Search results for: collaborative learning approach

Authors: Florian Engel

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Only with a radical change to an intrinsically motivated project team, through giving the employees the freedom for autonomy, mastery and purpose, it is then possible to develop excellent products. With these changes, combined with using a rapid application development approach, the group of users serves as an important indicator to test the market needs, rather than only as the stakeholders for requirements.

Keywords: intrinsic motivation, requirements elicitation, self-directed work, stakeholder participation

Procedia PDF Downloads 325

Authors: S. Fröhlich, M. Herold, M. Allmer

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Early stage quantitative analysis of host cell protein (HCP) variations is challenging yet necessary for comprehensive bioprocess development. High resolution mass spectrometry (HRMS) provides a high-end technology for accurate identification alongside with quantitative information. Hereby we describe a flexible HRMS assay platform to quantify HCPs relevant in microbial expression systems such as E. Coli in both up and downstream development by means of MVDA tools. Cell pellets were lysed and proteins extracted, purified samples not further treated before applying the SMART tryptic digest kit. Peptides separation was optimized using an RP-UHPLC separation platform. HRMS-MSMS analysis was conducted on an Orbitrap Velos Elite applying CID. Quantification was performed label-free taking into account ionization properties and physicochemical peptide similarities. Results were analyzed using SIEVE 2.0 (Thermo Fisher Scientific) and SIMCA (Umetrics AG). The developed HRMS platform was applied to an E. Coli expression set with varying productivity and the corresponding downstream process. Selected HCPs were successfully quantified within the fmol range. Analysing HCP networks based on pattern analysis facilitated low level quantification and enhanced validity. This approach is of high relevance for high-throughput screening experiments during upstream development, e.g. for titer determination, dynamic HCP network analysis or product characterization. Considering the downstream purification process, physicochemical clustering of identified HCPs is of relevance to adjust buffer conditions accordingly. However, the technology provides an innovative approach for label-free MS based quantification relying on statistical pattern analysis and comparison. Absolute quantification based on physicochemical properties and peptide similarity score provides a technological approach without the need of sophisticated sample preparation strategies and is therefore proven to be straightforward, sensitive and highly reproducible in terms of product characterization.

Keywords: process analytical technology, mass spectrometry, process characterization, MVDA, pattern recognition

Procedia PDF Downloads 238

Authors: João Madureira, Ricardo Lagido, Inês Sousa, Fraunhofer Portugal

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Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.

Keywords: inertial measurement unit (IMU), global positioning system (GPS), smartphone, surfing performance

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Authors: Siti Aminatu Zuhria

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On wet coffee processing can improve the quality of coffee, but the coffee liquid waste that can pollute the environment. Liquid waste a lot of coffee resulting from the stripping and washing the coffee. This research will be carried out the process of handling liquid waste stripping coffee from the coffee skin with media phytoremediation using plants kiambang. The purpose of this study was to determine the characteristics of the coffee liquid waste and plant phytoremediation kiambang as agent in various concentrations of liquid waste coffee as well as determining the most optimal concentration in the improved quality of waste water quality standard approach. This research will be conducted through two stages, namely the preliminary study and the main study. In a preliminary study aims to determine the ability of the plant life kiambang as phytoremediation agent in the media well water, distilled water and liquid waste coffee. The main study will be conducted wastewater dilution and coffee will be obtained COD concentration variations. Results are expected at this research that can determine the ability of plants kiambang as an agent for phytoremediation in wastewater treatment with various concentrations of waste and the most optimal concentration in the improved quality of waste water quality standard approach.

Keywords: wet coffee processing, phytoremediation, Kiambang plant, variation concentration liquid waste

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Authors: Z. Gharaee

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Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Bintou Jobe

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Background: The research is focused on the concept of equality, diversity, and inclusion (EDI) and the need to achieve equity by treating individuals according to their circumstances and needs. The research is rooted in the UK Equality Act 2010, which emphasizes the importance of equal opportunities for all individuals regardless of their background and social life. However, inequality persists in society, particularly for those from minority backgrounds who face discrimination. Research Aim: The aim of this research is to promote equality, diversity, and inclusion by encouraging the regeneration of minds and the eradication of stereotypes. The focus is on promoting good Equality, Diversity and Inclusion practices in various settings, including schools, colleges, universities, and workplaces, to create environments where every individual feels a sense of belonging. Methodology: The research utilises a literature review approach to gather information on promoting inclusivity, diversity, and inclusion. Findings: The research highlights the significance of promoting equality, diversity, and inclusion practices to ensure that individuals receive the respect and dignity they deserve. It emphasises the importance of treating individuals based on their unique circumstances and needs rather than relying on stereotypes. The research also emphasises the benefits of diversity and inclusion in enhancing innovation, creativity, and productivity. The theoretical importance of this research is to raise awareness about the importance of regenerating minds, challenging stereotypes, and promoting equality, diversity, and inclusion. The emphasis is on treating individuals based on their circumstances and needs rather than relying on generalizations. Diversity and inclusion are beneficial in different settings, as highlighted by the research. By raising awareness about the importance of mind regeneration, eradicating stereotypes, and promoting equality, diversity, and inclusion, this research makes a significant contribution to the subject area. It emphasizes the necessity of treating individuals based on their unique circumstances instead of relying on generalizations. However, the methodology could be strengthened by incorporating primary research to complement the literature review approach. Data Collection and Analysis Procedures: The research utilised a literature review approach to gather relevant information on promoting inclusivity, diversity, and inclusion. NVivo software application was used to analysed and synthesize the findings to identify themes and support the research aim and objectives. Question Addressed: This research addresses the question of how to promote inclusivity, diversity, and inclusion and reduce the prevalence of stereotypes and prejudice. It explores the need to treat individuals based on their unique circumstances and needs rather than relying on generic assumptions. Encourage individuals to adopt a more inclusive approach. Provide managers with responsibility and training that helps them understand the importance of their roles in shaping the workplace culture. Have an equality, diversity, and inclusion manager from a majority background at the senior level who can speak up for underrepresented groups and flag any issues that need addressing. Conclusion: The research emphasizes the importance of promoting equality, diversity, and inclusion practices to create a fairer society. It highlights the need to challenge stereotypes, treat individuals according to their circumstances and needs, and promote a culture of respect and dignity.

Keywords: equality, fairer society, inclusion, diversity

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Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

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This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

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Authors: Susanna Menis

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The context of this study revolves around the theme of consent and the construction of unlawfulness in judicial decisions. It aims to explore the formation of societal perceptions of unlawfulness within the context of consensual sexual acts leading to harmful consequences. This study investigates how judges create legal rules that reflect social solidarity and protect against violence. Specifically, the research aims to understand the justification behind criminalising consensual sexual activity when categorised under different offences. The main question addressed in this study will evaluate the way judges create legal rules that they believe reflect social solidarity and protect against violence. The study employs a historical genealogy approach as its methodology. This approach allows for tracing back the original formation of societal perspectives on unlawfulness, thus highlighting the socially constructed nature of the present understanding. The data for this study will be collected through an extensive literature review, examining historical legal cases and documents that shape the understanding of unlawfulness. This will provide a comprehensive view of how social attitudes toward private sexual relations influenced the creation of legal rules. The theoretical importance of this research lies in its contribution to socio-legal scholarship. This study adds to the existing knowledge on the topic by exploring questions of unconscious bias and its origins. The findings shed light on how and why individuals possess unconscious biases, particularly within the judicial system. In conclusion, this study investigates judicial decisions concerning consensual sexual acts and the construction of unlawfulness. By employing a historical genealogy approach, the research sheds light on how judges create legal rules that reflect social solidarity and aim to protect against violence. The theoretical importance of this study lies in its contribution to understanding unconscious bias and its origins within the judicial system. Through data collection and analysis procedures, this study aims to provide valuable insights into the formation of social attitudes towards private sexual relations and its impact on legal rulings.

Keywords: consent, sexual offences, offences against the person, legal genealogy, social construct

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Authors: M. S. Maglasang, S. O. Palacio, L. P. Ogdoc

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Business Process Outsourcing has been one of the fastest growing and emerging industry in the Philippines today. Unlike most of the contact service centers, more popularly known as "call centers", The BPO Industry’s primary outsourced service is performing audits of the global clients' logistics. As a service industry, manpower is considered as the most important yet the most expensive resource in the company. Because of this, there is a need to maximize the human resources so people are effectively and efficiently utilized. The main purpose of the study is to optimize the current manpower resources through effective distribution and assignment of different types of bills to the different skill-level of data entry operators. The assignment model parameters include the average observed time matrix gathered from through time study, which incorporates the learning curve concept. Subsequently, a simulation model was made to duplicate the arrival rate of demand which includes the different batches and types of bill per day. Next, a mathematical linear programming model was formulated. Its objective is to minimize direct labor cost per bill by allocating the different types of bills to the different skill-levels of operators. Finally, a hypothesis test was done to validate the model, comparing the actual and simulated results. The analysis of results revealed that the there’s low utilization of effective capacity because of its failure to determine the product-mix, skill-mix, and simulated demand as model parameters. Moreover, failure to consider the effects of learning curve leads to overestimation of labor needs. From 107 current number of operators, the proposed model gives a result of 79 operators. This results to an increase of utilization of effective capacity to 14.94%. It is recommended that the excess 28 operators would be reallocated to the other areas of the department. Finally, a manpower capacity planning model is also recommended in support to management’s decisions on what to do when the current capacity would reach its limit with the expected increasing demand.

Keywords: optimization modelling, linear programming, simulation, time and motion study, capacity planning

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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Transport infrastructure assets are key components of the national asset portfolio. The decision to invest in a new infrastructure in transports could take from a few years to some decades. This is mainly because of the need to reserve and spent many capitals, the long payback period, the number of the stakeholders involved in decision process and –many times- the investment and business risks are high. Therefore, the decision assessment framework is an essential challenge linked with the key decision factors meet the stakeholder expectations highlighting project trade-offs, financial risks, business uncertainties and market limitations. This paper examines the decision process for new transport infrastructure projects in cross border regions, where a wide range of stakeholders with different expectation is involved. According to a consequences analysis systemic approach, the relationship of transport infrastructure development, economic system development and stakeholder expectation is analyzed. Adopting the on system of system methodological approach, the decision making framework, variables, inputs and outputs are defined, highlighting the key shareholder’s role and expectations. The application provides the methodology outputs presenting the proposed decision framework for a strategic railway project in north Greece deals with the upgrade of the existing railway corridor connecting Greece, Turkey and Bulgaria.

Keywords: decision making, system of system, cross-border, infrastructure project

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

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Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

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Authors: Aaidha Hammad

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The age a child to be exposed to a second language is a controversial issue in communities such as the Maldives where English is taught as a second language. It has been observed that different stakeholders have different viewpoints towards the issue. Some believe that the earlier children are exposed to a second language, the better they learn, while others disagree with the notion. Hence, this case study investigates whether children learn a second language better when they are exposed at an earlier age or not. The spoken and written data collected confirm that earlier exposure helps in mastering the sound pattern and speaking fluency with more native-like accent, while a later age is better for learning more abstract and concrete aspects such as grammar and syntactic rules.

Keywords: age, fluency, second language acquisition, development of language skills

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Authors: Recep Sait Arpat, Hakan Güreşci

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Emergency, disaster and crisis management terms are generally perceived as the same processes. This conflict effects the approach and delegating policy of the political order. Crisis management starts in the aftermath of the mismanagement of disaster and emergency. In the light of the information stated above in this article Turkey and United Kingdom(UK)’s crisis management systems are analyzed. This article’s main aim is to clarify the main points of the emergency management system of United Kingdom and Turkey’s disaster management system by comparing them. To do this: A prototype model of the political decision making processes of the countries is drawn, decision making mechanisms and the planning functions are compared. As a result it’s found that emergency management policy in Turkey is reactive whereas it’s proactive in UK; as the delegating policy Turkey’s system is similar to UK; levels of emergency situations are similar but not the same; the differences are stemming from the civil order and nongovernmental organizations effectiveness; UK has a detailed government engagement model to emergencies, which shapes the doctrine of the approach to emergencies, and it’s successful in gathering and controlling the whole state’s efforts; crisis management is a sub-phase of UK emergency management whereas it’s accepted as a outmoded management perception and the focal point of crisis management perception in UK is security crisis and natural disasters while in Turkey it is natural disasters. In every anlysis proposals are given to Turkey.

Keywords: crisis management, disaster management, emergency management, turkey, united kingdom

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Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

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Authors: Janneth Gonzalez, Marco Avila, George Barreto

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GRP78 participates in multiple functions in the cell during normal and pathological conditions, controlling calcium homeostasis, protein folding and unfolded protein response. GRP78 is located in the endoplasmic reticulum, but it can change its location under stress, hypoxic and apoptotic conditions. NF-κB represents the keystone of the inflammatory process and regulates the transcription of several genes related with apoptosis, differentiation, and cell growth. The possible relationship between GRP78-NF-κB could support and explain several mechanisms that may regulate a variety of cell functions, especially following brain injuries. Although several reports show interactions between NF-κB and heat shock proteins family members, there is a lack of information on how GRP78 may be interacting with NF-κB, and possibly regulating its downstream activation. Therefore, we assessed the computational predictions of the GRP78 (Chain A) and NF-κB complex (IkB alpha and p65) protein-protein interactions. The interaction interface of the docking model showed that the amino acids ASN 47, GLU 215, GLY 403 of GRP78 and THR 54, ASN 182 and HIS 184 of NF-κB are key residues involved in the docking. The electrostatic field between GRP78-NF-κB interfaces and molecular dynamic simulations support the possible interaction between the proteins. In conclusion, this work shed some light in the possible GRP78-NF-κB complex indicating key residues in this crosstalk, which may be used as an input for better drug design strategy targeting NF-κB downstream signaling as a new therapeutic approach following brain injuries.

Keywords: computational biology, protein interactions, Grp78, bioinformatics, molecular dynamics

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Authors: W. Mughees, M. Alahmad

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Water is the most significant entity that controls local and global development. For the Gulf region, especially Saudi Arabia, with its limited potable water resources, the potential of the fresh water problem is highly considerable. In this research, the study involves the design and analysis of pinch-based water/wastewater networks. Multiple water/wastewater networks were developed using pinch analysis involving direct recycle/material recycle method. Property-integration technique was adopted to carry out direct recycle method. Particularly, a petroleum refinery was considered as a case study. In direct recycle methodology, minimum water discharge and minimum fresh water resource targets were estimated. Re-design (or retrofitting) of water allocation in the networks was undertaken. Chemical Oxygen Demand (COD) and hardness properties were taken as pollutants. This research was based on single and double contaminant approach for COD and hardness and the amount of fresh water was reduced from 340.0 m3/h to 149.0 m3/h (43.8%), 208.0 m3/h (61.18%) respectively. While regarding double contaminant approach, reduction in fresh water demand was 132.0 m3/h (38.8%). The required analysis was also carried out using mathematical programming technique. Operating software such as LINGO was used for these studies which have verified the graphical method results in a valuable and accurate way. Among the multiple water networks, the one possible water allocation network was developed based on mass exchange.

Keywords: minimization, water pinch, water management, pollution prevention

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Authors: Onyinyechi Joy Kingdom

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Mergers and Acquisitions (M&A) have been proposed as a mechanism through which, problems associated with inefficiency or poor performance in financial institution could be addressed. The aim of this study is to examine the proposition that recapitalization of banks, which encouraged Mergers and Acquisitions in Nigeria banking system, would strengthen the domestic banks, improve financial deepening and the confidence of depositors. Hence, this study examines the impact of the 2005 M&A in the Nigerian-banking sector on financial deepening using mixed method (quantitative and qualitative approach). The quantitative process of this study utilised annual time series for financial deepening indicator for the period of 1997 to 2012. While, the qualitative aspect adopted semi-structured interview to collate data from three merged banks and three stand-alone banks to explore, understand and complement the quantitative results. Furthermore, a framework thematic analysis is employed to analyse the themes developed using NVivo 11 software. Using the quantitative approach, findings from the equality of mean test (EMT) used suggests that M&A have significant impact on financial deepening. However, this method is not robust enough given its weak validity as it does not control for other potential factors that may determine financial deepening. Thus, to control for other factors that may affect the level of financial deepening, a Multiple Regression Model (MRM) and Interrupted Times Series Analysis (ITSA) were applied. The coefficient for M&A dummy turned negative and insignificant using MRM. In addition, the estimated linear trend of the post intervention when ITSA was applied suggests that after M&A, the level of financial deepening decreased annually; however, this was statistically insignificant. Similarly, using the qualitative approach, the results from the interview supported the quantitative results from ITSA and MRM. The result suggests that interest rate should fall when capital base is increased to improve financial deepening. Hence, this study contributes to the existing literature the importance of other factors that may affect financial deepening and the economy when policies that will enhance bank performance and the economy are made. In addition, this study will enable the use of valuable policy instruments relevant to monetary authorities when formulating policies that will strengthen the Nigerian banking sector and the economy.

Keywords: mergers and acquisitions, recapitalization, financial deepening, efficiency, financial crisis

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Authors: Badriah Alayidi, Emad Alyahya

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Background: Most people with Multiple Sclerosis (MS) report worsening balance as the condition progresses. Poor balance control is also well known to be a significant risk factor for both falling and fear of falling. The increased risk of falls with disease progression thus makes balance control an essential target of gait rehabilitation amongst people with MS. Intervention programs have developed various methods to improve balance control, and accumulating evidence suggests that exercise programs may help people with MS improve their balance. Among these methods, virtual reality (VR) is growing in popularity as a balance-training technique owing to its potential benefits, including better compliance and greater user happiness. However, it is not clear if a VR environment will induce different balance control mechanisms in MS as compared to healthy individuals or traditional environments. Therefore, this study aims to examine how individuals with MS control their balance in a VR setting. Methodology: The proposed study takes an empirical approach to estimate and determine the role of balance response in persons with MS using a VR environment. It will use primary data collected through patient observations, physiological and biomechanical evaluation of balance, and data analysis. Results: The preliminary systematic review and meta-analysis indicated that there was variability in terms of the outcome assessing balance response in people with MS. The preliminary results of these assessments have the potential to provide essential indicators of the progression of MS and contribute to the individualization of treatment and evaluation of the interventions’ effectiveness. The literature describes patients who have had the opportunity to experiment in VR settings and then used what they have learned in the real world, suggesting that this VR setting could be more appealing than conditional settings. The findings of the proposed study will be beneficial in estimating and determining the effect of VR on balance control in persons with MS. In previous studies, VR was shown to be an interesting approach to neurological rehabilitation, but more data are needed to support this approach in MS. Conclusions: The proposed study enables an assessment of balance and evaluations of a variety of physiological implications related to neural activity as well as biomechanical implications related to movement analysis.

Keywords: multiple sclerosis, virtual reality, postural control, balance

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Authors: Ezil Sam Leni, Shalen S.

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Transport service monitoring and upkeep are essential components of smart city initiatives. The main risks to the relevant departments and authorities are the ever-increasing vehicular traffic and the conditions of the roads. In India, the economy is greatly impacted by the road transport sector. In 2021, the Ministry of Road Transport and Highways Transport, Government of India, produced a report with statistical data on traffic accidents. The data included the number of fatalities, injuries, and other pertinent criteria. This study proposes a distributed infrastructure for the monitoring, detection, and reporting of potholes to the appropriate authorities. In a distributed environment, the nodes are the edge devices, and local edge servers, and global servers. The edge devices receive the initial model to be employed from the global server. The YOLOv8 model for pothole detection is used in the edge devices. The edge devices run the pothole detection model, gather the pothole images on their path, and send the updates to the nearby edge server. The local edge server selects the clients for its aggregation process, aggregates the model updates and sends the updates to the global server. The global server collects the updates from the local edge servers, performs aggregation and derives the updated model. The updated model has the information about the potholes received from the local edge servers and notifies the updates to the local edge servers and concerned authorities for monitoring and maintenance of road conditions. The entire process is implemented in FedCV distributed environment with the implementation using the client-server model and aggregation entities. After choosing the clients for its aggregation process, the local edge server gathers the model updates and transmits them to the global server. After gathering the updates from the regional edge servers, the global server aggregates them and creates the updated model. Performance indicators and the experimentation environment are assessed, discussed, and presented. Accelerometer data may be taken into consideration for improved performance in the future development of this study, in addition to the images captured from the transportation routes.

Keywords: federated Learning, pothole detection, distributed framework, federated averaging

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Authors: Stefan Andersson, Balram Panjwani, Bernd Wittgens, Jan Erik Olsen

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Polycyclic Aromatic hydrocarbons are organic compounds consisting of only hydrogen and carbon aromatic rings. PAH are neutral, non-polar molecules that are produced due to incomplete combustion of organic matter. These compounds are carcinogenic and interact with biological nucleophiles to inhibit the normal metabolic functions of the cells. Norways, the most important sources of PAH pollution is considered to be aluminum plants, the metallurgical industry, offshore oil activity, transport, and wood burning. Stricter governmental regulations regarding emissions to the outer and internal environment combined with increased awareness of the potential health effects have motivated Norwegian metal industries to increase their efforts to reduce emissions considerably. One of the objective of the ongoing industry and Norwegian research council supported "SCORE" project is to reduce potential PAH emissions from an off gas stream of a ferroalloy furnace through controlled combustion. In a dedicated combustion chamber. The sizing and configuration of the combustion chamber depends on the combined properties of the bulk gas stream and the properties of the PAH itself. In order to achieve efficient and complete combustion the residence time and minimum temperature need to be optimized. For this design approach reliable kinetic data of the individual PAH-species and/or groups thereof are necessary. However, kinetic data on the combustion of PAH are difficult to obtain and there is only a limited number of studies. The paper presents an evaluation of the kinetic data for some of the PAH obtained from literature. In the present study, the oxidation is modelled for pure PAH and also for PAH mixed with process gas. Using a perfectly stirred reactor modelling approach the oxidation is modelled including advanced reaction kinetics to study influence of residence time and temperature on the conversion of PAH to CO2 and water. A Chemical Reactor Network (CRN) approach is developed to understand the oxidation of PAH inside the combustion chamber. Chemical reactor network modeling has been found to be a valuable tool in the evaluation of oxidation behavior of PAH under various conditions.

Keywords: PAH, PSR, energy recovery, ferro alloy furnace

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Authors: Rosaline Govender, Shubnam Rambharos

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Universities are, to a certain extent, the source of under-preparedness ideologically, structurally, and pedagogically, particularly since organizational cultures often alienate students by failing to enable epistemological access. This is evident in the unsustainably low graduation rates that characterize South African higher education, which indicate that under 30% graduate in minimum time, under two-thirds graduate within 6 years, and one-third have not graduated after 10 years. Although the statistics for the Faculty of Accounting and Informatics at the Durban University of Technology (DUT) in South Africa have improved significantly from 2019 to 2021, the graduation (32%), throughput (50%), and dropout rates (16%) are still a matter for concern as the graduation rates, in particular, are quite similar to the national statistics. For our students to succeed, higher education should take a multi-pronged approach to ensure student success, and student engagement is one of the ways to support our students. Student engagement depends not only on students’ teaching and learning experiences but, more importantly, on their social and academic integration, their sense of belonging, and their emotional connections in the institution. Such experiences need to challenge students academically and engage their intellect, grow their communication skills, build self-discipline, and promote confidence. The aim of this mixed methods study is to explore the multi-pronged nature of student success within the Faculty of Accounting and Informatics at DUT and focuses on the enabling and constraining factors of student success. The sources of data were the Mid-year student experience survey (N=60), the Hambisa Student Survey (N=85), and semi structured focus group interviews with first, second, and third year students of the Faculty of Accounting and Informatics Hambisa program. The Hambisa (“Moving forward”) focus area is part of the Siyaphumelela 2.0 project at DUT and seeks to understand the multiple challenges that are impacting student success which create a large “middle” cohort of students that are stuck in transition within academic programs. Using the lens of the sociocultural influences on student engagement framework, we conducted a thematic analysis of the two surveys and focus group interviews. Preliminary findings indicate that living conditions, choice of program, access to resources, motivation, institutional support, infrastructure, and pedagogical practices impact student engagement and, thus, student success. It is envisaged that the findings from this project will assist the university in being better prepared to enable student success.

Keywords: social and academic integration, socio-cultural influences, student engagement, student success

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Authors: Minnie Y. Teng, Kathy Xie, Jarus Tal

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Rationale: The traditional approach to community programs for children with mental and/or developmental challenges often involves segregation from typically-developing peers. However, studies show that inclusive education improves children’s quality of life, self-concept, and long term health outcomes. Investigating factors that influence inclusion can thus have important implications in the design and facilitation of community programs such that all children - across a spectrum of needs and abilities - may benefit. Objectives: This study explores barriers and facilitators to inclusive community programming for children aged 0 to 12 with developmental/mental challenges. Methods: Using a participatory-action research methodology, semi-structured focus groups and interviews will be used to explore perspectives of sighted students, instructors, and staff. Data will be transcribed and coded thematically. Practice Implications or Results: By having a deeper understanding of the barriers and facilitators to inclusive programming in the community, researchers can work with the broader community to facilitate inclusion in children’s community programs. Conclusions: Expanding inclusive practices may improve the health and wellbeing of the pediatric populations with disabilities, which consistently reports lower levels of participation. These findings may help to identify gaps in existing practices and ways to approach them.

Keywords: aquatic programs, children, disabilities, inclusion, community programs

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Authors: Aliaksandr Huminski

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Semantic Role Labeling (SRL) as shallow semantic parsing approach includes recognition and labeling arguments of a verb in a sentence. Verb participants are linked with specific semantic roles (Agent, Patient, Instrument, Location, etc.). Thus, SRL can answer on key questions such as ‘Who’, ‘When’, ‘What’, ‘Where’ in a text and it is widely applied in dialog systems, question-answering, named entity recognition, information retrieval, and other fields of NLP. However, SRL has the following flaw: Two sentences with identical (or almost identical) meaning can have different semantic role structures. Let consider 2 sentences: (1) John put butter on the bread. (2) John buttered the bread. SRL for (1) and (2) will be significantly different. For the verb put in (1) it is [Agent + Patient + Goal], but for the verb butter in (2) it is [Agent + Goal]. It happens because of one of the most interesting and intriguing features of a verb: Its ability to capture participants as in the case of the verb butter, or their features as, say, in the case of the verb drink where the participant’s feature being liquid is shared with the verb. This capture looks like a total fusion of meaning and cannot be decomposed in direct way (in comparison with compound verbs like babysit or breastfeed). From this perspective, SRL looks really shallow to represent semantic structure. If the key point in semantic representation is an opportunity to use it for making inferences and finding hidden reasons, it assumes by default that two different but semantically identical sentences must have the same semantic structure. Otherwise we will have different inferences from the same meaning. To overcome the above-mentioned flaw, the following approach is suggested. Assume that: P is a participant of relation; F is a feature of a participant; Vcp is a verb that captures a participant; Vcf is a verb that captures a feature of a participant; Vpr is a primitive verb or a verb that does not capture any participant and represents only a relation. In another word, a primitive verb is a verb whose meaning does not include meanings from its surroundings. Then Vcp and Vcf can be decomposed as: Vcp = Vpr +P; Vcf = Vpr +F. If all Vcp and Vcf will be represented this way, then primitive verbs Vpr can be considered as a canonical form for SRL. As a result of that, there will be no hidden participants caught by a verb since all participants will be explicitly unfolded. An obvious example of Vpr is the verb go, which represents pure movement. In this case the verb drink can be represented as man-made movement of liquid into specific direction. Extraction and using primitive verbs for SRL create a canonical representation unique for semantically identical sentences. It leads to the unification of semantic representation. In this case, the critical flaw related to SRL will be resolved.

Keywords: decomposition, labeling, primitive verbs, semantic roles

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Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

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Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.

Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis

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Authors: Essam Al Daoud

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Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: gradient boosting, XGBoost, LightGBM, CatBoost, home credit

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Authors: Michael Wagner, Philipp Steinbauer, Andrea Katharina Lietz, Alexander Hoffelner, Johannes Fessler

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Background: Cardiopulmonary resuscitations are stressful situations in which vital decisions must be made within seconds. Lack of routine due to the infrequency of pediatric emergencies can lead to serious medical and communication errors. Virtual reality can fundamentally change the way simulation training is conducted in the future. It appears to be a useful learning tool for technical and non-technical skills. It is important to investigate the use of VR in providing a strong sense of presence within simulations. Methods: In this randomized study, we will enroll doctors and medical students from the Medical University of Vienna, who will receive learning material regarding the resuscitation of a one-year-old child. The study will be conducted in three phases. In the first phase, 20 physicians and 20 medical students from the Medical University of Vienna will be included. They will perform simulation-based training with a standardized scenario of a critically ill child with a hypovolemic shock. The main goal of this phase is to establish a baseline for the following two phases to generate comparative values regarding cognitive load and stress. In phase 2 and 3, the same participants will perform the same scenario in a VR setting. In both settings, on three set points of progression, one of three predefined events is triggered. For each event, three different stress levels (easy, medium, difficult) will be defined. Stress and cognitive load will be analyzed using the NASA Task Load Index, eye-tracking parameters, and heart rate. Subsequently, these values will be compared between VR training and traditional simulation-based training. Hypothesis: We hypothesize that the VR training and the traditional training groups will not differ in physiological response (cognitive load, heart rate, and heart rate variability). We further assume that virtual reality training can be used as cost-efficient additional training. Objectives: The aim of this study is to measure cognitive load and stress level during a real-life simulation training and compare it with VR training in order to show that VR training evokes the same physiological response and cognitive load as real-life simulation training.

Keywords: virtual reality, cognitive load, simulation, adaptive virtual reality training

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Authors: Rupesh S. Gundewar, Kanchan C. Khare

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Runoff contribution from urban areas is generally from manmade structures and few natural contributors. The manmade structures are buildings; roads and other paved areas whereas natural contributors are groundwater and overland flows etc. Runoff alleviation is done by manmade as well as natural storages. Manmade storages are storage tanks or other storage structures such as soakways or soak pits which are more common in western and European countries. Natural storages are catchment slope, infiltration, catchment length, channel rerouting, drainage density, depression storage etc. A literature survey on the manmade and natural storages/inflow has presented percentage contribution of each individually. Sanders et.al. in their research have reported that a vegetation canopy reduces runoff by 7% to 12%. Nassif et el in their research have reported that catchment slope has an impact of 16% on bare standard soil and 24% on grassed soil on rainfall runoff. Infiltration being a pervious/impervious ratio dependent parameter is catchment specific. But a literature survey has presented a range of 15% to 30% loss of rainfall runoff in various catchment study areas. Catchment length and channel rerouting too play a considerable role in reduction of rainfall runoff. Ground infiltration inflow adds to the runoff where the groundwater table is very shallow and soil saturates even in a lower intensity storm. An approximate percent contribution through this inflow and surface inflow contributes to about 2% of total runoff volume. Considering the various contributing factors in runoff it has been observed during a literature survey that integrated modelling approach needs to be considered. The traditional storm water network models are able to predict to a fair/acceptable degree of accuracy provided no interaction with receiving water (river, sea, canal etc), ground infiltration, treatment works etc. are assumed. When such interactions are significant then it becomes difficult to reproduce the actual flood extent using the traditional discrete modelling approach. As a result the correct flooding situation is very rarely addressed accurately. Since the development of spatially distributed hydrologic model the predictions have become more accurate at the cost of requiring more accurate spatial information.The integrated approach provides a greater understanding of performance of the entire catchment. It enables to identify the source of flow in the system, understand how it is conveyed and also its impact on the receiving body. It also confirms important pain points, hydraulic controls and the source of flooding which could not be easily understood with discrete modelling approach. This also enables the decision makers to identify solutions which can be spread throughout the catchment rather than being concentrated at single point where the problem exists. Thus it can be concluded from the literature survey that the representation of urban details can be a key differentiator to the successful understanding of flooding issue. The intent of this study is to accurately predict the runoff from impermeable areas from urban area in India. A representative area has been selected for which data was available and predictions have been made which are corroborated with the actual measured data.

Keywords: runoff, urbanization, impermeable response, flooding

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Authors: M. Radunovic

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Region of Southeastern Europe has a substantial energy resource potential and is witnessing an increasing rate of power and energy project investments. This comes as a result of countries harmonizing their legal framework and market regulations to conform the ones of European Union, enabling direct private investments. Funding in the power and energy market in this region originates from various resources and investment entities, including commercial and institutional ones. Risk anticipation and assessment is crucial to project success, especially given the long exploitation period of project in power and energy domain, as well as the wide range of stakeholders involved. This paper analyzes the possibility of combined application of tools used in total quality management and international financing institutions for project planning, execution and evaluation, with the goal of anticipating, assessing and minimizing the risks that might occur in the development and execution phase of a power and energy project in the market of southeastern Europe. History of successful project management and investments both in the industry and institutional sector provides sufficient experience, guidance and internationally adopted tools to provide proper project assessment for investments in power and energy. Business environment of southeastern Europe provides immense potential for developing power and engineering projects of various magnitudes, depending on stakeholders’ interest. Diversification on investment sources provides assurance that there is interest and commitment to invest in this market. Global economic and political developments will be intensifying the pace of investments in the upcoming period. The proposed approach accounts for key parameters that contribute to the sustainability and profitability of a project which include technological, educational, social and economic gaps between the southeastern European region and western Europe, market trends in equipment design and production on a global level, environment friendly approach to renewable energy sources as well as conventional power generation systems, and finally the effect of the One Belt One Road Initiative led by People’s Republic of China to the power and energy market of this region in the upcoming period on a long term scale. Analysis will outline the key benefits of the approach as well as the accompanying constraints. Parallel to this it will provide an overview of dominant threats and opportunities in present and future business environment and their influence to the proposed application. Through concrete examples, full potential of this approach will be presented along with necessary improvements that need to be implemented. Number of power and engineering projects being developed in southeastern Europe will be increasing in the upcoming period. Proper risk analysis will lead to minimizing project failures. The proposed successful combination of reliable project planning tools from different investment areas can prove to be beneficial in the future power and engineering investments, and guarantee their sustainability and profitability.

Keywords: capital investments, lean six sigma, logical framework approach, logical framework matrix, one belt one road initiative, project management tools, quality function deployment, Southeastern Europe, total quality management

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Authors: Mostafa Mjahed

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Tilt Rotor UAVs (Unmanned Aerial Vehicles) are naturally unstable and difficult to maneuver. The purpose of this paper is to design controllers for the stabilization and trajectory tracking of this type of UAV. To this end, artificial intelligence methods have been exploited. First, the dynamics of this UAV was modeled using the Lagrange-Euler method. The conventional method based on Proportional, Integral and Derivative (PID) control was applied by decoupling the different flight modes. To improve stability and trajectory tracking of the Tilt Rotor, the fuzzy approach and the technique of multilayer neural networks (NN) has been used. Thus, Fuzzy Proportional Integral and Derivative (FPID) and Neural Network-based Proportional Integral and Derivative controllers (NNPID) have been developed. The meta-heuristic approach based on Particle Swarm Optimization (PSO) method allowed adjusting the setting parameters of NNPID controller, giving us an improved NNPID-PSO controller. Simulation results under the Matlab environment show the efficiency of the approaches adopted. Besides, the Tilt Rotor UAV has become stable and follows different types of trajectories with acceptable precision. The Fuzzy, NN and NN-PSO-based approaches demonstrated their robustness because the presence of the disturbances did not alter the stability or the trajectory tracking of the Tilt Rotor UAV.

Keywords: neural network, fuzzy logic, PSO, PID, trajectory tracking, tilt-rotor UAV

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