Search results for: optimization framework

Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Sabuj Mallik

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The emerging approaches to sustainable manufacturing are considered to be solution-oriented with the aim of addressing the environmental, economic and social issues holistically. However, the analysis of the interdependencies amongst the three sustainability dimensions has not been fully captured in the literature. In a recent review of approaches to sustainable manufacturing, two categories of techniques are identified: 1) Sustainable Product Development (SPD), and 2) Sustainability Performance Assessment (SPA) techniques. The challenges of the approaches are not only related to the arguments and misconceptions of the relationships between the techniques and sustainable development but also to the inability to capture and integrate the three sustainability dimensions. This requires a clear definition of some of the approaches and a road-map to the development of a holistic approach that supports sustainability decision-making. In this context, eco-innovation, social impact assessment, and life cycle sustainability analysis play an important role. This paper deployed an integrative approach that enabled amalgamation of sustainable manufacturing approaches and the theories of reciprocity and motivation into a holistic simulation-based impact analysis framework. The findings in this research have the potential to guide sustainability analysts to capture the aspects of the three sustainability dimensions into an analytical model. Additionally, the research findings presented can aid the construction of a holistic simulation model of a sustainable manufacturing and support effective decision-making.

Keywords: life cycle sustainability analysis, sustainable manufacturing, sustainability performance assessment, sustainable product development

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Authors: Sina Kazemi, Farshid Torabi, Todd Peterson

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Drilling in shale formations is frequently time-consuming, challenging, and fraught with mechanical failures such as stuck pipes or hole packing off when the cutting removal rate is not sufficient to clean the bottom hole. Crossing the heavy oil shale and sand reservoirs with active shale and microfractures is generally associated with severe fluid losses causing a reduction in the rate of the cuttings removal. These circumstances compromise a well’s integrity and result in a lower rate of penetration (ROP). This study presents collective results of field studies and theoretical analysis conducted on data from South Pars and North Dome in an Iran-Qatar offshore field. Solutions to complications related to drilling in shale formations are proposed through systemically analyzing and applying modeling techniques to select field mud logging data. Field data measurements during actual drilling operations indicate that in a shale formation where the return flow of polymer mud was almost lost in the upper dolomite layer, the performance of hole cleaning and ROP progressively change when higher string rotations are initiated. Likewise, it was observed that this effect minimized the force of rotational torque and improved well integrity in the subsequent casing running. Given similar geologic conditions and drilling operations in reservoirs targeting shale as the producing zone like the Bakken formation within the Williston Basin and Lloydminster, Saskatchewan, a drill bench dynamic modeling simulation was used to simulate borehole cleaning efficiency and mud optimization. The results obtained by altering RPM (string revolution per minute) at the same pump rate and optimized mud properties exhibit a positive correlation with field measurements. The field investigation and developed model in this report show that increasing the speed of string revolution as far as geomechanics and drilling bit conditions permit can minimize the risk of mechanically stuck pipes while reaching a higher than expected ROP in shale formations. Data obtained from modeling and field data analysis, optimized drilling parameters, and hole cleaning procedures are suggested for minimizing the risk of a hole packing off and enhancing well integrity in shale reservoirs. Whereas optimization of ROP at a lower pump rate maintains the wellbore stability, it saves time for the operator while reducing carbon emissions and fatigue of mud motors and power supply engines.

Keywords: ROP, circulating density, drilling parameters, return flow, shale reservoir, well integrity

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Authors: Jana Beresova

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The paper presents a study carried out in 2015-2016 within the national scheme of research - VEGA 1/0106/15 based on theoretical research and empirical verification of the concept of intercultural communicative competence. It focuses on the current conception concerning target languages teaching compatible with the Common European Framework of Reference for Languages: Learning, teaching, assessment. Our research had revealed how the concept of intercultural communicative competence had been perceived by secondary-school teachers of English in Slovakia before they were intensively trained. Intensive workshops were based on the use of both authentic and instructional materials with the goal to support interculturally oriented language teaching aimed at challenging thinking. The former concept that supported the development of the students´ linguistic knowledge and the use of a target language to obtain information about the culture of the country whose language learners were learning was expanded by the meaning-making framework which views language as a typical means by which culture is mediated. The goal of the workshop was to influence English teachers to better understand the concept of intercultural communicative competence, combining theory and practice optimally. The results of the study will be presented and analysed, providing particular recommendations for language teachers and suggesting some changes in the National Educational Programme from which English learners should benefit in their future studies or professional careers.

Keywords: authentic materials, English language teaching, instructional materials, intercultural communicative competence

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Authors: A. Clementking, C. Jothi Venkateswaran

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Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

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Authors: Eyob Messele Sefene, Atinkut Atinafu Yilma

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The highest strength-to-weight ratio criterion has fascinated increasing curiosity in virtually all areas where weight reduction is indispensable. One of the recent advances in manufacturing to achieve this intention endears friction stir welding (FSW). The process is widely used for joining similar and dissimilar non-ferrous materials. In FSW, the mechanical properties of the weld joints are impelled by property-selected process parameters. This paper presents verdicts of optimum process parameters in attempting to attain enhanced mechanical properties of the weld joint. The experiment was conducted on a 5 mm 6061 aluminum alloy sheet. A butt joint configuration was employed. Process parameters, rotational speed, traverse speed or feed rate, axial force, dwell time, tool material and tool profiles were utilized. Process parameters were also optimized, making use of a mixed L18 orthogonal array and the Grey relation analysis method with larger is better quality characteristics. The mechanical properties of the weld joint are examined through the tensile test, hardness test and liquid penetrant test at ambient temperature. ANOVA was conducted in order to investigate the significant process parameters. This research shows that dwell time, rotational speed, tool shape, and traverse speed have become significant, with a joint efficiency of about 82.58%. Nine confirmatory tests are conducted, and the results indicate that the average values of the grey relational grade fall within the 99% confidence interval. Hence the experiment is proven reliable.

Keywords: friction stir welding, optimization, 6061 AA, Taguchi

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Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić

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Prion is a protein substance whose certain form is considered as infectious agent. It is presumed to be the cause of the transmissible spongiform encephalopathies (TSEs). The protein it is composed of, called PrP, can fold in structurally distinct ways. At least one of those 3D structures is transmissible to other prion proteins. Prions can be found in brain tissue of healthy people and have certain biological role. The structure of prions naturally occurring in healthy organisms is marked as PrPc, and the structure of infectious prion is labeled as PrPSc. PrPc may play a role in synaptic plasticity and neuronal development. Also, it may be required for neuronal myelin sheath maintenance, including a role in iron uptake and iron homeostasis. PrPSc can be considered as an environmental pollutant. The main aim of this study was to carry out the molecular modeling and calculation of molecular descriptors (lipophilicity, physico-chemical and topological descriptors) of structurally diverse compounds which can be considered as anti-prion agents. Molecular modeling was conducted applying ChemBio3D Ultra version 12.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The Austin Model 1 (AM-1) was used for full geometry optimization of all structures. The obtained set of molecular descriptors is applied in analysis of similarities and dissimilarities among the tested compounds. This study is an important step in further development of quantitative structure-activity relationship (QSAR) models, which can be used for prediction of anti-prion activity of newly synthesized compounds.

Keywords: chemometrics, molecular modeling, molecular descriptors, prions, QSAR

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Authors: Arunkumar Balamurugan, G. Soundharya Lakshmi, V. Thenmozhi, M. Jegannath, V. R. Sanal Kumar

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Aerodynamics of insects is of topical interest in aeronautical industries due to its wide applications on various types of Micro Air Vehicles (MAVs). Note that the MAVs are having smaller geometric dimensions operate at significantly lower speeds on the order of 10 m/s and their Reynolds numbers range is approximately 1,50,000 or lower. In this paper, numerical study has been carried out to capture the flow physics of a biological inspired Swallowtail Butterfly with fixed wing having twin tail at a flight speed of 10 m/s. Comprehensive numerical simulations have been carried out on swallow butterfly with twin tail flying at a speed of 10 m/s with uniform upper and lower angles of attack in both lateral and longitudinal position for identifying the best wing orientation with better aerodynamic efficiency. Grid system in the computational domain is selected after a detailed grid refinement exercises. Parametric analytical studies have been carried out with different lateral and longitudinal angles of attack for finding the better aerodynamic efficiency at the same flight speed. The results reveal that lift coefficient significantly increases with marginal changes in the longitudinal angle and vice versa. But in the case of drag coefficient the conventional changes have been noticed, viz., drag increases at high longitudinal angles. We observed that the change of twin tail section has a significant impact on the formation of vortices and aerodynamic efficiency of the MAV’s. We concluded that for every lateral angle there is an exact longitudinal orientation for the existence of an aerodynamically efficient flying condition of any MAV. This numerical study is a pointer towards for the design optimization of Twin tail MAVs with flapping wings.

Keywords: aerodynamics of insects, MAV, swallowtail butterfly, twin tail MAV design

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Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines to upgrade power systems into smart grids target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, there are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we introduce a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: anomaly, availability, detection, edge, maintainability, reliability, stochastic

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Authors: S. Hatamikia, A. Biguri, H. Furtado, G. Kronreif, J. Kettenbach, W. Birkfellner

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Nowadays, three dimensional Cone Beam CT (CBCT) has turned into a widespread clinical routine imaging modality for interventional radiology. In conventional CBCT, a circular sourcedetector trajectory is used to acquire a high number of 2D projections in order to reconstruct a 3D volume. However, the accumulated radiation dose due to the repetitive use of CBCT needed for the intraoperative procedure as well as daily pretreatment patient alignment for radiotherapy has become a concern. It is of great importance for both health care providers and patients to decrease the amount of radiation dose required for these interventional images. Thus, it is desirable to find some optimized source-detector trajectories with the reduced number of projections which could therefore lead to dose reduction. In this study we investigate some source-detector trajectories with the optimal arbitrary orientation in the way to maximize performance of the reconstructed image at particular regions of interest. To achieve this approach, we developed a box phantom consisting several small target polytetrafluoroethylene spheres at regular distances through the entire phantom. Each of these spheres serves as a target inside a particular region of interest. We use the 3D Point Spread Function (PSF) as a measure to evaluate the performance of the reconstructed image. We measured the spatial variance in terms of Full-Width-Half-Maximum (FWHM) of the local PSFs each related to a particular target. The lower value of FWHM shows the better spatial resolution of reconstruction results at the target area. One important feature of interventional radiology is that we have very well-known imaging targets as a prior knowledge of patient anatomy (e.g. preoperative CT) is usually available for interventional imaging. Therefore, we use a CT scan from the box phantom as the prior knowledge and consider that as the digital phantom in our simulations to find the optimal trajectory for a specific target. Based on the simulation phase we have the optimal trajectory which can be then applied on the device in real situation. We consider a Philips Allura FD20 Xper C-arm geometry to perform the simulations and real data acquisition. Our experimental results based on both simulation and real data show our proposed optimization scheme has the capacity to find optimized trajectories with minimal number of projections in order to localize the targets. Our results show the proposed optimized trajectories are able to localize the targets as good as a standard circular trajectory while using just 1/3 number of projections. Conclusion: We demonstrate that applying a minimal dedicated set of projections with optimized orientations is sufficient to localize targets, may minimize radiation.

Keywords: CBCT, C-arm, reconstruction, trajectory optimization

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Authors: Koboro J. Selala

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Whilst the system of collective bargaining is well-researched in South Africa, recent studies reveal that this is an area of law and practice that is poorly understood. Despite the growing attention being paid by most scholars to the role of collective bargaining in the labour relations system, only a handful of the studies have considered collective bargaining as a mechanism of dispute resolution. The purpose of this paper is to provide a critical analysis of the current understanding of the right to engage in collective bargaining in South Africa to assess the extent to which collective bargaining is used to resolve labour disputes. The overall objective is to offer a deeper understanding of the role of collective bargaining in dispute resolution process within the South African constitutional labour law context. To this end, the paper examines the applicable legal framework of collective bargaining to address two fundamental questions that are critical to the proper understanding of the functioning of the South African collective labour dispute resolution system. The first concerns the extent to which the current South African legislative framework supports the fundamental labour rights entrenched in the Constitution of the Republic of South Africa. The second addresses the role of trade unions in collective dispute resolution processes and the extent to which they can best utilize collective bargaining to resolve labour disputes. Finally, the paper discusses the general implications of the findings to stimulate further research and to enhance the constitutional development of collective labour rights in South Africa.

Keywords: collective bargaining, constitution, freedom of association, labour relations act

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Authors: Firas Mohamad Al-Sabek

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The Purpose of the paper is to examine the most critical and important factor which will affect the implementation of Total Quality Management (TQM) in the construction industry in the United Arab Emirates. It also examines the most effected Project outcome from implementing TQM. A framework was also proposed depending on the literature studies. The method used in this paper is a quantitative study. A survey with a sample of 60 respondents was created and distributed in a construction company in Abu Dhabi, which includes 15 questions to examine the most critical factor that will affect the implementation of TQM in addition to the most effected project outcome from implementing TQM. The survey showed that management commitment is the most important factor in implementing TQM in a construction company. Also it showed that Project cost is most effected outcome from the implementation of TQM. Management commitment is very important for implementing TQM in any company. If the management loose interest in quality then everyone in the organization will do so. The success of TQM will depend mostly on the top of the pyramid. Also cost is reduced and money is saved when the project team implement TQM. While if no quality measures are present within the team, the project will suffer a commercial failure. Based on literature, more factors can be examined and added to the model. In addition, more construction companies could be surveyed in order to obtain more accurate results. Also this study could be conducted outside the United Arab Emirates for further enchantment.

Keywords: construction project, total quality management, management commitment, cost, theoretical framework

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: S. Gowri, K. Narayanasamy, R. Krishnamurthy

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Plasma spraying, from the point of value engineering, is considered as a cost-effective technique to deposit high performance ceramic coatings on ferrous substrates for use in the aero,automobile,electronics and semiconductor industries. High-performance ceramics such as Alumina, Zirconia, and titania-based ceramics have become a key part of turbine blades,automotive cylinder liners,microelectronic and semiconductor components due to their ability to insulate and distribute heat. However, as the industries continue to advance, improved methods are needed to increase both the flexibility and speed of ceramic processing in these applications. The ceramics mentioned were individually coated on structural steel substrate with NiCr bond coat of 50-70 micron thickness with the final thickness in the range of 150 to 200 microns. Optimal spray parameters were selected based on bond strength and porosity. The 'optimal' processed specimens were super finished by lapping using diamond and green SiC abrasives. Interesting results could be observed as follows: The green SiC could improve the surface finish of lapped surfaces almost as that by diamond in case of alumina and titania based ceramics but the diamond abrasives could improve the surface finish of PSZ better than that by green SiC. The conventional random scratches could be absent in alumina and titania ceramics but in PS those marks were found to be less. However, the flatness accuracy could be improved unto 60 to 85%. The surface finish and geometrical accuracy were measured and modeled. The abrasives in the midrange of their particle size could improve the surface quality faster and better than the particles of size in low and high ranges. From the experimental investigations after lapping process, the optimal lapping time, abrasive size, lapping pressure etc could be evaluated.

Keywords: atmospheric plasma spraying, ceramics, lapping, surface qulaity, optimization

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Authors: Amós García Montaño

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In a democracy, a public policy must be developed within the regulatory framework and considering citizen participation in its planning, design, execution, and evaluation stages, necessary factors to have both legal support and sufficient legitimacy for its operation. However, the complexity and magnitude of certain public problems results in difficulties for the generation of consensus among society members, leading to unstable and unsuccessful scenarios for the exercise of the right to citizen participation and the generation of effective and efficient public policies. This is the case of public policies against corruption, an issue that in Mexico is difficult to define and generates conflicting opinions. To provide a possible solution to this delicate reality, this paper analyzes the principle of reasonableness as a tool for identifying the basic elements that guarantee a fundamental level of the exercise of the right to citizen participation in the fight against corruption, adopting elements of human rights indicator methodologies. In this sense, the relevance of having a legal framework that establishes obligations to incorporate proactive and transversal citizen participation in the matter is observed. It is also noted the need to monitor the operation of various citizen participation mechanisms in the decision-making processes of the institutions involved in the fight and prevention of corruption, which lead to an increase in the improvement of the perception of the citizen role as a relevant actor in this field. It is concluded that the principle of reasonableness is presented as a very useful tool for the identification of basic elements that facilitate the fulfillment of human rights commitments in the field of public policies.

Keywords: anticorruption, public participation, public policies, reasonableness

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modelling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modelling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modelling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.

Keywords: content analysis, factors, integrated waste management system, time series

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Deborah Eric, Abbas Ahmad Khan

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Lead halide perovskites quantum dots have attracted immense scientific and technological interest for successful photovoltaic applications because of their remarkable optoelectronic properties. In this paper, we have simulated CsMAPbI3-xBrx based quantum dots to implement their use in intermediate band solar cells (IBSC). These types of materials exhibit optical and electrical properties distinct from their bulk counterparts due to quantum confinement. The conceptual framework provides a route to analyze the electronic properties of quantum dots. This layer of quantum dots optimizes the position and bandwidth of IB that lies in the forbidden region of the conventional bandgap. A three-dimensional MAPbI3 quantum dot (QD) with geometries including spherical, cubic, and conical has been embedded in the CsPbBr3 matrix. Bound energy wavefunction gives rise to miniband, which results in the formation of IB. If there is more than one miniband, then there is a possibility of having more than one IB. The optimization of QD size results in more IBs in the forbidden region. One band time-independent Schrödinger equation using the effective mass approximation with step potential barrier is solved to compute the electronic states. Envelope function approximation with BenDaniel-Duke boundary condition is used in combination with the Schrödinger equation for the calculation of eigen energies and Eigen energies are solved for the quasi-bound states using an eigenvalue study. The transfer matrix method is used to study the quantum tunneling of MAPbI3 QD through neighbor barriers of CsPbI3. Electronic states are computed using Schrödinger equation with effective mass approximation by considering quantum dot and wetting layer assembly. Results have shown the varying the quantum dot size affects the energy pinning of QD. Changes in the ground, first, second state energies have been observed. The QD is non-zero at the center and decays exponentially to zero at boundaries. Quasi-bound states are characterized by envelope functions. It has been observed that conical quantum dots have maximum ground state energy at a small radius. Increasing the wetting layer thickness exhibits energy signatures similar to bulk material for each QD size.

Keywords: perovskite, intermediate bandgap, quantum dots, miniband formation

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Authors: Pedro J. Rolim-Neto, Leslie R. M. Ferraz, Fabiana L. A. Santos, Pablo A. Ferreira, Ricardo T. L. Maia-Jr., Magaly A. M. Lyra, Danilo A F. Fonte, Salvana P. M. Costa, Amanda C. Q. M. Vieira, Larissa A. Rolim

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Initially developed as an antimalarial agent, hydroxychloroquine (HCQ) sulfate is often used as a slow-acting antirheumatic drug in the treatment of disorders of connective tissue. The United States Pharmacopeia (USP) 37 provides a reversed-phase HPLC method for quantification of HCQ. However, this method was not reproducible, producing asymmetric peaks in a long analysis time. The asymmetry of the peak may cause an incorrect calculation of the concentration of the sample. Furthermore, the analysis time is unacceptable, especially regarding the routine of a pharmaceutical industry. The aiming of this study was to develop a fast, easy and efficient method for quantification of HCQ sulfate by High Performance Liquid Chromatography (HPLC) based on the Quality by Design (QbD) methodology. This method was optimized in terms of peak symmetry using the surface area graphic as the Design of Experiments (DoE) and the tailing factor (TF) as an indicator to the Design Space (DS). The reference method used was that described at USP 37 to the quantification of the drug. For the optimized method, was proposed a 33 factorial design, based on the QbD concepts. The DS was created with the TF (in a range between 0.98 and 1.2) in order to demonstrate the ideal analytical conditions. Changes were made in the composition of the USP mobile-phase (USP-MP): USP-MP: Methanol (90:10 v/v, 80:20 v/v and 70:30 v/v), in the flow (0.8, 1.0 and 1.2 mL) and in the oven temperature (30, 35, and 40ºC). The USP method allowed the quantification of drug in a long time (40-50 minutes). In addition, the method uses a high flow rate (1,5 mL.min-1) which increases the consumption of expensive solvents HPLC grade. The main problem observed was the TF value (1,8) that would be accepted if the drug was not a racemic mixture, since the co-elution of the isomers can become an unreliable peak integration. Therefore, the optimization was suggested in order to reduce the analysis time, aiming a better peak resolution and TF. For the optimization method, by the analysis of the surface-response plot it was possible to confirm the ideal setting analytical condition: 45 °C, 0,8 mL.min-1 and 80:20 USP-MP: Methanol. The optimized HPLC method enabled the quantification of HCQ sulfate, with a peak of high resolution, showing a TF value of 1,17. This promotes good co-elution of isomers of the HCQ, ensuring an accurate quantification of the raw material as racemic mixture. This method also proved to be 18 times faster, approximately, compared to the reference method, using a lower flow rate, reducing even more the consumption of the solvents and, consequently, the analysis cost. Thus, an analytical method for the quantification of HCQ sulfate was optimized using QbD methodology. This method proved to be faster and more efficient than the USP method, regarding the retention time and, especially, the peak resolution. The higher resolution in the chromatogram peaks supports the implementation of the method for quantification of the drug as racemic mixture, not requiring the separation of isomers.

Keywords: analytical method, hydroxychloroquine sulfate, quality by design, surface area graphic

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Authors: Alex Hughes

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Patients with advanced heart failure develop specific palliative care needs due to the progressive symptom burden and unpredictable disease trajectory. NICE guidance advises that palliative care should be provided to patients with both cancer and non-cancer conditions as and when required. However, there is some way to go before this guidance is consistently and effectively implemented nationwide in conditions such as heart failure. The Ambitions for Palliative and End of Life Care: A national framework for local action in England provides a set of foundations and ambitions which outline a vision for what high-quality palliative and end-of-life care look like in England. This poster aims to critically consider how to improve access to palliative care for heart failure patients in England by analysing the foundations taken from this framework to generate specific recommendations using Soft Systems Methodology (SSM). The eight foundations analysed are: ‘Personalised care planning’, ‘Shared records’, ‘Evidence and information’, ‘Involving, supporting and caring for those important to the dying Person’, ‘Education and training’, ‘24/7 access’, ‘Co-design’ and ‘Leadership.’ A number of specific recommendations have been generated which highlight a need to close the evidence-policy gap and implement policy with sufficient evidence. These recommendations, alongside the creation of an evidence-based national strategy for palliative care and heart failure, should improve access to palliative care for heart failure patients in England. Once implemented, it will be necessary to evaluate the effect of these proposals to understand if access to palliative care for heart failure patients actually improves.

Keywords: access, health systems, heart failure, palliative care

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Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

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Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

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Authors: Nora Mohammed Rehan Hussien

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Cities all over the world face daunting urban challenges that have increased in scope in recent years. The biggest challenge includes issues of urban planning, housing, safety aspects, scarcity of land for development and traffic congestion. So every city in the world aspires to adopt the strategy of ‘Livable City’ which guarantees the cities urbanization manner that preserves the environment, and achieve the greatest benefit from the resources and achieve a good standard of living. Essentially, a livable city should possess basic yet unique attributes to welcome people from all strata of society without marginalizing any particular group. Most of these cities began to move towards sustainability and livability to enhance quality and performance of urban services, to reduce costs and resources consumption, to engage more affectivity and actively with its citizens, and to describe the quality of life and the characteristics of cities that make them livable. From here came the idea of the research which is creating ‘A framework of livable and sustainable city’ as a sustainable approach that must follow to achieve the principle of sustainable livability. From this point of view the research deals with one of the most successful case studies all over the world in’ livable cities system’ (Vienna) to know how to explore and understand the issues and challenges in becoming a full- livable and creative city through analyzing the criteria, principles and strategy of livable city then deducing the framework towards this concept. Finally, it suggests a set of recommendations help for applying the concept of livable city.

Keywords: quality of life, livability & livable city, sustainability, sustainable city

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Authors: Guangyan Chen

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This study examined Chinese teachers’ perceptions of assessing U.S. college students’ L2 (second language) Chinese oral performances at different levels. Ten oral performances were videotaped from which three were chosen as samples to represent three different proficiency levels based on professionals’ judgments according to the ACTFL proficiency guidelines. The three samples were shown to L2 Chinese teachers who completed questionnaires about their assessments for each speech sample. In total, 104 L2 Chinese teachers responded to each of the three samples. The Exploratory Factor Analyses (EFA) of the teachers’ responses revealed three similar rating criteria patterns for assessing the three levels of oral performances. The teachers’ responses to Samples 2 and 3 revealed five rating criteria: Global proficiency, Chinese conceptual framework, content richness, communication appropriateness, and communication clarity. The teachers’ responses to Sample 1 revealed four rating criteria: global proficiency, Chinese conceptual framework, communication appropriateness/content richness, and communication clarity. However, the analyses of variance (ANOVAs) revealed that the proficiency levels of the three oral performances differed significantly across all rating criteria. Therefore, the data suggests that L2 classroom teachers could use the similar rating criteria pattern to assess college-level L2 Chinese students’ oral performances at different proficiency levels.

Keywords: language assessment, L2 Chinese, oral performance, rating criteria

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Authors: Amna Tariq Shah

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Amid the pandemic, the contemporary landscape has experienced accelerated growth in small business activities and an expanding digital marketplace, further exacerbating the issue of non-compliance among self-employed individuals through aggressive tax planning and evasion. This research seeks to address these challenges by developing strategic tax policies that promote voluntary compliance and improve taxpayer facilitation. The study employs the innovative MINDSPACE framework to examine three psychosocial factors—tax communication, tax literacy, and shaming—to optimize policy responses, address administrative shortcomings, and ensure adequate revenue collection for public goods and services. Preliminary findings suggest that incomprehensible communication from tax authorities drives individuals to seek alternative, potentially biased sources of tax information, thereby exacerbating non-compliance. Furthermore, the study reveals low tax literacy among Australian and Pakistani respondents, with many struggling to navigate complex tax processes and comprehend tax laws. Consequently, policy recommendations include simplifying tax return filing and enhancing pre-populated tax returns. In terms of shaming, the research indicates that Australians, being an individualistic society, may not respond well to shaming techniques due to privacy concerns. In contrast, Pakistanis, as a collectivistic society, may be more receptive to naming and shaming approaches. The study employs a mixed-method approach, utilizing interviews and surveys to analyze the issue in both jurisdictions. The use of mixed methods allows for a more comprehensive understanding of tax compliance behavior, combining the depth of qualitative insights with the generalizability of quantitative data, ultimately leading to more robust and well-informed policy recommendations. By examining evidence from opposite jurisdictions, namely a developed country (Australia) and a developing country (Pakistan), the study's applicability is enhanced, providing perspectives from two disparate contexts that offer insights from opposite ends of the economic, cultural, and social spectra. The non-comparative case study methodology offers valuable insights into human behavior, which can be applied to other jurisdictions as well. The application of the MINDSPACE framework in this research is particularly significant, as it introduces a novel approach to tax compliance behavior analysis. By integrating insights from behavioral economics, the framework enables a comprehensive understanding of the psychological and social factors influencing taxpayer decision-making, facilitating the development of targeted and effective policy interventions. This research carries substantial importance as it addresses critical challenges in tax compliance and administration, with far-reaching implications for revenue collection and the provision of public goods and services. By investigating the psychosocial factors that influence taxpayer behavior and utilizing the MINDSPACE framework, the study contributes invaluable insights to the field of tax policy. These insights can inform policymakers and tax administrators in developing more effective tax policies that enhance taxpayer facilitation, address administrative obstacles, promote a more equitable and efficient tax system, and foster voluntary compliance, ultimately strengthening the financial foundation of governments and communities.

Keywords: individual tax compliance behavior, psychosocial factors, tax non-compliance, tax policy

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Authors: Arianna Nativio, Zoran Kapelan, Jan Peter van der Hoek

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Bio-composite materials are becoming increasingly popular in various applications, such as the automotive industry. Usually, bio-composite materials are made from natural resources recovered from plants, now, a new type of bio-composite material has begun to be produced in the Netherlands. This material is made from resources recovered from drinking water treatments (calcite), wastewater treatment (cellulose), and material from surface water management (aquatic plants). Surface water, raw drinking water, and wastewater can be contaminated with pathogens and chemical compounds. Therefore, it would be valuable to develop a framework to assess, monitor, and control the potential risks. Indeed, the goal is to define the major risks in terms of human health, quality of materials, and environment associated with the production and application of these new materials. This study describes the general risk assessment framework, starting with a qualitative risk assessment. The qualitative risk analysis was carried out by using the HAZOP methodology for the hazard identification phase. The HAZOP methodology is logical and structured and able to identify the hazards in the first stage of the design when hazards and associated risks are not well known. The identified hazards were analyzed to define the potential associated risks, and then these were evaluated by using the qualitative Event Tree Analysis. ETA is a logical methodology used to define the consequences for a specific hazardous incidents, evaluating the failure modes of safety barriers and dangerous intermediate events that lead to the final scenario (risk). This paper shows the effectiveness of combining of HAZOP and qualitative ETA methodologies for hazard identification and risk mapping. Then, key risks were identified, and a quantitative framework was developed based on the type of risks identified, such as QMRA and QCRA. These two models were applied to assess human health risks due to the presence of pathogens and chemical compounds such as heavy metals into the bio-composite materials. Thus, due to these contaminations, the bio-composite product, during its application, might release toxic substances into the environment leading to a negative environmental impact. Therefore, leaching tests are going to be planned to simulate the application of these materials into the environment and evaluate the potential leaching of inorganic substances, assessing environmental risk.

Keywords: bio-composite, risk assessment, water reuse, resource recovery

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Soumya Bhattacharjya, Avinandan Sahoo, Gaurav Datta

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Wind fragility analysis of chimney is often carried out disregarding temperature effect. However, the combined effect of wind and temperature is the most critical limit state for chimney design. Hence, in the present paper, an efficient fragility analysis for concrete chimney is explored under combined wind and temperature effect. Wind time histories are generated by Davenports Power Spectral Density Function and using Weighed Amplitude Wave Superposition Technique. Fragility analysis is often carried out in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, in the present paper, an efficient adaptive metamodelling technique is adopted to judiciously approximate limit state function, which will be subsequently used in the simulation framework. This will save substantial computational time and make the approach computationally efficient. Uncertainty in wind speed, wind load related parameters, and resistance-related parameters is considered. The results by the full simulation approach, conventional metamodelling approach and proposed adaptive metamodelling approach will be compared. Effect of disregarding temperature in wind fragility analysis will be highlighted.

Keywords: adaptive metamodelling technique, concrete chimney, fragility analysis, stochastic extreme wind load, temperature effect

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Authors: Fatemeh Torabi, Jamal El-Den, Narumon Sriratanviriyakul

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Perpetual changes in the workplace and daily business activities bring a need for imbedding organizational knowledge sharing within the organizations’ culture, routines and processes. Organizations should adapt to the changing in the environment in order to survive. Accordingly, the management should promote a knowledge sharing culture which might result in knowledge accumulation, hence better response to these changing environmental conditions. Researchers in the field of strategy and marketing stressed that employees’, as well as the overall performance of the organization, would improve as a result of implementing a knowledge-oriented culture. The research investigated the significant impact of knowledge sharing on market response and the competitiveness of organizations. A knowledge sharing framework was developed based on current literary frameworks with additional constructs such as employees’ learning commitments, experiences and prior knowledge. Linear regression was used to analyze the relationships among dependent and independent variables. The research’s results indicated strong positive correlation between the dependent and independent variables, especially in organizational market sharing. We anticipate that this correlation would improve organizational knowledge sharing related practices and the associated knowledge entities. The research posits the introduced framework could be a solid ground for further investigations on how some organizational factors would influence the organization’s response to the market as well as on competitiveness. Final results support all hypotheses. Finding of this research show that knowledge sharing intention had the significant and positive effect on market response and competitiveness of organizations.

Keywords: knowledge management, knowledge sharing, market response, organizational competitiveness

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Authors: Sylvie Michel, François Cocula

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Digital agriculture is an approach that exploits information and communication technologies. These encompass data acquisition tools like mobile applications, satellites, sensors, connected devices, and smartphones. Additionally, it involves transfer and storage technologies such as 3G/4G coverage, low-bandwidth terrestrial or satellite networks, and cloud-based systems. Furthermore, embedded or remote processing technologies, including drones and robots for process automation, along with high-speed communication networks accessible through supercomputers, are integral components of this approach. While farm-level adoption studies regarding digital agricultural technologies have emerged in recent years, they remain relatively limited in comparison to other agricultural practices. To bridge this gap, this study delves into understanding farmers' intention to adopt digital tools, employing the technology, organization, environment framework. A qualitative research design encompassed semi-structured interviews, totaling fifteen in number, conducted with key stakeholders both prior to and following the 2020-2021 COVID-19 lockdowns in France. Subsequently, the interview transcripts underwent thorough thematic content analysis, and the data and verbatim were triangulated for validation. A coding process aimed to systematically organize the data, ensuring an orderly and structured classification. Our research extends its contribution by delineating sub-dimensions within each primary dimension. A total of nine sub-dimensions were identified, categorized as follows: perceived usefulness for communication, perceived usefulness for productivity, and perceived ease of use constitute the first dimension; technological resources, financial resources, and human capabilities constitute the second dimension, while market pressure, institutional pressure, and the COVID-19 situation constitute the third dimension. Furthermore, this analysis enriches the TOE framework by incorporating entrepreneurial orientation as a moderating variable. Managerial orientation emerges as a pivotal factor influencing adoption intention, with producers acknowledging the significance of utilizing digital sales support tools to combat "greenwashing" and elevate their overall brand image. Specifically, it illustrates that producers recognize the potential of digital tools in time-saving and streamlining sales processes, leading to heightened productivity. Moreover, it highlights that the intent to adopt digital sales support tools is influenced by a market mimicry effect. Additionally, it demonstrates a negative association between the intent to adopt these tools and the pressure exerted by institutional partners. Finally, this research establishes a positive link between the intent to adopt digital sales support tools and economic fluctuations, notably during the COVID-19 pandemic. The adoption of sales support tools in agriculture is a multifaceted challenge encompassing three dimensions and nine sub-dimensions. The research delves into the adoption of digital farming technologies at the farm level through the TOE framework. This analysis provides significant insights beneficial for policymakers, stakeholders, and farmers. These insights are instrumental in making informed decisions to facilitate a successful digital transition in agriculture, effectively addressing sector-specific challenges.

Keywords: adoption, digital agriculture, e-commerce, TOE framework

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Authors: Suleman Ibrahim

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Purpose: The research is seeking people's perceptions on cybercrime issues, rather than their knowledge of the facts. Unlike the Tripartite Cybercrime Framework (TCF), the binary models are ill-equipped to differentiate between cyber fraud (a socioeconomic crime) and cyber bullying or cyber stalking (psychosocial cybercrimes). Whilst the binary categories suggested that digital crimes are dichotomized: (i.e. cyber-enabled and cyber-dependent), the TCF, recently proposed, argued that cybercrimes can be conceptualized into three groups: socioeconomic, psychosocial and geopolitical. Concomitantly, as regards to the experience/perceptions of cybercrime, the TCF’s claim requires substantiation beyond its theoretical realm. Approach/Methodology: This scholar endeavor framed with the TCF, deploys a survey method to explore the experience of cybercrime across gender. Drawing from over 400 participants in the UK, this study aimed to contrast the differential perceptions/experiences of socioeconomic cybercrime (e.g. cyber fraud) and psychological cybercrime (e.g. cyber bullying and cyber stalking) across gender. Findings: The results revealed that cyber stalking was rated as least serious of the different digital crime categories. Further revealed that female participants judged all types of cybercrimes as more serious than male participants, with the exception of socioeconomic cybercrime – cyber fraud. This distinction helps to emphasize that gender cultures and nuances not only apply both online and offline, it emphasized the utilitarian value of the TCF. Originality: Unlike existing data, this study has contrasted the differential perceptions and experience of socioeconomic and psychosocial cybercrimes with more refined variables.

Keywords: gender variations, psychosocial cybercrime, socioeconomic cybercrime, tripartite cybercrime framework

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