Search results for: low cost and highly efficient

Authors: Paria Tajabor, Azin Azarbani

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The purpose of this research study is exploring two kind of semantic repositories with regards to various factors to find the best approaches that an artificial manager can use to produce ontology in a system based on their interaction, association and research. To this end, as the best way to evaluate each system and comparing with others is analysis, several benchmarking over these two repositories were examined. These two semantic repositories: OWLIM and AllegroGraph will be the main core of this study. The general objective of this study is to be able to create an efficient and cost-effective manner reports which is required to support decision making in any large enterprise.

Keywords: OWLIM, allegrograph, RDF, reasoning, semantic repository, semantic-web, SPARQL, ontology, query

Procedia PDF Downloads 244

Authors: Imad Khan, Imran Shafi, Sarmad Farooq

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Large diameter pipes, barrels, tubes, and ducts are used in a variety of applications covering civil and defense-related technologies. This may include heating/cooling networks, sign poles, bracing, casing, and artillery and tank gun barrels. These large diameter assemblies require regular inspection and cleaning to increase their life and reduce replacement costs. This paper describes the design, development, and testing results of an efficient yet simplified, low maintenance mechanical design controlled with minimal essential electronics using an electric motor for a non-technical staff. The proposed solution provides a simplified user interface and an automated cleaning mechanism that requires a single user to optimally clean pipes and barrels in the range of 105 mm to 203 mm caliber. The proposed system employs linear motion of specially designed brush along the barrel using a chain of specific strength and a pulley anchor attached to both ends of the barrel. A specially designed and manufactured gearbox is coupled with an AC motor to allow movement of contact brush with high torque to allow efficient cleaning. A suitably powered AC motor is fixed to the front adapter mounted on the muzzle side whereas the rear adapter has a pulley-based anchor mounted towards the breach block in case of a gun barrel. A mix of soft nylon and hard copper bristles-based large surface brush is connected through a strong steel chain to motor and anchor pulley. The system is equipped with limit switches to auto switch the direction when one end is reached on its operation. The testing results based on carefully established performance indicators indicate the superiority of the proposed user-friendly cleaning mechanism vis-à-vis its life cycle cost.

Keywords: pipe cleaning mechanism, limiting switch, pipe cleaning robot, large pipes

Procedia PDF Downloads 87

Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

Procedia PDF Downloads 156

Authors: Muhammad Zahid, Ilker S. Bayer, Athanassia Athanassiou

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Fluorinated polymers having C8 chemistry (chemicals with 8 fluorinated carbon atoms) are well renowned for their excellent low surface tension and water repelling properties. However, these polymers degrade into highly toxic heavy perfluoro acids in the environment. When the C8 chemistry is reduced to C6 chemistry, this environmental concern is eliminated at the expense of reduced liquid repellent performance. In order to circumvent this, in this study, we demonstrate pre-treatment of woven cotton fabrics with a fluorinated acrylic copolymer with C6 chemistry and subsequently with a silicone polymer to render them hydrophobic. A commercial fluorinated acrylic copolymer was blended with silica nanoparticles to form hydrophobic nano-roughness on cotton fibers and a second coating layer of polydimethylsiloxane (PDMS) was applied on the fabric. A static water contact angle (for 5µl) and rolling angle (for 12.5µl) of 147°±2° and 31° were observed, respectively. Hydrostatic head measurements were also performed to better understand the performance with 26±1 cm and 2.56kPa column height and static pressure respectively. Fabrication methods (with rod coater etc.) were kept simple, reproducible, and scalable and cost efficient. Moreover, the robustness of applied coatings was also evaluated by sonication cleaning and abrasion methods. Water contact angle (WCA), water shedding angle (WSA), hydrostatic head, droplet bouncing-rolling off and prolonged staining tests were used to characterize hydrophobicity of materials. For chemical and morphological analysis, various characterization methods were used such as attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), atomic force microscopy (AFM) and scanning electron microscopy (SEM).

Keywords: fluorinated polymer, hydrophobic, polydimethylsiloxane, water contact angle

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Authors: Bara' Al-Mistarehi

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Documentation and assessment of conservation state of an archaeological structure is a significant procedure in any management plan. However, it has always been a challenge to apply this with a low coast and safe methodology. It is also a time-demanding procedure. Therefore, a low cost, efficient methodology for documenting the state of a structure is needed. In the scope of this research, this paper will employ digital photogrammetry and laser scanner to one of highly significant structures in Germany, The Old Castle (German: Altes Schloss). The site is well known for its unique features. However, the castle suffers from serious deterioration threats because of the environmental conditions and the absence of continuous monitoring, maintenance and repair plans. Digital photogrammetry is a generally accepted technique for the collection of 3D representations of the environment. For this reason, this image-based technique has been extensively used to produce high quality 3D models of heritage sites and historical buildings for documentation and presentation purposes. Additionally, terrestrial laser scanners are used, which directly measure 3D surface coordinates based on the run-time of reflected light pulses. These systems feature high data acquisition rates, good accuracy and high spatial data density. Despite the potential of each single approach, in this research work maximum benefit is to be expected by a combination of data from both digital cameras and terrestrial laser scanners. Within the paper, the usage, application and advantages of the technique will be investigated in terms of building high realistic 3D textured model for some parts of the old castle. The model will be used as diagnosing tool of the conservation state of the castle and monitoring mean for future changes.

Keywords: Digital photogrammetry, Terrestrial laser scanners, 3D textured model, archaeological structure

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Anish Desai, Reshmi Pillai, Nilesh Mahajan, Hitesh Chopra, Vishal Mahajan, Ajay Grover, Ashish Kohli

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Surgical Site Infection (SSI) is hospital acquired infection of growing concern. This study presents the efficacy and cost-effectiveness of triclosan-coated suture, in reducing the burden of SSI in India. Methodology: A systematic literature search was conducted for economic burden (1998-2018) of SSI and efficacy of triclosan-coated sutures (TCS) vs. non-coated sutures (NCS) (2000-2018). PubMed Medline and EMBASE indexed articles were searched using Mesh terms or Emtree. Decision tree analysis was used to calculate, the cost difference between TCS and NCS at private and public hospitals, respectively for 7 surgical procedures. Results: The SSI range from low to high for Caesarean section (C-section), Laparoscopic hysterectomy (L-hysterectomy), Open Hernia (O-Hernia), Laparoscopic Cholecystectomy (L-Cholecystectomy), Coronary artery bypass graft (CABG), Total knee replacement (TKR), and Mastectomy were (3.77 to 24.2%), (2.28 to 11.7%), (1.75 to 60%), (1.71 to 25.58%), (1.6 to 18.86%), (1.74 to 12.5%), and (5.56 to 25%), respectively. The incremental cost (%) of TCS ranged 0.1%-0.01% in private and from 0.9%-0.09% at public hospitals across all surgical procedures. Cost savings at median efficacy & SSI risk was 6.52%, 5.07 %, 11.39%, 9.63%, 3.62%, 2.71%, 9.41% for C-section, L-hysterectomy, O-Hernia, L-Cholecystectomy, CABG, TKR, and Mastectomy in private and 8.79%, 4.99%, 12.67%, 10.58%, 3.32%, 2.35%, 11.83% in public hospital, respectively. Efficacy of TCS and SSI incidence in a particular surgical procedure were important determinants of cost savings using one-way sensitivity analysis. Conclusion: TCS suture led to cost savings across all 7 surgeries in both private and public hospitals in India.

Keywords: cost Savings, non-coated sutures, surgical site infection, triclosan-coated sutures

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Authors: Eman Elsebaie, A. Sedrak, R. Ziada

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Introduction: In the recent decades, heart failure (HF) has become one of the most prevalent cardio-vascular disease (CVDs), especially in the elderly and the main cause of hospitalization in Egypt cardiology departments. By 2030, the prevalence of HF is expected to increase by 25%. Total direct costs will increase to $818 billion, and the total indirect cost in terms of lost productivity is close to $275 billion. The current study was conducted to estimate the economic costs of services delivered for heart failure patients at the cardiology department in Cairo University Hospitals (CUHs). Aim: To gain an understanding of the cost of heart failure disease and its main drivers aiming to minimize associated health care costs. Subjects and Methods: Economic cost analysis study was conducted for a prospective group of all cases of HF admitted to the cardiology department in CUHs from end of March till end of April 2016 and another retrospective randomized sample from patients with HF, during the first 3 months of 2016 to measure estimated average cost per patient per day. Results: The mean age of the prospective group was 48.6 ± 17.16 years versus 52.3 ± 11.5 years for the retrospective group. The median (IQR) of Length of stay was 15 (15) days in the prospective group versus 9 (16) days in the retrospective group. The average HF inpatient cost/day in the cardiology department during April 2016 was 362.32 (255.5) L.E. versus 391.2(255.9) L.E. during January and February 2016. Conclusion: Up to 70% of expenditure in the management of HF is related to hospital admission. The average cost of such an admission was 5540.03 (IQR=7507.8) L.E. and 4687.4 (IQR=7818.8) L.E. with the average cost per day estimated at 362.32 (IQR=255.5) L.E. and 386.2(IQR=255.9) L.E. in prospective and retrospective groups respectively.

Keywords: health care cost, heart failure, hospitalization, inpatient

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Authors: Alex Ellery

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Geoengineering approaches to climate change mitigation are unpopular and regarded with suspicion. Of these, space-based approaches are regarded as unworkable and enormously costly. Here, a space-based approach is presented that is modest in cost, fully controllable and reversible, and acts as a natural spur to the development of solar power satellites over the longer term as a clean source of energy. The low-cost approach exploits self-replication technology which it is proposed may be enabled by 3D printing technology. Self-replication of 3D printing platforms will enable mass production of simple spacecraft units. Key elements being developed are 3D-printable electric motors and 3D-printable vacuum tube-based electronics. The power of such technologies will open up enormous possibilities at low cost including space-based geoengineering.

Keywords: 3D printing, in-situ resource utilization, self-replication technology, space-based geoengineering

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Authors: Amirah Azzeri, Fatiha H. Shabaruddin, Scott A. McDonald, Rosmawati Mohamed, Maznah Dahlui

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Objective: A scaled-up treatment cascade with direct-acting antiviral (DAA) therapy is necessary to achieve global WHO targets for hepatitis C virus (HCV) elimination in Malaysia. Recently, limited access to Sofosbuvir/Daclatasvir (SOF/DAC) is available through compulsory licensing, with future access to Sofosbuvir/Velpatasvir (SOF/VEL) expected through voluntary licensing due to recent agreements. SOF/VEL has superior clinical outcomes, particularly for cirrhotic stages, but has higher drug acquisition costs compared to SOF/DAC. It has been proposed that a stratified treatment cascade might be the most cost-efficient approach for Malaysia whereby all HCV patients are treated with SOF/DAC except for patients with cirrhosis who are treated with SOF/VEL. This study aimed to conduct a five-year budget impact analysis from the provider perspective of the proposed stratified treatment cascade for HCV treatment in Malaysia. Method: A disease progression model that was developed based on model-predicted HCV epidemiology data in Malaysia was used for the analysis, where all HCV patients in scenario A were treated with SOF/DAC for all disease stages while in scenario B, SOF/DAC was used only for non-cirrhotic patients and SOF/VEL was used for the cirrhotic patients. The model projections estimated the annual numbers of patients in care and the numbers of patients to be initiated on DAA treatment nationally. Healthcare costs associated with DAA therapy and disease stage monitoring was included to estimate the downstream cost implications. For scenario B, the estimated treatment uptake of SOF/VEL for cirrhotic patients were 25%, 50%, 75%, 100% and 100% for 2018, 2019, 2020, 2021 and 2022 respectively. Healthcare costs were estimated based on standard clinical pathways for DAA treatment described in recent guidelines. All costs were reported in US dollars (conversion rate US$1=RM4.09, the price year 2018). Scenario analysis was conducted for 5% and 10% reduction of SOF/VEL acquisition cost anticipated from the competitive market pricing of generic DAA in Malaysia. Results: The stratified treatment cascade with SOF/VEL in Scenario B was found to be cost-saving compared to Scenario A. A substantial portion of the cost reduction was due to the costs associated with DAA therapy which resulted in USD 40 thousand (year 1) to USD 443 thousand (year 5) savings annually, with cumulative savings of USD 1.1 million after 5 years. Cost reductions for disease stage monitoring were seen in year three onwards which resulted in cumulative savings of USD 1.1 thousand. Scenario analysis estimated cumulative savings of USD 1.24 to USD 1.35 million when the acquisition cost of SOF/VEL was reduced. Conclusion: A stratified treatment cascade with SOF/VEL was expected to be cost-saving and can results in a budget impact reduction in overall healthcare expenditure in Malaysia compared to treatment with SOF/DAC. The better clinical efficacy with SOF/VEL is expected to halt patients’ HCV disease progression and may reduce downstream costs of treating advanced disease stages. The findings of this analysis may be useful to inform healthcare policies for HCV treatment in Malaysia.

Keywords: Malaysia, direct acting antiviral, compulsory licensing, voluntary licensing

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Authors: Ganesh Nandakumaran, Mehmet Karaata

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A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Ashley R. Logsdon, Becky F. Antle, Cynthia M. Kamer

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This study examines the cost and benefits of a family treatment drug court in an urban county in a southeastern state. Additionally, this cost analysis will provide a detailed description of the type and cost of activities to produce the services provided to child welfare families. This study utilized return-on-investment analysis, which uses child welfare practices, disaggregates them into separate activities and estimates costs for these activities including child-level placement data for total cost of care for the child. Direct and indirect costs were considered as well as saving calculations what costs would be associated with child welfare outcomes both short and long term. The costs included were general program costs (salaries, drug screens, transportation, childcare, parent education, program evaluation, visitation, incentives) or personnel costs for other team members (judges, court administrators, child welfare workers, child welfare supervisors, and community mental health provider). The savings that were used in the study were length of time in out of home care, Medicaid costs, substance exposed births, emergency room utilization and jail/probation costs. This study documents an overall savings of between $168,993.30 and $837,993.30. The total savings per family divided by the 40 families who have participated in the program was between $4,224.83 to $20,949.83 per family. The results of this cost benefit analysis are consistent with prior research documenting savings associated with out of home care and jail/probation; however, there are also unique contributions of this study to the literature on cost effectiveness of family treatment drug courts. We will present recommendations for further utilization of family treatment drug courts and how to expand the current model.

Keywords: child welfare, cost analysis, family drug court, family treatment drug court

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Authors: Paula Salazar, Rodrigo Henríquez, Pablo Zerega

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The textile, food and pharmaceutical industries are expanding daily worldwide, and they are located within the most polluting industries due to the fact that wastewater is discharged into watercourses with high concentrations of dyes and traces of drugs. Many of these compounds are stable to light and biodegradation, being considered as emerging organic contaminants. Advanced oxidation processes (AOPs) emerge as an effective alternative for the removal and elimination of this type of contaminants. Heterogeneous photocatalysis has been extensively studied as it is an efficient, low-cost and durable method. As the main photocatalyst, TiO₂ has been used for the degradation of a large number of dyes and drugs. The disadvantage of TiO₂ is its absorption in the UV region of the solar spectrum. On the other hand, quaternary chalcogenides based on Cu₂SnZnX₄ (X = S, Se) are a possible alternative due to their narrow bandgap (ca. between 0.8 to 1.5 eV depending on the phase considered), low cost, an abundance of its constituent elements in the earth's crust and its low toxicity. The objective of this research was to synthesize Cu₂SnZnS₄ (CZTS) through of a low-cost hydrothermal method and evaluate it as a potential photo-catalyst in the photo-degradation process of Congo Red. The synthesis of the nanoparticle in suspension and film onto fluorine-doped tin oxide coated glass (FTO) was carried out using a mixture of: 2 mmol CuCl₂, 1 mmol ZnCl₂, 1 mmol SnCl₂ and 4 mmol CH4N₂S in a Teflon reactor at 180⁰C for 72 h. Characterization was performed through scanning electron microscopy (SEM), X-ray diffraction (XRD) and UV VIS spectroscopy. Photo-degradation monitoring was carried out employing a UV VIS spectrophotometer. The results show that photodegradation of 55% of the dye can be obtained after 4h of exposure to polychromatic light, it should be noted that the Congo Red dye is being studied for the first time.

Keywords: CZTS, hydrothermal, photocatalysis, dye

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Authors: Vipul Shiralkar, Rohit Khadilkar, Shekhar Kulkarni, Ismail Mullani, Omkar Malvankar

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The use of water cooler has increased and become an important appliance in the world of global warming. Most of the coolers are electrically operated. In this study an experimental setup of evaporative water cooler using solar energy is designed and developed. It works on the principle of heat transfer using evaporation of water. Water is made to flow through copper tubes arranged in a specific array manner. Cotton plug is wrapped on copper tubes and rubber pipes are arranged in the same way as copper tubes above it. Water percolated from rubber pipes is absorbed by cotton plug. The setup has 40L water carrying capacity with forced cooling arrangement and variable speed fan which uses solar energy stored in 20Ah capacity battery. Fan speed greatly affects the temperature drop. Tests were performed at different fan speed. Maximum temperature drop achieved was 90C at 1440 rpm of fan speed. This temperature drop is very attractive. This water cooler uses solar energy hence it is cost efficient and it is affordable to rural community as well. The cooler is free from any harmful emissions like other refrigerants and hence environmental friendly. Very less maintenance is required as compared to the conventional electrical water cooler.

Keywords: evaporation, cooler, energy, copper, solar, cost

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Authors: Sachin Sharma

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A wireless sensor network (WSN) consists of a large number of sensor nodes which are deployed over an area to perform local computations based on information gathered from the surroundings. With the increasing demand for real-time applications in WSN, real-time critical events anticipate an efficient quality-of-service (QoS) based routing for data delivery from the network infrastructure. Hence, maximizing the lifetime of the network through minimizing the energy is an important challenge in WSN; sensors cannot be easily replaced or recharged due to their ad-hoc deployment in a hazardous environment. Considerable research has been focused on developing robust energy efficient QoS based routing protocols. The main focus of this article is primarily on periodical cycling schemes which represent the most compatible technique for energy saving and we also focus on the data-driven approaches that can be used to improve the energy efficiency. Finally, we will make a review on some communication protocols proposed for sensor networks.

Keywords: energy efficient, quality of service, wireless sensor networks, MAC

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Authors: Baikunthanath Sahoo, Santosh Kumar Sahu, Krishna Malakar

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With the essence of global environmental sustainability and green business management, the wind of business research moved towards Corporate Social Responsibility. In addition to international and national treaties, businesses have also started realising environmental protection and energy efficiency through CSR as part of business strategy in response to climate change. Considering the ambitious emission reduction target and rapid economic development of India, this study is an attempt to explore the effect of CSR on the energy efficiency management of manufacturing firms in India. By using firm-level data, the panel fixed effect model shows that the CSR dummy variable is negatively influencing the energy intensity or technically, they are energy efficient. The result demonstrates that in the presence of CSR, all the production economic variables are significant. The result also shows that doing environmental expenditure does not improve energy efficiency might be because very few firms are motivated to do such expenditure and also not common to all sectors. The interactive effect model result conforms that without considering CSR dummy as an intervening variable only Manufacturers of Chemical and Chemical products, Manufacturers of Pharmaceutical, medical chemical, and botanical products firms energy intensity low but after considering CSR in their business practices all six sub-sector firms become energy efficient. The empirical result also validate that firms are continuously engaged in CSR activities they are highly energy efficient. It is an important motivational factor for firms to become economically and environmentally sustainable in the corporate world. This analysis would help business practitioners to know how to manage today’s profitability and tomorrow’s sustainability to achieve a comparative advantage in the emerging market economy. The paper concludes that reducing energy consumption as part of their social responsibility to care for the environment, will need collaborative efforts of business society and policy bodies.

Keywords: CSR, Energy Efficiency, Indian manufacturing Sector, Business strategy

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Authors: Walid Moudani

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The Crew Reserve Assignment Problem (CRAP) considers the assignment of the crew members to a set of reserve activities covering all the scheduled flights in order to ensure a continuous plan so that operations costs are minimized while its solution must meet hard constraints resulting from the safety regulations of Civil Aviation as well as from the airlines internal agreements. The problem considered in this study is of highest interest for airlines and may have important consequences on the service quality and on the economic return of the operations. In this communication, a new mathematical formulation for the CRAP is proposed which takes into account the regulations and the internal agreements. While current solutions make use of Artificial Intelligence techniques run on main frame computers, a low cost approach is proposed to provide on-line efficient solutions to face perturbed operating conditions. The proposed solution method uses a dynamic programming approach for the duties scheduling problem and when applied to the case of a medium airline while providing efficient solutions, shows good potential acceptability by the operations staff. This optimization scheme can then be considered as the core of an on-line Decision Support System for crew reserve assignment operations management.

Keywords: airlines operations management, combinatorial optimization, dynamic programming, crew scheduling

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Authors: Rafia Hassan, Ali Rizwan, Sadaf Farhan, Bushra Sabir

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The purpose of this study is to compare the conventional crop monitoring system with the satellite based crop monitoring system in Pakistan. This study is conducted for SUPARCO (Space and Upper Atmosphere Research Commission). The study focused on the wheat crop, as it is the main cash crop of Pakistan and province of Punjab. This study will answer the following: Which system is better in terms of cost, time and man power? The man power calculated for Punjab CRS is: 1,418 personnel and for SUPARCO: 26 personnel. The total cost calculated for SUPARCO is almost 13.35 million and CRS is 47.705 million. The man hours calculated for CRS (Crop Reporting Service) are 1,543,200 hrs (136 days) and man hours for SUPARCO are 8, 320hrs (40 days). It means that SUPARCO workers finish their work 96 days earlier than CRS workers. The results show that the satellite based crop monitoring system is efficient in terms of manpower, cost and time as compared to the conventional system, and also generates early crop forecasts and estimations. The research instruments used included: Interviews, physical visits, group discussions, questionnaires, study of reports and work flows. A total of 93 employees were selected using Yamane’s formula for data collection, which is done with the help questionnaires and interviews. Comparative graphing is used for the analysis of data to formulate the results of the research. The research findings also demonstrate that although conventional methods have a strong impact still in Pakistan (for crop monitoring) but it is the time to bring a change through technology, so that our agriculture will also be developed along modern lines.

Keywords: area frame, crop reporting service, CRS, sample frame, SRS/GIS, satellite remote sensing/ geographic information system

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Authors: Mehdi Jalalpour, Mazdak Tootkaboni

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We present a computationally efficient method for reliability-based topology optimization under material properties uncertainty, which is assumed to be lognormally distributed and correlated within the domain. Computational efficiency is achieved through estimating the response statistics with stochastic perturbation of second order, using these statistics to fit an appropriate distribution that follows the empirical distribution of the response, and employing an efficient gradient-based optimizer. The proposed algorithm is utilized for design of new structures and the changes in the optimized topology is discussed for various levels of target reliability and correlation strength. Predictions were verified thorough comparison with results obtained using Monte Carlo simulation.

Keywords: material uncertainty, stochastic perturbation, structural reliability, topology optimization

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Authors: Joseph E. Hummer

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An efficient freeway system will be essential to the development of Africa, and interchanges are a key to that efficiency. Around the world, many interchanges between freeways and surface streets, called service interchanges, are of the diamond configuration, and interchanges using roundabouts or loop ramps are also popular. However, many diamond interchanges have serious operational problems, interchanges with roundabouts fail at high demand levels, and loops use lots of expensive land. Newer service interchange designs provide other options. The most popular new interchange design in the US at the moment is the double crossover diamond (DCD), also known as the diverging diamond. The DCD has enormous potential, but also has several significant limitations. The objectives of this paper are to review new service interchange options and to highlight some of the main features of those alternatives. The paper tests four conventional and seven unconventional designs using seven measures related to efficiency, cost, and safety. The results show that there is no superior design in all measures investigated. The DCD is better than most designs tested on most measures examined. However, the DCD was only superior to all other designs for bridge width. The DCD performed relatively poorly for capacity and for serving pedestrians. Based on the results, African freeway designers are encouraged to investigate the full range of alternatives that could work at the spot of interest. Diamonds and DCDs have their niches, but some of the other designs investigated could be optimum at some spots.

Keywords: interchange, diamond, diverging diamond, capacity, safety, cost

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Authors: Tarek Aboueldahab, Hanan Farag

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Cost minimization of Multiple Vehicle Routing Problem becomes a critical issue in the field of transportation because it is NP-hard optimization problem and the search space is complex. Many researches use the hybridization of artificial intelligence (AI) models to solve this problem; however, it can not guarantee to reach the best solution due to the difficulty of searching the whole search space. To overcome this problem, we introduce the hybrid model of Discrete Particle Swarm Optimization (DPSO) with a passive congregation which enable searching the whole search space to compromise between both local and global search. The practical experiment shows that our model obviously outperforms other hybrid models in cost minimization.

Keywords: cost minimization, multi-vehicle routing problem, passive congregation, discrete swarm, passive congregation

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Authors: John P. Ulhøi

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Firms are faced with pressure to stay innovative and entrepreneurial while at the same time leaving lighter ecological footprints. Traditionally inspiration for new product development (NPD) has come from the creative in-house staff and from the marketplace. Often NPD offered by this approach has proven to be (far from) optimal for its purpose or highly (resource and energy) efficient. More recently, a bio-inspired NPD approach has surfaced under the banner of biomimetics. Biomimetics refers to inspiration from and translations of designs, systems, processes, and or specific properties that exist in nature. The principles and structures working in nature have evolved over a long period of time enable them to be optimized for the purpose and resource and energy-efficient. These characteristics reflect the raison d'être behind the field of biomimetics. While biological expertise is required to understand and explain such natural and biological principles and structures, engineers are needed to translate biological design and processes into synthetic applications. It can, therefore, hardly be surprising, biomimetics long has gained a solid foothold in both biology and engineering. The commercial adoption of biomimetic applications in new production development (NDP) in industry, however, does not quite reflect a similar growth. Differently put, this situation suggests that something is missing in the biomimetic-NPD-equation, thus acting as a brake towards the wider commercial application of biomimetics and thus the use of eco-materials and design in the industry. This paper closes some of that gap. Before concluding, avenues for future research and implications for practice will be briefly sketched out.

Keywords: biomimetics, eco-materials, NPD, commercialization

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Authors: Priya Kedia, Kiranmoy Das

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There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

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The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

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Authors: V. E. Selaule, R. M. Schoeman H. C. Z. Pienaar

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Research has shown that solar energy is a renewable energy resource with the most potential when compared to other renewable energy resources in South Africa. There are many makes of Photovoltaic (PV) panels on the market and it is difficult to assess which to use. PV panel manufacturers use Standard Test Conditions (STC) to rate their PV panels. STC conditions are different from the actual operating environmental conditions were the PV panels are used. This paper describes a practical method to determine the most cost effective available PV panel. The method shows that PV panel manufacturer STC ratings cannot be used to select a cost effective PV panel.

Keywords: PV orientation, PV panel, PV STC, Solar energy

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Authors: Mao Zhaofang, Xu Yida, Fang Kan, Fu Enyuan, Zhao Zhao

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Nowadays, last-mile distribution plays an increasingly important role in the whole industrial chain delivery link and accounts for a large proportion of the whole distribution process cost. Promoting the upgrading of logistics networks and improving the layout of final distribution points has become one of the trends in the development of modern logistics. Due to the discrete and heterogeneous needs and spatial distribution of customer demand, which will lead to a higher delivery failure rate and lower vehicle utilization, last-mile delivery has become a time-consuming and uncertain process. As a result, courier companies have introduced a range of innovative parcel storage facilities, including pick-up points and lockers. The introduction of pick-up points and lockers has not only improved the users’ experience but has also helped logistics and courier companies achieve large-scale economy. Against the backdrop of the COVID-19 of the previous period, contactless delivery has become a new hotspot, which has also created new opportunities for the development of collection services. Therefore, a key issue for logistics companies is how to design/redesign their last-mile distribution network systems to create integrated logistics and distribution networks that consider pick-up points and lockers. This paper focuses on the introduction of self-pickup facilities in new logistics and distribution scenarios and the heterogeneous demands of customers. In this paper, we consider two types of demand, including ordinary products and refrigerated products, as well as corresponding transportation vehicles. We consider the constraints associated with self-pickup points and lockers and then address the location-routing problem with self-pickup facilities and heterogeneous demands (LRP-PFHD). To solve this challenging problem, we propose a mixed integer linear programming (MILP) model that aims to minimize the total cost, which includes the facility opening cost, the variable transport cost, and the fixed transport cost. Due to the NP-hardness of the problem, we propose a hybrid adaptive large-neighbourhood search algorithm to solve LRP-PFHD. We evaluate the effectiveness and efficiency of the proposed algorithm by using instances generated based on benchmark instances. The results demonstrate that the hybrid adaptive large neighbourhood search algorithm is more efficient than MILP solvers such as Gurobi for LRP-PFHD, especially for large-scale instances. In addition, we made a comprehensive analysis of some important parameters (e.g., facility opening cost and transportation cost) to explore their impacts on the results and suggested helpful managerial insights for courier companies.

Keywords: city logistics, last-mile delivery, location-routing, adaptive large neighborhood search

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Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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Authors: Antonio Ruiz Gonzalez, Kwang-Leong Choy

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The measurement of electrolytes has a high value in the clinical routine. Ions are present in all body fluids with variable concentrations and are involved in multiple pathologies such as heart failures and chronic kidney disease. In the case of dissolved potassium, although a high concentration in the blood (hyperkalemia) is relatively uncommon in the general population, it is one of the most frequent acute electrolyte abnormalities. In recent years, the integration of thin films technologies in this field has allowed the development of highly sensitive biosensors with ultra-low limits of detection for the assessment of metals in liquid samples. However, despite the current efforts in the miniaturization of sensitive devices and their integration into portable systems, only a limited number of successful examples used commercially can be found. This fact can be attributed to a high cost involved in their production and the sustained degradation of the electrodes over time, which causes a signal drift in the measurements. Thus, there is an unmet necessity for the development of low-cost and robust sensors for the real-time monitoring of analyte concentrations in patients to allow the early detection and diagnosis of diseases. This paper reports a thin film ion-selective sensor for the evaluation of potassium ions in aqueous samples. As an alternative for this fabrication method, aerosol assisted chemical vapor deposition (AACVD), was applied due to cost-effectivity and fine control over the film deposition. Such a technique does not require vacuum and is suitable for the coating of large surface areas and structures with complex geometries. This approach allowed the fabrication of highly homogeneous surfaces with well-defined microstructures onto 50 nm thin gold layers. The degradative processes of the ubiquitously employed poly (vinyl chloride) membranes in contact with an electrolyte solution were studied, including the polymer leaching process, mechanical desorption of nanoparticles and chemical degradation over time. Rational design of a protective coating based on an organosilicon material in combination with cellulose to improve the long-term stability of the sensors was then carried out, showing an improvement in the performance after 5 weeks. The antifouling properties of such coating were assessed using a cutting-edge quartz microbalance sensor, allowing the quantification of the adsorbed proteins in the nanogram range. A correlation between the microstructural properties of the films with the surface energy and biomolecules adhesion was then found and used to optimize the protective film.

Keywords: hyperkalemia, drift, AACVD, organosilicon

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Authors: Dilip Saikia, Suparna Bhattacharjee, Nirab Adhikary

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In this piece of work, we have presented the synthesis and characterization of CdTe/ZnS core/shell (CS) quantum dots (QD). CS QDs are used as a fluorescence probe to design a simple cost-effective and ultrasensitive sensor for the detection of toxic Hg(II) in an aqueous medium. Mercaptosuccinic acid (MSA) has been used as a capping agent for the synthesis CdTe/ZnS CS QD. Photoluminescence quenching mechanism has been used in the detection experiment of Hg(II). The designed sensing technique shows a remarkably low detection limit of about 1 picomolar (pM). Here, the CS QDs are synthesized by a simple one-pot aqueous method. The synthesized CS QDs are characterized by using advanced diagnostics tools such as UV-vis, Photoluminescence, XRD, FTIR, TEM and Zeta potential analysis. The interaction between CS QDs and the Hg(II) ions results in the quenching of photoluminescence (PL) intensity of QDs, via the mechanism of excited state electron transfer. The proposed mechanism is explained using cyclic voltammetry and zeta potential analysis. The designed sensor is found to be highly selective towards Hg (II) ions. The analysis of the real samples such as drinking water and tap water has been carried out and the CS QDs show remarkably good results. Using this simple sensing method we have designed a prototype low-cost electronic device for the detection of Hg(II) in an aqueous medium. The findings of the experimental results of the designed sensor is crosschecked by using AAS analysis.

Keywords: photoluminescence, quantum dots, quenching, sensor

Procedia PDF Downloads 244