Search results for: thermal performance

Authors: Caroline Rocco, Feyza Karasu, Céline Croutxé-Barghorn, Xavier Allonas, Maxime Lecompère, Gérard Riess, Yujing Zhang, Catarina Esteves, Leendert van der Ven, Rolf van Benthem Gijsbertus de With

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Acrylates are widely used in UV-curing technology. Their high reactivity can, however, limit their conversion due to early vitrification. In addition, the free radical photopolymerization is known to be sensitive to oxygen inhibition leading to tacky surfaces. Although epoxides can lead to full polymerization, they are sensitive to humidity and exhibit low polymerization rate. To overcome the intrinsic limitations of both classes of monomers, Interpenetrating Polymer Networks (IPNs) can be synthesized. They consist of at least two cross linked polymers which are permanently entangled. They can be achieved under thermal and/or light induced polymerization in one or two steps approach. IPNs can display homogeneous to heterogeneous morphologies with various degrees of phase separation strongly linked to the monomer miscibility and also synthesis parameters. In this presentation, we synthesize UV-cured methacrylate - epoxide based IPNs with different chemical compositions in order to get a better understanding of their formation and phase separation. Miscibility before and during the photopolymerization, reaction kinetics, as well as mechanical properties and morphology have been investigated. The key parameters controlling the morphology and the phase separation, namely monomer miscibility and synthesis parameters have been identified. By monitoring the stiffness changes on the film surface, atomic force acoustic microscopy (AFAM) gave, in conjunction with polymerization kinetic profiles and thermomechanical properties, explanations and corroborated the miscibility predictions. When varying the methacrylate / epoxide ratio, it was possible to move from a miscible and highly-interpenetrated IPN to a totally immiscible and phase-separated one.

Keywords: investigation of properties and morphology, kinetics, phase separation, UV-cured IPNs

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Authors: Abenezer Nigussie

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Strategic control practice is a critical exercise, as it provides a sturdy influence towards firms or production partners to achieve the full implementation of effective predetermined plans. The importance of strategic control in a company is often measured by observing the relationship between strategic management and organizational performance. The conventional philosophy of strategic control in academia and the industry places significant emphasis on the ability to plan and execute initiatives. In contrast, the same emphasis on strategic management has received less attention in the housing industry. Although the pressures of project performance can often obscure the wider social, economic, and professional context in which strategic management is undertaken, it is these broad contextual areas that make strategic control a vital issue for construction businesses. Rapidly changing social and technological issues are creating an informed environment that will appear very different in the coming decades from what is experienced in today’s companies. Construction project activity is not adequately led by strategic management tools; projects are mostly executed through simple plans and schedules. The issues that this thesis addresses and solves involve the successful accompaniment of the construction project process through these strategic management tools. The second important aspect is an evaluation of project activity, which is mostly done through simple economic and technical valuation. However, during this research, effective strategic management tools are evaluated and suggested for the assessment of project activities. The research introduces a study of the current strategic management practices of construction companies and also presents the concept of strategic management and the areas that companies need to address to compete in the global market. A summary of an industry survey is documented along with the historical research that prompted the investigation of these topics with a focus on the implementation of tools. Strategic management is a concept that concerns making decisions and taking corrective actions to achieve the future goals and objectives of a company. The objective of this paper is to review the practice of strategic management in construction companies. Questionnaires were distributed to major construction companies listed under categories of each project capable of specifying the complete expression of strategic management tools. Findings of the research showed that the majority of development companies practice strategic management tools in the process and implementation of each tool.

Keywords: strategic management, management, analysis, project management

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Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger

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Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.

Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration

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Authors: Anass Hsissi, Hakim Allali, Abdelmajid Hajami

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This article presents the results of a doctoral research which aims to integrate metacognitive dimension in the design of human learning computing environments (ILE). We conducted a detailed study on the relationship between metacognitive processes and learning, specifically their positive impact on the performance of learners in the area of reading comprehension. Our contribution is to implement methods, using an intelligent agent based on BDI paradigm to ensure intelligent and reliable support for low readers, in order to encourage regulation and a conscious and rational use of their metacognitive abilities.

Keywords: metacognition, text comprehension EIAH, autoregulation, BDI agent

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Authors: Parastou Kharazmi

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Degradation of building materials particularly pipelines causes environmental damage during the renovation or replacement, disturbance for people living in the buildings, is time-consuming and last but not least is very costly. Rehabilitation by composite materials is a solution for renovation of degraded pipeline in residential buildings and any other structures which is less costly, faster and causes less damage to the environment. This study provides a brief state of technology, methods, and materials which are being used in Nordic and some other European countries and an investigation on the performance of the relined pipes after they have been in working condition. The investigation was carried by different analyses in laboratory as well as numerous field inspections.

Keywords: buildings, pipeline, rehabilitation, polymer materials

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Authors: Jularat Chumnaul

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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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Authors: Nandu C. Nair, Kamal Bijlani

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This paper proposes a concept-based assessment to track the performance of the students. The idea behind this approach is to map the exam questions with the concepts learned in the course. So at the end of the course, each student will know how well he learned each concept. This system will give a self assessment for the students as well as instructor. By analyzing the score of all students, instructor can decide some concepts need to be teaching again or not. The system’s efficiency is proved using three courses from M-tech program in E-Learning technologies and results show that the concept-wise assessment improved the score in final exam of majority students on various courses.

Keywords: assessment, concept, examination, question, score

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Authors: Ali M. EL-Soll

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Physical properties of Sarir waxy crude oil was investigated, pour-point was determined using ASTM D-79 procedure, paraffin content and carbon number distribution of the paraffin was determined using gas liquid Chromatography(GLC), polymeric additives were prepared and their structures were confirmed using IR spectrophotometer. The molecular weight and molecular weigh distribution of these additives were determined by gel permeation chromatography (GPC). the performance of the synthesized additives as pour-point depressants was evaluated, for the mentioned crude oil.

Keywords: sarir, waxy, crude, pour point, depressants

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Authors: Munawar Malik, Muntaha Ahmad, Khalil Ullah Khan

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Linguistic abilities in students with hearing impairment yet remain a concern for educationists. The emerging technological support and provisions in recent era vows to have addressed the situation and claims significant contribution in terms of linguistic repertoire. Being a descriptive and quantitative paradigm of study, the purpose of this research set forth was to assess linguistic competencies of students with hearing impairment in English language. The goals were further broken down to identify level of reading abilities in the subject population. The population involved students with HI studying at higher secondary level in Lahore. Simple random sampling technique was used to choose a sample of fifty students. A purposive curriculum-based assessment was designed in line with accelerated learning program by Punjab Government, to assess Linguistic competence among the sample. Further to it, an Informal Reading Inventory (IRI) corresponding to reading levels was also developed by researchers duly validated and piloted before the final use. Descriptive and inferential statistics were utilized to reach to the findings. Spearman’s correlation was used to find out relationship between degree of hearing loss, grade level, gender and type of amplification device. Independent sample t-test was used to compare means among groups. Major findings of the study revealed that students with hearing impairment exhibit significant deviation from the mean scores when compared in terms of grades, severity and amplification device. The study divulged that respective students with HI have yet failed to qualify an independent level of reading according to their grades as majority falls at frustration level of word recognition and passage comprehension. The poorer performance can be attributed to lower linguistic competence as it shows in the frustration levels of reading, writing and comprehension. The correlation analysis did reflect an improved performance grade wise, however scores could only correspond to frustration level and independent levels was never achieved. Reported achievements at instructional level of subject population may further to linguistic skills if practiced purposively.

Keywords: linguistic competence, hearing impairment, reading levels, educationist

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Authors: Burcu Uçan

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The certification approach differs in civil and military projects in aviation. Sets of criteria and standards created by airworthiness authorities for the determination of certification basis are distinct. While the civil standards are more understandable and clear because of not only include detailed specifications but also the help of guidance materials such as Advisory Circular, military criteria do not provide this level of guidance. Therefore, specifications that are more negotiable and sometimes more difficult to reconcile arise for the certification basis of a military aircraft. This study investigates a method of how to develop a military specification set by taking advantage of civil standards, regarding the European Military Airworthiness Criteria (EMACC) that establishes the airworthiness criteria for aircraft systems. Airworthiness Certification Criteria (MIL-HDBK-516C) is a handbook published for guidance that contains qualitative evaluation for military aircrafts meanwhile Certification Specifications (CS-29) is published for civil aircrafts by European Union Aviation Safety Agency (EASA). This method intends to compare and contrast specifications that MIL-HDBK-516C and CS-29 contain within the scope of Human Factors. Human Factors supports human performance and aims to improve system performance by encompassing knowledge from a range of scientific disciplines. Human Factors focuses on how people perform their tasks and reduce the risk of an accident occurring due to human physical and cognitive limitations. Hence, regardless of whether the project is civil or military, the specifications must be guided at a certain level by taking into account human limits. This study presents an advisory method for this purpose. The method in this study develops a solution for the military certification process by identifying the CS requirement corresponding to the criteria in the MIL-HDBK-516C by means of EMACC. Thus, it eases understanding the expectations of the criteria and establishing derived requirements. As a result of this method, it may not always be preferred to derive new requirements. Instead, it is possible to add remarks to make the expectancy of the criteria and required verification methods more comprehensible for all stakeholders. This study contributes to creating a certification basis for military aircraft, which is difficult and takes plenty of time for stakeholders to agree due to gray areas in the certification process for military aircrafts.

Keywords: human factors, certification, aerospace, requirement

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Chante Van Tonder, Bart Bossink, Chris Schachtebeck, Cecile Nieuwenhuizen

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Small and Medium-Sized Enterprises (SMEs) play a key role in national economies around the world, being contributors to economic and social well-being. Due to this, the success, growth and competitiveness of SMEs are critical. However, there are many factors that undermine this, such as resource constraints, poor information communication infrastructure (ICT), skills shortages and poor management. The Fourth Industrial Revolution offers new tools and opportunities such as digital transformation and business model innovation (BMI) to the SME sector to enhance its competitiveness. Adopting and leveraging digital technologies such as cloud, mobile technologies, big data and analytics can significantly improve business efficiencies, value proposition and customer experiences. Digital transformation can contribute to the growth and competitiveness of SMEs. However, SMEs are lagging behind in the participation of digital transformation. Extant research lacks conceptual and empirical research on how digital transformation drives BMI and the impact it has on the growth and competitiveness of SMEs. The purpose of the study is, therefore, to close this gap by developing and empirically validating a conceptual model to determine if SMEs are achieving BMI through digital transformation and how this is impacting the growth, competitiveness and overall business performance. An empirical study is being conducted on 300 SMEs, consisting of 150 South-African and 150 Dutch SMEs, to achieve this purpose. Structural equation modeling is used, since it is a multivariate statistical analysis technique that is used to analyse structural relationships and is a suitable research method to test the hypotheses in the model. Empirical research is needed to gather more insight into how and if SMEs are digitally transformed and how BMI can be driven through digital transformation. The findings of this study can be used by SME business owners, managers and employees at all levels. The findings will indicate if digital transformation can indeed impact the growth, competitiveness and overall performance of an SME, reiterating the importance and potential benefits of adopting digital technologies. In addition, the findings will also exhibit how BMI can be achieved in light of digital transformation. This study contributes to the body of knowledge in a highly relevant and important topic in management studies by analysing the impact of digital transformation on BMI on a large number of SMEs that are distinctly different in economic and cultural factors

Keywords: business models, business model innovation, digital transformation, SMEs

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Authors: Dehni Abdellatif, Lounis Mourad

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The new approach of applied spatial geostatistics in materials sciences, agriculture accuracy, agricultural statistics, permitted an apprehension of managing and monitoring the water and groundwater qualities in a relationship with salt-affected soil. The anterior experiences concerning data acquisition, spatial-preparation studies on optical and multispectral data has facilitated the integration of correction models of electrical conductivity related with soils temperature (horizons of soils). For tomography apprehension, this physical parameter has been extracted from calibration of the thermal band (LANDSAT ETM+6) with a radiometric correction. Our study area is Oran region (Northern West of Algeria). Different spectral indices are determined such as salinity and sodicity index, the Combined Spectral Reflectance Index (CSRI), Normalized Difference Vegetation Index (NDVI), emissivity, Albedo, and Sodium Adsorption Ratio (SAR). The approach of geostatistical modeling of electrical conductivity (salinity), appears to be a useful decision support system for estimating corrected electrical resistivity related to the temperature of surface soils, according to the conversion models by substitution, the reference temperature at 25°C (where hydrochemical data are collected with this constraint). The Brightness temperatures extracted from satellite reflectance (LANDSAT ETM+) are used in consistency models to estimate electrical resistivity. The confusions that arise from the effects of salt stress and water stress removed followed by seasonal application of the geostatistical analysis in Geographic Information System (GIS) techniques investigation and monitoring the variation of the electrical conductivity in the alluvial aquifer of Es-Sénia for the salt-affected soil.

Keywords: geostatistical modelling, landsat, brightness temperature, conductivity

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Authors: Anna Strakowska, Marian Zaborski

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This abstract focuses an overview of the methods used to create self-healing silicone composites. It has been shown how incorporating of polyhedral oligomeric silsesquioxanes (POSS) molecules with acid and basic groups to silicone rubber affects the barrier properties, mechanical properties in room and reduced temperature or the influence on relaxation rates of the methylvinylsilicone rubber vulcanizates. Moreover, the presence of silsesquioxanes, their content and the way of composites preparing affect the amount of ionic bonds, as indicated by dynamic - mechanical thermal analysis (DMTA) as well as measurements of equilibrium swelling in toluene. The aim of this work was to study the influence of concentration and different functional groups types selected silsesquioxanes compounds on self-healing effect of silicone rubber and obtain elastomers with good barrier and mechanical properties. Composites based on the methylvinylsilicone rubber with fumed silica as the fillers were manufactured and studied. To obtain self-healing effect various silsesquioxanes with amino and acid groups were used. Every tested sample demonstrated the ability to the self-treatment. The most significant effect was observed for system containing amic-acid isobytyl POSS/ aminopropylisobutyl POSS. Composite with this silsesquioxanes was exhibited the best improvement of gas permeability after heal. Moreover, the addition of POSS with acid and basic groups clearly affects the mechanical properties of the vulcanizates. The most significant effect was observed for the composite material consisting of amic-acid isobytyl POSS / aminoethylaminopropylisobutyl POSS, which tensile strength was even greater than the reference vulcanizate with fumed silica. The development of autonomous self-healing materials could have an enormous influence on all industry branches from motorization to power industry. Self-repairing materials would have a massive impact on lengthening product lifetimes, increasing safety, and lowering product costs by reducing maintenance requirements.

Keywords: barrier properties, mechanical properties, POSS, self-healing composites

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Authors: Sandrine Cardinal, Jean-Marc Pelletier, Guang Xie, Florian Mercier, Florent Delmas

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Bulk metallic glasses exhibit several superior properties, compared to their corresponding crystalline counterpart, such as high strength, high elastic limit or good corrosion resistance. Therefore they can be considered as good candidates for structural applications in many sectors. However, they are generally brittle and do not exhibit plastic deformation at room temperature. These materials are mainly obtained by rapid cooling from a liquid state to prevent crystallization, which limits their size. To overcome these two drawbacks: fragility and limited dimensions, composite metallic glass matrix reinforced by a second phase whose role is to slow crack growth are developed. Concerning the limited size of the pieces, the proposed solution is to get the material from amorphous powders by densifying under load. In this study, Cu50Zr45Al5 bulk metallic glassy matrix composites (MGMCs) containing different volume fraction (Vf) of Zr crystalline particles were manufactured by spark plasma sintering (SPS). Microstructure, thermal stability and mechanical properties of the MGMCs were investigated. Matrix of the composites remains a fully amorphous phase after consolidation at 420°C under 600 MPa. A good dispersion of the particles in the glassy matrix is obtained. Results show that the compressive strength decreases with Vf : 1670 MPa (Vf=0%) to 1300MPa (Vf=30%), the elastic modulus decreases but only slighty respectively 97.3GPa and 94.5 GPa and plasticity is improved from 0 to 4%. Fractographic investigation indicates a good bonding between amorphous and crystalline particles. In conclusion, present study has demonstrated that SPS method is useful for the synthesis of the bulk glassy composites. Large controlled microstructure specimens with interesting ductility can be obtained compared with others methods.

Keywords: composite, mechanical properties, metallic glasses, spark plasma sintering

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Authors: Akiyoshi Wakatani

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This paper describes the Message Passing Interface (MPI) implementation of ADETRAN language, and its evaluation on SX-ACE supercomputers. ADETRAN language includes pdo statement that specifies the data distribution and parallel computations and pass statement that specifies the redistribution of arrays. Two methods for implementation of pass statement are discussed and the performance evaluation using Splitting-Up CG method is presented. The effectiveness of the parallelization is evaluated and the advantage of one dimensional distribution is empirically confirmed by using the results of experiments.

Keywords: iterative methods, array redistribution, translator, distributed memory

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Authors: Shukri Dughman, Anthony Rossiter

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This paper builds on earlier work which demonstrated that Model Predictive Control (MPC) may give a poor choice of default feed forward compensator. By first demonstrating the impact of future information of target changes on the performance, this paper proposes a pragmatic method for identifying the amount of future information on the target that can be utilised effectively in both finite and infinite horizon algorithms. Numerical illustrations in MATLAB give evidence of the efficacy of the proposal.

Keywords: model predictive control, tracking control, advance knowledge, feed forward

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Authors: Lamin B Ceesay, Cecilia Rossignoli

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Inter-organizational collaboration is a growing phenomenon in both research and practice. The partnership between organizations enables firms to leverage external resources, experiences, and technology that lie with other firms. This collaborative practice is a source of improved business model performance, technological advancement, and increased competitive advantage for firms. However, the competitive intents, and even diverse institutional logics of firms, make inter-firm innovation-based partnership even more complex, and its governance more challenging. The purpose of this paper is to present a systematic review of research linking the inter-organizational relationship of firms with their innovation practice and specify the different project management issues and gaps addressed in previous research. To do this, we employed a systematic review of the literature on inter-organizational innovation using two complementary scholarly databases - ScienceDirect and Web of Science (WoS). Article scoping relies on the combination of keywords based on similar terms used in the literature:(1) inter-organizational relationship, (2) business network, (3) inter-firm project, and (4) innovation network. These searches were conducted in the title, abstract, and keywords of conceptual and empirical research papers done in English. Our search covers between 2010 to 2019. We applied several exclusion criteria including Papers published outside the years under the review, papers in a language other than English, papers neither listed in WoS nor ScienceDirect and papers that are not sharply related to the inter-organizational innovation-based partnership were removed. After all relevant search criteria were applied, a final list of 84 papers constitutes the data for this review. Our review revealed an increasing evolution of inter-organizational relationship research during the period under the review. The descriptive analysis of papers according to Journal outlets finds that International Journal of Project Management (IJPM), Journal of Industrial Marketing, Journal of Business Research (JBR), etc. are the leading journal outlets for research in the inter-organizational innovation project. The review also finds that Qualitative methods and quantitative approaches respectively are the leading research methods adopted by scholars in the field. However, literature review and conceptual papers constitute the least in the field. During the content analysis of the selected papers, we read the content of each paper and found that the selected papers try to address one of the three phenomena in inter-organizational innovation research: (1) project antecedents; (2) project management and (3) project performance outcomes. We found that these categories are not mutually exclusive, but rather interdependent. This categorization also helped us to organize the fragmented literature in the field. While a significant percentage of the literature discussed project management issues, we found fewer extant literature on project antecedents and performance. As a result of this, we organized the future research agenda addressed in several papers by linking them with the under-researched themes in the field, thus providing great potential to advance future research agenda especially, in the under-researched themes in the field. Finally, our paper reveals that research on inter-organizational innovation project is generally fragmented which hinders a better understanding of the field. Thus, this paper contributes to the understanding of the field by organizing and discussing the extant literature to advance the theory and application of inter-organizational relationship.

Keywords: inter-organizational relationship, inter-firm collaboration, innovation projects, project management, systematic review

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Authors: Kamolvara Sirisuksakulchai, Soamwadee Chaianansutcharit, Kazunori Sato

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Solid Oxide Fuel Cells (SOFCs) have been considered as one of the most efficient large unit power generators for household and industrial applications. The efficiency of an electronic cell depends mainly on the electrochemical reactions in the anode. The development of anode materials has been intensely studied to achieve higher kinetic rates of redox reactions and lower internal resistance. Recent studies have introduced an efficient cermet (ceramic-metallic) material for its ability in fuel oxidation and oxide conduction. This could expand the reactive site, also known as the triple-phase boundary (TPB), thus increasing the overall performance. In this study, a bimetallic catalyst Ni₀.₇₅Co₀.₂₅Oₓ was combined with Gd₀.₁Ce₀.₉O₁.₉₅ (GDC) to be used as a cermet anode (NiCo-GDC) for an anode-supported type SOFC. The synthesis of Ni₀.₇₅Co₀.₂₅Oₓ was carried out by ball milling NiO and Co3O4 powders in ethanol and calcined at 1000 °C. The Gd₀.₁Ce₀.₉O₁.₉₅ was prepared by a urea co-precipitation method. Precursors of Gd(NO₃)₃·6H₂O and Ce(NO₃)₃·6H₂O were dissolved in distilled water with the addition of urea and were heated subsequently. The heated mixture product was filtered and rinsed thoroughly, then dried and calcined at 800 °C and 1500 °C, respectively. The two powders were combined followed by pelletization and sintering at 1100 °C to form an anode support layer. The fabrications of an electrolyte layer and cathode layer were conducted. The electrochemical performance in H₂ was measured from 800 °C to 600 °C while for CH₄ was from 750 °C to 600 °C. The maximum power density at 750 °C in H₂ was 13% higher than in CH₄. The difference in performance was due to higher polarization resistances confirmed by the impedance spectra. According to the standard enthalpy, the dissociation energy of C-H bonds in CH₄ is slightly higher than the H-H bond H₂. The dissociation of CH₄ could be the cause of resistance within the anode material. The results from lower temperatures showed a descending trend of power density in relevance to the increased polarization resistance. This was due to lowering conductivity when the temperature decreases. The long-term stability was measured at 750 °C in CH₄ monitoring at 12-hour intervals. The maximum power density tends to increase gradually with time while the resistances were maintained. This suggests the enhanced stability from charge transfer activities in doped ceria due to the transition of Ce⁴⁺ ↔ Ce³⁺ at low oxygen partial pressure and high-temperature atmosphere. However, the power density started to drop after 60 h, and the cell potential also dropped from 0.3249 V to 0.2850 V. These phenomena was confirmed by a shifted impedance spectra indicating a higher ohmic resistance. The observation by FESEM and EDX-mapping suggests the degradation due to mass transport of ions in the electrolyte while the anode microstructure was still maintained. In summary, the electrochemical test and stability test for 60 h was achieved by NiCo-GDC cermet anode. Coke deposition was not detected after operation in CH₄, hence this confirms the superior properties of the bimetallic cermet anode over typical Ni-GDC.

Keywords: bimetallic catalyst, ceria-based SOFCs, methane oxidation, solid oxide fuel cell

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Authors: Yuanxiaoyue Yang

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Emissions trading, or ‘cap-and-trade', has been long promoted by economists as a more cost-effective pollution control approach than traditional performance standard approaches. While there is a large body of empirical evidence for the overall effectiveness of emissions trading, relatively little attention has been paid to other unintended consequences brought by emissions trading. One important consequence is that cap-and-trade could introduce the risk of creating high-level emission concentrations in areas where emitting facilities purchase a large number of emission allowances, which may cause an unequal distribution of environmental benefits. This study will contribute to the current environmental policy literature by linking trading activity with environmental injustice concerns and empirically analyzing the causal relationship between trading activity and emissions reduction under a cap-and-trade program for the first time. To investigate the potential environmental injustice concern in cap-and-trade, this paper uses a differences-in-differences (DID) with instrumental variable method to identify the causal effect of allowance trading behaviors on emission reduction levels under the clean air interstate rule (CAIR), a cap-and-trade program targeting on the power sector in the eastern US. The major data source is the facility-year level emissions and allowance transaction data collected from US EPA air market databases. While polluting facilities from CAIR are the treatment group under our DID identification, we use non-CAIR facilities from the Acid Rain Program - another NOx control program without a trading scheme – as the control group. To isolate the causal effects of trading behaviors on emissions reduction, we also use eligibility for CAIR participation as the instrumental variable. The DID results indicate that the CAIR program was able to reduce NOx emissions from affected facilities by about 10% more than facilities who did not participate in the CAIR program. Therefore, CAIR achieves excellent overall performance in emissions reduction. The IV regression results also indicate that compared with non-CAIR facilities, purchasing emission permits still decreases a CAIR participating facility’s emissions level significantly. This result implies that even buyers under the cap-and-trade program have achieved a great amount of emissions reduction. Therefore, we conclude little evidence of environmental injustice from the CAIR program.

Keywords: air pollution, cap-and-trade, emissions trading, environmental justice

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Authors: Ali Al-Shehri, Abdulaziz Al-Qasim, Abdulkarim Sofi, Ali Yousef

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The oil and gas industry has played a major role in improving the prosperity of mankind and driving the world economy. According to the International Energy Agency (IEA) and Integrated Environmental Assessment (EIA) estimates, the world will continue to rely heavily on hydrocarbons for decades to come. This growing energy demand mandates taking sustainability measures to prolong the availability of reliable and affordable energy sources, and ensure lowering its environmental impact. Unlike any other industry, the oil and gas upstream operations are energy-intensive and scattered over large zonal areas. These challenging conditions require unique sustainability solutions. In recent years there has been a concerted effort by the oil and gas industry to develop and deploy innovative technologies to: maximize efficiency, reduce carbon footprint, reduce CO2 emissions, and optimize resources and material consumption. In the past, the main driver for research and development (R&D) in the exploration and production sector was primarily driven by maximizing profit through higher hydrocarbon recovery and new discoveries. Environmental-friendly and sustainable technologies are increasingly being deployed to balance sustainability and profitability. Analyzing technology and its sustainability impact is increasingly being used in corporate decision-making for improved portfolio management and allocating valuable resources toward technology R&D.This paper articulates and discusses a novel workflow to identify strategic sustainable technologies for improved portfolio management by addressing existing and future upstream challenges. It uses a systematic approach that relies on sustainability key performance indicators (KPI’s) including energy efficiency quotient, carbon footprint, and CO2 emissions. The paper provides examples of various technologies including CCS, reducing water cuts, automation, using renewables, energy efficiency, etc. The use of 4IR technologies such as Artificial Intelligence, Machine Learning, and Data Analytics are also discussed. Overlapping technologies, areas of collaboration and synergistic relationships are identified. The unique sustainability analyses provide improved decision-making on technology portfolio management.

Keywords: sustainability, oil& gas, technology portfolio, key performance indicator

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Authors: S. MacDougall-Davis, S. Wysling, R. Willmore

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Background: The application of good non-technical skills, also known as crew resource management (CRM), is central to the delivery of safe, effective healthcare. The authors have been running remote trauma courses for over 10 years, primarily focussing on developing participants’ CRM in time-critical, high-stress clinical situations. The course has undergone an iterative process over the past 10 years. We employ a number of experiential learning techniques for improving CRM, including small group workshops, military command tasks, high fidelity simulations with reflective debriefs, and a ‘flipped classroom’, where participants are asked to create their own simulations and assess and debrief their colleagues’ CRM. We created a randomised simulation study to assess the impact of our course on UK medical students’ CRM, both at an individual and a teams level. Methods: Sixteen students took part. Four clinical scenarios were devised, designed to be of similar urgency and complexity. Professional moulage effects and experienced clinical actors were used to increase fidelity and to further simulate high-stress environments. Participants were block randomised into teams of 4; each team was randomly assigned to one pre-course simulation. They then underwent our 5 day remote trauma CRM course. Post-course, students were re-randomised into four new teams; each was randomly assigned to a post-course simulation. All simulations were videoed. The footage was reviewed by two independent CRM-trained assessors, who were blinded to the before/after the status of the simulations. Assessors used the internationally validated team emergency assessment measure (TEAM) to evaluate key areas of team performance, as well as a global outcome rating. Prior to the study, assessors had scored two unrelated scenarios using the same assessment tool, demonstrating 89% concordance. Participants also completed pre- and post-course questionnaires. Likert scales were used to rate individuals’ perceived NTS ability and their confidence to work in a team in time-critical, high-stress situations. Results: Following participation in the course, a significant improvement in CRM was observed in all areas of team performance. Furthermore, the global outcome rating for team performance was markedly improved (40-70%; mean 55%), thus demonstrating an impact at Level 4 of Kirkpatrick’s hierarchy. At an individual level, participants’ self-perceived CRM improved markedly after the course (35-70% absolute improvement; mean 55%), as did their confidence to work in a team in high-stress situations. Conclusion: Our study demonstrates that with a short, cost-effective course, using easily reproducible teaching sessions, it is possible to significantly improve participants’ CRM skills, both at an individual and, perhaps more importantly, at a teams level. The successful functioning of multi-disciplinary teams is vital in a healthcare setting, particularly in high-stress, time-critical situations. Good CRM is of paramount importance in these scenarios. The authors believe that these concepts should be introduced from the earliest stages of medical education, thus promoting a culture of effective CRM and embedding an early appreciation of the importance of these skills in enabling safe and effective healthcare.

Keywords: crew resource management, non-technical skills, training, simulation

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Authors: A. Ramkumar, Anvesh Sagar, Preetham P. Karkera

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Globalization in the modern era is dependent on the International logistics, the economic and reliable means is provided by the ocean going merchant vessel. The propulsion system which drives this massive vessels has gone through leaps and bounds of evolution. Most reliable system of propulsion adopted by the majority of vessels is by marine diesel engine. Since the first oil crisis of 1973, there is demand in increment of efficiency of main engine. Due to increase in the oil prices ship-operators explores for reduction in the operational cost of ship. And newly adopted IMO’s EEDI & SEEMP rules calls for the effective measures taken in this regard. The main engine of a ship suffers a lot of thermal losses, they mainly occur due to exhaust gas waste heat, radiation and cooling. So to increase the overall efficiency of system, we have to look into the solution to harnessing this waste energy of main engine to increase the fuel economy. During the course of research, engine manufacturers have developed many waste heat recovery systems. In our paper we see about additional options to harness this waste heat. The exhaust gas of engine coming out from the turbocharger still holds enough heat to go to the exhaust gas economiser to produce steam. This heat of exhaust gas can be used to heat a liquid of less boiling point after coming out from the turbocharger. The vapour of this secondary liquid can be superheated by a bypass exhaust or exhaust of turbocharger. This vapour can be utilized to rotate the turbine which is coupled to a generator. And the electric power for ship service can be produced with proper configuration of system. This can be included in PMS of ship. In this paper we seek to concentrate on power generation with use of exhaust gas. Thereby taking out the load on the main generator and increasing the efficiency of the system. This will help us to comply with the new rules of IMO. Our method helps to develop clean energy.

Keywords: EEDI–energy efficiency design index, IMO–international maritime organization PMS-power management system, SEEMP–ship energy efficiency management plan

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Authors: Ardavan Zamanpour, Somaieh Yassari

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ZigBee protocol network was developed in industries and MIT laboratory in 1997. ZigBee is a wireless networking technology by alliance ZigBee which is designed to low board and low data rate applications. It is a Protocol which connects between electrical devises with very low energy and cost. The first version of IEEE 802.15.4 which was formed ZigBee was based on 2.4GHZ MHZ 912MHZ 868 frequency band. The name of system is often reminded random directions that bees (BEES) traversing during pollination of products. Such as alloy of the ways in which information packets are traversed within the mesh network. This paper aims to study the performance and effectiveness of this protocol in wireless networks.

Keywords: ZigBee, protocol, wireless, networks

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Authors: Marko Niinimaki

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Cryptocurrencies are getting increasingly popular, but very few of them can be conveniently used in daily mobile phone purchases. To solve this problem, we demonstrate how to build a functional prototype of a mobile cryptocurrency-based e-commerce application the communicates with Near-Field Communication (NFC) tags. Using the system, users are able to purchase physical items with an NFC tag that contains an e-commerce URL. The payment is done simply by touching the tag with a mobile device and accepting the payment. Our method is constructive: we describe the design and technologies used in the implementation and evaluate the security and performance of the solution. Our main finding is that the analysis and measurements show that our solution is feasible for e-commerce.

Keywords: cryptocurrency, e-commerce, NFC, mobile devices

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Authors: Azmanirah Ab Rahman, Jamil Ahmad, Ruhizan Muhammad Yasin

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Rubric is a very important tool for teachers and students for a variety of purposes. Teachers use the rubric for evaluating student work while students use rubrics for self-assessment. Therefore, this paper was emphasized scoring rubric as a scoring tool for teachers in an environment of Competency Based Education and Training (CBET) in Malaysia Vocational College. A total of three teachers in the fields of electrical and electronics engineering were interviewed to identify how the use of rubrics practiced since vocational transformation implemented in 2012. Overall holistic rubric used to determine the performance of students in the skills area.

Keywords: rubric, vocational education, teachers, CBET

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Authors: Maria Bonolo Mathevula

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Background: Children are important members of communities playing major role in the future of any given country (Pera, Fails, Gelsomini, &Garzotto, 2018). Visual Perceptual Skills (VPSs) in children are important health aspect of early childhood development through the Foundation Phases in school. Subsequently, children should undergo visual screening before commencement of schooling for early diagnosis ofVPSs anomalies because the primary role of VPSs is to capacitate children with academic performance in general. Aim : The aim of this study was to determine the anomalies of visual VPSs amongst school children in Foundation Phase. The study’s objectives were to determine the prevalence of VPSs anomalies amongst school children in Foundation Phase; Determine the relationship between children’s academic and VPSs anomalies; and to investigate the relationship between VPSs anomalies and refractive error. Methodology: This study was a mixed method whereby triangulated qualitative (interviews) and quantitative (questionnaire and clinical data) was used. This was, therefore, descriptive by nature. The study’s target population was school children in Foundation Phase. The study followed purposive sampling method. School children in Foundation Phase were purposively sampled to form part of this study provided their parents have given a signed the consent. Data was collected by the use of standardized interviews; questionnaire; clinical data card, and TVPS standard data card. Results: Although the study is still ongoing, the preliminary study outcome based on data collected from one of the Foundation Phases have suggested the following:While VPSs anomalies is not prevalent, it, however, have indirect relationship with children’s academic performance in Foundation phase; Notably, VPSs anomalies and refractive error are directly related since majority of children with refractive error, specifically compound hyperopic astigmatism, failed most subtests of TVPS standard tests. Conclusion: Based on the study’s preliminary findings, it was clear that optometrists still have a lot to do in as far as researching on VPSs is concerned. Furthermore, the researcher recommends that optometrist, as the primary healthcare professionals, should also conduct the school-readiness pre-assessment on children before commencement of their grades in Foundation phase.

Keywords: foundation phase, visual perceptual skills, school children, refractive error

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Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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All along the length of the supply chain, fresh food firms face the challenge of managing both product quality, due to the perishable nature of the products, and product cost. This paper develops a method to assist logistics managers upstream in the fresh food supply chain in making cost optimized decisions regarding transportation, with the objective of minimizing the total cost while maintaining the quality of food products above acceptable levels. Considering the case of multiple fresh food products collected from multiple farms being transported to a warehouse or a retailer, this study develops a total cost model that includes various costs incurred during transportation. The practical application of the model is illustrated by using several computational intelligence approaches including Genetic Algorithms (GA), Fuzzy Genetic Algorithms (FGA) as well as an improved Simulated Annealing (SA) procedure applied with a repair mechanism for efficiency benchmarking. We demonstrate the practical viability of these approaches by using a simulation study based on pertinent data and evaluate the simulation outcomes. The application of the proposed total cost model was demonstrated using three approaches of GA, FGA and SA with a repair mechanism. All three approaches are adoptable; however, based on the performance evaluation, it was evident that the FGA is more likely to produce a better performance than the other two approaches of GA and SA. This study provides a pragmatic approach for supporting logistics and supply chain practitioners in fresh food industry in making important decisions on the arrangements and procedures related to the transportation of multiple fresh food products to a warehouse from multiple farms in a cost-effective way without compromising product quality. This study extends the literature on cold supply chain management by investigating cost and quality optimization in a multi-product scenario from farms to a retailer and, minimizing cost by managing the quality above expected quality levels at delivery. The scalability of the proposed generic function enables the application to alternative situations in practice such as different storage environments and transportation conditions.

Keywords: cost optimization, food supply chain, fuzzy sets, genetic algorithms, product quality, transportation

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Authors: Mohammad Rajabalinejad

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Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: safety, safety cube, product, system, machinery, design

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Authors: Jose Melena, Rosa Santander, Tanya Gonzalez, Richard Duque, Juan Illanes

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Ecuador is one of the countries with the greatest aquatic biodiversity worldwide. In particular, there are at least a dozen native marine species with great aquaculture potential locally. This research concerns one of those species. It has proposed to implement experimental protocols in order to induce spawning and to generate the early larval development of the giant reef clam P. multicostata under controlled conditions. Bioassays were carried out with one adult batch (n= 8) with an average valvar length of 118,4 ± 5,8 mm, which were collected near of the Puerto Santa Rosa (2° 12' 30'' S, 80° 58' 28'' W), Santa Elena Province. During a short acclimation stage, the eight adults of giant reef clam P. multicostata were exposed to thermal stress. Briefly, the experimental protocol for spawning induction was based on the application of 20°C for 1 h and 30°C for 1 h on P. multicostata broodstock at least three consecutive times by one day. After spawning, collected sexual material was released for external fertilization process. After the delivery of gametes, it was achieved 3,25 × 10⁶ viable zygotes. As results, fertilized eggs had 56 µm diameter; while first and second cell divisions were observed to 2,5 h post-fertilization, with individual average length of 68 ± 5 µm and polar body. Latter cell divisions, including gastrula stage, appeared at 9 h post-fertilization, with individual average length of 73 ± 4 µm and trochophore stage at 15 h post-fertilization with individual average length of 75 ± 4 µm. In addition, veliger stage was registered at 20 h post-fertilization with individual average length of 82 ± 6 µm. Umboned larvae appeared at day 8 post-fertilization, with individual average length of 148 ± 6 µm. These pioneering results worldwide can strengthen the local conservation process of the overexploited P. multicostata and to encourage its production for commercial purposes.

Keywords: Ecuador, larval development, Periglypta multicostata, spawning induction

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