Search results for: modelling approach

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Raquel Nieto, Marta Vázquez, Anita Drumond, Luis Gimeno

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One of the hot spots of climate change is the increment of ocean evaporation. The best estimation of evaporation, OAFlux data, shows strong increasing trends in evaporation from the oceans since 1978, with peaks during the hemispheric winter and strongest along the paths of the global western boundary currents and any inner Seas. The transport of moisture from oceanic sources to the continents is the connection between evaporation from the ocean and precipitation over the continents. A key question is to try to relate evaporative source regions over the oceans where trends have occurred in the last decades with their sinks over the continents to check if there have been also any trends in the precipitation amount or its characteristics. A Lagrangian approach based on FLEXPART and ERA-interim data is used to establish this connection. The analyzed period was 1980 to 2012. Results show that there is not a general pattern, but a significant agreement was found in important areas of climate interest.

Keywords: ocean evaporation, Lagrangian approaches, contiental precipitation, Europe

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Authors: Rakesh Choudhary, Ajay Kumar, Deepak Sharma

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The main goal of this paper is to investigate the challenges and benefits of IoT integration in biogas production. This overview explains how the inclusion of IoT can enhance biogas production efficiency. Therefore, such collected data can be explored by advanced analytics, including Artificial intelligence (AI) and Machine Learning (ML) algorithms, consequently improving bio-energy processes. To boost biogas generation efficiency, this report examines the use of IoT devices for real-time data collection on key parameters, e.g., pH, temperature, gas composition, and microbial growth. Real-time monitoring through big data has made it possible to detect diverse, complex trends in the process of producing biogas. The Informed by advanced analytics can also help in improving bio-energy production as well as optimizing operational conditions. Moreover, IoT allows remote observation, control and management, which decreases manual intervention needed whilst increasing process effectiveness. Such a paradigm shift in the incorporation of IoT technologies into biogas production systems helps to achieve higher productivity levels as well as more practical biomass quality biomethane through real-time monitoring-based proactive decision-making, thus driving continuous performance improvement.

Keywords: internet of things, biogas, renewable energy, sustainability, anaerobic digestion, real-time monitoring, optimization

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Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

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Authors: Radim Sip, Denisa Denglerova

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It’s impossible to capture complex phenomena, such as inclusion, with reductionism. The most common form of reductionism is the objectivist approach, where processes and relationships are reduced to entities and clearly outlined phases, with a consequent search for relationships between them. Constructivism as a paradigm and situational analysis as a methodological research portfolio represent a way to avoid the dominant objectivist approach. They work with a situation, i.e. with the essential blending of actors and their environment. Primary transactions are taking place between actors and their surroundings. Researchers create constructs based on their need to solve a problem. Concepts therefore do not describe reality, but rather a complex of real needs in relation to the available options how such needs can be met. For examination of a complex problem, corresponding methodological tools and overall design of the research are necessary. Using an original research on inclusion in the Czech Republic as an example, this contribution demonstrates that inclusion is not a substance easily described, but rather a relationship field changing its forms in response to its actors’ behaviour and current circumstances. Inclusion consists of dynamic relationship between an ideal, real circumstances and ways to achieve such ideal under the given circumstances. Such achievement has many shapes and thus cannot be captured by description of objects. It can be expressed in relationships in the situation defined by time and space. Situational analysis offers tools to examine such phenomena. It understands a situation as a complex of dynamically changing aspects and prefers relationships and positions in the given situation over a clear and final definition of actors, entities, etc. Situational analysis assumes creation of constructs as a tool for solving a problem at hand. It emphasizes the meanings that arise in the process of coordinating human actions, and the discourses through which these meanings are negotiated. Finally, it offers “cartographic tools” (situational maps, socials worlds / arenas maps, positional maps) that are able to capture the complexity in other than linear-analytical ways. This approach allows for inclusion to be described as a complex of phenomena taking place with a certain historical preference, a complex that can be overlooked if analyzed with a more traditional approach.

Keywords: constructivism, situational analysis, objective realism, reductionism, inclusion

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Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir

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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

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Authors: Tingting Huang, Sha Li, Geoffrey Griffiths, Martin Lukac, Jianning Zhu

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Territorial landscapes have experienced a gradual loss of their typical characteristics during long-term human activities. In order to protect the integrity of regional landscapes, it is necessary to characterize, evaluate and protect them in a graded manner. The study takes Fujian, China, as an example and classifies the landscape characters of the site at the regional scale, middle scale, and detailed scale. A multi-scale approach combining parametric and holistic approaches is used to classify and partition the landscape character types (LCTs) and landscape character areas (LCAs) at different scales, and a multi-element landscape assessment approach is adopted to explore the conservation strategies of the landscape character. Firstly, multiple fields and multiple elements of geography, nature and humanities were selected as the basis of assessment according to the scales. Secondly, the study takes a parametric approach to the classification and partitioning of landscape character, Principal Component Analysis, and two-stage cluster analysis (K-means and GMM) in MATLAB software to obtain LCTs, combines with Canny Operator Edge Detection Algorithm to obtain landscape character contours and corrects LCTs and LCAs by field survey and manual identification methods. Finally, the study adopts the Landscape Sensitivity Assessment method to perform landscape character conservation analysis and formulates five strategies for different LCAs: conservation, enhancement, restoration, creation, and combination. This multi-scale identification approach can efficiently integrate multiple types of landscape character elements, reduce the difficulty of broad-scale operations in the process of landscape character conservation, and provide a basis for landscape character conservation strategies. Based on the natural background and the restoration of regional characteristics, the results of landscape character assessment are scientific and objective and can provide a strong reference in regional and national scale territorial spatial planning.

Keywords: parameterization, multi-scale, landscape character identify, landscape character assessment

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Authors: Maria Valeria De Bonis, Gianpaolo Ruocco

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Nowadays, computational modeling is paving new design and verification ways in a number of industrial sectors. The technology is ripe to challenge some case in the Bioengineering and Medicine frameworks: for example, looking at the strategical and ethical importance of oncology research, efforts should be made to yield new and powerful resources to tumor knowledge and understanding. With these driving motivations, we approach this gigantic problem by using some standard engineering tools such as the mathematics behind the biomass transfer. We present here some bacterial colonization studies in complex structures. As strong analogies hold with some tumor proliferation, we extend our study to a benchmark case of solid tumor. By means of a commercial software, we model biomass and energy evolution in arbitrary media. The approach will be useful to cast virtualization cases of cancer growth in human organs, while augmented reality tools will be used to yield for a realistic aid to informed decision in treatment and surgery.

Keywords: bacteria, simulation, tumor, precision medicine

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Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

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Authors: Qi Wu, Dian-Yong Chen, Feng-Kun Guo, Gang Li

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In the past decade, a growing number of new hadron states have been observed, which are dubbed as XYZ states in the heavy quarkonium mass regions. In this work, we present our study on the production of some new hadron states. In particular, we investigate the processes Υ(5S,6S)→ Zb (10610)/Zb (10650)π, Bc→ Zc (3900)/Zc (4020)π and Λb→ Pc (4312)/Pc (4440)/Pc (4457)K. (1) For the production of Zb (10610)/Zb (10650) from Υ(5S,6S) decay, two types of bottom-meson loops were discussed within a nonrelativistic effective field theory. We found that the loop contributions with all intermediate states being the S-wave ground state bottom mesons are negligible, while the loops with one bottom meson being the broad B₀* or B₁' resonance could provide the dominant contributions to the Υ(5S)→ Zb⁽'⁾ π. (2) For the production of Zc (3900)/Zc (4020) from Bc decay, the branching ratios of Bc⁺→ Z (3900)⁺ π⁰ and Bc⁺→ Zc (4020)⁺ π⁰ are estimated to be of order of 10⁽⁻⁴⁾ and 10⁽⁻⁷⁾ in an effective Lagrangian approach. The large production rate of Zc (3900) could provide an important source of the production of Zc (3900) from the semi-exclusive decay of b-flavored hadrons reported by D0 Collaboration, which can be tested by the exclusive measurements in LHCb. (3) For the production of Pc (4312), Pc (4440) and Pc (4457) from Λb decay, the ratio of the branching fraction of Λb→ Pc K was predicted in a molecular scenario by using an effective Lagrangian approach, which is weakly dependent on our model parameter. We also find the ratios of the productions of the branching fractions of Λb→ Pc K and Pc→ J/ψ p can be well interpreted in the molecular scenario. Moreover, the estimated branching fractions of Λb→ Pc K are of order 10⁽⁻⁶⁾, which could be tested by further measurements in LHCb Collaboration.

Keywords: effective Lagrangian approach, hadron loops, molecular states, new hadron states

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Authors: A. Brahma

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Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

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Authors: Nadine Wills

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The whole life thinking of buildings (independent if these are commercial properties or residential properties) will raise if incentive systems are provided to investors, planners and users. The Use of Building Information Modelling (BIM)-Systems offers planners the possibility to plan and re-plan buildings for decades after a period of utilization without spending many capacities. The strategy-incentive should be to plan the building in a way that makes rescheduling possible by changing just parameters in the system and not re-planning the whole building. If users receive the chance to patient incentive systems, the building stock will have a long life period. Business models of tenant electricity or self-controlled operating costs are incentive systems for building –users to let fixed running costs decline without producing damages due to wrong purposes. BIM is the controlling body to ensure that users do not abuse the incentive solution and take negative influence on the building stock. The investor benefits from the planner’s and user’s incentives: the fact that the building becomes useful for the whole life without making unnecessary investments provides possibilities to make investments in different assets. Moreover, the investor gains the facility to achieve higher rents by merchandise the property with low operating costs. To execute BIM offers whole property life cycles.

Keywords: BIM, incentives, life cycle, sustainability

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Authors: Tony Mann

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This paper sets out the case for involving and engaging employees/workers/stakeholders/staff in any significant change that is being considered by the senior executives of the organization. It establishes the rationale, the approach, the methodology of engagement and the benefits of a participative approach. It challenges the new norm of imposing change for fear of resistance and instead suggests that involving people has better outcomes and a longer-lasting impact. Various strategic models are introduced and illustrated to explain how the process can be most effective. The paper highlights one model in particular (the Process Iceberg® Organizational Change model) that has proven to be instrumental in developing effective change. Its use is demonstrated in its various forms and explains why so much change fails to address the key elements and how we can be more productive in managing change. ‘Participation’ in change is too often seen as negative, expensive and unwieldy. The paper aims to show that another model: UIA=O+E, can offset the difficulties and, in fact, produce much more positive and effective change.

Keywords: facilitation, stakeholders, buy-in, digital workshops

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Authors: Lukholo Raxangana

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Fourth Industrial Revolution (4IR)-era teaching offers in-service mathematics teachers opportunities to use blended approaches to engage learners while teaching mathematics. This study explores in-service high school teachers' experiences with a blended teaching approach to mathematics. This qualitative case study involved eight pre-service teachers from four selected schools in the Sedibeng West District of the Gauteng Province. The study used the community of inquiry model as its analytical framework for data analysis. Data collection was through semi-structured interviews and focus-group discussions to explore in-service teachers' experiences with the influence of blended teaching (BT) on learning mathematics. The study results are the impact of load-shedding, benefits of BT, and perceptions of in-service and hindrances of BT. Based on these findings, the study recommends that further research should focus on developing data-free BT tools to assist during load-shedding, regardless of location.

Keywords: bended teaching, teachers, in-service, and mathematics

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Authors: Sahbi Farhani

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This study investigates the relationship between external debt and military spending in case of India over the period of 1970–2012. In doing so, we have applied the structural break unit root tests to examine stationarity properties of the variables. The Auto-Regressive Distributed Lag (ARDL) bounds testing approach is used to test whether cointegration exists in presence of structural breaks stemming in the series. Our results indicate the cointegration among external debt, military spending, debt servicing, and economic growth. Moreover, military spending and debt servicing add in external debt. Economic growth helps in lowering external debt. The Vector Error Correction Model (VECM) analysis and Granger causality test reveal that military spending and economic growth cause external debt. The feedback effect also exists between external debt and debt servicing in case of India.

Keywords: external debt, military spending, ARDL approach, India

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Authors: Zoran Jovanovic, Zoran Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, results concerning flame propagation of various fuels in a particular combustion chamber with four tilted valves were elucidated. Flame propagation was represented by the evolution of spatial distribution of temperature in various cut-planes within combustion chamber while the flame front location was determined by dint of zones with maximum temperature gradient. The results presented are only a small part of broader on-going scrutinizing activity in the field of multidimensional modeling of reactive flows in combustion chambers with complicated geometries encompassing various models of turbulence, different fuels and combustion models. In the case of turbulence two different models were applied i.e. standard k-ε model of turbulence and k-ξ-f model of turbulence. In this paper flame propagation results were analyzed and presented for two different hydrocarbon fuels, such as CH4 and C8H18. In the case of combustion all differences ensuing from different turbulence models, obvious for non-reactive flows are annihilated entirely. Namely the interplay between fluid flow pattern and flame propagation is invariant as regards turbulence models and fuels applied. Namely the interplay between fluid flow pattern and flame propagation is entirely invariant as regards fuel variation indicating that the flame propagation through unburned mixture of CH4 and C8H18 fuels is not chemically controlled.

Keywords: automotive flows, flame propagation, combustion modelling, CNG

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Authors: Ibrahim A. Alhammad, Suleiman A. Al-Otaibi, Khalid S. Al-Gahtani, Naïf Al-Otaibi, Abdulaziz A. Bubshait

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In the last decade, the use of project delivery system of design build engineering contracts is increasing in North America due to the reasons of reducing the project duration and minimizing costs. The shift from traditional approach of Design-Bid-Build to Design-Build contracts have been attributed to many factors such as evolution of the regulatory and legal frameworks governing the engineering contracts and improvement in integrating design and construction. The aforementioned practice of contracting is more appropriate in North America; yet, it may not be the case in Saudi Arabia where the traditional approach of construction contracting remains dominant. The authors believe there are number of factors related to the gaps in the level of sophistication of the engineering and management of the construction projects in both countries. A step towards improving the Saudi construction practice by adopting the new trend of construction contracting, this paper identifies the reasons why Design/Build form of contracting are not frequently utilized. A field survey, which includes the questionnaire addressing the research problem, is distributed to three main parties of the construction contracts: clients, consultants, and contractors. The analyzed collected data were statistically sufficient to finding the reasons of not adopting the new trend of good practice of deign build approach in Saudi Arabia. In addition, the reasons are: (1) lack of regulation and legal framework; (2) absence of clear criteria of the owner for the trade-off between competing contractors, (3) and lack of experience, knowledge and skill.

Keywords: design built projects, Saudi Arabia, GCC, mega projects

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Authors: Margarita Mayoral-Villa, J. Klapp, L. Di G. Sigalotti, J. E. V. Guzmán

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Automated learning techniques are widely applied in the energy sector to address challenging problems from a practical point of view. To this end, we discuss the implementation of a Message Passing algorithm (MPNN)within a Graph Neural Network(GNN)to leverage the neighborhood of a set of nodes during the aggregation process. This approach enables the characterization of multiphase diffusion processes in the reservoir, such that the flow paths underlying the interconnections between multiple wells may be inferred from previously available data on flow rates and bottomhole pressures. The results thus obtained compare favorably with the predictions produced by the Reduced Order Capacitance-Resistance Models (CRM) and suggest the potential of MPNNs to enhance the robustness of the forecasts while improving the computational efficiency.

Keywords: multiphase diffusion, message passing neural network, well interconnection, interwell connectivity, graph neural network, capacitance-resistance models

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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Authors: Shreya Poddar

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Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice.

Keywords: AI-driven legal drafting, legal automation, futureoflegalwork, largelanguagemodels

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Authors: Prandesha Govender, Chris Cloete

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Purpose: The objective of the paper is to develop a tool for the evaluation of the financial risk of a shopping center. Methodology: Important factors that indicate the success of a shopping center were identified from the available literature. Weights were allocated to these factors and a risk rating was calculated for 505 shopping centers in the largest province in South Africa by taking the factor scores, factor weights, and category weights into account. The ratings for ten randomly selected shopping centers were correlated with consumer feedback and standardized against the ECAI (External Credit Assessment Institutions) data for the same centers. The ratings were also mapped to corporates with the same risk rating to provide a better intuitive assessment of the meaning of the inherent risk of each center. Results: The proposed risk tool shows a strong linear correlation with consumer views and can be compared to expert opinions, such as that of fund managers and REITs. Interpretation of the tool was also illustrated by correlating the risk rating of selected shopping centers to the risk rating of reputable and established entities. Conclusions: The proposed Shopping Centre Risk Tool, used in conjunction with financial inputs from the relevant center, should prove useful to an investor when the desirability of investment in or expansion, renovation, or purchase of a shopping center is being considered.

Keywords: risk, shopping centres, risk modelling, investment, rating tool, rating scale

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Authors: Joseph Siani

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Over the last decades, dissatisfaction with global indicators of economic performance, such as GDP (Gross Domestic Product) per capita, has shifted the attention to what is now referred to as multidimensional poverty. In this framework, poverty goes beyond income to incorporate aspects of well-being not captured by income measures alone. This paper applies the totally fuzzy approach to estimate the fuzzy index of poverty (FIP) in fourteen Sub-Saharan African (SSA) countries using Demographic and Health Survey (DHS) data and explores whether pictures created by the standard headcount ratio at $1.90 a day and the fuzzy index of poverty tell a similar story. The results suggest that there is indeed considerable mismatch between poverty headcount and the fuzzy index of multidimensional poverty, meaning that the majority of the most deprived people (as identified by the fuzzy index of multidimensional poverty) would not be identified by the poverty headcount ratio. Moreover, we find that poverty is distributed differently by colonial heritage (language). In particular, the most deprived countries in SSA are French-speaking.

Keywords: fuzzy set approach, multidimensional poverty, poverty headcount, overlap, Sub-Saharan Africa

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Authors: N. G. Thangan, A. B. Deoghare, P. M. Padole

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Computational Fluid Dynamics (CFD) aids in modeling the prototype of a real world processes. CFD approach is useful in predicting the fluid flow, heat transfer mass transfer and other flow related phenomenon. In present study, hydrodynamic characteristics of gas-solid cylindrical fluidized bed is compared with conical fluidized beds. A 2D fluidized bed consists of different configurations of particle size of iron oxide, bed height and superficial velocities of nitrogen. Simulations are performed to capture the complex physics associated with it. The Eulerian multiphase model is prepared in ANSYS FLUENT v.14 which is used to simulate fluidization process. It is analyzed with nitrogen as primary phase and iron oxide as secondary phase. The bed hydrodynamics is assessed prominently to examine effect on fluidization time, pressure drop, minimum fluidization velocity, and gas holdup in the system.

Keywords: fluidized bed, bed hydrodynamics, Eulerian multiphase approach, computational fluid dynamics

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Authors: Abdulrahman S. Alqahtani

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The revolution of computing and networks could revolutionise terrorism in the same way that it has brought about changes in other aspects of life. The modern technological era has faced countries with a new set of security challenges. There are many states and potential adversaries who have the potential and capacity in cyberspace, which makes them able to carry out cyber-attacks in the future. Some of them are currently conducting surveillance, gathering and analysis of technical information, and mapping of networks and nodes and infrastructure of opponents, which may be exploited in future conflicts. This poster presents the results of the quantitative study (survey) to test the validity of the proposed theoretical framework for the cyber terrorist threats. This theoretical framework will help to in-depth understand these new digital terrorist threats. It may also be a practical guide for managers and technicians in critical infrastructure, to understand and assess the threats they face. It might also be the foundation for building a national strategy to counter cyberterrorism. In the beginning, it provides basic information about the data. To purify the data, reliability and exploratory factor analysis, as well as confirmatory factor analysis (CFA) were performed. Then, Structural Equation Modelling (SEM) was utilised to test the final model of the theory and to assess the overall goodness-of-fit between the proposed model and the collected data set.

Keywords: cyberterrorism, critical infrastructure, , national security, theoretical framework, terrorism

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Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

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Authors: Patrick Ahern, David Collery

Abstract:

The implementation of lean thinking in the manufacturing industry revolutionized the traditional approach to large-scale production through the process of identifying the waste in each task and putting in place mitigation measures to eliminate the waste in all its forms. The Irish construction industry, however, has been much slower to adopt the principles of lean, opting instead to stick with the traditional approach to construction project delivery which is inherently wasteful. Lean thinking holds the potential to revolutionize the construction industry in a similar manner to the adoption of lean manufacturing. Lean principles present opportunities for reduced project duration, reduced project cost, improved quality, and elimination of re-works and non-value-added activities. The following research has been designed to accumulate research data through available literature, electronic surveys, and interviews. The results show an industry reluctant to accept change and an undefined path to successful lean construction implementation.

Keywords: barriers, lean construction, lean implementation, lean manufacturing, lean philosophy

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Authors: Obiora E. Anisiji, Jeremiah L. Chukwuneke, Chinonso H. Achebe, Paul C. Okolie

Abstract:

This work developed a mathematical model of a biogas plant from a mechanistic point of view, for urban area clean energy requirement. It aimed at integrating thermodynamics; which deals with the direction in which a process occurs and Biochemical kinetics; which gives the understanding of the rates of biochemical reaction. The mathematical formulation of the proposed gas plant follows the fundamental principles of thermodynamics, and further analysis were accomplished to develop an algorithm for evaluating the plant performance preferably in terms of daily production capacity. In addition, the capacity of the plant is equally estimated for a given cycle of operation and presented in time histories. A nominal 1500m3 biogas plant was studied characteristically and its performance efficiency evaluated. It was observed that the rate of biogas production is essentially a function of enthalpy ratio, the reactor temperature, pH, substrate concentration, rate of degradation of the biomass, and the accumulation of matter in the system due to bacteria growth. The results of this study conform to a very large extent with reported empirical data of some existing plant and further model validations were conducted in line with classical records found in literature.

Keywords: anaerobic digestion, biogas plant, biogas production, bio-reactor, energy, fermentation, rate of production, temperature, therm

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Authors: Jaypalsinh B. Parmar, Pintu Nakrani, Ashish Chaurasia

Abstract:

Digital Elevation Model (DEM) is considered as an important data in GIS-based terrain analysis for many applications and assessment of processes such as environmental and climate change studies, hydrologic modelling, etc. Vertical accuracy of DEM having geographically dynamic nature depends on different parameters which affect the model simulation outcomes. Vertical accuracy assessment in Indian landscape especially in low-lying coastal urban terrain such as lower Tapi Basin is very limited. In the present study, attempt has been made to evaluate the vertical accuracy of 30m resolution open source Indian National Cartosat-1 DEM v3 for Lower Tapi Basin (LTB) from western India. The extensive field investigation is carried out using stratified random fast static DGPS survey in the entire study region, and 117 high accuracy ground control points (GCPs) have been obtained. The above open source DEM was compared with obtained GCPs, and different statistical attributes were envisaged, and vertical error histograms were also evaluated.

Keywords: CartoDEM, Digital Elevation Model, GPS, lower Tapi basin

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Authors: Tim Wollert, Fabian Behrendt

Abstract:

Value Stream Management (VSM) is a widely used methodology in the context of Lean Management for improving end-to-end material and information flows from a supplier to a customer from a company’s perspective. Whereas the design principles, e.g. Pull, value-adding, customer-orientation and further ones are still valid against the background of an increasing digitalized and dynamic environment, the methodology itself for mapping a value stream is characterized as time- and resource-intensive due to the high degree of manual activities. The digitalization of processes in the context of Industry 4.0 enables new opportunities to reduce these manual efforts and make the VSM approach more agile. The paper at hand aims at providing a modular data and calculation framework, utilizing the available business data, provided by information and communication technologies for automizing the value stream mapping process with focus on the manufacturing process.

Keywords: lean management 4.0, value stream management (VSM) 4.0, dynamic value stream mapping, enterprise resource planning (ERP)

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Authors: Kousay Abid

Abstract:

The aim of this paper is to better understand talent and talent management (TM) in small French companies as well as in medium-sized ones (SME). While previous empirical investigations have largely focused on multinationals and big companies and concentrated on the Anglo-Saxon context, we focus on the pressing need for implementing TM strategies and practices, not only on a new ground of SME but also within a new European context related to France and the French context. This study also aims at understanding strategies adopted by those firms as means to attract, retain, maintain and to develop talents. We contribute to TM issues by adopting a multilevel approach, holding the goal of reaching a global holistic vision of interactions between various levels while applying TM, to make it more and more familiar to us. A qualitative research methodology based on a multiple-case study design, bottomed firstly on a qualitative survey and secondly on two in-depth case study, both built on interviews, will be used in order to develop an ideal analysis for TM strategies and practices. The findings will be based on data collected from more than 15 French SMEs. Our theoretical contributions are the fruit of context considerations and the dynamic of multilevel approach. Theoretically, we attempt first to clarify how talents and TM are seen and defined in French SMEs and consequently to enrich the literature on TM in SMEs out of the Anglo-Saxon context. Moreover, we seek to understand how SMEs manage jointly their talents and their TM strategies by setting up this contextualized pilot study. As well, we focus on the systematic TM model issue from French SMEs. Our prior managerial goal is to shed light on the need for TM to achieve a better management of these organizations by directing leaders to better identify the talented people whom they hold at all levels. In addition, our TM systematic model strengthens our analysis grid as recommendations for CEO and Human Resource Development (HRD) to make them rethink about the companies’ HR business strategies. Therefore, our outputs present a multiple lever of action that should be taken into consideration while reviewing HR strategies and systems, as well as their impact beyond organizational boundaries.

Keywords: french context, multilevel approach, small and medium-sized enterprises, talent management

Procedia PDF Downloads 179