Search results for: effective demand

Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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The paper discusses the main aspects involved in the development of a supply chain management system using the newly developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: demand forecasting, machine learning, risk management, supply chain design

Procedia PDF Downloads 61

Authors: Yuang Guo, Dewancker Bart

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The primary energy consumption of buildings throughout China was approximately 814 million tons of coal equivalents in 2014, which accounts for 19.12% of China's total primary energy consumption. Also, the energy consumption of public buildings takes a bigger share than urban residential buildings and rural residential buildings among the total energy consumption. To improve the level of energy demand, various design parameters were chosen. Meanwhile, a series of simulations by Energy Plus (EP-Launch) is performed using a base case model established in Open Studio. Through the results, 16%-23% of total energy demand reductions can be found in the severe cold zone of China, and it can also provide a reference for the architectural design of other similar climate zones.

Keywords: energy consumption, design parameters, indoor thermal comfort, simulation study, severe cold climate zone

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Authors: Mohammed Alaa Alwafaie, Bela Kovacs

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With the rapid emergence and evolution of renewable energy sources like wind and solar power, there is an increasing demand for effective energy harvester architectures. This paper focuses on investigating the concept of energy harvesting using a wheel-motion energy source. The proposed method involves the placement of magnets and copper coils inside the hubcap rod of a wheel. When the wheel is set in motion, following Faraday's Law, the movement of the magnet within the coil induces an electric current. The paper includes an experiment to measure the output voltage of electromagnetics, as well as a numerical simulation to further explore the potential of this energy harvesting approach. By harnessing the rotational motion of wheels, this research aims to contribute to the development of innovative techniques for generating electrical power in a sustainable and efficient manner.

Keywords: harvesting energy, electromagnetic, hubcap rod wheel, magnet movement inside coil, faraday law

Procedia PDF Downloads 52

Authors: Salman Al-Alyani

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In line with the Kingdom’s Vision 2030, the Saudi Green initiative was announced aimed at reducing carbon emissions by more than 4% of the global contribution. The initiative included plans to generate 50% of its energy from renewables by 2030. The geographical location of Saudi Arabia makes it among the best countries in terms of solar irradiation and has good wind resources in many areas across the Kingdom. Saudi Arabia is a wide country and has many remote locations where it is not economically feasible to connect those loads to the national grid. With the improvement of battery innovation and reduction in cost, different renewable technologies (primarily wind and solar) can be integrated to meet the need for energy in a more effective and cost-effective way. Saudi Arabia is famous for high solar irradiations in which solar power generation can extend up to six (6) hours per day (25% capacity factor) in some locations. However, the net present value (NPV) falls down to negative in some locations due to distance and high installation costs. Wind generation in Saudi Arabia is a promising technology. Hybrid renewable generation will increase the net present value and lower the payback time due to additional energy generated by wind. The infrastructure of the power system can be capitalized to contain solar generation and wind generation feeding the inverter, controller, and load. Storage systems can be added to support the hours that have an absence of wind or solar energy. Also, the smart controller that can help integrate various renewable technologies primarily wind and solar, to meet demand considering load characteristics. It could be scalable for grid or off-grid applications. The objective of this paper is to study the feasibility of introducing a hybrid renewable system in remote locations and the concept for the development of a smart controller.

Keywords: battery storage systems, hybrid power generation, solar energy, wind energy

Procedia PDF Downloads 154

Authors: T. Yuri M. Zagloel, Inaki M. Hakim, Syarafi A. M.

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Manufacturing process has been considered as one of the most important activity in business process. It correlates with productivity and quality of the product so industries could fulfill customer’s demand. With the increasing demand from customer, industries must improve their manufacturing ability such as shorten lead time and reduce wastes on their process. Lean manufacturing has been considered as one of the tools to waste elimination in manufacturing or service industri. Workforce development is one practice in lean manufacturing that can reduce waste generated from operator such as waste of unnecessary motion. Anthropometric approach is proposed to determine the recommended measurement in operator’s work area. The method will get some dimensions from Indonesia people that related to piston workstation. The result from this research can be obtained new design for the workarea considering ergonomic aspect.

Keywords: adjustable, anthropometric, ergonomic, waste

Procedia PDF Downloads 384

Authors: Khashayar Kazemzadeh, Mohammad Hanif Dasoomi

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According to the increasing volume of traffic, lane changing plays a crucial role in traffic flow. Lane changing in traffic depends on several factors including road geometrical design, speed, drivers’ behavioral characteristics, etc. A great deal of research has been carried out regarding these fields. Despite of the other significant factors, the drivers’ behavioral characteristics of lane changing has been emphasized in this paper. This paper has predicted the effective equation based on personal characteristics of lane changing by regression models.

Keywords: effective equation, lane changing, drivers’ behavioral characteristics, regression models

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Authors: A. H. Nanher, N. P. Singh, Shashidhar Yadav, Sachin Tyagi

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Agricultural production system is an outcome of a complex interaction of seed, soil, water and agro-chemicals (including fertilizers). Therefore, judicious management of all the inputs is essential for the sustainability of such a complex system. Precision agriculture gives farmers the ability to use crop inputs more effectively including fertilizers, pesticides, tillage and irrigation water. More effective use of inputs means greater crop yield and/or quality, without polluting the environment the focus on enhancing the productivity during the Green Revolution coupled with total disregard of proper management of inputs and without considering the ecological impacts, has resulted into environmental degradation. To evaluate a new approach for site-specific nutrient management (SSNM). Large variation in initial soil fertility characteristics and indigenous supply of N, P, and K was observed among Field- and season-specific NPK applications were calculated by accounting for the indigenous nutrient supply, yield targets, and nutrient demand as a function of the interactions between N, P, and K. Nitrogen applications were fine-tuned based on season-specific rules and field-specific monitoring of crop N status. The performance of SSNM did not differ significantly between high-yielding and low-yielding climatic seasons, but improved over time with larger benefits observed in the second year Future, strategies for nutrient management in intensive rice systems must become more site-specific and dynamic to manage spatially and temporally variable resources based on a quantitative understanding of the congruence between nutrient supply and crop demand. The SSNM concept has demonstrated promising agronomic and economic potential. It can be used for managing plant nutrients at any scale, i.e., ranging from a general recommendation for homogenous management of a larger domain to true management of between-field variability. Assessment of pest profiles in FFP and SSNM plots suggests that SSNM may also reduce pest incidence, particularly diseases that are often associated with excessive N use or unbalanced plant nutrition.

Keywords: nutrient, pesticide, crop, yield

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Authors: T. Godwin

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The design of a supply chain always entails the trade-off between responsiveness and efficiency. The launch of e-commerce has not only changed the way of shopping but also altered the supply chain design while trading off efficiency with responsiveness. A concept called ‘virtual responsiveness’ is introduced in the context of e-commerce supply chain. A simulation model is developed to compare actual responsiveness and virtual responsiveness to the customer in an e-commerce supply chain. The simulation is restricted to the movement of goods from the e-tailer to the customer. Customer demand follows a statistical distribution and is generated using inverse transformation technique. The two responsiveness schemes of the supply chain are compared in terms of the minimum number of inventory required at the e-tailer to fulfill the orders. Computational results show the savings achieved through virtual responsiveness. The insights gained from this study could be used to redesign e-commerce supply chain by incorporating virtual responsiveness. A part of the achieved cost savings could be passed back to the customer, thereby making the supply chain both effective and competitive.

Keywords: e-commerce, simulation modeling, supply chain, virtual responsiveness

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Authors: Sheikh Saeed Ahmad

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Electricity is vital for any state’s development that needs policy for planning the power network extension. This study is about simulation modeling for electricity in Balochistan province. Baseline data of electricity consumption was used of year 2004 and projected with the help of LEAP model up to subsequent 30 years. Three scenarios were created to run software. One scenario was baseline and other two were alternative or green scenarios i.e. solar and wind energy scenarios. Present study revealed that Balochistan has much greater potential for solar and wind energy for electricity production. By adopting these alternative energy forms, Balochistan can save energy in future nearly 23 and 48% by incorporating solar and wind power respectively. Thus, the study suggests to government planners, an aspect of integrating renewable sources in power system for ensuring sustainable development and growth.

Keywords: demand and supply, LEAP, solar energy, wind energy, households

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Authors: Mohammed Al Awadh

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In order for businesses to take advantage of the opportunities for expanded production and trade that have arisen as a result of globalization and increased levels of competition, productivity growth is required. The number of available sources is decreasing with each passing day, which results in an ever-increasing demand. In response to this, there will be an increased demand placed on firms to improve the efficiency with which they utilise their resources. As a scientific method, work and time research techniques have been employed in all manufacturing and service industries to raise the efficiency of use of the factors of production. These approaches focus on work and time. The goal of this research is to improve the productivity of a manufacturing industry's production system by looking at ways to measure work. The work cycles were broken down into more manageable and quantifiable components. On the observation sheet, these aspects were noted down. The operation has been properly analysed in order to identify value-added and non-value-added components, and observations have been recorded for each of the different trails.

Keywords: time study, work measurement, work study, efficiency

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

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Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

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Authors: Abubakar Uba Ibrahim, Ibrahim Haruna Shanono

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Smart metering and demand response are gaining ground in industrial and residential applications. Smart Appliances have been given concern towards achieving Smart home. The success of Smart grid development relies on the successful implementation of Information and Communication Technology (ICT) in power sector. Smart Appliances have been the technology under development and many new contributions to its realization have been reported in the last few years. The role of ICT here is to capture data in real time, thereby allowing bi-directional flow of information/data between producing and utilization point; that lead a way for the attainment of Smart appliances where home appliances can communicate between themselves and provide a self-control (switch on and off) using the signal (information) obtained from the grid. This paper depicts the background on ICT for smart appliances paying a particular attention to the current technology and identifying the future ICT trends for load monitoring through which smart appliances can be achieved to facilitate an efficient smart home system which promote demand response program. This paper grouped and reviewed the recent contributions, in order to establish the current state of the art and trends of the technology, so that the reader can be provided with a comprehensive and insightful review of where ICT for smart appliances stands and is heading to. The paper also presents a brief overview of communication types, and then narrowed the discussion to the load monitoring (Non-intrusive Appliances Load Monitoring ‘NALM’). Finally, some future trends and challenges in the further development of the ICT framework are discussed to motivate future contributions that address open problems and explore new possibilities.

Keywords: communication technology between appliances, demand response, load monitoring, smart appliances, smart grid

Procedia PDF Downloads 582

Authors: A. S. Zgalei, B. T. Al-Mabrouk

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With a particularly significant growth rate observed in the Libyan commercial and residential buildings coupled with a growth in energy demand, solar desiccant evaporative cooling offers energy savings and promises a good sharing for sustainable buildings where the availability of solar radiation matches with the cooling load demand. The paper presents a short introduction for the desiccant systems. A mathematical model of a selected system has been developed and a simulation has been performed in order to investigate the system performance at different working conditions and an optimum design of the system structure is established. The results showed a technical feasibility of the system working under the Libyan climatic conditions with a reasonable COP at temperatures that can be obtained through the solar reactivation system. Discussion of the results and the recommendations for future work are proposed.

Keywords: computer program, solar desiccant wheel cooling, system modelling, simulation, technical feasibility

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Authors: Samira Mohabbatdar, Abbas Ahmadi, Mohsen S. Sajadieh

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This paper deals with a two-level supply chain consisted of one manufacturer and one retailer for single-type product. The demand function of the customers depends on price. We consider an integrated production inventory system where the manufacturer processes raw materials in order to deliver finished product with imperfect quality to the retailer. Then retailer inspects the products and after that delivers perfect products to customers. The proposed model is based on the joint total profit of both the manufacturer and the retailer, and it determines the optimal ordering lot-size, number of shipment and selling price of the retailer. A numerical example is provided to analyse and illustrate the behaviour and application of the model. Finally, sensitivity analysis of the key parameters are presented to test feasibility of the model.

Keywords: supply chain, pricing policy, defective quality, joint economic lot sizing

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Authors: M. Pramila Devi, J. Praveena

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In today’s industrial scenario, the expectations and demand of customers are reaching great heights. In order to satisfy the customer requirements the users are increasingly turning towards fourth party logistics (4PL) service providers to manage their total supply chain operations. In this present research, initially, the criteria for the selection of integrated service providers have been identified and an integrated modal based on their inter-relationship has been developed with help of shippers, with this idea of what factors to be considered and their inter-relationships while selecting integrated service provider. Later, various methods deriving the priority weights viz. Analytical Hierarchy Process (AHP) have been employed for 4PL service provider selection. The derived priorities of 4PL alternatives using methods have been critically analyzed and compared for effective selection. The use of the modal indicates that the computed quantitative evaluation can be applied to improve the precision of the selection.

Keywords: analytical hierarchy process, fourth party logistics, priority weight, criteria selection

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Authors: Collen Tebogo Masilo, Erik Schmikl

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The demand for the DataMiner product by customers has presented a great challenge for the vendor in Skyline Communications in deploying its limited resources in the form of human resources, financial resources, and office space, to achieve high organisational performance in all its international operations. The rapid growth of the organisation has been unable to efficiently support its existing customers across the globe, and provide services to new customers, due to the limited number of approximately one hundred employees in its employ. The combined descriptive and explanatory case study research methods were selected as research design, making use of a survey questionnaire which was distributed to a sample of 100 respondents. A sample return of 89 respondents was achieved. The sampling method employed was non-probability sampling, using the convenient sampling method. Frequency analysis and correlation between the subscales (the four themes) were used for statistical analysis to interpret the data. The investigation was conducted into mechanisms that can be deployed to balance the high demand for products and the limited production capacity of the company’s Belgian operations across four aspects: demand management strategies, capacity management strategies, communication methods that can be used to align a sales management department, and reward systems in use to improve employee performance. The conclusions derived from the theme ‘demand management strategies’ are that the company is fully aware of the future market demand for its products. However, there seems to be no evidence that there is proper demand forecasting conducted within the organisation. The conclusions derived from the theme 'capacity management strategies' are that employees always have a lot of work to complete during office hours, and, also, employees seem to need help from colleagues with urgent tasks. This indicates that employees often work on unplanned tasks and multiple projects. Conclusions derived from the theme 'communication methods used to align sales management department with operations' are that communication is not good throughout the organisation. This means that information often stays with management, and does not reach non-management employees. This also means that there is a lack of smooth synergy as expected and a lack of good communication between the sales department and the projects office. This has a direct impact on the delivery of projects to customers by the operations department. The conclusions derived from the theme ‘employee reward systems’ are that employees are motivated, and feel that they add value in their current functions. There are currently no measures in place to identify unhappy employees, and there are also no proper reward systems in place which are linked to a performance management system. The research has made a contribution to the body of research by exploring the impact of the four sub-variables and their interaction on the challenges of organisational productivity, in particular where an organisation experiences a capacity problem during its growth stage during tough economic conditions. Recommendations were made which, if implemented by management, could further enhance the organisation’s sustained competitive operations.

Keywords: high demand for products, high organisational performance, limited production capacity, limited resources

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Authors: B. Philip, J. Littlewood, R. Radford, N. Evans, T. Whyman, D. P. Jones

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UK buildings and energy infrastructures are heavily dependent on natural gas, a large proportion of which is used for domestic space heating. However, approximately half of the gas consumed in the UK is imported. Improving energy security and reducing carbon emissions are major government drivers for reducing gas dependency. In order to do so there needs to be a wholesale shift in the energy provision to householders without impacting on thermal comfort levels, convenience or cost of supply to the end user. Heat pumps are seen as a potential alternative in modern well insulated homes, however, can the same be said of older homes? A large proportion of housing stock in Britain was built prior to 1919. The age of the buildings bears testimony to the quality of construction; however, their thermal performance falls far below the minimum currently set by UK building standards. In recent years significant sums of money have been invested to improve energy efficiency and combat fuel poverty in some of the most deprived areas of Wales. Increasing energy efficiency of older properties remains a significant challenge, which cannot be achieved through insulation and air-tightness interventions alone, particularly when alterations to historically important architectural features of the building are not permitted. This paper investigates the energy demand of pre-1919 dwellings in a former Welsh mining village, the feasibility of meeting that demand using water from the disused mine workings to supply a district heat network and potential barriers to success of the scheme. The use of renewable solar energy generation and storage technologies, both thermal and electrical, to reduce the load and offset increased electricity demand, are considered. A wholistic surveying approach to provide a more accurate assessment of total household heat demand is proposed. Several surveying techniques, including condition surveys, air permeability, heat loss calculations, and thermography were employed to provide a clear picture of energy demand. Additional insulation can bring unforeseen consequences which are detrimental to the fabric of the building, potentially leading to accelerated dilapidation of the asset being ‘protected’. Increasing ventilation should be considered in parallel, to compensate for the associated reduction in uncontrolled infiltration. The effectiveness of thermal performance improvements are demonstrated and the detrimental effects of incorrect material choice and poor installation are highlighted. The findings show estimated heat demand to be in close correlation to household energy bills. Major areas of heat loss were identified such that improvements to building thermal performance could be targeted. The findings demonstrate that the use of heat pumps in older buildings is viable, provided sufficient improvement to thermal performance is possible. Addition of passive solar thermal and photovoltaic generation can help reduce the load and running cost for the householder. The results were used to predict future heat demand following energy efficiency improvements, thereby informing the size of heat pumps required.

Keywords: heat demand, heat pump, renewable energy, retrofit

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Authors: Mirzahmedov Ismoiljon Karimjon Ugli, Juraeva Shakhnoza Abdumalik Kizi

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The article deals with the current scientific problems of natural geography related to the development of new pedagogical technologies and their implementation in the educational process. The use of recommended interactive methods in independent study is considered very effective and is a very useful method for students, especially for students who work more on themselves. Today's demand is to make young people talented, intelligent, innovative, as well as mature and well-rounded individuals, as a result of the work carried out in the field of education today. This is how creating tables of different contents and filling them out shows the student's talent and desire for innovation. Also, the techniques and methods necessary for today's student are shown, the role of the teacher in conducting lessons meaningfully, the suitability of the method used by the teacher for the lesson, factors affecting the quality of education, and natural issues of the use of methods based on the specific features of geography are highlighted.

Keywords: teaching methods, educational process, educational technologies, education, problem, didactics, natural geography

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Authors: Sameh S. Namnqani, Yaqoob Y. Abobakar, Ahmed M. Alsewehri, Khaled M. AlQethami

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The main objective of this research is to know the impact of the application of the electronic supply system on the performance of the supply department of health organizations. To reach this goal, the study adopted independent variables to measure the dependent variable (performance of the supply department), namely: integration with suppliers, integration with intermediaries and distributors and knowledge of supply size, inventory, and demand. The study used the descriptive method and was aided by the questionnaire tool that was distributed to a sample of workers in the Supply Chain Management Department of King Abdullah Medical City. After the statistical analysis, the results showed that: The 70 sample members strongly agree with the (electronic integration with suppliers) axis with a p-value of 0.001, especially with regard to the following: Opening formal and informal communication channels between management and suppliers (Mean 4.59) and exchanging information with suppliers with transparency and clarity (Mean 4.50). It also clarified that the sample members agree on the axis of (electronic integration with brokers and distributors) with a p-value of 0.001 and this is represented in the following elements: Exchange of information between management, brokers and distributors with transparency, clarity (Mean 4.18) , and finding a close cooperation relationship between management, brokers and distributors (Mean 4.13). The results also indicated that the respondents agreed to some extent on the axis (knowledge of the size of supply, stock, and demand) with a p-value of 0.001. It also indicated that the respondents strongly agree with the existence of a relationship between electronic procurement and (the performance of the procurement department in health organizations) with a p-value of 0.001, which is represented in the following: transparency and clarity in dealing with suppliers and intermediaries to prevent fraud and manipulation (Mean 4.50) and reduce the costs of supplying the needs of the health organization (Mean 4.50). From the results, the study recommended several recommendations, the most important of which are: that health organizations work to increase the level of information sharing between them and suppliers in order to achieve the implementation of electronic procurement in the supply management of health organizations. Attention to using electronic data interchange methods and using modern programs that make supply management able to exchange information with brokers and distributors to find out the volume of supply, inventory, and demand. To know the volume of supply, inventory, and demand, it recommended the application of scientific methods of supply for storage. Take advantage of information technology, for example, electronic data exchange techniques and documents, where it can help in contact with suppliers, brokers, and distributors, and know the volume of supply, inventory, and demand, which contributes to improving the performance of the supply department in health organizations.

Keywords: healthcare supply chain, performance, electronic system, ERP

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Authors: Mohamed Sifan, Brabha Nagaratnam, Julian Thamboo, Keerthan Poologanathan

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Ultra high performance concrete (UHPC) is a type of cementitious material known for its exceptional strength, ductility, and durability. However, its production is often associated with high costs due to the significant amount of cementitious materials required and the use of fine powders to achieve the desired strength. The aim of this research is to explore the feasibility of developing cost-effective UHPC mixes using locally available materials. Specifically, the study aims to investigate the use of coarse limestone sand along with other sand types, namely, basalt sand, dolomite sand, and river sand for developing UHPC mixes and evaluating its performances. The study utilises the particle packing model to develop various UHPC mixes. The particle packing model involves optimising the combination of coarse limestone sand, basalt sand, dolomite sand, and river sand to achieve the desired properties of UHPC. The developed UHPC mixes are then evaluated based on their workability (measured through slump flow and mini slump value), compressive strength (at 7, 28, and 90 days), splitting tensile strength, and microstructural characteristics analysed through scanning electron microscope (SEM) analysis. The results of this study demonstrate that cost-effective UHPC mixes can be developed using locally available materials without the need for silica fume or fly ash. The UHPC mixes achieved impressive compressive strengths of up to 149 MPa at 28 days with a cement content of approximately 750 kg/m³. The mixes also exhibited varying levels of workability, with slump flow values ranging from 550 to 850 mm. Additionally, the inclusion of coarse limestone sand in the mixes effectively reduced the demand for superplasticizer and served as a filler material. By exploring the use of coarse limestone sand and other sand types, this study provides valuable insights into optimising the particle packing model for UHPC production. The findings highlight the potential to reduce costs associated with UHPC production without compromising its strength and durability. The study collected data on the workability, compressive strength, splitting tensile strength, and microstructural characteristics of the developed UHPC mixes. Workability was measured using slump flow and mini slump tests, while compressive strength and splitting tensile strength were assessed at different curing periods. Microstructural characteristics were analysed through SEM and energy dispersive X-ray spectroscopy (EDS) analysis. The collected data were then analysed and interpreted to evaluate the performance and properties of the UHPC mixes. The research successfully demonstrates the feasibility of developing cost-effective UHPC mixes using locally available materials. The inclusion of coarse limestone sand, in combination with other sand types, shows promising results in achieving high compressive strengths and satisfactory workability. The findings suggest that the use of the particle packing model can optimise the combination of materials and reduce the reliance on expensive additives such as silica fume and fly ash. This research provides valuable insights for researchers and construction practitioners aiming to develop cost-effective UHPC mixes using readily available materials and an optimised particle packing approach.

Keywords: cost-effective, limestone powder, particle packing model, ultra high performance concrete

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Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

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Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

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Authors: Shaila Rana, Wasim Alhamdani

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Effective cybersecurity training is of the utmost importance, given the plethora of attacks that continue to increase in complexity and ubiquity. VR cybersecurity training remains a starkly understudied discipline. Studies that evaluated the effectiveness of VR cybersecurity training over traditional methods are required. An engaging and interactive platform can support knowledge retention of the training material. Consequently, an effective form of cybersecurity training is required to support a culture of cybersecurity awareness. Measurements of effectiveness varied throughout the studies, with surveys and observations being the two most utilized forms of evaluating effectiveness. Further research is needed to evaluate the effectiveness of VR cybersecurity training and traditional training. Additionally, research for evaluating if VR cybersecurity training is more effective than traditional methods is vital. This paper proposes a methodology to compare the two cybersecurity training methods and their effectiveness. The proposed framework includes developing both VR and traditional cybersecurity training methods and delivering them to at least 100 users. A quiz along with a survey will be administered and statistically analyzed to determine if there is a difference in knowledge retention and user satisfaction. The aim of this paper is to bring attention to the need to study VR cybersecurity training and its effectiveness compared to traditional training methods. This paper hopes to contribute to the cybersecurity training field by providing an effective way to train users for security awareness. If VR training is deemed more effective, this could create a new direction for cybersecurity training practices.

Keywords: virtual reality cybersecurity training, VR cybersecurity training, traditional cybersecurity training

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Authors: Dilek Turan Eroğlu

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Educators have been searching the more effective and appalling methods of teaching for ages. It has always been an issue among the teachers and scientists to improve the quality of education and to ensure that all students have equal opportunities to learn. However, when it comes to the effective ways of learning,the learners are exposed to the ways which are chosen and approved to be effective by their teachers not by the learners themselves. This is the main problem of this study as the learners are not always happy to be in their classes being treated with their teachers’ favourite styles. This paper is telling the results of a study which has been conducted with the university students in Turkey. The students have been interviewed and asked to respond some questions related to best practices to find out their favourite styles, medium, techniques and strategies. The study has been conducted using qualitative research methods i.e one to one interviews and group discussions. The results show that the learners have significantly different views than the educators when it comes to modern teaching styles. Their definition of the term “modern teaching styles” is different than the general understanding. The university students expect their teachers to be “early adopter”. of ICT tools and or the other electronic devices, but a modern teacher must have many other characteristics for them.

Keywords: effective, innovation, teaching, modern teaching styles

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Authors: B. Sudhakara Reddy

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The transition to a clean and green energy system is an economic and social transformation that is exciting as well as challenging. The world today faces a formidable challenge in transforming its economy from being driven primarily by fossil fuels, which are non-renewable and a major source of global pollution, to becoming an economy that can function effectively using renewable energy sources and by achieving high energy efficiency levels. In the present study, a green economy scenario is developed for India using a bottom-up approach. The results show that the penetration rate of renewable energy resources will reduce the total primary energy demand by 23% under GE. Improvements in energy efficiency (e.g. households, industrial and commercial sectors) will result in reduced demand to the tune of 318 MTOE. The volume of energy-related CO2 emissions decline to 2,218 Mt in 2030 from 3,440 under the BAU scenario and the per capita emissions will reduce by about 35% (from 2.22 to 1.45) under the GE scenario. The reduction in fossil fuel demand and focus on clean energy will reduce the energy intensity to 0.21 (TOE/US$ of GDP) and carbon intensity to 0.42 (ton/US$ of GDP) under the GE scenario. total import bill (coal and oil) will amount to US$ 334 billion by 2030 (at 2010/11 prices), but as per the GE scenario, it would be US$ 194.2 billion, a saving of about US$ 140 billion. The building of a green energy economy can also serve another purpose: to develop new ‘pathways out of poverty’ by creating more than 10 million jobs and thus raise the standard of living of low-income people. The differences between the baseline and green energy scenarios are not so much the consequence of the diffusion of various technologies. It is the result of the active roles of different actors and the drivers that become dominant.

Keywords: emissions, green energy, fossil fuels, green jobs, renewables, scenario

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Sawanath Treesathon

Abstract:

As there are several countries which import agriculture product from Thailand, those countries demand Thailand to establish the traceability system. The traceability system is the tool to reduce the risk in the supply chain in a very effective way as it will help the stakeholder in the supply chain to identify the defect point which will reduce the cost of operation in the supply chain. This research is aimed to design the traceability system for Tubtimjun roseapple for exporting to China, and it is the qualitative research. The data was collected from the expert in the tuntimjun roseapple and fruit exporting industry, and the data was used to design the traceability system. The design of the tubtimjun roseapple traceability system was followed the theory of supply chain which starts from the upstream of the supply chain to the downstream of the supply chain to support the process and condition of the exporting which included the database designing, system architecture, user interface design and information technology of the traceability system.

Keywords: design information, technology system, traceability, tubtimjun roseapple

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Authors: Philipp Sommer, Amgad Agoub

Abstract:

The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Catia S. A. Sima, K. Bousson

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Congestion in the Terminal Maneuvering Areas (TMAs) of larger airports impacts all aspects of air traffic flow, not only at national level but may also induce arrival delays at international level. Hence, there is a need to monitor appropriately the air traffic flow in TMAs so that efficient decisions may be taken to manage their occupancy rates. It would be desirable to physically increase the existing airspace to accommodate all existing demands, but this question is entirely utopian and, given this possibility, several studies and analyses have been developed over the past decades to meet the challenges that have arisen due to the dizzying expansion of the aeronautical industry. The main objective of the present paper is to propose concepts to manage and reduce the degree of uncertainty in the air traffic operations, maximizing the interest of all involved, ensuring a balance between demand and supply, and developing and/or adapting resources that enable a rapid and effective adaptation of measures to the current context and the consequent changes perceived in the aeronautical industry. A central task is to emphasize the increase in air traffic flow management capacity to the present day, taking into account not only a wide range of methodologies but also equipment and/or tools already available in the aeronautical industry. The efficient use of these resources is crucial as the human capacity for work is limited and the actors involved in all processes related to air traffic flow management are increasingly overloaded and, as a result, operational safety could be compromised. The methodology used to answer and/or develop the issues listed above is based on the advantages promoted by the application of Markov Chain principles that enable the construction of a simplified model of a dynamic network that describes the air traffic flow behavior anticipating their changes and eventual measures that could better address the impact of increased demand. Through this model, the proposed concepts are shown to have potentials to optimize the air traffic flow management combined with the operation of the existing resources at each moment and the circumstances found in each TMA, using historical data from the air traffic operations and specificities found in the aeronautical industry, namely in the Portuguese context.

Keywords: air traffic flow, terminal maneuvering area, TMA, air traffic management, ATM, Markov chains

Procedia PDF Downloads 107

Authors: Seung Yeon Son

Abstract:

In today’s rapidly changing and increasingly complex environment, organizations have relied on their members’ positive attitude toward their employers. In particular, employees’ organizational commitment (primarily, the effective component) has been recognized as an essential component of organizational functioning and success. Hence, identifying the determinants of effective commitment is one of the most important research issues. This study tested the influence of leader-member exchange (LMX) and exchange ideology on employee’s effective commitment. In addition, the interactive effect of LMX and exchange ideology was examined. Data from 198 members of the Korean military supports each of the hypotheses. Lastly, implications for research and directions for future research are discussed.

Keywords: affective commitment, exchange ideology, leader-member exchange, commitment

Procedia PDF Downloads 405