Projection System Research Articles

Evaluating the performance of the Anwaralardh photovoltaic power generation plant in Jordan: Comparative analysis using artificial neural networks and multiple linear regression modeling

The global energy demand is rising, driven by population growth, economic development, and industrialization. Shifting towards renewable energy, like solar energy, is gaining momentum worldwide because of ecological concerns and resource depletion. This paper aims to utilize Artificial Neural Networks (ANNs) and multiple linear regression (MLR) modeling techniques to evaluate the productivity of 11 MW photovoltaic (PV) solar power plant currently operational in Jordan. The case study reveals that both models can be used to predict the daily, monthly, and yearly average power produced and system efficiency with reasonable accuracy. The ANN model exhibited promising results, where the best value for the coefficient of determination (R2) and mean absolute percentage error (MAPE) for training were 95.85% and 0.59%, respectively. However, R2 was 93.7%, and MAPE was 1.27% for validation tests. All these results were achieved using a 7-6-1 model, with a sample ratio of 1:1 for the data allocated in training and validation. When using multiple linear regression, the R2 and standard error values were 93.42% and 0.17%. On the other hand, the results showed that the yearly output power for actual and predicted by both models over the year was 24,399 MWh, 24,538 MWh, and 24,401 MWh, respectively. This research showed valuable results in the monthly output power for solar cells at the Anwaralardh PV power system project, contributing to a better understanding of solar energy generation in arid desert climates and emphasizing the potential of solar power plants to play a crucial role in achieving SDG 7 objectives.

Characterizing thermo-hydro-mechanical behavior of rock using a grain interface-based discrete element model (GIB-DEM)

Understanding the meso-structure evolution and macro-mechanical property changes in rocks under thermo-hydro-mechanical (THM) treatment is crucial for advancing and managing deep geological projects. However, due to complex discontinuity networks in rocks, achieving an accurate characterization that quantitatively correlates the micro-macro mechanical behaviors under THM conditions remains challenging. This study introduces a groundbreaking multi-scale analysis method called the grain interface-based discrete element model (GIB-DEM) to tackle this issue. By utilizing digital imaging processing (DIP) and meso-mechanical measurements, the GIB-DEM directly determines the meso-mechanical parameters of bonds, eliminating the need for complex calibration found in traditional methods. After validating the GIB-DEM through experimental and numerical Brazilian Splitting tests, we investigate the macro- mechanical behaviors of rock under different THM conditions. Our results indicate that the increase in the tensile strength at 75 °C is attributed to the tensile strength increase of quartz grain interfaces. The development of micro-cracks on the interfaces of feldspar and feldspar-quartz accounts for the decrease in tensile strength of rock under thermal and hydraulic treatment. Overall, this pioneering research provides valuable insights for optimizing Enhanced Geothermal System (EGS) projects and effectively managing Hot Dry Rock (HDR) resources.

Development of an in-service NDT system for storage tanks

The large storage tank is one of the major infrastructures. Once a leak occurs, it often causes environmental pollution and even catastrophic accidents. In the early years, the method of emptying tanks and cutting plates for defects inspection was adopted to avoid leakage. However, there exist some deficiencies such as large blindness, long downtime and high cost. Since there are many problems in the traditional testing, inspection without emptying the tank and without stopping production is an indispensable technical means to ensure the safe operation of the tank. An in-service non-destructive testing (NDT) system for storage tanks without emptying is developed in this paper, which mainly includes sensors, the signal processing module, the testing crawler, the winding and releasing mechanism and control module et. al. The sensors, signal processing module and testing crawler need to be placed into the tank from the roof man-hole by the crane, while the control module is located outside the tank. The sensor can realize the combined inspection of magnetic field leakage (MFL) and electromagnetic acoustic transducer (EMAT). The laboratory experiments indicate that the system can realize in-service inspection of the corrosion defects on the bottom and works well in water. The new testing system will overcome the shortage of off-line service inspection methods that emptying and cleaning tanks are needed before inspection and environmental risks are involved. These research works guarantee the safe operation of storage tanks and provide an alternative NDT system for storages related industrial projects.

An Architectural View Model for Designing and Implementing Microservices-based Systems: Use Case in FinTech

Describing the architecture of microservices systems allows for the illustration of various aspects of design and implementation with information tailored to different stakeholders. On the one hand, the microservices architecture provides flexibility, scalability, faster deployment times, and the potential to design solutions incorporating multiple technologies. An architecture-centered, scenario-driven, iterative development method, on the other hand, is used to explain the system from the perspective of many stakeholders, such as project managers, system architects, developers, and end users. To complement this point of view, this paper proposes an architectural view model that highlights numerous viewpoints and disciplines in microservices-based software development. Such methods are typically well suited for developing and implementing microservices-based software processes to satisfy stakeholders' demands and expectations.

Pemberantasan Dan Pencegahan Oligopoli dan Persekongkolan Oleh KPPU (Studi Kasus PT.Telekomumikasi Indonesia)

The Indonesian Telecommunications Industry Development The Republic of Indonesian government launched the program has a noble goal of ensuring that telecommunications infrastructure reaches all parts of Indonesia. To achieve this goal, several telecommunications companies joined the Parapa Ring consortium and organized the Parapa Ring project which aims to expand telecommunications networks throughout Indonesia. In handling bid manipulation cases, the Komisi Pengawasan Persaingan Usaha Perusahaan (KPPU) applies two main principles, namely the principle of per se illegality and the principle of reasonableness. However, the application of these principles is often challenged and flawed, as evidenced by Decision No. 36/KPPU-L/2010 on alleged discriminatory practices and collusion in the tender for the procurement of the Palapa Ring Mataram-Kupang cable system project. The doctrine of unlawfulness states that a particular agreement or business activity is unlawful if there is no further evidence of its effects. On the other hand, the rule of reason requires further evidence to determine whether an action inhibits or promotes competition. In a tender conspiracy, KPPU applies the rule of reason because it needs to be proven in more depth the effect of the act on business competition. Decision Number 36/KPPU-L/2010 highlights the misapplication of the principle of reason.

Use of Participatory sUAS in Resilient Socioecological Systems (SES) Research: A Review and Case Study from the Southern Great Plains, USA

Since the publication of the seminal work People and Pixels: Linking Remote Sensing and the Social Sciences, the call to “socialize the pixel” and “pixelize the social” has gone largely unheeded from a truly participatory research context. Instead, participatory remote sensing has primarily involved ground truthing to verify remote sensing observations and/or participatory mapping methods to complement remotely sensed data products. However, the recent proliferation of relatively low-cost, ready-to-fly small unoccupied aerial systems (sUAS), colloquially known as drones, may be changing this trajectory. sUAS may provide a means for community participation in all aspects of the photogrammetric/remote sensing process, from mission planning and data acquisition to data processing and analysis. We present an overview of the present state of so-called participatory sUAS through a comprehensive literature review of recent English-language journal articles. This is followed by an overview of our own experiences with the use of sUAS in a multi-year participatory research project in an agroecological system encompassing a tri-county/tri-state region in the Southern Great Plains, USA. We conclude with a discussion of opportunities and challenges associated with our experience.

A data-driven bit projection system with motor yield prediction and advisory for directional drilling and well trajectory control

In the evolving of the oil and gas industry, where innovation and technological advancement are paramount, directional drilling stands as a pioneering technique that has revolutionized the extraction of hydrocarbon resources from beneath the Earth's surface. For drilling with mud motor, accurate projection of bit position from the latest survey and comprehensive evaluation of the current motor yield (MY) are essential to avoiding early well trajectory deviation and optimizing future directional plans. Currently, these responsibilities primarily rest on the shoulders of directional drillers (DDs), consuming valuable drilling operation time and being subject to biased human judgments. In this study, a data-driven bit projection system for directional drilling optimization and well trajectory control is developed. A kinematic model is first constructed for the projection of bit inclination (INC), azimuth (AZI), and north-east-vertical (NEV) in drilling with mud motors. Moreover, in scenarios involving curve section slide drilling, a machine learning model is developed to predict instant MYs observed between surveys, which is trained and tested on a dataset comprising drilling over 350 Delaware Basin curve section stands. Ultimately, a low MY reasoning algorithm is proposed to identify the dominant factor that causes the suboptimal MY output and provides recommendations for upcoming drilling plans. The proposed system is validated using 1189 vertical stands, 240 curve stands, and 1837 lateral stands from 17 different wells. The validation results illustrate that the bit NEV projection error averages below 0.82 ft for 90-foot surveys in vertical/lateral sections. In curve sections, the average MY prediction error is 0.96° one hundred feet or 7.6% in the relative sense and the average 30-foot bit NEV projection error is 0.228 ft, with the predicted MY as input. Compared with the physics-based bottomhole assembly (BHA) bending model and other data-driven approaches in the literature, the proposed system sees a large improvement in MY prediction and the bit NEV projection accuracies. With the minimal input data requirements, fast computation speed, and accurate projection/prediction results, the proposed bit projection system holds the opportunity of application in the autonomous directional drilling system, real-time drilling job evaluations, and well trajectory optimization.

Can nudging with descriptive norms help internal auditors stop runaway information systems projects?

AbstractAlthough internal auditors are expected to play an important role in corporate governance, they are not always effective in bringing their message to management’s attention when they observe that a risky course of action is being taken that could harm the organization. When information systems projects go awry, for example, internal auditors often struggle to get managers to listen to their warnings. Instead, managers may turn a deaf ear to the auditor’s warnings. In this paper, we build on the idea that internal auditors can follow an approach that combines two elements to reduce this so-called deaf effect: (1) the auditor can apply communication techniques to more effectively deliver the message, and (2) the internal auditor can develop a relationship with the manager such that the auditor is viewed as a ‘partner’ rather than an ‘opponent.’Following a mixed method approach, we examined how ‘nudging with a descriptive norm’ as a communication technique could help internal auditors to reduce the deaf effect and how this can be understood in the context of the auditor-manager relationship (AMR). We conducted two experiments showing consistent evidence that both (1) nudging with a descriptive norm and (2) AMR, had significant indirect effects on the deaf effect that were mediated through perceived social norms. A complementary series of ten interviews with Chief Audit Executives shed further light on how internal auditors could apply ‘nudging with a descriptive norm’ as a communication technique, and what should be considered, including the auditor-manager relationship. Implications for both internal audit research and practice are discussed.

Growing Small Grains in Sub‐Arctic Alaska

Abstract The largest state in the U.S., Alaska has only 1% of its land devoted to agriculture. Yet, there’s a strong need for and interest in increasing local production to help fortify food security in the state. The Alaska Collaborative Food Production Systems Project develops research projects and supports agricultural producers in the state. At the 2023 ASA, CSSA, and SSSA Annual Meeting, researchers from the team talked about the project’s objectives and progress. With one growing season under their belts, they’ve made headway on breeding trials, gathered novel data on soil health and quality, finished a year of cover crop trials, and interviewed producers and consumers about food agency in the state.

Visual Materials in Classroom Teaching Learning: A Case Study on Nonformal Primary School

The evolution of technology and the paradigm shift triggered by the COVID-19 pandemic have reshaped educational practices, transitioning from conventional to digital mechanisms. The integration of digital learning resources has introduced a new dimension to the classroom environment. This paper aims to investigate the practicality of utilizing existing visual learning materials in non-formal educational settings. The case study focuses on non-formal primary schools operated by the JAAGO Foundation in Dhaka, serving as a representative sample. Data for this study were gathered through semi-structured interviews, focus group discussions, and observation notes from teachers, learners, and experts in the sampled non-formal primary schools. Thematic analysis was employed to analyze and present the collected data. The findings of the study underscore significant positive effects of employing visual learning materials in non-formal primary classrooms. These effects manifest in the areas of motivation enhancement, assessment of prior knowledge, and promotion of active participation, particularly among disadvantaged learners. The study also highlights the effectiveness of visual materials in facilitating clear comprehension, fostering creativity and imagination, enhancing critical thinking skills, and promoting digital literacy as essential 21st-century skills. Moreover, the research reveals that visual learning materials play a crucial role in achieving desired learning outcomes, aligning with both learners' psychology and pedagogical perspectives. However, the study identifies key challenges hindering the effective use of visual materials in non-formal classrooms, including infrastructural inconveniences such as poor projection systems, noisy sound systems, and inadequate seating arrangements for students. In light of these findings, the study recommends the implementation of professional training sessions for educators and emphasizes the need for school authorities to take responsibility in addressing identified challenges. By doing so, the study advocates for the creation of an environment conducive to effective classroom practices utilizing visual materials in non-formal educational settings. Teacher’s World: Journal of Education and Research, 49 (2),37-51

Inventory Management System

For organizations that handle transactions involving consumer goods, an inventory management system is critical for quality control. A huge retail store could run out of supply of a critical item if inventory is not properly managed. When it’s time to reorder, an effective inventory management system will notify the retailer. This inventory management system is also useful for tracking huge shipments automatically. Counting each pair of stocks by hand will almost certainly result in a mistake. The risk of human error can be reduced by using an automated inventory management system. An Inventory Management System also aids in the tracking of retail product theft, providing useful information regarding store revenues and the need for theft-prevention devices. Scanning a barcode on the item or a barcode scanner is how Automated Inventory Management Systems function. The central computer system then keeps track of this data. The purchase order can also include a list of items that need to be pulled for packaging and shipping. In this situation, the Inventory Management System can perform a range of tasks. It can assist a warehouse worker in locating things on an order list, encoding shipment information such as tracking numbers and delivery addresses and removing purchased items from the inventory tally to maintain a correct count of in-stock items. All of this information works together to give firms real-time inventory tracking data. The simple search in a database makes it easy to find and look at inventory information in real-time.The inventory management system project abstract tells the overall function of the software. It consists of the reason why the project was proposed and the solutions made to answer the needs of the targeted users. To enlighten you with this, here’s the Inventory Management System Project Abstract

Null cross-modal effects of olfactory training on visual, auditory or olfactory working memory in 6- to 9-year-old children.

Systematic exposure to odours (olfactory training, OT) is a method of smell loss treatment. Due to olfactory system projections to prefrontal brain areas, OT has been hypothesized to enhance cognitive functions, but its effects have been studied predominantly in adults. This study tested OT effects on working memory (WM), i.e., the ability to store and manipulate information for a short time, in healthy children aged 6-9 years. We expected OT to improve olfactory WM and establish cross-modal transfer to visual and auditory WM. Participants performed 12 weeks of bi-daily OT with either 4 odours (lemon, eucalyptus, rose, cloves; OT group) or odourless propylene glycol (placebo group). Pre- and post-training, participants' WM was measured utilizing odours (olfactory WM) or pictures (visual WM) and a word-span task (auditory WM). 84 children (40 girls) completed the study. The analyses revealed no changes in the WM performance following OT. The olfactory WM task was the most difficult for children, highlighting the need to include olfactory-related tasks in educational programmes to improve children's odour knowledge and memory, just as they learn about sounds and pictures. Further neuroimaging research is needed to fully understand the impact of OT on cognitive functions in children.

Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN) for cross-modal individual analysis of the whole brain

Cross-modal analysis of the same whole brain is an ideal strategy to uncover brain function and dysfunction. However, it remains challenging due to the slow speed and destructiveness of traditional whole-brain optical imaging techniques. Here we develop a new platform, termed Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN), for non-destructive, high-speed, 3D imaging of ex vivo rodent, ferret, and non-human primate brains. Using an optimally designed image acquisition scheme and an accompanying machine-learning algorithm, PATTERN extracts signals of genetically-encoded probes from photobleaching-based temporal modulation and enables reliable visualization of neural projection in the whole central nervous system with 3D isotropic resolution. Without structural and biological perturbation to the sample, PATTERN can be combined with other whole-brain imaging modalities to acquire the whole-brain image with both high resolution and morphological fidelity. Furthermore, cross-modal transcriptome analysis of an individual brain is achieved by PATTERN imaging. Together, PATTERN provides a compatible and versatile strategy for brain-wide cross-modal analysis at the individual level.

Grievance Management System in PHP

The college grievance system project outlined in these abstract aims to streamlined and improve the process through the student can raise concerns and complaint within the academic community. Recognizing the importance of addressing student grievance promptly and fairly. Project seeks to design and implement effective an accessibility system that enhance the overall student experience.

Rolling Mechanism of Launch Vehicle during the Prelaunch Phase in Sea Launch

During the sea launch of a launch vehicle in low sea state, a rolling phenomenon of the launch vehicle has been observed. In rough sea conditions, launch may failure. This study utilizes dimensionality reduction-driven spatial system projection methods and virtual prototype modeling technology to reveal that the launch vehicle’s rolling is caused by differences in the motion paths of the center of mass. Additionally, during the prelaunch stage, the variation in the trajectory of the launch vehicle’s center of mass caused by the rolling and pitching motions of the transportation vessel has a significant impact on the roll motion of the launch vehicle. The motion in other degrees of freedom has minimal influence on the launch vehicle’s rolling. The minimum rocket rolling occurs when the dynamic coefficient of friction of the launchpad–launch vehicle contact is 0.05, and the dynamic coefficient of friction of the adapters and guideways is 0.4. The conclusions provide a theoretical foundation for optimizing the sea launch system and enhancing the reliability of sea launch in rough sea conditions.

Research on Stakeholder Behavior Strategy in Green PPP Project Financing

In the context of green development, while promoting green industry and sustainable development, green PPP faces the challenge of financing difficulties. Based on the evolutionary game theory of bounded rationality and taking government, social capital and financial institutions as the game players, this paper constructs an evolutionary game model for the behavioral decision-making of stakeholders in green PPP project financing. Using MATLAB software, we simulate and analyze the key factors affecting the behavioral strategies of each game player. The results indicate that: (1) The additional income obtained from participation in green PPP projects is a key factor affecting the decision-making of social capital and financial institutions, so it is necessary to improve the reasonable return mechanism of green PPP projects and attach importance to the construction of reputation mechanism; (2) Government subsidies can effectively encourage social capital and financial institutions to participate in green PPP projects, but the amount of subsidies should be within a reasonable range; (3) The government's reward and punishment intensity is a significant factor affecting the decision-making of social capital behavior. To this end, it is imperative for the government to enhance the performance evaluation system for green PPP projects and establish a balanced reward and punishment mechanism. This paper puts forward some suggestions on the decision-making of stakeholders in the financing process of green PPP projects, and provides references for the policy formulation of encouraging social capital and financial institutions to participate in green PPP projects.

Population-specific climate sensitive top height curves and their applications to assisted migration

AbstractGrowth and yield (G&Y) of forest plantations can be significantly impacted by maladaptation resulting from climate change, and assisted migration has been proposed to mitigate these impacts by restoring populations to their historic climates. However, genecology models currently used for guiding assisted migration do not account for impacts of climate change on cumulative growth and assume that responses of forest population to climate do not change with age. Using provenance trial data for interior lodgepole pine (Pinus contorta subsp. latifolia Douglas) and white spruce (Picea glauca (Moench) Voss) in western Canada, we integrated Universal Response Functions, representing the relationship of population performance with their provenance and site climates, into top height curves in a G&Y model (Growth and Yield Projection System, GYPSY) to develop population-specific climate sensitive top height curves for both species. These new models can estimate the impact of climate change on top height of local populations and populations from a range of provenances to help guide assisted migration. Our findings reveal that climate change is expected to have varying effects on forest productivity across the landscape, with some areas projected to experience a slight increase in productivity by the 2050s, while the remainder are projected to face a significant decline in productivity for both species. Adoption of assisted migration, however, with the optimal populations selected was projected to maintain and even improve productivity at the provincial scale. The findings of this study provide a novel approach to incorporating assisted migration approaches into forest management to mitigate the negative impacts of climate change.

Polar-vision1: A Novel Collinearity Equation of Perspective Projection in Polar Coordinate System

Abstract. Progress has been made in the community of photogrammetry and 3d computer vision in addressing the mathematical challenge posed by the collinearity equation. We introduce a new method for establishing the coordinate reference for 2d pixels and 3d landmarks using 'angular coordinates'. The mathematical relationships required for converting 3d landmarks, expressed in angular coordinates, to the camera framework are presented. The landmarks are then projected using perspective projection to obtain 2d pixels represented in angular coordinates. This framework is formally nominated as the 'Polar-vision1', which has been developed and integrated into the commercial software G3D-Cluster. Its application to pinhole camera image processing has demonstrated superior efficiency and admission rates of tie points, as well as reconstruction detail capabilities, compared to OpenMVG, achieving approximately a 1.4× improvement. The project 'Key Technologies and Tool System for Realistic 3D Modeling through Integration of Multi-Source Information in the Space-Air-Ground Domain' was awarded First Prize at the 2023 Surveying Science and Technology Awards, with Polar-vision1 as one of the innovative points.

A Study on the Dynamic Evolution Paths of Social Risks in PPP Projects of Water Environmental Governance—From the Vulnerability Perspective

The Chinese economy is transitioning from high-speed development to high-quality development, and water environmental governance is a key factor promoting economic transformation. Due to low returns and high investment in China’s water environmental governance, the PPP (public–private-partnership) model is often adopted. However, the PPP model has historically faced challenges adapting to local conditions in China, leading to social risks in the PPP projects of water environmental governance. To reduce these risks, this paper takes a vulnerability perspective, employing the system dynamics simulation method to explore the dynamic evolution process of social risks in the PPP projects of water environmental governance. The main results show the following: (1) the external manifestations of social risks during the construction and operation periods vary significantly, exhibiting notable fluctuations; (2) during the construction period, there is a surge in social risks followed by a returns to lower than normal levels, then a gradual upward trend; during the operation period, social risks initially decrease to a lower level before gradually increasing; and (3) city class, relevant legal systems, and resource reserves emerge as critical factors influencing vulnerability and social risks. The higher the city class, the lower the project vulnerability; the soundness of the legal system for PPP projects can effectively reduce vulnerability and social risks; sufficient resource reserves can reduce social risks. Based on the above findings, this paper proposes several suggestions aiming to reduce the vulnerability and social risks in PPP projects, optimize the process of water environmental governance, and further promote the sustainable development of water environmental governance and the high-quality economy of China.

Advances in enhanced geothermal systems: Integrating laboratory, numerical and field insights

An enhanced geothermal system is a designed and engineered thermal reservoir that has been deliberately stimulated to extract economically viable amounts of heat from geothermal resources having no natural permeability. Enhanced geothermal system projects are typically initiated to meet the industrial production standards, usually via techniques such as chemical stimulation, hydraulic fracturing, or thermal processes to enhance the permeability of the reservoir. The main aim of this study is to evaluate the current advancements in enhanced geothermal system through a comprehensive examination of laboratory experiments, numerical simulation, and fieldwork investigations from numerous studies that are insufficient captures and combined by current open literature. This study highlighted the critical importance of precisely developing fracture systems, whether natural or artificially induced, in ensuring the effectiveness of such projects. Notably, hydraulic fracturing techniques have been proven instrumental in enhancing the performance of enhanced geothermal systems. On the contrary, research conducted through numerical simulations has demonstrated consistent findings that it is beneficial to enhance the permeability of low-permeability rock for the efficient use of enhanced geothermal systems. Additionally, this study has highlighted the intricate and expensive nature of designing enhanced geothermal systems due to uncertainties in subsurface conditions especially from projects that are in initial stages of development. This study enables researchers and operators to improve the efficiency and safety of geothermal energy extraction, paving the way for more sustainable enhanced geothermal system projects in the future.