Engineering Methods Research Articles

An Overview of Digital Engineering Methods for Platform Integration of Power and Energy Systems

US Navy ships, and combatant ships in particular, have requirements for integrated systems that are designed and configured for operational efficiency, redundancy, and survivability. Mission systems today and in the future will not always come with their own energy and many may, at times, require extreme pulse power loads. In addition, the migration away from fossil fuels to hybrid systems with energy storage, or the requirements for autonomous platforms, is challenging our ability to design platforms for these systems. Understanding the interdependencies between components, the systems they support, and the energy domains they are member of is a critical ontological design requirement. This paper will address how we applied digital engineering principles and computer science to the design of ontologies that allow for the modeling of complex operational systems riding on the same shipboard energy network. This system network must support varying levels of detail needed during design while at the same time understanding the impacts of that design on ship system operations and their energy loads over time.

Identifying player skill of dota 2 using machine learning pipeline

The esports industry is one of the prominent business sectors in the digital era, particularly, Multiplayer Online Battle Arena (MOBA) games which gain much attention from gamers and streaming audiences. Among such games, Defense of the Ancient 2 or Dota 2 is the record holder for the highest prize esports tournament. Therefore, various companies and investors start their esports teams to compete in the Dota 2 tournaments, the Internationals. To success in the competition, player recruitment is a crucial process as it usually takes considerable effort to find a skillful player. Watching the game replay to evaluate the player’s skill is one of the approaches. However, it can be too exhaustive, also some player’s ranking, which represent the player’s skill, are often not available. In this paper, we propose an effective machine learning pipeline to evaluate the player’s skill. Our designed pipeline includes data collection, feature engineering, and machine learning modeling. We show the data collection process using open-source API. An effective method for feature engineering is proposed. Features, e.g., end-game, or tactical decision related statistics, are incorporated along with the resource in the game distribution, harassment tactic, or spatiotemporal features, in order to provide effective models. Subsequently, we apply major machine learning models based on a single game data, i.e., logistic regression and random forest, to the processed data. The most effective model can achieve up to 0.7091 precision, 0.5850 recall, 0.6411 F1-score, and 0.8123 ROC AUC score.

An explainable & prescriptive solution for space-based energy consumption optimization using BIM data & genetic algorithm

Creating energy-efficient buildings is a multifaceted challenge that involves carefully considering architectural, mechanical, and electrical parameters. With the increasing emphasis on low-energy building mandates and sustainable construction practices, integrating energy performance simulation into the design process has become imperative. However, existing methods often struggle to handle the vast amount of design information and to explore optimal alternatives effectively. While recent approaches such as Building Information Models (BIM) and data-driven solutions show promise for energy analysis, they frequently lack transparency and robust design optimization capabilities, limiting their applicability in critical contexts within the Architecture, Engineering, Construction, and Operation (AECO) industry. In response to these challenges, this research proposes a novel prescriptive model aimed at addressing these limitations. The proposed methodology integrates building energy simulation with optimization techniques, utilizing BIM data and a Genetic Algorithm (GA). The Genetic algorithm provides some optimized solutions, including different alternatives of geometry, material, electrical, and mechanical elements to help engineering for data-driven decision-making. This integration aims to develop a model that is both prescriptive and explainable for indoor building design. Leveraging the value engineering method, the proposed approach seeks to strike a balance between energy consumption, functionality, and cost. By doing so, it aims to enhance energy efficiency while providing tangible design optimization solutions.

Analytical detection of “ Smart Stock Trading System” utilizing AI-model

In the realm of finance, stock trading stands out as one of the most significant activities. Predicting stock prices involves analyzing available market data to forecast the future value of a particular stock or share. In our research, we developed a machine learning model along with LSTM (Long Short-Term Memory) to predict stock prices. Our model follows the 70:30 principle, allowing the model to improve its accuracy over time. We collected a decade's worth of data from Yahoo Finance and employed customized feature engineering and deep learning techniques to analyze the stock market trends. Our approach has shown promising accuracy in predicting stock market trends. By carefully optimizing prediction term lengths, feature engineering methods, and data preprocessing techniques, our work contributes to advancing research in both financial analysis and technical modeling within the stock market domain. Keywords— LSTM, Machine learning, RNN, Data Prediction, finance, linear regression.

Effect of over-expansion in a cycloidal rotary engine

An over-expanded (Atkinson cycle) reciprocating internal combustion engine is a crucial component of hybrid and range-extended electric vehicles. The realization of the over-expansion cycle with high efficiency in novel power devices with a compact, simple design, such as cycloidal rotary engines, is a promising alternative. The cycloidal rotary engine is an internal combustion engine that operates four strokes without a reciprocating mechanism and valve train. The over-expansion cycle is implemented in the cycloidal rotary engine by asymmetrical intake and exhaust port arrangements, resulting in open and closure timings. This study aimed to establish inherent characteristics of the over-expansion cycle in gasoline-fueled rotary engines with spark ignition. A numerical simulation of the gas exchange and combustion process in a wide range of over-expansion ratios was conducted. It was concluded that the over-expansion cycle is realized without typical piston engine methods such as variable valve timing and multilink mechanism. The thermal conversion efficiency is a peak function of the over-expansion ratio. In the over-expansion range of 1.1–1.2, the thermal conversion efficiency of the cycloidal rotary engine increased up to 32.7–34.5%. The benefits of fuel economy and carbon oxide emission can also be achieved within the specified range of over-expansion ratio.

Analysis of the Accuracy of CAD Modeling in Engineering and Medical Industries Based on Measurement Data Using Reverse Engineering Methods

The reverse engineering (RE) process is often necessary in today’s engineering and medical industries. Expertise in measurement technology, data processing, and CAD modeling is required to ensure accurate reconstruction of an object’s geometry. However, errors are generated at every stage of geometric reconstruction, affecting the dimensional and geometric accuracy of the final 3D-CAD model. In this article, the geometry of reconstructed models was measured using contact and optical methods. The measurement data representing 2D profiles, 3D point clouds, and 2D images acquired in the reconstruction process were saved to a stereolithography (STL) model. The reconstructed models were then subjected to a CAD modeling process, and the accuracy of the parametric modeling was evaluated by comparing the 3D-CAD model to the 3D-STL model. Based on the results, the model used for clamping and positioning parts to perform the machining process and the connecting rod provided the most accurate mapping errors. These models represented deviations within ±0.02 mm and ±0.05 mm. The accuracy of CAD modeling for the turbine blade model and the pelvis part was comparable, presenting deviations within ±0.1 mm. However, the helical gear and the femur models showed the highest deviations of about ±0.2 mm. The procedures presented in the article specify the methods and resolution of the measurement systems and suggest CAD modeling strategies to minimize reconstruction errors. These results can be used as a starting point for further tests to optimize CAD modeling procedures based on the obtained measurement data.

A Five-Step Framework for Creating Forests for the Future

Changing environmental conditions, disturbances, and escalating demands for forest ecosystem services require foresters to restore present forestlands with new forest generations that will exhibit ecological integrity, diversity, high adaptive capacity, and the ability to provide essential ecosystem services. Establishing such forests requires careful consideration of the forest landscape and site dynamics. In pursuit of these requirements, we developed a novel framework that enables the restoration of forest sites and promotes the desired features of the forest complex at the same time. This framework was designed with the methods of system engineering and was organized in the same way as the forest planning process. It was tested in the habitat type of Illyrian Fagus sylvatica forests belonging to the Natura 2000 network. The environmental, vegetation, and site conditions were investigated via field inspections, available forest management plans, and simple GIS analyses. Additionally, we established a seminatural stand composed of European beech, sessile oak, sycamore maple, silver fir, and some wild fruit tree species. The survival of planted species was assessed using census and simple random sampling, the performance of provenances by the Student’s test, while microhabitat factors were explored by a one-way ANOVA. The survival rate of key species was estimated to be 55.6%, while that of fruit species was estimated to be 94.5%. Our framework demonstrated satisfactory performance and contained sufficient benchmarks to facilitate consistent decision-making. In the discussion, we elucidate the framework’s primary features and attributes of the mixed stand, where we also expose some open issues to be addressed in the future.

Comparing Methods to Genetically Engineer Bacteriophage and Increase Host Range.

Antibacterial resistance is an emerging problem in military medicine. Disruptions to the health care systems in war-torn countries that result from ongoing conflict can potentially exacerbate this problem and increase the risk to U.S. forces in the deployed environment. Therefore, novel therapies are needed to mitigate the impact of these potentially devastating infections on military operations. Bacteriophages are viruses that infect and kill bacteria. They can be delivered as therapeutic agents and offer a promising alternative to traditional antibiotic chemotherapy. There are several potential benefits to their use, including high specificity and comparative ease of use in the field setting. However, the process of engineering phages for military medical applications can be a laborious and time-consuming endeavor. This review examines available techniques and compares their efficacy. This review evaluates the scientific literature on the development and application of four methods of bacteriophage genome engineering and their consideration in the context of military applications. Preffered Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed for a systematic review of available literature that met criteria for analysis and inclusion. The research completed for this review article originated from the United States Military Academy's library "Scout" search engine, which compiles results from 254 available databases (including PubMed, Google Scholar, and SciFinder). Particular attention was focused on identifying useful mechanistic insight into the nature of the engineering technique, the ease of use, and the applicability of the technique to countering the problem of antimicrobial resistance in the military setting. A total of 52 studies were identified that met inclusion criteria following PRISMA guidelines. The bioengineering techniques analyzed included homologous recombination (12 articles), in vivo recombineering (9 articles), bacteriophage recombineering of electroporated DNA (7 articles), and the CRISPR-Cas system (10 articles). Rates of success and fidelity varied across each platform, and comparative benefits and drawbacks are considered. Each of the phage engineering techniques addressed herein varies in amount of effort and overall success rate. CRISPR-Cas-facilitated modification of phage genomes presents a highly efficient method that does not require a lengthy purification and screening process. It therefore appears to be the method best suited for military medical applications.

Visible-hidden hybrid automatic feature engineering via multi-agent reinforcement learning

Feature engineering is one of the most important and time-consuming steps of machine learning algorithms. In recent years, automatic feature engineering (AFE) methods have received a lot of attention due to their low cost and scalability. However, the existing AFE methods do not take into account the interactions of features in the evolution process and cannot achieve effective feature selection, which weakens the performance of these methods. To tackle the above issues, a novel visible-hidden hybrid automatic feature engineering (VHAFE) method is proposed in this work. Specifically, a visible-hidden hybrid feature transformation graph (VHFTG) is devised to represent both various kinds of feature transformation functions and the feature selection process. Afterward, a multi-pointer state identification method is proposed, which enables the interactions among derived features and the efficient utilization of historically derived features. Furthermore, the multi-agent reinforcement learning algorithm is introduced to optimize the evolution process of VHFTG, where an input variable selection network is devised as the auxiliary policy network to avoid the generation of excessive noise features. Additionally, the VHAFE achieves the state-of-the-art results on a total of 19 public datasets and 1 dataset collected from the actual industrial operation process of gas turbines, which demonstrates the effectiveness of the proposed method.

High-performance tin perovskite transistors through formate pseudohalide engineering

The lack of high-performance p-type semiconducting materials hinders the integration of complementary metal-oxide semiconductors with well-established n-type metal-oxide counterparts. Although tin halide perovskites are promising p-type material candidates, their practical implementation is hindered by excessive hole concentrations and difficulties in precisely controlling crystallization, which leads to poor device performance and yield. In this paper, we propose a formate pseudohalide engineering method to overcome these issues and demonstrate high-performance tin perovskite thin-film transistors (TFTs). The incorporation of formate anion greatly suppresses the vacancy defects at the surfaces of the perovskite films with an increase in crystallinity and grain size. This reduces the hole concentration and eliminates the dependence on the addition of excessive tin fluoride for hole suppression. Hence, high-performance TFTs with a high average field-effect hole mobility of 57.34 cm2 V−1 s−1 and on/off current ratios surpassing 108 can be achieved, approaching p-channel low-temperature polysilicon devices.

A gradient phage-assisted continuous evolution method for screening suppressor tRNAs in Escherichia coli

Suppressor tRNAs, notable for their capability of reading through the stop codon while maintaining normal peptide synthesis, are promising in treating diseases caused by premature termination codons (PTC). However, the lack of effective engineering methods for suppressor tRNAs has curtailed their application potential. Here, we introduce a directed evolution technology that employs phage-assisted continuous evolution (PACE), combined with gradient biosensors featuring various PTCs in the M13 gene III. Utilizing this novel methodology, we have successfully evolved tRNATrp (UGG) reading through the UGA stop codon in Escherichia coli. Massively parallel sequencing revealed that these mutations predominantly occurred in the anticodon loop. Finally, two suppressor tRNATrp (UGA) mutants exhibited over fivefold increases in readthrough efficiency.

CHALLENGES AND OPPORTUNITIES TO DESIGN FUTURE CROPS: GATEWAY TO SUSTAINABLE AGRICULTURE IN 21ST CENTURY

The global food production system is facing numerous challenges due to factors such as population growth, climate change, limited resources, and environmental preservation. To address these challenges, various strategies can be employed to develop future crops that are more productive, nutritious, and resilient. One strategy is to improve the yield potential of existing crops by developing new high-yielding cultivars. This can be achieved through the development of new varieties that can produce more grain under optimal conditions. Additionally, improving the nutritional quality of crops is important to address nutrient deficiencies. Synthetic biology and metabolic engineering methods can be used to develop crops with enhanced nutritional value. Efficient utilization of agricultural resources is another important aspect of crop improvement. This includes developing crops that use water and nutrients more efficiently, reducing the need for irrigation and fertilizers, and minimizing environmental impacts. Increasing the resistance of crops to pests, diseases, and extreme weather events can also help reduce the use of pesticides and minimize crop losses. The domestication of wild or semi-wild plants through genetic manipulation offers new opportunities for crop design. These plants may have high nutritional value, stress tolerance, and specialized metabolites that can be incorporated into cultivated crops. Similarly, the domestication of orphan or neglected plants can contribute to crop improvement by incorporating unique traits. Genetic improvement through the transfer of genes from wild relatives or other species can also enhance crop productivity. Advancements in genomics and genetic technologies can aid in the identification and transfer of beneficial alleles. Agronomic improvements, such as maximizing the effectiveness of crop protection agents and fertilizers while minimizing their environmental impact, can also contribute to crop performance. The emerging field of synthetic biology offers opportunities for developing novel biological devices and systems that can further enhance crop productivity and resilience. Overall, these strategies can help address the challenges faced by the global food production system.

Encapsulation structure and in-situ embedding test and model study of a new type of road piezoelectric energy collector

In recent years, research on road piezoelectric energy harvesters (RPEH) has made great progress in the field of road vibration energy harvesting. However, the research on the packaging structure and embedding method of RPEH is not comprehensive. In this paper, a new type of transducer unit structure is developed, which can improve the electrical energy output compared with the drum piezoelectric transducer, and its waterproof performance of the transducer unit is tested under different water depth and duration. Then, a new RPEH package structure is made, and the output performance is compared with the three commonly used package structures in the current research, and the field construction of RPEH with different embedding methods is carried out on the actual road to evaluate the electrical energy output capacity of RPEH under different embedding methods, and the best construction method of RPEH is summarized through durability test. Finally, the three-dimensional simulation model of RPEH with different construction methods is established, and the stress and voltage are analyzed by finite element method to verify the best embedding method. The test results show that the piezoelectric output efficiency of the new transducer unit is increased by 38.9 %, and it still has good electrical energy output after 24 h immersion at a depth of 1.5 m, and its waterproof level reaches IPX8. Under larger excitation frequency and load, the indoor output of RPEH in the new package structure has better output performance in indoor test. The bolt-spring package is used to apply pre-pressure to RPEH, and the output efficiency of RPEH is improved. When the excitation conditions are 10 kN, 10 Hz, the output power is increased by 11.1 %, 127.3 % and 247.4 % compared with the other three package structures. The maximum power of RPEH is 3.41 W by placing concrete on the bottom surface of RPEH sponge washer and using asphalt as the pavement layer to ensure the durability of piezoelectric pavement. The finite element analysis illustrates the strain and voltage variation of piezoelectric pavement with different embedment modes, and the simulation results are consistent with the test results. The research results provide an important basis for the design of RPEH packaging structure and embedding method in road piezoelectric engineering.

Information Theory, Living Systems, and Communication Engineering.

Mainstream research on information theory within the field of living systems involves the application of analytical tools to understand a broad range of life processes. This paper is dedicated to an opposite problem: it explores the information theory and communication engineering methods that have counterparts in the data transmission process by way of DNA structures and neural fibers. Considering the requirements of modern multimedia, transmission methods chosen by nature may be different, suboptimal, or even far from optimal. However, nature is known for rational resource usage, so its methods have a significant advantage: they are proven to be sustainable. Perhaps understanding the engineering aspects of methods of nature can inspire a design of alternative green, stable, and low-cost transmission.

Implementation of Label Cutting Workstations Improvement in The Jago Jaya Shuttlecock Industry to Increase Productivity Based on Ergonomic Aspects

Jago Jaya Shuttlecock Industry is an MSME in Jagalan, Surakarta, that produces shuttlecocks. Based on these conditions, a study was conducted in 2020 by Sherlinta Kaban, which produced a label cutting tool tested on a label cutting workstation. However, in the trial, there are several obstacles found in using the label cutting tool, so follow-up study to analyze and improve the label cutting tools in previous studies to produce a new design that can be re-implemented. Ergonomics aspects used in this study are analysis of work posture using REBA, measurement of standard time with Westinghouse adjustments, the study of left and right-hand map movements, and tool redesign using the Reverse Engineering method. The improvements include implementing a new label cutting tool that can improve the operator's work posture, reduce standard time, increase the number of standard outputs, and improve operator hand movements to increase productivity at label cutting work stations.

DIN 18009-2 – a New German Standard on Evacuation Simulation

After more than eight years of intensive work, the second part of the German DIN 18009 standard on "Simulation of evacuation and personal safety" was published in August 2022. The DIN 18009 series offers a guideline for fire protection engineering for Germany. The first part "Principles and application rules" was published in 2016, with further parts describing standards for smoke simulation and safety concepts to follow. This marks a milestone in the application of simulation models in the safety context for Germany. This article discusses the advantages and disadvantages of prescriptive guidelines and performance-based engineering methods in the context of building evacuation. Furthermore, aspects of the application of the DIN 18009-2 are highlighted, and what challenges are still to be tackled and how. This includes in particular the choice and definition of scenarios and performance criteria.

Nanostructured Biomaterials in 3D Tumor Tissue Engineering Scaffolds: Regenerative Medicine and Immunotherapies.

The evaluation of nanostructured biomaterials and medicines is associated with 2D cultures that provide insight into biological mechanisms at the molecular level, while critical aspects of the tumor microenvironment (TME) are provided by the study of animal xenograft models. More realistic models that can histologically reproduce human tumors are provided by tissue engineering methods of co-culturing cells of varied phenotypes to provide 3D tumor spheroids that recapitulate the dynamic TME in 3D matrices. The novel approaches of creating 3D tumor models are combined with tumor tissue engineering (TTE) scaffolds including hydrogels, bioprinted materials, decellularized tissues, fibrous and nanostructured matrices. This review focuses on the use of nanostructured materials in cancer therapy and regeneration, and the development of realistic models for studying TME molecular and immune characteristics. Tissue regeneration is an important aspect of TTE scaffolds used for restoring the normal function of the tissues, while providing cancer treatment. Thus, this article reports recent advancements in the development of 3D TTE models for antitumor drug screening, studying tumor metastasis, and tissue regeneration. Also, this review identifies the significant opportunities of using 3D TTE scaffolds in the evaluation of the immunological mechanisms and processes involved in the application of immunotherapies.

Exploring the antimicrobial and anticancer activities of zinc doped nanohydroxyapatite prepared via ultrasonic-assisted method for bone tissue engineering

Exploring the antimicrobial and anticancer activities of zinc doped nanohydroxyapatite prepared via ultrasonic-assisted method for bone tissue engineering

Autonomous Stabilization of Fock States in an Oscillator against Multiphoton Losses.

Fock states with a well-defined number of photons in an oscillator have shown a wide range of applications in quantum information science. Nonetheless, their usefulness has been marred by single and multiphoton losses due to unavoidable environment-induced dissipation. Though several dissipation engineering methods have been developed to counteract the leading single-photon-loss error, averting multiple-photon losses remains elusive. Here, we experimentally demonstrate a dissipation engineering method that autonomously stabilizes multiphoton Fock states against losses of multiple photons using a cascaded selective photon-addition operation in a superconducting quantum circuit. Through measuring the photon-number populations and Wigner tomography of the oscillator states, we observe a prolonged preservation of nonclassical Wigner negativities for the stabilized Fock states |N⟩ with N=1, 2, 3 for a duration of about 10ms. Furthermore, the dissipation engineering method demonstrated here also facilitates the implementation of a nonunitary operation for resetting a binomially encoded logical qubit. These results highlight potential applications in error-correctable quantum information processing against multiple-photon-loss errors.

Development of approaches for genome editing of pea plants using CRISPR/Cas9 prime-editing technique

Mitogen-activated protein kinases (MAPKs) play an important role as intracellular regulators of signal pathways in plants. Some MAPKs have been shown to be induced in the roots of legume plants during symbiosis with nitrogen-fixing rhizobial bacteria. One of such signal regulators, MAPK6, was shown to be involved in the development of symbiosis between Pisum sativum L. pea plants and rhizobia. Using genetic engineering approaches, we overexpressed the MAPK6 gene in transgenic roots, that resulted in an increase in the number of nodules and the biomass of pea plants. New approaches for genome editing of pea plants have been designed using the CRISPR/Cas9 prime-editing technique, when the MAPK6 gene was used as a target. We have analyzed the transgenic roots of pea transformants and observed the presence of the gene encoding Cas9 the pegRNA sequence in the genome of transformants. Therefore, the possibility of using genetic engineering methods to obtain plants with increased efficiency of symbiosis will be investigated in future experiments.