the clavicle and skull but the entire skeleton because the membranous as well as endochondral bone formation may be affected. Upon follow-up, our patient was found to have global developmental delay. Conclusions: We report a near-term neonate with characteristic features of cleidocranial dysplasia and a 6p21.1-p12.3 microdeletion. Cleidocranial dysplasia syndrome is a rare autosomal dominant skeletal dysplasia. The mutation of the RUNX2 gene results in cleidocranial dysplasia syndrome.
Peningkatan Sistem Keamanan Autentikasi Single Sign On (SSO) Menggunakan Algoritma AES dan One-Time Password Studi Kasus: SSO Universitas Ubudiyah Indonesia
Authors: Musliyana Zuhar , Arif Teuku Yuliar , Munadi Rizal 
Published: August 2016

Single Sign On (SSO) merupakan model autentikasi independen yang diimplementasikan Universitas Ubudiyah Indonesia (UUI) menggunakan Message-Digest Algorithm 5 (MD5) dan web service NuSOAP berbasis bahasa pemograman PHP. Sistem ini berjalan pada protokol Hypertext Transfer Protocol (HTTP). Faktanya penggunaan protokol HTTP ini sangat rentan terhadap berbagai jenis serangan karena data dikirim dalam bentuk plaintext tanpa ada proses enkripsi dan penerapan algoritma MD5 pada autentikasi login juga rentan terhadap serangan dictionary attacks dan rainbow tables. Disisi lain, Penggunaan web service NuSOAP juga menciptakan celah keamanan karena pengiriman dan penerimaan payload tidak dienkripsi. Saat ini diketahui sudah ada beberapa metode yang dapat digunakan untuk meningkatkan pengamanan kerentanan tersebut diantaranya yaitu menggunakan Hypertext Transfer Protocol Secure (HTTPS), Secure Hypertext Transfer Protocol (SHTTP) dan Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA). Namun beberapa hasil penelitian terkait memperlihatkan masih terdapat beberapa kelemahan dari penggunaan HTTPS, SHTTP dan CAPTCHA. Penelitian ini mengusulkan penggunaan algoritma Advanced Encryption Standard (AES) dengan pembangkit kunci dinamis dan metode One-Time Password (OTP) berbasis sinkronisasi waktu dengan kombinasi salt untuk meningkatkan keamanan pada autentikasi SSO UUI. Hasil pengujian menunjukkan penerapan algoritma AES dan OTP dapat mengamankan proses autentikasi SSO dari serangan dictionary attack dan rainbow table.
Research on the Dynamic Evolution Behavior of Group Loitering Air Vehicles
Authors: Bing Li , Ning You 
Published: August 2016

Abstract
In this paper we focus on integrated Reconnaissance/Strike LAV, in order to reveal the evolution regularity when group LAVs combats cooperatively. The evolution of cooperative behavior of group LAVs, which is described with finite state machine, can be regarded as a conversion process of a LAV in different task states, using the rate equation for probability analysis. Then based on the missions of integration of reconnaissance, attack, and damage effectiveness evaluation, we build the model of finite state machine based on behavior state transition. Solved with Runge-Kutta method. We can analyze how the key technology quota of LAV impact on the operational effectiveness of Group LAVs.the fractional order control approach.
Electrical Submersible Pump Operation Optimization with Time Series Production Data Analysis
Authors: Zhu David , Alyamkin Sergey , Sesack Laura , Bridges Jeffrey , Letzig Jamie 
Published: August 2016

Abstract
Electrical Submersible Pump (ESP) operation faces new challenges with the advent of unconventional completions. Quick production decline means that ESP operators need proactive methods to deploy equipment for applicable flowrate ranges. The benefit for production forecasting and optimization is not only maximized accumulated oil production, but also improved ESP run life. This paper demonstrates the production forecasting capability of a time series data analysis method called Singular Spectrum Analysis (SSA).
Applying SSA to customer-provided raw, daily production data results in production data historical matching and future production forecasting. The strength of SSA stems from the ability to make a decomposition of the original series into a summation of the principal independent and interpretable components such as slowly varying trends, cycling components and random noise. [1] The trending component can be used for future production forecasting if it is the only principle component among all decomposed components.
Research proves that SSA can be utilized to forecast daily production rates based on a raw production dataset without any preprocessing or transformation of the original series. The trending component revealed by SSA for production prediction matches the forecasting capability of traditional reservoir production decline curve analysis (DCA), and is a considerable time-saving method. Unlike DCA, SSA is a nonparametric, modeless time series analysis method so no assumption for a certain model is needed to be setup before analysis.
Not only can SSA be used for production forecasting, but it can also be used for ESP operational optimization. Secondary or tertiary decomposed components from SSA can shed light on possible ESP operational issues or wellbore issues that could change the course of the typical production decline behavior for a well. Several case studies are included in this paper to demonstrate the capability of SSA in areas of ESP early faulty detection, evaluating the impact of ESP operation parameters on the reservoir and detection of cycling pattern on production that could lead to further investigation.
Enhanced Well Control Implementing Human Factors
Authors: De Nicolais Nelly , Vadala Rossana , Abate John , Olsen Jan , McHattie Jamie 
Published: August 2016

Abstract
Recently, there have been significant enhancements for well control training. Accidents have motivated and necessitated this improvement. As a result of accident investigation, the IOGP (International Association of Oil and Gas Producers) recommended to define, develop and implement enhanced technical and behavioral practices for well control training coupled with evaluation and certification of the recognized industry certifying bodies. Implementation of these recommendations and improvements is the topic treated in this paper.
These enhancements address best practices and add the topic "human factors" to the course. Human factors refer to situational awareness, decision-making, teamwork and dynamics, leadership, communication and performance shaping factors. This paper also outlines traditional well control training. Traditional well control training has typically four levels, each with its own materials, and thereby targets various drilling professionals with different roles on the rig. The highest level course is designed for supervisors, and is required in order to participate in the new IWCF (International Well Control Forum) accredited Enhanced Well Control course. The Enhanced Well Control course has been developed with the accreditation body (IWCF), a drilling contractor (Seadrill) and a training provider (Maersk Training). Having representation of these three entities maximizes the effectiveness of this training in that the interests of the end user, the accreditor and, of course, the service provider are all met within a common and agreed upon framework. Enhanced Well Control incorporates expanded scenarios (setting of cement, running casing, and unconventional well kill methods), specific practices and exercises and behavioral responses. Many topics are covered with focus on teamwork, leadership, decision-making and situational awareness. Case studies and customized scenarios are also treated. These developments in well control training provide a safer and more productive drilling environment.
Using a Forensic Tool to Save Bed Space With Visual Planning
Authors: Little Joe , Fleming Claire , Donnelly Bob 
Published: August 2016

Abstract
This paper will show how learning from another industry can have a measureable, positive impact on the energy sector; and how BP's recognition and early adoption of one visualization system has generated significant value through reduced Operational Expenditures (OPEX), increased efficiencies and enhanced collaboration.
This paper will show how BP was a pioneering adopter of visual asset management (VAM) through its use of the R2S system and how its search for innovative technological solutions outside the energy industry uncovered R2S, a technology that had been used since 2003 for crime scene forensic investigations. BP recognized that R2S would be invaluable in providing onshore staff with a detailed view of offshore facilities, comprehensive visual context, reduced travel and bed space requirements and improved access to vital information.
The case studies referenced in this paper provide examples from both the North Sea and Gulf of Mexico that demonstrate how the adoption of this technology has yielded considerable financial and time savings (stretching into man years); improved collaboration, familiarisation, problem solving, HSE and, crucially, reduced bed space requirements.
From a technology designed to support a completely different industry - forensic, R2S has evolved into a technology which is supporting BP, to meet several key challenges facing the industry, not least the lack of offshore bed space. As an established norm for asset management within various BP business segments and throughout its supply chains, this paper will also show how, through continued collaboration with the R2S development team, BP's R2S users are working to ensure the system evolves to meet business needs going forward.
Enhancing Real Time Decision Making Through Virtual Metering by Integrating Third Party Simulation Software with Live Data
Authors: Filsell G. R. , Rohnean A. I. 
Published: August 2016

Abstract
On Oil & Gas facilities, metering systems are used for monitoring and recording plant conditions and specifications in order to support decision making. However many key specifications required for operational decisions cannot be physically metered. Traditionally this would require an engineer to analyse other recorded variables to determine the value for such a specification. This paper describes an innovative approach to support real time operational decision making by creating virtual meters.
While useful on a small scale, the traditional method is time consuming and error-prone. Our approach involves the development of an automated service that gathers live data from the plant's operational historian and integrates with third party simulation software to enable more complex calculations of plant specifications of interest. The service is then able to publish the calculated values back to the operational historian in near-real time, simulating the behaviour of plant meters.
This approach is effectively creating virtual meters that support real-time decision making at an operational level. The process is automated, allowing the engineers to focus on using these specifications rather than calculating them. The produced data is recorded periodically and available in the same format as the rest of the plant data. The same methods and tools can be used for analysis of the live and historical data for identifying trends and predicting when a specification is approaching key thresholds, enabling the operator to take steps to rectify the process. The concept has been successfully used for a major operator in the North Sea to allow them to maintain production specifications within contractual requirements.
The creation of virtual meters by integrating key systems to support near-real time decision making is a novel approach, which can be extended to other areas where measuring plant conditions / specifications is not physically easy or possible.
Results of Real-Time Production Optimization of a Maturing North Sea Gas Asset with Production Constraints
Authors: de Boer J. , van der Linden R. , Renes W. 
Published: August 2016

Abstract
Operating maturing assets poses increasingly complex challenges to operators. Meeting hourly or daily production targets becomes more difficult when wells are more often shut in for e.g. water washes (against salt deposition) or solvent jobs (at asphaltenes deposition). Declining reservoir pressure in turn results in less margin to compensate lost production while topside facilities can put constraints when production GOR and watercut increase at late production life. In a joint industry project of Wintershall, GdF, EBN, Siemens and TNO the applicability of real-time optimization is explored. The problem description, system architecture and initial optimizer results were presented in Linden (2013). This paper presents results of the optimization project and looks ahead to further field realization. The goal of this paper is to demonstrate that production of a mature North Sea gas asset can be optimized taking into account realistic constraints. All wells at this gas asset are intermittently shut in for water washes while daily nominations must be met. It will be shown that the optimization algorithm obeys the constraints and is fast enough for real-time application and thereby ready for field implementation.
Real-Time Production Surveillance and Optimization at a Mature Subsea Asset
Authors: Ma Xiang , Borden Zachary , Porto Paul , Burch Damian , Huang Nancy , Benkendorfer Paul , Bouquet Lynne , Xu Peng , Swanberg Cassandra , Hoefer Lynne , Barber Daniel F. , Ryan Tom C. 
Published: August 2016

Abstract
A real-time production surveillance and optimization system has been developed to integrate available surveillance data with the objective of driving routine production optimization. The system aims to streamline data capture, automate data quality assurance, integrate high and low frequency data to extract maximum value, optimize the design and analysis of commingled well tests, and provide real-time multi-phase well rate estimates for continuous well performance evaluation.
A key challenge identified was the need to understand individual well contribution during commingled well tests, as traditional approaches may provide unrepresentative results. Additionally, the well tests are typically infrequent, thus further limiting the reliability of estimated well rates as production system dynamics between well tests are not accounted for. A third challenge recognized was the need for efficient testing procedures in order to minimize deferred production. To address these issues, a fully integrated model of the production system was used, and is driven by a computational algorithm that automatically calibrates the model to real-time sensor data.
A new systematic approach was developed to analyze multi-segment commingled well tests simultaneously to improve the accuracy of resulting measurements. Between well tests, a robust regression algorithm is used to continuously adapt and re-calibrate the model when well conditions change. This algorithm can automatically detect sensor bias and apply an appropriate weighting when calibrating the model. In addition, a regularization technique is also used to prevent physically unrealistic changes in the well parameters between infrequent well tests.
The technology is currently applied to an offshore deepwater asset and early benefits include a 2% production uplift realized from optimizing gas lift allocation and performing a single well routing change recommended by the technology. Furthermore, more reliable rate allocation to wells has improved the quality of subsurface models used for reservoir management.
Monitoring of Non-Technical Barriers
Authors: Næss S. , Fløtaker H. P. , Kaarstad M. , Drøivoldsmo A. 
Published: August 2016

Abstract
Companies on the Norwegian continental shelf (NCS) have in recent years mainly focused on control of the integrity of technical barriers. Against the background of learning from incidents, verification and monitoring activities, both authorities and companies have seen the need to strengthen the work of the management of non-technical barriers.
DNV GL and IFE have together with an NCS operator company developed a method to proactively capture factors that have impact on major accident risk in the organisation. The method monitors the use and maintenance of non-technical barriers against major accidents on three levels of management. It is pro-active, and strengthens the management's ability to identify and understand the subtle signals of weakening of non-technical barriers against major accidents. The method may be included in the existing management system; it is based on existing requirements and does not need new systems, resources or expertise.
The testing on the three management levels showed that the method is relatively easy to learn, but using the method required understanding. Those who were involved seem relatively quickly to take ownership and see the usefulness of the method. The strength of the method is its ability to support the company's subject matter expertise to interpret ambiguous information, identify weak signals and assemble knowledge into information that can be used to assess the status of non-technical barriers. Based on this, the expertise can prioritize and highlight few and effective measures at all levels of the organization. On the basis of the good experience from the testing, the project recommends to implement the method in the organisation.