Search results for: innovation cost

Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

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The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

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Authors: R. C. Tyagi

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Quasi-periodicity of frequency intervals observed in Shruti based Absolute Scale of Music has been used to graphically identify the Anchor notes ‘Vadi’ and ‘Samvadi’ which are nodal points for expansion, elaboration and iteration of the emotional theme represented by the characteristic tonic arrangement in Raga compositions. This analysis leads to defining the Tonic parameters in the octave including the key-note frequency, tonic intervals’ anchor notes and the on-set and range of quasi-periodicities as exponents of 2. Such uniformity of representation of characteristic data would facilitate computational analysis and synthesis of music compositions and also help develop noise suppression techniques. Criteria for tuning of strings for compatibility with placement of frets on finger boards is discussed. Natural Rhythmic cycles in music compositions are analytically shown to lie between 3 and 126 beats.

Keywords: absolute scale, anchor notes, computational analysis, frets, innovation, noise suppression, Quasi-periodicity, rhythmic cycle, tonic interval, Shruti

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Authors: Matich Lyubov

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Today roadmaps are becoming commonly used tools for detecting and designing a desired future for companies, states and the international community. The growing popularity of this method puts tasks such as identifying basic roadmapping principles, creation of concepts and determination of the characteristics of the use of roadmaps depending on the objectives as well as restrictions and opportunities specific to the study area on the agenda. However, the system approach, e.g. the elements which are recognized to be major for high-quality roadmapping, remains one of the main fields for improving the methodology and practice of their development as limited research was devoted to the detailed analysis of the roadmaps from the view of system approach. Therefore, this article is an attempt to examine roadmaps from the view of the system analysis, to compare areas, where, as a rule, roadmaps and systems analysis are considered the most effective tools. To compare the structure and composition of roadmaps and systems models the identification of common points between construction stages of roadmaps and system modeling and the determination of future directions for research roadmaps from a systems perspective are of special importance.

Keywords: technology roadmap, roadmapping, systems analysis, system modeling, innovation management

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Authors: Justin D. Olmanson, Katrina S. Kennett, Bill Cope

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In the field of education technology, innovation is often tightly coupled to recent technological inventions and emerging technologies. Despite this, some scholars have argued that using established technologies in new pedagogical or curricular ways recasts them and places them once more under the umbrella of emerging education technologies. In this study, we trace how an innovative education technology design emerged, not from a technological breakthrough, but rather via a techno-pedagogical pivot. We describe the design and impact of a digital writing tool created to scaffold student self-evaluation of academic texts. We theorize about and trace how innovation can also emerge from a pivot, namely how leveraging existing practices in new ways can create pedagogically and experientially innovative learning opportunities. After describing the design of Info Writer, we unpack the results of a study based on an implementation the tool, and then theorize and reflect on the way the design process and study findings suggest that pivoting an existing practice can lead to innovative education technology designs.

Keywords: design, education, revision, technology, writing

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Authors: Ibrahim Ahmed Jajere

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Resource use conflicts capable of undermining of pastoralists’ livelihoods are on the increase in the North East Arid Zone of Nigeria. In order to expose socio - economic effects of conflicts and benefits of peace, this study assessed cost implications of farmers/pastoralists conflicts over natural resources. Interviews were conducted with 94 farmers, 90 agro-pastoralists and 91 pastoralists’ household heads. The farmers and agro-pastoralists were systematically sampled while pastoralists were located using snowballing. Both farmers and pastoralists suffered losses in the form of injuries to, and even death of household members, and loss of shelter. Farmers sustained losses of facilities and farm produce while pastoralists suffered loss and seizure of livestock, arrest of household members and forced migrations. The material losses in monetary terms amounted to 14,242,200.00 nairas for farmers, a figure higher than the 10,915,500.00 nairas incurred by pastoralists.

Keywords: cost, conflicts, farmers, pastoralists

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Authors: Anna Ching-Yu Wong

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Introduction: Textbooks play a sizable portion of the overall cost of higher education students. It is a board consent that open education resources (OER) reduce the te4xtbook costs and provide students a way to receive high-quality learning materials at little or no cost to them. However, there is less agreement over exactly how much. This study presents an approach for calculating OER savings by using SUNY Canton NON-OER courses (N=233) to estimate the potentially textbook savings for one semester – Fall 2022. The purpose in collecting data is to understand how much potentially saved from using OER materials and to have a record for future further studies. Literature Reviews: In the past years, researchers identified the rising cost of textbooks disproportionately harm students in higher education institutions and how much an average cost of a textbook. For example, Nyamweya (2018) found that on average students save $116.94 per course when OER adopted in place of traditional commercial textbooks by using a simple formula. Student PIRGs (2015) used reports of per-course savings when transforming a course from using a commercial textbook to OER to reach an estimate of $100 average cost savings per course. Allen and Wiley (2016) presented at the 2016 Open Education Conference on multiple cost-savings studies and concluded $100 was reasonable per-course savings estimates. Ruth (2018) calculated an average cost of a textbook was $79.37 per-course. Hilton, et al (2014) conducted a study with seven community colleges across the nation and found the average textbook cost to be $90.61. There is less agreement over exactly how much would be saved by adopting an OER course. This study used SUNY Canton as a case study to create an approach for estimating OER savings. Methodology: Step one: Identify NON-OER courses from UcanWeb Class Schedule. Step two: View textbook lists for the classes (Campus bookstore prices). Step three: Calculate the average textbook prices by averaging the new book and used book prices. Step four: Multiply the average textbook prices with the number of students in the course. Findings: The result of this calculation was straightforward. The average of a traditional textbooks is $132.45. Students potentially saved $1,091,879.94. Conclusion: (1) The result confirms what we have known: Adopting OER in place of traditional textbooks and materials achieves significant savings for students, as well as the parents and taxpayers who support them through grants and loans. (2) The average textbook savings for adopting an OER course is variable depending on the size of the college and as well as the number of enrollment students.

Keywords: textbook savings, open textbooks, textbook costs assessment, open access

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Authors: Wen Liang Chang, Mei Wei Wang, Ruey Huei Yeh

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This paper studies the comparisons of individual and group replacement policies for a series connection system with two machines. Suppose that manufacturer’s production system is a series connection system which is combined by two machines. For two machines, when machines fail within the operating time, minimal repair is performed for machines by the manufacturer. The manufacturer plans to a preventive replacement for machines at a pre-specified time to maintain system normal operation. Under these maintenance policies, the maintenance cost rate models of individual and group replacement for a series connection system with two machines is derived and further, optimal preventive replacement time is obtained such that the expected total maintenance cost rate is minimized. Finally, some numerical examples are given to illustrate the influences of individual and group replacement policies to the maintenance cost rate.

Keywords: individual replacement, group replacement, replacement time, two machines, series connection system

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Authors: Zeta Dooly, Aidan Duane

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The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

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Authors: Muhammad Arif Mahmood, Andrei C. Popescu, Mihai Oane, Diana Chioibascu, Carmen Ristoscu, Ion N. Mihailescu

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Powder flow and temperature distributions are recognized as influencing factors during laser melting deposition (LMD) process, that not only affect the consolidation rate but also characteristics of the deposited layers. Herewith, two simplified analytical models will be presented to simulate the powder flow with the inclusion of powder particles size distribution in Gaussian form, under three powder jet nozzles, and temperature analyses during LMD process. The output of the 1st model will serve as the input in the 2nd model. The models will be validated with experimental data, i.e., weight measurement method for powder particles distribution and infrared imaging for temperature analyses. This study will increase the cost-efficiency of the LMD process by adjustment of the operating parameters for reaching optimal powder debit and energy. This research has received funds under the Marie Sklodowska-Curie grant agreement No. 764935, from the European Union’s Horizon 2020 research and innovation program.

Keywords: laser additive manufacturing, powder particles size distribution in Gaussian form, powder stream distribution, temperature analyses

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Authors: Benga Ebouele, Thomas Tengen

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Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

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Authors: Tedros Asefaw Gebremeskel, Xaoyi Yang

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The potential of solar energy in Eritrea is relatively high, based on this truth, there are a number of isolated and remote villages situated far away from the electrical national grid which don’t get access to electricity. The core objective of this work is to design a most favorable and cost-effective power by means of standalone PV system for the electrification of a single housing in the inaccessible area of Eritrea. The sizing of the recommended PV system is achieved, such as radiation data and electrical load for the typical household of the selected site is also well thought-out in the design steps. Finally, the life cycle cost (LCC) analysis is conducted to evaluate the economic viability of the system. The outcome of the study promote the use of PV system for a residential building and show that PV system is a reasonable option to provide electricity for household applications in the rural area of Eritrea.

Keywords: electrification, inaccessible area, life cycle cost, residential building, stand-alone PV system

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Authors: Jin Woo Hwang, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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As greenhouse effect has been recognized as serious environmental problem of the world, interests in carbon dioxide (CO₂) emission which comprises major part of greenhouse gas (GHG) emissions have been increased recently. Since construction industry takes a relatively large portion of total CO₂ emissions of the world, extensive studies about reducing CO₂ emissions in construction and operation of building have been carried out after the 2000s. Also, performance based design (PBD) methodology based on nonlinear analysis has been robustly developed after Northridge Earthquake in 1994 to assure and assess seismic performance of building more exactly because structural engineers recognized that prescriptive code based design approach cannot address inelastic earthquake responses directly and assure performance of building exactly. Although CO₂ emissions and PBD approach are recent rising issues on construction industry and structural engineering, there were few or no researches considering these two issues simultaneously. Thus, the objective of this study is to minimize the CO₂ emissions and cost of building designed by PBD approach in structural design stage considering structural materials. 4 story and 4 span reinforced concrete building optimally designed to minimize CO₂ emissions and cost of building and to satisfy specific seismic performance (collapse prevention in maximum considered earthquake) of building satisfying prescriptive code regulations using non-dominated sorting genetic algorithm-II (NSGA-II). Optimized design result showed that minimized CO₂ emissions and cost of building were acquired satisfying specific seismic performance. Therefore, the methodology proposed in this paper can be used to reduce both CO₂ emissions and cost of building designed by PBD approach.

Keywords: CO2 emissions, performance based design, optimization, sustainable design

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Authors: Maziyar Nouraee

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Electronic markets in recent decades contribute remarkably in business transactions. Many organizations consider traditional ways of trade non-economical and therefore they do trade only through electronic markets. There are different categorizations of electronic markets functions. In one classification, functions of electronic markets are categorized into classes as information, transactions, and value added. In the present paper, effects of the three classes on the two major elements of the supply chain management are measured. The two elements are decrease in the product unit cost and reduction in response time to the customer. The results of the current research show that among nine minor elements related to the three classes of electronic markets functions, six factors and three factors influence on reduction of the product unit cost and reduction of response time to the customer, respectively.

Keywords: electronic commerce, electronic market, B2B trade, supply chain management

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Authors: Daral Maesincee, Jompol Thongpaen

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Thus far, most of the decisions made within the walls of Thai higher education (HE) institutions have primarily been supply-oriented. With the current supply-driven, itemized HE financing systems, the nation is struggling to systemically produce high-quality manpower that serves the market’s needs, often resulting in education mismatches and unemployment – particularly in science, technology, and innovation (STI)-related fields. With the COVID-19 pandemic challenges widening the education inequality (accessibility and quality) gap, HE becomes even more unobtainable for underprivileged students, permanently leaving some out of the system. Therefore, Thai HE needs a new financing system that produces the “right people” for the “right occupations” through the “right ways,” regardless of their socioeconomic backgrounds, and encourages the creation of non-degree courses to tackle these ongoing challenges. The “Demand-Side Financing for Thai Higher Education” policy aims to do so by offering a new paradigm of HE resource allocation via two main mechanisms: i) standardized formula-based unit-cost subsidizations that is specific to each study field and ii) student loan programs that respond to the “demand signals” from the labor market and the students, that are in line with the country’s priorities. Through in-dept reviews, extensive studies, and consultations with various experts, education committees, and related agencies, i) the method of demand signal analysis is identified, ii) the unit-cost of each student in the sample study fields is approximated, iii) the method of budget analysis is formulated, iv) the interagency workflows are established, and v) a supporting information database is created to suggest the number of graduates each HE institution can potentially produce, the study fields and skillsets that are needed by the labor market, the employers’ satisfaction with the graduates, and each study field’s employment rates. By responding to the needs of all stakeholders, this policy is expected to steer Thai HE toward producing more STI-related manpower in order to uplift Thai people’s quality of life and enhance the nation’s global competitiveness. This policy is currently in the process of being considered by the National Education Transformation Committee and the Higher Education Commission.

Keywords: demand-side financing, higher education resource, human capital, higher education

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Authors: Jyun-Huei Huang, Ting-I Lee

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Urban heat island effect is derived from the reduction of vegetative cover by urban development. Because plants can improve air quality and microclimate, green walls have been applied as a sustainable design approach to cool building temperature. By using plants to green vertical surfaces, they decrease room temperature and, as a result, decrease the energy use for air conditioning. Based on their structures, green walls can be divided into two categories, green façades and living walls. A green façade uses the climbing ability of a plant itself, while a living wall assembles planter modules. The latter one is widely adopted in public space, as it is time-effective and less limited. Although a living wall saves energy spent on cooling, it is not necessarily cost-effective from the perspective of a lifecycle analysis. The Italian study shows that the overall benefit of a living wall is only greater than its costs after 47 years of its establishment. In Taiwan, urban greening policies encourage establishment of green walls by referring to their benefits of energy saving while neglecting their low performance on cost-effectiveness. Thus, this research aims at understanding the perception of appliers and consumers on the cost-effectiveness of their living wall products from the lifecycle viewpoint. It adopts semi-structured interviews and field observations on the maintenance of the products. By comparing the two results, it generates insights for sustainable urban greening policies. The preliminary finding shows that stakeholders do not have a holistic sense of lifecycle or cost-effectiveness. Most importantly, a living wall well maintained is often with high input due to the availability of its maintenance budget, and thus less sustainable. In conclusion, without a comprehensive sense of cost-effectiveness throughout a product’s lifecycle, it is very difficult for suppliers and consumers to maintain a living wall system while achieve sustainability.

Keywords: case study, maintenance, post-occupancy evaluation, vertical greening

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Hamed Saremi, Shahla Saremi

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In this study, control and management of construction projects is evaluated through developing a dynamic model in which some means are used in order to evaluating planning assumptions and reviewing the effectiveness of some project control policies based on previous researches about time, cost, project schedule pressure management, source management, project control, adding elements and sub-systems from cost management such as estimating consumption budget from budget due to costs, budget shortage effects and etc. using sensitivity analysis, researcher has evaluated introduced model that during model simulation by VENSIM software and assuming optimistic times and adding information about doing job and changes rate and project is forecasted with 373 days (2 days sooner than forecasted) and final profit $ 1,960,670 (23% amount of contract) assuming 15% inflation rate in year and costs rate accordance with planned amounts and other input information and final profit.

Keywords: dynamic planning, cost, time, performance, project management

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Authors: Grace Rachid, Mutasem El Fadel, Mahmoud Al Hindi, Ibrahim Jamali, Daniel Abdel Nour

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This study examines the feasibility of indirect solar desalination in oil producing countries in the Middle East and North Africa (MENA) region. It relies on value engineering (VE) and cost-benefit with sensitivity analyses to identify optimal coupling configurations of desalination and solar energy technologies. A comparative return on investment was assessed as a function of water costs for varied plant capacities (25,000 to 75,000 m3/day), project lifetimes (15 to 25 years), and discount rates (5 to 15%) taking into consideration water and energy subsidies, land cost as well as environmental externalities in the form of carbon credit related to greenhouse gas (GHG) emissions reduction. The results showed reverse osmosis (RO) coupled with photovoltaic technologies (PVs) as the most promising configuration, robust across different prices for Brent oil, discount rates, as well as different project lifetimes. Environmental externalities and subsidies analysis revealed that a 16% reduction in existing subsidy on water tariffs would ensure economic viability. Additionally, while land costs affect investment attractiveness, the viability of RO coupled with PV remains possible for a land purchase cost < $ 80/m2 or a lease rate < $1/m2/yr. Beyond those rates, further subsidy lifting is required.

Keywords: solar energy, desalination, value engineering, CBA, carbon credit, subsidies

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Authors: Wendy De Gomez

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The University of Waterloo is situated in central Canada in the Province of Ontario- one hour from the metropolitan city of Toronto. For over 30 years, it has held Canada’s top spot as the most innovative university; and has been consistently ranked in the top 25 computer science and top 50 engineering schools in the world. Waterloo benefits from the federal government’s over 100 domestic innovation policies which have assisted in the country’s 15th place global ranking in the World Intellectual Property Organization’s (WIPO) 2022 Global Innovation Index. Yet undoubtedly, the University of Waterloo’s unique characteristics are what propels its innovative creativeness forward. This paper will provide a contextual definition of innovation in higher education and then demonstrate the five operational attributes that contribute to the University of Waterloo’s innovative reputation. The methodology is based on statistical analyses obtained from ranking bodies such as the QS World University Rankings, a secondary literature review related to higher education innovation in Canada, and case studies that exhibit the operationalization of the attributes outlined below. The first attribute is geography. Specifically, the paper investigates the network structure effect of the Toronto-Waterloo high-tech corridor and the resultant industrial relationships built there. The second attribute is University Policy 73-Intellectal Property Rights. This creator-owned policy grants all ownership to the creator/inventor regardless of the use of the University of Waterloo property or funding. Essentially, through the incentivization of IP ownership by all researchers, further commercialization and entrepreneurship are formed. Third, this IP policy works hand in hand with world-renowned business incubators such as the Accelerator Centre in the dedicated research and technology park and velocity, a 14-year-old facility that equips and guides founders to build and scale companies. Communitech, a 25-year-old provincially backed facility in the region, also works closely with the University of Waterloo to build strong teams, access capital, and commercialize products. Fourth, Waterloo’s co-operative education program contributes 31% of all co-op participants to the Canadian economy. Home to the world’s largest co-operative education program, data shows that over 7,000 from around the world recruit Waterloo students for short- and long-term placements- directly contributing to the student’s ability to learn and optimize essential employment skills when they graduate. Finally, the students themselves at Waterloo are exceptional. The entrance average ranges from the low 80s to the mid-90s depending on the program. In computer, electrical, mechanical, mechatronics, and systems design engineering, to have a 66% chance of acceptance, the applicant’s average must be 95% or above. Singularly, none of these five attributes could lead to the university’s outstanding track record of innovative creativity, but when bundled up into a 1000 acre- 100 building main campus with 6 academic faculties, 40,000+ students, and over 1300 world-class faculty, the recipe for success becomes quite evident.

Keywords: IP policy, higher education, economy, innovation

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Harun Ozdemirci

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Complexity and chaos are the characteristics of our new world today. Either business or governmental sector, inner and outer environment changes in all aspects. To ensure leaders to guide organizations accurately and effectively, leaders also must change their attitudes towards this changing world . We need new tools, new mindsets and new views for new century. Every leader have to operate within an cerative and innovative way of thinking. But how it will occur and at which direction it will be managed or directed? What kind of abilities and attitudes make leader compatible with this ever-changing and ambigous environment? Leader who will lead in the future must have some special skillls. But how can we develop these skills and behaviours? What must be the mindset of a future leader? This paper searchs for answers of some of these questions. But asking questions is more important than giving answers to them. Innovation and creativity have been at the centerpiece of our lives for some years. But we don’t know how to manage and how to tackle with the challenges come up with this new situation. This new world order compel us to take some new positions against new employees who have different types of lives and habits, new productivity processes, new adversaries… Future environment will not be the same as we experience before. So, our responses to this new environment can not be the same as our predecessors gave. We have to innovate new ways of thinking, and new tools for solving new type of problems.

Keywords: innovation, creativity, leader, future, liberal arts

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Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

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Authors: Yehya Abdellatif, Iyad M. Muslih, Azzah Alkhalailah, Abdallah Muslih

Abstract:

Hybrid Optimization Model for Electric Renewable (HOMER) software was utilized to find the optimum design of a hybrid off-Grid system, by choosing the optimal solution depending on the cost analysis of energy based on different capacity shortage percentages. A complete study for the site conditions and load profile was done to optimize the design and implementation of a hybrid off-grid power station. In addition, the solution takes into consecration the ambient temperature effect on the efficiency of the power generation and the economical aspects of selection depending on real market price. From the analysis of the HOMER model results, the optimum hybrid power station was suggested, based on wind speed, and solar conditions. The optimization function objective is to minimize the Net Price Cost (NPC) and the Cost of Energy (COE) with zero and 10 percentage of capacity shortage.

Keywords: energy modeling, HOMER, off-grid system, optimization

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Authors: Babak Darvish Rouhani, Mohd Nazri Mahrin, Fatemeh Nikpay, Pourya Nikfard, Maryam Khanian Najafabadi

Abstract:

Enterprise Architecture (EA) is a strategy that is employed by enterprises in order to align their business and Information Technology (IT). EA is managed, developed, and maintained through Enterprise Architecture Implementation Methodology (EAIM). The effectiveness of EA implementation is the degree in which EA helps to achieve the collective goals of the organization. This paper analyzes the results of a survey that aims to explore the factors that affect the effectiveness of EAIM and specifically the relationship between factors and effectiveness of the output and functionality of EA project. The exploratory factor analysis highlights a specific set of five factors: alignment, adaptiveness, support, binding, and innovation. The regression analysis shows that there is a statistically significant and positive relationship between each of the five factors and the effectiveness of EAIM. Consistent with theory and practice, the most prominent factor for developing an effective EAIM is innovation. The findings contribute to the measuring the effectiveness of EA implementation project by providing an indication of the measurement implementation approaches which is used by the Enterprise Architects, and developing an effective EAIM.

Keywords: enterprise architecture, enterprise architecture implementation methodology, implementation methodology, factors, EA, effectiveness

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Authors: Tofigh Hamidavi, Sepehr Abrishami, Pasquale Ponterosso, David Begg

Abstract:

Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.

Keywords: building information, modelling, BIM, genetic algorithm, GA, architecture-engineering-construction, AEC, optimisation, structure, design, population, generation, selection, mutation, crossover, offspring

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Authors: Johnson Adafin, James O. B. Rotimi, Suzanne Wilkinson, Abimbola O. Windapo

Abstract:

An aspect of client expenditure management that requires attention is the level of accuracy achievable in design-stage elemental cost planning. This has been a major concern for construction clients and practitioners in New Zealand (NZ). Pre-tender estimating inaccuracies are significantly influenced by the level of risk information available to estimators. Proper cost planning activities should ensure the production of a project’s likely construction costs (initial and final), and subsequent cost control activities should prevent unpleasant consequences of cost overruns, disputes and project abandonment. If risks were properly identified and priced at the design stage, observed variance between design-stage elemental cost plans (ECPs) and final tender sums (FTS) (initial contract sums) could be reduced. This study investigates the variations between design-stage ECPs and FTS of construction projects, with a view to identifying risk factors that are responsible for the observed variance. Data were sourced through interviews, and risk factors were identified by using thematic analysis. Access was obtained to project files from the records of study participants (consultant quantity surveyors), and document analysis was employed in complementing the responses from the interviews. Study findings revealed the discrepancies between ECPs and FTS in the region of -14% and +16%. It is opined in this study that the identified risk factors were responsible for the variability observed. The values obtained from the analysis would enable greater accuracy in the forecast of FTS by Quantity Surveyors. Further, whilst inherent risks in construction project developments are observed globally, these findings have important ramifications for construction projects by expanding existing knowledge on what is needed for reasonable budgetary performance and successful delivery of construction projects. The findings contribute significantly to the study by providing quantitative confirmation to justify the theoretical conclusions generated in the literature from around the world. This therefore adds to and consolidates existing knowledge.

Keywords: accuracy, design-stage, elemental cost plan, final tender sum

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Authors: Shwadhin Sharma, Monica Perez, Vinita Patel, Tyler Kuwatani, Siobhan Scott

Abstract:

The purpose of this research is to explain and analyze why the Internet of Things (IoT) is an emerging technology trend. The aspects of this research paper include an overview of IoT, what research has already been done, the benefits, implications, and our own perspectives on the trend in order to thoroughly analyze how the trend of IoT will make an impact on society. Through the identification of what makes IoT important, it is concluded that IoT will have a tremendous impact for the whole world. Technology is never going to go away, it is going to get smarter and have the potential to change the world.

Keywords: internet of things, enablers of IoT, cost of IoT, benefits of IoT

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Authors: Inês Ramalhete, Hugo Farias, Rui da Silva Pinto

Abstract:

Adequate housing has been a widely discussed theme in academic circles related to low-cost housing, whereas its physical features are easy to deal with, overcrowding (related to social, cultural and economic aspects) is still ambiguous, particularly regarding the set of indicators that can accurately reflect and measure it. This paper develops research on low-cost housing models for developing countries and what is the best method to embed overcrowding as an important parameter for adaptability. A critical review of international overcrowding indicators and their application in two developing countries, Cape Verde and Angola, is presented. The several rationales and the constraints for an accurate assessment of overcrowding are considered, namely baseline data (statistics), which can induce misjudgments, as well as social and cultural factors (such as personal choices of residents). This paper proposes a way to tackle overcrowding through housing adaptability, considering factors such as physical flexibility, functional ambiguity, and incremental expansion schemes. Moreover, a case-study is presented to establish a framework for the theoretical application of the proposed approach.

Keywords: adaptive housing, low cost housing, overcrowding, housing model

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Authors: Elena Tkachenko, Vladimir Kokh, Alina Osipenko, Vladislav Surkov

Abstract:

The modern period of development of Russian economy is fraught with a number of problems related to limitations in the use of traditional planning and financial management tools. Restrictions in the use of foreign software when performing an order of the Russian Government, on the one hand, and sanctions limiting the support of the major ERP and MRP II systems in the Russian Federation, on the other hand, entail the necessity to appeal to the basics of developing budgeting and analysis systems for industrial enterprises. Thus, cost calculation theory becomes the theoretical foundation for the development of industrial cost management systems. Based on the foregoing, it would be fair to make an assumption that the development of a working managerial accounting model on an industrial enterprise using an automated enterprise resource management system should rest upon the concept of the inevitability of alterations of business processes. On the other hand, optimized business processes make the architecture of financial analytics more transparent and permit the use of all the benefits of data cubes. The metrics and indicator slices provide online assessment of the state of key business processes at a given moment of time, which improves the quality of managerial decisions considerably. Therefore, the bilateral sanctions situation boosted the development of corporate business analytics and took industrial companies to the next level of understanding of business processes.

Keywords: cost culculation, ERP, OLAP, modern Russian economy

Procedia PDF Downloads 207