Technical Perspective Research Articles

Techno-economic analysis and tri-objective optimization of a novel HDH desalination with PVT and vapor-compression chiller for sustainable water supply in remote areas

Desalination is a powerful tool for addressing freshwater scarcity. This study introduces a stand-alone desalination unit based on humidification-dehumidification, photovoltaic-thermal, and vapor-compression chiller technologies for providing sustainable water supply in remote areas. The system is evaluated from both technical and economic perspectives, and three refrigerants (R22, R134a, and R407C) are tested to determine the best option for the vapor-compression chiller. The system is comprehensively modeled using an artificial neural network trained for tri-objective optimization by employing a genetic algorithm. The optimization aims to maximize the freshwater production rate and gain output ratio while minimizing the cost rate. The results indicate that the photovoltaic-thermal unit comprises about 97% of the cost rate. At the optimum point, the freshwater production rates are 43.81 m3/day for R22, 40.56 m3/day for R407C, and 36.65 m3/day for R134a. The cost rates are highest for R407C at 48.04 $/h, followed by R134a at 45.72 $/h and R22 at 43.74 $/h. Similarly, the gain output ratio follows the same order, with R407C having the highest ratio of 1.28, followed by R134a with 1.27 and R22 with 1.24. The study concludes that R407C is the best option in terms of technical, economic, and environmental factors.

A Comprehensive Review of Machine Learning for Water Quality Prediction over the Past Five Years

Water quality prediction, a well-established field with broad implications across various sectors, is thoroughly examined in this comprehensive review. Through an exhaustive analysis of over 170 studies conducted in the last five years, we focus on the application of machine learning for predicting water quality. The review begins by presenting the latest methodologies for acquiring water quality data. Categorizing machine learning-based predictions for water quality into two primary segments—indicator prediction and water quality index prediction—further distinguishes between single-indicator and multi-indicator predictions. A meticulous examination of each method’s technical details follows. This article explores current cutting-edge research trends in machine learning algorithms, providing a technical perspective on their application in water quality prediction. It investigates the utilization of algorithms in predicting water quality and concludes by highlighting significant challenges and future research directions. Emphasis is placed on key areas such as hydrodynamic water quality coupling, effective data processing and acquisition, and mitigating model uncertainty. The paper provides a detailed perspective on the present state of application and the principal characteristics of emerging technologies in water quality prediction.

Optimizing the CO2 capture and removal process to recover energy and CO2 from the flue gas of boilers and gas turbines outlet with considering the techno-economic analysis

This research aims to evaluate, simulate, and model the CO2 capture process for removing CO2 from the flue gas outlet flow of boilers and gas turbines. To the best of the knowledge Aspen HYSYS was employed to simulate these processes, enabling the analysis of technical conditions and evaluation of the problems and advantages associated with various designs from a technical perspective. Additionally, Aspen Capital Cost Estimator (ICARUS) was utilized for economic analysis.Initially, the CO2 capture process was examined for the removal of CO2 in the flue gas outlet flows of gas turbines and boilers. Subsequently, the process was simulated in the software to explore different optimal modes. Moreover, the feasibility of using a compressor, blower, ejector, and a combination of ejector and compressor was considered so as to provide the necessary pressure for absorption. Finally, the optimal design was selected, and more detailed studies were conducted on its absorption process, taking into account major variables. Among the important factors affecting absorption, were the number of trays, diameter, height, the amount of inlet gas and amine flow rate entering from the top of the tower, as well as the inlet gas pressure.

Unsupervised technical phrase extraction by incorporating structure and position information

The vigorous development of patent applications in recent years provides an opportunity to unveil the inherent laws of innovation, but it also puts forward higher requirements for patent mining technology. An essential step for patent text mining is to establish a technology portrait for each patent, that is, identify the technical phrases involved, which can be summarized and represented by the patent from the technical point of view. Currently, there is a large body of work focusing on keyword extraction. However, technical phrase extraction differs from keyword extraction due to the unique properties of technical phrases. Specifically, technical phrases must contain rich technical information and are essential to the entire patent text from a technical perspective. Meanwhile, finding potential relationships between phrases with different technical meanings is challenging for technical phrase extraction. Based on the analysis of the characteristics of technical phrases, we found that the position of technical phrases in the patent text and the structural relationship between technical phrases are crucial, and how to make good use of these two pieces of information is a challenge. Motivated by this, we propose a new Unsupervised Technical phrase Extraction model from the Structure and Position information perspective, named UTESP. Specifically, UTESP includes four key steps: candidate generation, graph construction, candidate score, and candidate selection. The structure information refers to adjusting the incoming edge weight of candidate phrases through the distance relations between candidate phrases and applying the graph ranking algorithm to obtain the structure score of the candidate phrase. The position information simultaneously incorporates the position and frequency of candidate phrases in the patent text to calculate a position score for candidate technical phrases. The effectiveness of our framework has been demonstrated by comparing with seven competitive algorithms on the patent datasets in terms of three evaluation metrics: Precision, Recall, and F1 scores. Besides, our new framework indicated significant improvements in the representation ability of technical phrases by comparing Information Retrieval Efficiency (IRE) with competitive algorithms.

TECHNO-ECONOMICAL STUDY ON THE PRODUCTION OF HIGH OCTANE GASOLINE IN LIGHT NAPHTHA PLANT

The Indonesian government is optimizing the production of high-octane gasoline by utilizing existing ingredients that are plentiful and rarely used in Indonesia to keep up with the rising demand for it. Although light naphtha, a by product of the oil refinery process, has the potential to be transformed into fuel with a high Research Octane Number, its application has not yet been fully realized. The objective of this study is to carry out a study of the economic and technical feasibility of high-octane gasoline plants. A 10,000 barrel/day production potential has been built into the plant. In order to reach the RON objective of 98 for high-octane fuel, light naphtha, which has a Research Octane Number of 73, will need to be increased. The production process includes isomerization, depentanizing, and adsorption. From a technical perspective, this plant can produce high-octane gasoline from light naphtha with RON98. From an economic perspective, the Net Present Value is $ 138,247,252; Internal Rate of Return of 29.38 % per year; Pay Out Time is 3 years 5 months; and Break Even Point is 49 %. Overall, based on technical and economic perspectives, this power plant is feasible.

Allocation of Dynamic Operating Envelopes in Distribution Networks: Technical and Equitable Perspectives

A Dynamic Operating Envelope (DOE) specifies the available capacity to import/export power for Distributed Energy Resources (DERs) or connection points of a distribution network in a time interval without violating its physical and operational constraints. This paper proposes a two-stage, top-down approach to allocate DOEs in MV-LV (medium voltage-low voltage) integrated distribution networks. In the first stage, Distribution System State Estimation (DSSE) and Capacity Constrained State Optimisation (CCSO) techniques are employed to allocate DOEs at transformer connection points. Using network data from available metering infrastructure, DSSE estimates the current operational state of the network, whereas CCSO facilitates the DOE allocations at transformer connection points considering technical, soft-equitable and equitable perspectives. In the second stage, the allocated DOEs, containing available aggregate export/import power, are distributed among DERs of LV networks ensuring network integrity. Real-world data of an Australian MV-LV network is employed to demonstrate the effectiveness of proposed approach. Test results show that technical perspective can offer maximum allocated export/import power, whereas, minimum disparity of allocated power among different connection-points is attained for equitable perspective. Further, insightful performance studies of DOE and existing fixed export policies are conducted considering the condition of present as well as future power systems expecting substantial proliferations of renewables.

The CAREPATH Study for Personalized Management of Multimorbidity in Elderly with Mild Cognitive Impairment and Mild Dementia

Introduction: Multimorbidity is prevalent among older adults and is associated with cognitive impairment and dementia, increasing the need for innovative care solutions. The CAREPATH project, funded by the European Commission Horizon 2020 program, has developed an integrated care platform tailored to older adults with multimorbidity, particularly those with mild cognitive impairment or mild dementia. This platform aims to enhance screening, optimize personalized treatment, and support multidisciplinary care, aligning with the European Society of Medicine's policy framework for managing neurodegenerative diseases. Methods: This paper describes the methodology for implementing an integrated care platform focused on managing mild cognitive impairment and mild dementia. CAREPATH architecture supports multidisciplinary care teams in creating personalized treatment plans based on evidence-based guidelines, involving patients and their caregivers. The platform for healthcare professionals features modular disease pages for comprehensive care, including dedicated sections for screening complications and delivering non-pharmacological interventions such as nutrition, lifestyle, and physical exercise recommendations. Results: The CAREPATH platform has been fully implemented from a technical perspective, with the next step being the clinical investigation to evaluate its efficacy in improving health-related quality-of-life for older adults with mild cognitive impairment or mild dementia and its cost-effectiveness. This study will be conducted in two phases: a technical validation and usability study, followed by a clinical investigation (randomized clinical trial) across four European centers in Spain, Germany, the United Kingdom and Romania. Preliminary tests, including functional, integration, and laboratory system testing, have been conducted to ensure the platform's readiness, with most technical issues resolved. The TVU phase is scheduled to begin in September 2024.

Conception of a predictive maintenance system for forest harvesters from multiple data sources

For cost-effective use of harvesters, expensive repairs and unplanned downtimes must be reduced as far as possible. The predictive detection of failing systems and the calculation of intelligent service intervals, necessary to avoid these factors, require in-depth knowledge of the machines' behavior. Such know-how needs permanent monitoring of the machine state from different technical perspectives. In this paper three approaches will be presented as they are currently pursued in the publicly funded project PreForst at Ostfalia University of Applied Sciences. These include the intelligent linking of workshop and service data, sensors on the harvester and a special online hydraulic oil condition monitoring system. Furthermore the paper shows potentials as well as challenges for the use of these data in the conception of a predictive maintenance system.

IoT based electric power theft detection system

Science and technology, with their miraculous advancements, have fascinated human life to such an extent that imagining a world without these innovations is hardly possible. While technology is on the rise, an increase in immoral activities should also be noted. From a technical perspective, “power theft” is a non-ignorable crime that is highly prevalent and directly affects the economy of a nation. Today's life is unimaginable without electricity, almost all things, equipment, and appliances used daily rely on electric power to run smoothly. Solar energy is an alternative but has limitations, such as environmental changes and high initial costs. From rural to urban areas and from domestic to industrial sectors, the use of electricity has increased, but so has power theft. Detecting and eradicating such crimes with the help of the developing scientific field is the “need of the hour.” With these views, the paper was conceived and designed. The paper provides a complete and comprehensive tool to stop power theft, which is extremely simple to understand and easy to implement.

Application of Biopori Technology for Sustainable Management of Household Organic Waste

Management of household organic waste is very important, especially in urban areas, because improper disposal causes the environment to become unhealthy. This research aims to determine the adoption and application of bio pore technology for sustainable organic waste management in Sleman Regency, Yogyakarta. The method used is descriptive quantitative using survey techniques, participatory action research (PAR), and focus group discussions (FGD) to determine public perceptions and the effectiveness of technology. The analysis was carried out descriptively using indicators of relative advantage, compatibility, complexity, trialability, and observability of biopori technology. The research results using the Wilcoxon-Rank test analysis showed a significant difference in Knowledge, Attitudes, and Practices (KAP) scores before and after training. The public assesses waste processing using bio-Pori technology based on relative advantage, compatibility, complexity, trialability, and observability very good. Biopori technology is compatible with previous technologies, easy to learn, accepted, applied, and successfully tested. The application of Biopori technology improves soil quality , reduces organic waste, and provides benefits to society both from an economic and technical perspective. The research results have implications for the acceptance and feasibility of bio-Pori technology as a sustainable solution for managing household organic waste of household

Research on Security Governance of Data Elements in the Context of Digitization

Abstract This paper presents a multi-subject collaborative data security governance system architecture that caters to various aspects of data security governance. It also introduces an attribute-based encryption technology that utilizes multi-subject data, specifically a multi-subject access control policy fusion algorithm scheme from a technical perspective. The neural network is chosen to build the prediction model. The particle speed is changed using the linear decreasing weight strategy. The improved particle swarm algorithm is used to set the initial weight coefficients and bias variables of the BP neural network. This creates the shared information security risk prediction model. In order to derive the maximum number of iterations of the data security risk prediction model, analyze the encryption and decryption overhead of the multi-owner access control strategy. Additionally, analyze the fluctuation amplitude of MAE and MRE that meets the error threshold range, selecting the virus attack industry for analysis. The probability of occurrence of information data risk points is assessed by analyzing the frequency of coding structure for data technology risk, data management risk, and data legal risk, which is combined with the interview data. The statistics show that the data management risk category, with a standard deviation of 32.64, is more volatile than the two core categories of data technology risk and data legal risk. The lack of stability exposes the data security of e-commerce platforms to risky turbulence.

Transesophageal echocardiography related complications.

Transesophageal Echocardiography (TEE) is an important imaging method for the evaluation of cardiac structure and function, and it holds significant value in the clinical management of cardiovascular diseases. Unlike transthoracic echocardiography (TTE), which is non-invasive, TEE involves semi-invasive intracavity operations, leading to increasing attention to its safety and potential complications. Especially with the increasing demand for TEE applications in clinical practice and the rapid growth in the number of facilities utilizing it, the standardized application and safe operation of TEE technology have become particularly crucial. This article will review the literature and draw upon personal experience to analyze the complications and safety of TEE examinations from a technical perspective.

Prosthetic rehabilitation of unilateral midfacial defect resulting from flap related complication: A case report of clinical challenges and their solutions.

Composite defects of the head and neck region after oncologic resection are challenging and require reconstruction of several layers, including the intraoral lining, osseous reconstruction of the mandible or maxilla and soft tissue/skin coverage. Management of complications resulting from flap failure is a challenging task from a technical and aesthetic perspective that can have a substantial social and psychological impact on those affected. This clinical report describes prosthetic rehabilitation of a lateral midfacial defect and the clinical challenges encountered and their solutions in a patient with carcinoma of gingivobuccal complex who underwent composite bite resection, reconstruction and adjuvant radiation therapy. A conventional approach that employed an acrylic substructure and silicone (one-piece) prosthesis was implemented to address the cutaneous cheek defect taking into account history of recent radiotherapy and comprehensive medical history. The delivered prosthesis effectively restored the lost facial contour and concealed the facial defect, contributing to aesthetics and improving the patient's quality of life.

Complementary waste heat utilization from data center to ecological farm: A technical, economic and environmental perspective

The waste heat recovery technology of data center has attracted the attentions for energy conservation and emission reduction in recent years. This paper presents a new scheme which uses heat recovery technology to link the data center and the agricultural sector. The detailed system design, technical validation, and environmental and economic analysis show that the project can fully absorb a large amount of waste heat in the data center, and use the air source heat pump (ASHP) to transport heat to an ecological farm, reducing the consumption of electric energy and promoting the development of agriculture and animal husbandry. In a case study of China Brain Green Data Center, the dynamic payback period is about 3.4 years, and the cumulative net present value will reach $666 k. In terms of environmental impact, the proposed ASHP-based complementary utilization scheme can save 676 MWh of electricity for the data center and 88 MWh of electricity for the ecological farm in each year, which is equivalent to reducing coal by 230 tons and reducing CO2 emissions by 168 tons. Therefore, from the perspective of economic and environmental benefits, this new complementary waste heat utilization technology realizes a win-win development.

Technical and Religious Perspectives on AI Misinformation and Disinformation

Technical and Religious Perspectives on AI Misinformation and Disinformation

РОЛЬ ТЕХНИЧЕСКОГО И ФУНДАМЕНТАЛЬНОГО АНАЛИЗА В РАЗРАБОТКЕ ТОРГОВЫХ СТРАТЕГИЙ НА РЫНКЕ КРИПТОВАЛЮТ

Using an empirical and comparative approach, this study examines the economic factors influencing price dynamics in the cryptocurrency market. Using content analysis methodology, two main methods of forecasting market prices necessary to create an effective trading strategy are studied. These methods are technical analysis, based on the study of price dynamics itself and on identifying certain patterns of price movements, and fundamental analysis, the meaning of which is to analyze the internal value of an asset and to study the factors of movement of cryptocurrency prices. Fundamental analysis also discusses the impact of news and technological changes on the value of a cryptocurrency. From a technical analysis perspective, some of the basic graphical tools needed for forecasting are discussed. This work is intended to highlight the need to use both types of analysis to develop a profitable trading strategy.

Manual Data Collection in Assembly Lines: A Case Study on the Human Factor in Data Accuracy

Due to the growing presence of digital technologies in factories, an increasing number of automated processes systematically record various data such as timestamps, product IDs, quantities, and defects. However, this is still not the case for many manual assembly lines, which often rely on manual data acquisition where workers, in addition to the assembly tasks, are asked to record data manually. Such manual data generation can significantly reduce the data quality and increase the variation of the data. In this paper, the authors study this problem by conducting a case study of a manufacturer of engine components based in Switzerland. The paper examines the antecedents of deviations in manually collected assembly line data—both from a technical and behavioral perspective. Based on the findings, a model is developed for the case company that compares manually collected data to the same data in the planning systems to identify and act on data discrepancies. The paper concludes with practical guidelines on how to mitigate data quality loss in manual assembly.

Technical, Environmental and Economic analysis of utilizing Hydrogen-rich fuel in Decarbonized Container Ships

This paper analyzes the substitution of conventional fuels with hydrogen-rich fuel derived from ammonia for two different types of container ships, focusing on technical, environmental, and economic perspectives. Four operation...

Business Continuity Innovation in Disruption Time: Sociotechnical Systems, Business Analytics, Virtual Business, and Mediating Role of Knowledge Absorptive Capacity

The continuity strategy of business innovation to deal with the disruption condition, it is still many to be designed and explained. Referring to a sociotechnical systems (STSs) approach, this article conceptualizes and practically examines the business analytics, virtual business, and knowledge absorptive capacity that increase and produce the continuity capability of business innovation in uncertain business environment (e.g., COVID-19). We used SmartPLS to empirically evaluate the model based on 145 companies in a developing country of Indonesia that is currently under high disruption. Drawing a technical perspective, business analytics has successfully enhanced business continuity innovation and knowledge absorptive capacity. In a socio perspective, knowledge absorptive capacity significantly produces business continuity innovation. Business continuity innovation suffers if firms adopt virtual business without increasing their knowledge capabilities. Furthermore, mediating effects present higher support from management level to knowledge absorptive capacity strategy, a bigger impact for business analytics, and virtual business to improve and increase the goals opportunities of business continuity innovation. A novel contribution is the integration of STSs (business analytics, virtual business, and knowledge absorptive capacity) that drives business continuity innovation to deal and recover from uncertain environment. Our efforts also align several fields such as information technology-business alignment strategy, knowledge management, and knowledge-business services. Future research would be worthwhile and interesting whether our framework will suitable to different companies/respondents, business context, industry area, and crisis condition.

Biosocial Technical Systems: An Emerging Approach to Analyse Responses to Novel Diseases.

The COVID-19 pandemic emerged in the context of a parallel epidemic of information, namely an infodemic. With the development of vaccines occurring in record time, a disinformation campaign ensued rendering the infodemic ever more troubling. As COVID-19 had to be curbed with vaccines opinion pools and surveys indicated that a minority, but relevant, part of the general public had weakened trust in public health policies and also on governmental responses to the pandemic in general. This dissent in public opinion on pandemic response is interpreted in this chapter as a controversy related to the efficacy and risks associated to vaccines. Such controversy gained momentum partly because traditional scientific communication has been largely unidirectional rather than bi-directional. We propose to apply a novel biosocial technical perspective to examine the COVID-19 pandemic controversy and communication, articulating social, biological and technical issues. The interaction between COVID-19 and vaccines, i.e. artefact-biological interactions, resulted in vaccine development in record time. However, the interaction between social systems and vaccine as artefacts was plagued by partial public reluctance in their acceptance. This rendered communication efforts ever more relevant, bringing lessons related to the importance of a more fluid bi-directional communication in future disease epidemics.