Search results for: low cost housing scheme

Authors: Jackie Oakley, Alice V. Brown

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Those experiencing homelessness are regularly excluded from the development of policies and services that impact their lives. This is particularly true for Aboriginal and Torres Strait Islander people experiencing homelessness in Australia, who tend to have differing needs, cultural obligations, and views of what equates to a ‘home’ and ‘homelessness’ than non-Aboriginal Australians. Aboriginal people are the traditional owners of Australia yet have had to survive within colonial housing customs, housing and homelessness policies, and markets that often conflict with their culture. Recognising this, in 2022, we commenced community-led research into the needs of Aboriginal people experiencing homelessness in Perth. Historically, research has often been done on Aboriginal people rather than with them. As such, a Participatory Action Research methodology was chosen, which recognises that those being researched are the experts of their circumstances rather than the research team, and facilitates their driving of the research, its questions, and how their community can directly benefit. A Community Ownership Group (COG) was formed to guide this process and negotiate the best ways that the Aboriginal community can be fairly and adequately involved. The COG approved a process developed by an Aboriginal Elder called Ngala Kadidjiny (Knowledge Vault), which outlines who and when various groups should be consulted throughout the research to ensure adequate involvement of the Aboriginal community at all stages. The process includes many markers of research integrity, including ensuring a Community Ownership Group is formed with diversity and recruiting its members through votes taking place within Elders groups across the metropolitan area. The process also demands that the community have the chance to review research findings before any findings are published. Additionally, the process asks that draft reports and findings are delivered to the broader community and Community Ownership Groups before being finalised, published, and shared officially with stakeholders and the government. This paper details how Ngala Kadidjiny’s process impacted the research, how it was explained and agreed upon by the Aboriginal community, the benefits and challenges of such a process, and its implications for other community-led research for and with Aboriginal people experiencing homelessness.

Keywords: Aboriginal and Torres Strait Islander peoples, Aboriginal elders, homelessness, community-led research, community consultation

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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: Ahmed Al-Adaileh

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Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

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Authors: Kong Ngai Pei

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The argument scheme approach to argumentation has two components. One is to identify the recurrent patterns of inferences used in everyday discourse. The second is to devise critical questions to evaluate the inferences in these patterns. Although this approach is intuitive and contains many insightful ideas, it has been noted to be not free of problems. One is that due to its disavowing the probability calculus, it cannot give the exact strength of an inference. In order to tackle this problem, thereby paving the way to a more complete normative account of argument strength, it has been proposed, the most promising way is to combine the scheme-based approach with Bayesian networks (BNs). This paper pursues this line of thought, attempting to combine three common schemes, Appeal to Ignorance, Composition, and Division, with BNs. In the first part, it is argued that most (if not all) formulations of the critical questions corresponding to these schemes in the current argumentation literature are incomplete and not very informative. To remedy these flaws, more thorough and precise formulations of these questions are provided. In the second part, how to use graphical idioms (e.g. measurement and synthesis idioms) to translate the schemes as well as their corresponding critical questions to graphical structure of BNs, and how to define probability tables of the nodes using functions of various sorts are shown. In the final part, it is argued that many misuses of these schemes, traditionally called fallacies with the same names as the schemes, can indeed be adequately accounted for by the BN models proposed in this paper.

Keywords: appeal to ignorance, argument schemes, Bayesian networks, composition, division

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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: H. Jung, N. Kim, B. Kang, J. Choe

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History matching is a crucial procedure for predicting reservoir performances and making future decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it is important to have reliable initial models for successful history matching of highly heterogeneous reservoirs such as channel reservoirs. In this paper, we proposed a novel scheme for regenerating geological models using support vector machine (SVM) and principal component analysis (PCA). First, we perform PCA for figuring out main geological characteristics of models. Through the procedure, permeability values of each model are transformed to new parameters by principal components, which have eigenvalues of large magnitude. Secondly, the parameters are projected into two-dimensional plane by multi-dimensional scaling (MDS) based on Euclidean distances. Finally, we train an SVM classifier using 20% models which show the most similar or dissimilar well oil production rates (WOPR) with the true values (10% for each). Then, the other 80% models are classified by trained SVM. We select models on side of low WOPR errors. One hundred channel reservoir models are initially generated by single normal equation simulation. By repeating the classification process, we can select models which have similar geological trend with the true reservoir model. The average field of the selected models is utilized as a probability map for regeneration. Newly generated models can preserve correct channel features and exclude wrong geological properties maintaining suitable uncertainty ranges. History matching with the initial models cannot provide trustworthy results. It fails to find out correct geological features of the true model. However, history matching with the regenerated ensemble offers reliable characterization results by figuring out proper channel trend. Furthermore, it gives dependable prediction of future performances with reduced uncertainties. We propose a novel classification scheme which integrates PCA, MDS, and SVM for regenerating reservoir models. The scheme can easily sort out reliable models which have similar channel trend with the reference in lowered dimension space.

Keywords: history matching, principal component analysis, reservoir modelling, support vector machine

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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: Hafizah Che Hasan, Fateen Nazwa Yusof, Maslina Daud

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Internet of Things (IoT) is a powerful industry system, which end-devices are interconnected and automated, allowing the devices to analyze data and execute actions based on the analysis. The IoT technology leverages the technology of Radio-Frequency Identification (RFID) and Wireless Sensor Network (WSN), including mobile and sensor. These technologies contribute to the evolution of IoT. However, due to more devices are connected each other in the Internet, and data from various sources exchanged between things, confidentiality of the data becomes a major concern. This paper focuses on one of the major challenges in IoT; authentication, in order to preserve data integrity and confidentiality are in place. A few solutions are reviewed based on papers from the last few years. One of the proposed solutions is securing the communication between IoT devices and cloud servers with Elliptic Curve Cryptograhpy (ECC) based mutual authentication protocol. This solution focuses on Hyper Text Transfer Protocol (HTTP) cookies as security parameter.  Next proposed solution is using keyed-hash scheme protocol to enable IoT devices to authenticate each other without the presence of a central control server. Another proposed solution uses Physical Unclonable Function (PUF) based mutual authentication protocol. It emphasizes on tamper resistant and resource-efficient technology, which equals a 3-way handshake security protocol.

Keywords: Internet of Things (IoT), authentication, PUF ECC, keyed-hash scheme protocol

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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: Almas Hamid, Ghazala Yaqub, Aqsa Riaz

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Qualitative validation was performed to detect the presence of persistent organic pollutants (POPs) in various wastewater samples collected from domestic sources (Askari XI housing society, Bedian road Lahore) industrial sources (PET bottles, pharmaceutical, textile) and a municipal drain (Hudiara drain) in Lahore. In addition wastewater analysis of the selected parameter was carried out. pH for wastewater samples from Askari XI, PET bottles, pharmaceutical, textile and Hudiara drain were 6.9, 6.7, 6.27, 7.18 and 7.9 respectively, within the NEQS Pakistan range that is 6-9. TSS for the respective samples was 194, 241, 254, 140 and 251 mg/L, in effluent for pet bottle industry, pharmaceutical and Hudiara drain and exceeded the NEQS Pakistan. Chemical oxygen demand (COD) for the wastewater samples was 896 mg/L, 166 mg/L, 419 mg/L, 812 mg/L and 610 mg/L respectively, all in excess of NEQS (150 mg/L). Similarly the biological oxygen demand (BOD) values (110.8, 170, 423, 355 and 560 mg/L respectively) were also above NEQS limits (80 mg/L). Chloride (Cl-) content, total dissolved solids (TDS) and temperature were found out to be within the prescribed standard limits. The POPs selected for analysis included five pesticides/insecticides (D. D, Karate, Commando, Finis insect killer, Bifenthrin) and three polycyclic aromatic hydrocarbons (PAHs) (naphthalene, anthracene, phenanthrene). Peak values of standards were compared with that of wastewater samples. The results showed the presence of D.D in all wastewater samples, pesticide Karate was identified in Askari XI and textile industry sample. Pesticide Commando, Finis (insect killer) and Bifenthrin were detected in Askari XI and Hudiara drain wastewater samples. In case of PAHs; naphthalene was identified in all the five wastewater samples whereas anthracene and phenanthrene were detected in samples of Askari XI housing society, PET bottles industry, pharmaceutical industry and textile industry but totally absent in Hudiara drain wastewater. Practical recommendations have been put forth to avoid hazardous impacts of incurred samples.

Keywords: HPLC studies, lahore, physicochemical analysis, wastewater

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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: 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: 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

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

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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

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

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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

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Authors: Abdallah Bouguettoucha, Derradji Chebli, Sara Aga, Agueniou Fazia

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The objective of this study was to looking for alternative materials (low cost) for the adsorption of textile dyes and optimizes the type which gives optimum adsorption and provides an explanation of the mechanism involved in the adsorption process. Adsorption of Orange II and Methylene blue on H2SO4 traited cone of Pinus brutia, was carried out at different initial concentrations of the dye (20, 50 and 100 mg / L) and at tow initial pH, pH 1 and 10 respectively. The models of Langmuir, Freundlich and Sips were used in this study to analyze the obtained results of the adsorption isotherm. PCB-0M had high adsorption capacities namely 32.8967 mg/g and 128.1651 mg/g, respectively for orange II and methylene blue and further indicated that the removal of dyes increased with increase in the ionic strength of solution, this was attributed to aggregation of dyes in solution. The potential of H2SO4 traited cone of Pinus brutia, an easily available and low cost material, to be used as an alternative biosorbent material for the removal of a dyes, Orange II and Methylene Bleu, from aqueous solutions was therefore confirmed.

Keywords: Methylene blue, orange II, cones of pinus brutia, adsorption

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Authors: N. P. Patidar, J. Earnest, Laxmikant Nagar, Akshay Sharma

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This paper describes the diligence of a new input signal based fuzzy power system stabilizer in multi-machine power system. Instead of conventional input pairs like speed deviation (∆ω) and derivative of speed deviation i.e. acceleration (∆ω ̇) or speed deviation and accelerating power deviation of each machine, in this paper, deviation of active power through the tie line colligating two areas is used as one of the inputs to the fuzzy logic controller in concurrence with the speed deviation. Fuzzy Logic has the features of simple concept, easy effectuation, and computationally efficient. The advantage of this input is that, the same signal can be fed to each of the fuzzy logic controller connected with each machine. The simulated system comprises of two fully symmetrical areas coupled together by two 230 kV lines. Each area is equipped with two superposable generators rated 20 kV/900MVA and area-1 is exporting 413 MW to area-2. The effectiveness of the proposed control scheme has been assessed by performing small signal stability assessment and transient stability assessment. The proposed control scheme has been compared with a conventional PSS. Digital simulation is used to demonstrate the performance of fuzzy logic controller.

Keywords: Power System Stabilizer (PSS), small signal stability, inter-area oscillation, fuzzy logic controller, membership function, rule base

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Authors: Elise Machline

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Policy instruments have been developed worldwide to reduce the energy demand of buildings. Two types of such instruments have been green building rating systems and energy efficiency standards for buildings -such as Green Star (Australia), LEED (United States, Leadership in Energy and Environmental Design), Energy Star (United States), and BREEAM (United Kingdom, Building Research Establishment Environmental Assessment Method). The popularity of the idea of sustainable development has allowed the actors to consider the potential value generated by the environmental performance of buildings, labeled “green value” in the literature. Sustainable performances of buildings are expected to improve their attractiveness, increasing their value. A growing number of empirical studies demonstrate that green buildings yield rental/sale premia, as well as higher occupancy rates and thus higher asset values. The results suggest that green buildings are not affordable to all and that their construction tends to have a gentrifying effect. An increasing number of countries are institutionalizing green strategies for affordable housing. In that sense, making green buildings affordable to all will depend on government policies. That research aims to investigate whether green building fosters inequality in Israel, under the banner of sustainability. The method is comparison (of the market value). This method involves comparing the green buildings sale prices with non-certified buildings of the same type that have undergone recent transactions. The “market value” is deduced from those sources by analogy. The results show that, in Israel, green building projects are usually addressed to the middle to upper classes. The green apartment’s sale premium is about 19% (comparing to non-certified dwelling). There is a link between energy and/or environmental performance and the financial value of the dwellings. Moreover, price differential is much higher than the value of energy savings. This perpetuates socio-spatial and socio-economic inequality as well as ecological vulnerability for the poor and other socially marginal groups. Moreover, there are no green affordable housings and the authorities do not subsidy green building or retrofitting.

Keywords: green building, gentrification, social housing, green value, green building certification

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Authors: Chang Liu, John Nash, Stephen D. Prior

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This paper presents the design and implementation details of a complete unmanned aerial system (UAS) based on commercial-off-the-shelf (COTS) components, focusing on safety, security, search and rescue scenarios in GPS-denied environments. In particular, the aerial platform is capable of semi-autonomously navigating through extremely low-light, GPS-denied indoor environments based on onboard sensors only, including a downward-facing optical flow camera. Besides, an additional low-cost payload camera system is developed to stream both infrared video and visible light video to a ground station in real-time, for the purpose of detecting sign of life and hidden humans. The total cost of the complete system is estimated to be $1150, and the effectiveness of the system has been tested and validated in practical scenarios.

Keywords: unmanned aerial system, commercial-off-the-shelf, extremely low-light, GPS-denied, optical flow, infrared video

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Authors: Syed Asif Ali Naqvi, Muhammad Azeem Tufail

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Inadequate sanitation causes direct costs of treating illnesses and loss of income through reduced productivity. This study estimated the economic cost of health (ECH) due to poor sanitation and factors determining the lack of access to latrine for the rural, backward hamlets and slums of district Faisalabad, Pakistan. Cross sectional data were collected and analyzed for the study. As the population under study was homogenous in nature, it is why a simple random sampling technique was used for the collection of data. Data of 440 households from 4 tehsils were gathered. The ordinary least square (OLS) model was used for health cost analysis, and the Probit regression model was employed for determining the factors responsible for inaccess to toilets. The results of the study showed that condition of toilets, situation of sewerage system, access to adequate sanitation, Cholera, diarrhea and dysentery, Water and Sanitation Agency (WASA) maintenance, source of medical treatment can plausibly have a significant connection with the dependent variable. Outcomes of the second model showed that the variables of education, family system, age, and type of dwelling have positive and significant sway with the dependent variable. Variable of age depicted an insignificant association with access to toilets. Variable of monetary expenses would negatively influence the dependent variable. Findings revealed the fact, health risks are often exacerbated by inadequate sanitation, and ultimately, the cost on health also surges. Public and community toilets for youths and social campaigning are suggested for public policy.

Keywords: sanitation, toilet, economic cost of health, water, Punjab

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Authors: Frimpong Kyeremeh, Albert Y. Appiah, Ben B. K. Ayawli

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Energy storage system (ESS) is an essential part of a microgrid (MG) because of its immense benefits to the economics and the stability of MG. For a direct current (DC) MG (DCMG) in which the generating units are mostly variable renewable energy generators, DC bus voltage fluctuation is inevitable; hence ESS is vital in managing the mismatch between load demand and generation. Besides, to accrue the maximum benefits of ESS in the microgrid, there is the need for proper sizing and location of the ESSs. In this paper, a performance comparison is made between two configurations of ESS; distributed battery energy storage system (D-BESS) and an aggregated (centralized) battery energy storage system (A-BESS), on the basis of stability and operational cost for a DCMG. The configuration consists of four households with rooftop PV panels and a wind turbine. The objective is to evaluate and analyze the technical efficiencies, cost effectiveness as well as controllability of each configuration. The MG is first modelled with MATLAB Simulink then, a mathematical model is used to determine the optimal size of the BESS that minimizes the total operational cost of the MG. The performance of the two configurations would be tested with simulations. The two configurations are expected to reduce DC bus voltage fluctuations, but in the cases of voltage stability and optimal cost, the best configuration performance will be determined at the end of the research. The work is in progress, and the result would help MG designers and operators to make the best decision on the use of BESS for DCMG configurations.

Keywords: aggregated energy storage system, DC bus voltage, DC microgrid, distributed battery energy storage, stability

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Authors: Michael John S. Maceda

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Waste has been a global concern aggravated by climate change. In the case of Imus, Cavite which in the past has little or no regard to waste experienced heavy flooding during August 19, 2013. This event led to a full blown implementation of Municipal Solid Waste Management integrating participation and the use of low-cost technology to reduce the amount of waste generated. The methodology employed by the city of Imus, provided a benchmark in the province of Cavite. Reducing the amount of waste generated and Solid Waste Management Cost.

Keywords: SWM, IMUS, composting, policy

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Authors: Paul Kipchumba

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Kenya is an East African Country lying at the Equator. It had a population of 46 million in 2015 with an annual growth rate of 2.7%, making a population of at least 65 million in 2030. Kenya’s GDP in 2015 was about 63 billion USD with per capita GDP of about 1400 USD. The rural population is 74%, whereas urban population is 26%. Kenya grapples with not only access to energy but also with energy security. There is direct correlation between economic growth, population growth, and energy consumption. Kenya’s energy composition is at least 74.5% from renewable energy with hydro power and geothermal forming the bulk of it; 68% from wood fuel; 22% from petroleum; 9% from electricity; and 1% from coal and other sources. Wood fuel is used by majority of rural and poor urban population. Electricity is mostly used for lighting. As of March 2015 Kenya had installed electricity capacity of 2295 MW, making a per capital electricity consumption of 0.0499 KW. The overall retail cost of electricity in 2015 was 0.009915 USD/ KWh (KES 19.85/ KWh), for installed capacity over 10MW. The actual demand for electricity in 2015 was 3400 MW and the projected demand in 2030 is 18000 MW. Kenya is working on vision 2030 that aims at making it a prosperous middle income economy and targets 23 GW of generated electricity. However, cost and non-cost factors affect generation and consumption of electricity in Kenya. Kenya does not care more about CO2 emissions than on economic growth. Carbon emissions are most likely to be paid by future costs of carbon emissions and penalties imposed on local generating companies by sheer disregard of international law on C02 emissions and climate change. The study methodology was a simulated application of carbon tax on all carbon emitting sources of electricity generation. It should cost only USD 30/tCO2 tax on all emitting sources of electricity generation to have solar as the only source of electricity generation in Kenya. The country has the best evenly distributed global horizontal irradiation. Solar potential after accounting for technology efficiencies such as 14-16% for solar PV and 15-22% for solar thermal is 143.94 GW. Therefore, the paper recommends adoption of solar power for generating all electricity in Kenya in order to attain zero carbon electricity generation in the country.

Keywords: co2 emissions, cost factors, electricity generation, non-cost factors

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Authors: M. Khazam, M. Altawil, A. Eljabri

Abstract:

Fluid properties in states near a vapor-liquid critical region are the most difficult to measure and to predict with EoS models. The principal model difficulty is that near-critical property variations do not follow the same mathematics as at conditions far away from the critical region. Libyan NC98 field in Sirte basin is a typical example of near critical fluid characterized by high initial condensate gas ratio (CGR) greater than 160 bbl/MMscf and maximum liquid drop-out of 25%. The objective of this paper is to model NC98 phase behavior with the proper selection of EoS parameters and also to model reservoir depletion versus gas cycling option using measured PVT data and EoS Models. The outcomes of our study revealed that, for accurate gas and condensate recovery forecast during depletion, the most important PVT data to match are the gas phase Z-factor and C7+ fraction as functions of pressure. Reasonable match, within -3% error, was achieved for ultimate condensate recovery at abandonment pressure of 1500 psia. The smooth transition from gas-condensate to volatile oil was fairly simulated by the tuned PR-EoS. The predicted GOC was approximately at 14,380 ftss. The optimum gas cycling scheme, in order to maximize condensate recovery, should not be performed at pressures less than 5700 psia. The contribution of condensate vaporization for such field is marginal, within 8% to 14%, compared to gas-gas miscible displacement. Therefore, it is always recommended, if gas recycle scheme to be considered for this field, to start it at the early stage of field development.

Keywords: EoS models, gas-condensate, gas cycling, near critical fluid

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Authors: Tirtha Raj Dhakal, Brian Davidson, Bob Farquharson

Abstract:

Institutional design is an important aspect in efficient water resource management. In Nepal, the water supply in both farmers’- and agency-managed irrigation systems has become sub-standard because of the weak institutional framework. This study characterizes both forms of the schemes and links existing institution and governance of the schemes with its performance with reference to cost recovery, maintenance of the schemes and water distribution throughout the schemes. For this, two types of surveys were conducted. A management survey of ten farmers’-managed and five agency-managed schemes of Chitwan valley and its periphery was done. Also, a farm survey comprising 25 farmers from each of head, middle and tail regions of both schemes; Narayani Lift Irrigation Project (agency-managed) and Khageri Irrigation System (farmers’-managed) of Chitwan Valley as a case study was conducted. The results showed that cost recovery of agency-managed schemes in 2015 was less than two percent whereas service fee collection rate in farmers’-managed schemes was nearly 2/3rd that triggered poor maintenance of the schemes and unequal distribution of water throughout the schemes. Also, the institution on practice is unable to create any incentives for farmers for economical use of water as well as willingness to pay for its use. This, thus, compels the need of refined institutional framework which has been suggested in this paper aiming to improve the cost recovery and better water distribution throughout the irrigation schemes.

Keywords: cost recovery, governance, institution, schemes' performance

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Authors: Danijela Tuljak-Suban, Valter Suban

Abstract:

Food as perishable goods represents a specific and sensitive part in the supply chain theory, since changing of its physical or chemical characteristics considerably influences the approach to stock management. The most delicate phase of this process is transportation, where it becomes difficult to ensure stability conditions that limit the deterioration, since the value of the deterioration rate could be easily influenced by the transportation mode. Fuzzy definition of variables allows taking into account these variations. Furthermore an appropriate choice of the defuzzification method permits to adapt results, as much as possible, to real conditions. In the article will be applied the those methods to the relationship between the deterioration rate of perishable goods and transportation by ship, with the aim: (a) to minimize the total costs function, defined as the sum of the ordering cost, holding cost, disposing cost and transportation costs, and (b) to improve supply chain sustainability by reducing the environmental impact and waste disposal costs.

Keywords: perishable goods, fuzzy reasoning, transport by ship, supply chain sustainability

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Authors: Viveka Jackson, Erouscilla Joseph, Denise Beckles, Thomas Christopher

Abstract:

Sulphur Dioxide (SO2) has been defined as a non-flammable, non-explosive, colourless gas, having a pungent, irritating odour, and is one of the main gases emitted from volcanoes. Sulphur dioxide has been recorded in concentrations hazardous to humans (0.25 – 0.5 ppm (~650 – 1300 μg/m3), downwind of many volcanoes and hence warrants constant air-quality monitoring around these sites. It has been linked to an increase in chronic respiratory disease attributed to long-term exposures and alteration in lung and other physiological functions attributed to short-term exposures. Sulphur Springs in Saint Lucia is a highly active geothermal area, located within the Soufrière Volcanic Centre, and is a park widely visited by tourists and locals. It is also a current source of continuous volcanic emissions via its many fumaroles and bubbling pools, warranting concern by residents and visitors to the park regarding the effects of exposure to these gases. In this study, we introduce a novel SO2 measurement system for the monitoring and quantification of ambient levels of airborne volcanic SO2 using low-cost technology. This work involves the extensive production of low-cost SO2 monitors/samplers, as well as field examination in tandem with standard commercial samplers (SO2 diffusion tubes). It also incorporates community involvement in the volcanic monitoring process as non-professional users of the instrument. We intend to present the preliminary monitoring results obtained from the low-cost samplers, to identify the areas in the Park exposed to high concentrations of ambient SO2, and to assess the feasibility of the instrument for non-professional use and application in volcanic settings

Keywords: ambient SO2, community-based monitoring, risk-reduction, sulphur springs, low-cost

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Authors: Ashwini Gowda K. S, Archana M. R, Anjaneyappa V

Abstract:

This paper presents pavement maintenance and management system (PMMS) to obtain optimum pavement maintenance and rehabilitation strategies and maintenance scheduling for a network using a multi-objective genetic algorithm (MOGA). Optimal pavement maintenance & rehabilitation strategy is to maximize the pavement condition index of the road section in a network with minimum maintenance and rehabilitation cost during the planning period. In this paper, NSGA-II is applied to perform maintenance optimization; this maintenance approach was expected to preserve and improve the existing condition of the highway network in a cost-effective way. The proposed PMMS is applied to a network that assessed pavement based on the pavement condition index (PCI). The minimum and maximum maintenance cost for a planning period of 20 years obtained from the non-dominated solution was found to be 5.190x10¹⁰ ₹ and 4.81x10¹⁰ ₹, respectively.

Keywords: genetic algorithm, maintenance and rehabilitation, optimization technique, pavement condition index

Procedia PDF Downloads 150