Actual Planning Research Articles

Machine learning-based decision support system for orthognathic diagnosis and treatment planning

BackgroundDento-maxillofacial deformities are common problems. Orthodontic–orthognathic surgery is the primary treatment but accurate diagnosis and careful surgical planning are essential for optimum outcomes. This study aimed to establish and verify a machine learning–based decision support system for treatment of dento-maxillofacial malformations.MethodsPatients (n = 574) with dento-maxillofacial deformities undergoing spiral CT during January 2015 to August 2020 were enrolled to train diagnostic models based on five different machine learning algorithms; the diagnostic performances were compared with expert diagnoses. Accuracy, sensitivity, specificity, and area under the curve (AUC) were calculated. The adaptive artificial bee colony algorithm was employed to formulate the orthognathic surgical plan, and subsequently evaluated by maxillofacial surgeons in a cohort of 50 patients. The objective evaluation included the difference in bone position between the artificial intelligence (AI) generated and actual surgical plans for the patient, along with discrepancies in postoperative cephalometric analysis outcomes.ResultsThe binary relevance extreme gradient boosting model performed best, with diagnostic success rates > 90% for six different kinds of dento-maxillofacial deformities; the exception was maxillary overdevelopment (89.27%). AUC was > 0.88 for all diagnostic types. Median score for the surgical plans was 9, and was improved after human–computer interaction. There was no statistically significant difference between the actual and AI- groups.ConclusionsMachine learning algorithms are effective for diagnosis and surgical planning of dento-maxillofacial deformities and help improve diagnostic efficiency, especially in lower medical centers.

Implementing A resistance-relief approach into evaluating urban disaster management capacity: A case study of Xuzhou

In the field of disaster management, urban planning is a crucial tool for reducing the vulnerability of areas prone to natural disasters. Assessing the disaster management efficacy of urban planning is essential. However, the theoretical evaluation frameworks and precise assessment methods currently available are quite limited. Therefore, this study developed a new Resistance-Relief (2Rs) approach to evaluate disaster management capabilities in different regions. Based on the “2Rs” evaluation framework, an indicator system was developed to assess disaster management capabilities at the level of urban planning and construction. On this basis, a directed weighted graph model was established to comprehensively evaluate a city's disaster resistance and disaster relief capabilities, addressing the accuracy and comprehensiveness issues commonly found in single-dimensional evaluations. Furthermore, an indicator sensitivity analysis method based on the cloud model was proposed to analyze the sensitivity of evaluation indicators and the robustness of evaluation results. Using actual urban planning and construction data, this method was applied to assess seven disaster management zones in Xuzhou City, China. The results revealed inadequacies in the city's disaster preparedness and mitigation construction, as well as key factors affecting Xuzhou's disaster management capabilities. This new method contributes to further improvements in both disaster risk management and urban disaster prevention and mitigation planning.

Building an Information Modeling-Based System for Automatically Generating the Assembly Sequence of Precast Concrete Components Using a Genetic Algorithm

Facing a significant decrease in economic working processes, Off-Site Construction (OSC) methods have been frequently adopted in response to challenges such as declining productivity and labor shortages in the construction industry. Currently, in most OSC applications, the assembly phase is traditionally managed based on the personal experience and judgment of the site managers. This approach can lead to inaccuracies or omissions, particularly when dealing with a large amount of information on large, complex construction sites. Additionally, there are limitations in exploring more efficient and productive alternatives for rapidly adapting to changing on-site conditions. Given that the assembly phase significantly affects the OSC productivity, a systematic management approach is crucial for expanding OSC methods. Some initial studies used computer algorithms to determine the optimal assembly sequences. However, these studies often focused on geometrical characteristics, such as component weight or spatial occupancy, neglecting crucial factors in actual site planning, such as the work radius and component installation status. Moreover, these studies tended to prioritize the generation of initial assembly sequences rather than providing alternatives for adapting to evolving on-site conditions. In response to these limitations, this study presents a systematic framework utilizing a Building Information Modeling (BIM)–Genetic Algorithm (GA) approach to generate Precast Concrete (PC) component installation sequences. The developed system employs Genetic Algorithms to objectively explore diverse assembly plans, emphasizing the flexibility of accommodating evolving on-site conditions. Real on-site scenarios were simulated using this framework to explore multiple assembly plan alternatives and validate their applicability. Comprehensive interviews were conducted to validate the research and confirm the system’s potential contributions, especially at just-in-time-focused PC sites. Acknowledging a broader range of variables such as equipment and manpower, this study anticipates fostering more systematic on-site management within the context of a digitized construction environment. The proposed algorithm contributes to improving both productivity and sustainability of the construction industry by optimizing the management process of the off-site construction projects.

Fostering Literacy Culture at SD Negeri Tanah Merah: Success of Educational Seminar and Its Positive Impact on the Community

This community service aims to increase awareness and implementation of literacy culture at Tanah Merah State Elementary School, Aceh Tamiang. By holding a one-day seminar on January 10 2024, this program brings together participants from various parties, including teachers, students and parents, in a united effort to create awareness of the importance of literacy as the main foundation of education. Keynote lectures and interactive discussions in seminars dive deeper into the concept of literacy, which includes not only reading and writing skills but also critical thinking skills, interpretation, and thorough knowledge of various types of texts. This seminar also provides a platform to produce actual action plans, which reflect participants' commitment to integrating literacy culture in everyday life. Evaluation and reflection findings revealed that this activity was successful in providing positive changes in attitudes and understanding, with awards given at the end of the event as appreciation for the participants' commitment. By expressing the conclusions of this service, this abstract shows the success of the initial steps in improving literacy culture at Tanah Merah State Elementary School. This aims to ensure that the enthusiasm and understanding that emerges from this activity can become a catalyst for sustainable change at the school level and in the local community.

Sustainable synergistic development of marine economic degree growth and marine art industry

Marine and port economy estimation is conducive to the understanding of the development law of marine economy degree. This study proposes a neural-learning network estimation model of the marine economy degree based on a priori architectural knowledge and adopts time-combined class array columns and multivariate modeling methods to estimate the indicators reflecting the development level of the marine economy degree in the ZJP region. The study adopts the PK_NN multivariate modeling method, taking cargo transportation volume, cargo turnover, cargo carrying value of ports near the sea, foreign trade throughput, port container throughput, and port container throughput as multivariate model inputs, and compared with the other modeling methods, the model of the time combination class array columns of type GM_11, which has a better comprehensive performance. Finally, the PK_NN time-combined class array column model is used to estimate the development level of the marine economy in the ZJP region near the seaport from 2011 to 2020, and the results show that the estimated value of the marine economy in the ZJP region is close to the actual planning value of the ZJP region. The algorithm was applied to estimate the economic degree curves of the five near-seaport areas of ABCDE under different harbor head construction art modes, and the results showed that the relative value error of the estimation was controlled between 4% and 10%, and the fluctuation ranges of each month's specific growth value area estimation were comparable. This proves the effectiveness and accuracy of the a priori marine neural-learning-based network algorithm in this paper.

Stress and hope distinguish individuals with suicidal plan from suicide ideators among Chinese college students.

Suicide among college students is a significant public health concern in China. While suicidal ideation serves as a crucial predictor of subsequent suicidal plans and behaviors, it is important to recognize that most instances of suicidal ideation may only be fleeting thoughts that do not progress to an actual plan. Therefore, it is imperative to identify the factors associated with the transition from suicidal ideation to a concrete plan. Consequently, this study aims to investigate whether certain frequently cited factors can differentiate individuals who have formulated a specific suicidal plan from those who have experienced suicidal thoughts without planning, based on data obtained through a cross-sectional survey. This survey was conducted as part of routine mental health assessments among second-year college students in October 2023. Data from a total of 4,858 second-year college students were utilized for the final analyses. Two survey questions were employed to identify past-year suicidal ideation and past-year suicidal plan. All participants were required to complete various assessments, including the Chinese version of Depression Anxiety Stress Scale 21 items (DASS-21), the Chinese version of Gratitude Questionnaire-six items (GQ-6), the Chinese version of Meaning in Life Questionnaire (MLQ), and the Chinese version of State Hope Scale (SHS). Among 4,858 participants, a total of 134 individuals (2.8%) were confirmed to have experienced past-year suicidal ideation. Out of these, 53 (1.1% overall) reported having a past-year suicidal plan, accounting for approximately 39.6% of those with suicidal ideation. Logistic regression analyses revealed that while most potential variables differentiated between students with and without suicidal ideation, only two factors stood out in distinguishing individuals with a suicidal plan from those who had not made such plans despite experiencing suicidal thoughts-presence of stress (OR=2.49, 95% CI: 1.04-5.96) and lower scores of hope agency (OR=0.84, 95% CI: 0.72-0.98). These findings suggest that the stress may contribute to susceptibility for transitioning from mere thoughts to actual planning regarding suicide; conversely, hope agency appears to offer protection against this transition process. Therefore, we advocate for targeted interventions aimed at fostering hope among individuals who have encountered adverse and stressful life events.

STUDY ON THE TROPICAL-STORM-GENERATED WAVE FIELD ON THE SEA AREA AROUND LY SON ISLAND

Ly Son is a frontline island of our country that is often affected by adverse weather conditions such as monsoons or tropical storms. Studying the hydraulic parameters of tropical storms, including the storm's wave field, to determine extreme conditions plays an important role in forecasting, planning and construction of hydraulic works. The author uses the two-dimensional wave propagation model MIKE 21 SW to simulate the wave field of Molave storm 2020 in Ly Son sea. The results show a good agreement between the values obtained from the model and the actual measurements at Ly Son station. Based on the results obtained, the author proposes a method to simulate storm wave fields that is relatively accurate and effective. In particular, current standards based on wind speed and wind fetch still have many limitations. This is valuable in the actual design and planning of hydraulic works.

Smartphone-based augmented reality patient education in radiation oncology

We built an augmented reality (AR) patient education application for portable iOS and Android devices that allows patients to view a virtual simulation of themselves receiving radiation treatment. We created software that reads data from the clinical treatment planning system and renders the patient’s actual radiotherapy plan in AR on a tablet or smartphone. The patient's CT simulation data are converted into a 3D translucent virtual human shown being treated with visible radiation beams from a virtual linear accelerator. We conducted a patient study to determine if showing patients this AR simulation improves patient understanding of radiotherapy and/or reduces anxiety about treatment. A total of 75 patients completed this study. The most common plans were 3D breast tangents and intensity modulated radiotherapy lung plans. Patients were administered questionnaires both before and after their AR viewing experience. After their AR viewing, 95% of patients indicated that they had a better understanding of how radiotherapy will be used to treat their cancer. Of the 35 patients who expressed anxiety about radiotherapy beforehand, 21 (60%) indicated that they had decreased anxiety after the AR session. In our single-arm prospective patient study, we found that this simplified low-cost tablet-based personalized AR simulation can be a helpful educational tool for cancer patients undergoing radiotherapy.

Principals’ Management of Co-curricular Activities as Determinant of Students’ Completion Rates in Public Technical Training Institutions in Kiambu County, Kenya

Purpose: Principals play an important role in the management of co-curricular activities such as planning. However, in Kiambu County, students’ completion rates in technical training institutions are low. This study intended to assess principals’ management of co-curricular activities as determinant of students’ completion rates in public technical training institutions in Kiambu County, Kenya.
 Methodology: The study adopted mixed methodology and concurrent triangulation research design. Qualitative data were analyzed thematically along the objectives and presented in narrative forms. Quantitative data were analyzed using descriptive statistics such as frequencies and percentages and inferentially using Pearson’s Product Moment Correlation Analysis with the help of Statistical Packages for Social Sciences and presented by using tables.
 Findings: The study established that, dropout rates among students in public technical training institutions have been high which has led to fluctuating students’ completion rates. The study further established that principals play a key role in the management of co-curricular activities and how such activities influence students’ completion rates in public technical training institutions. However, the study revealed that most principals are rarely involved in the actual planning of CCAs but appreciate the value of such activities in the wholistic growth and development of students.
 Unique Contribution to Theory, Practice and Policy: The study recommends that, as a practice, principals should continue allocating more resources for improving infrastructure for co-curricular activities. As a policy, the Ministry of Education should formulate a policy enabling colleges to partner with other statehooders to provide resources and better the quality of facilities meant for CCAs in technical training institutions.

Research on the formula series with green energy resources drive system

Formula E is a kind of racing that combines green energy use with high-speed racing. From the organization's methods and the technological achievements of recent years, it shows the potential for zero emissions of carbon dioxide. The situation now is optimal and with a clear future (actual plan published by FIA), it shows lots of events still need to improve to achieve the goal. The essay wants to achieve a balance between zero emissions and the observability of racing. So first, the essay focuses on the Formula E, its plan, and its GEN-3 racing cars data. The essay also collects the models of the newly developed hydrogen racing car and nuclear-power racing car. Using this data, the essay concludes that it is better to only focus on Formula E recently, but there is still a larger potential for other driving systems.

Multiobjective Optimization for Vehicle Routing Optimization Problem in Low-Carbon Intelligent Transportation

The work aims to reduce the energy consumption and carbon emissions generated during the urban logistics transportation and distribution and make the actual path planning flexible. Based on Vehicle Routing Problem (VRP), the routing problem of distribution vehicles is optimized under satisfying customers’ cargo demand and time requirements. Because Non-dominated Sorting Genetic Algorithm (NSGA-II) reduces the complexity of non-inferior sorting genetic algorithm and is characterized by fast running speed and good convergence, it is deeply improved. NSGA-II algorithm based on Multifactorial Evolutionary Algorithm (MFEA) (M-NSGA-II) is proposed. In terms of the solution of the stability of the optimal values of four target functions, including distribution cost, customer satisfaction, fuel conservation, and carbon emission, the lowest distribution costs of M-NSGA-II algorithm in ten experiments were all lower than those of other three standard algorithms. The solution duration of M-NSGA-II algorithm was 85.2s and the corresponding average frontier value amounted to 20. The multi-objective path optimization model designed is of great value for reducing carbon emissions under satisfying customers’ cargo demand and time requirements.

Landscape-Scale Long-Term Drought Prevalence Mapping for Small Municipalities Adaptation, the Czech Republic Case Study

Drought is a phenomenon that is strengthening with the progress of climate change. Many fields of human activities such as agriculture, forestry, ecology, economy, water supply, or energy production are affected. Municipalities are one of the most important actors, because final adaptation often takes place at this level. However, planning measures is challenging for small municipalities, with adaptation capacity being lower than in big cities. A model working with data from the Global Change research Institute CzechGlobe and the Czech national drought monitor Intersucho allows for information to be obtained at the landscape scale about drought, and their utilization for small municipalities is introduced. In addition to detailed maps for the years 1991–2014, the model enables long-term prediction of drought prevalence for the years 2021–2040 and 2041–2060. GIS-integrated Random Forest regression and twelve climate, topography, and land use/land cover variables were involved in the model construction. The tuned model could explain 70% of reference data variability, and was used for drought prevalence mapping in 20 m spatial detail. Utilisation of overlay and visualisation tools and consultation of actual spatial planning maps helped create maps for spatial decision-making support in precautionary measure and landscape management within the municipalities.

General Layout Planning Model of Landscape Ceramic Sculpture Based on NSGA - Ⅱ Algorithm

The current overall layout planning model matrix of landscape ceramic sculpture is generally unidirectional, and the planning efficiency is low, resulting in a decline in the layout optimization ratio of the model. Therefore, the design and verification analysis of landscape ceramic sculpture’s overall layout planning model based on the Nondominated Sorting Genetic Algorithm (NSGA - II) algorithm is proposed. According to the actual planning needs and standards, first set the basic layout points, establish a cross-planning matrix in a multi-level manner, and improve the efficiency of the overall layout planning of the sculpture. The NSGA - II calculation landscape ceramic sculpture layout planning structure is constructed on this basis, and the model design is realized by level conversion. This novel NSGA-II with level conversion performs better layout planning when compared with other conventional models. The final test results show that through three stages of layout optimization processing, compared with the initial planning layout, the optimal layout optimization ratio for the setting of the plaza sculpture can reach more than 60%, indicating that with the help of this method, the layout planning of sculpture has been further improved, the space has been expanded, and has practical application value.

Optimization of Vehicles Routing Problem using GA For AL-Rasheed municipality, Baghdad, Iraq

There are several problems with waste collection, transportation, processing, and disposal, particularly in major cities. The frequency of garbage collection is an important concern for municipal control. If waste is not disposed of properly, environmental problems such as air pollution and groundwater contamination may occur. This problem raises the alarm for the need for specialized solutions for averting potential calamities that might occur throughout the world. Before deploying to actual situations, computer modeling and planning of waste collection are frequently performed to minimize the negative impact solid waste can have on the environment. As a result, choosing the optimal waste collection policy has a large effect on cost savings. The current study's objective is to apply a genetic algorithm to reach the goals, illustrating the process of selecting the optimal route for the vehicle with the lowest time and greatest weight among several paths. The other goal is to create a schedule for the vehicles in order to decrease them. The schedule will minimize vehicle-related costs such as maintenance, gasoline, work staff salaries, and other vehicle-related costs. In the current study, the MATLAB application R2020a is used to apply reliable data of 10 vehicles from the AL-Rasheed Municipality waste collection vehicles after processing it to be acceptable with the GA. After optimizing the time for routes and weights of lifted trash, the majority of the results improved dramatically. The results reveal that the top five vehicles (8, 6, 7, 1, 4) have a great percentage improvement in the number of collection points (133.3%, 100%, 100%, 66.7%, and 50%), respectively.

An Optimal Opportunistic Maintenance Planning Integrating Discrete- and Continuous-State Information

Information-driven group maintenance is crucial to enhance the operational availability and profitability of diverse industrial systems. Existing group maintenance models have primarily concentrated on a single health criterion upon maintenance implementation, where the fusion of multiple health criteria is rarely reported. However, this is not aligned with actual maintenance planning of multi-component systems on many occasions, where multi-source health information can be integrated to support robust decision making. Additionally, how to improve maintenance effectiveness through a scientific union of both scheduled and unscheduled maintenance remains a challenge in group maintenance. This study addresses these research gaps by devising an innovative multiple-information-driven group replacement policy for serial systems. In contrast to existing studies, both discrete-state information (hidden defect) and continuous degradation information are employed for group maintenance planning, and scheduled postponed maintenance and unscheduled opportunistic maintenance are dynamically integrated for the first time to mitigate downtime loss. To be specific, inspections are equally spaced to reveal system health states, followed by the multi-level replacement implemented when either (a) the degradation of the continuously degrading unit reaches a specified threshold, or (b) the age of the multi-state unit since the defect’s identification reaches a pre-set age (delayed replacement). Such scheduling further enables the implementation of multi-source opportunistic replacement to alleviate downtime. The Semi-Markov Decision Process (SMDP) is utilized for the collaborative optimization of continuous- and discrete-state thresholds, so as to minimize the operational costs. Numerical experiments conducted on the critical structure of circulating pumps verify the model’s applicability.

Virtual reality and 3D printing in clinical anesthesia: a case series of two years' experience in a single tertiary medical centre.

Anatomically correct patient-specific models made from medical imaging can be printed on a three-dimensional (3D) printer or turned into a virtual reality (VR) program. Until recently, use in anesthesia has been limited. In 2019, the anesthesia department at Tel Aviv Medical Center launched a 3D program with the aim of using 3D modelling to assist in preoperative anesthesia planning. A retrospective review of all relevant patients between July 2019 and June 2021 referred for preoperative airway planning with 3D modelling. Patient files were reviewed for correlation between the model-based airway plan and the actual airway plan, the type of model used, and any anesthetic complications related to airway management. Twenty patients were referred for 3D modelling. Of these, 15 models were printed, including 12 children requiring one lung ventilation. Five patients had VR reconstructions, including three with mediastinal masses. One patient had both a 3D-printed model and a VR reconstruction. There were two cases (10%) where the model plan did not correlate with the final airway plan and one case where a model could not be created because of poor underlying imaging. For the remaining 17 cases, the plan devised on the model matched the final airway plan. There were no anesthetic complications. Three-dimensional modelling and subsequent printing or VR reconstruction are feasible in clinical anesthesia. Its routine use for patients with challenging airway anatomy correlated well with the final clinical outcome in most cases. High-quality imaging is essential.

Effects Of Financial Management Practices On The Operational Performance Of The Ghana Police Force

The study was to establish the effect of the financial management practices on the operational performance of the Ghana Police force in the Greater Accra Region of Ghana. The study used a descriptive survey design of the quantitative approach. It targeted staff of Ghana Police Service in the Greater Accra Region of Ghana. The study employed census and questionnaire was employed to gather data from them. The questionnaire was analysed descriptively using frequencies and percentages with the aid of Statistical Package for Service Solution version 26. The study found that effective financial management practices have assisted in reducing, crime apprehension and prosecution, crime rate, crime detection and prevention, protection of life and property, as well as peace and tranquility. Factors that hinder the effective financial management practices in the Ghana Police force included; political changes/interference, timeliness of resources and finance, problems of accountability and transparency, and problems of bureaucracy and inefficiency. Therefore, the study recommended that the Ghana Police Service should ensure that liquidity policy is reviewed periodically. Also, the Ghana Police Service should strengthen the system of supervision for cash collection and disbursement. Moreover, the Ghana Police Service should ensure that there is analysis of performance and plans are compared to actual plans with budget. Furthermore, the Ministry of finance in collaboration with the Ghana Police Service should release resources and finance on time. Lastly, the Ghana Police Service should ensure that there is accountability and transparency as well as reducing the bureaucracy and inefficiency

3D PET/CT Tumor Co-Segmentation Based on Background Subtraction Hybrid Active Contour Model

Accurate tumor segmentation in medical images plays an important role in clinical diagnosis and disease analysis. However, medical images usually have great complexity, such as low contrast of computed tomography (CT) or low spatial resolution of positron emission tomography (PET). In the actual radiotherapy plan, multimodal imaging technology, such as PET/CT, is often used. PET images provide basic metabolic information and CT images provide anatomical details. In this paper, we propose a 3D PET/CT tumor co-segmentation framework based on active contour model. First, a new edge stop function (ESF) based on PET image and CT image is defined, which combines the grayscale standard deviation information of the image and is more effective for blurry medical image edges. Second, we propose a background subtraction model to solve the problem of uneven grayscale level in medical images. Apart from that, the calculation format adopts the level set algorithm based on the additive operator splitting (AOS) format. The solution is unconditionally stable and eliminates the dependence on time step size. Experimental results on a dataset of 50 pairs of PET/CT images of non-small cell lung cancer patients show that the proposed method has a good performance for tumor segmentation.

A Co-Ordinated BIM System to Track the Time and Cost of the Construction Projects

Now a day the construction industries are facing many problems due to improper planning and time and cost overruns. This has made to discuss how it could be improved. Many techniques have been raised in recent times one of them is Earned worth administration (EWA), which gives better administration of time and cost requirements. BIM is an approach where it improves the arrangement and improvement stages of a venture plan. Here the scheduling, quantity takeoff, representation module, and earned worth administration platform play a vital role in tracking the project as per the actual planning of the project and avoiding time delay and cost overrun, then with the final updated architectural model the 5D building architectural model with reference to the time and cost is setup and keeps on updating as the calendar of the project gets updated, by incorporating this tool of the integrated system properly into the construction practice the above said problems of cost and time overruns can be overcome.

Innovative study in renewable energy source through mixed surfactant system for eco-friendly environment.

Actual plan of research work was proposed for systematic investigating in the field of photogalvanic (PG) cells for solar energy transformation. It was necessary and proposed to carry out experimental work under the solar parameters for PG cells. The object of the research work is to enhance the solar energy conversion into electricity and store it through PG cells. Various parameters were studied in a PG cell having D-Xylose + MB + Brij-35 + NaLS system (mixed surfactants). In this study, the observed optimum results in terms of the open circuit voltage, photopotential, maximum photocurrent, and short circuit current are 921.00mV, 698.00mV, 311uA, and 245.0uA, respectively. The observed equilibrium photocurrent, current at power point, fill factor, and conversion efficiency were 243.0uA and 142.0uA, 0.4521, and 0.6769%, respectively. For individual surfactants, the observed results in terms of the open circuit voltage, photopotential, maximum photocurrent, and short circuit current are 870.00mV, 635.00mV, 175uA, and 90.0uA, respectively. For individualsurfactant system,the observed equilibrium photocurrent, current at power point, fill factor, and conversion efficiency were 84.0uA and 55.0uA, 0.3630, and 0.3100%, respectively. The impact of solar energy was studied by varying the various parameters in PG cells. On the basis of above obtained values, the mixed surfactants (NaLS + Brij-35) have experimentally proved the efficient system as the desired object of research with special reference to enhance electrical out and storage of solar energy.