A Multigranular Linguistic Additive Ratio Assessment Model in Group Decision Making

Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain context where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ELH-ARAS). Within the ELH-ARAS approach, the decision maker (DMs) can diagnose the results (the ranking of the alternatives) in a decomposed style i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e., the collective final results of all experts are able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ELH-ARAS technique makes it easier for decision-makers to understand the results. Finally, an MCGDM case study is given to illustrate the proposed approach.

The Analysis of Different Classes of Weighted Fuzzy Petri Nets and Their Features

This paper presents the analysis of six different classes of Petri nets: fuzzy Petri nets (FPN), generalized fuzzy Petri nets (GFPN), parameterized fuzzy Petri nets (PFPN), T2GFPN, flexible generalized fuzzy Petri nets (FGFPN), binary Petri nets (BPN). These classes were simulated in the special software PNeS® for the analysis of its pros and cons on the example of models which are dedicated to the decision-making process of passenger transport logistics. The paper includes the analysis of two approaches: when input values are filled with the experts’ knowledge; when fuzzy expectations represented by output values are added to the point. These approaches fulfill the possibilities of triples of functions which are replaced with different combinations of t-/s-norms.

Applying Systematic Literature Review and Delphi Methods to Explore Digital Transformation Key Success Factors

Digital transformation is about identifying the necessary changes of the entire business model, rethinking how to transform the traditional operations into digital ones that can create better value to its customers. Efforts are common across industries, but they often fail due to a lack of understanding of the factors required to focus on and change to be able to embark in digital transformation successfully. Further research is required to bridge the knowledge gap between academia and industry to support companies starting their digital transformation journey. To date there is no consensus on digital transformation key success factors. Therefore, the aim of this paper is to identify the success factors in digital transformation journey, throughout conducting a systematic literature review of 134 peer-reviewed articles to get better insights regarding the research progress in this field.  After completing the systematic literature review it will be followed by Delphi study to get experts consensus on the most significant factors affecting digital transformation implementation. The findings indicate that organizations undergoing digital transformation should focus mainly on (1) well managed digital transformation activities; (2) digital business strategy; (3) supportive culture; (4) top management support; (5) organizational change capabilities.

Data Collection in Hospital Emergencies: A Questionnaire Survey

Many methods are used to collect data like questionnaires, surveys, focus group interviews. Or the collection of poor-quality data resulting, for example, from poorly designed questionnaires, the absence of good translators or interpreters, and the incorrect recording of data allow conclusions to be drawn that are not supported by the data or to focus only on the average effect of the program or policy. There are several solutions to avoid or minimize the most frequent errors, including obtaining expert advice on the design or adaptation of data collection instruments; or use technologies allowing better "anonymity" in the responses. In this context, and to overcome the aforementioned problems, we suggest in this paper an approach to achieve the collection of relevant data, by carrying out a large-scale questionnaire-based survey. We have been able to collect good quality, consistent and practical data on hospital emergencies to improve emergency services in hospitals, especially in the case of epidemics or pandemics.

Sustainable Balanced Scorecard for Kaizen Evaluation: Comparative Study between Egypt and Japan

Continuous improvement activities are becoming a key organizational success factor; those improvement activities include but are not limited to kaizen, six sigma, lean production, and continuous improvement projects. Kaizen is a Japanese philosophy of continuous improvement by making small incremental changes to improve an organization’s performance, reduce costs, reduce delay time, reduce waste in production, etc. This research aims at proposing a measuring system for kaizen activities from a sustainable balanced scorecard perspective. A survey was developed and disseminated among kaizen experts in both Egypt and Japan with the purpose of allocating key performance indicators for both kaizen process (critical success factors) and result (kaizen benefits) into the five sustainable balanced scorecard perspectives. This research contributes to the extant literature by presenting a kaizen measurement of both kaizen process and results that will illuminate the benefits of using kaizen. Also, the presented measurement can help in the sustainability of kaizen implementation across various sectors and industries. Thus, grasping the full benefits of kaizen implementation will contribute to the spread of kaizen understanding and practice. Also, this research provides insights on the social and cultural differences that would influence the kaizen success. Determining the combination of the proper kaizen measures could be used by any industry, whether service or manufacturing for better kaizen activities measurement. The comparison between Japanese implementation of kaizen, as the pioneers of continuous improvement, and Egyptian implementation will help recommending better practices of kaizen in Egypt and contributing to the 2030 sustainable development goals. The study results reveal that there is no significant difference in allocating kaizen benefits between Egypt and Japan. However, with regard to the critical success factors some differences appeared reflecting the social differences and understanding between both countries, a single integrated measurement was reached between the Egyptian and Japanese allocation highlighting the Japanese experts’ opinion as the ultimate criterion for selection.

An Approach to Capture, Evaluate and Handle Complexity of Engineering Change Occurrences in New Product Development

This paper represents the conception that complex problems do not necessary need similar complex solutions in order to cope with the complexity. Furthermore, a simple solution based on established methods can provide a sufficient way dealing with the complexity. To verify this conception, the presented paper focuses on the field of change management as a part of new product development process in automotive sector. In the field of complexity management, dealing with increasing complexity is essential, while, only non-flexible rigid processes that are not designed to handle complexity are available. The basic methodology of this paper can be divided in four main sections: 1) analyzing the complexity of the change management, 2) literature review in order to identify potential solutions and methods, 3) capturing and implementing expertise of experts from change management filed of an automobile manufacturing company and 4) systematical comparison of the identified methods from literature and connecting these with defined requirements of the complexity of the change management in order to develop a solution. As a practical outcome, this paper provides a method to capture the complexity of engineering changes (EC) and includes it within the EC evaluation process, following case-related process guidance to cope with the complexity. Furthermore, this approach supports the conception that dealing with complexity is possible while utilizing rather simple and established methods by combining them in to a powerful tool.

Research Design for Developing and Validating Ice-Hockey Team Diagnostics Scale

In the modern world, ice-hockey (and in a broader sense, team sports) is becoming an increasingly popular field of entertainment. Although the main element is most likely perceived as the show itself, winning is an inevitable part of the successful operation of any sports team. In this paper, the author creates a research design allowing to develop and validate an ice-hockey team-focused diagnostics scale, which enables researchers and practitioners to identify the problems associated with underperforming teams. The construction of the scale starts with personal interviews with experts of the field, carefully chosen from Hungarian ice-hockey sector. Based on the interviews, the author is shown to be in the position to create the categories and the relevant items for the scale. When constructed, the next step is the validation process on a Hungarian sample. Data for validation are acquired through reaching the licensed database of the Hungarian Ice-Hockey Federation involving Hungarian ice-hockey coaches and players. The Ice-Hockey Team Diagnostics Scale is to be created to orientate practitioners in understanding both effective and underperforming team work.

Participatory Financial Inclusion Hypothesis: A Preliminary Empirical Validation Using Survey Design

In Nigeria, enormous efforts/resources had, over the years, been expended on promoting financial inclusion (FI); however, it is seemingly discouraging that many of its self-declared targets on FI remained unachieved, especially amongst the Rural Dwellers and Actors in the Informal Sectors (RDAIS). Expectedly, many reasons had been earmarked for these failures: low literacy level, huge informal/rural sectors etc. This study posits that in spite of these truly-debilitating factors, these FI policy failures could have been avoided or mitigated if the principles of active and better-managed citizens’ participation had been strictly followed in the (re)design/implementation of its FI policies. In other words, in a bid to mitigate the prevalent financial exclusion (FE) in Nigeria, this study hypothesizes the significant positive impact of involving the RDAIS in policy-wide decision making in the FI domain, backed by a preliminary empirical validation. Also, the study introduces the RDAIS-focused Participatory Financial Inclusion Policy (PFIP) as a major FI policy regeneration/improvement tool. The three categories of respondents that served as research subjects are FI experts in Nigeria (n = 72), RDAIS from the very rural/remote village of Unguwar Dogo in Northern Nigeria (n = 43) and RDAIS from another rural village of Sekere (n = 56) in the Southern region of Nigeria. Using survey design (5-point Likert scale questionnaires), random/stratified sampling, and descriptive/inferential statistics, the study often recorded independent consensus (amongst these three categories of respondents) that RDAIS’s active participation in iterative FI policy initiation, (re)design, implementation, (re)evaluation could indeed give improved FI outcomes. However, few questionnaire items also recorded divergent opinions and various statistically (in)significant differences on the mean scores of these three categories. The PFIP (or any customized version of it) should then be carefully integrated into the NFIS of Nigeria (and possibly in the NFIS of other developing countries) to truly/fully provide FI policy integration for these excluded RDAIS and arrest the prevalence of FE.

Real-Time Land Use and Land Information System in Homagama Divisional Secretariat Division

Lands are valuable & limited resource which constantly changes with the growth of the population. An efficient and good land management system is essential to avoid conflicts associated with lands. This paper aims to design the prototype model of a Mobile GIS Land use and Land Information System in real-time. Homagama Divisional Secretariat Division situated in the western province of Sri Lanka was selected as the study area. The prototype model was developed after reviewing related literature. The methodology was consisted of designing and modeling the prototype model into an application running on a mobile platform. The system architecture mainly consists of a Google mapping app for real-time updates with firebase support tools. Thereby, the method of implementation consists of front-end and back-end components. Software tools used in designing applications are Android Studio with JAVA based on GeoJSON File structure. Android Studio with JAVA in GeoJSON File Synchronize to Firebase was found to be the perfect mobile solution for continuously updating Land use and Land Information System (LIS) in real-time in the present scenario. The mobile-based land use and LIS developed in this study are multiple user applications catering to different hierarchy levels such as basic users, supervisory managers, and database administrators. The benefits of this mobile mapping application will help public sector field officers with non-GIS expertise to overcome the land use planning challenges with land use updated in real-time.

Analysis of Differences between Public and Experts’ Views Regarding Sustainable Development of Developing Cities: A Case Study in the Iraqi Capital Baghdad

This paper describes the differences in views on sustainable development between the general public and experts in a developing country, Iraq. This paper will answer the question: How do the views of the public differ from the generally accepted view of experts in the context of sustainable urban development in Iraq? In order to answer this question, the views of both the public and the experts will be analysed. These results are taken from a public survey and a Delphi questionnaire. These will be analysed using statistical methods in order to identify the significant differences. This will enable investigation of the different perceptions between the public perceptions and the experts’ views towards urban sustainable development factors. This is important due to the fact that different viewpoints between policy-makers and the public will impact on the acceptance by the public of any future sustainable development work that is undertaken. The brief findings of the statistical analysis show that the views of both the public and the experts are considered different in most of the variables except six variables show no differences. Those variables are ‘The importance of establishing sustainable cities in Iraq’, ‘Mitigate traffic congestion’, ‘Waste recycling and separating’, ‘Use wastewater recycling’, ‘Parks and green spaces’, and ‘Promote investment’.

Using Analytical Hierarchy Process and TOPSIS Approaches in Designing a Finite Element Analysis Automation Program

Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

A BIM-Based Approach to Assess COVID-19 Risk Management Regarding Indoor Air Ventilation and Pedestrian Dynamics

In the context of the international spread of COVID-19, the Centre Scientifique et Technique du Bâtiment (CSTB) has led a joint research with the French government authorities Hauts-de-Seine department, to analyse the risk in school spaces according to their configuration, ventilation system and spatial segmentation strategy. This paper describes the main results of this joint research. A multidisciplinary team involving experts in indoor air quality/ventilation, pedestrian movements and IT domains was established to develop a COVID risk analysis tool based on Building Information Model. The work started with specific analysis on two pilot schools in order to provide for the local administration specifications to minimize the spread of the virus. Different recommendations were published to optimize/validate the use of ventilation systems and the strategy of student occupancy and student flow segmentation within the building. This COVID expertise has been digitized in order to manage a quick risk analysis on the entire building that could be used by the public administration through an easy user interface implemented in a free BIM Management software. One of the most interesting results is to enable a dynamic comparison of different ventilation system scenarios and space occupation strategy inside the BIM model. This concurrent engineering approach provides users with the optimal solution according to both ventilation and pedestrian flow expertise.

Simulation Model for Optimizing Energy in Supply Chain Management

In today's world, with increasing environmental awareness, firms are facing severe pressure from various stakeholders, including the government and customers, to reduce their harmful effects on the environment. Over the past few decades, the increasing effects of global warming, climate change, waste, and air pollution have increased the global attention of experts to the issue of the green supply chain and led them to the optimal solution for greenery. Green supply chain management (GSCM) plays an important role in motivating the sustainability of the organization. With increasing environmental concerns, the main objective of the research is to use system thinking methodology and Vensim software for designing a dynamic system model for green supply chain and observing behaviors. Using this methodology, we look for the effects of a green supply chain structure on the behavioral dynamics of output variables. We try to simulate the complexity of GSCM in a period of 30 months and observe the complexity of behaviors of variables including sustainability, providing green products, and reducing energy consumption, and consequently reducing sample pollution.

Mechanical Properties of Enset Fibers Obtained from Different Breeds of Enset Plant

Enset fiber is agricultural waste and available in a surplus amount in Ethiopia. However, the hypothesized variation in properties of this fiber due to diversity of its plant source breed, fiber position within plant stem and chemical treatment duration had not proven that its application for the development of composite products is problematic. Currently, limited data are known on the functional properties of the fiber as a potential functional fiber. Thus, an effort is made in this study to narrow the knowledge gaps by characterizing it. The experimental design was conducted using Design-Expert software and the tensile test was conducted on Enset fiber from 10 breeds: Dego, Dirbo, Gishera, Itine, Siskela, Neciho, Yesherkinke, Tuzuma, Ankogena, and Kucharkia. The effects of 5% Na-OH surface treatment duration and fiber location along and across the plant pseudostem was also investigated. The test result shows that the rupture stress variation is not significant among the fibers from 10 Enset breeds. However, strain variation is significant among the fibers from 10 Enset breeds that breed Dego fiber has the highest strain before failure. Surface treated fibers showed improved rupture strength and elastic modulus per 24 hours of treatment duration. Also, the result showed that chemical treatment can deteriorate the load-bearing capacity of the fiber. The raw fiber has the higher load-bearing capacity than the treated fiber. And, it was noted that both the rupture stress and strain increase in the top to bottom gradient, whereas there is no significant variation across the stem. Elastic modulus variation both along and across the stem was insignificant. The rupture stress, elastic modulus, and strain result of Enset fiber are 360.11 ± 181.86 MPa, 12.80 ± 6.85 GPa and 0.04 ± 0.02 mm/mm, respectively. These results show that Enset fiber is comparable to other natural fibers such as abaca, banana, and sisal fibers and can be used as alternatives natural fiber for composites application. Besides, the insignificant variation of properties among breeds and across stem is essential for all breeds and all leaf sheath of the Enset fiber plant for fiber extraction. The use of short natural fiber over the long is preferable to reduce the significant variation of properties along the stem or fiber direction. In conclusion, Enset fiber application for composite product design and development is mechanically feasible.

Protection of Cultural Heritage against the Effects of Climate Change Using Autonomous Aerial Systems Combined with Automated Decision Support

The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.

The Socio-Economic Impact of the English Leather Glove Industry from the 17th Century to Its Recent Decline

Gloves are significant physical objects, being one of the oldest forms of dress. Glove culture is part of every facet of life; its extraordinary history encompasses practicality, and symbolism reflecting a wide range of social practices. The survival of not only the gloves but associated articles enables the possibility to analyse real lives, however so far this area has been largely neglected. Limited information is available to students, researchers, or those involved with the design and making of gloves. There are several museums and independent collectors in England that hold collections of gloves (some from as early as 16th century), machinery, tools, designs and patterns, marketing materials and significant archives which demonstrate the rich heritage of English glove design and manufacturing, being of national significance and worthy of international interest. Through a research glove network which now exists thanks to research grant funding, there is potential for the holders of glove collections to make connections and explore links between these resources to promote a stronger understanding of the significance, breadth and heritage of the English glove industry. The network takes an interdisciplinary approach to bring together interested parties from academia, museums and manufacturing, with expert knowledge of the production, collections, conservation and display of English leather gloves. Academics from diverse arts and humanities disciplines benefit from the opportunities to share research and discuss ideas with network members from non-academic contexts including museums and heritage organisations, industry, and contemporary designers. The fragmented collections when considered in entirety provide an overview of English glove making since earliest times and those who wore them. This paper makes connections and explores links between these resources to promote a stronger understanding of the significance, breadth and heritage of the English Glove industry. The following areas are explored: current content and status of the individual museum collections, potential links, sharing of information histories, social and cultural and relationship to history of fashion design, manufacturing and materials, approaches to maintenance and conservation, access to the collections and strategies for future understanding of their national significance. The facilitation of knowledge exchange and exploration of the collections through the network informs organisations’ future strategies for the maintenance, access and conservation of their collections. By involving industry in the network, it is possible to ensure a contemporary perspective on glove-making in addition to the input from heritage partners. The slow fashion movement and awareness of artisan craft and how these can be preserved and adopted for glove and accessory design is addressed. Artisan leather glove making was a skilled and significant industry in England that has now declined to the point where there is little production remaining utilising the specialist skills that have hardly changed since earliest times. This heritage will be identified and preserved for future generations of the rich cultural history of gloves may be lost.

Implementation of Building Information Modeling in Turkish Government Sector Projects

In recent years, the Building Information Modeling (BIM) approach has been developed expeditiously. As people see the benefits of this approach, it has begun to be used widely in construction projects and some countries made it mandatory to get more benefits from it. To promote the implementation of BIM in construction projects, it will be helpful to get some relevant information from surveys and interviews. The purpose of this study is to research the current adoption and implementation of BIM in public projects in Turkey. This study specified the challenges of BIM implementation in Turkey and proposed some solutions to overcome them. In this context, the challenges for BIM implementation and the factors that affect the BIM usage are determined based on previous academic researches and expert opinions by conducting interviews and questionnaire surveys. Several methods are used to process information in order to obtain weights of different factors to make BIM widespread in Turkey. This study concluded interviews' and questionnaire surveys' outcomes and proposed some suggestions to promote the implementation of BIM in Turkey. We believe research findings will be a good reference for boosting BIM implementation in Turkey.

Rule-Based Expert System for Headache Diagnosis and Medication Recommendation

With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.

A Systematic Map of the Research Trends in Wildfire Management in Mediterranean-Climate Regions

Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Air Handling Units Power Consumption Using Generalized Additive Model for Anomaly Detection: A Case Study in a Singapore Campus

The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.