Risk Management Techniques in Construction Projects:Development and Assessment of an Innovative

Professional and trade skills are required for handling the construction related projects;Construction industries of the present day however lack useful information concerning different practices,patterns and trends involved in risk management.Considering this,the present study focuses on the aforementioned variables of risk management by quantitative analysis specifically in the domain of construction industry.This study has used IBM’s SPSS(Statistical Package for Social Sciences)version 25.0 to analyze the results.This study is an initiative to assess the impact of risk management in the construction sector of Jordan.It will assist the construction sector for exploring the limitations with respect to integrate effective risk management.A sense of competition will be developed through a comparison of risk factors of construction projects among the project stakeholders such as contractors should enhance their risk management practices.

Effects. of Change Orders through Technical Programs on Construction Projects in Jordan

Regarding construction projects, no project is implemented exactly as planned. Changes in construction projects are common due to the dynamic nature of the construction process. It is necessary to use effective and appropriate tools by project management to support decision-making and control changes during all stages of project implementation. This study examined the effects of change orders through technical programs on construction projects in Jordan and focused on how to overcome these effects by making usual orders that can be handled by each of the contracting parties. Also, this study added an advantage by not addressing the negative effects of change orders, but it provided many positive effects of change orders by using technical programs method, which has not been yet researched in Jordanian studies in particular, and in global studies in general. The researcher used descriptive analytical method by interviews to collect data through nine questions to a random sample of 30 engineers selected form constructions projects in Jordan. The results related to the study questions on the effect of change orders through technical programs on construction projects in Jordan showed that, most of the study samples confirm that change orders through technical programs decrease the cost of the projects, cause no need for more materials, cause no delay in the completion schedule, enhances the quality of work, and increase the productivity of the work force. The study recommended applying integrated change management system with technical supports form different technologies, developing effective innovative and practical solution to manage change orders and increase training programs to qualify and increase engineering skills in dealing with ICT （information and communication technologies） program.

Design of Aided Decision-Making Program for Prioritizing Construction Projects in Urban Road Network Planning

The importance and complexity of prioritizing construction projects (PCP) in urban road network planning lead to the necessity to develop an aided decision making program (ADMP). Cost benefit ratio model and stage rolled method are chosen as the theoretical foundations of the program, and then benefit model is improved to accord with the actuality of urban traffic in China. Consequently, program flows, module functions and data structures are designed, and particularly an original data structure of road ...

Penalty model for delay of bidding section construction period in South-to-North Water Diversion Eastern Route Project from perspective of programs

According to the multi-project and program management theory, this paper analyzes the program generation principle and establishes a program based on progress goals. On the basis of the present situation of calculation of penalty for delay of the bidding section construction period with the critical path method, we studied the effects of contractor-induced delay of the bidding section construction period in detail, including the effects on the construction period of the bidding section itself, the earliest start times of the next bidding section and other subsequent bidding sections, and the construction period of the program, and then constructed a penalty model for delay of the bidding section construction period from the perspective of programs. Using the penalty model, we conducted a practical analysis of penalty for delay of the construction period of the Baoying station program in the South-to-North Water Diversion Project. The model can help determine the amount of penalty for delay of the construction period in bidding sections scientifically and reasonably,

Research and Practice of Cardiopulmonary Rehabilitation Training Programs

In today’s society, the incidence of cardiopulmonary diseases is increasing annually, seriously affecting patients’ quality of life. Therefore, developing a scientific and effective rehabilitation training program is of great significance. This study first analyzes the theoretical basis of cardiopulmonary rehabilitation training, including the effects of aerobic exercise, interval training, and strength training on cardiopulmonary function. Based on this, a comprehensive rehabilitation training program is designed, which includes personalized training plans, comprehensive interventions, multidisciplinary collaboration, patient education, and regular follow-up visits. The cardiopulmonary rehabilitation training plan developed in this study has certain scientific practicability, which provides a theoretical basis for cardiopulmonary rehabilitation training, and also provides a reference for medical institutions, rehabilitation centers and communities, which is helpful for promotion and application to a wider range of patients with cardiopulmonary diseases.

Contractor-Related Factors and Performance of Bridge Construction Projects Implemented by Kenya National Highways Authority (KeNHA) Kenya

The performance of bridge projects in Kenya is poor in terms of completion by schedule, cost, and quality (scope). Yet, there is less evidence of empirical research on what factors contribute to this outcome. This study aimed to bridge this gap by examining the effects of contractor-related factors on the performance of bridge construction projects in Kenya through a case study of the Bridge projects Implemented by the Kenya National Highway Agency (KeNHA). The theory of constraints (TOC) was adopted as its theoretical framework. Descriptive research was used, and the target population was 18 bridge construction projects, which were the units of analysis from 2012 to 2022. In each of these projects, 18 respondents, namely clients, consultants, contractors, engineers, environment and social guards, project managers, stakeholders, subcontractors, technical advisors, and inspectors, were included in a target population of 144 respondents. A census was conducted and a structured questionnaire was administered from which a response rate of 68% was achieved. The information was analyzed using descriptive, correlation, and multiple linear regression analysis. The contractor-related factors considered in the study were staff and management factors. The findings indicated that staff and management factors had a positive and significant outcome on performance of bridge construction projects. The study recommends continuous training and a safe learning environment for staff to improve their skills and performance in future projects. The study also recommends that a special category for bridge contractors be created in Kenya’s National Construction Authority rankings to ensure that only qualified contractors implement the Bridge projects.

Women Awareness on the Importance of Agriculture Technologies Using ICT-Based Training Programs

Awareness policy intended to contribute to changing rural women realities to urgent needs of information and gain knowledge was to be demonstrated through in-depth information and communication technology-based(ICTs-based)training program that focused on the importance of advanced agricultural technologies in the production chain in developing countries like Egypt through access and use of the ICTs.Women are becoming well trained on the detailed steps of improved technologies applied in supply chain.Their increased awareness of the necessity of quality management to be followed during their work in the postharvest handling system helped them to produce high-quality products to meet the export requirements of foreign markets and add value to the export quality.Women have been able to reduce the extremely high losses that occurred due to improper handling in particular.The outcomes of proper and healthy procedures,precautions and personal protection were gained by rural women and technicians working in the supply chain.Moreover,women themselves became more confident in their know-how and more comfortable in transgressing cultural norms that inhibited their progress.

Impacts of forest plantation programs on sectoral CO_(2) emissions regionally in New Zealand

Investing in projects that support environmental benefits,such as tree harvesting,has the potential to reduce air pollution levels in the atmosphere in the future.However,this kind of investment may increase the current level of emissions.Therefore,it is necessary to estimate how much the policy affects the current level of CO_(2) emissions.This makes sure the policy doesn’t increase the level of CO_(2) emis-sions.This study aims to analyze the effect of the One Bil-lion Trees program on CO_(2) emissions in New Zealand by employing the 2020 input–output table analysis.This inves-tigation examines the direct and indirect effects of policy on both the demand and supply sides across six regions of New Zealand.The results of this study for the first year of plantation suggest that the policy increases the level of CO_(2) emissions in all regions,especially in the Waikato region.The direct and indirect impact of the policy leads to 64 kt of CO_(2) emissions on the demand side and 270 kt of CO_(2) emis-sions on the supply side.These lead to 0.19 and 0.74%of total CO_(2) emissions being attributed to investment shocks.Continuing the policy is recommended,as it has a low effect on CO_(2) emissions.However,it is crucial to prioritize the use of low-carbon machinery that uses fossil fuels during the plantation process.

Does enhanced recovery after surgery programs improve clinical outcomes in liver cancer surgery?

Enhanced recovery after surgery(ERAS)programs have been widely applied in liver surgery since the publication of the first ERAS guidelines in 2016 and the new recommendations in 2022.Liver surgery is usually performed in oncological patients(liver metastasis,hepatocellular carcinoma,cholangiocarcinoma,etc.),but the real impact of liver surgery ERAS programs in oncological outcomes is not clearly defined.Theoretical advantages of ERAS programs are:ERAS decreases postoperative complication rates and has been demonstrated a clear relationship between complications and oncological outcomes;a better and faster posto-perative recovery should let oncologic teams begin chemotherapeutic regimens on time;prehabilitation and nutrition actions before surgery should also improve the performance status of the patients receiving chemotherapy.So,ERAS could be another way to improve our oncological results.We will discuss the literature about liver surgery ERAS focusing on its oncological implications and future investigations projects.

Multi-Criteria Wildfire Risk Hazard Assessment in GIS Environment: Projection for the Future and Impact on RES Projects Installation Planning

It is alarming for the fact that Wildfires number, severity and consequently impact have significantly increased during the last years, an aftermath of the Climate Change. One of the most affected areas worldwide is Mediterranean, due to the unique combination of its type of vegetation and demanding climatic conditions. This research is focused on the Region of Epirus in Greece, an area with significant natural vegetation and a range of geomorphological aspects. In order to estimate the Wildfire Risk Hazard, several factors have been used: geomorphological (slope, aspect, elevation, TWI, Hydrographic network), social (Settlements and landfils, roads, overhead lines and substations), environmental (land cover) and climatic (Fire Weather Index). Through a multi-criteria decision analysis (MCDA) and an analytic hierarchy process (AHP) in a GIS environment, the Wildfire Risk Hazard has been estimated not only for current conditions but also for future projections for the near future (2031-2060) and the far future (2071-2100). The selected case study includes the potential impact of the Wildfires to the installed (or targeted to be installed) RES projects in the studied region.

Glia-to-neuron reprogramming to the rescue?

Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells could be generated from adult mouse fibroblasts is powerful proof that cell fate can be changed.An exciting extension of the discovery of cell fate impermanence is the direct cellular reprogram ming hypothesis-that terminally differentiated cells can be reprogrammed into other adult cell fates without first passing through a stem cell state.

An Approach to Detect Structural Development Defects in Object-Oriented Programs

Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.

Neurocircuit regeneration by extracellular matrix reprogramming

The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.

A Review on Determinants Affecting Commercialization of Academic Institution Final Year Projects

Final year project is an important training and assessment component incorporated in many courses of academic institution.The ability to translate ideas,research,and creativity into actual products,services,or businesses shows how successful and impactful people or institutions can be in the wider economy.However,in most of the cases,the outcomes of the final year project usually remain as academic discussion without maximizing their potential to be converted into a commercialized product or services.In this review,theory and applications are discussed to understand how entrepreneurial skills and networking abilities,components of individuals’human capital can impact the commercialisation of final year projects.Furthermore,determinants affecting commercialization of final year projects will also be explored namely:entrepreneurial skills,networking ability,access to resources,institutional support as well as creativity and innovation.

Assessing and Improving the Quality of Undergraduates in Preschool Education Programs in China:The Course Experience

This study investigated the current status of course satisfaction among 416 undergraduate students majoring in preschool education from four universities in China.And it explored the predictive effects of five influencing factors(teacher instruction,course management,course setting,course environment,and course resources)on student satisfaction.Through SPSS data analysis,the findings revealed that:1.the mean value of course experience was M=3.861(out of 5);2.there were differences in the satisfaction of undergraduate students'course experience by different background variables;3.course,course resources,and loyalty had significant predictive power on undergraduate students'satisfaction with course experience;4.instructor instruction(TI)did not significantly predict students'satisfaction with course experience(SCES)(p>0.001);5.Faculty instruction(TI)in this study had the highest mean satisfaction score(M=4.191)and the mean satisfaction score was only(M=3.861).The results show that the current status of course satisfaction among Chinese preschool undergraduates is at an moderate level,and there is more space for improvement;although students'satisfaction with teacher instruction(TI)is high,effective teacher instruction does not have a substantial impact on the acquisition of SCES or general competencies,and this passive learning and teaching style leads to a lack of independent learning and active participation among Chinese preschool undergraduate students.

Exploration of the Maturity Evaluation of College Students’Innovation and Entrepreneurship Projects Based on Computer Database Technology

The college innovation and entrepreneurship program is a powerful means to enhance students’innovation and entrepreneurship skills.Evaluating the maturity of innovation and entrepreneurship projects can stimulate students’enthusiasm and initiative to participate.Utilizing computer database technology for maturity evaluation can make the process more efficient,accurate,and convenient,aligning with the needs of the information age.Exploring strategies for applying computer database technology in the maturity evaluation of innovation and entrepreneurship projects offers valuable insights and directions for developing these projects,while also providing strong support for enhancing students’innovation and entrepreneurship abilities.

Financial Calculation Problems and Countermeasure Analysis of Large-Scale Engineering Construction Projects

The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s economic benefits,minimize unnecessary costs,and provide decision-makers with a robust financial foundation.Additionally,implementing an effective cash flow control mechanism and conducting a comprehensive assessment of potential project risks can ensure financial stability and mitigate the risk of fund shortages.Developing a practical and feasible fundraising plan,along with stringent fund management practices,can prevent fund wastage and optimize fund utilization efficiency.These measures not only facilitate smooth project progression and improve project management efficiency but also enhance the project’s economic and social outcomes.

Research on Financial Risk Management in the S Water Conservancy Project and Its Implications for Similar Projects

As a vital infrastructure initiative with significant impacts on national development and public welfare,water conservancy projects play an essential role in advancing agricultural development and mitigating losses caused by flooding.However,these projects often require substantial investments and extended construction periods,leading to the inevitable emergence of various financial risks during implementation.This paper aims to explore the current challenges in financial risk management of the S water conservancy project,offering practical management strategies and solutions to address these financial difficulties.Through a detailed assessment and analysis of the S water conservancy project,the study seeks to provide valuable references and insights for similar projects to better manage financial risks,ensuring their smooth progression and successful completion.The proposed control measures are designed not only to effectively mitigate the financial risks specific to the S water conservancy project but also to offer actionable lessons for other similar projects.By promoting and applying these measures,the overall financial management capabilities of the industry can be enhanced,providing robust support for the sustainable development of water conservancy projects.

Trust beyond Technology Algorithms: A Theoretical Exploration of Consumer Trust and Behavior in Technological Consumption and AI Projects

In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing customer trust in AI systems through a mixed-methods approach, blending quantitative analysis with qualitative insights to create a comprehensive conceptual framework. Quantitatively, the study analyzes responses from 1248 participants using structural equation modeling (SEM), exploring interactions between technological factors like perceived usefulness and transparency, psychological factors including perceived risk and domain expertise, and organizational factors such as leadership support and ethical accountability. The results confirm the model, showing significant impacts of these factors on consumer trust and AI adoption attitudes. Qualitatively, the study includes 35 semi-structured interviews and five case studies, providing deeper insight into the dynamics shaping trust. Key themes identified include the necessity of explainability, domain competence, corporate culture, and stakeholder engagement in fostering trust. The qualitative findings complement the quantitative data, highlighting the complex interplay between technology capabilities, human perceptions, and organizational practices in establishing trust in AI. By integrating these findings, the study proposes a novel conceptual model that elucidates how various elements collectively influence consumer trust in AI. This model not only advances theoretical understanding but also offers practical implications for businesses and policymakers. The research contributes to the discourse on trust creation and decision-making in technology, emphasizing the need for interdisciplinary efforts to address societal challenges associated with technological advancements. It lays the groundwork for future research, including longitudinal, cross-cultural, and industry-specific studies, to further explore consumer trust in AI.

Research on Intelligent Cost Estimation of Engineering Foundation Projects Based on CSIs Theory

Against the backdrop of rapid development in China’s construction and infrastructure sectors,discrepancies between project budgets and actual costs have become pronounced,manifesting in project overruns and suspensions,posing significant challenges.To address inaccuracies in investment targets and operational complexities,this study focuses on a beam-bridge construction project in a district of Shijiazhuang city as a case study.Drawing upon historical analogs,the project employs a Work Breakdown Structure(WBS)to decompose the engineering works.Building on theories of Cost Significant(CS)and Whole Life Costing(WLC),the study constructs Cost Significant Items(CSIs)and develops a CNN-BiLSTM-Attention neural network for nonlinear prediction.By identifying significant cost drivers in engineering projects,this paper presents a streamlined cost estimation method that significantly reduces computational burdens,simplifies data collection processes,and optimizes data analysis and forecasting,thereby enhancing prediction accuracy.Finally,validation with real-world cost fluctuation data demonstrates minor errors,meeting predictive requirements across project execution phases.