Search results for: potential problem

Authors: A. Rosazlin Abdullah, I. Che Fauziah, K. Wan Rasidah, A. B. Rosenani

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The paper industry performs an essential role in the global economy of the world. A study was conducted on the paper mill sludge that is applied on the Khaya senegalensis for 1 year planning period at University Agriculture Park, Puchong, Selangor, Malaysia to determine the growth of Khaya senegalensis, soil properties, nutrients concentrations and effects on the status of heavy metals. Paper Mill Sludge (PMS) and composted Recycled Paper Mill Sludge (RPMS) were used with different rates of nitrogen (0, 150, 300 and 600 kg ha-1) at the ratio of 1:1 (Recycled Paper Mill Sludge (RPMS) : Empty Fruit Brunch (EFB). The growth parameters were measured twice a month for 1 year. Plant nutrients and heavy metal uptake were determined. The paper mill sludge has the potential to be a supplementary N fertilizer as well as a soil amendment. The application of RPMS with N, significantly contributed to the improvement in plant growth parameters such as plant height (4.24 m), basal diameter (10.30 cm), total plant biomass and improved soil physical and chemical properties. The pH, EC, available P and total C in soil were varied among the treatments during the planting period. The treatments with raw and RPM compost had higher pH values than those applied with inorganic fertilizer and control. Nevertheless, there was no salinity problem recorded during the planting period and available P in soil treated with raw and RPMS compost was higher than the control plots that reflects the mineralization of organic P from the decomposition of pulp sludge. The weight of the free and occluded light fractions of carbon concentration was significantly higher in the soils treated with raw and RPMS compost. The application of raw and composted RPMS gave significantly higher concentration of the heavy metals, but the total concentrations of heavy metals in the soils were below the critical values. Hence, the paper mill sludge can be successfully used as soil amendment in acidic soil without any serious threat. The use of paper mill sludge for the soil fertility, shows improvement in land application signifies a unique opportunity to recycle sludge back to the land to alleviate the potential waste management problem.

Keywords: growth, heavy metals, nutrients uptake, production, waste management

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Authors: E. S. Johal, M. S. Saini, M. K. Jha

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Currently, 1.1 billion people are at risk due to lack of clean water and about 35 % of people in the developed world die from water related problem. To alleviate these problems water purification technology requires new approaches for effective management and conservation of water resources. Electrospun nanofibres membrane has a potential for water purification due to its high large surface area and good mechanical strength. In the present study PAMAM dendrimers composite nynlon-6 nanofibres membrane was prepared by crosslinking method using Glutaraldehyde. Further, the efficacy of the modified membrane can be renewed by mere exposure of the saturated membrane with the solution having acidic pH. The modified membrane can be used as an effective tool for water purification.

Keywords: dendrimer, nanofibers, nanocomposite membrane, water purification

Procedia PDF Downloads 333

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: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

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Authors: Manana Lobzhanidze

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Introduction: The paper will argue that labor migration is the most important problem Georgia faces today. The structure of labor migration by age and gender of Georgia is analyzed. The main driving factors of circular labor migration during the last ten years are identified. While studying migration, it is necessary to discuss the interconnection of economic, social, and demographic features, also taking into consideration the policy of state regulations in terms of education and professional training. Methodology: Different research methods are applied in the presented paper: statistical, such as selection, grouping, observation, trend, and qualitative research methods, namely; analysis, synthesis, induction, deduction, comparison ones. Main Findings: Labour migrants are filling the labor market as a low salary worker. The main positive feedback of migration from developing countries is poverty eradication, but this process is accompanied by problems, such as 'Brain Drain'. The country loses an important part of its intellectual potential, and it is invested by households or state itself. Conclusions: Labor migration is characterized to be temporary, but socio-economic problems of the country often push the labor migration in the direction of longterm and illegal migration. Countries with developed economies try to stricter migration policy and fight illegal migration with different methods; circular migration helps solve this problem. Conclusions and recommendations are included about circular labor migration consequences in Georgia and its influence on the reduction of unemployment level.

Keywords: migration, circular labor migration, labor migration employment, unemployment

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Authors: L. Sefouhi, M. Djebabra

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Industrial operations have been accompanied by a problem: industrial waste which may be toxic, ignitable, corrosive or reactive. If improperly managed, this waste can pose dangerous health and environmental consequences. The industrial waste management becomes a real problem for them. The oil industry is an important sector in Algeria, from exploration to development and marketing of hydrocarbons. For this sector, industrial wastes pose a big problem. The aim of the present study is to present in a systematic way the subject of industrial waste from the point-of-view of definitions in engineering and legislation. This analysis is necessary, as many different approaches and we will attempt to diagnose the current management of industrial waste, namely an inventory of deposits and methods of sorting, packing, storage, and a description of the different disposal routes. Thus, a proposal for a reasoned and responsible management of waste by avoiding a shift towards future expenses related to the disposal of such waste, and prevents pollution they cause to the environment.

Keywords: industrial waste, environment, management, pollution, risks

Procedia PDF Downloads 312

Authors: Ali Kirkbas

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R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

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Authors: Muhammad Mukhtar Aliyu

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This study investigated tutors’ experiences and perceptions of a problem-based learning approach (PBL) in a writing classroom. The study involved two Nigerian lecturers who facilitated an intact class of second-year students in an English composition course for the period of 12 weeks. Semi-structured interviews were employed to collect data of the study. The lecturers were interviewed before and after the implementation of the PBL process. The overall findings of the study show that the lecturers had positive perceptions of the use of PBL in a writing classroom. Specifically, the findings reveal the lecturers’ positive experiences and perception of the group activities. Finally, the paper gives some pedagogical implications which would give insight for better implementation of the PBL approach.

Keywords: experiences and perception, Nigeria, problem-based learning approach, writing classroom

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Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan

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In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: rough sets, decision rules, rule induction, classification

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Authors: Anteneh Getachew Gebrie, Rabian Wangkeeree

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The purpose of this paper is to introduce iterative algorithm solving split system of minimization problem given as a task of finding a common minimizer point of finite family of proper, lower semicontinuous convex functions and whose image under a bounded linear operator is also common minimizer point of another finite family of proper, lower semicontinuous convex functions. We obtain strong convergence of the sequence generated by our algorithm under some suitable conditions on the parameters. The iterative schemes are developed with a way of selecting the step sizes such that the information of operator norm is not necessary. Some applications and numerical experiment is given to analyse the efficiency of our algorithm.

Keywords: Hilbert Space, minimization problems, Moreau-Yosida approximate, split feasibility problem

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Authors: A. Luft, S. Bremen, N. Balc

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The task of flexibility planning and design, just like factory planning, for example, is to create the long-term systemic framework that constitutes the restriction for short-term operational management. This is a strategic challenge since, due to the decision defect character of the underlying flexibility problem, multiple types of flexibility need to be considered over the course of various scenarios, production programs, and production system configurations. In this context, an evaluation model has been developed that integrates both conventional and additive resources on a basic task level and allows the quantification of flexibility enhancement in terms of mix and volume flexibility, complexity reduction, and machine capacity. The model helps companies to decide in early decision-making processes about the potential gains of implementing additive manufacturing technologies on a strategic level. For companies, it is essential to consider both additive and conventional manufacturing beyond pure unit costs. It is necessary to achieve an integrative view of manufacturing that incorporates both additive and conventional manufacturing resources and quantifies their potential with regard to flexibility and manufacturing complexity. This also requires a structured process for the strategic production systems design that spans the design of various scenarios and allows for multi-dimensional and comparative analysis. A respective guideline for the planning of additive resources on a strategic level is being laid out in this paper.

Keywords: additive manufacturing, production system design, flexibility enhancement, strategic guideline

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Authors: Mazura Mokhtar, Adibah Shuib, Daud Mohamad

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Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.

Keywords: portfolio optimization, mathematical programming, multi-objective programming, solution approaches

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Authors: Frode van der Laak

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The paper contributes to the feasibility of using a 5G mobile connection as a node for a Proof of Authority (PoA) blockchain, which is used for microtransactions at the same time. It uses the phone number identity of the users that are linked to the crypto wallet address. It also proposed a consensus protocol based on Proof-of-Authority (PoA) blockchain; PoA is a permission blockchain where consensus is achieved through a set of designated authority rather than through mining, as is the case with a Proof of Work (PoW) blockchain. This report will first explain the concept of a PoA blockchain and how it works. It will then discuss the potential benefits and challenges of using a 5G mobile connection as a node in such a blockchain, and finally, the main open problem statement and proposed solutions with the requirements.

Keywords: 5G, mobile, connection, node, PoA, blockchain, microtransaction

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Authors: Eman Tadros

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Solution Focused Therapy sheds a positive light on a client’s problem(s) by instilling hope, focusing on the connection with the client, and describing the problem in a way to display change being possible. Solution focused therapists highlight clients’ positive strengths, reframe what clients say, do, or believe in a positive statement, action, or belief. Narrative Therapy focuses on the stories individuals tell about their past in which shape their current and future lives. Changing the language used aids clients in reevaluating their values and views of themselves, this then constructs a more positive way of thinking about their story. Both therapies are based on treating each client as an individual with a problem rather than that the individual is a problem and being able to give power back to the client. The purpose of these ideologies is to open a client to alternative understandings. This paper displays how clinicians can empower and identify their clients’ positive strengths and resiliency factors. Narrative and Solution-Focused Techniques will be integrated to instill positivity and empowerment in clients. Techniques such as deconstruction, collaboration, complimenting, miracle/exception/scaling questioning will be analyzed and modeled. Furthermore, bridging Solution Focused Therapy and Narrative Therapy gives a voice to unheard client(s).

Keywords: solution focused therapy, narrative therapy, empowerment, resilience

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Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain

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The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.

Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR

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Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

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The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

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Authors: Ajay R, Rammohan B, Sridhar K S S, Gurusharan N

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The objective of the work is to develop a numerical method to solve the inverse mode shape problem by determining the cross-sectional area of a structure for the desired mode shape via the vibration response study of the humerus bone, which is in the form of a cantilever beam with anisotropic material properties. The humerus bone is the long bone in the arm that connects the shoulder to the elbow. The mode shape is assumed to be a higher-order polynomial satisfying a prescribed set of boundary conditions to converge the numerical algorithm. The natural frequency and the mode shapes are calculated for different boundary conditions to find the cross-sectional area of humerus bone from Eigenmode shape with the aid of the inverse mode shape algorithm. The cross-sectional area of humerus bone validates the mode shapes of specific boundary conditions. The numerical method to solve the inverse mode shape problem is validated in the biomedical application by finding the cross-sectional area of a humerus bone in the human arm.

Keywords: Cross-sectional area, Humerus bone, Inverse mode shape problem, Mode shape

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Authors: Didem Can

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Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

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Authors: Chimeri Muzano Leonard

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The study was carried out to investigate the perceptions of male and female Ordinary Level students on the effects of alcohol abuse at Gatsi Secondary School. The study showed that alcohol abuse has academic, social, psychological and health effects on Ordinary Level students. The negative effects comprises of death, dropping out, poor grades, poor concentration, risky behaviors, impairment of the brain and central nervous system , risky behaviors and Impairment of reproductive functioning Only students who enrolled for Ordinary Level in the 2014 academic year participated in this study. Fifty students (25 males and 25 females) were randomly selected to participate in the study. A formal survey questionnaire was used to collect data. The respondents were asked to use a scale of 0 (totally disagree) to 10 (completely agree) to indicate the extent to which they agreed with each perception. The Statistical Package for Social Sciences (SPSS) version 19.0 was used for data analysis. The Mann Whitney U test was used to test for the significance of differences in the perceptions of male and female students. No statistically significant differences were detected between males and females in most of their perceptions regarding the effects of alcohol abuse on Ordinary Level students. However, there were three perceptions found to be significantly different between male and female. They comprises of “Peers influence one to drink alcohol”, “Alcohol abuse is a major problem among male students compared to their female peers” and “ Female students should not drink beer”.It was evident from this study that Gatsi Secondary School needs to implement more effective interventions that combat alcohol abuse. A deeper analysis of the issues that predispose Ordinary Level students to alcohol abuse should inform the interventions. Consequently, unravelling the problem of negative effects of alcohol abuse was desirable because of its potential usefulness in developing strategies that might help curb the problem and presumably improve the performance of Ordinary Level students and above all the quality of education at Gatsi Secondary School.

Keywords: perceived effects, alcohol, Gatsi Secondary School, alcohol abuse

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Authors: Sabah Mohammed, Jinan Fiaidhi, Darien Sawyer

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Describing clinical cases according to a clinical charting standard that enforces interoperability and enables connected care services can save lives in the event of a medical emergency or provide efficient and effective interventions for the benefit of the patients through the integration of bedside and bench side clinical research. This article presented a multi-tenant extension to the problem-oriented medical record that we have prototyped previously upon using the GraphQL Application Programming Interface to represent the notion of a problem list. Our implemented extension enables physicians and patients to collaboratively describe the patient case via using multi chatbots to collaboratively describe the patient case using the SOAP charting standard. Our extension also connects the described SOAP patient case with the HL7 FHIR (Health Interoperability Resources) medical record for connecting the patient case to the bench data.

Keywords: problem-oriented medical record, graphQL, chatbots, SOAP

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Authors: Abdeljalil Beniiche

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The limitation with smart contracts is that they cannot access external data that might be required to control the execution of business logic. Oracles can be used to provide external data to smart contracts. An oracle is an interface that delivers data from external data outside the blockchain to a smart contract to consume. Oracle can deliver different types of data depending on the industry and requirements. In this paper, we study and describe the widely used blockchain oracles. Then, we elaborate on his potential role, technical architecture, and design patterns. Finally, we discuss the human oracle and its key role in solving the truth problem by reaching a consensus about a certain inquiry and tasks.

Keywords: blockchain, oracles, oracles design, human oracles

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Authors: Xiaojie Cheng, Ulrike Frank, Feng Zhao, Karin Pritsch

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Ragweed (Ambrosia artemisiifolia) is an invasive weed that has become an increasing global problem. In addition to affecting land use and crop yields, ragweed has a strong impact on human health as it produces highly allergenic pollen. Global warming will result in an earlier and longer pollen season enhanced pollen production and an increase in pollen allergenicity with a negative effect on atopic patients. The aims of this study were to investigate the effects of increasing temperature, the future climate scenario in the Munich area, southern Germany, predicted on the basis of RCP8.5 until the end of 2050s, or/and NO₂, a major air pollutant, 1) on the vegetative and reproductive characteristics of ragweed plants, 2) on the total allergenicity of ragweed pollen, 3) on the total pollen proteomic patterns. Ragweed plants were cultivated for the whole plant vegetation period under controlled conditions either under ambient climate conditions or 4°C higher temperatures with or without additional NO₂. Higher temperature resulted in bigger plant sizes, longer male inflorescences, and longer pollen seasons. The total allergenic potential of the pollen was accessed by dot blot using serum from ragweed pollen sensitized patients. The comparative immunoblot analysis revealed that the in vivo fumigation of ragweed plants with elevated NO₂-concentrations significantly increased the allergenic potential of the pollen, and in combination with increased temperature, the allergenic potential was even higher. On the other hand, label-free protein quantification by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed. The results showed that more proteins were significantly up- and down-regulated under higher temperatures with/without elevated NO₂ conditions. Most of the highly expressed proteins were participating intensively in the metabolic process, the cellular process, and the stress defense process. These findings suggest that rising temperature and elevated NO₂ are important environmental factors for higher abiotic stress activities, catalytic activities, and thus higher allergenic potential observed in pollen proteins.

Keywords: climate change, NO₂, pollen proteome, ragweed, temperature

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Authors: Shunichi Ohmori, Sirawadee Arunyanart, Kazuho Yoshimoto

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We consider a periodic review inventory control problem of minimizing production cost, inventory cost, and lost-sales under demand uncertainty, in which product demands are not specified exactly and it is only known to belong to a given uncertainty set, yet the constraints must hold for possible values of the data from the uncertainty set. We propose a robust optimization formulation for obtaining lowest cost possible and guaranteeing the feasibility with respect to range of order quantity and inventory level under demand uncertainty. Our formulation is based on the adaptive robust counterpart, which suppose order quantity is affine function of past demands. We derive certainty equivalent problem via second-order cone programming, which gives 'not too pessimistic' worst-case.

Keywords: robust optimization, inventory control, supply chain managment, second-order programming

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Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: Carolina Silva, João Nuno Oliveira, Rui Sousa, João Paulo Silva

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This study uses genetic algorithms to solve a job scheduling problem in a weaving factory. The underline problem regards an NP-Hard problem concerning unrelated parallel machines, with sequence-dependent setup times. This research uses real data regarding a weaving industry located in the North of Portugal, with a capacity of 96 looms and a production, on average, of 440000 meters of fabric per month. Besides, this study includes a high level of complexity once most of the real production constraints are applied, and several real data instances are tested. Topics such as data analyses and algorithm performance are addressed and tested, to offer a solution that can generate reliable and due date results. All the approaches will be tested in the operational environment, and the KPIs monitored, to understand the solution's impact on the production, with a particular focus on the total number of weeks of late deliveries to clients. Thus, the main goal of this research is to develop a solution that allows for the production of automatically optimized production plans, aiming to the tardiness minimizing.

Keywords: genetic algorithms, textile industry, job scheduling, optimization

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Authors: Verónica Díaz

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A Cartesian graph, as a mathematical object, becomes a tool for configuration of change. Its best comprehension is done through everyday life problem-solving associated with its representation. Despite this, the current educational framework favors general graphs, without consideration of their argumentation. Students are required to find the mathematical function without associating it to the development of graphical language. This research describes the use made by students of configurations made prior to Cartesian graphs with regards to an everyday life problem related to a time and distance variation phenomenon. The theoretical framework describes the function conditions of study and their modeling. This is a qualitative, descriptive study involving six undergraduate case studies that were carried out during the first term in 2016 at University of Los Lagos. The research problem concerned the graphic modeling of a real person’s movement phenomenon, and two levels of analysis were identified. The first level aims to identify local and global graph interpretations; a second level describes the iconicity and referentiality degree of an image. According to the results, students were able to draw no figures before the Cartesian graph, highlighting the need for students to represent the context and the movement of which causes the phenomenon change. From this, they managed Cartesian graphs representing changes in position, therefore, achieved an overall view of the graph. However, the local view only indicates specific events in the problem situation, using graphic and verbal expressions to represent movement. This view does not enable us to identify what happens on the graph when the movement characteristics change based on possible paths in the person’s walking speed.

Keywords: cartesian graphs, higher education, movement modeling, problem solving

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Authors: Omar Dib, Alexandre Caminada, Marie-Ange Manier

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The purpose of this study is to introduce a novel approach to solve the one-to-one shortest path problem. A directed connected graph is assumed in which all edges’ weights are positive. Our method is based on a memetic algorithm in which we combine a genetic algorithm (GA) and a variable neighborhood search method (VNS). We compare our approximate method with two exact algorithms Dijkstra and Integer Programming (IP). We made experimentations using random generated, complete and real graph instances. In most case studies, numerical results show that our method outperforms exact methods with 5% average gap to the optimality. Our algorithm’s average speed is 20-times faster than Dijkstra and more than 1000-times compared to IP. The details of the experimental results are also discussed and presented in the paper.

Keywords: shortest path problem, Dijkstra’s algorithm, integer programming, memetic algorithm

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Authors: Sagar Hedaoo, Fazle Baki, Ahmed Azab

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In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used.

Keywords: emission, mixed integer linear programming, metaheuristic, simulated annealing

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Authors: Ashwani Kumar Aggarwal

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NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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Authors: Apurva Patil, Sujatha Srinivasan

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Reducing actuator loads is important for applications in which human effort is required for actuation. The potential benefit of applying spring balancing to rehabilitation devices which work against gravity on a nonhorizontal plane is well recognized, but practical applications have been elusive. Although existing methods provide exact spring balance, they require additional masses or auxiliary links, or all the springs used originate from the ground, which makes the resulting device bulky and space-inefficient. This paper uses a method of static balancing of mechanisms with conservative loads such as gravity and spring loads using non-zero-free-length springs and no auxiliary links. Application of this method to a manually operated swimming pool lift mechanism which lowers and raises the physically challenged users into or out of the swimming pool is presented here. Various possible configurations using extension and compression springs as well as gas spring in the mechanism are compared. This work involves approximate spring balancing of the mechanism using minimization of potential energy variance. It uses the approach of flattening the potential energy distribution over the workspace and fuses it with numerical optimization. The results show the considerable reduction in actuator torque requirement with practical spring design and arrangement. Although the method provides only an approximate balancing, it is versatile, flexible in choosing appropriate control variables that are relevant to the design problem and easy to implement. The true potential of this technique lies in the fact that it uses a very simple optimization to find the spring constant, free length of the spring and the optimal attachment points subject to the optimization constraints. Also, it uses physically realizable non-zero-free-length springs directly, thereby reducing the complexity involved in simulating zero-free-length springs from non-zero-free-length springs. This method allows springs to be attached inside the mechanism, which makes the implementation of spring balancing practical. Because auxiliary linkages can be avoided, the resultant swimming pool lift mechanism is compact. The cost benefits and reduced complexity can be significant advantages in the development of this user-actuated swimming pool lift for developing countries.

Keywords: gas spring, rehabilitation device, spring balancing, swimming pool lift

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