Search results for: complexity analysis

Authors: O. O. Onafowokan, K. Anderson, M. R. Norton, R. G. Middleton

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Revision total hip arthroplasty (THA) is known to be a challenging procedure with potential for poor outcomes. Due to its lack of metaphyseal encroachment, hip resurfacing arthroplasty (HRA) is classified as a bone conserving procedure. Although the literature postulates that this is an advantage at time of revision surgery, there is no evidence to either support or refute this claim. We identified 129 hips that had undergone HRA and 129 controls undergoing first revision THA. We recorded the clinical assessment and survivorship of implants in a multi-surgeon, single centre, retrospective case control series for both arms. These were matched for age and sex. Data collected included demographics, indications for surgery, Oxford Hip Score (OHS), length of surgery, length of hospital stay, blood transfusion, implant complexity and further surgical procedures. Significance was taken as p < 0.05. Mean follow up was 7.5 years (1 to 15). There was a significant 6 point difference in postoperative OHS in favour of the revision resurfacing group (p=0.0001). The revision HRA group recorded 48 minutes less length of surgery (p<0.0001), 2 days less in length of hospital stay (p=0.018), a reduced need for blood transfusion (p=0.0001), a need for less complexity in revision implants (p=0.001) and a reduced probability of further surgery being required (P=0.003). Whilst we acknowledge the limitations of this study our results suggest that, in contrast to THA, the bone conservation element of HRA may make for a less traumatic revision procedure with better functional outcomes. Use of HRA has seen a dramatic decline as a result of concerns regarding metallosis. However, this information remains of relevance when counselling young active patients about their arthroplasty options and may become pertinent in the future if the promise of ceramic hip resurfacing is ever realized.

Keywords: hip resurfacing, metallosis, revision surgery, total hip arthroplasty

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Authors: Raghava Dhanya, Shashank S.

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This paper delves into the intersection of chess and computer science, specifically focusing on the efficient representation of chess game states. We propose two methods: the Static Method and the Dynamic Method, each offering unique advantages in terms of space efficiency and computational complexity. The Static Method aims to represent the game state using a fixedlength encoding, allocating 192 bits to capture the positions of all pieces on the board. This method introduces a protocol for ordering and encoding piece positions, ensuring efficient storage and retrieval. However, it faces challenges in representing pieces no longer in play. In contrast, the Dynamic Method adapts to the evolving game state by dynamically adjusting the encoding length based on the number of pieces in play. By incorporating Alive Bits for each piece kind, this method achieves greater flexibility and space efficiency. Additionally, it includes provisions for encoding additional game state information such as castling rights and en passant squares. Our findings demonstrate that the Dynamic Method offers superior space efficiency compared to traditional Forsyth-Edwards Notation (FEN), particularly as the game progresses and pieces are captured. However, it comes with increased complexity in encoding and decoding processes. In conclusion, this study provides insights into optimizing the representation of chess game states, offering potential applications in chess engines, game databases, and artificial intelligence research. The proposed methods offer a balance between space efficiency and computational overhead, paving the way for further advancements in the field.

Keywords: chess, optimisation, encoding, bit manipulation

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Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

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Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular/nanoscale models is demonstrated.

Keywords: cement composite, mechanical properties, molecular dynamics, plasticizer additives

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Authors: Ameni Mejri, Moufida Hajjaj, Salem Hasnaoui, Ridha Bouallegue

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The technology advances have most lately made the millimeter wave (mmWave) communication possible. Due to the huge amount of spectrum that is available in MmWave frequency bands, this promising candidate is considered as a key technology for the deployment of 5G cellular networks. In order to enhance system capacity and achieve spectral efficiency, very large antenna arrays are employed at mmWave systems by exploiting array gain. However, it has been shown that conventional beamforming strategies are not suitable for mmWave hardware implementation. Therefore, new features are required for mmWave cellular applications. Unlike traditional multiple-input-multiple-output (MIMO) systems for which only digital precoders are essential to accomplish precoding, MIMO technology seems to be different at mmWave because of digital precoding limitations. Moreover, precoding implements a greater number of radio frequency (RF) chains supporting more signal mixers and analog-to-digital converters. As RF chain cost and power consumption is increasing, we need to resort to another alternative. Although the hybrid precoding architecture has been regarded as the best solution based on a combination between a baseband precoder and an RF precoder, we still do not get the optimal design of hybrid precoders. According to the mapping strategies from RF chains to the different antenna elements, there are two main categories of hybrid precoding architecture. Given as a hybrid precoding sub-array architecture, the partially-connected structure reduces hardware complexity by using a less number of phase shifters, whereas it sacrifices some beamforming gain. In this paper, we treat the hybrid precoder design in mmWave MIMO systems as a problem of matrix factorization. Thus, we adopt the alternating minimization principle in order to solve the design problem. Further, we present our proposed algorithm for the partially-connected structure, which is based on the iterative hard thresholding method. Through simulation results, we show that our hybrid precoding algorithm provides significant performance gains over existing algorithms. We also show that the proposed approach reduces significantly the computational complexity. Furthermore, valuable design insights are provided when we use the proposed algorithm to make simulation comparisons between the hybrid precoding partially-connected structure and the fully-connected structure.

Keywords: alternating minimization, hybrid precoding, iterative hard thresholding, low-complexity, millimeter wave communication, partially-connected structure

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Authors: Pedro M. Abreu, Bruno R. Mendes

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The management of pharmacotherapy and the process of dispensing medicines is becoming critical in clinical pharmacy due to the increase of incidence and prevalence of chronic diseases, the complexity and customization of therapeutic regimens, the introduction of innovative and more expensive medicines, the unbalanced relation between expenditure and revenue as well as due to the lack of rationalization associated with medication use. For these reasons, co-payments emerged in Europe in the 70s and have been applied over the past few years in healthcare. Co-payments lead to a rationing and rationalization of user’s access under healthcare services and products, and simultaneously, to a qualification and improvement of the services and products for the end-user. This analysis, under hospital practices particularly and co-payment strategies in general, was carried out on all the European regions and identified four reference countries, that apply repeatedly this tool and with different approaches. The structure, content and adaptation of European co-payments were analyzed through 7 qualitative attributes and 19 performance indicators, and the results expressed in a scorecard, allowing to conclude that the German models (total score of 68,2% and 63,6% in both elected co-payments) can collect more compliance and effectiveness, the English models (total score of 50%) can be more accessible, and the French models (total score of 50%) can be more adequate to the socio-economic and legal framework. Other European models did not show the same quality and/or performance, so were not taken as a standard in the future design of co-payments strategies. In this sense, we can see in the co-payments a strategy not only to moderate the consumption of healthcare products and services, but especially to improve them, as well as a strategy to increment the value that the end-user assigns to these services and products, such as medicines.

Keywords: clinical pharmacy, co-payments, healthcare, medicines

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Authors: Long Guo, Hong Liu, Hongyu Yang, Hu Chen, Wenchao Du, Yu Liu

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Alzheimer’s disease (AD) is an incurable neurodegenerative disorder, underscoring the need for early diagnosis and intervention. Traditional clinical approaches pose challenges due to their inconvenience and high costs. In contrast, automatic AD screening systems based on speech analysis provide a noninvasive and scalable alternative. These systems commonly rely on extensively annotated datasets to fine-tune pre-trained language models for classification. Nevertheless, the diversity and complexity of the AD patient population, compounded by the limited availability of data for diverse groups, often result in suboptimal detection across various demographics. This research explores the effectiveness of large language models in zero-shot and few-shot learning scenarios for AD detection. Specific prompt engineering techniques have been developed for these scenarios, and large language models, including GPT-3.5 and GPT-4, have been employed on the ADReSSo test set. The models achieved an accuracy rate of 83.3%, which exceeds the results of traditional, data-intensive methods. Additionally, a ’thought chain’ mechanism was designed to guide the models in a step-by-step analysis of AD symptoms, yielding not only accurate but also interpretable results. The findings suggest that minimal data, when strategically applied through disease-specific prompt engineering and large language models, can significantly improve AD detection, presenting a viable direction for future medical diagnostic research.

Keywords: Alzheimer’s disease, few-shot, interpretability, large language model, zero-shot

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Authors: Fátima Gonçalves, Joaquim Brigas, Jorge Gonçalves

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As a way of managing the increasing volume and complexity of information that circulates in the present time, graphical representations are increasingly used, which add meaning to the information presented in communication media, through an efficient communication design. The visual culture itself, driven by technological evolution, has been redefining the forms of communication, so that contemporary visual communication represents a major impact on society. This article presents the results and respective comparative analysis of four publications in the Iberian press, focusing on the formal aspects of newspapers and the space they dedicate to the various communication elements. Two Portuguese newspapers and two Spanish newspapers were selected for this purpose. The findings indicated that the newspapers show a similarity in the use of graphic solutions, which corroborate a visual trend in communication design. The results also reveal that Spanish newspapers are more meticulous with graphic consistency. This study intended to contribute to improving knowledge of the Iberian generalist press.

Keywords: communication design, graphic resources, Iberian press, visual journalism

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Authors: Edinei Coser, Cátia Regina Silva de Carvalho Pinto, Kleber Isaac Silva de Souza

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The road transportation system is an integral part of the Brazilian economy, so investing in this sector is paramount. Despite being a significant contributor to national and regional development, implementing road infrastructures brings about significant environmental changes, resulting in negative impacts that need to be mitigated through environmental licensing. However, by considering potential environmental impacts from a strategic perspective earlier, we can ensure that the sustainable development resulting from investments in this sector is more efficient. Therefore, this work aims to incorporate strategic environmental assessment into the road transportation system in the state of Santa Catarina using a tool that evaluates the entire territory. This tool analyzes 15 qualitative socio-environmental factors that may complicate environmental licensing and project implementation, with the help of multi-criteria analysis based on AHP and geographic information systems with Python, which presents a surface map of environmental cost for Santa Catarina state in Brazil. This map represents how environmental restrictions are spatially distributed in the territory and can be used for governments and decision-makers to assess potential areas for road implementation or paving, evaluate and propose road corridors, propose, promote, and evaluate risks for governmental programs and investments, set environmental management guidelines and enhance contracting and environmental assessment processes.

Keywords: environmental impact assessment., GIS, highways, multi-criteria analysis, strategic environmental assessment

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Authors: Pratima Poudel, Austin Himes, Heidi Renninger, Eric McConnel

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Populus spp. (poplar) are the fastest-growing trees in North America, making them ideal for a range of applications as they can achieve high yields on short rotations and regenerate by coppice. Furthermore, poplar undergoes biochemical conversion to fuels without complexity, making it one of the most promising, purpose-grown, woody perennial energy sources. Employing wood-based biomass for bioenergy offers numerous benefits, including reducing greenhouse gas (GHG) emissions compared to non-renewable traditional fuels, the preservation of robust forest ecosystems, and creating economic prospects for rural communities.In order to gain a better understanding of the potential use of poplar as a biomass feedstock for biofuel in the southeastern US, the conducted a techno-economic assessment (TEA). This assessment is an analytical approach that integrates technical and economic factors of a production system to evaluate its economic viability. the TEA specifically focused on a short rotation coppice system employing a single-pass cut-and-chip harvesting method for poplar. It encompassed all the costs associated with establishing dedicated poplar plantations, including land rent, site preparation, planting, fertilizers, and herbicides. Additionally, we performed a sensitivity analysis to evaluate how different costs can affect the economic performance of the poplar cropping system. This analysis aimed to determine the minimum average delivered selling price for one metric ton of biomass necessary to achieve a desired rate of return over the cropping period. To inform the TEA, data on the establishment, crop care activities, and crop yields were derived from a field study conducted at the Mississippi Agricultural and Forestry Experiment Station's Bearden Dairy Research Center in Oktibbeha County and Pontotoc Ridge-Flatwood Branch Experiment Station in Pontotoc County.

Keywords: biomass, populus species, sensitivity analysis, technoeconomic analysis

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Authors: Desmond Wade, Alfredo Ormazabal

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Background: Ever since it commenced its registration process of pre-hospital practitioners in the year 2000 through the Irish Government Statute Instrument (SI 109 of 2000) process, the approach to education of its professionals has changed drastically. The progression from the traditional behaviouristic to the current constructivist approach has been based on experiences from other sectors and industries, nationally and internationally. Today, the delivery of a safe and efficient ambulance service heavily depends on its practitioners’ range of technical skills, academic knowledge, and overall competences. As these increase, so does the level of complexity of paramedics’ everyday practice. This has made it inevitable to consider the 'Human Factor' as a source of potential risk and made formative institutions like the National Ambulance Service College to include it in their curriculum. Methods: This paper used a mixed-method approach, where both, an online questionnaire and a set of semi-structured interviews were the source of primary data. An analysis of this data was carried out using qualitative and quantitative data analysis. Conclusions: The evidence presented leads to the conclusion that in the National Ambulance Service there is a considerable lack of education of Human Factors and the levels in understanding of how to manage Human Factors in practice vary across its spectrum. Paramedic Practitioners in Ireland seem to understand that the responsibility of patient care lies on the team, rather than on the most hierarchically senior practitioner present in the scene.

Keywords: human factors, ergonomics, stress, decision making, pre-hospital care, paramedic, education

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Authors: Zihan Geng, L. Quentin Dixon

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It has been proposed that early bilingual experience confers a number of advantages in the development of executive control mechanisms. Although the literature provides empirical evidence for bilingual benefits, some studies also reported null or mixed results. To make sense of these contradictory findings, the current review synthesize recent empirical studies investigating bilingual effects on children’s executive function and attention control. The publication time of the studies included in the review ranges from 2010 to 2017. The key searching terms are bilingual, bilingualism, children, executive control, executive function, and attention. The key terms were combined within each of the following databases: ERIC (EBSCO), Education Source, PsycINFO, and Social Science Citation Index. Studies involving both children and adults were also included but the analysis was based on the data generated only by the children group. The initial search yielded 137 distinct articles. Twenty-eight studies from 27 articles with a total of 3367 participants were finally included based on the selection criteria. The selective studies were then coded in terms of (a) the setting (i.e., the country where the data was collected), (b) the participants (i.e., age and languages), (c) sample size (i.e., the number of children in each group), (d) cognitive outcomes measured, (e) data collection instruments (i.e., cognitive tasks and tests), and (f) statistic analysis models (e.g., t-test, ANOVA). The results show that the majority of the studies were undertaken in western countries, mainly in the U.S., Canada, and the UK. A variety of languages such as Arabic, French, Dutch, Welsh, German, Spanish, Korean, and Cantonese were involved. In relation to cognitive outcomes, the studies examined children’s overall planning and problem-solving abilities, inhibition, cognitive complexity, working memory (WM), and sustained and selective attention. The results indicate that though bilingualism is associated with several cognitive benefits, the advantages seem to be weak, at least, for children. Additionally, the nature of the cognitive measures was found to greatly moderate the results. No significant differences are observed between bilinguals and monolinguals in overall planning and problem-solving ability, indicating that there is no bilingual benefit in the cooperation of executive function components at an early age. In terms of inhibition, the mixed results suggest that bilingual children, especially young children, may have better conceptual inhibition measured in conflict tasks, but not better response inhibition measured by delay tasks. Further, bilingual children showed better inhibitory control to bivalent displays, which resembles the process of maintaining two language systems. The null results were obtained for both cognitive complexity and WM, suggesting no bilingual advantage in these two cognitive components. Finally, findings on children’s attention system associate bilingualism with heightened attention control. Together, these findings support the hypothesis of cognitive benefits for bilingual children. Nevertheless, whether these advantages are observable appears to highly depend on the cognitive assessments. Therefore, future research should be more specific about the cognitive outcomes (e.g., the type of inhibition) and should report the validity of the cognitive measures consistently.

Keywords: attention, bilingual advantage, children, executive function

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Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

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Authors: Manoj Reghu, Prabhu Rajagopal, C. V. Krishnamurthy, Krishnan Balasubramaniam

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A thorough understanding of guided ultrasonic wave behavior in structures is essential for the application of existing Non Destructive Evaluation (NDE) technologies, as well as for the development of new methods. However, the analysis of guided wave phenomena is challenging because of their complex dispersive and multimodal nature. Although numerical solution procedures have proven to be very useful in this regard, the increasing complexity of features and defects to be considered, as well as the desire to improve the accuracy of inspection often imposes a large computational cost. Hybrid models that combine numerical solutions for wave scattering with faster alternative methods for wave propagation have long been considered as a solution to this problem. However usually such models require modification of the base code of the solution procedure. Here we aim to develop Generic Hybrid models that can be directly applied to any two different solution procedures. With this goal in mind, a Numerical Hybrid model and an Analytical-Numerical Hybrid model has been developed. The concept and implementation of these Hybrid models are discussed in this paper.

Keywords: guided ultrasonic waves, Finite Element Method (FEM), Hybrid model

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Authors: Massimiliano Condotta, Giovanni Borga, Chiara Scanagatta

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Urban systems are places where the various actors involved interact and enter in conflict, in particular with reference to topics such as traffic congestion and security. But topics of discussion, and often clash because of their strong complexity, are air and noise pollution. For air pollution, the complexity stems from the fact that atmospheric pollution is due to many factors, but above all, the observation and measurement of the amount of pollution of a transparent, mobile and ethereal element like air is very difficult. Often the perceived condition of the inhabitants does not coincide with the real conditions, because it is conditioned - sometimes in positive ways other in negative ways - from many other factors such as the presence, or absence, of natural elements such as trees or rivers. These problems are seen with noise pollution as well, which is also less considered as an issue even if it’s problematic just as much as air quality. Starting from these opposite positions, it is difficult to identify and implement valid, and at the same time shared, mitigation solutions for the problem of urban pollution (air and noise pollution). The LOOPER (Learning Loops in the Public Realm) project –described in this paper – wants to build and test a methodology and a platform for participatory co-design, planning, and construction process inside a learning loop process. Novelties in this approach are various; the most relevant are three. The first is that citizens participation starts since from the research of problems and air quality analysis through a participatory data collection, and that continues in all process steps (design and construction). The second is that the methodology is characterized by a learning loop process. It means that after the first cycle of (1) problems identification, (2) planning and definition of design solution and (3) construction and implementation of mitigation measures, the effectiveness of implemented solutions is measured and verified through a new participatory data collection campaign. In this way, it is possible to understand if the policies and design solution had a positive impact on the territory. As a result of the learning process produced by the first loop, it will be possible to improve the design of the mitigation measures and start the second loop with new and more effective measures. The third relevant aspect is that the citizens' participation is carried out via Urban Living Labs that involve all stakeholder of the city (citizens, public administrators, associations of all urban stakeholders,…) and that the Urban Living Labs last for all the cycling of the design, planning and construction process. The paper will describe in detail the LOOPER methodology and the technical solution adopted for the participatory data collection and design and construction phases.

Keywords: air quality, co-design, learning loops, noise pollution, urban living labs

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Asawari Alok Pawaskar

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This study was aimed at investigating quality assurance (QA) done with IBA matrix, the discrepan­cies observed for helical tomotherapy plans. A selection of tomotherapy plans that initially failed the with Matrix process was chosen for this investigation. These plans failed the fluence analysis as assessed using gamma criteria (3%, 3 mm). Each of these plans was modified (keeping the planning constraints the same), beamlets rebatched and reoptimized. By increasing and decreasing the modula­tion factor, the fluence in a circumferential plane as measured with a diode array was assessed. A subset of these plans was investigated using varied pitch values. Factors for each plan that were examined were point doses, fluences, leaf opening times, planned leaf sinograms, and uniformity indices. In order to ensure that the treatment constraints remained the same, the dose-volume histograms (DVHs) of all the modulated plans were compared to the original plan. It was observed that a large increase in the modulation factor did not significantly improve DVH unifor­mity, but reduced the gamma analysis pass rate. This also increased the treatment delivery time by slowing down the gantry rotation speed which then increases the maximum to mean non-zero leaf open time ratio. Increasing and decreasing the pitch value did not substantially change treatment time, but the delivery accuracy was adversely affected. This may be due to many other factors, such as the complexity of the treatment plan and site. Patient sites included in this study were head and neck, breast, abdomen. The impact of leaf tim­ing inaccuracies on plans was greater with higher modulation factors. Point-dose measurements were seen to be less susceptible to changes in pitch and modulation factors. The initial modulation factor used by the optimizer, such that the TPS generated ‘actual’ modulation factor within the range of 1.4 to 2.5, resulted in an improved deliverable plan.

Keywords: dose volume histogram, modulation factor, IBA matrix, tomotherapy

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Authors: Athanasios Karasimos, Vasiliki Makri

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This research focuses on the design and development of the first text Corpus based on Board Game Rulebooks (BGRC) with direct application on the morphological analysis of neologisms and tendencies in word-formation processes. Corpus linguistics is a dynamic field that examines language through the lens of vast collections of texts. These corpora consist of diverse written and spoken materials, ranging from literature and newspapers to transcripts of everyday conversations. By morphologically analyzing these extensive datasets, morphologists can gain valuable insights into how language functions and evolves, as these extensive datasets can reflect the byproducts of inflection, derivation, blending, clipping, compounding, and neology. This entails scrutinizing how words are created, modified, and combined to convey meaning in a corpus of challenging, creative, and straightforward texts that include rules, examples, tutorials, and tips. Board games teach players how to strategize, consider alternatives, and think flexibly, which are critical elements in language learning. Their rulebooks reflect not only their weight (complexity) but also the language properties of each genre and subgenre of these games. Board games are a captivating realm where strategy, competition, and creativity converge. Beyond the excitement of gameplay, board games also spark the art of word creation. Word games, like Scrabble, Codenames, Bananagrams, Wordcraft, Alice in the Wordland, Once uUpona Time, challenge players to construct words from a pool of letters, thus encouraging linguistic ingenuity and vocabulary expansion. These games foster a love for language, motivating players to unearth obscure words and devise clever combinations. On the other hand, the designers and creators produce rulebooks, where they include their joy of discovering the hidden potential of language, igniting the imagination, and playing with the beauty of words, making these games a delightful fusion of linguistic exploration and leisurely amusement. In this research, more than 150 rulebooks in English from all types of modern board games, either language-independent or language-dependent, are used to create the BGRC. A representative sample of each genre (family, party, worker placement, deckbuilding, dice, and chance games, strategy, eurogames, thematic, role-playing, among others) was selected based on the score from BoardGameGeek, the size of the texts and the level of complexity (weight) of the game. A morphological model with morphological networks, multi-word expressions, and word-creation mechanics based on the complexity of the textual structure, difficulty, and board game category will be presented. In enabling the identification of patterns, trends, and variations in word formation and other morphological processes, this research aspires to make avail of this creative yet strict text genre so as to (a) give invaluable insight into morphological creativity and innovation that (re)shape the lexicon of the English language and (b) test morphological theories. Overall, it is shown that corpus linguistics empowers us to explore the intricate tapestry of language, and morphology in particular, revealing its richness, flexibility, and adaptability in the ever-evolving landscape of human expression.

Keywords: board game rulebooks, corpus design, morphological innovations, neologisms, word-formation processes

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Authors: David Serero, Loic Couton, Jean-Denis Parisse, Robert Leroy

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This paper presents an analysis method of airflow at the periphery of several typologies of architectural volumes. To understand the complexity of the urban environment on the airflows in the city, we compared three sites at different architectural scale. The research sets a method to identify the optimal location for the installation of wind turbines on the edges of a building and to achieve an improvement in the performance of energy extracted by precise localization of an accelerating wing called “aero foil”. The objective is to define principles for the installation of wind turbines and natural ventilation design of buildings. Instead of theoretical winds analysis, we combined numerical aeraulic simulations using STAR CCM + software with wind data, over long periods of time (greater than 1 year). If airflows computer fluid analysis (CFD) simulation of buildings are current, we have calibrated a virtual wind tunnel with wind data using in situ anemometers (to establish localized cartography of urban winds). We can then develop a complete volumetric model of the behavior of the wind on a roof area, or an entire urban island. With this method, we can categorize: - the different types of wind in urban areas and identify the minimum and maximum wind spectrum, - select the type of harvesting devices - fixing to the roof of a building, - the altimetry of the device in relation to the levels of the roofs - The potential nuisances around. This study is carried out from the recovery of a geolocated data flow, and the connection of this information with the technical specifications of wind turbines, their energy performance and their speed of engagement. Thanks to this method, we can thus define the characteristics of wind turbines to maximize their performance in urban sites and in a turbulent airflow regime. We also study the installation of a wind accelerator associated with buildings. The “aerofoils which are integrated are improvement to control the speed of the air, to orientate it on the wind turbine, to accelerate it and to hide, thanks to its profile, the device on the roof of the building.

Keywords: wind energy harvesting, wind turbine selection, urban wind potential analysis, CFD simulation for architectural design

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Authors: Lassaad Smirani

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In this paper we propose a Neurosymbolic Learning System (NLS) as a channel estimator for Long Term Evolution Advanced (LTE-A) uplink. The proposed system main idea based on Neural Network has modules capable of performing bidirectional information transfer between symbolic module and connectionist module. We demonstrate various strengths of the NLS especially the ability to integrate theoretical knowledge (rules) and experiential knowledge (examples), and to make an initial knowledge base (rules) converted into a connectionist network. Also to use empirical knowledge witch by learning will have the ability to revise the theoretical knowledge and acquire new one and explain it, and finally the ability to improve the performance of symbolic or connectionist systems. Compared with conventional SC-FDMA channel estimation systems, The performance of NLS in terms of complexity and quality is confirmed by theoretical analysis and simulation and shows that this system can make the channel estimation accuracy improved and bit error rate decreased.

Keywords: channel estimation, SC-FDMA, neural network, hybrid system, BER, LTE-A

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Authors: Ritu Sharma

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In order to be objective, critics must examine the dynamic relationships between the author, the reader, the text, and the outside world. However, it is also crucial to recognize that because the language was created by God, meaning is ingrained in it. Meaning is located in and discovered through literature rather than being limited to the author, reader, text, or the outside world. The link between the author, the reader, and the text is crucial because literature unites an author and a reader through the use of language. Literature is a potent kind of communication, and Ethan Frome's audience is forever changed as a result of the book's language and the language its characters use. The narrative of Ethan Frome and his wife Zeena is presented in Ethan Frome. Ethan's story is told throughout the course of the book, revealed through the eyes of the narrator, an outsider passing through Starkfield, as well as through the insight that the narrator gains from the townspeople and his stay on the Frome farm. The story is set in the rural New England community of Starkfield, Massachusetts. The weather provides the ideal setting for Ethan and the narrator to get to know one another as the narrator gets preoccupied with unraveling the narrative that underlies Ethan's physical anomalies. In addition to telling a gripping tale and capturing human nature as it is, Ethan Frome uses its storyline to achieve something more significant. The book by Edith Wharton supports language. Zeena's deliberate and convincing language challenges relativity and meaninglessness. Ethan and Mattie's effort to effectively use words reflects the complexity of language, and their battle illustrates the influence that language may have if and when it is used. Ethan Frome defends the written word, the foundation upon which it is constructed, as a literary work. Communication is based on language, and as the characters respond to and get involved in disputes throughout the book, Zeena, Ethan, and Mattie, each reflects particular theories of communication that help define their uses of communication within the broader context of language.

Keywords: dynamic relationships, potent, communication, complexity

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Authors: Amanda Kavner, Richard Lamb

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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.

Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience

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Authors: Iva Zdrilić, Petra Došenović Bonča, Darija Aleksić

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Since the boundaryless career, with its emphasis on cross-employer movements, was introduced as a new paradigm of career development, inter-organizational employee mobility has been increasing. Although this phenomenon may have positive implications for individual careers and destination organizations, the consequences for the source organizations losing workers are less clear. The aim of this paper is thus to develop a comprehensive typology of possible inter-organizational employee mobility determinants. Since the most common classification differentiates between mobility determinants at different levels (i.e., economic, organizational, and individual), this paper focuses on building a comprehensive multi-level typology of inter-organizational mobility determinants across diverse sectors and industries. By using a structured literature review approach and bibliometric analysis, the paper reveals both intricate relationships between different mobility determinants and the complexity of inter-organizational networks and social ties. The latter appears as both a mobility determinant (at the organizational and individual level) and a mobility effect. Indeed, inter-organizational employee mobility leads to the formation of networks between source and destination organizations. These networks are practically based on the social ties between mobile employees and their colleagues and, in this way, they close the "inter-organizational employee mobility - inter-organizational network/ties" circle. The paper contributes to the career development literature by uncovering hitherto underexplored diverse determinants of intra- and inter-sectoral mobility as well as the conflicting results of the existing studies on some factors (e.g., inter-organizational networks and/or social ties) that appear both as a mobility determinant and a mobility effect.

Keywords: inter-organizational mobility, social ties, inter-organizational network, knowledge transfer

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Authors: Erin McKellar, Narelle Yeo

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Gender disparity can be found in the representation of the female characters in Leonard Bernstein’s musical West Side Story. As a postmodern composer, Bernstein was open about his social activism, yet did not consider his compositional portrayal of female characters as part of that activism. Using discretization as an analysis tool, this thesis explores the melodic contours of male and female songs in West Side Story to show differences in complexity between male and female characterisation. The analysis explores the intervallic relationship between the vocal line and melodic color in relation to the accompaniment harmony, taking into consideration the use of consonance and dissonance. West Side Story is commonly known for its distinct use of the tritone motif and its inherent dissonance. It is evident when reviewing the findings of this study that there is a distinct disparity between male-led and female-led music. The male-led numbers consistently adhere to a dissonant aesthetic with the tritone motif implemented in all of the extracted songs. By contrast, the female songs remain consonant with simple intervallic movements. By examining the results of this study through the lens of Equality Feminism, this thesis finds that Bernstein has simplified the characterisations of the female leads. The thesis further proposes that without cognisant consideration of the compositional portrayal of women, the musical theatre will continue to reinforce gender stereotypes, as evident through this study of Bernstein’s West Side Story.

Keywords: music theatre, gender bias, composition, Leonard Bernstein

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Authors: Priyanka Dargode, Suhas Gore, Manju Sharma, Arvind Lali

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Anaerobic digestion has been widely used for production of methane from different biowastes. However, the complexity of microbial communities involved in the process is poorly understood. The performance of biogas production process concerning the process productivity is closely coupled to its microbial community structure and syntrophic interactions amongst the community members. The present study aims at understanding taxonomic variations occurring in any starter inoculum when acclimatised to different lignocellulosic biomass (LBM) feedstocks relating to time of digestion. The work underlines use of high throughput Next Generation Sequencing (NGS) for validating the changes in taxonomic patterns of microbial communities. Biomethane Potential (BMP) batches were set up with different pretreated and non-pretreated LBM residues using the same microbial consortium and samples were withdrawn for studying the changes in microbial community in terms of its structure and predominance with respect to changes in metabolic profile of the process. DNA of samples withdrawn at different time intervals with reference to performance changes of the digestion process, was extracted followed by its 16S rRNA amplicon sequencing analysis using Illumina Platform. Biomethane potential and substrate consumption was monitored using Gas Chromatography(GC) and reduction in COD (Chemical Oxygen Demand) respectively. Taxonomic analysis by QIIME server data revealed that microbial community structure changes with different substrates as well as at different time intervals. It was observed that biomethane potential of each substrate was relatively similar but, the time required for substrate utilization and its conversion to biomethane was different for different substrates. This could be attributed to the nature of substrate and consequently the discrepancy between the dominance of microbial communities with regards to different substrate and at different phases of anaerobic digestion process. Knowledge of microbial communities involved would allow a rational substrate specific consortium design which will help to reduce consortium adaptation period and enhance the substrate utilisation resulting in improved efficacy of biogas process.

Keywords: amplicon sequencing, biomethane potential, community predominance, taxonomic analysis

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Authors: Michaela Chovancova, Jakub Elcner

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Real bronchial tree is very complicated piping system. Analysis of flow and pressure losses in this system is very difficult. Due to the complex geometry and the very small size in the lower generations is examination by CFD possible only in the central part of bronchial tree. For specify the pressure losses of lower generations is necessary to provide a mathematical equation. Determination of mathematical formulas for calculating the pressure losses in the real lungs is due to its complexity and diversity lengthy and inefficient process. For these calculations is necessary the lungs to slightly simplify (same cross-section over the length of individual generation) or use one of the models of lungs. The simplification could cause deviations from real values. The article compares the values of pressure losses obtained from CFD simulation of air flow in the central part of the real bronchial tree with the values calculated in a slightly simplified real lungs by using a mathematical relationship derived from the Bernoulli equation and continuity equation. Then, evaluate the desirability of using this formula to determine the pressure loss across the bronchial tree.

Keywords: pressure gradient, airways resistance, real geometry of bronchial tree, breathing

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Authors: Marina Magdy Naguib Karas

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New methods of providing banking services to the customer have been introduced, such as online banking. Banks have begun to consider electronic banking (e-banking) as a way to replace some traditional branch functions by using the Internet as a new distribution channel. Some consumers have at least one account at multiple banks and access these accounts through online banking. To check their current net worth, clients need to log into each of their accounts, get detailed information, and work toward consolidation. Not only is it time-consuming, but it is also a repeatable activity with a certain frequency. To solve this problem, the concept of account aggregation was added as a solution. Account consolidation in e-banking as a form of electronic banking appears to build a stronger relationship with customers. An account linking service is generally referred to as a service that allows customers to manage their bank accounts held at different institutions via a common online banking platform that places a high priority on security and data protection. The article provides an overview of the account aggregation approach in e-banking as a new service in the area of e-banking.

Keywords: compatibility, complexity, mobile banking, observation, risk banking technology, Internet banks, modernization of banks, banks, account aggregation, security, enterprise development

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Authors: Daniel Panario, Daniel Santana de Freitas, Brett Stevens

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Almost Perfect Nonlinear (APN) permutations with optimal resistance against differential cryptanalysis can be found in several domains. The permutation used in the standard for symmetric cryptography (the AES), for example, is based on a special kind of inversion in GF(28). Although very close to APN (2-uniform), this permutation still contains one number 4 in its differential spectrum, which means that, rigorously, it must be classified as 4-uniform. This fact motivates the search for fully APN permutations in other domains of definition. The extremely high complexity associated to this kind of problem precludes an exhaustive search for an APN permutation with 256 elements to be performed without the support of a suitable mathematical structure. On the other hand, in principle, there is nothing to indicate which mathematically structured domains can effectively help the search, and it is necessary to test several domains. In this work, the search for APN permutations in rings ℤ2×ℤ2k is investigated. After a full, exhaustive search with k=2 and k=3, all possible APN permutations in those rings were recorded, together with their differential profiles. Some very promising heuristics in these cases were collected so that, when used as a basis to prune backtracking for the same search in ℤ2×ℤ8 (search space with size 16! ≅244), just a few tenths of a second were enough to produce an APN permutation in a single CPU. Those heuristics were empirically extrapolated so that they could be applied to a backtracking search for APNs over ℤ2×ℤ16 (search space with size 32! ≅2117). The best permutations found in this search were further refined through Simulated Annealing, with a definition of neighbors suitable to this domain. The best result produced with this scheme was a 3-uniform permutation over ℤ2×ℤ16 with only 24 values equal to 3 in the differential spectrum (all the other 968 values were less than or equal 2, as it should be the case for an APN permutation). Although far from being fully APN, this result is technically better than a 4-uniform permutation and demanded only a few seconds in a single CPU. This is a strong indication that the use of mathematically structured domains, like the rings described in this work, together with heuristics based on smaller cases, can lead to dramatic cuts in the computational resources involved in the complexity of the search for APN permutations in extremely large domains.

Keywords: APN permutations, heuristic searches, symmetric cryptography, S-box design

Procedia PDF Downloads 129

Authors: Olga Maksakova

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A work with unconscious patients after acute brain damages besides special knowledge and practical skills of all the participants requires a very specific organization. A lot of said about team approach in neurorehabilitation, usually as for outpatient mode. Rehabilitologists deal with fixed patient problems or deficits (motion, speech, cognitive or emotional disorder). Team-building means superficial paradigm of management psychology. Linear mode of teamwork fits casual relationships there. Cases with deep altered states of consciousness (vegetative states, coma, and confusion) require non-linear mode of teamwork: recovery of consciousness might not be the goal due to phenomenon uncertainty. Rehabilitation team as Semi-open Complex System includes the patient as a part. Patient's response pattern becomes formed not only with brain deficits but questions-stimuli, context, and inquiring person. Teamwork is sourcing of phenomenology knowledge of patient's processes as Third-person approach is replaced with Second- and after First-person approaches. Here is a chance for real-time change. Patient’s contacts with his own body and outward things create a basement for restoration of consciousness. The most important condition is systematic feedbacks to any minimal movement or vegetative signal of the patient. Up to now, recovery work with the most severe contingent is carried out in the mode of passive physical interventions, while an effective rehabilitation team should include specially trained psychologists and psychotherapists. It is they who are able to create a network of feedbacks with the patient and inter-professional ones building up the team. Characteristics of ‘Team-Patient’ system (TPS) are energy, entropy, and complexity. Impairment of consciousness as the absence of linear contact appears together with a loss of essential functions (low energy), vegetative-visceral fits (excessive energy and low order), motor agitation (excessive energy and excessive order), etc. Techniques of teamwork are different in these cases for resulting optimization of the system condition. Directed regulation of the system complexity is one of the recovery tools. Different signs of awareness appear as a result of system self-organization. Joint meetings are an important part of teamwork. Regular or event-related discussions form the language of inter-professional communication, as well as the patient's shared mental model. Analysis of complex communication process in TPS may be useful for creation of the general theory of consciousness.

Keywords: rehabilitation team, urgent rehabilitation, severe brain damage, consciousness disorders, complex system theory

Procedia PDF Downloads 119

Authors: Idris M. Olatunde, Kareem B.

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In manufacturing systems, especially job shops, service performance is a key factor that determines customer satisfaction. Service performance depends not only on the quality of the output but on the delivery lead times as well. Besides product quality enhancement, delivery lead time must be minimized for optimal patronage. Quoting accurate due dates is sine quo non for job shop operational survival in a global competitive environment. Quoting accurate due dates in job shops has been a herculean task that nearly defiled solutions from many methods employed due to complex jobs routing nature of the system. This class of NP-hard problems possessed no rigid algorithms that can give an optimal solution. Jobshop operational problem is more complex in developing nations due to some peculiar factors. Operational complexity in job shops emanated from political instability, poor economy, technological know-how, and the non-promising socio-political environment. The mentioned exogenous factors were hardly considered in the previous studies on scheduling problem related to due date determination in job shops. This study has filled the gap created in the past studies by developing a dynamic model that incorporated the exogenous factors for accurate determination of due dates for varying jobs complexity. Real data from six job shops selected from the different part of Nigeria, were used to test the efficacy of the model, and the outcomes were analyzed statistically. The results of the analyzes showed that the model is more promising in determining accurate due dates than the traditional models deployed by many job shops in terms of patronage and lead times minimization.

Keywords: due dates prediction, improved performance, customer satisfaction, dynamic model, exogenous factors, job shops

Procedia PDF Downloads 381

Authors: Rawan K. Al-Duaij, Salem A. Al-Salem

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Projects, the unique and temporary process of achieving a set of requirements have always been challenging; Planning the schedule and budget, managing the resources and risks are mostly driven by a similar past experience or the technical consultations of experts in the matter. With that complexity of Projects in Scope, Time, and execution environment, Adjustment Orders are tools to reflect changes to the original project parameters after Contract signature. Adjustment Orders are the official/legal amendments to the terms and conditions of a live Contract. Reasons for issuing Adjustment Orders arise from changes in Contract scope, technical requirement and specification resulting in scope addition, deletion, or alteration. It can be as well a combination of most of these parameters resulting in an increase or decrease in time and/or cost. Most business leaders (handling projects in the interest of the owner) refrain from using Adjustment Orders considering their main objectives of staying within budget and on schedule. Success in managing the changes results in uninterrupted execution and agreed project costs as well as schedule. Nevertheless, this is not always practically achievable. In this paper, a detailed study through utilizing Industrial Engineering & Systems Management tools such as Six Sigma, Data Analysis, and Quality Control were implemented on the organization’s five years records of the issued Adjustment Orders in order to investigate their prevalence, and time and cost impact. The analysis outcome revealed and helped to identify and categorize the predominant causations with the highest impacts, which were considered most in recommending the corrective measures to reach the objective of minimizing the Adjustment Orders impacts. Data analysis demonstrated no specific trend in the AO frequency in past five years; however, time impact is more than the cost impact. Although Adjustment Orders might never be avoidable; this analysis offers’ some insight to the procedural gaps, and where it is highly impacting the organization. Possible solutions are concluded such as improving project handling team’s coordination and communication, utilizing a blanket service contract, and modifying the projects gate system procedures to minimize the possibility of having similar struggles in future. Projects in the Oil and Gas sector are always evolving and demand a certain amount of flexibility to sustain the goals of the field. As it will be demonstrated, the uncertainty of project parameters, in adequate project definition, operational constraints and stringent procedures are main factors resulting in the need for Adjustment Orders and accordingly the recommendation will be to address that challenge.

Keywords: adjustment orders, data analysis, oil and gas sector, systems management

Procedia PDF Downloads 131