Seamless Information Flow Research Articles

Enhancing Information Exchange in Ship Maintenance through Digital Twins and IoT: A Comprehensive Framework

This article proposes a comprehensive framework for enhancing information exchange in ship maintenance through the integration of Digital Twins (DTs) and the Internet of Things (IoT). The maritime industry faces significant challenges in maintaining ships due to issues like data silos, delayed information flow, and insufficient real-time updates. By leveraging advanced technologies such as DTs and IoT, this framework aims to optimize maintenance processes, improve decision-making, and increase the operational efficiency of maritime vessels. Digital Twins create virtual replicas of physical assets, allowing for continuous monitoring, simulation, and prediction of ship conditions. Meanwhile, IoT devices enable real-time data collection and transmission from various ship components, facilitating a seamless flow of information. This integrated approach enhances predictive maintenance capabilities, reduces downtime, and improves resource allocation. The article will delve into the architecture of the proposed framework, implementation steps, and potential challenges, supported by case studies that demonstrate its practical application and benefits. By addressing these aspects, the framework aims to provide a robust solution for modernizing ship maintenance operations and ensuring the longevity and reliability of maritime assets.

Interpretable Spatial–Temporal Graph Convolutional Network for System Log Anomaly Detection

To ensure seamless information flow and operational integrity, computer systems need effectively to manage their system logs, but the expansion in their scale and complexity makes it hard to detect anomalies. Current methodologies exhibit deficiencies, including inefficiencies in handling abnormal sequences, lack of interpretability, and limited consideration of both temporal and spatial information. To improve, this paper develops a semi-supervised graph neural network model termed the Interpretable Spatial–Temporal Graph Convolutional Network (IST-GCN). By integrating temporal and event similarity perspectives, the IST-GCN harnesses directed and undirected graphs to capture the temporal and spatial aspects of system log events. Hence, the IST-GCN offers temporal and spatial interpretability. Further, a lightweight feature regularization technique is developed to enhance interpretability in both time and space domains, and thus facilitates anomaly detection efficiently. Comprehensive testing verifies that the IST-GCN approach surpasses nearly all state-of-the-art methods across five public log anomaly datasets. On average, IST-GCN improves Average Precision (AP) by approximately 3% and ROC AUC (RC) by about 4% compared to the best-performing baseline methods, underscoring its effectiveness and robustness.

ANALYSIS OF THE FUNCTIONALITY OF LOGISTICS MANAGEMENT FOR EFFECTIVE SUPPLY CHAIN MANAGEMENT IN CONSTRUCTION

The article delves into the critical role of logistics management in the construction industry, emphasizing the need for efficient material resource management and optimized supply chains. It aims to explore the principles of logistics management in construction organizations for supply chain management, with a specific focus on minimizing costs and optimizing resource utilization. The proposed strategic approach involves the transformation of classical concepts into logistics-oriented organizational activities, integrating advanced technologies and innovative resource management systems to unlock the full potential of material assets and streamline operations. The article underscores the potential impact of these strategies on the nation's economic landscape, emphasizing their contribution to economic stability and resilience. Additionally, the integration of logistics management into construction practices is highlighted as a catalyst for scientific advancements within the field. Serving as a roadmap for construction companies, the article urges the adoption of forward-thinking strategies aligned with the demands of the contemporary construction landscape. By embracing innovative approaches and leveraging advanced technologies, construction organizations can drive economic revitalization and contribute to broader urban development initiatives. Additionally, the article emphasizes the importance of collaboration and integration among stakeholders in the construction industry, leveraging digital platforms and collaborative tools to enhance communication, share real-time data, and streamline coordination among suppliers, logistics providers, and project teams. Integrated logistics networks will enable seamless flow of information and resources.

Advancements in health informatics for monitoring perioperative patient data

Advancements in health informatics are revolutionizing perioperative care by enhancing patient monitoring, improving clinical decision-making, and promoting patient safety. The integration of electronic health records (EHR) facilitates seamless information flow across all perioperative stages, ensuring up-to-date patient data is accessible to the entire healthcare team. This accessibility reduces errors, improves coordination, and enhances overall patient outcomes. EHR systems also support standardized documentation, reducing variability in record-keeping and ensuring comprehensive patient information is consistently captured. Real-time data analytics and predictive modeling are powerful tools in perioperative settings, enabling clinicians to anticipate and manage potential complications proactively. By analyzing vast datasets, predictive models identify patterns and risk factors associated with adverse outcomes, allowing for targeted interventions and personalized care plans. Real-time analytics provide continuous monitoring of patient status during surgery, offering immediate feedback and enabling prompt adjustments to ensure patient stability. Wearable devices and remote monitoring systems further augment real-time data analytics by continuously tracking physiological parameters throughout the surgical process and into the postoperative period. This continuous data stream allows for ongoing assessment of patient status and early detection of complications, enhancing patient safety and outcomes. Health informatics solutions, including automated alerts and decision support tools, minimize human error and ensure adherence to clinical guidelines. Automated reminders for critical actions, such as timely antibiotic administration, significantly reduce the incidence of surgical site infections. Decision support tools provide real-time, evidence-based recommendations at the point of care, supporting clinicians in making informed decisions and improving patient outcomes. Additionally, health informatics facilitates continuous quality improvement by enabling the collection and analysis of performance data, informing targeted interventions and process improvements. Overall, advancements in health informatics are transforming perioperative care, offering numerous benefits in terms of efficiency, accuracy, and patient safety, ultimately leading to better patient outcomes and higher quality of care. Continued innovation in this field will be essential for maintaining and improving the standards of perioperative care.

Conceptual Framework of Information Flow Synchronization Throughout the Building Lifecycle

The construction industry’s reliance on traditional methods and fragmented workflows results in significant information loss, inefficiencies, increased costs, and errors. This study addresses these issues by integrating comprehensive urban planning with building information modeling (BIM) to create a seamless information flow throughout the building lifecycle. We propose a holistic framework that synchronizes data from planning to demolition, incorporating national and municipal digital twins. An imperative literature review and analysis of international best practices were conducted to develop a conceptual framework aimed at improving data accuracy and interoperability. Our findings underscore the importance of adopting open standards such as Industry Foundation Classes (IFC) and CityGML for effective information exchange. By implementing an information model (IM)-based approach in urban planning and public sector permit processes, project timelines can be streamlined, and regulatory compliance enhanced. This study concludes that continuous, integrated information flow facilitates more efficient, cost-effective construction practices and improved decision-making. Furthermore, this research illustrates the potential of digital twin technology to revolutionize the construction industry by enabling real-time data integration and fostering stakeholder collaboration, ultimately offering a robust framework for practitioners, and significantly enhancing the efficiency and accuracy of construction processes.

A Semantic Digital Twin for the Dynamic Scheduling of Industry 4.0-based Production of Precast Concrete Elements

Precast concrete construction enhances project efficiency, sustainability, and durability by leveraging a controlled production environment that ensures high-quality outputs. Still, the sequential nature of off-site production, encompassing casting, curing, and storage of the precast elements, is subject to significant uncertainties, including supply chain variability and environmental factors affecting curing times. Dynamic adjustments to the production schedule are essential for aligning with real-time changes, necessitating a robust framework for real-time data acquisition and analysis. Dynamic Scheduling (DS) is a responsive and adaptive approach that accommodates real-time changes, optimizes the production flow, and minimizes downtime or delays. However, the DS approach demands real-time data to quickly and efficiently respond to unforeseen challenges, which requires acquiring and analyzing production-relevant data throughout the production process. The Digital Twin (DT) emerges in Industry 4.0 (I4.0) as a bridge between physical operations and digital capabilities, enabling a seamless flow of information, for which the Asset Administration Shell (AAS) is a reference implementation. This study introduces a DS framework to optimize precast element production, utilizing a DT for real-time data aggregation across the production system. The framework implements a Semantic DT based on the AAS and the Linked Data approach. It employs Resource Description Framework (RDF) serialization of the AAS and an ontological representation of the production system for data integration. The framework leverages a simulation-based scheduler, which exchanges data with the DT in a Service-oriented Architecture (SoA) using SPARQL, a language for querying and updating graph databases. The approach is evaluated through a proof of concept, demonstrating effective uncertainty management in a dynamic production environment.

To Enhance the Efficiency and Effectiveness of Electronic Health Record for Hospital Management System

Our project hospital management system includes registration of patient's details storing into the system and booking appointments with the doctors and taking care of staff. This website is powerful, flexible, and easy to use. Our software has the facility to give unique IDs to patients and staff. The details of each patient and staff are stored on this website. This interface is user friendly. Here website can be login through username and password. The lost data can be recovered easily. The admin can manage the total website and data is well protected here by admin. It improves the quality and management of the hospitals. The primary goal of a Hospital Management System is to enhance the efficiency and effectiveness of healthcare delivery by providing a centralized platform for managing various aspects of hospital administration, patient care, and related activities. The Hospital Management System encompasses a wide range of functionalities, including patient registration, appointment scheduling, billing and invoicing, electronic health records (EHR), inventory management, and reporting. It leverages information technology to create a seamless flow of information between different departments within the hospital, ensuring smooth communication and coordination.

COLLABORATIVE AUDITING IN OSMOTIC COMPUTING ENVIRONMENTS: OPPORTUNITIES AND CHALLENGES

As organizations increasingly embrace digital transformation and interconnected ecosystems, the need for effective auditing mechanisms becomes paramount. This research paper delves into the emerging paradigm of collaborative auditing within osmotic environments, exploring both the opportunities and challenges associated with this novel approach. Osmotic environments characterized by their permeable boundaries, allowing the seamless flow of information across diverse platforms, devices, and networks. The opportunities presented by collaborative auditing in osmotic environments are manifold. By leveraging collective intelligence and distributed resources, organizations can achieve more comprehensive and real-time audits.

Open innovation in a smart city context: the case of Sejong smart city initiative

Open innovation in a smart city context: the case of Sejong smart city initiative

Investigation and development of scheduling and networking technologies for small cells based on optical transmission networks

In addition to the power dispatching department, other related departments and management agencies are also interested in power grid data. These developments coincide with an increase in the number of plants and stations, a dramatic increase in the amount of power system data, and an increase in the difficulty of managing and analyzing the data. Thus, a key area of current power information system research is how to analyze and process the massive amounts of grid operation data to guarantee the safe and effective implementation of power production while also being able to support decision-making for power production and power scheduling. In light of this, this paper builds a complete number distribution system on top of the current scheduling program-controlled exchange, hoping to inherit the high reliability and stability of the scheduling switching network. It also introduces the IPoE technology networking and offers a technical foundation for the state management of the equipment. Finally, it uses the optical transmission network scheduling telephone networking technology as its foundation, based on a thorough analysis of the current state of the domestic power dispatching management system. In order to improve the quality of power grid management, it is helpful in the development of an organic and unified integrated intelligent system, the creation of an ideal and seamless information flow, and the eventual realization of the integration and standardization of the production plan, the production process, and the sale of electricity.

Precision technologies for the management of reproduction in dairy cows.

Precision livestock farming (PLF) utilizes information and communication technology (ICT) to continuously monitor, control, and enhance the productivity, reproduction, health, welfare, and environmental impact of livestock. Technological advancements have facilitated the seamless flow of information from animals to humans, enabling practical decision-making processes concerning health, reproduction management, and calving surveillance. With the increasing population of livestock per farm, it has become impractical for farmers to individually track every animal within these large groups. Historically, cattle management decisions heavily relied on human observation, judgment, and experience. However, it is impossible for a single individual to gather reliable audio-visual monitoring data round the clock. Presently, dairy cows exhibit subtler indicators of estrus, resulting in a substantial chance of missing an estrus cycle. Furthermore, calving complications sometimes go unnoticed on farms, resulting in a higher number of culled cattle. In addition, an increasing number of crossbred cows experience delayed return to estrus after calving due to low body condition scores (BCS). The decline in BCS during the dry period is associated with a reduced likelihood of pregnancy following the first and second postpartum inseminations. Precision technologies enable the monitoring and tracking of an individual cow's physiological behavior and reproductive parameters, thereby optimizing management practices and farm performance. Despite the exploration of various technologies, there are still some common challenges that need to be addressed, including battery lifespan, transmission range, specificity and sensitivity, storage capacity, and economic affordability. Nonetheless, the demand for these tools from farmers and researchers is growing, and the implementation of PLF in grazing systems can yield positive outcomes in terms of animal reproductive welfare and labor optimization. This review primarily focuses on the different aspects of reproduction management in dairy using sensors, automated cameras, and various computer software.

Digital Transformation and Digital Culture: A Literature Review of the Digital Cultural Attributes to Enable Digital Transformation

Abstract Digital transformation is unavoidable for organizations nowadays. The promise of financial success pushes organizations to speed up their digital transformation, by increasing the budgets allocated to it. Organizations understand more and more that digital transformation is not only an IT endeavor and that it implies, among others, the important aspect of digital culture. Digital culture goes hand in hand with the process of digital transformation, being both a premise to, and an outcome of it. As a premise, digital culture can be either an enabler for, or a barrier to digital transformation, which is why digital culture is receiving increased attention in scientific literature. This study analyzes the scientific literature to create a well-rounded definition of digital culture, categorizing and describing in detail the attributes of digital culture, both the ones mentioned by previous studies with a similar purpose and adding new categories to provide a more comprehensive understanding of what digital culture entails. Digital culture is characterized by collaboration, both internal and external, customer-centricity, seamless flow of information, decision making at lower organizational levels, responsiveness and rapid action, innovation and entrepreneurial mindset, risk-affinity, flexibility, agility and adaptability, learning and growth orientation, as well as datadriven decisions, digital-first mindset, openness to unusual career developments and change openness and readiness.

A Realistic and Practical Guide for Creating Intelligent Integrated Solutions in Higher Education Using Enterprise Architecture

Enterprise architecture (EA) plays a crucial role in organizations by providing a clear strategy for digital transformation and seamless information flow across boundaries. It is a tool for achieving current and future objectives effectively. By providing a comprehensive view, EA helps organizations build suitable and sustainable software solutions while avoiding complex challenges caused by unmanageable information flow blockages. Moreover, EA provides a standard framework for implementing enterprise resource planning (ERP) systems. Although EA and ERP systems have different concepts, they possess complementary characteristics that support decision-makers in the ERP selection process, which can be quite risky due to cost feasibility, time consumption, and team effort. This study proposes using the EA concept as a reference module for selecting the most suitable integrated solution for the higher education sector. The aim is to provide high-impact criteria for choosing the most appropriate ERP system as a core solution. Additionally, EA supports other related solutions integrated with the ERP system under the EA umbrella to run a fully automated smart entity. To determine the most suitable ERP solution for higher education entities in the study country, a set of critical criteria for ERP selection as a core solution in the education sector is generated through brainstorming, which is based on an EA reference module specifically designed for higher education entities that seek to operate smartly. A comparison technique is employed to evaluate the highlighted criteria, including a case study for ABC University. The study’s results reveal that fully integrated and sustainable solutions can be envisioned for higher education entities, which can support the digital transformation of the higher education sector based on a smart EA reference module along with a set of critical main ERP selection criteria. This can mitigate the risk associated with ERP selection as a core solution and support decision-makers in selecting the most suitable ERP package for educational entities.

Relevance of tumor boards for the inclusion of patients in oncological clinical trials.

Major national and international oncological societies generally recommend treating a significant proportion of oncological patients in clinical trials to improve therapy strategies for cancer patients. At cancer centers, the recommendation about the appropriate therapy for the individual tumor patient is usually made in interdisciplinary case discussions in multidisciplinary tumor boards (MDT). In this study, we examined the impact of MDTs for the inclusion of patients in therapy trials. A prospective, explorative study of the Comprehensive Cancer Center Munich (CCCM) was conducted at both university hospitals in 2019. In the first phase, various MDTs' case discussions about oncological situations and their decisions regarding possible therapy trials were recorded in a structured manner. In the second phase, the actual inclusion rates of patients in therapy trials and reasons for non-inclusion were examined. Finally, the data of the respective university hospitals were anonymized, pooled and analyzed. A total of 1797 case discussions were reviewed. Therapy recommendations were made in 1527 case presentations. 38 (2.5%) of 1527 patients were already included in a therapy trial at the time of case presentation. The MDTs recommended inclusion of an additional 107 cases (7%), for a therapy trial. Of these patients, 41 were finally enrolled in a therapy trial which resulted in a total recruitment rate of 5.2%. Despite MDTs' recommendations, 66 patients were not included in a therapy trial. The main reason for non-inclusion was insufficient inclusion or existing exclusion criteria (n = 18, 28%). In 48% of all cases (n = 31), the reason for non-inclusion could not be determined. The potential of MDTs as an instrument for the inclusion of patients in therapy trials is high. To increase the enrollment of patients in oncological therapy trials, structural measures such as the central use of trial administration and MTB software in addition to standardized tumor board discussions must be established to ensure a seamless flow of information about actual recruiting trials and the current status of trial participation of patients.

Design and Implementation of Baggao North Central School Computer-Based Record Management System

This study aims to design and develop a computer-based student record management system for Baggao North Central School. The system is expected to streamline the administrative tasks of the school, from keeping track of student records to generating reports. Its user-friendly interface makes it easy for staff to navigate through the system, reducing the chance of human error during record-keeping. Additionally, the quick access feature enables staff to locate student records within seconds, making it an invaluable tool for effective academic management. The system incorporates security features to maintain the privacy of sensitive student information, ensuring that only authorized individuals have access to the data. Moreover, the system ensures that data is always up-to-date and accurate, minimizing the risk of issues arising from inconsistencies in recordkeeping. The system allows selected staff members to input, edit, and view student-related information, promoting seamless information flow within Baggao North Central School (BNCS). This promotes efficiency in managing student records and enables timely decision-making when necessary.

Leveraging Blockchain-Based Electronic Health Record Systems in Healthcare 4.0

Digitalization has become a crucial part of healthcare 4.0 by transforming systems such as electronic health records (EHR), electronic medical records (EMR), and electronic personal medical records (ePHR). Healthcare 4.0 is derived from industry 4.0 and aims to enhance collaboration, virtualization, coherence, and convergence, which helps transform modern healthcare into more personalized and predictive. Healthcare 4.0 also aims to develop digital enablers which will support coordination among various stakeholders and seamless information flow in the patient journey towards wellbeing. These systems enhance patient care through the timely sharing of patient data across different providers globally. Timely sharing helps, but it also makes the electronic system vulnerable to alteration and breaches. In healthcare, blockchain application is widely used in various areas, such as health information exchange, pharmaceutical counterfeit, clinical trials, health supply chain management, patient data management, insurance claims, and product recall in case of adverse events. This research paper aims to identify how blockchain technology can help enhance the privacy and security of electronic health record systems. This paper discusses various blockchain-based systems, which provide a more efficient and secure option than client-server architecture-based traditional EHR systems.

Studies on Effective Usage of SAP ERP Tool to Control Materials Planned Delivery Time in Oil and Gas Industries

The global competitions are making rapid changes in production. Procedure integration and seamless flow of information and data play a vital role in productivity. The planning order improbability, manufacturing lead time and lack of systematic approach are the main concerns in production industries. Enterprise Resource Planning (ERP) and Lean Manufacturing (LM) are the two distinct processes to deal with the above mentioned concerns for competitive manufacturing. ERP focuses on data and schedule accuracy and ensures repeatable and predictable processes. LM concentrates on identifying and eradicating or minimizing all kinds of manufacturing wastes and focuses on reducing process inconsistency. The paper narrates about some holistic approaches that can be practiced with SAP ERP tool in order to achieve the efficient materials planning, master production schedule and capacity planning.

Enhancing the resilience of low-income housing using emerging digital technologies

The research discussed is part of a Belmont Forum disaster risk reduction project aimed at enhancing the resilience of low-income housing. This paper examines feasibility and viability of using emerging digital technologies to enhance the resilience of low-income housing based on requirements of resource constrained, low-lying coastal areas in East Africa. The authors focus on the need to facilitate data and knowledge sharing across domains to: 1) reduce or avoid the potential property loss from flooding events through mapping the interdependencies and interconnectedness across natural and human systems; 2) coordinate the provision of temporary shelter for displaced victims, and 3) building (back) better during the recovery phase. The deployment of Artificial Intelligence, Internet of Things, BIM, Digital twin, VR/AR in disaster risk management is still an emerging area of research. In general, cutting-edge digital technologies are deployed as standalone solutions to address existing data and knowledge sharing needs that are unique to a sub-group of stakeholders. A more holistic and comprehensive solution will require an integrative framework that supports the seamless flow of information across the stakeholders. We propose to address this need through an artificial intelligence enhanced data, information and knowledge sharing platform that synthesizes content into actionable insights

Technology Focus: Data Analytics (October 2022)

Oil and gas companies are starting to invest more in the energy transition and establish emissions-reduction goals, such as an end to routine gas venting and flaring, with some going as far as setting net-zero goals by mid-century. A wide range of climate technologies with varying degrees of maturity levels are needed to pave the road to net zero. These include electrification and grid decarbonization, advances in battery technology, blue and green hydrogen fuels, bioenergy, carbon capture use and storage, and mitigating emissions of potent greenhouse gases such as methane. The COVID-19 pandemic has helped accelerate the pace of the digital transformation in the oil and gas industry. Digitalization is, in effect, a part of the broader energy transition that is occurring in the industry. This includes a move from on-premises data centers to the cloud, building digital twins of physical assets, process automation using the Internet of Things (IoT), leveraging reams of data from oil and gas operations for artificial intelligence/machine leaning (AI/ML) applications, cloud-based high-performance computing for applications such as seismic imaging for carbon capture and storage, and predictive maintenance to fix leaky equipment to reduce the environmental footprint of operations. These technologies serve to improve productivity, increase operational efficiency, reduce downtime, increase cost savings, and reduce the carbon intensity of operations. The International Energy Agency report “The Oil and Gas Industry in Energy Transitions” states that reducing methane leaks to the atmosphere is the single most important and cost-effective way for the industry to bring down these emissions. This is a domain that can benefit significantly from the use of AI/ML techniques for leak detection and remediation (LDAR) efforts. ML techniques such as computer vision and anomaly detection can be used to identify both large and localized methane leaks from remote-sensing data and data streaming in from IoT sensors in the field. A combination of data modalities, with varying spatiotemporal resolutions, together with appropriate AI/ML technologies, would be essential for an effective methane LDAR program. As companies look to reduce their Scope 1, 2, and 3 emissions, breaking down data silos and establishing data standardization with common data models becomes critical in systems integration to develop an optimal emissions-reduction strategy. A seamless flow of information will enable the generation of high-fidelity data sets, which can be used to lower the operational footprint and drive business effects with AI solutions. With cloud-enabled technologies, driven by the application of ML and deep learning, companies can combine speed of implementation with scalability to accelerate their energy-transition efforts. I would like to invite readers to review the selection of papers to get an idea of various applications in the upstream oil and gas space where ML methods have been used. The highlighted papers cover the use of transformer-based models to predict oil production, the use of data analytics to study parent/child well relationships in shale plays, and the use of convolutional neural networks in core analysis. Recommended additional reading at OnePetro: www.onepetro.org. SPE 207744 Accelerating Subsurface Data Processing and Interpretation With Cloud-Based Full Waveform Inversion Systems by Sirivan Chaleunxay, Amazon Web Services, et al. SPE 205443 Natural-Language Processing and Text-Mining Approaches in Production-Shortfalls Analytics: Methodology, Case Study, and Value in the North Sea by Edgar Bernier, Total Denmark, et al. URTEC 208367 Real-Time Applications for Geological Operations: Repeatable AI Use Cases by Alfio Malossi, Eni, et al.

Intelligent Network Solution for Improved Efficiency in 6G-Enabled Expanded IoT Network

The fast-moving world relies on intelligent connected networks to support the numerous applications of the expanded Internet-of-Things (IoT). The evolving communication requirements of this connected world require a new sixth generation (6G) radio to enable intelligent interaction with the massive number of connected objects. The energy management of billions of connected devices supporting massive Internet-of-Things (IoT) applications is the main challenge. These IoT devices and connected nodes are energy limited, and hence, energy-aware solutions are needed to enable seamless information flow between these communicating nodes. This paper presents an intelligent network solution for improved energy efficiency in a 6G-enabled expanded IoT network. A cell-free massive multiple input multiple output (mMIMO) technology is utilized for maximum energy efficiency with optimum network resource allocation. A practical power consumption model is proposed for the designed network topology which contains all the power components related to data transmission and circuit power. The proposed scheme aims to achieve maximum energy efficiency by the optimal allocation of pilot reuse factor and access point (AP) density for a given number of antennas at each AP and number of users. It is observed that the maximum energy efficiency of 5.2362 Mbit/Joule is achieved at the AP density of 29 and pilot reuse factor of 4 with PMMSE receive combining. In the end, the role of energy efficiency and area throughput tradeoff on the system performance is also evaluated, which suggests that both the energy efficiency and area throughput can be jointly increased until maximum energy efficiency is reached at a point.