Search results for: cost%20analysis

Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Raja Ezman Raja Shariff

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Acute kidney injury (AKI) is commonly seen in inpatients, and places a great cost on the NHS and patients. Timely and appropriate management is both nephron sparing and potentially life-saving. Ultrasound scanning (USS) is a well-recognised method for stratifying patients. Subsequently, the NICE AKI guidance has defined groups in whom scanning is recommended within 6 hours of request (pyonephrosis), within 24 hours (obstruction/cause unknown), and in whom routine scanning isn't recommended (cause for AKI identified). The audit looks into whether Stockport NHS Trust USS practice was in line with such recommendations. The audit evaluated 92 patients with AKI who had USS, between 01/01/14 to 30/04/14. Data collection was divided into 2 parts. Firstly, radiology request cards and the online imaging software (PACS) were evaluated. Then, the electronic case notes (ADVANTIS) was evaluated further. Based on request cards, 10% of requests were for pyonephrosis. Only 33% were scanned within 6hours and a further 33% within 24hours. 75% were requested for possible obstructions and unknown cause collectively. Of those due to possible obstruction, 71% of patients were scanned within 24 hours. Of those with unknown cause, 50% were scanned within 24 hours. 15% of requests had a cause declared and so potentially did not require scanning. Evaluation of the patients’ notes suggested further interesting findings. Firstly, potentially 39% of patients had a known cause for AKI, therefore, did not need USS. Subsequently, the cohort of unknown cause and possible obstruction was collectively reduced to 45%. Alarmingly the patient cohort with possible pyonephrosis went up to 16%, suggesting an under-recognition of this life-threatening condition. We plan to highlight these findings within our institution and make changes to encourage more appropriate requesting and timely scanning. Time will tell if we manage to save or increase our costs in this cost-conscious NHS. Patient benefits, though, seem to be guaranteed.

Keywords: AKI, ARF, kidney, renal

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Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

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Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

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Authors: Geeta Gahlawat, Sanjeev Kumar Soni

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An imprudent use of environmentally hazardous petrochemical-based plastics and limited availability of fossil fuels have provoked research interests towards production of biodegradable plastics - polyhydroxyalkanoate (PHAs). However, the industrial application of PHAs based products is primarily restricted by their high cost of recovery and extraction protocols. Moreover, solvents used for the extraction and purification are toxic and volatile which causes adverse environmental hazards. Development of efficient downstream recovery strategies along with utilization of non-toxic solvents will accelerate their commercialization. In this study, various extraction strategies were designed for sustainable and cost-effective recovery of PHAs from Cupriavidus necator using non-toxic environment friendly solvents viz. 1,2-propylene carbonate, ethyl acetate, isoamyl alcohol, butyl acetate. The effect of incubation time i.e. 10, 30 and 50 min and temperature i.e. 60, 80, 100, 120°C was tested to identify the most suitable solvent. PHAs extraction using a recyclable solvent, 1,2 propylene carbonate, showed the highest recovery yield (90%) and purity (93%) at 120°C and 30 min incubation. Ethyl acetate showed the better capacity to recover PHAs from cells than butyl acetate. Extraction with ethyl acetate exhibited high recovery yield and purity of 96% and 92%, respectively at 100°C. Effect of non-toxic surfactant such as linear alkylbenzene sulfonic acid (LAS) was also studied at 40, 60 and 80°C, and detergent pH range of 3.0, 5.0, 7.0 and 9.0 for the extraction of PHAs from the cells. LAS gave highest yield of 86% and purity of 88% at temperature 80°C and 5.0 pH.

Keywords: polyhydroxyalkanoates, Cupriavidus necator, extraction, recovery yield

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Authors: Anwesha Pathak

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Space law refers to all legal provisions that may regulate or apply to space travel, as well as to space-related activity. Although there is undoubtedly a core corpus of “space law,” rather than designating a conceptually distinct single kind of law, the phrase can be seen as a label applied to a bucket that includes a variety of different laws and regulations. Similar to ‘family law' or ‘environmental law' "space law" refers to a variety of laws that are identified by the subject matter they address rather than by the logical extension of a single legal concept. The word "space law" refers to the Law of Space, which can cover anything from the specifics of an insurance agreement for a specific space launch to the most general guidelines that direct state behaviour in space. Space debris, often referred to as space junk, space pollution, space waste, space trash, or space garbage, is a term used to describe abandoned human-made objects in space, primarily in Earth orbit. These include disused spacecraft, discarded launch vehicle stages, mission-related detritus, and fragmentation material from the destruction of disused rocket bodies and spacecraft, which is particularly prevalent in Earth orbit. Other types of space debris, besides abandoned human-made objects in orbit, include pieces left over from collisions, erosion, and disintegration, or even paint specks, solidified liquids ejected from spacecraft, and unburned components from solid rocket engines. The initial action of launching or using a spacecraft in near-Earth orbit imposes an external cost on others that is typically not taken into account or fully accounted for in the cost by the launcher or payload owner.

Keywords: space, outer space treaty, geostationary orbit, satellites, spacecrafts

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Authors: R. Tajau, R. Rohani, M. S. Alias, N. H. Mudri, K. A. Abdul Halim, M. H. Harun, N. Mat Isa, R. Che Ismail, S. Muhammad Faisal, M. Talib, M. R. Mohamed Zin

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Bio-based polymeric materials are increasingly used for a variety of applications, including surface coating, drug delivery systems, and tissue engineering. These polymeric materials are ideal for the aforementioned applications because they are derived from natural resources, non-toxic, low-cost, biocompatible, and biodegradable, and have promising thermal and mechanical properties. The nature of hydrocarbon chains, carbon double bonds, and ester bonds allows various sources of oil (edible), such as soy, sunflower, olive, and oil palm, to fine-tune their particular structures in the development of innovative materials. Palm oil can be the most eminent raw material used for manufacturing new and advanced natural polymeric materials involving radiation techniques, such as coating resins, nanoparticles, scaffold, nanotubes, nanocomposites, and lithography for different branches of the industry in countries where oil palm is abundant. The radiation technique is among the most versatile, cost-effective, simple, and effective methods. Crosslinking, reversible addition-fragmentation chain transfer (RAFT), polymerisation, grafting, and degradation are among the radiation mechanisms. Exposure to gamma, EB, UV, or laser irradiation, which are commonly used in the development of polymeric materials, is used in these mechanisms. Therefore, this review focuses on current radiation processing technologies for the development of various radiation-curable bio-based polymeric materials with a promising future in biomedical and industrial applications. The key focus of this review is on radiation curable palm oil-based products, which have been published frequently in recent studies.

Keywords: palm oil, radiation processing, surface coatings, VOC

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Adel Nikfarjam, Hamed Tayebi, Sadoullah Ebrahimnejad

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This paper considers a two-echelon inventory system with a number of warehouses and a single retailer. The retailer replenishes its required items from warehouses, and assembles them into a single final product. We assume that each warehouse supplies only one kind of the raw material for the retailer. The demand process of the final product is assumed to be Poissson, and unsatisfied demand of the final product will be lost. The retailer applies one-for-one-period ordering policy which is also known as (1, T) ordering policy. In this policy the retailer orders to each warehouse a fixed quantity of each item at fixed time intervals, which the fixed quantity is equal to the utilization of the item in the final product. Since, this policy eliminates all demand uncertainties at the upstream echelon, the standard lot sizing model can be applied at all warehouses. In this paper, we calculate the total cost function of the inventory system. Then, based on this function, we present a procedure to obtain the optimal time interval between two consecutive order placements from retailer to the warehouses, and the optimal order quantities of warehouses (assuming that there are positive ordering costs at warehouses). Finally, we present some numerical examples, and conduct numerical sensitivity analysis for cost parameters.

Keywords: two-echelon supply chain, multi-vendor-single-buyer inventory system, lost sales, Poisson demand, one-for-one-period policy, lot sizing model

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Authors: Maariyah Irfan

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Intro: Current cardiovascular (CV) care faces challenges such as low budgets and high hospital admission rates. This review aims to evaluate Big Data in CV healthcare management through the use of wearable devices in atrial fibrillation (AF) detection. AF may present intermittently, thus it is difficult for a healthcare professional to capture and diagnose a symptomatic rhythm. Methods: The iRhythm ZioPatch, AliveCor portable electrocardiogram (ECG), and Apple Watch were chosen for review due to their involvement in controlled clinical trials, and their integration with smartphones. The cost-effectiveness and AF detection of these devices were compared against the 12-lead ambulatory ECG (Holter monitor) that the NHS currently employs for the detection of AF. Results: The Zio patch was found to detect more arrhythmic events than the Holter monitor over a 2-week period. When patients presented to the emergency department with palpitations, AliveCor portable ECGs detected 6-fold more symptomatic events compared to the standard care group over 3-months. Based off preliminary results from the Apple Heart Study, only 0.5% of participants received irregular pulse notifications from the Apple Watch. Discussion: The Zio Patch and AliveCor devices have promising potential to be implemented into the standard duty of care offered by the NHS as they compare well to current routine measures. Nonetheless, companies must address the discrepancy between their target population and current consumers as those that could benefit the most from the innovation may be left out due to cost and access.

Keywords: atrial fibrillation, big data, cardiovascular healthcare management, wearable devices

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Authors: Neha Dimri, Varsha Gupta

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Purpose: Fast Fashion trend promotes consumption of low cost high fashion garments at a rapid rate. Frequent change in fashion trend results in higher disposability of Fast Fashion products. To cater for the Fast Fashion appetite of the present day consumer, fashion giants have ramped up production of garments, thus imposing a massive strain on the planet’s natural resources. Also, ethical issues related to cheaper methods of production are of concern. India being a large consumer base has a major role to play in proliferation of the Fast Fashion trend. This paper is an attempt to study the effect of fast fashion trends on the Indian consumer’s behaviour. It also attempts to ascertain the awareness of the consumer about the detrimental effect that the fast fashion trends manifest on the environment. Design /methodology/approach: The survey was conducted using a questionnaire targeted at a set of urban Indian consumers of varied age, profession and socio economic backgrounds. Trends regarding frequency of purchase, expenditure on clothing, disposal methods and awareness about environmental issues were analyzed using the obtained data. Findings: The result of the study indicates that urban Indian consumer has a strong affinity towards fast fashion trends, but is largely unaware of its detrimental effect on the environment and strain on natural resources. Research Limitation/implications: The sample size for survey was only of a hundred consumers, and the same could be expanded for a better estimate of trends. Also, the sample consumers were mostly urban. A big chunk of Indian fashion consumers reside in small towns and the same could be included in the survey. Practical implications: As the true cost of Fast Fashion in terms of environmental and ethical aspects is getting realized worldwide, a big market like India cannot remain isolated from this phenomenon. Globally there has been an increase in demand of ethically produced clothing. It is imperative that the Indian consumer be made aware about the unsustainable nature of Fast Fashion so that he can contribute towards conservation of natural resources and ethical production of garments. Originality/value The research attempts to ascertain consumption pattern of the Indian fashion consumer and also his awareness about the true cost and consequences of Fast Fashion. The inferences may be used by fashion giants to use ‘Green Marketing’ and ‘Social Marketing’ techniques to make the Indian consumer more aware about sustainable fashion and to market their own products as ‘Sustainable, Green and Ethical’.

Keywords: consumption, disposable, fast fashion, Indian consumer

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Authors: Krishna Nand, Mohammad Taufik

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Fused Filament Fabrication (FFF) is one of the most popular additive manufacturing (AM) technology. In FFF technology, a wire form material (filament) is fed inside a heated chamber, where it gets converted into semi-solid form and extruded out of a nozzle to be deposited on the build platform to fabricate the part. FFF technology is expanding and covering the market at a very rapid rate, so the need of raw materials for 3D printing is also increasing. The cost of 3D printing is directly affected by filament cost. To make 3D printing more economic, a compact and portable filament/wire extrusion system is needed. Wire extrusion systems to extrude ordinary wire/filament made of a single material are available in the market. However, extrusion system to make a composite wire/filament are not available. Hence, in this study, initial efforts have been made to develop a table-top composite wire extruder. The developed system is consisted of mechanical parts, electronics parts, and a control system. A multiple channel hopper, extrusion screw, melting chamber and nozzle, cooling zone, and spool winder are some mechanical parts. While motors, heater, temperature sensor, cooling fans are some electronics parts, which are used to develop this system. A control board has been used to control the various process parameters like – temperature and speed of motors. For the production of composite wire/filament, two different materials could be fed through two channels of hopper, which will be mixed and carried to the heated zone by extrusion screw. The extrusion screw is rotated by a motor, and the speed of this motor will be controlled by the controller as per the requirement of material extrusion rate. In the heated zone, the material will melt with the help of a heating element and extruded out of the nozzle in the form of wire. The developed system occupies less floor space due to the vertical orientation of its heating chamber. It is capable to extrude ordinary filament as well as composite filament, which are compatible with 3D printers available in the market. Further, the developed system could be employed in the research and development of materials, processing, and characterization for 3D printer. The developed system presented in this study could be a better choice for hobbyists and researchers dealing with the fused filament fabrication process to reduce the 3D printing cost significantly by recycling the waste material into 3D printer feed material. Further, it could also be explored as a better alternative for filament production at the commercial level.

Keywords: additive manufacturing, 3D Printing, filament extrusion, pellet extrusion

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: J. M. Counsell, Y. Khalid, M. J. Stewart

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Achieving nearly zero carbon heating continues to be identified by UK government analysis as an important feature of any lowest cost pathway to reducing greenhouse gas emissions. Heat currently accounts for 48% of UK energy consumption and approximately one third of UK’s greenhouse gas emissions. Heat Networks are being promoted by UK investment policies as one means of supporting hybrid heat pump based solutions. To this effect the RISE (Renewable Integrated and Sustainable Electric) heating system project is investigating how an all-electric heating sourceshybrid configuration could play a key role in long-term decarbonisation of heat.  For the purposes of this study, hybrid systems are defined as systems combining the technologies of an electric driven air source heat pump, electric powered thermal storage, a thermal vessel and micro-heat network as an integrated system.  This hybrid strategy allows for the system to store up energy during periods of low electricity demand from the national grid, turning it into a dynamic supply of low cost heat which is utilized only when required. Currently a prototype of such a system is being tested in a modern house integrated with advanced controls and sensors. This paper presents the virtual performance analysis of the system and its design for a micro heat network with multiple dwelling units. The results show that the RISE system is controllable and can reduce carbon emissions whilst being competitive in running costs with a conventional gas boiler heating system.

Keywords: gas boilers, heat pumps, hybrid heating and thermal storage, renewable integrated and sustainable electric

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Authors: Samkeliso S. Ndzimandze, Welldone Moyo, Oranso T. Mahlangu, Adolph A. Muleja, Alex T. Kuvarega, Thabo T. I. Nkambule

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The high cost of precursor materials has hindered the commercialization of ceramic membrane technology in water treatment. In this work, a ceramic membrane disc (approximately 50 mm in diameter and 4 mm thick) was prepared from low-cost starting materials, kaolin, and fly ash by pressing at 200 bar and calcining at 900 °C. The fabricated membrane was characterized for various physicochemical properties, natural organic matter (NOM) removal as well as fouling propensity using several techniques. Further, the ceramic membrane was tested on samples collected from four drinking water treatment plants in KwaZulu-Natal, South Africa (named plants 1-4). The membrane achieved 48.6%, 54.6%, 57.4%, and 76.4% bulk UV254 reduction for raw water at plants 1, 2, 3, and 4, respectively. These removal rates were comparable to UV254 reduction achieved by coagulation/flocculation steps at the respective plants. Further, the membrane outperformed sand filtration steps in plants 1-4 in removing disinfection by-product precursors (8%-32%) through size exclusion. Fluorescence excitation-emission matrices (FEEM) studies showed the removal of fluorescent NOM fractions present in the water samples by the membrane. The membrane was fabricated using an up-scalable facile method, and it has the potential for application as a polishing step to complement conventional processes in water treatment for drinking purposes.

Keywords: crossflow filtration, drinking water treatment plants, fluorescence excitation-emission matrices, ultraviolet 254 (UV₂₅₄)

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Authors: Hanan A. Anwar

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This paper introduces green building construction in Egypt with different concepts and practices. The following study includes green building applied definition, guidelines, regulations and Standards. Evaluation of cost/benefit of green construction methods and green construction rating systems are presented. Relevant case studies will be reviewed. Four sites will be included.

Keywords: green construction, ecofreindly, self-sufficient town, carbon neutral atmosphere

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Authors: Mahnaz Sanjari, Sedigheh Salemi, Mohammad Mirzabeigi

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Nowadays, the world is facing a crisis of workforce and one of the most striking examples is the shortage of nurses. Nursing workforce productivity is related by various factors such as absenteeism, professional effectiveness and quality care. This cross-sectional study was conducted in 700 nurses who work in government hospitals from 35 hospitals of 9 provinces in Iran. The study was approved by the Nursing Council and was carried out with the authorization of the Research Ethics Committee. The questionnaire included 33 questions and 4 sub categories such as human resource, education and management. The reliability was evaluated by Cronbach's alpha (α=0/85). Statistical analyzes were performed, using SPSS version 16. The result showed that nurses emphasized on "respect to nurse-to-bed ratio" and less importance item was "using less experienced nurse". In addition, another important factor in clinical productivity is "Proper physical structure and amenities","good communication with colleagues" and "having good facilities". Also, "human resources at all levels of standard", "promoting on merit" and "well defined relationship in health system" are another important factors in productivity from nurse` view. The main managerial factor is "justice between employees" and the main educational component of productivity is “updating nursing knowledge”. The results show that more than half of the participants emphasized on the management and educational factors. Productivity as one of the main part of the health care quality leads to appropriate use of human and organizational resources, reduce cost services, and organizational development.

Keywords: productivity, nursing services, workforce, cost services

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Authors: Mohammad Amin Hamedirad, Seyed Javad Vaziri Kang Olyaei

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Project planning and control are one of the most critical issues in the management of construction projects. Traditional methods of project planning and control, such as the critical path method or Gantt chart, are not widely used for planning projects with discrete and repetitive activities, and one of the problems of project managers is planning the implementation process and optimal allocation of its resources. Massive concreting projects is also a project with discrete and repetitive activities. This study uses the concept of simulating discrete events to manage resources, which includes finding the optimal number of resources considering various limitations such as limitations of machinery, equipment, human resources and even technical, time and implementation limitations using analysis of resource consumption rate, project completion time and critical points analysis of the implementation process. For this purpose, the concept of discrete-event simulation has been used to model different stages of implementation. After reviewing the various scenarios, the optimal number of allocations for each resource is finally determined to reach the maximum utilization rate and also to reduce the project completion time or reduce its cost according to the existing constraints. The results showed that with the optimal allocation of resources, the project completion time could be reduced by 90%, and the resulting costs can be reduced by up to 49%. Thus, allocating the optimal number of project resources using this method will reduce its time and cost.

Keywords: simulation, massive concreting, discrete event simulation, resource management

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Authors: Yong-Sung Kim, Je-Seok Shin, Ho-Jun Jo, Jin-O Kim

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Home Energy Management System (HEMS) which makes the residential consumers contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it also represents impacts of the comfort level on the scheduling result.

Keywords: load scheduling, usage pattern, user’s comfort, copula function, branch and bound, electric heater

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Authors: Udeh Nneka Evelyn

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The shortcomings of traditional costing system, in terms of validity, accuracy, consistency and relevance increased the need for modern management accounting system. ABC (Activity-Based Costing) can be used as a modern tool for planning, control and decision making for management. Past studies on activity-based costing (ABC) system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing techniques in service oriented business organisations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on activity-based costing (ABC). Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry, and government organizations. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: Identification of the most profitable customers; more accurate product and service pricing; increase product profitability; well-organized process costs.

Keywords: profitability, activity-based costing (ABC), management accounting, manufacture

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Authors: Shailja Thakur

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In this paper it is shown that how farmers are suffering from all sides including vagaries of weather then price fluctuations, demand supply constraints, poor soil health etc. Also the ICT can prove to be of great help if incorporated rightly into Indian agriculture. Some innovative ways to reward farmers and distribution of subsidies to them can improve the current scenario.

Keywords: cost of farming, information and communication technology, innovative steps, roof gardening, vermicomposting

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Authors: Lindiwe Ngcobo

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The aim of the study is to describe and understand the benefits and costs of having biogas digesters at both household and society level. On a household level, the purpose is to understand how rural households benefit from the biogas digesters, for example, by converting animal and human waste through biogas digesters, and at what costs the benefits are realized. At a societal level, the purpose is to understand the costs and benefits of biogas digesters relative to the situation of rural communities who do not have flush toilets and have no appropriate waste disposal services while they incur electricity costs. Multiple regression analysis was used to determine the effect of biogas digesters on electricity availability and waste management. The results showed that beneficiaries spent less on electricity using household waste, and also waste disposal costs were eliminated from household expenses. A move to biogas energy production can be beneficial to rural households. It is economically and environmentally friendly. Small-scale farmers need to be introduced to agricultural innovations that can assist them in producing nutritious crops at a low cost. This can be a good opportunity to start an agribusiness that focuses on organic crops. Extensions and training institutions have to play a part in supporting households to develop entrepreneurial skills. Cost-benefit analysis showed that the benefits of biogas exceed the costs of the biogas projects. This implies that this technology should be promoted in rural households. Government financial incentives must be put in place to motivate a generation of organic Agri-prenuers.

Keywords: Agri-prenuers, biogas digester, biogas energy, disposal costs

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Authors: Adel Mohamed El-Baghdady, Walid Sayed Abdulgalil, Ahmad Asran, Ibrahim Nosier

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This paper studies the effectiveness of applying value engineering to actual concrete mixtures. The study was conducted in the State of Qatar on a number of strategic construction projects with international engineering specifications for the 2022 World Cup projects. The study examined the concrete mixtures of Doha Metro project and the development of KAHRAMAA’s (Qatar Electricity and Water Company) Abu Funtas Strategic Desalination Plant, in order to generally improve the quality and productivity of ready-mixed concrete used in construction and hydraulic projects. The application of value engineering to such concrete mixtures resulted in the following: i) improving the quality of concrete mixtures and increasing the durability of buildings in which they are used; ii) reducing the waste of excess materials of concrete mixture, optimizing the use of resources, and enhancing sustainability; iii) reducing the use of cement, thus reducing CO₂ emissions which ensures the protection of environment and public health; iv) reducing actual costs of concrete mixtures and, in turn, reducing the costs of construction projects; and v) increasing the market share and competitiveness of concrete producers. This research shows that applying the methodology of value engineering to ready-mixed concrete is an effective way to save around 5% of the total cost of concrete mixtures supplied to construction and hydraulic projects, improve the quality according to the technical requirements and as per the standards and specifications for ready-mixed concrete, improve the environmental impact, and promote sustainability.

Keywords: value management, cost of concrete, performance, optimization, sustainability, environmental impact

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Authors: Sumra Siddique Abbasi, Cheng Shikun

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Biogas technology has rapidly developed in agriculture sector to upgrade and improve the life of farmers by providing them alternative and cost-effective energy source. Main purpose of this study is to understand the advantages of biogas plants by livestock owners either they are household-based livestock owners or may own farms for livestock. Similarly, a pertinent and major purpose of this research is to examine the factors affecting the decision to adopt biogas technologies at the household level. Based on the result, both public and private sector organization can make decisions related to the installation of biogas projects. Biogas is major energy source which can be used as an alternative and renewable energy source. This energy production technology can contribute in uplifting the lifestyle of farmers and can contribute into sustainable development of rural communities in Pakistan. People with livestock in any community in Pakistan can get benefit from biogas plants and it will contribute in sustainable development program which generates socio economic benefits, heath upgradation, cost effective energy source and positive impact on climate change or environmental issues. This study was conductive using survey method and descriptive analysis. One hundred fifty (150) farmers were the respondents who participated in survey. These farmers were from Layyah district of Punjab and were selected using snowball sampling technique. To generate the results, SPSS tool was used for data analysis.

Keywords: biogas plant, animal dunk, renewable energy, pakistan

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Authors: Tolulope Allo, Mofoluwake P. Ajayi, Adenike E. Idowu, Emmanuel O. Amoo, Fadeke Esther Olu-Owolabi

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Breast cancer which was more prevalent in Europe and America in the past is gradually being mirrored across the world today with greater economic burden on low and middle income countries (LMCs). Breast cancer is the most common cancer among women globally and current studies have shown that a woman dies with the diagnosis of breast cancer every thirteen minutes. The economic cost of breast cancer is overwhelming particularly for developing economies. While it causes billion of dollar in losses of national income, it pushes millions of people below poverty line. This study examined the economic burden of breast cancer on Nigerian women, its impacts on their standard of living and its effects on Nigeria’s socio economic development. The study adopts a qualitative research approach using the in-depth interview technique to elicit valuable information from respondents with cancer experience from the Southern part of Nigeria. Respondents constituted women in their reproductive age (15-49 years) that have experienced and survived cancer and also those that are currently receiving treatment. Excerpts from the interviews revealed that the cost of treatment is one of the major factors contributing to the late presentation of breast cancer incidences among women as many of them could not afford to pay for their own treatment. The study also revealed that many women prefer to explore other options such as herbal treatments and spiritual consultations which is less expensive and affordable. The study therefore concludes that breast cancer diagnosis and treatment should be subsidized by the government in order to facilitate easy access and affordability thereby promoting early detection and reducing the economic burden of treatment on women.

Keywords: breast cancer, development, economic burden, women

Procedia PDF Downloads 357

Authors: Milica Ž. Karadžić, Lidija R. Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Z. Kovačević, Anamarija I. Mandić, Katarina Penov-Gaši, Andrea R. Nikolić, Aleksandar M. Oklješa

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This study considered selection of the in silico molecular descriptors and the models for newly synthesized steroid derivatives description and their characterization using chemometric techniques. Multiple linear regression (MLR) models were established and gave the best molecular descriptors for quantitative structure-retention relationship (QSRR) modeling of the retention of the investigated molecules. MLR models were without multicollinearity among the selected molecular descriptors according to the variance inflation factor (VIF) values. Used molecular descriptors were ranked using generalized pair correlation method (GPCM). In this method, the significant difference between independent variables can be noticed regardless almost equal correlation between dependent variable. Generated MLR models were statistically and cross-validated and the best models were kept. Models were ranked using sum of ranking differences (SRD) method. According to this method, the most consistent QSRR model can be found and similarity or dissimilarity between the models could be noticed. In this study, SRD was performed using average values of experimentally observed data as a golden standard. Chemometric analysis was conducted in order to characterize newly synthesized steroid derivatives for further investigation regarding their potential biological activity and further synthesis. This article is based upon work from COST Action (CM1105), supported by COST (European Cooperation in Science and Technology).

Keywords: generalized pair correlation method, molecular descriptors, regression analysis, steroids, sum of ranking differences

Procedia PDF Downloads 346

Authors: Ahmed Z. Mazen, Nejat Rahmanian, Iqbal Mujtaba, Ali Hassanpour

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In oil and gas well drilling, the drill bit is an important part of the Bottom Hole Assembly (BHA), which is installed and designed to drill and produce a hole by several mechanisms. The efficiency of the bit depends on many drilling parameters such as weight on bit, rotary speed, and mud properties. When the bit is pulled out of the hole, the evaluation of the bit damage must be recorded very carefully to guide engineers in order to select the bits for further planned wells. Having a worn bit for hole drilling may cause severe damage to bit leading to cutter or cone losses in the bottom of hole, where a fishing job will have to take place, and all of these will increase the operating cost. The main factor to reduce the cost of drilling operation is to maximize the rate of penetration by analyzing real-time data to predict the drill bit wear while drilling. There are numerous models in the literature for prediction of the rate of penetration based on drilling parameters, mostly based on empirical approaches. One of the most commonly used approaches is Bourgoyne and Young model, where the rate of penetration can be estimated by the drilling parameters as well as a wear index using an empirical correlation, provided all the constants and coefficients are accurately determined. This paper introduces a new methodology to estimate the eight coefficients for Bourgoyne and Young model using the gPROMS parameters estimation GPE (Version 4.2.0). Real data collected form similar formations (12 ¼’ sections) in two different fields in Libya are used to estimate the coefficients. The estimated coefficients are then used in the equations and applied to nearby wells in the same field to predict the bit wear.

Keywords: Bourgoyne and Young model, bit wear, gPROMS, rate of penetration

Procedia PDF Downloads 152

Authors: Pawitchaya Srijaiwong, Surin Khomfoi

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There are several solutions to supply electricity to an island in Thailand such as diesel generation, submarine power cable, and renewable energy power generation. However, each alternative has its own limitation like fuel and pollution of diesel generation, submarine power cable length resulting in loss of cable and cost of investment, and potential of renewable energy in the local area. This paper shows microgrid system which is a new alternative for power supply to an island. It integrates local power plant from renewable energy, energy storage system, and microgrid controller. The suitable renewable energy power generation on an island is selected from geographic location and potential evaluation. Thus, photovoltaic system and hydro power plant are taken into account. The capacity of energy storage system is also estimated by transient stability study in order to supply electricity demand sufficiently under normal condition. Microgrid controller plays an important role in conducting, communicating and operating for both sources and loads on an island so that its functions are discussed in this study. The conceptual design of microgrid operation is investigated in order to analyze the reliability and power quality. The result of this study shows that microgrid is able to operate in parallel with the main grid and in case of islanding. It is applicable for electricity supply to an island and a remote area. The advantages of operating microgrid on an island include the technical aspect like improving reliability and quality of power system and social aspects like outage cost saving and CO₂ reduction.

Keywords: energy storage, islanding, microgrid, renewable energy

Procedia PDF Downloads 324

Authors: Daud Mustafa Minhas, Raja Rehan Khalid, Georg Frey

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The next generation power systems are equipped with abundantly available free renewable energy resources (RES). During their low-cost operations, the price of electricity significantly reduces to a lower value, and sometimes it becomes negative. Therefore, it is recommended not to operate the traditional power plants (e.g. coal power plants) and to reduce the losses. In fact, it is not a cost-effective solution, because these power plants exhibit some shutdown and startup costs. Moreover, they require certain time for shutdown and also need enough pause before starting up again, increasing inefficiency in the whole power network. Hence, there is always a trade-off between avoiding negative electricity prices, and the startup costs of power plants. To exploit this trade-off and to increase the profit of a power plant, two main contributions are made: 1) introducing retrofit technology for state of art coal power plant; 2) proposing optimal control strategy for a power plant by exploiting different flexibility features. These flexibility features include: improving ramp rate of power plant, reducing startup time and lowering minimum load. While, the control strategy is solved as mixed integer linear programming (MILP), ensuring optimal solution for the profit maximization problem. Extensive comparisons are made considering pre and post-retrofit coal power plant having the same efficiencies under different electricity price scenarios. It concludes that if the power plant must remain in the market (providing services), more flexibility reflects direct economic advantage to the plant operator.

Keywords: discrete optimization, power plant flexibility, profit maximization, unit commitment model

Procedia PDF Downloads 141

Authors: Jamshed Ahmad, Abdul Wahid Khan, Javed Ali Khan

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Managing software quality requirements change management is a difficult task in the field of software engineering. Avoiding incoming changes result in user dissatisfaction while accommodating to many requirement changes may delay product delivery. Poor requirements management is solely considered the primary cause of the software failure. It becomes more challenging in global software outsourcing. Addressing success factors in quality requirement change management is desired today due to the frequent change requests from the end-users. In this research study, success factors are recognized and scrutinized with the help of a systematic literature review (SLR). In total, 16 success factors were identified, which significantly impacted software quality requirement change management. The findings show that Proper Requirement Change Management, Rapid Delivery, Quality Software Product, Access to Market, Project Management, Skills and Methodologies, Low Cost/Effort Estimation, Clear Plan and Road Map, Agile Processes, Low Labor Cost, User Satisfaction, Communication/Close Coordination, Proper Scheduling and Time Constraints, Frequent Technological Changes, Robust Model, Geographical distribution/Cultural differences are the key factors that influence software quality requirement change. The recognized success factors and validated with the help of various research methods, i.e., case studies, interviews, surveys and experiments. These factors are then scrutinized in continents, database, company size and period of time. Based on these findings, requirement change will be implemented in a better way.

Keywords: global software development, requirement engineering, systematic literature review, success factors

Procedia PDF Downloads 195

Authors: Hyacinth Dawam Dakwang

Abstract:

Outsourcing is growing at a rapid rate throughout the world because organizations view it as a way to achieve strategic goals, improve customer satisfaction and provide other efficiency and effectiveness improvements. With the increasing globalization, outsourcing has become an important business approach, and a competitive advantage may be gained as products or services are produced more effectively and efficiently by outside suppliers. Several organizations have embarked on outsourcing strategies over the years but many still suffer in terms of their goal achievement; some have experienced low productivity both in terms of quality and quantity, their profitability has not been stable, and their capacities are grossly underutilized. This research work determined the effect of outsourcing strategies on the performance of manufacturing firms in Kaduna State. The study adopted descriptive research design. The questionnaire for the study was subjected to test- re-test reliability assessment. The data collected was analysed using the Statistical Package for Social Sciences (SPSS 20). Results were presented on frequency distribution tables and graphs. The findings reveal that firms that outsourcing strategy reduce average cost, increased productivity and profitability improved quality, improves customer satisfaction and save time for core activities. This study therefore recommended that firms should embark more on outsourcing strategies to attain the benefits of cost savings/restructuring which results in better customer service at profit; also, outsourcing strategy should come from the workers themselves. Also, organisations should ensure that, the costs of managing the outsourcing process is not greater than the benefits generated by the outsourcing program.

Keywords: Manufacturing Firms, Outsourcing , Performance, Strategies

Procedia PDF Downloads 149