Search results for: auto logistics

Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

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The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

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Authors: Uzma Rashid, Mommnah Asad

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As more and more people fall victim to the intolerance that has become a plague globally, academicians are faced with the herculean task of sowing the roots for more tolerant individuals. Being the multilayered task that it is, promoting an acceptance of diversity and pushing an agenda to push back hate requires efforts on multiple levels. Not only does the curriculum need to be in line with such goals, but teachers also need to be trained to cater to the sensitivities surrounding conversations of tolerance and diversity. In addition, institutional support needs to be there to provide conducive conditions for a diversity driven learning process to take place. In reality, teachers have to struggle with forwarding ideas about diversity and tolerance which do not sound particularly risky to be shared but given the current socio-political and religious milieu, can put the teacher in a difficult position and can make the task exponentially challenging. This paper is based on an auto-ethnographic account of teaching undergraduate and graduate courses at a private university in Pakistan. These courses were aimed at teaching tolerance to adult learners through classes focused on key notions pertaining to religion, culture, gender, and society. Authors’ classroom experiences with the students in these courses indicate a marked heightening of religious sensitivities that can potentially threaten a teacher’s life chances and become a hindrance in deep, meaningful conversations, thus lending a superficiality to the whole endeavor. The paper will discuss in detail the challenges that this teacher dealt with in the process, how those were addressed, and locate them in the larger picture of how tolerance can be materialized in current times in the universities in Pakistan and in similar contexts elsewhere.

Keywords: tolerance, diversity, gender, Pakistani Universities

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Authors: D. Shamatov

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Becoming a teacher is a journey with significant learning experiences. Exploring teachers’ lives and experiences can provide much-needed insights into the multiple realities of teaching. Teachers’ stories through qualitative narrative studies help understand and appreciate the complexities of the socio-political, economic and practical realities facing teachers. Events and experiences, both past and present, that take place at home, school, and in the broader social sphere help to shape these teachers’ lives and careers. Researchers and educators share the responsibility of listening to these teachers’ stories and life experiences and being sensitive to their voices in order to develop effective models for teacher development. A better understanding of how teachers learn to become teachers can help teacher educators prepare more effective teacher education programs. This paper is based on qualitative research which includes individual and focus group interviews, as well as auto-biography stories of Master of Science in School Leadership students at Graduate School of Education of Nazarbayev University. Twenty five MSc students from across Kazakhstan reflected on their professional journey and wrote their professional autobiographies as teachers. Their autobiographies capture the richness of their experiences and beliefs as a teacher, but also serve as window to understand broader socio-economic and political contexts where these teachers live and work. The study also provides an understanding of the systemic and socio-economic challenges of teachers in the context of post-Soviet Kazakhstan. It helps the reader better understand how wider societal forces interact and frame the development of teachers. The paper presents the findings from these stories of MSc students and offers some practical and policy implications for teacher preparation and teacher development.

Keywords: becoming a teacher, Kazakhstan, teacher stories, teacher development

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Authors: Cristian Pauna

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Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

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Authors: Rahim Sarvar, Bahram Azadbakht, Samira Safaee

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The leading goal of all planning is to attain sustainable development, regional balance, suitable distribution of activities, and maximum use of environmental capabilities in the process of development of regions. Intensive concentration of population and activities in one or some limited geographical locality is of main characteristics of most developing countries, especially Iran. Not considering the long-term programs and relying on temporary and superficial plans by people in charge of decision-making to attain their own objectives causes obstacles, resulting in unbalance development. The basic reason for these problems is to establish the development planning while economic aspects are merely considered and any attentions are not paid to social and regional feedbacks, what have been ending up to social and economic inequality, unbalanced distribution of development among the regions as well. In addition to study of special planning and structure of the county of Malekan, this research tries to achieve some other aims, i.e. recognition and introduction of approaches in order to utilize resources optimally, to distribute the population, activities, and facilities in optimum fashion, and to investigate and identify the spatial development potentials of the County. Based on documentary, descriptive, analytical, and field studies, this research employs maps to analyze the data, investigates the variables, and applies SPSS, Auto CAD, and Arc View software. The results show that the natural factors have a significant influence on spatial layout of settlements; distribution of facilities and functions are not equal among the rural districts of the county; and there is a spatial equivalence in the region area between population and number of settlements.

Keywords: development, entropy index, Malekan City, planning, regional equilibrium

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Authors: Filipa Vasconcelos

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The administration of endoplasmic reticulum amino peptidases (ERAP1 or ERAP2) inhibitors can be used for therapeutic approaches against cancer and auto-immune diseases. However, one of the main shortcomings of drug delivery systems (DDS) is associated with the drug off-target distribution, which can lead to an increase in its side effects on the patient’s body. To overcome such limitations, the encapsulation of four representative compounds of ERAP inhibitors into Polycaprolactone (PCL), Polyvinyl-alcohol (PVA), crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes is proposed as a safe and controlled drug release system. The use of electrospun fibrous meshes as a DDS allows efficient solvent evaporation giving limited time to the encapsulated drug to recrystallize, continuous delivery of the drug while the fibers degrade, prevention of initial burst release (sustained release), tunable dosages, and the encapsulation of other agents. This is possible due to the fibers' small diameters and resemblance to the extracellular matrix (confirmed by scanning electron microscopy results), high specific surface area, and good mechanical strength/stability. Furthermore, release studies conducted on PCL, PVA, crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes with each of the ERAP compounds encapsulated demonstrated that they were capable of releasing >60%, 50%, 40%, and 45% of the total ERAP concentration, respectively. Fibrous meshes with ERAP_E compound encapsulated achieved higher released concentrations (75.65%, 62.41%, 56.05%, and 65.39%, respectively). Toxicity studies of fibrous meshes with encapsulated compounds are currently being accessed in vitro, as well as pharmacokinetics and dynamics studies. The last step includes the implantation of the drug-loaded fibrous meshes in vivo.

Keywords: drug delivery, electrospinning, ERAP inhibitors, liposomes

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Authors: Shankar Dhakal, Andrew Jones, Geoffrey W. Lummis

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The Federal Democratic Republic of Nepal is a linguistically, culturally, and ethnically diverse country with approximately 123 different spoken languages that represent several ethnic, cultural, and religious groups of people. With a population of about 30 million, long-standing disparities and inequalities in access and achievement in education have constantly been challenging to provide equitable educational opportunities for all students. While the new constitution of federal Nepal (2015) stipulates that all schools serve the interests of diverse communities, leadership practices have failed to adopt local contextual sensitivities, leading to traditional, authoritarian approaches and entrenched inequalities. However, little is known about how Nepali secondary school principals can adapt and implement context-responsive and equitable strategies to ensure equity and inclusiveness in its enormously diverse socio-cultural contexts. To fill this gap, this study explores how educational leadership approaches and philosophies are transformed using a multi-case automated/ethnographic research methodology underpinned by the paradigm of critical constructivism. This paper reconstructs to see if school leadership in Nepal can produce more equitable and contextual outcomes. The results of this study highlight the need for a paradigm shift and the adoption of innovative leadership approaches that foster humility, empathy, and compassion in school leaders to achieve better school outcomes. This research provides valuable insights into existing literary gaps and provides guidance for future school leadership policies and practices at the personal, cultural, and political levels.

Keywords: school leadership, auto/ethnography, equitable and context-responsive leadership, Nepal

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Authors: Sanchita Abrol, Kunal Rana, Ankit Dhir, S. K. Gupta

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According to N.R.E.L.’s findings, 700 crore gallons of petrol is used annually to run the air conditioners of passenger vehicles (nearly 6% of total fuel consumption in the USA). Beyond fuel use, the Environmental Protection Agency reported that refrigerant leaks from auto air conditioning units add an additional 5 crore metric tons of carbon emissions to the atmosphere each year. The objective of our project is to deal with this vital issue by carefully modifying the interiors of a car thereby increasing its mileage and the efficiency of its engine. This would consequently result in a decrease in tail emission and generated pollution along with improved car performance. An automatic mechanism, deployed between the front and the rear seats, consisting of transparent thermal insulating sheet/curtain, would roll down as per the requirement of the driver in order to optimize the volume for effective air conditioning, when travelling alone or with a person. The reduction in effective volume will yield favourable results. Even on a mild sunny day, the temperature inside a parked car can quickly spike to life-threatening levels. For a stationary parked car, insulation would be provided beneath its metal body so as to reduce the rate of heat transfer and increase the transmissivity. As a result, the car would not require a large amount of air conditioning for maintaining lower temperature, which would provide us similar benefits. Authors established the feasibility studies, system engineering and primarily theoretical and experimental results confirming the idea and motivation to fabricate and test the actual product.

Keywords: automation, car, cooling insulating curtains, heat optimization, insulation, reduction in tail emission, mileage

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Authors: Amenawo I. Offiong, Hodo B. Riman

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Public debt profile of Nigeria has continuously been on the increase over the years. The drop in international crude oil prices has further worsened revenue position of the country, thus, necessitating further acquisition of public debt to bridge the gap in revenue deficit. Yet, when we look back at the increasing public sector spending, there are concerns that the government spending do not amount to increase in public goods provided for the country. Using data from 1980 to 2014 the study therefore seeks to investigate the factors responsible for the poor provision of public goods in the face of increasing public debt profile. Using the unrestricted VAR model Governance and Tax revenue were introduced into the model as structural variables. The result suggested that governance and tax revenue were structural determinants of the effectiveness of public goods provisioning in Nigeria. The study therefore identified weak governance as the major reason for the non-provision of public goods in Nigeria. While tax revenue exerted positive influence on the provisions of public goods, weak/poor governance was observed to crowd the benefits from increase tax revenue. The study therefore recommends reappraisal of the governance system in Nigeria. Elected officers in governance should be more transparent and accountable to the electorates they represent. Furthermore, the study advocates for an annual auditing of all government MDAs accounts by external auditors to ensure (a) accountability of public debts utilization, (b) transparent in implementation of program support funds, (c) integrity of agencies responsible for program management, and (d) measuring program effectiveness with amount of funds expended.

Keywords: impulse response function, public debt shocks, governance, public goods, tax revenue, vector auto-regression

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Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

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Authors: Geetanjali Sharma

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Guillain Barre’ syndrome (GBS) is an auto-immune mediated demyelination poly-radiculo-neuropathy. Clinical features include progressive symmetrical ascending muscle weakness of more than two limbs, areflexia with or without sensory, autonomic and brainstem abnormalities, the purpose of this study was to determine subclinical neurological changes of CNS with GBS and to establish the presence of central demyelination in GBS. The study was prospective and conducted in the Department of Physiology, Pt. B. D. Sharma Post-graduate Institute of Medical Sciences, University of Health Sciences, Rohtak, Haryana, India to find out early central demyelination in clinically diagnosed patients of GBS. These patients were referred from the department of Medicine of our Institute to our department for electro-diagnostic evaluation. The study group comprised of 40 subjects (20 clinically diagnosed GBS patients and 20 healthy individuals as controls) aged between 6-65 years. Brain Stem evoked Potential (BAEP) were done in both groups using RMS EMG EP mark II machine. BAEP parameters included the latencies of waves I to IV, inter peak latencies I-III, III-IV & I-V. Statistically significant increase in absolute peak and inter peak latencies in the GBS group as compared with control group was noted. Results of evoked potential reflect impairment of auditory pathways probably due to focal demyelination in Schwann cell derived myelin sheaths that cover the extramedullary portion of auditory nerves. Early detection of the sub-clinical abnormalities is important as timely intervention reduces morbidity.

Keywords: brainstem, demyelination, evoked potential, Guillain Barre’

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Authors: Chayakarn Bamrungbutr, James Sillitoe

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The term ‘shadow port’ is used to describe a port whose markets are dominated by an adjacent port that has a more competitive capability. Recently, researchers have put effort into studying the mechanisms of how a regional port, in the shadow of a nearby predominant port which is a capital city port, can compete and grow. However, such mechanism is still unclear. This study thus focuses on understanding the growth of shadow port and the type of shadow port by using the two capital city ports of Thailand; Bangkok port (the former main port) and Laem Chabang port (the current main port), as the case study. By developing an understanding of the mechanisms of shadow, port could ultimately lead to an increase in the competitiveness. In this study, a framework of opportunity capture (introduced by Magala, 2004) will be used to create a framework for the study of the growth of the selected shadow port. In the process of building this framework, five groups of port development experts, consisting of government, council, academia, logistics provider and industry, will be interviewed. To facilitate this work, the Noticing, Collecting and Thinking model which was developed by Seidel (1998) will be used in an analysis of the dataset. The resulting analysis will be used to classify the type of shadow port. The type of these ports will be a significant factor for developing a feasible strategic guideline for the future management planning of ports, particularly, shadow ports, and then to increase the competitiveness of a nation’s maritime transport industry, and eventually lead to a boost in the national economy.

Keywords: shadow port, Bangkok Port, Laem Chabang Port, port growth

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Authors: K. Debkowska

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The aim of this article is presenting the possibilities of using Fuzzy Set Qualitative Comparative Analysis (fsQCA) in researches concerning business models of enterprises. FsQCA is a bridge between quantitative and qualitative researches. It's potential can be used in analysis and evaluation of business models. The article presents the results of a study conducted on the basis of enterprises belonging to different sectors: transport and logistics, industry, building construction, and trade. The enterprises have been researched taking into account the components of business models and the financial condition of companies. Business models are areas of complex and heterogeneous nature. The use of fsQCA has enabled to answer the following question: which components of a business model and in which configuration influence better financial condition of enterprises. The analysis has been performed separately for particular sectors. This enabled to compare the combinations of business models' components which actively influence the financial condition of enterprises in analyzed sectors. The following components of business models were analyzed for the purposes of the study: Key Partners, Key Activities, Key Resources, Value Proposition, Channels, Cost Structure, Revenue Streams, Customer Segment and Customer Relationships. These components of the study constituted the variables shaping the financial results of enterprises. The results of the study lead us to believe that fsQCA can help in analyzing and evaluating a business model, which is important in terms of making a business decision about the business model used or its change. In addition, results obtained by fsQCA can be applied by all stakeholders connected with the company.

Keywords: business models, components of business models, data analysis, fsQCA

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Authors: Yi-Hui Lai, Chih-Hsiang Yang, Li-Chung Hsu

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The inflammasome is a protein complex that modulates caspase-1 activity, resulting in proteolytic cleavage of proinflammatory cytokines such as IL-1β and IL-18, into their bioactive forms. It has been shown that the inflammasomes play a crucial role in the clearance of pathogenic infection and tissue repair. However, dysregulated inflammasome activation contributes to a wide range of human diseases such as cancers and auto-inflammatory diseases. Yet, regulation of NLRP3 inflammasome activation remains largely unknown. We discovered a novel DEAD box protein, whose biological function has not been reported, not only negatively regulates NLRP3 inflammasome activation by interfering NLRP3 inflammasome assembly and cellular localization but also mitigate pyroptosis upon pathogen evasion. The DEAD-box protein is the first DEAD-box protein gets involved in modulation of the inflammasome activation. In our study, we found that caspase-1 activation and mature IL-1β production were largely enhanced upon LPS challenge in the DEAD box-containing protein- deleted THP-1 macrophages and bone marrow-derived macrophages (BMDMs). In addition, this DEAD box-containing protein migrates from the nucleus to the cytoplasm upon LPS stimulation, which is required for its inhibitory role in NLRP3 inflammasome activation. The DEAD box-containing protein specifically interacted with the LRR motif of NLRP3 via its DEAD domain. Furthermore, due to the crucial role of the NLRP3 LRR domain in the recruitment of NLRP3 to mitochondria and binding to its adaptor ASC, we found that the interaction of NLRP3 and ASC was downregulated in the presence of the DEAD box-containing protein. In addition to the mechanical study, we also found that this DEAD box protein protects host cells from inflammasome-triggered cell death in response to broad-ranging pathogens such as Candida albicans, Streptococcus pneumoniae, etc., involved in nosocomial infections and severe fever shock. Collectively, our results suggest that this novel DEAD box molecule might be a key therapeutic strategy for various infectious diseases.

Keywords: inflammasome, inflammation, innate immunity, pyroptosis

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Authors: Sai Rajeev Reddy, Ishita Roy, M. Anji Reddy

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The paper describes the importance of preventive measures and immediate Emergency logistics during accidents and unfortunate Disasters for the Hyderabad Metro Rails in their various stages of construction. This is the need of the modern generation where accidents, explosions, attacks and sudden crisis are frequent casualties which take huge tolls of life in the present world. The paper utilizes the workflow and application of Geographical information System (GIS) to provide information about problems and crisis structures for efficient Metro Transportation in the city. The study analyzes the difficulties and problems which cause accidents during operation and maintenance stages of the Metro Rail. The paper focuses upon the intermediate and firsthand information of Crisis with the help of GIS technology to share Disaster data for effective measures by the Cyber Police stations, Emergency Responders, Hospitals and First Aid Centre to act immediately and save lives. The results and conclusions have nevertheless proved very informative and useful for the safety board authorities of the Hyderabad Metro Rail. The operation and Maintenance are integral stages in the development of any Multipurpose transportation Projects and are usually prone to various Disasters and tragedies. Hence, the GIS technologies help in distribution of information among the masses with the web Technologies and advanced software developed to prevent and manage crisis widely and in a cost-benefits manner.

Keywords: Geographical Information System, emergency assessment, accident zones, surveillance

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Authors: Reza Alikhani

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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Firdaous Zair, Zoubir Elfelsoufi, Mohammed Fourka

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The allocation of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players, manufacturers and Click & Mortars that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. Our contribution is a decision support system and tool for improving the allocation of resources in logistics chains e-commerce B2C context. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. In addition, every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource allocation in customized online shopping service mode, which is different from the supply chain resource allocation under traditional manufacturing or service circumstances. Then we realized an optimization model and algorithm for the development based on the analysis of the allocation of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: e-commerce, supply chain, B2C, optimisation, resource allocation

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Authors: Muhammad Siddique, Volodymyr Lugovskyy

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This paper explores how nations might mitigate the unfavorable impacts of oil price volatility on economic growth by switching to renewable energy sources. The impacts of uncertain factor prices on economic activity are examined by looking at the Realized Volatility (RV) of oil prices rather than the more traditional method of looking at oil price shocks. The United States of America (USA), China (C), India (I), United Kingdom (UK), Germany (G), Malaysia (M), and Pakistan (P) are all included to round out the traditional literature's examination of selected nations, which focuses on oil-importing and exporting economies. Granger Causality Tests (GCT), Impulse Response Functions (IRF), and Variance Decompositions (VD) demonstrate that in a Vector Auto-Regressive (VAR) scenario, the negative impacts of oil price volatility extend beyond what can be explained by oil price shocks alone for all of the nations in the sample. Different nations have different levels of vulnerability to changes in oil prices and other factors that may play a role in a sectoral composition and the energy mix. The conventional method, which only takes into account whether a country is a net oil importer or exporter, is inadequate. The potential economic advantages of initiatives to decouple the macroeconomy from volatile commodities markets are shown through simulations of volatility shocks in alternative energy mixes (with greater proportions of renewables). It is determined that in developing countries like Pakistan, increasing the use of renewable energy sources might lessen an economy's sensitivity to changes in oil prices; nonetheless, a country-specific study is required to identify particular policy actions. In sum, the research provides an innovative justification for mitigating economic growth's dependence on stable oil prices in our sample countries.

Keywords: oil price volatility, renewable energy, economic growth, developed and developing economies

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Authors: Melanie Macgregor-Ramiasa, Isabel Hopp, Patricia Murray, Krasimir Vasilev

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Stem cells based therapies are one of the greatest promises of new-age medicine due to their potential to help curing most dreaded conditions such as cancer, diabetes and even auto-immune disease. However, establishing suitable in vitro culture materials allowing to control the fate of stem cells remain a challenge. Amongst the factor influencing stem cell behavior, substrate chemistry and nanotopogaphy are particularly critical. In this work, we used plasma assisted surface modification methods to produce model substrates with tailored nanotopography and controlled chemistry. Three different sizes of gold nanoparticles were bound to amine rich plasma polymer layers to produce homogeneous and gradient surface nanotopographies. The outer chemistry of the substrate was kept constant for all substrates by depositing a thin layer of our patented biocompatible polyoxazoline plasma polymer on top of the nanofeatures. For the first time, protein adsorption and stem cell behaviour (mouse kidney stem cells and mesenchymal stem cells) were evaluated on nanorough plasma deposited polyoxazoline thin films. Compared to other nitrogen rich coatings, polyoxazoline plasma polymer supports the covalent binding of proteins. Moderate surface nanoroughness, in both size and density, triggers cell proliferation. In association with polyoxazoline coating, cell proliferation is further enhanced on nanorough substrates. Results are discussed in term of substrates wetting properties. These findings provide valuable insights on the mechanisms governing the interactions between stem cells and their growth support.

Keywords: nanotopography, stem cells, differentiation, plasma polymer, oxazoline, gold nanoparticles

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Authors: Nikolay P. Brayanov, Anna V. Stoynova

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Model-based development approach is gaining more support and acceptance. Its higher abstraction level brings simplification of systems’ description that allows domain experts to do their best without particular knowledge in programming. The different levels of simulation support the rapid prototyping, verifying and validating the product even before it exists physically. Nowadays model-based approach is beneficial for modelling of complex embedded systems as well as a generation of code for many different hardware platforms. Moreover, it is possible to be applied in safety-relevant industries like automotive, which brings extra automation of the expensive device certification process and especially in the software qualification. Using it, some companies report about cost savings and quality improvements, but there are others claiming no major changes or even about cost increases. This publication demonstrates the level of maturity and autonomy of model-based approach for code generation. It is based on a real live automotive seat heater (ASH) module, developed using The Mathworks, Inc. tools. The model, created with Simulink, Stateflow and Matlab is used for automatic generation of C code with Embedded Coder. To prove the maturity of the process, Code generation advisor is used for automatic configuration. All additional configuration parameters are set to auto, when applicable, leaving the generation process to function autonomously. As a result of the investigation, the publication compares the quality of generated embedded code and a manually developed one. The measurements show that generally, the code generated by automatic approach is not worse than the manual one. A deeper analysis of the technical parameters enumerates the disadvantages, part of them identified as topics for our future work.

Keywords: embedded code generation, embedded C code quality, embedded systems, model-based development

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Ridwan Dewayanto Rusli

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We show how prisoner's dilemma-type competition problems can be mitigated through rapid platform diversification and ecosystem expansion. We analyze a ride-hailing company in Southeast Asia, Gojek, whose network grew to more than 170 million users comprising consumers, partner drivers, merchants, and complementors within a few years and has already achieved higher contribution margins than ride-hailing peers Uber and Lyft. Its ecosystem integrates ride-hailing, food delivery and logistics, merchant solutions, e-commerce, marketplace and advertising, payments, and fintech offerings. The company continues growing its network of complementors and App developers, expanding content and gaining critical mass in consumer data analytics and advertising. We compare the company's growth and diversification trajectory with those of its main international rivals and peers. The company's rapid growth and future potential are analyzed using Cusumano's (2012) Staying Power and Six Principles, Hax and Wilde's (2003) and Hax's (2010) The Delta Model as well as Santos' (2016) home-market advantages frameworks. The recently announced multi-billion-dollar merger with one of Southeast Asia's largest e-commerce majors lends additional support to the above arguments.

Keywords: ride-hailing, prisoner's dilemma, platform and ecosystem strategy, digital applications, diversification, home market advantages, e-commerce

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Authors: Songyan Yin, Ravindra Rajarao, Veena Sahajwalla

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Automotive plastics waste (widely known as auto-fluff or ASR) is a complicated mixture of various plastics incorporated with a wide range of additives and fillers like titanium dioxide, magnesium oxide, and silicon dioxide. Automotive plastics waste is difficult to recycle and its landfilling poses the significant threat to the environment. In this study, a sustainable technology to fabricate protective nanoscale TiN thin film on a steel substrate surface by using automotive waste plastics as titanium and carbon resources is suggested. When heated automotive plastics waste with steel at elevated temperature in a nitrogen atmosphere, titanium dioxide contented in ASR undergo carbothermal reduction and nitridation reactions on the surface of the steel substrate forming a nanoscale thin film of titanium nitride on the steel surface. The synthesis of TiN film on steel substrate under this technology was confirmed by X-ray photoelectron spectrometer, high resolution X-ray diffraction, field emission scanning electron microscope, a high resolution transmission electron microscope fitted with energy dispersive X-ray spectroscopy, and inductively coupled plasma mass spectrometry techniques. This sustainably fabricated TiN film was verified of dense, well crystallized and could provide good oxidation resistance to the steel substrate. This sustainable fabrication technology is maneuverable, reproducible and of great economic and environmental benefit. It not only reduces the fabrication cost of TiN coating on steel surface, but also provides a sustainable environmental solution to recycling automotive plastics waste. Moreover, high value copper droplets and char residues were also extracted from this unique fabrication process.

Keywords: automotive plastics waste, carbonthermal reduction and nitirdation, sustainable, TiN film

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Aminu Musa Audu

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This paper examines the human resources management issues of the Nigeria Police and how it is impacting the community policing policy transfer. Nigeria Police Force is the organisation in the country with the constitutional responsibility of maintaining law and order. The high level of crime and other forms of insecurity called for the introduction of ‘police-community partnership’ strategy in 2003. The trend of events has suggested that the effort is not yielding result, partly because the police in Nigeria are facing human resources management challenges. For instance, the prospective candidates for the police jobs are usually not vetted a situation which provides the possibility of recruiting persons of low academic background and questionable character, or even criminal records. Moreover, the existing training, development infrastructure and other logistics for the job of policing are not in good condition. Consequently, the implementation of the ‘community policing’ policy for crime prevention and control in Nigeria stands to suffer setbacks. Adopting qualitative methods and with focus groups discussions and individual in-depth interviews for data collections, the findings from the views and perspectives of the participants were suggestive of poor handlings of human resources management of the Nigeria police organisation and with negative effect on the implementation of community policing policy. The paper therefore recommends that a total overhaul of the human resources component of the police organisation is necessary in the community policing policy transfer process for crime prevention and control in Nigeria.

Keywords: Nigeria Police Force, community policing policy transfer, human resources management, police-community partnership

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Authors: Ephraim Ugwu, Christopher Ehinomen

Abstract:

Despite efforts by the Nigerian government to harmonize the macroeconomic policy implementations by establishing various committees to resolve disputes between the fiscal and monetary authorities, it is still evident that the federal government had continued its expansionary policy by increasing spending, thus creating huge budget deficit. This study evaluates the effect of macroeconomic policy coordination on economic growth uncertainty in Nigeria from 1980 to 2020. Employing the Auto regressive distributed lag (ARDL) bound testing procedures, the empirical results shows that the error correction term, ECM(-1), indicates a negative sign and is significant statistically with the t-statistic value of (-5.612882 ). Therefore, the gap between long run equilibrium value and the actual value of the dependent variable is corrected with speed of adjustment equal to 77% yearly. The long run coefficient results showed that the estimated coefficients of the intercept term indicates that other things remains the same (ceteris paribus), the economics growth uncertainty will continue reduce by 7.32%. The coefficient of the fiscal policy variable, PUBEXP, indicates a positive sign and significant statistically. This implies that as the government expenditure increases by 1%, economic growth uncertainty will increase by 1.67%. The coefficient of monetary policy variable MS also indicates a positive sign and insignificant statistically. The coefficients of merchandise trade variable, TRADE and exchange rate EXR show negative signs and significant statistically. This indicate that as the country’s merchandise trade and the rate of exchange increases by 1%, the economic growth uncertainty reduces by 0.38% and 0.06%, respectively. This study, therefore, advocate for proper coordination of monetary, fiscal and exchange rate policies in order to actualize the goal of achieving a stable economic growth.

Keywords: macroeconomic, policy coordination, growth uncertainty, ARDL, Nigeria

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Authors: Siddhartha Paul, Debabrata Das

Abstract:

Closed-loop supply chain (CLSC) management focuses on integrating forward and reverse flow of material as well as information to maximize value creation over the entire life-cycle of a product. Bullwhip effect in supply chain management refers to the phenomenon where a small variation in customers’ demand results in larger variation of orders at the upstream levels of supply chain. Since the quality and quantity of products returned to the collection centers (as a part of reverse logistics process) are uncertain, bullwhip effect is inevitable in CLSC. Therefore, in the present study, first, through an extensive literature survey, we identify all the important factors related to forward as well as reverse supply chain which causes bullwhip effect in CLSC. Second, we develop a system dynamics model to study the interrelationship among the factors and their effect on the performance of overall CLSC. Finally, the results of the simulation study suggest that demand forecasting, lead times, information sharing, inventory and work in progress adjustment rate, supply shortages, batch ordering, price variations, erratic human behavior, parameter correcting, delivery time delays, return rate of used products, manufacturing and remanufacturing capacity constraints are the important factors which have a significant influence on system’s performance, specifically on bullwhip effect in a CLSC.

Keywords: bullwhip effect, closed-loop supply chain, system dynamics, variance ratio

Procedia PDF Downloads 154

Authors: Xianglei Yin, Shen Wang, Baoyi Wang, Laihong Shen

Abstract:

Chemical looping partial oxidation of methane (CLPOM) is a novel technology to produce high-quality syngas with an auto-thermic process and low equipment investment. The development of oxygen carriers is important for the improvement of the CLPOM performance. In this work, the effect of the nickel-substitution proportion on the performance of LaMn₁₋ᵧNiᵧO₃₊δ perovskites for CLPOM was studied in the aspect of reactivity, syngas selectivity, resistance towards carbon deposition and thermal stability in cyclic redox process. The LaMn₁₋ₓNiₓO₃ perovskite oxides with x = 0, 0.1, 0.2 were prepared by the sol-gel method. The performance of LaMn₁₋ᵧNiᵧO₃₊δ perovskites for CLPOM was investigated through the characterization of XRD, H₂-TPR, XPS, and fixed-bed experiments. The characterization and test results suggest that the doping of nickel enhances the generation rate of syngas, leading to high syngas yield, methane conversion, and syngas selectivity. This is attributed to the that the introduction of nickel provides active sites to promote the methane activation on the surface and causes the addition of oxygen vacancies to accelerate the migration of oxygen anion in the bulk of oxygen carrier particles. On the other hand, the introduction of nickel causes carbon deposition to occur earlier. The best substitution proportion of nickel is y=0.1 and LaMn₀.₉Ni₀.₁O₃₊δ could produce high-quality syngas with a yield of 3.54 mmol·g⁻¹, methane conversion of 80.7%, and CO selectivity of 84.8% at 850℃. In addition, the LaMn₀.₉Ni₀.₁O₃₊δ oxygen carrier exhibits superior and stable performance in the cyclic redox process.

Keywords: chemical looping partial oxidation of methane, LaMnO₃₊δ, Ni doping, syngas, carbon deposition

Procedia PDF Downloads 91

Authors: Dana Mohammed, Fatemah Abdullah, Hawraa Ali, Najat Al-Shaer, Rawan Al-Awadhi, , Magdy Helal

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We study the patient service performance at the emergency department of a major Kuwaiti public hospital, using discrete simulation and lean concepts. In addition to the common problems in such health care systems (over crowdedness, facilities planning and usage, scheduling and staffing, capacity planning) the emergency department suffered from several cultural and patient behavioural issues. Those contributed significantly to the system problems and constituted major obstacles in maintaining the performance in control. This led to overly long waiting times and the potential of delaying providing help to critical cases. We utilized the visual management tools to mitigate the impact of the patients’ behaviours and attitudes and improve the logistics inside the system. In addition a proposal is made to automate the date collection and communication within the department using RFID-based barcoding system. Discrete event simulation models were developed as decision support systems; to study the operational problems and assess achieved improvements. The simulation analysis resulted in cutting the patient delays to about 35% of their current values by reallocating and rescheduling the medical staff. Combined with the application of the visual management concepts, this provided the basis to improving patient service without any major investments.

Keywords: simulation, visual management, health care system, patient

Procedia PDF Downloads 464

Authors: Atousa Khodadadyan, Ali Rostami

Abstract:

The objective of off-site construction manufacturing is to utilise the workforce and machinery in a controlled environment without external interference for higher productivity and quality. The usage of prefabricated components can save up to 14% of the total energy consumption in comparison with the equivalent number of cast-in-place ones. Despite the benefits of prefabrication construction, its current project practices encompass technical and managerial issues. Building design, precast components’ production, logistics, and prefabrication installation processes are still mostly discontinued and fragmented. Furthermore, collaboration among prefabrication manufacturers, transportation parties, and on-site assemblers rely on real-time information such as the status of precast components, delivery progress, and the location of components. From the technical point of view, in this industry, geometric variability is still prevalent, which can be caused during the transportation or production of components. These issues indicate that there are still many aspects of prefabricated construction that can be developed using disruptive technologies. Practical real-time risk analysis can be used to address these issues as well as the management of safety, quality, and construction environment issues. On the other hand, the lack of research about risk assessment and the absence of standards and tools hinder risk management modeling in prefabricated construction. It is essential to note that no risk management standard has been established explicitly for prefabricated construction projects, and most software packages do not provide tailor-made functions for this type of projects.

Keywords: project risk management, risk analysis, risk modelling, prefabricated construction projects

Procedia PDF Downloads 165