Search results for: non-convex cost function
Commenced in January 2007
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Edition: International
Paper Count: 10425

Search results for: non-convex cost function

8505 Techno-Economic Analysis of Offshore Hybrid Energy Systems with Hydrogen Production

Authors: Anna Crivellari, Valerio Cozzani

Abstract:

Even though most of the electricity produced in the entire world still comes from fossil fuels, new policies are being implemented in order to promote a more sustainable use of energy sources. Offshore renewable resources have become increasingly attractive thanks to the huge entity of power potentially obtained. However, the intermittent nature of renewables often limits the capacity of the systems and creates mismatches between supply and demand. Hydrogen is foreseen to be a promising vector to store and transport large amounts of excess renewable power by using existing oil and gas infrastructure. In this work, an offshore hybrid energy system integrating wind energy conversion with hydrogen production was conceptually defined and applied to offshore gas platforms. A techno-economic analysis was performed by considering two different locations for the installation of the innovative power system, i.e., the North Sea and the Adriatic Sea. The water depth, the distance of the platform from the onshore gas grid, the hydrogen selling price and the green financial incentive were some of the main factors taken into account in the comparison. The results indicated that the use of well-defined indicators allows to capture specifically different cost and revenue features of the analyzed systems, as well as to evaluate their competitiveness in the actual and future energy market.

Keywords: cost analysis, energy efficiency assessment, hydrogen production, offshore wind energy

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8504 Hybrid Renewable Energy Systems for Electricity and Hydrogen Production in an Urban Environment

Authors: Same Noel Ngando, Yakub Abdulfatai Olatunji

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Renewable energy micro-grids, such as those powered by solar or wind energy, are often intermittent in nature. This means that the amount of energy generated by these systems can vary depending on weather conditions or other factors, which can make it difficult to ensure a steady supply of power. To address this issue, energy storage systems have been developed to increase the reliability of renewable energy micro-grids. Battery systems have been the dominant energy storage technology for renewable energy micro-grids. Batteries can store large amounts of energy in a relatively small and compact package, making them easy to install and maintain in a micro-grid setting. Additionally, batteries can be quickly charged and discharged, allowing them to respond quickly to changes in energy demand. However, the process involved in recycling batteries is quite costly and difficult. An alternative energy storage system that is gaining popularity is hydrogen storage. Hydrogen is a versatile energy carrier that can be produced from renewable energy sources such as solar or wind. It can be stored in large quantities at low cost, making it suitable for long-distance mass storage. Unlike batteries, hydrogen does not degrade over time, so it can be stored for extended periods without the need for frequent maintenance or replacement, allowing it to be used as a backup power source when the micro-grid is not generating enough energy to meet demand. When hydrogen is needed, it can be converted back into electricity through a fuel cell. Energy consumption data is got from a particular residential area in Daegu, South Korea, and the data is processed and analyzed. From the analysis, the total energy demand is calculated, and different hybrid energy system configurations are designed using HOMER Pro (Hybrid Optimization for Multiple Energy Resources) and MATLAB software. A techno-economic and environmental comparison and life cycle assessment (LCA) of the different configurations using battery and hydrogen as storage systems are carried out. The various scenarios included PV-hydrogen-grid system, PV-hydrogen-grid-wind, PV-hydrogen-grid-biomass, PV-hydrogen-wind, PV-hydrogen-biomass, biomass-hydrogen, wind-hydrogen, PV-battery-grid-wind, PV- battery -grid-biomass, PV- battery -wind, PV- battery -biomass, and biomass- battery. From the analysis, the least cost system for the location was the PV-hydrogen-grid system, with a net present cost of about USD 9,529,161. Even though all scenarios were environmentally friendly, taking into account the recycling cost and pollution involved in battery systems, all systems with hydrogen as a storage system produced better results. In conclusion, hydrogen is becoming a very prominent energy storage solution for renewable energy micro-grids. It is easier to store compared with electric power, so it is suitable for long-distance mass storage. Hydrogen storage systems have several advantages over battery systems, including flexibility, long-term stability, and low environmental impact. The cost of hydrogen storage is still relatively high, but it is expected to decrease as more hydrogen production, and storage infrastructure is built. With the growing focus on renewable energy and the need to reduce greenhouse gas emissions, hydrogen is expected to play an increasingly important role in the energy storage landscape.

Keywords: renewable energy systems, microgrid, hydrogen production, energy storage systems

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8503 Economic Impact and Benefits of Integrating Augmented Reality Technology in the Healthcare Industry: A Systematic Review

Authors: Brenda Thean I. Lim, Safurah Jaafar

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Augmented reality (AR) in the healthcare industry has been gaining popularity in recent years, principally in areas of medical education, patient care and digital health solutions. One of the drivers in deciding to invest in AR technology is the potential economic benefits it could bring for patients and healthcare providers, including the pharmaceutical and medical technology sectors. Works of literature have shown that the benefits and impact of AR technologies have left trails of achievements in improving medical education and patient health outcomes. However, little has been published on the economic impact of AR in healthcare, a very resource-intensive industry. This systematic review was performed on studies focused on the benefits and impact of AR in healthcare to appraise if they meet the founded quality criteria so as to identify relevant publications for an in-depth analysis of the economic impact assessment. The literature search was conducted using multiple databases such as PubMed, Cochrane, Science Direct and Nature. Inclusion criteria include research papers on AR implementation in healthcare, from education to diagnosis and treatment. Only papers written in English language were selected. Studies on AR prototypes were excluded. Although there were many articles that have addressed the benefits of AR in the healthcare industry in the area of medical education, treatment and diagnosis and dental medicine, there were very few publications that identified the specific economic impact of technology within the healthcare industry. There were 13 publications included in the analysis based on the inclusion criteria. Out of the 13 studies, none comprised a systematically comprehensive cost impact evaluation. An outline of the cost-effectiveness and cost-benefit framework was made based on an AR article from another industry as a reference. This systematic review found that while the advancements of AR technology is growing rapidly and industries are starting to adopt them into respective sectors, the technology and its advancements in healthcare were still in their early stages. There are still plenty of room for further advancements and integration of AR into different sectors within the healthcare industry. Future studies will require more comprehensive economic analyses and costing evaluations to enable economic decisions for or against implementing AR technology in healthcare. This systematic review concluded that the current literature lacked detailed examination and conduct of economic impact and benefit analyses. Recommendations for future research would be to include details of the initial investment and operational costs for the AR infrastructure in healthcare settings while comparing the intervention to its conventional counterparts or alternatives so as to provide a comprehensive comparison on impact, benefit and cost differences.

Keywords: augmented reality, benefit, economic impact, healthcare, patient care

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8502 Integral Form Solutions of the Linearized Navier-Stokes Equations without Deviatoric Stress Tensor Term in the Forward Modeling for FWI

Authors: Anyeres N. Atehortua Jimenez, J. David Lambraño, Juan Carlos Muñoz

Abstract:

Navier-Stokes equations (NSE), which describe the dynamics of a fluid, have an important application on modeling waves used for data inversion techniques as full waveform inversion (FWI). In this work a linearized version of NSE and its variables, neglecting deviatoric terms of stress tensor, is presented. In order to get a theoretical modeling of pressure p(x,t) and wave velocity profile c(x,t), a wave equation of visco-acoustic medium (VAE) is written. A change of variables p(x,t)=q(x,t)h(ρ), is made on the equation for the VAE leading to a well known Klein-Gordon equation (KGE) describing waves propagating in variable density medium (ρ) with dispersive term α^2(x). KGE is reduced to a Poisson equation and solved by proposing a specific function for α^2(x) accounting for the energy dissipation and dispersion. Finally, an integral form solution is derived for p(x,t), c(x,t) and kinematics variables like particle velocity v(x,t), displacement u(x,t) and bulk modulus function k_b(x,t). Further, it is compared this visco-acoustic formulation with another form broadly used in the geophysics; it is argued that this formalism is more general and, given its integral form, it may offer several advantages from the modern parallel computing point of view. Applications to minimize the errors in modeling for FWI applied to oils resources in geophysics are discussed.

Keywords: Navier-Stokes equations, modeling, visco-acoustic, inversion FWI

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8501 Constitutive Androstane Receptor (CAR) Inhibitor CINPA1 as a Tool to Understand CAR Structure and Function

Authors: Milu T. Cherian, Sergio C. Chai, Morgan A. Casal, Taosheng Chen

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This study aims to use CINPA1, a recently discovered small-molecule inhibitor of the xenobiotic receptor CAR (constitutive androstane receptor) for understanding the binding modes of CAR and to guide CAR-mediated gene expression profiling studies in human primary hepatocytes. CAR and PXR are xenobiotic sensors that respond to drugs and endobiotics by modulating the expression of metabolic genes that enhance detoxification and elimination. Elevated levels of drug metabolizing enzymes and efflux transporters resulting from CAR activation promote the elimination of chemotherapeutic agents leading to reduced therapeutic effectiveness. Multidrug resistance in tumors after chemotherapy could be associated with errant CAR activity, as shown in the case of neuroblastoma. CAR inhibitors used in combination with existing chemotherapeutics could be utilized to attenuate multidrug resistance and resensitize chemo-resistant cancer cells. CAR and PXR have many overlapping modulating ligands as well as many overlapping target genes which confounded attempts to understand and regulate receptor-specific activity. Through a directed screening approach we previously identified a new CAR inhibitor, CINPA1, which is novel in its ability to inhibit CAR function without activating PXR. The cellular mechanisms by which CINPA1 inhibits CAR function were also extensively examined along with its pharmacokinetic properties. CINPA1 binding was shown to change CAR-coregulator interactions as well as modify CAR recruitment at DNA response elements of regulated genes. CINPA1 was shown to be broken down in the liver to form two, mostly inactive, metabolites. The structure-activity differences of CINPA1 and its metabolites were used to guide computational modeling using the CAR-LBD structure. To rationalize how ligand binding may lead to different CAR pharmacology, an analysis of the docked poses of human CAR bound to CITCO (a CAR activator) vs. CINPA1 or the metabolites was conducted. From our modeling, strong hydrogen bonding of CINPA1 with N165 and H203 in the CAR-LBD was predicted. These residues were validated to be important for CINPA1 binding using single amino-acid CAR mutants in a CAR-mediated functional reporter assay. Also predicted were residues making key hydrophobic interactions with CINPA1 but not the inactive metabolites. Some of these hydrophobic amino acids were also identified and additionally, the differential coregulator interactions of these mutants were determined in mammalian two-hybrid systems. CINPA1 represents an excellent starting point for future optimization into highly relevant probe molecules to study the function of the CAR receptor in normal- and pathophysiology, and possible development of therapeutics (for e.g. use for resensitizing chemoresistant neuroblastoma cells).

Keywords: antagonist, chemoresistance, constitutive androstane receptor (CAR), multi-drug resistance, structure activity relationship (SAR), xenobiotic resistance

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8500 Decomposition of the Discount Function Into Impatience and Uncertainty Aversion. How Neurofinance Can Help to Understand Behavioral Anomalies

Authors: Roberta Martino, Viviana Ventre

Abstract:

Intertemporal choices are choices under conditions of uncertainty in which the consequences are distributed over time. The Discounted Utility Model is the essential reference for describing the individual in the context of intertemporal choice. The model is based on the idea that the individual selects the alternative with the highest utility, which is calculated by multiplying the cardinal utility of the outcome, as if the reception were instantaneous, by the discount function that determines a decrease in the utility value according to how the actual reception of the outcome is far away from the moment the choice is made. Initially, the discount function was assumed to have an exponential trend, whose decrease over time is constant, in line with a profile of a rational investor described by classical economics. Instead, empirical evidence called for the formulation of alternative, hyperbolic models that better represented the actual actions of the investor. Attitudes that do not comply with the principles of classical rationality are termed anomalous, i.e., difficult to rationalize and describe through normative models. The development of behavioral finance, which describes investor behavior through cognitive psychology, has shown that deviations from rationality are due to the limited rationality condition of human beings. What this means is that when a choice is made in a very difficult and information-rich environment, the brain does a compromise job between the cognitive effort required and the selection of an alternative. Moreover, the evaluation and selection phase of the alternative, the collection and processing of information, are dynamics conditioned by systematic distortions of the decision-making process that are the behavioral biases involving the individual's emotional and cognitive system. In this paper we present an original decomposition of the discount function to investigate the psychological principles of hyperbolic discounting. It is possible to decompose the curve into two components: the first component is responsible for the smaller decrease in the outcome as time increases and is related to the individual's impatience; the second component relates to the change in the direction of the tangent vector to the curve and indicates how much the individual perceives the indeterminacy of the future indicating his or her aversion to uncertainty. This decomposition allows interesting conclusions to be drawn with respect to the concept of impatience and the emotional drives involved in decision-making. The contribution that neuroscience can make to decision theory and inter-temporal choice theory is vast as it would allow the description of the decision-making process as the relationship between the individual's emotional and cognitive factors. Neurofinance is a discipline that uses a multidisciplinary approach to investigate how the brain influences decision-making. Indeed, considering that the decision-making process is linked to the activity of the prefrontal cortex and amygdala, neurofinance can help determine the extent to which abnormal attitudes respect the principles of rationality.

Keywords: impatience, intertemporal choice, neurofinance, rationality, uncertainty

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8499 Radial Distribution Network Reliability Improvement by Using Imperialist Competitive Algorithm

Authors: Azim Khodadadi, Sahar Sadaat Vakili, Ebrahim Babaei

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This study presents a numerical method to optimize the failure rate and repair time of a typical radial distribution system. Failure rate and repair time are effective parameters in customer and energy based indices of reliability. Decrease of these parameters improves reliability indices. Thus, system stability will be boost. The penalty functions indirectly reflect the cost of investment which spent to improve these indices. Constraints on customer and energy based indices, i.e. SAIFI, SAIDI, CAIDI and AENS have been considered by using a new method which reduces optimization algorithm controlling parameters. Imperialist Competitive Algorithm (ICA) used as main optimization technique and particle swarm optimization (PSO), simulated annealing (SA) and differential evolution (DE) has been applied for further investigation. These algorithms have been implemented on a test system by MATLAB. Obtained results have been compared with each other. The optimized values of repair time and failure rate are much lower than current values which this achievement reduced investment cost and also ICA gives better answer than the other used algorithms.

Keywords: imperialist competitive algorithm, failure rate, repair time, radial distribution network

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8498 Investigation of Mechanical Properties on natural fiber Reinforced Epoxy Composites

Authors: Gopi Kerekere Rangaraju, Madhu Puttegowda

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Natural fibres composites include coir, jute, bagasse, cotton, bamboo, and hemp. Natural fibers come from plants. These fibers contain lingo cellulose in nature. Natural fibers are eco-friendly; lightweight, strong, renewable, cheap, and biodegradable. The natural fibers can be used to reinforce both thermosetting and thermoplastic matrices. Thermosetting resins such as epoxy, polyester, polyurethane, and phenolic are commonly used composites requiring higher performance applications. They provide sufficient mechanical properties, in particular, stiffness and strength at acceptably low-price levels. Recent advances in natural fibers development are genetic engineering. The composites science offers significant opportunities for improved materials from renewable resources with enhanced support for global sustainability. Natural fibers composites are attractive to industry because of their low density and ecological advantages over conventional composites. These composites are gaining importance due to their non-carcinogenic and bio-degradable nature. Natural fibers composites are a very costeffective material, especially in building and construction, packaging, automobile and railway coach interiors, and storage devices. These composites are potential candidates for the replacement of high- cost glass fibers for low load bearing applications. Natural fibers have the advantages of low density, low cost, and biodegradability

Keywords: PMC, basalt, coir, carbon fibers

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8497 Development and Evaluation of a Gut-Brain Axis Chip Based on 3D Printing Interconnecting Microchannel Scaffolds

Authors: Zhuohan Li, Jing Yang, Yaoyuan Cui

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The gut-brain axis (GBA), a communication network between gut microbiota and the brain, benefits for investigation of brain diseases. Currently, organ chips are considered one of the potential tools for GBA research. However, most of the available GBA chips have limitations in replicating the three-dimensional (3D) growth environment of cells and lack the required cell types for barrier function. In the present study, a microfluidic chip was developed for GBA interaction. Blood-brain barrier (BBB) module was prepared with HBMEC, HBVP, U87 cells and decellularized matrix (dECM). Intestinal epithelial barrier (IEB) was prepared with Caco-2 and vascular endothelial cells and dECM. GBA microfluidic device was integrated with IEB and BBB modules using 3D printing interconnecting microchannel scaffolds. BBB and IEB interaction on this GBA chip were evaluated with lipopolysaccharide (LPS) exposure. The present GBA chip achieved multicellular three-dimensional cultivation. Compared with the co-culture cell model in the transwell, fluorescein was absorbed more slowly by 5.16-fold (IEB module) and 4.69-fold (BBB module) on the GBA chip. Accumulation of Rhodamine 123 and Hoechst33342 was dramatically decreased. The efflux function of transporters on IEB and BBB was significantly increased on the GBA chip. After lipopolysaccharide (LPS) disrupted the IEB, and then BBB dysfunction was further observed, which confirmed the interaction between IEB and BBB modules. These results demonstrated that this GBA chip may offer a promising tool for gut-brain interaction study.

Keywords: decellularized matrix, gut-brain axis, organ-on-chip, three-dimensional printing.

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8496 Antigen-Presenting Cell Characteristics of Human γδ T Lymphocytes in Chronic Myeloid Leukemia

Authors: Piamsiri Sawaisorn, Tienrat Tangchaikeeree, Waraporn Chan-On, Chaniya Leepiyasakulchai, Rachanee Udomsangpetch, Suradej Hongeng, Kulachart Jangpatarapongsa

Abstract:

Human Vγ9Vδ2 T lymphocytes are regarded as promising effector cells for cancer immunotherapy since they have the ability to eliminate several tumor cells through non-peptide antigen recognition and non-major histocompatibility complex (MHC) restriction. An issue of recent interest is the capability to activate γδ T cells by use of a group of drugs, such as pamidronate, that cause accumulation of phosphoantigen which is recognized by γδ T cell receptors. Moreover, their antigen presenting cell-like phenotype and function have been confirmed in many clinical trials. In this study, Vγ9Vδ2 T cells derived from normal peripheral blood mononuclear cells were activated with pamidronate and the expanded Vγ9Vδ2 T cells can recognize and kill chronic myeloid leukemia (CML) cells treated with pamidronate through their cytotoxic activity. To support the strong role played by Vγ9Vδ2 T cells against cancer, we provide the evidence that Vγ9Vδ2 T cells activated with CML cell lysate antigen can efficiently express antigen presenting cell (APC) phenotype and function. In conclusion, pamidronate can be used in intentional activation of human Vγ9Vδ2 T cells and can increase the susceptibility of CML cells to cytotoxicity of Vγ9Vδ2 T cells. The activated Vγ9Vδ2 T cells by cancer cells lysate can show their APC characteristics, and so greatly increase the interest in exploring their therapeutic potential in hematologic malignancy.

Keywords: γδ T lymphocytes, antigen-presenting cells, chronic myeloid leukemia, cancer, immunotherapy

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8495 Design and Implementation of Agricultural Machinery Equipment Scheduling Platform Based On Case-Based Reasoning

Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

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8494 Effects of Virtual Reality Treadmill Training on Gait and Balance Performance of Patients with Stroke: Review

Authors: Hanan Algarni

Abstract:

Background: Impairment of walking and balance skills has negative impact on functional independence and community participation after stroke. Gait recovery is considered a primary goal in rehabilitation by both patients and physiotherapists. Treadmill training coupled with virtual reality technology is a new emerging approach that offers patients with feedback, open and random skills practice while walking and interacting with virtual environmental scenes. Objectives: To synthesize the evidence around the effects of the VR treadmill training on gait speed and balance primarily, functional independence and community participation secondarily in stroke patients. Methods: Systematic review was conducted; search strategy included electronic data bases: MEDLINE, AMED, Cochrane, CINAHL, EMBASE, PEDro, Web of Science, and unpublished literature. Inclusion criteria: Participant: adult >18 years, stroke, ambulatory, without severe visual or cognitive impartments. Intervention: VR treadmill training alone or with physiotherapy. Comparator: any other interventions. Outcomes: gait speed, balance, function, community participation. Characteristics of included studies were extracted for analysis. Risk of bias assessment was performed using Cochrane's ROB tool. Narrative synthesis of findings was undertaken and summary of findings in each outcome was reported using GRADEpro. Results: Four studies were included involving 84 stroke participants with chronic hemiparesis. Interventions intensity ranged (6-12 sessions, 20 minutes-1 hour/session). Three studies investigated the effects on gait speed and balance. 2 studies investigated functional outcomes and one study assessed community participation. ROB assessment showed 50% unclear risk of selection bias and 25% of unclear risk of detection bias across the studies. Heterogeneity was identified in the intervention effects at post training and follow up. Outcome measures, training intensity and durations also varied across the studies, grade of evidence was low for balance, moderate for speed and function outcomes, and high for community participation. However, it is important to note that grading was done on few numbers of studies in each outcome. Conclusions: The summary of findings suggests positive and statistically significant effects (p<0.05) of VR treadmill training compared to other interventions on gait speed, dynamic balance skills, function and participation directly after training. However, the effects were not sustained at follow up in two studies (2 weeks-1 month) and other studies did not perform follow up measurements. More RCTs with larger sample sizes and higher methodological quality are required to examine the long term effects of VR treadmill effects on function independence and community participation after stroke, in order to draw conclusions and produce stronger robust evidence.

Keywords: virtual reality, treadmill, stroke, gait rehabilitation

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8493 Rapid-Access Multispecialty Nurse-Led Tongue Tie Service: A Retrospective Evaluation of Cost-Effectiveness

Authors: Jia Yin Tan, Daniel Rambei, Kate Mann, Samuel price, Ahmed Aboelela

Abstract:

Introduction: Breastfeeding is a complex process, influenced by various factors. Tongue-tie may lead to breastfeeding difficulties due to an inability to suck effectively, causing sore nipples and poor infant weight gain. In the UK, most frenotomies on infants are performed by doctors, nurses, health visitors or midwives. Objectives: Evaluation of safety and efficacy of a multispecialty nurse-led rapid access tongue-tie service at Sheffield Children’s Hospital, run jointly by the ENT and paediatric surgery departments. Methodology: A retrospective observational study, including all patients attending the ENT and paediatric surgery nurse-led tongue tie clinics between 1/10/2021 and 30/09/2022. Results: During the study period there were 1135 referrals for frenotomy, with a mean of 15 days between referral to clinic episode. 86.8% of referred patients underwent frenotomy, with a complication rate of 0.1% and revision rate of 5.4%. Conclusions: Our findings suggest that our rapid access nurse-led outpatient tongue tie service is safe and efficacious, with low complication and revision rates. This suggests a potential for developing a community-based service, allowing safe and effective care closer to home.

Keywords: tongue tie, frenotomy, cost, nurse-led

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8492 Degree Tracking System (DTS) to Improve the Efficiency and Effectiveness of Open Distance Learning System: A Case Study of Islamabad Allama Iqbal Open University (AIOU)

Authors: Hatib Shabbir

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Student support services play an important role in providing technical and motivational support to distance learner. ICT based systems have improved the efficiency and effectiveness of support services. In distance education, students being at distant require quick responses from their institution. In the manual system, it is practically hard to give prompt response to each and every student, so as a result student has to suffer a lot. The best way to minimize inefficiencies is to use automated systems. This project involves the development of centralized automated software that would not only replace the manual degree issuance system of 1.3 million students studying at AIOU but also provide online tracking to all the students applying for Degrees. DTS is also the first step towards the paperless culture which is adopted by the major organizations of the world. DTS would not only save university cost but also save students cost and time too by conveying all the information/objection through email and SMS. Moreover, DTS also monitors the performance of each and every individual working in the exam department AIOU and generates daily, monthly and yearly reports of every individual which helps a lot in continuous performance monitoring of the employees.

Keywords: aiou dts, dts aiou, dts, degree tracking aiou

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8491 Heuristic Methods for the Capacitated Location- Allocation Problem with Stochastic Demand

Authors: Salinee Thumronglaohapun

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The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.

Keywords: location-allocation problem, stochastic demand, local search, genetic algorithm

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8490 Proposal of Non-Destructive Inspection Function Based on Internet of Things Technology Using Drone

Authors: Byoungjoon Yu, Jihwan Park, Sujung Sin, Junghyun Im, Minsoo Park, Sehwan Park, Seunghee Park

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In this paper, we propose a technology to monitor the soundness of an Internet-based bridge using a non-conductive inspection function. There has been a collapse accident due to the aging of the bridge structure, and it is necessary to prepare for the deterioration of the bridge. The NDT/SHM system for maintenance of existing bridge structures requires a large number of inspection personnel and expensive inspection costs, and access of expensive and large equipment to measurement points is required. Because current drone inspection equipment can only be inspected through camera, it is difficult to inspect inside damage accurately, and the results of an internal damage evaluation are subjective, and it is difficult for non-specialists to recognize the evaluation results. Therefore, it is necessary to develop NDT/SHM techniques for maintenance of new-concept bridge structures that allow for free movement and real-time evaluation of measurement results. This work is financially supported by Korea Ministry of Land, Infrastructure, and Transport (MOLIT) as 'Smart City Master and Doctor Course Grant Program' and a grant (14SCIP-B088624-01) from Construction Technology Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: Structural Health Monitoring, SHM, non-contact sensing, nondestructive testing, NDT, Internet of Things, autonomous self-driving drone

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8489 New Variational Approach for Contrast Enhancement of Color Image

Authors: Wanhyun Cho, Seongchae Seo, Soonja Kang

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In this work, we propose a variational technique for image contrast enhancement which utilizes global and local information around each pixel. The energy functional is defined by a weighted linear combination of three terms which are called on a local, a global contrast term and dispersion term. The first one is a local contrast term that can lead to improve the contrast of an input image by increasing the grey-level differences between each pixel and its neighboring to utilize contextual information around each pixel. The second one is global contrast term, which can lead to enhance a contrast of image by minimizing the difference between its empirical distribution function and a cumulative distribution function to make the probability distribution of pixel values becoming a symmetric distribution about median. The third one is a dispersion term that controls the departure between new pixel value and pixel value of original image while preserving original image characteristics as well as possible. Second, we derive the Euler-Lagrange equation for true image that can achieve the minimum of a proposed functional by using the fundamental lemma for the calculus of variations. And, we considered the procedure that this equation can be solved by using a gradient decent method, which is one of the dynamic approximation techniques. Finally, by conducting various experiments, we can demonstrate that the proposed method can enhance the contrast of colour images better than existing techniques.

Keywords: color image, contrast enhancement technique, variational approach, Euler-Lagrang equation, dynamic approximation method, EME measure

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8488 Cross-sectional Developmental Trajectories of Executive Function and Relations to Theory of Mind in Autism Spectrum Disorder

Authors: Evangelia-Chrysanthi Kouklari, Evdokia Tagkouli, Vassiliki Ntre, Artemios Pehlivanidis, Stella Tsermentseli, Gerasimos Kolaitis, Katerina Papanikolaou

Abstract:

Executive Function (EF) is a set of goal-directed cognitive skills essentially needed in problem-solving and social behavior. Developmental EF research has indicated that EF emerges early in life and marks dramatic changes before the age of 5. Research evidence has suggested that it may continue to develop up to adolescence as well, following the development of the prefrontal cortex. Over the last decade, research evidence has suggested distinguished domains of cool and hot EF, but traditionally the development of EF in Autism Spectrum Disorder (ASD) has been examined mainly with tasks that address the “cool” cognitive aspects of EF. Thus, very little is known about the development of “hot” affective EF processes and whether the cross-sectional developmental pathways of cool and hot EF present similarities in ASD. Cool EF has also been proven to have a strong correlation with Theory of Mind (ToM) in young and middle childhood in typical development and in ASD, but information about the relationship of hot EF to ToM skills is minimal. The present study’s objective was to explore the age-related changes of cool and hot EF in ASD participants from middle childhood to adolescence, as well as their relationship to ToM. This study employed an approach of cross-sectional developmental trajectories to investigate patterns of cool and hot EF relative to chronological age within ASD. Eighty-two participants between 7 and 16 years of age were recruited to undertake measures that assessed cool EF (working memory, cognitive flexibility, planning & inhibition), hot EF (affective decision making & delay discounting) and ToM (false belief and mental state/emotion recognition). Results demonstrated that trajectories of all cool EF presented age-related changes in ASD (improvements with age). With regards to hot EF, affective decision-making presented age-related changes, but for delay discounting, there were no statistically significant changes found across younger and older ASD participants. ToM was correlated only to cool EF. Theoretical implications are discussed as the investigation of the cross-sectional developmental trajectories of the broader EF (cool and hot domains) may contribute to better defining cognitive phenotypes in ASD. These findings highlight the need to examine developmental trajectories of both hot and cool EF in research and clinical practice as they may aid in enhancing diagnosis or better-informed intervention programs.

Keywords: autism spectrum disorder, developmental trajectories, executive function, theory of mind

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8487 Socioeconomic Impacts of Innovative Housing Construction Technologies in Slum Upgrading: Case of Mathare Valley Nairobi, Kenya

Authors: Edmund M. Muthigani

Abstract:

Background: Adequate, decent housing is a universal human right integral component. Resources’ costs and intensified rural-urban migration have increased the demand for affordable housing in urban areas. Modern knowledge-based economy uses innovation. The construction industry uses product and process innovation to provide adequate and decent low-cost housing. Kenya adopted innovation practices in slum upgrading that used cost-effectively locally available building materials. This study objectively looked at the outcomes, social and economic impacts of innovative housing technologies construction in the Mathare valley slums upgrading project. Methods: This post-occupancy study used an exploratory-descriptive research design. Random sampling was used to sample 384 users of low-cost housing projects in Mathare Valley, Nairobi County. Research instruments included semi-structured questionnaires and interview guides. Pilot study, validity and reliability tests ensured the quality of a study. Ethical considerations included university approval and consent. Statistical package for social sciences (SPSS) software version 21 was applied to compute the descriptive and inferential statistics. Findings: Slum-upgrading had a significant-positive outcome on improved houses and community. Social impacts included communal facilities, assurance of security of tenure, and retained frameworks of establishments. Economic impacts included employment; affordable and durable units (p values <0.05). The upgrading process didn’t influence rent fees, was corrupt and led to the displacement of residents. Conclusion: Slum upgrading process impacted positively. Similar projects should consider residents in decision-making.

Keywords: innovation, technologies, slum upgrading, Mathare valley slum, social impact, economic impact

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8486 Risk Assessment of Heavy Rainfall and Development of Damage Prediction Function for Gyeonggi-Do Province

Authors: Jongsung Kim, Daegun Han, Myungjin Lee, Soojun Kim, Hung Soo Kim

Abstract:

Recently, the frequency and magnitude of natural disasters are gradually increasing due to climate change. Especially in Korea, large-scale damage caused by heavy rainfall frequently occurs due to rapid urbanization. Therefore, this study proposed a Heavy rain Damage Risk Index (HDRI) using PSR (Pressure – State - Response) structure for heavy rain risk assessment. We constructed pressure index, state index, and response index for the risk assessment of each local government in Gyeonggi-do province, and the evaluation indices were determined by principal component analysis. The indices were standardized using the Z-score method then HDRIs were obtained for 31 local governments in the province. The HDRI is categorized into three classes, say, the safest class is 1st class. As the results, the local governments of the 1st class were 15, 2nd class 7, and 3rd class 9. From the study, we were able to identify the risk class due to the heavy rainfall for each local government. It will be useful to develop the heavy rainfall prediction function by risk class, and this was performed in this issue. Also, this risk class could be used for the decision making for efficient disaster management. Acknowledgements: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B3005695).

Keywords: natural disaster, heavy rain risk assessment, HDRI, PSR

Procedia PDF Downloads 192
8485 Suppression of Immunostimulatory Function of Dendritic Cells and Prolongation of Skin Allograft Survival by Dryocrassin

Authors: Hsin-Lien Lin, Ju-Hui Fu

Abstract:

Dendritic cells (DCs) are the major professional antigen-presenting cells for the development of optimal T-cell immunity. DCs can be used as pharmacological targets to screen novel biological modifiers for the treatment of harmful immune responses, such as transplantation rejection. Dryopteris crassirhizoma Nakai (Aspiadaceae) is used for traditional herbal medicine in the region of East Asia. The root of this fern plant has been listed for treating inflammatory diseases. Dryocrassin is the tetrameric phlorophenone component derived from Dryopteris. Here, we tested the immunomodulatory potential of dryocrassin on lipopolysaccharide (LPS)-stimulated activation of mouse bone marrow-derived DCs in vitro and in skin allograft transplantation in vivo. Results demonstrated that dryocrassin reduced the secretion of tumor necrosis factor-α, interleukin-6, and interleukin-12p70 by LPS-stimulated DCs. The expression of LPS-induced major histocompatibility complex class II, CD40, and CD86 on DCs was also blocked by dryocrassin. Moreover, LPS-stimulated DC-elicited allogeneic T-cell proliferation was lessened by dryocrassin. In addition, dryocrassin inhibited LPS-induced activation of IϰB kinase, JNK/p38 mitogen-activated protein kinase, as well as the translocation of NF-ϰB. Treatment with dryocrassin obviously diminished 2,4-dinitro-1-fluorobenzene- induced delayed-type hypersensitivity and prolonged skin allograft survival. Dryocrassin may be one of the potent immunosuppressive agents for transplant rejection through the destruction of DC maturation and function.

Keywords: dryocrassin, dendritic cells, immunosuppression, skin allograft

Procedia PDF Downloads 377
8484 Potential of Irish Orientated Strand Board in Bending Active Structures

Authors: Matt Collins, Bernadette O'Regan, Tom Cosgrove

Abstract:

To determine the potential of a low cost Irish engineered timber product to replace high cost solid timber for use in bending active structures such as gridshells a single Irish engineered timber product in the form of orientated strand board (OSB) was selected. A comparative study of OSB and solid timber was carried out to determine the optimum properties that make a material suitable for use in gridshells. Three parameters were identified to be relevant in the selection of a material for gridshells. These three parameters are the strength to stiffness ratio, the flexural stiffness of commercially available sections, and the variability of material and section properties. It is shown that when comparing OSB against solid timber, OSB is a more suitable material for use in gridshells that are at the smaller end of the scale and that have tight radii of curvature. Typically, for solid timber materials, stiffness is used as an indicator for strength and engineered timber is no different. Thus, low flexural stiffness would mean low flexural strength. However, when it comes to bending active gridshells, OSB offers a significant advantage. By the addition of multiple layers, an increased section size is created, thus endowing the structure with higher stiffness and higher strength from initial low stiffness and low strength materials while still maintaining tight radii of curvature. This allows OSB to compete with solid timber on large scale gridshells. Additionally, a preliminary sustainability study using a set of sustainability indicators was carried out to determine the relative sustainability of building a large-scale gridshell in Ireland with a primary focus on economic viability but a mention is also given to social and environmental aspects. For this, the Savill garden gridshell in the UK was used as the functional unit with the sustainability of the structural roof skeleton constructed from UK larch solid timber being compared with the same structure using Irish OSB. Albeit that the advantages of using commercially available OSB in a bending active gridshell are marginal and limited to specific gridshell applications, further study into an optimised engineered timber product is merited.

Keywords: bending active gridshells, high end timber structures, low cost material, sustainability

Procedia PDF Downloads 369
8483 Finite-Sum Optimization: Adaptivity to Smoothness and Loopless Variance Reduction

Authors: Bastien Batardière, Joon Kwon

Abstract:

For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

Procedia PDF Downloads 57
8482 Manufacturing and Characterization of Bioresorbable Self-Reinforced PLA Composites for Bone Applications

Authors: Carolina Pereira Lobato Costa, Cristina Pascual-González, Monica Echeverry, Javier LLorca, Carlos Gonzáléz, Juan Pedro Fernández-Bláquez

Abstract:

Although the potential of PLA self-reinforced composites for bone applications, not much literature addresses optimal manufacturing conditions. In this regard, this paper describes the woven self-reinforced PLA composites manufacturing processes: the commingling of yarns, weaving, and hot pressing and characterizes the manufactured laminates. Different structures and properties can be achieved by varying the hot compaction process parameters (pressure, holding time, and temperature). The specimens manufactured were characterized in terms of thermal properties (DSC), microstructure (C-scan optical microscope and SEM), strength (tensile test), and biocompatibility (MTT assays). Considering the final device, 155 ℃ for 10 min at 2 MPa act as the more appropriate hot pressing parameters. The laminate produced with these conditions has few voids/porosity, a tensile strength of 30.39 ± 1.21 MPa, and a modulus of 4.09 ± 0.24 GPa. Subsequently to the tensile testing was possible to observe fiber pullout from the fracture surfaces, confirming that this material behaves as a composite. From the results, no single laminate can fulfill all the requirements, being necessary to compromise in function of the priority property. Further investigation is required to improve materials' mechanical performance. Subsequently, process parameters and materials configuration can be adjusted depending on the place and type of implant to suit its function.

Keywords: woven fabric, self-reinforced polymer composite, poly(lactic acid), biodegradable

Procedia PDF Downloads 183
8481 Seismic Behavior and Loss Assessment of High–Rise Buildings with Light Gauge Steel–Concrete Hybrid Structure

Authors: Bing Lu, Shuang Li, Hongyuan Zhou

Abstract:

The steel–concrete hybrid structure has been extensively employed in high–rise buildings and super high–rise buildings. The light gauge steel–concrete hybrid structure, including light gauge steel structure and concrete hybrid structure, is a new–type steel–concrete hybrid structure, which possesses some advantages of light gauge steel structure and concrete hybrid structure. The seismic behavior and loss assessment of three high–rise buildings with three different concrete hybrid structures were investigated through finite element software, respectively. The three concrete hybrid structures are reinforced concrete column–steel beam (RC‒S) hybrid structure, concrete–filled steel tube column–steel beam (CFST‒S) hybrid structure, and tubed concrete column–steel beam (TC‒S) hybrid structure. The nonlinear time-history analysis of three high–rise buildings under 80 earthquakes was carried out. After simulation, it indicated that the seismic performances of three high–rise buildings were superior. Under extremely rare earthquakes, the maximum inter–storey drifts of three high–rise buildings are significantly lower than 1/50. The inter–storey drift and floor acceleration of high–rise building with CFST‒S hybrid structure were bigger than those of high–rise buildings with RC‒S hybrid structure, and smaller than those of high–rise building with TC‒S hybrid structure. Then, based on the time–history analysis results, the post-earthquake repair cost ratio and repair time of three high–rise buildings were predicted through an economic performance analysis method proposed in FEMA‒P58 report. Under frequent earthquakes, basic earthquakes and rare earthquakes, the repair cost ratio and repair time of three high-rise buildings were less than 5% and 15 days, respectively. Under extremely rare earthquakes, the repair cost ratio and repair time of high-rise buildings with TC‒S hybrid structure were the most among three high rise buildings. Due to the advantages of CFST-S hybrid structure, it could be extensively employed in high-rise buildings subjected to earthquake excitations.

Keywords: seismic behavior, loss assessment, light gauge steel–concrete hybrid structure, high–rise building, time–history analysis

Procedia PDF Downloads 167
8480 Factors Affecting Cost Efficiency of Municipal Waste Services in Tuscan Municipalities: An Empirical Investigation by Accounting for Different Management

Authors: María Molinos-Senante, Giulia Romano

Abstract:

This paper aims at investigating the effect of ownership in the efficiency assessment of municipal solid waste management. In doing so, the Data Envelopment Analysis meta-frontier approach integrating unsorted waste as undesirable output was applied. Three different clusters of municipalities have been created on the basis of the ownership type of municipal waste operators. In the second stage of analysis, the paper investigates factors affecting efficiency, in order to provide an outlook of levers to be used by policy and decision makers to improve efficiency, taking into account different management models in force. Results show that public waste management firms have better performance than mixed and private ones since their efficiency scores are significantly larger. Moreover, it has been demonstrated that the efficiency of waste management firms is statistically influenced by the age of population, population served, municipal size, population density and tourism rate. It evidences the importance of economies of scale on the cost efficiency of waste management. This issue is relevant for policymakers to define and implement policies aimed to improve the long-term sustainability of waste management in municipalities.

Keywords: data envelopment analysis, efficiency, municipal solid waste, ownership, undesirable output

Procedia PDF Downloads 148
8479 A Monte Carlo Fuzzy Logistic Regression Framework against Imbalance and Separation

Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

Abstract:

Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

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8478 Logistics Process of Pineapple’s Leaves Product in Prachuapkhirikhan Province

Authors: Atcharawan Phenwansuk

Abstract:

The product design is important to the development of SME towards the global, because it made to the quality product to react the needs of consumers and could reduces cost in the production, making it more profitable. As a results, the business are competition advantage for more marketing. It also enhance image of product and firms to build its own brand products to be acceptable. The product was designed should be shape, size, colorful, and direct of target consumers. This is method to add value products to get popular and effective, because the beauty is first satisfaction which come from main shape and color of the design product, but the product was designed need to hold data and law combination of shape and color between artistic theory and satisfaction of consumers together. The design must consider the safety of life and asset of consumers the most important. From to use of designed products should be to consider the cost savings, convenient distance, transportation, routes (land, water or air) of living space on transport (capacity, volume, width, length of the car, truck and container, etc). The packaging must be can to prevent not damage of the products. If products is more large , maybe to design new packaging, which can easily disassembled for make smaller package such as designing the assembly. Products must be packed in the container for size standard for save costs, as well as the buyer can make transport and assembly of products to fit easily on your own.

Keywords: logistics process , pineapple’s leaves product, product design, satisfaction of consumers

Procedia PDF Downloads 389
8477 A 'Systematic Literature Review' of Specific Types of Inventory Faced by the Management of Firms

Authors: Rui Brito

Abstract:

This contribution regards a literature review of inventory management that is a relevant topic for the firms, due to its important use of capital with implications in firm’s profitability within the complexity of a more competitive and globalized world. Firms look for small inventories in order to reduce holding costs, namely opportunity cost, warehousing and handling costs, deterioration and being out of style, but larger inventories are required by some reasons, such as customer service, ordering cost, transportation cost, supplier’s payment to reduce unit costs or to take advantage of price increase in the near future, and equipment setup cost. Thus, management shall address a trade-off between small inventories and larger inventories. This literature review concerns three types of inventory (spare parts, safety stock, and vendor) whose management usually is beyond the scope of logistics. The applied methodology consisted of an online search of databases regarding scientific documents in English, namely Elsevier, Springer, Emerald, Wiley, and Taylor & Francis, but excluding books except if edited, using search engines, such as Google Scholar and B-on. The search was based on three keywords/strings (themes) which had to be included just as in the article title, suggesting themes were very relevant to the researchers. The whole search period was between 2009 and 2018 with the aim of collecting between twenty and forty studies considered relevant within each of the key words/strings specified. Documents were sorted by relevance and to prevent the exclusion of the more recent articles, based on lower quantity of citations partially due to less time to be cited in new research articles, the search period was divided into two sub-periods (2009-2015 and 2016-2018). The number of surveyed articles by theme showed a variation from 40 to 200 and the number of citations of those articles showed a wider variation from 3 to 216. Selected articles from the three themes were analyzed and the first seven of the first sub-period and the first three of the second sub-period with more citations were read in full to make a synopsis of each article. Overall, the findings show that the majority of article types were models, namely mathematical, although with different sub-types for each theme. Almost all articles suggest further studies, with some mentioning it for their own author(s), which widen the diversity of the previous research. Identified research gaps concern the use of surveys to know which are the models more used by firms, the reasons for not using the models with more performance and accuracy, and which are the satisfaction levels with the outcomes of the inventories management and its effect on the improvement of the firm’s overall performance. The review ends with the limitations and contributions of the study.

Keywords: inventory management, safety stock, spare parts inventory, vendor managed inventory

Procedia PDF Downloads 84
8476 Vehicle Risk Evaluation in Low Speed Accidents: Consequences for Relevant Test Scenarios

Authors: Philip Feig, Klaus Gschwendtner, Julian Schatz, Frank Diermeyer

Abstract:

Projects of accident research analysis are mostly focused on accidents involving personal damage. Property damage only has a high frequency of occurrence combined with high economic impact. This paper describes main influencing parameters for the extent of damage and presents a repair cost model. For a prospective evaluation method of the monetary effect of advanced driver assistance systems (ADAS), it is necessary to be aware of and quantify all influencing parameters. Furthermore, this method allows the evaluation of vehicle concepts in combination with an ADAS at an early point in time of the product development process. In combination with a property damage database and the introduced repair cost model relevant test scenarios for specific vehicle configurations and their individual property damage risk may be determined. Currently, equipment rates of ADAS are low and a purchase incentive for customers would be beneficial. The next ADAS generation will prevent property damage to a large extent or at least reduce damage severity. Both effects may be a purchasing incentive for the customer and furthermore contribute to increased traffic safety.

Keywords: accident research, accident scenarios, ADAS, effectiveness, property damage analysis

Procedia PDF Downloads 334