Search results for: supply chain delivery models

Authors: K. Anas, M. Selvakumar, Samson David, R. R. Babu, S. Chattopadhyay

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The dynamic deformation of a visco elastic material can cause heat generation. This heat generation is aspect energy dissipation. The present work investigates the contribution of various factors like; elastomer structure, cross link type and density, filler networking, reinforcement potential and temperature at energy dissipation mechanism. The influences of these elements are investigated using very high frequency analyzer (VHF ) and dynamical mechanical analysis(DMA).VHF follows transmissibility and vibration isolation principle whereas DMA works on dynamical mechanical deformation principle. VHF analysis of different types of elastomers reveals that elastomer can act as a transmitter or damper of energy depending on the applied frequency ratio (ω/ωn). Dynamic modulus (G') of low damping rubbers like natural rubber does not varies rapidly with frequency but vice-versa for high damping rubber like butyl rubber (IIR). VHF analysis also depicts that polysulfidic linkages has high damping ratio (ζ) than mono sulfidic linkages due to its dissipative nature. At comparable cross link density, mono sulfidic linkages shows higher glass transition temperature (Tg) than poly sulfidic linkages. The intensity and location of loss modulus (G'') peak of different types of carbon black filled natural rubber compounds suggests that segmental relaxation at glass transition temperature (Tg) is seldom affected by filler particles, but the filler networks can influence the cross link density by absorbing the curatives. The filler network breaking and reformation during a dynamic strain is a thermally activated process. Thus, stronger aggregates are highly dissipative in nature. Measurements indicate that at lower temperature regimes polymeric chain friction is highly dissipative in nature.

Keywords: damping ratio, natural frequency, crosslinking density, segmental motion, surface activity, dissipative, polymeric chain friction

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Authors: V. D. Thi, M. Li, M. Khelifa, M. El Ganaoui, Y. Rogaume

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This paper presents a two-dimensional model to study the heat and moisture transfer through porous building materials. Dynamic and static coupled models of heat and moisture transfer in porous material under low temperature are presented and the coupled models together with variable initial and boundary conditions have been considered in an analytical way and using the finite element method. The resulting coupled model is converted to two nonlinear partial differential equations, which is then numerically solved by an implicit iterative scheme. The numerical results of temperature and moisture potential changes are compared with the experimental measurements available in the literature. Predicted results demonstrate validation of the theoretical model and effectiveness of the developed numerical algorithms. It is expected to provide useful information for the porous building material design based on heat and moisture transfer model.

Keywords: finite element method, heat transfer, moisture transfer, porous materials, wood

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Authors: Benbiao Song, Yan Gao, Zhuo Liu

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Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

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Authors: Zakaria Baka, Halima Alem

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Cancer is a major worldwide health problem that has caused around ten million deaths in 2020. In addition, efforts to develop new anti-cancer drugs still face a high failure rate. This is partly due to the lack of preclinical models that recapitulate in-vivo drug responses. Indeed conventional cell culture approach (known as 2D cell culture) is far from reproducing the complex, dynamic and three-dimensional environment of tumors. To set up more in-vivo-like cancer models, 3D bioprinting seems to be a promising technology due to its ability to achieve 3D scaffolds containing different cell types with controlled distribution and precise architecture. Moreover, the introduction of microfluidic technology makes it possible to simulate in-vivo dynamic conditions through the so-called “cancer-on-chip” platforms. Whereas several cancer types have been modeled through the cancer-on-chip approach, such as lung cancer and breast cancer, only a few works describing ovarian cancer models have been described. The aim of this work is to combine 3D bioprinting and microfluidic technics with setting up a 3D dynamic model of ovarian cancer. In the first phase, alginate-gelatin hydrogel containing SKOV3 cells was used to achieve tumor-like structures through an extrusion-based bioprinter. The desired form of the tumor-like mass was first designed on 3D CAD software. The hydrogel composition was then optimized for ensuring good and reproducible printability. Cell viability in the bioprinted structures was assessed using Live/Dead assay and WST1 assay. In the second phase, these bioprinted structures will be included in a microfluidic device that allows simultaneous testing of different drug concentrations. This microfluidic dispositive was first designed through computational fluid dynamics (CFD) simulations for fixing its precise dimensions. It was then be manufactured through a molding method based on a 3D printed template. To confirm the results of CFD simulations, doxorubicin (DOX) solutions were perfused through the dispositive and DOX concentration in each culture chamber was determined. Once completely characterized, this model will be used to assess the efficacy of anti-cancer nanoparticles developed in the Jean Lamour institute.

Keywords: 3D bioprinting, ovarian cancer, cancer-on-chip models, microfluidic techniques

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Authors: Tony Mann

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This paper sets out the case for involving and engaging employees/workers/stakeholders/staff in any significant change that is being considered by the senior executives of the organization. It establishes the rationale, the approach, the methodology of engagement and the benefits of a participative approach. It challenges the new norm of imposing change for fear of resistance and instead suggests that involving people has better outcomes and a longer-lasting impact. Various strategic models are introduced and illustrated to explain how the process can be most effective. The paper highlights one model in particular (the Process Iceberg® Organizational Change model) that has proven to be instrumental in developing effective change. Its use is demonstrated in its various forms and explains why so much change fails to address the key elements and how we can be more productive in managing change. ‘Participation’ in change is too often seen as negative, expensive and unwieldy. The paper aims to show that another model: UIA=O+E, can offset the difficulties and, in fact, produce much more positive and effective change.

Keywords: facilitation, stakeholders, buy-in, digital workshops

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Authors: Rajkumar Ghosh

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The present study focuses on conducting a socio-economic assessment of groundwater contamination by arsenic and iron and explores the feasibility of rainwater harvesting (RWH) as an alternative water source in the Amdanga Block of North 24 Parganas, West Bengal, India. The region is plagued by severe groundwater contamination, primarily due to excessive concentrations of arsenic and iron, which pose significant health risks to the local population. The study utilizes a mixed-methods approach, combining quantitative analysis of water samples collected from different locations within the Amdanga Block and socio-economic surveys conducted among the affected communities. The results reveal alarmingly high levels of arsenic and iron contamination in the groundwater, surpassing the World Health Organization (WHO) and Indian government's permissible limits. This contamination significantly impacts the health and well-being of the local population, leading to a range of health issues such as skin The water samples are analyzed for arsenic and iron levels, while the surveys gather data on water usage patterns, health conditions, and socio-economic factors. lesions, respiratory disorders, and gastrointestinal problems. Furthermore, the socio-economic assessment highlights the vulnerability of the affected communities due to limited access to safe drinking water. The findings reveal the adverse socio-economic implications, including increased medical expenditures, reduced productivity, and compromised educational opportunities. To address these challenges, the study explores the feasibility of rainwater harvesting as an alternative source of clean water. RWH systems have the potential to mitigate groundwater contamination by providing a sustainable and independent water supply. The assessment includes evaluating the rainwater availability, analyzing the infrastructure requirements, and estimating the potential benefits and challenges associated with RWH implementation in the study area. The findings of this study contribute to a comprehensive understanding of the socio-economic impact of groundwater contamination by arsenic and iron, emphasizing the urgency to address this critical issue in the Amdanga Block. The feasibility assessment of rainwater harvesting serves as a practical solution to ensure a safe and sustainable water supply, reducing the dependency on contaminated groundwater sources. The study's results can inform policymakers, researchers, and local stakeholders in implementing effective mitigation measures and promoting the adoption of rainwater harvesting as a viable alternative in similar arsenic and iron-contaminated regions.

Keywords: contamination, rainwater harvesting, groundwater, sustainable water supply

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Authors: Vishal H. Shukla, Sanjay B. Deshmukh

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Traffic engineering, at its center, is the ability of moving traffic approximately so that traffic from a congested link is moved onto the unused capacity on another link. Traffic Engineering ensures the best possible use of the resources. Now to support traffic engineering in the today’s network, Multiprotocol Label Switching (MPLS) is being used which is very helpful for reliable packets delivery in an ongoing internet services. Here a topology is been implemented on GNS3 to focus on the analysis of the communication take place from one site to other through the ISP. The comparison is made between the IP network & MPLS network based on Bandwidth & Jitter which are one of the performance parameters using JPERF simulator.

Keywords: GNS3, JPERF, MPLS, traffic engineering, VMware

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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

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Authors: Galit Harel

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This article describes the long-term psychoanalytic psychotherapy of a young woman who had experienced trauma during her childhood. The details of the trauma were unknown, as all memory of the trauma had been repressed. Past trauma is analyzable through a prism of transference, dreaming and dreams, mental states, and thinking processes that offer an opportunity to explore and analyze the influence of both reality and fantasy on the patient. The presented case describes a therapeutic process that strives to discover hidden meanings through the unconscious system and illustrates the movement from unconscious to conscious during exploration of the patient’s personal trauma in treatment. The author discusses the importance of classical and contemporary psychoanalytic models of childhood sexual trauma through the discovery of manifest and latent content, unconscious fantasies, and actual events of trauma. It is suggested that the complexity of trauma is clarified by the tension between these models and by the inclusion of aspects of both of them for a complete understanding.

Keywords: dreams, psychoanalytic psychotherapy, thinking processes, transference, trauma

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Authors: E. Mosiniewicz-Szablewska, P. Suchocki, P. C. Morais

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Despite the significant progress in cancer treatment, there is a need to search for new therapeutic methods in order to minimize side effects. Chemotherapy, the main current method of treating cancer, is non-selective and has a number of limitations. Toxicity to healthy cells is undoubtedly the biggest problem limiting the use of many anticancer drugs. The problem of how to kill cancer without harming a patient can be solved by using organic selenium (IV) compounds. Organic selenium (IV) compounds are a new class of materials showing a strong anticancer activity. They are first organic compounds containing selenium at the +4 oxidation level and therefore they eliminate the multidrug-resistance for all tumor cell lines tested so far. These materials are capable of selectively killing cancer cells without damaging the healthy ones. They are obtained by the incorporation of selenous acid (H2SeO3) into molecules of fatty acids of sunflower oil and therefore, they are inexpensive to manufacture. Attaching these compounds to magnetic carriers enables their precise delivery directly to the tumor area and the simultaneous application of the magnetic hyperthermia, thus creating a huge opportunity to effectively get rid of the tumor without any side effects. Polylactic-co-glicolic acid (PLGA) nanocapsules loaded with maghemite (-Fe2O3) nanoparticles and organic selenium (IV) compounds are successfully prepared by nanoprecipitation method. In vitro antitumor activity of the nanocapsules were evidenced using murine melanoma (B16-F10), oral squamos carcinoma (OSCC) and murine (4T1) and human (MCF-7) breast lines. Further exposure of these cells to an alternating magnetic field increased the antitumor effect of nanocapsules. Moreover, the nanocapsules presented antitumor effect while not affecting normal cells. Magnetic properties of the nanocapsules were investigated by means of dc magnetization, ac susceptibility and electron spin resonance (ESR) measurements. The nanocapsules presented a typical superparamagnetic behavior around room temperature manifested itself by the split between zero field-cooled/field-cooled (ZFC/FC) magnetization curves and the absence of hysteresis on the field-dependent magnetization curve above the blocking temperature. Moreover, the blocking temperature decreased with increasing applied magnetic field. The superparamagnetic character of the nanocapsules was also confirmed by the occurrence of a maximum in temperature dependences of both real ′(T) and imaginary ′′ (T) components of the ac magnetic susceptibility, which shifted towards higher temperatures with increasing frequency. Additionally, upon decreasing the temperature the ESR signal shifted to lower fields and gradually broadened following closely the predictions for the ESR of superparamagnetoc nanoparticles. The observed superparamagnetic properties of nanocapsules enable their simple manipulation by means of magnetic field gradient, after introduction into the blood stream, which is a necessary condition for their use as magnetic drug carriers. The observed anticancer and superparamgnetic properties show that the magnetic nanocapsules loaded with organic selenium (IV) compounds should be considered as an effective material system for magnetic drug delivery and magnetohyperthermia inductor in antitumor therapy.

Keywords: cancer treatment, magnetic drug delivery system, nanomaterials, nanotechnology

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Authors: Safia Hocine, Djamil Aïssani

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Risk models, recently studied in the literature, are becoming increasingly complex. It is rare to find explicit analytical relations to calculate the ruin probability. Indeed, the stability issue occurs naturally in ruin theory, when parameters in risk cannot be estimated than with uncertainty. However, in most cases, there are no explicit formulas for the ruin probability. Hence, the interest to obtain explicit stability bounds for these probabilities in different risk models. In this paper, we interest to the stability bounds of the univariate classical risk model established using the regenerative processes approach. By adopting an algorithmic approach, we implement this approximation and determine numerically the bounds of ruin probability in the case of large claims (heavy-tailed distribution).

Keywords: heavy-tailed distribution, large claims, regenerative process, risk model, ruin probability, stability

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Authors: Margarita Mayoral-Villa, J. Klapp, L. Di G. Sigalotti, J. E. V. Guzmán

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Automated learning techniques are widely applied in the energy sector to address challenging problems from a practical point of view. To this end, we discuss the implementation of a Message Passing algorithm (MPNN)within a Graph Neural Network(GNN)to leverage the neighborhood of a set of nodes during the aggregation process. This approach enables the characterization of multiphase diffusion processes in the reservoir, such that the flow paths underlying the interconnections between multiple wells may be inferred from previously available data on flow rates and bottomhole pressures. The results thus obtained compare favorably with the predictions produced by the Reduced Order Capacitance-Resistance Models (CRM) and suggest the potential of MPNNs to enhance the robustness of the forecasts while improving the computational efficiency.

Keywords: multiphase diffusion, message passing neural network, well interconnection, interwell connectivity, graph neural network, capacitance-resistance models

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Authors: Niveen M. Hassan-Abbas

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The COVID-19 pandemic created a range of stressors, among them difficulties related to work conditions, financial changes, lack of childcare, and confinement or isolation due to social distancing. Among families and married individuals, these stressors were often expressed in additional daily hassles, with an influence on mental health. This study examined two moderated mediation models based on Bodenmann’s systemic-transactional stress model. Specifically, the models tested the hypothesis that intra-dyadic stress mediates the association between extra-dyadic stress and mental health, while two measures of family functioning, cohesion, and flexibility, moderate the relationship between extra and intra-dyadic stress. Participants were 480 heterosexual married Palestinians from Israel who completed self-report questionnaires. The results showed partial mediation patterns supporting both models, indicating that family cohesion and flexibility weakened the mediating effect of intra-dyadic stress on the relationship between extra-dyadic stress and mental health. These findings increase our understanding of the variables that affected mental health during the pandemic and suggested that when faced with extra-dyadic stress, married individuals with good family environments are less likely to experience high levels of intra-dyadic stress, which is in turn associated with preserved mental health. Limitations and implications for planning interventions for couples and families during the pandemic are discussed.

Keywords: Palestinian families in Israel, COVID-19 pandemic, family cohesion and flexibility, extra-dyadic stress, intra-dyadic stress, mental health

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Authors: Eman Hegazy, Stefan Anderberg, Joakim Krook

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Urban water infrastructure is crucial for efficient and reliable water supply in growing cities. With the growth of cities, the need for maintenance and renewal of these systems increases but often goes unfulfilled due to a variety of reasons, such as limited funding, political priorities, or lack of public awareness. Neglecting the renewal needs of these systems can lead to frequent malfunctions and reduced quality and reliability of water supply, as well as increased costs and health and environmental hazards. It is important for cities to prioritize investment in water infrastructure and develop long-term plans to address renewal needs. Drawing general conclusions about the rate of renewal of urban water infrastructure systems at an international or national level can be challenging due to the influence of local management decisions. In many countries, the responsibility for water infrastructure management lies with the municipal authorities, who are responsible for making decisions about the allocation of resources for repair, maintenance, and renewal. These decisions can vary widely based on factors such as local finances, political priorities, and public perception of the importance of water infrastructure. As a result, it is difficult to make generalizations about the rate of renewal across different countries or regions. In Sweden, the situation is not different, and the information from Svenskt Vatten indicates that the rate of renewal varies across municipalities and can be insufficient, leading to a buildup of maintenance and renewal needs. This study aims to examine the adequacy of the rate of renewal of urban water infrastructure in Linköping case city in Sweden. Using a case study framework, the study will assess the current status of the urban water system and the need for renewal. The study will also consider the role of factors such as proper identification processes, limited funding, competing for political priorities, and local management decisions in contributing to insufficient renewal. The study investigates the following questions: (1) What is the current status of water and sewerage networks in terms of length, age distribution, and material composition, estimated total water leakage in the network per year, damages, leaks, and outages occur per year, both overall and by district? (2) What are the main causes of these damages, leaks, and interruptions, and how are they related to lack of maintenance and renewal? (3) What is the current status of renewal work for the water and sewerage networks, including the renewal rate and changes over time, recent renewal material composition, and the budget allocation for renewal and emergency repairs? (4) What factors influence the need for renewal and what conditions should be considered in the assessment? The findings of the study provide insights into the challenges facing urban water infrastructure and identify strategies for improving the rate of renewal to ensure a reliable and sustainable water supply.

Keywords: case study, infrastructure, management, renewal need, Sweden

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Authors: Donatello Cardone

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Bilinear hysteresis models are usually used to describe the cyclic behavior of high damping rubber bearings. However, they neglect a number of phenomena (such as the interaction between axial load and shear force, buckling and post-buckling behavior, cavitation, scragging effects, etc.) that can significantly influence the dynamic behavior of such isolation devices. In this work, an advanced hysteresis model is examined and properly calibrated using consolidated procedures. Results of preliminary numerical analyses, performed in OpenSees, are shown and compared with the results of experimental tests on high damping rubber bearings and simulation analyses using alternative nonlinear models. The findings of this study can provide an useful tool for the accurate evaluation of the seismic response of structures with rubber-based isolation systems.

Keywords: seismic isolation, high damping rubber bearings, numerical modeling, axial-shear force interaction

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Authors: Nazedah Ain Ibrahim, Mohamed Mansor Manan

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Treatment of suspected early onset neonatal sepsis (EONS) in Neonatal Intensive Care Unit (NICU) is essential. However, information regarding EONS pathogens may vary between regions. Global perspectives showed Group B Streptococcal (GBS) as the most common causative pathogens, but the widespread use of intrapartum antibiotics has changed the pathogens pattern towards gram negative microorganisms, especially E. coli. Objective of this study is to describe the pathogens isolated, to assess current treatment and risk of EONS. Records of 899 neonates born in three General Hospitals between 2009 until 2012 were retrospectively reviewed. The inclusion criteria were neonates with blood culture taken prior to empiric antibiotics administration and within 72 hours of life. Of the study group, a total of 734 (82%) cases had documented blood culture that met the inclusion criteria. Proven EONS (as confirmed by positive blood culture) was found in 22 (3%) neonates. The majority was isolated with gram positive organisms, 17 (2.3%). In addition, other common gram positive organism isolated were Coagulase negative staphylococci (7) followed by Bacillus sp. (5) and Streptococcus pneumonia (2), and only one case isolated with GBS, Streptococcus spp. and Enterococcus sp. Meanwhile, only five cases of gram negative organisms [Stenotropomonas (xantho) maltophi (1), Haemophilus influenza (1), Spingomonas paucimobilis (1), Enterobacter gergoviae (1) and E. coli (1)] were isolated. A total of 286 (39%) cases were exposed to intrapartum antibiotics and of those, 157 (21.4%) were administered prior to delivery. All grams positive and most gram negative organisms showed sensitivity to the tested antibiotics. Only two rare gram negative organisms showed total resistant. Male, surfactant, caesarean delivery and prolonged rapture of membrane >18hours were a possible risk of proven EONS. Although proven EONS remains uncommon in Malaysia, nonetheless, the effect of intrapartum antibiotics still required continuous surveillance. However, by analyzing isolated pathogens it can be used as treatment guidance in managing suspected EONS.

Keywords: early onset neonatal sepsis, neonates, pathogens, gram positive, gram negative

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Authors: Vikram Kalekar

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Modern Internet Protocol (IP) networks deploy traditional and modern Quality of Service (QoS) management methods to ensure the smooth flow of network packets during regular operations. SDN (Software-defined networking) networks have also made headway into better service delivery by means of novel QoS methodologies. While many of these techniques are experimental, some of them have been tested extensively in controlled environments, and few of them have the potential to be deployed widely in the industry. With this survey, we plan to analyze the approaches to QoS and resource allocation in SDN, and we will try to comment on the possible improvements to QoS management in the context of SDN.

Keywords: QoS, policy, congestion, flow management, latency, delay index terms-SDN, delay

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Authors: Amritpal Slaich, Mark Elshaw

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This paper explores the development of a decision support framework for the introduction of business intelligence (BI) through operational research techniques for application by SMEs. Aligned with the goals of the new Midlands Enterprise Initiative of improving the skill levels of the Midlands workforce and addressing high levels of regional unemployment, we have developed a framework to increase the level of business intelligence used by SMEs to improve business decision-making. Many SMEs in the Midlands fail due to the lack of high quality decision making. Our framework outlines how universities can: engage with SMEs in the use of BI through operational research techniques; develop appropriate and easy to use Excel spreadsheet models; and make use of a process to allow SMEs to feedback their findings of the models. Future work will determine how well the framework performs in getting SMEs to apply BI to improve their decision-making performance.

Keywords: SMEs, decision support framework, business intelligence, operational research techniques

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Authors: B. Schmid, C. Kexel, E. Djafarova

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Understanding consumers is elementary for practitioners in marketing. Consumers of sports events, the sports spectators, are a particularly complex consumer crowd. In order to identify and define their profiles different segmentation approaches can be found in literature, one of them being multidimensional segmentation. Multidimensional segmentation models correspond to the broad range of attitudes, behaviours, motivations and beliefs of sports spectators, other than earlier models. Moreover, in sports there are some well-researched disciplines (e.g. football or North American sports) where consumer profiles and marketing strategies are elaborate and others where no research at all can be found. For example, there is almost no research on athletics spectators. This paper explores the current state of research on sports spectators segmentation. An in-depth literature review provides the framework for a spectators segmentation in athletics. On this basis, additional potential consumer groups and implications for social media marketing will be explored. The findings are the basis for further research.

Keywords: multidimensional segmentation, social media, sports marketing, sports spectators segmentation

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Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

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Authors: Haoshu Li, Shaolong Wan

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The recent focus has been on directional signal amplification of a signal input at one end of a one-dimensional chain and measured at the other end. The amplification rate is given by the end-to-end Green’s functions of the system. In this work, we derive the exact formulas for the end-to-end Green's functions of non-Hermitian single-band systems. While in the bulk region, it is found that the Green's functions are displaced from the prior established integral formula by O(e⁻ᵇᴸ). The results confirm the correspondence between the signal amplification and the non-Hermitian skin effect.

Keywords: non-Hermitian, Green's function, non-Hermitian skin effect, signal amplification

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Authors: R. Pravin Kumar, L. Roopa

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Enzymes are molecular machines used in various industries such as pharmaceuticals, cosmetics, food and animal feed, paper and leather processing, biofuel, and etc. Nevertheless, this has been possible only by the breath-taking efforts of the chemists and biologists to evolve/engineer these mysterious biomolecules to work the needful. Main agenda of this enzyme engineering project is to derive screening and selection tools to obtain focused libraries of enzyme variants with desired qualities. The methodologies for this research include the well-established directed evolution, rational redesign and relatively less established yet much faster and accurate insilico methods. This concept was initiated as a Receptor Rependent-4Dimensional Quantitative Structure Activity Relationship (RD-4D-QSAR) to predict kinetic properties of enzymes and extended here to study transaminase by a 7D QSAR approach. Induced-fit scenarios were explored using Quantum Mechanics/Molecular Mechanics (QM/MM) simulations which were then placed in a grid that stores interactions energies derived from QM parameters (QMgrid). In this study, the mutated enzymes were immersed completely inside the QMgrid and this was combined with solvation models to predict descriptors. After statistical screening of descriptors, QSAR models showed > 90% specificity and > 85% sensitivity towards the experimental activity. Mapping descriptors on the enzyme structure revealed hotspots important to enhance the enantioselectivity of the enzyme.

Keywords: QMgrid, QM/MM simulations, RD-4D-QSAR, transaminase

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Authors: Levent Basayigit, Mert Dedeoglu, Fadime Ozogul

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In this study, an application was carried out to determine the Volcanic Soils by using remote sensing.  The study area was located on the Golcuk formation in Isparta-Turkey. The thermal bands of Landsat 7 image were used for processing. The implementation of the climate model that was based on the water index was used in ERDAS Imagine software together with pixel based image classification. Soil Moisture Index (SMI) was modeled by using the surface temperature (Ts) which was obtained from thermal bands and vegetation index (NDVI) derived from Landsat 7. Surface moisture values were grouped and classified by using scoring system. Thematic layers were compared together with the field studies. Consequently, different moisture levels for volcanic soils were indicator for determination and separation. Those thermal wavelengths are preferable bands for separation of volcanic soils using moisture and temperature models.

Keywords: Landsat 7, soil moisture index, temperature models, volcanic soils

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: Hicham Maklache, Rajae Delhi, Fatiha Benzha, Mohamed Tahiri

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In Morocco, where semi-arid climate is dominant, the supply of industrial and drink water is provided primarily by surface water. Morocco has currently 118 multi-purpose dams. If the construction of these works was a necessity to ensure in all seasons, the water essential to our country, it is impartial to control and protect the quality of running water. -Most dam reservoir used are threatened by eutrophication due to increased terrigenous and anthropogenic pollutants, coming from an over-fertilization of water by phosphorus and nitrogen nutrients and accelerated by uncontrolled development of microalgae aging. It should also be noted that the daily practices of citizens with respect to the resource, an essential component involved in almost all human activities (agriculture, agro-industries, hydropower, ...), has contributed significantly to the deterioration of water quality despite its treatment in several plants. Therefore, the treated water, provides a legacy of bad tastes and odors unacceptable to the consumer. -The present work exhibits results of water quality watershed Oum Erbia used to supply drinking water to the whole terraced area connecting the city of Khenifra to the city of Azemmour. The area south west of Great Casablanca (metropolis of the kingdom with about 4 million inhabitants) supplied 50% of its water needs by sourcing Dam Sidi Said Maachou located, last anchor point of the watershed before the spill in the Atlantic Ocean. The results were performed in a spatio-temporal scale and helped to establish a history of monitoring water quality during the 2009-2011 cycles, the study also presents the development of quality according to the seasonal rhythmicity and rainfall. It gives also an overview on the concept of watershed stewardship.

Keywords: crude surface water quality, Oum Er Rbia hydraulic basin, spatio-temporal monitoring, Great Casablanca drink water quality, Morocco

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Rob van den Dam

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Today’s Internet of Things (IoT) comprises more than a billion intelligent devices, connected via wired/wireless communications. The expected proliferation of hundreds of billions more places us at the threshold of a transformation sweeping across the communications industry. Yet, we found that the IoT architecture and solutions that currently work for billions of devices won’t necessarily scale to tomorrow’s hundreds of billions of devices because of high cost, lack of privacy, not future-proof, lack of functional value and broken business models. As the IoT scales exponentially, decentralized networks have the potential to reduce infrastructure and maintenance costs to manufacturers. Decentralization also promises increased robustness by removing single points of failure that could exist in traditional centralized networks. By shifting the power in the network from the center to the edges, devices gain greater autonomy and can become points of transactions and economic value creation for owners and users. To validate the underlying technology vision, IBM jointly developed with Samsung Electronics the autonomous decentralized peer-to- peer proof-of-concept (PoC). The primary objective of this PoC was to establish a foundation on which to demonstrate several capabilities that are fundamental to building a decentralized IoT. Though many commercial systems in the future will exist as hybrid centralized-decentralized models, the PoC demonstrated a fully distributed proof. The PoC (a) validated the future vision for decentralized systems to extensively augment today’s centralized solutions, (b) demonstrated foundational IoT tasks without the use of centralized control, (c) proved that empowered devices can engage autonomously in marketplace transactions. The PoC opens the door for the communications and electronics industry to further explore the challenges and opportunities of potential hybrid models that can address the complexity and variety of requirements posed by the internet that continues to scale. Contents: (a) The new approach for an IoT that will be secure and scalable, (b) The three foundational technologies that are key for the future IoT, (c) The related business models and user experiences, (d) How such an IoT will create an 'Economy of Things', (e) The role of users, devices, and industries in the IoT future, (f) The winners in the IoT economy.

Keywords: IoT, internet, wired, wireless

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Authors: Sima Ajami, Batool Akbari

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Background: Radio frequency identification (RFID) system has been successfully applied to the areas of manufacturing, supply chain, agriculture, transportation, healthcare, and services. The RFID is already used to track and trace the victims in a disaster situation. Data can be collected in real time and be immediately available to emergency personnel and saves time by the RFID. Objectives: The aim of this study was, first, to identify stakeholders and customers for rescuing earthquake victims, second, to list key internal and external factors to use RFID to track earthquake victims, finally, to assess SWOT for rescuers' viewpoint. Materials and Methods: This study was an applied and analytical study. The study population included scholars, experts, planners, policy makers and rescuers in the "red crescent society of Isfahan province", "disaster management Isfahan province", "maintenance and operation department of Isfahan", "fire and safety services organization of Isfahan municipality", and "medical emergencies and disaster management center of Isfahan". After that, researchers held a workshop to teach participants about RFID and its usages in tracking earthquake victims. In the meanwhile of the workshop, participants identified, listed, and weighed key internal factors (strengths and weaknesses; SW) and external factors (opportunities and threats; OT) to use RFID in tracking earthquake victims. Therefore, participants put weigh strengths, weaknesses, opportunities, and threats (SWOT) and their weighted scales were calculated. Then, participants' opinions about this issue were assessed. Finally, according to the SWOT matrix, strategies to solve the weaknesses, problems, challenges, and threats through opportunities and strengths were proposed by participants. Results: The SWOT analysis showed that the total weighted score for internal and external factors were 3.91 (Internal Factor Evaluation) and 3.31 (External Factor Evaluation) respectively. Therefore, it was in a quadrant SO strategies cell in the SWOT analysis matrix and aggressive strategies were resulted. Organizations, scholars, experts, planners, policy makers and rescue workers should plan to use RFID technology in order to save more victims and manage their life. Conclusions: Researchers suppose to apply SO strategies and use a firm’s internal strength to take advantage of external opportunities. It is suggested, policy maker should plan to use the most developed technologies to save earthquake victims and deliver the easiest service to them. To do this, education, informing, and encouraging rescuers to use these technologies is essential. Originality/ Value: This study was a research paper that showed how RFID can be useful to track victims in earthquake.

Keywords: frequency identification system, strength, weakness, earthquake, victim

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Authors: Renee Yi-Mond Yuan

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The fast development of tourism industries around the world, has largely contributed to many cities, and countries economical and social progress. Past year Taiwan in particular was ranked among one of fastest raise growth country. Thanks to the prominent importance of this phenomenon; seasonal mobility or multipurpose trips have reached more than 1 Billion tourists crossing International borders and more than 4 billion intramural travelers that have nourished the economy and employment in the service sector in most attractive regions, representing about one tenth of World GDP amount, including trade, research, cultural or journalistic purposes. Then the increased activities are giving pressure to the consumption of energy, water, resources, and Greenhouse Gas emissions. The further concentration of tourists in most beautiful sites of the World with consistent supply and reduced pollutions and means for waste control and risks management are challenging the preservation and protection of the natural original environment, including species and their ecosystems, ethnics and their cultures or languages, protection of inherited landscapes and monuments for the future generations to come. In this article, few projects will be analyzed, methods and directions in the EU sustainable development scheme giving way to economical and social activities and preserve rural areas and remote countryside as well as smarter cities development. EU ETS forecasting escalation in the next few decades for road and air, and will reconsider investments and reliance on Biobased alternatives that may turn out solutions and contributions to sustain popularization of tourism development. Study of Examples of Stakeholders practices and Governments efforts, consumer’s attitude to bring new forms of more responsible holidays models: ecotourism, eco-certification, partnerships, investment in technologies and facilities, and possibly create greener perceptions and less impacting demands for the longer term through association, organizations and awards.

Keywords: tourism, sustainability, protection, risks management, change in rural/urban environment

Procedia PDF Downloads 333