Search results for: collaborative approach

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: R. L. David, E. C. P. Tan, M. A. Ferenczi

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This study aimed to investigate the effect of a 'one-time' optional Information Literacy (IL) workshop to enhance Year 1 medical students' literature search, writing, and citation management skills as directed by a customized five-year IL framework developed for LKC Medicine students. At the end of the IL workshop, the overall rated 'somewhat difficult' when finding, citing, and using information from sources. The study method is experimental using a standardized IL test to study the cohort effect of a 'one-time' optional IL workshop on Year 1 students; experimental group in comparison to Year 2 students; control group. Test scores from both groups were compared and analyzed using mean scores and one-way analysis of variance (ANOVA). Unexpectedly, there were no statistically significant differences between group means as determined by One-Way ANOVA (F₁,₁₉₃ = 3.37, p = 0.068, ηp² = 0.017). Challenges and shortfalls posed by 'one-time' interventions raised a rich discussion to adopt an 'embedded librarianship' approach, which shifts the medial librarians' role into the curriculum and uses Team Based Learning to teach IL skills to medical students. The customized five-year IL framework developed for LKC Medicine students becomes a useful librarian-faculty model for embedding and bringing IL into the classroom.

Keywords: information literacy, 'one-time' interventions, medical students, standardized tests, embedded librarianship, curriculum, medical librarians

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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: 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: 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: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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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: Heather Fulford, Melanie Liddell

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The recruitment and retention of high quality employees can prove to be challenging for social enterprises, particularly in some of the core business support functions such as marketing, communications, IT and finance. This holds true for social enterprises in urban contexts, where roles with more attractive remuneration in these business functions can often be found quite readily in the private sector. For social enterprises situated in rural locations, the challenges of staff recruitment and retention are even more acute. Such challenges can lead to a skills deficit in rural social enterprises, which can, at best, hinder their growth potential, and worse, jeopardise their chances of survival. This in turn, can have a negative impact on the sustainability and resilience of the surrounding rural community in which the social enterprise is located. The purpose of this paper is to report on aspects of a collaborative initiative established to stimulate innovation and business growth in remote rural businesses in Scotland. Launched in 2010, this initiative was designed to attract young students and graduates from the region to stay in the region upon completion of their studies, and to attract others from outside the region to re-locate there post-university. To facilitate this, SMEs in the region were offered wage subsidies to encourage them to recruit a student or graduate on a work placement for up to one year to participate in an innovation or business growth-oriented project. A number of the employers offering work placements were social enterprises. Through analysis of the placement project and role specifications devised by the participating social enterprises, an overview is provided of their business development needs and the skills they require to stimulate innovation and growth. Scrutiny of the reflective accounts compiled by the students and graduates at the close of their work placements highlights the benefits they derived from being able to put their academic knowledge and skills into action within a social enterprise. Examination of interviews conducted with a sample of placement employers reveals the contribution the students and graduates made during the business development projects with the social enterprises. The challenges of hosting such placements are also discussed. The paper concludes with indications of the lessons learned and an outline of the wider implications for other remote rural locations in which social enterprises play an important role in the local economy and life of the community.

Keywords: resilience, rural development, regeneration, regional development, recruitment, resource management, retention, remuneration

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Authors: Haifeng Wang, Haili Zhang

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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

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Authors: Tesfaw Belayneh Abebe

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Integrating low-altitude earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN) with the assistance of reconfigurable intelligent surfaces (RIS), we investigate the problem of how to enhance throughput through integrated LEO satellites and UAVs with the assistance of RIS. We propose a method to jointly optimize the associations with the LEO satellite, the 3D trajectory of the UAV, and the phase shifts of the RIS to maximize communication throughput for RIS-assisted integrated LEO satellite and UAV-enabled wireless communications, which is challenging due to the time-varying changes in the position of the LEO satellite, the high mobility of UAVs, an enormous number of possible control actions, and also the large number of RIS elements. Utilizing a multi-agent double deep Q-network (MADDQN), our approach dynamically adjusts LEO satellite association, UAV positioning, and RIS phase shifts. Simulation results demonstrate that our method significantly outperforms baseline strategies in maximizing throughput. Lastly, thanks to the integrated network and the RIS, the proposed scheme achieves up to 65.66x higher peak throughput and 25.09x higher worst-case throughput.

Keywords: integrating low-altitude earth orbit (LEO) satellites, unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN), reconfigurable intelligent surfaces (RIS), multi-agent double deep Q-network (MADDQN)

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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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Authors: Julian Mehler, Marcus Fischer, Martin Hartmann, Peter S. Schulz

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During the last two decades, the synthesis of metal-organic frameworks (MOFs) has gained ever increasing attention. Based on their pore size and shape as well as host-guest interactions, they are of interest for numerous fields related to porous materials, like catalysis and gas separation. Usually, MOF-synthesis takes place in an organic solvent between room temperature and approximately 220 °C, with mixtures of polyfunctional organic linker molecules and metal precursors as substrates. Reaction temperatures above the boiling point of the solvent, i.e. solvothermal reactions, are run in autoclaves or sealed glass vessels under autogenous pressures. A relatively new approach for the synthesis of MOFs is the so-called ionothermal synthesis route. It applies an ionic liquid as a solvent, which can serve as a structure-directing template and/or a charge-compensating agent in the final coordination polymer structure. Furthermore, this method often allows for less harsh reaction conditions than the solvothermal route. Here a variation of the ionothermal approach is reported, where the ionic liquid also serves as an organic linker source. By using 1-ethyl-3-methylimidazolium terephthalates ([EMIM][Hbdc] and [EMIM]₂[bdc]), the one-step synthesis of MIL-53(Al)/Boehemite composites with interesting features is possible. The resulting material is already formed at moderate temperatures (90-130 °C) and is stabilized in the usually unfavored ht-phase. Additionally, in contrast to already published procedures for MIL-53(Al) synthesis, no further activation at high temperatures is mandatory. A full characterization of this novel composite material is provided, including XRD, SS-NMR, El-Al., SEM as well as sorption measurements and its interesting features are compared to MIL-53(Al) samples produced by the classical solvothermal route. Furthermore, the syntheses of the applied ionic liquids and salts is discussed. The influence of the degree of ionicity of the linker source [EMIM]x[H(2-x)bdc] on the crystal structure and the achievable synthesis temperature are investigated and give insight into the role of the IL during synthesis. Aside from the synthesis of MIL-53 from EMIM terephthalates, the use of the phosphonium cation in this approach is discussed as well. Additionally, the employment of ILs in the preparation of other MOFs is presented briefly. This includes the ZIF-4 framework from the respective imidazolate ILs and chiral camphorate based frameworks from their imidazolium precursors.

Keywords: ionic liquids, ionothermal synthesis, material synthesis, MIL-53, MOFs

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Authors: Sunita Boro, Saurabh Kumar Dixit

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Terroir, an intricate fusion of geography, climate, soil, and human expertise, has long been acknowledged as a defining factor in the character of wines and foods. This research embarks on an exploration of terroir's profound influence on gastronomic tourism, shedding light on the intricate interplay between the physical environment and culinary artistry. Delving into the intricate science of terroir, we scrutinize its role in shaping the sensory profiles of wines and foods, emphasizing the profound impact of specific regions on flavor, aroma, and texture. We deploy a multifaceted methodology, amalgamating sensory analysis, chemical profiling, geographical information systems, and qualitative interviews to unearth the nuanced nuances of terroir expression. Through an exhaustive review of the literature, we elucidate the historical roots of terroir, unveil the intricate cultural dimensions shaping it, and provide a comprehensive examination of prior studies in the field. Our findings underscore the pivotal role of terroir in promoting regional identities, enhancing the economic viability of locales, and attracting gastronomic tourists. The paper also dissects the marketing strategies employed to promote terroir-driven food and wine experiences. We elucidate the utilization of storytelling, branding, and collaborative endeavors in fostering a robust terroir-based tourism industry. This elucidates both the potential for innovation and the challenges posed by oversimplification or misrepresentation of terroir. Our research spotlights the intersection of terroir and sustainability, emphasizing the significance of environmentally conscious practices in terroir-driven productions. We discern the harmonious relationship between sustainable agriculture, terroir preservation, and responsible tourism, encapsulating the essence of ecological integrity in gastronomic tourism. Incorporating compelling case studies of regions and businesses excelling in the terroir-based tourism realm, we offer in-depth insights into successful models and strategies, with an emphasis on their replicability and adaptability to various contexts. Ultimately, this paper not only contributes to the scholarly understanding of terroir's role in the world of food and wine tourism but also provides actionable recommendations for stakeholders to leverage terroir's allure, preserve its authenticity, and foster sustainable and enriching culinary tourism experiences.

Keywords: terroir, food tourism, wine tourism, sustainability

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Authors: Mariya Salihu Ingawa, Sani Suleiman Isah

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The assessment of Integrated Information System (IIS) in organisation is an important initiative to enable the Information System (IS) managers, as well as top management to understand the success status of their investment in IS integration efforts. However, without a proper assessment, an organisation will not know its IIS status, which may affect their judgment on what action should be taken onwards. Current research on IIS assessment is lacking and those related literature on IIS assessment focus more on assessing the technical aspect of IIS. It is argued that assessing technical aspect alone is inadequate since organisational and strategic aspects in IIS should also be considered. Current methods, techniques and tools used by vendors for IIS assessment also are lack of comprehensive measures to fully assess the Integrated Information System in term of technical, organisational and strategic domains. The purpose of this study is to establish critical success factors for measuring success of an Integrated Information System. These factors are used as the basis for constructing an approach to comprehensively assess IIS in an organisation. A comprehensive list of success factors for IIS assessment, established from literature, was initially presented. An expert surveys using both manual and online methods were conducted to verify the factors. Based on the factors, an instrument for IIS assessment was constructed. The results from a case study indicate that through comprehensive assessment approach, not only the level of success been known, but also reveals the contributing factors. This research contributes to the field of Information Systems specifically in the area of Integrated Information System assessment.

Keywords: integrated information system, expert surveys, organisation, assessment

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Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

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As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

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Authors: Thaiurie Govender, Shannon Verne

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The Fourth Industrial Revolution has ushered in an era where technology significantly impacts various aspects of life, including higher education. Blended learning, which combines synchronous and asynchronous learning, has gained popularity as a pedagogical approach. However, its effective implementation is a challenge, particularly in the context of the COVID-19 pandemic and technological obstacles faced in South Africa. This study focused on lecturers' teaching and learning practices to implement blended learning, aiming to understand the teaching and learning strategies used with the integration of digital tools to facilitate the blended learning approach within a private higher educational institution in South Africa. Using heutagogy and constructivism theoretical frameworks, the study aimed to uncover insights into the lecturer’s teaching and learning practices to overcome challenges in designing and facilitating blended learning modules. Through a qualitative analysis, the themes of student engagement, teaching and learning strategies, digital tools, and feedback emerged, highlighting the complexities and opportunities in a blended learning classroom. The findings emphasize the importance of tailoring methods to students' needs and subject matter, aligning with constructivist principles. Recommendations include promoting professional development opportunities, addressing infrastructure issues, and fostering a supportive learning environment.

Keywords: blended learning, digital tools, higher education, teaching strategies

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Authors: Samuel Quashie

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PhDs in Construction Management often designs their methods based on those established in social sciences using theoretical models, to collect, gather and analysis data to answer research questions. Work aim is to apply qualitative and quantitative as a data analysis method, and as part of the theoretical framework - descriptive theory. To improve the ability to replicate the contribution to knowledge the research. Using practical triangulation approach, which covers, interviews and observations, literature review and (archival) document studies, project-based case studies, questionnaires surveys and review of integrated systems used in, construction and construction related industries. The clarification of organisational context and management delivery that influences organizational performance and quality of product and measures are achieved. Results illustrate improved reliability in this research approach when interpreting real world phenomena; cumulative results of research can be applied with confidence under similar environments. Assisted validity of the PhD research outcomes and strengthens the confidence to apply cumulative results of research under similar conditions in the Built Environment research systems, which have been criticised for the lack of reliability in approaches when interpreting real world phenomena.

Keywords: case studies, descriptive theory, theoretical framework, qualitative and quantitative research

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

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Authors: Geng Cui, Naoto Imura, Katsuhiro Nishinari, Takahiro Ezaki

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The bullwhip effect, which refers to the amplification of demand variance as one moves up the supply chain, has been observed in various industries and extensively studied through analytic approaches. Existing methods to mitigate the bullwhip effect, such as decentralized demand information, vendor-managed inventory, and the Collaborative Planning, Forecasting, and Replenishment System, rely on the willingness and ability of supply chain participants to share their information. However, in practice, information sharing is often difficult to realize due to privacy concerns. The purpose of this study is to explore new ways to mitigate the bullwhip effect without the need for information sharing. This paper proposes a 'bullwhip absorption strategy' (BAS) to alleviate the bullwhip effect by absorbing it downstream in the supply chain. To achieve this, a two-stage supply chain system was employed, consisting of a single retailer and a single manufacturer. In each time period, the retailer receives an order generated according to an autoregressive process. Upon receiving the order, the retailer depletes the ordered amount, forecasts future demand based on past records, and places an order with the manufacturer using the order-up-to replenishment policy. The manufacturer follows a similar process. In essence, the mechanism of the model is similar to that of the beer game. The BAS is implemented at the retailer's level to counteract the bullwhip effect. This strategy requires the retailer to reduce the uncertainty in its orders, thereby absorbing the bullwhip effect downstream in the supply chain. The advantage of the BAS is that upstream participants can benefit from a reduced bullwhip effect. Although the retailer may incur additional costs, if the gain in the upstream segment can compensate for the retailer's loss, the entire supply chain will be better off. Two indicators, order variance and inventory variance, were used to quantify the bullwhip effect in relation to the strength of absorption. It was found that implementing the BAS at the retailer's level results in a reduction in both the retailer's and the manufacturer's order variances. However, when examining the impact on inventory variances, a trade-off relationship was observed. The manufacturer's inventory variance monotonically decreases with an increase in absorption strength, while the retailer's inventory variance does not always decrease as the absorption strength grows. This is especially true when the autoregression coefficient has a high value, causing the retailer's inventory variance to become a monotonically increasing function of the absorption strength. Finally, numerical simulations were conducted for verification, and the results were consistent with our theoretical analysis.

Keywords: bullwhip effect, supply chain management, inventory management, demand forecasting, order-to-up policy

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Authors: Ogunwole Cecilia Oluwakemi, Timothy Ayomitunde Aderemi

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Provision of sufficient food and elimination of abject poverty have usually been the conventional benefits of agriculture in any society. Meanwhile, despite the fact that Nigeria is an agrarian society, food insecurity and poverty have become the issues of concern among both scholars and policymakers in the recent times. Against this backdrop, this study examined the nexus among agriculture, food security, and poverty reduction in Nigeria from 1990 to 2019 within the framework of the Cointegration and Granger Causality approach. Data was collected from the Central Bank of Nigeria Statistical Bulletin and the World Development Indicators, respectively. The following are the major results that emanated from the study. A long run equilibrium relationship exists among agricultural value added, food production index, and GDP per capita in Nigeria. Similarly, there is a unidirectional causality which flows from food production index to poverty reduction in Nigeria. In the same vein, one way causality flows from poverty reduction to agricultural value added in Nigeria. Consequently, this study makes the following recommendation for the policymakers in Nigeria, and other African countries by extension, that agricultural value added and food production are the important variables that cannot be undermined when poverty reduction occupies the central focus of the policymakers. Therefore, any time these policymakers want to reduce poverty, policies that drive agricultural value added and food production should be embarked upon. Therefore, this study will contribute to the literature by establishing the type of linkage that exists between agriculture, food security, and poverty reduction in Nigeria.

Keywords: agriculture, value added, food production, GDP per capita, Nigeria

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Authors: Shirl H. Terrell

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In the telling of mythologies, stories of cultural and religious histories, the creative arts provide an archetypal lens through which the personal and collective unconscious are viewed, thus revealing mysteries of the unknown psyche. To that end, the author of this paper, using the hermeneutic approach, proves that Carlisle Floyd’s (1955) English language opera Susannah illuminates humanity’s instinctual nature and behaviors through music, libretto, and drama. While impressive musical works such as Wagner’s Ring Cycle and Webber’s Phantom of the Opera have received extensive Jungian analyses, critics and scholars often ignore lesser esteemed works, such as Susannah, notwithstanding the fact that they have been consistently performed on the theater circuit. Such pieces, when given notice, allow viewers to grasp the soul-making depth and timeless quality of productions which may otherwise go unrecognized as culturally or psychologically significant. Although Susannah has sometimes been described as unsophisticated and simple in scope, the author demonstrates why Floyd’s 'little' opera, set in New Hope Valley, Appalachia, a cultural region in the Eastern United States known for its prevailing myths and distortions of isolation, temperament, and the judgmentally conservative behavior of its inhabitants, belongs to opera’s hallmark works. Its approach to powerful underlying archetypal themes, which give rise to the poignant and haunting depictions of the darker and destructive side of the human soul, the Shadow, provides crucial significance to the work. The Shadow’s manifestation in the form of the scapegoating complex is central to the plot of Susannah; the church’s meting out of rules, judgment, and reparation for sins point to the foreboding aspects of human behavior that evoke their intrinsic nature. The scapegoating complex is highlighted in an eight-step process gleaned from the works of Kenneth Burke and Rene Girard. In summary, through depth psychological terms and mythological motifs, the author provides an insightful approach to perceiving instinctual behaviors as they play out in an American opera that has been staged over eight-hundred times, yet, unfortunately, remains in the shadows. Susannah’s timelessness is now.

Keywords: archetypes, mythology, opera, scapegoating, Shadow, Susannah

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Lisa Graham, Kathleen Grant

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South Africa is a multicultural country with eleven official languages, yet most of the formal education at institutions of higher education in the country is in English. It is well known that many students, irrespective of their home language, struggle to grasp difficult scientific concepts and the same is true for students enrolled in the Extended Curriculum Programme at the Cape Peninsula University of Technology (CPUT), studying biomedical sciences. Today we are fortunate in that there is a plethora of resources available to students to research and better understand subject matter online. For example, the students often use YouTube videos to supplement the formal education provided in our course. Unfortunately, most of this material is presented in English. The rationale behind this project lies in that it is well documented that students think and grasp concepts easier in their home language and addresses the fact that the lingua franca of instruction in the field of biomedical science is English. A project aimed at addressing the lack of available resources in most of the South African languages is planned, where students studying Bachelor of Health Science in Medical Laboratory Science will collaborate with those studying Film and Video Technology to create educational videos, explaining scientific concepts in their home languages. These videos will then be published on our own YouTube channel, thereby making them accessible to fellow students, future students and anybody with interest in the subject. Research will be conducted to determine the benefit of the project as well as the published videos to the student community. It is suspected that the students engaged in making the videos will benefit in such a way as to gain further understanding of their course content, a broader appreciation of the discipline, an enhanced sense of civic responsibility, as well as greater respect for the different languages and cultures in our classes. Indeed, an increase in student engagement has been shown to play a central role in student success, and it is well noted that deeper learning and more innovative solutions take place in collaborative groups. We aim to make a meaningful contribution towards the production and repository of knowledge in multilingual teaching and learning for the benefit of the diverse student population and staff. This would strengthen language development, multilingualism, and multiculturalism at CPUT and empower and promote African languages as languages of science and education at CPUT, in other institutions of higher learning, and in South Africa as a whole.

Keywords: educational videos, multiculturalism, multilingualism, student engagement

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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Authors: William J. Crowther, Conor Marsh

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Object-based flow simulation allows fast computation of arbitrarily complex aerodynamic models made up of simple objects with limited flow interactions. The proposed approach is universally applicable to objects made from arbitrarily scaled ellipsoid primitives at arbitrary aerodynamic attitude and angular rate. The use of a component-based aerodynamic modelling approach increases efficiency by allowing selective inclusion of different physics models at run-time and allows extensibility through the development of new models. Insight into the numerical stability of the model under first order fixed-time step integration schemes is provided by stability analysis of the drag component. The compute cost of model components and functions is evaluated and compared against numerical benchmarks. Model static outputs are verified against theoretical expectations and dynamic behaviour using falling plate data from the literature. The model is applied to a range of case studies to demonstrate the efficacy of its application in extensibility, ease of use, and low computational cost. Dynamically complex multi-body systems can be implemented in a transparent and efficient manner, and we successfully demonstrate large scenes with hundreds of objects interacting with diverse flow fields.

Keywords: aerodynamics, real-time simulation, low-order model, flight dynamics

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Authors: Wanhyun Cho, Seongchae Seo, Soonja Kang

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In this work, we propose a variational technique for image contrast enhancement which utilizes global and local information around each pixel. The energy functional is defined by a weighted linear combination of three terms which are called on a local, a global contrast term and dispersion term. The first one is a local contrast term that can lead to improve the contrast of an input image by increasing the grey-level differences between each pixel and its neighboring to utilize contextual information around each pixel. The second one is global contrast term, which can lead to enhance a contrast of image by minimizing the difference between its empirical distribution function and a cumulative distribution function to make the probability distribution of pixel values becoming a symmetric distribution about median. The third one is a dispersion term that controls the departure between new pixel value and pixel value of original image while preserving original image characteristics as well as possible. Second, we derive the Euler-Lagrange equation for true image that can achieve the minimum of a proposed functional by using the fundamental lemma for the calculus of variations. And, we considered the procedure that this equation can be solved by using a gradient decent method, which is one of the dynamic approximation techniques. Finally, by conducting various experiments, we can demonstrate that the proposed method can enhance the contrast of colour images better than existing techniques.

Keywords: color image, contrast enhancement technique, variational approach, Euler-Lagrang equation, dynamic approximation method, EME measure

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Authors: Sukhbaatar Dorj, Erdenebaatar Altangerel

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As alternative to existing e-government measuring models, here proposed a new customer centric, service oriented, simple approach for measuring countries e-Governments. If successfully implemented, built infrastructure will provide a single e-government index number for countries. Main schema is as follows. Country CIO or equal position government official, at the beginning of each year will provide to United Nations dedicated web site 4 numbers on behalf of own country: 1) Ratio of available online public services, to total number of public services, 2) Ratio of interagency inter ministry online public services to total number of available online public services, 3) Ratio of total number of citizen and business entities served online annually to total number of citizen and business entities served annually online and physically on those services, 4) Simple index for geographical spread of online served citizen and business entities. 4 numbers then combined into one index number by mathematical Average function. In addition to 4 numbers 5th number can be introduced as service quality indicator of online public services. If in ordering of countries index number is equal, 5th criteria will be used. Notice: This approach is for country’s current e-government achievement assessment, not for e-government readiness assessment.

Keywords: countries e-government index, e-government, infrastructure for measuring e-government, measuring e-government

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Authors: D. Garg, S. Luthra, A. Haleem

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Due to growing concern about environmental and social consequences throughout the world, a need has been felt to incorporate sustainability concepts in conventional manufacturing. This paper is an attempt to identify and evaluate drivers in implementing sustainable manufacturing in Indian context. Nine possible drivers for successful implementation of sustainable manufacturing have been identified from extensive review. Further, Decision Making Trial and Evaluation Laboratory (DEMATEL) approach has been utilized to evaluate and categorize these identified drivers for implementing sustainable manufacturing in to the cause and effect groups. Five drivers (Societal Pressure and Public Concerns; Regulations and Government Policies; Top Management Involvement, Commitment and Support; Effective Strategies and Activities towards Socially Responsible Manufacturing and Market Trends) have been categorized into the cause group and four drivers (Holistic View in Manufacturing Systems; Supplier Participation; Building Sustainable culture in Organization; and Corporate Image and Benefits) have been categorized into the effect group. “Societal Pressure and Public Concerns” has been found the most critical driver and “Corporate Image and Benefits” as least critical or the most easily influenced driver to implementing sustainable manufacturing in Indian context. This paper may surely help practitioners in better understanding of these drivers and their priorities towards effective implementation of sustainable manufacturing.

Keywords: drivers, decision making trial and evaluation laboratory (DEMATEL), India, sustainable manufacturing

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