Search results for: cross-validation support vector machine

Authors: Vasantha Gouri Prathapagiri

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Innovations in ICT sector facilitate qualitative life style for citizens across the globe. Countries that facilitate usage of new techniques in ICT, i.e., big data analytics find it easier to fulfil the needs of their citizens. Big data is characterised by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves into the field of machine learning, artificial intelligence all leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy making is a proper way to march towards all round development of any country. The data driven insights can help the government to take important strategic decisions with regard to socio-economic development of her country. Developed nations like UK and USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need for big data analytics adaptation in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focussed on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet the results are not as effective as they should be. Big data has a major role to play in this context as can assist in improving both policy making and implementation aiming at all round development of the country.

Keywords: Digital India Mission, public service delivery system, public policy, Indian administration

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Authors: Ana Mercedes Vernia Carrasco

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The objective of this work is to reflect through the theoretical framework on the access to the university for the formation of a degree in a teacher of primary education. The University Access Tests in Spain evaluate a series of skills and competencies in writing, which leave aside the sample of another set of skills and tools that this type of test cannot evaluate. In the last years, a very much diversified student body has arrived in the classrooms of the Universities. Nowadays, talking about special education means attending to the changes that are being experienced in this area. At present, the educational model focuses on the reinforcement by the educational institutions so that they form the students according to their personal characteristics and that it is not the students that must adapt to the system. A bibliographic review plus some years of experience in training for the future teacher allows us to make an initial assessment about the lack of rigor in the tests of access to the university. In conclusion, we can say that, although we are not a specialist in the type of Special Educational Needs that can manifest the students, therefore, we understand that teacher today needs training and support to develop their teaching with the best quality possible. These teacher and student needs also imply more institutional support.

Keywords: training, special needs, didactics, music

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Authors: M. O. Durojaye, J. T. Agee

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This paper is on the one-dimensional, positive temperature coefficient (PTC) thermistor model with a hyperbolic tangent function approximation for the electrical conductivity. The method of asymptotic expansion was adopted to obtain the steady state solution and the unsteady-state response was obtained using the method of lines (MOL) which is a well-established numerical technique. The approach is to reduce the partial differential equation to a vector system of ordinary differential equations and solve numerically. Our analysis shows that the hyperbolic tangent approximation introduced is well suitable for the electrical conductivity. Numerical solutions obtained also exhibit correct physical characteristics of the thermistor and are in good agreement with the exact steady state solutions.

Keywords: electrical conductivity, hyperbolic tangent function, PTC thermistor, method of lines

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Authors: Jiawei Dai, Xinrong Li, Yulong Sun, Yunxiao Hao

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Recently, participatory approaches have become popular in a variety of fields, including social work, community, and population health, as important research tools for researchers to understand and immerse communities and conceptualize social phenomena. The participatory visual research methods promote the diversification and depth of the exploration process and communication forms to support the feasibility and practicality of the scheme, which helps to further inspire designers and avoid blind spots caused by the solidification of single thinking. This paper focuses on how to develop visual toolkits for participatory methods to assist and shape crowd participation and trigger idea generation in community issues. This project helps to verify the value of participatory visual tools in shaping participation and arousing expression, which provides support for gaining community diversity insights and community problem-solving. In addition, a visual toolbox was developed based on an actual case in a community for field testing, and further discussion was carried out after the data results were analyzed.

Keywords: participatory design, community service, visual toolbox, visual metaphor

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Authors: Elena Carbone, Chiara Meneghetti, Ivan Innocenti, Monica Musicanti, Paola Volpe, Francesca Pazzaglia

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Promoting environmental sustainability is becoming a priority for organizations. Little is known, however, on the extent to which green workplace behaviors are linked, alongside organizational determinants, and also to various employees’ individual characteristics. The BE-GREEN research project, in collaboration with Eni S.p.A., aimed at investigating the relationship between the adoption of green workplace behaviors and various employees’ job-related and broader individual characteristics as well as organizational determinants. A sample of 513 Eni employees was administered a survey assessing the adoption of green workplace behaviors and the management of events (e.g., near-miss, unsafe conditions, weak signals) that could anticipate the occurrence of incidents with a harmful environmental impact. The survey also assessed employees’ job-related (e.g., proneness toward behaving pro-environmentally at work) and general (e.g., soft skills, connectedness to nature and environmental awareness) characteristics and perceived organizational support (e.g., environmental culture, leadership). Results showed that the adoption of green workplace behaviors was associated with employees’ proneness toward behaving pro-environmentally at work, and these factors were, in turn, influenced by broader individual characteristics related to soft skills as well as a connectedness to nature and environmental awareness, along with perceived organizational support. The management of events potentially anticipating the occurrence of incidents with a harmful environmental impact was mainly associated with perceived organizational support. These findings highlight how, alongside organizational determinants, different employees’ individual characteristics influence their adoption of green workplace behaviors, with important implications for the development of interventions tailored to promote environmental sustainability in organizations.

Keywords: green workplace behaviors, soft skills, connectedness to nature, environmental awareness.

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Adam J. Bowen

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Abstract— Should robots have rights or legal protections. Often debates concerning whether robots and AI should be afforded rights focus on conditions of personhood and the possibility of future advanced forms of AI satisfying particular intrinsic cognitive and moral attributes of rights-holding persons. Such discussions raise compelling questions about machine consciousness, autonomy, and value alignment with human interests. Although these are important theoretical concerns, especially from a future design perspective, they provide limited guidance for addressing the moral and legal standing of current and near-term AI that operate well below the cognitive and moral agency of human persons. Robots and AI are already being pressed into service in a wide range of roles, especially in healthcare and biomedical contexts. The design and large-scale implementation of robots in the context of core societal institutions like healthcare systems continues to rapidly develop. For example, we bring them into our homes, hospitals, and other care facilities to assist in care for the sick, disabled, elderly, children, or otherwise vulnerable persons. We enlist surgical robotic systems in precision tasks, albeit still human-in-the-loop technology controlled by surgeons. We also entrust them with social roles involving companionship and even assisting in intimate caregiving tasks (e.g., bathing, feeding, turning, medicine administration, monitoring, transporting). There have been advances to enable severely disabled persons to use robots to feed themselves or pilot robot avatars to work in service industries. As the applications for near-term AI increase and the roles of robots in restructuring our biomedical practices expand, we face pressing questions about the normative implications of human-robot interactions and collaborations in our collective worldmaking, as well as the moral and legal status of robots. This paper argues that robots operating in public and private spaces be afforded some protections as either moral patients or legal agents to establish prohibitions on robot abuse, misuse, and mistreatment. We already implement robots and embed them in our practices and institutions, which generates a host of human-to-machine and machine-to-machine relationships. As we interact with machines, whether in service contexts, medical assistance, or home health companions, these robots are first encountered in relationship to us and our respective roles in the encounter (e.g., surgeon, physical or occupational therapist, recipient of care, patient’s family, healthcare professional, stakeholder). This proposal aims to outline a framework for establishing limiting factors and determining the extent of moral or legal protections for robots. In doing so, it advocates for a relational approach that emphasizes the priority of mapping the complex contextually sensitive roles played and the relations in which humans and robots stand to guide policy determinations by relevant institutions and authorities. The relational approach must also be technically informed by the intended uses of the biomedical technologies in question, Design History Files, extensive risk assessments and hazard analyses, as well as use case social impact assessments.

Keywords: biomedical robots, robot ethics, robot laws, human-robot interaction

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Authors: Nicole Nicholson, Anne Spillane

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The purpose of this quantitative, descriptive analysis was to determine the success of a post-graduate new teacher education program, designed to teach educators the knowledge and skills necessary to use technology in the classroom, improve the ability to communicate with stakeholders, and implement EBPs and UDL principles into instruction for students with ASD (Autism Spectrum Disorders ). The success of candidates (n=20) in the program provided evidence as to how candidates were effectively able to use technology to create meaningful learning opportunities and implement EBPs for individuals with ASD. ≥90% of participants achieved the following competencies: podcast creation; technology used to share information about assistive technology; and created a resource website on ASD (including information on EBPs, local and national support groups, ASD characteristics, and the latest research on ASD). 59% of students successfully created animation. Results of the analysis indicated that the teacher education program was successful in teaching candidates desired competencies during its first year of implementation.

Keywords: autism spectrum disorders, ASD, evidence based practices, EBP, universal design for learning, UDL

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Authors: Jobo Dubihlela, Kofi Boamah

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The inimitable role of the internal auditing, challenges and the predicament of state-owned enterprises in emerging markets are acknowledged. Study sought to address the inter-related questions, about how does IAF complement the performance and sustainability of SOEs? How can effective IA control systems be implemented to improve the performance results and culture of SOEs in Namibia? The weaknesses inherent in the SOE sector, unfortunately, impacts on the IAF ability to effectively support the SOEs. Despite these challenges, the study has unearthed IAF potential capabilities to contribute to SOE survival in Namibia by complementing the governance practices of the sector. Using a quantitative research approach, the dataset was collected and analysed from SOEs to confirm the role of the internal auditing function (IAF) as an indispensable concomitant of SOE performance. The study adopted a data approach supported by the literary evidence, which enabled generalisation and connectedness of the issues being addressed. The outcome of the data analysis contributed to achieving the results, which are discussed and eventually support the conclusions reached. Results show that the intractable task of internal auditing depends on the leadership of the board of directors of the SOEs. Study also revealed critical priorities needed to influence policymakers and oversight bodies to overcome the iniquities influencing SOE operations, understand and embrace IAF to salvage a sector that has a lot to offer and yet is severely mismanaged. Results support literature on IA’s contribution to SOE development from a developing country’s point of view and is the first of its kind in Namibia. Findings suggest ways to possibly enhance knowledge development of future researchers and ‘wet their appetite’ for further research in emerging markets and on a global scale.

Keywords: internal auditing activity, state-owned enterprises, emerging markets, auditing function

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Authors: Farid Arya, Trevor Hyde, Andrea Trevisi, Paolo Basso, Danilo Bardaro

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Heat transfer through multiple pane windows can be reduced by creating a vacuum pressure less than 0.1 Pa between the glass panes, with low emittance coatings on one or more of the internal surfaces. Fabrication of vacuum glazing (VG) requires the formation of a hermetic seal around the periphery of the glass panes together with an array of support pillars between the panes to prevent them from touching under atmospheric pressure. Atmospheric pressure and temperature differentials induce stress which can affect the integrity of the glazing. Several parameters define the stresses in VG including the glass thickness, pillar specifications, glazing dimensions and edge seal configuration. Inherent stresses in VG can result in fractures in the glass panes and failure of the edge seal. In this study, stress in VG with different glass thicknesses is theoretically studied using Finite Element Modelling (FEM). Based on the finding in this study, suggestions are made to address problems resulting from the use of thinner glass panes in the fabrication of VG. This can lead to the development of high performance, light and thin VG.

Keywords: vacuum glazing, stress, vacuum insulation, support pillars

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Authors: Chu Shi Wei

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Supported employment in Malaysia is in the early stages of development. The development of supported employment in Malaysia is an important step towards the inclusion of individuals with disabilities who have previously lacked the necessary support for employment in the open labour market as they were confined to sheltered workshops. There is a paradigm shift from sheltered to supported employment as the sheltered workshop is based on the medical model of disability, which focuses on the disability of the individual and segregated training institutions. The paradigm shift revolves around the social model of disability, which emphasizes the abilities of the individual and the removal of the barriers in the environment by the provision of support. This study explores the development of supported employment by utilizing a mixed methods approach which consists of collecting quantitative data through a survey and interviewing participants to collect qualitative data. Job coaches from six employment sectors participated in the survey and interview. The findings of the study indicate that the role of job coaches is integral to the development of supported employment. The role of job coaches includes job matching, on-the-job training, and developing natural supports to foster greater diversity and inclusion in the workplace.

Keywords: supported employment, disabilities, diversity, development

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Kai-Jui Kou, Tzu-Ling Shen, Ying-Fang Wang

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The objectives of the present study are to characterize nanoparticles generated from the different working type in 3D printing room and the stack flue during 3D printing process. The studied laboratory (10.5 m× 7.2 m × 3.2 m) with a ventilation rate of 500 m³/H is installed a 3D metal printing machine. Direct-reading instrument of a scanning mobility particle sizer (SMPS, Model 3082, TSI Inc., St. Paul, MN, USA) was used to conduct static sampling for nanoparticle number concentration and particle size distribution measurements. The SMPS obtained particle number concentration at every 3 minutes, the diameter of the SMPS ranged from 11~372 nm when the aerosol and sheath flow rates were set at 0.6 and 6 L/min, respectively. The concentrations of background, printing process, clearing operation, and screening operation were performed in the laboratory. On the other hand, we also conducted nanoparticle measurement on the 3D printing machine's stack flue to understand its emission characteristics. Results show that the nanoparticles emitted from the different operation process were the same distribution in the form of the uni-modal with number median diameter (NMD) as approximately 28.3 nm to 29.6 nm. The number concentrations of nanoparticles were 2.55×10³ count/cm³ in laboratory background, 2.19×10³ count/cm³ during printing process, 2.29×10³ count/cm³ during clearing process, 3.05×10³ count/cm³ during screening process, 2.69×10³ count/cm³ in laboratory background after printing process, and 6.75×10³ outside laboratory, respectively. We found that there are no emission nanoparticles during the printing process. However, the number concentration of stack flue nanoparticles in the ongoing print is 1.13×10⁶ count/cm³, and that of the non-printing is 1.63×10⁴ count/cm³, with a NMD of 458 nm and 29.4 nm, respectively. It can be confirmed that the measured particle size belongs to easily penetrate the filter in theory during the printing process, even though the 3D printer has a high-efficiency filtration device. Therefore, it is recommended that the stack flue of the 3D printer would be equipped with an appropriate dust collection device to prevent the operators from exposing these hazardous particles.

Keywords: nanoparticle, particle emission, 3D printing, number concentration

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

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Authors: Weber-Lewerenz Bianca

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Digitization is developing fast and has become a powerful tool for digital planning, construction, and operations. Its transformation bears high potentials for companies, is critical for success, and thus, requires responsible handling. This study provides an assessment of calls made in the sustainable development goals by the United Nations (SDGs), White Papers on AI by international institutions, EU-Commission and German Government requesting for the consideration and protection of values and fundamental rights, the careful demarcation between machine (artificial) and human intelligence and the careful use of such technologies. The study discusses digitization and the impacts of artificial intelligence (AI) in construction engineering from an ethical perspective by generating data via conducting case studies and interviewing experts as part of the qualitative method. This research evaluates critically opportunities and risks revolving around corporate digital responsibility (CDR) in the construction industry. To the author's knowledge, no study has set out to investigate how CDR in construction could be conceptualized, especially in relation to the digitization and AI, to mitigate digital transformation both in large, medium-sized, and small companies. No study addressed the key research question: Where can CDR be allocated, how shall its adequate ethical framework be designed to support digital innovations in order to make full use of the potentials of digitization and AI? Now is the right timing for constructive approaches and apply ethics-by-design in order to develop and implement a safe and efficient AI. This represents the first study in construction engineering applying a holistic, interdisciplinary, inclusive approach to provide guidelines for orientation, examine benefits of AI and define ethical principles as the key driver for success, resources-cost-time efficiency, and sustainability using digital technologies and AI in construction engineering to enhance digital transformation. Innovative corporate organizations starting new business models are more likely to succeed than those dominated by conservative, traditional attitudes.

Keywords: construction engineering, digitization, digital transformation, artificial intelligence, ethics, corporate digital responsibility, digital innovation

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Authors: Sin Ying Tan, Mohammed Alloghani, A. J. Aljaaf, Abir Hussain, Jamila Mustafina

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Industry 4.0 is a term frequently used to describe the new upcoming industry era. Higher education institutions aim to prepare students to fulfil the future industry needs. Advancement of digital technology has paved the way for the evolution of education and technology. Evolution of education has proven its conservative nature and a high level of resistance to changes and transformation. The gap between the industry's needs and competencies offered generally by education is revealing the increasing need to find new educational models to face the future. The aim of this study was to identify the main issues faced by both universities and students in preparing the future workforce. From December 2018 to April 2019, a regional qualitative study was undertaken in Liverpool, United Kingdom (UK). Interviews were conducted with employers, faculty members and undergraduate students, and the results were analyzed using the open coding method. Four main issues had been identified, which are the characteristics of the future workforce, student's readiness to work, expectations on different roles played at the tertiary education level and awareness of the latest trends. The finding of this paper concluded that the employers and academic practitioners agree that their expectations on each other’s roles are different and in order to face the rapidly changing technology era, students should not only have the right skills, but they should also have the right attitude in learning. Therefore, the authors address this issue by proposing a learning framework known as 'ASK SUMA' framework as a guideline to support the students, academicians and employers in meeting the needs of 'Industry 4.0'. Furthermore, this technology era requires the employers, academic practitioners and students to work together in order to face the upcoming challenges and fast-changing technologies. It is also suggested that an interactive system should be provided as a platform to support the three different parties to play their roles.

Keywords: attitude, expectations, industry needs, knowledge, skills

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Authors: Humaira Mujeeb, Farah Qadir

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The present study aimed to explore the association between interpersonal relationship and postpartum depression with a special focus on gender of the infant among women in Gilgit, Gilgit-Baltistan, Pakistan. The research was quantitative in nature. It was a correlation study with a cross-sectional study design. The target population was women between six weeks to six months after the delivery of a baby. The sample size of 158 women has been computed by using G*Power (3.0.10 version). The sample was taken through quota sampling technique which was used to gather data according to the specifically predefined groups (79 women with female infants and 79 women with male infants). The sample was selected non-randomly according to the fixed quota. A protocol which had demographic and interpersonal relationship variables alongside with the Urdu version Edinburgh postnatal depression scale was used to collect the relevant data. The data was analyzed by using SPSS 16.0 software package. A statistically significant association between the attachment with husband in women who had a female infant and postpartum depression has been found. The association between the husband’s emotional and physical support in women who had a female infant and postpartum depression had also been found significant. In case of women with a male infant, the association between support of in-laws and postpartum depression is statistically significant. An association between the violence/discrimination based on the basis of infant's gender in women who had a female infant and postpartum depression is also found. These findings points out that when studying the correlates of postpartum depression, it is imperative to carry out an analysis in the context of gender by considering gender of the infant especially in societies where strict gender preferences exists.

Keywords: infant, gender, attachment, husband, in-laws, support, violence, discrimination, Edinburgh postnatal depression scale, Gilgit, Pakistan

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Authors: Xiaolian Jiang, Dongling Liu, Kun Liu

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Aims: To examine the prevalence of POST-TRAUMATIC STRESS DISORDER (PTSD) symptoms among Tibetan adolescents in heavily-hit disaster area three years after Yushu earthquake, and to explore the interactions of the psycho-social-genetic risk factors. Methods: This was a three-stage study. Firstly, demographic variables，PTSD Checklist-Civilian Version （PCL-C），the Internality、Powerful other、Chance Scale，（IPC），Coping Style Scale（CSS），and the Social Support Appraisal（SSA）were used to explore the psychosocial factors of PTSD symptoms among adolescent survivors. PCL-C was used to examine the PTSD symptoms among 4072 Tibetan adolescents，and the Structured Clinical Interview for DSM-IV Disorders（SCID）was used by psychiatrists to make the diagnosis precisely. Secondly，a case-control trial was used to explore the relationship between PTSD and gene polymorphisms. 287adolescents diagnosed with PTSD were recruited in study group, and 280 adolescents without PTSD in control group. Polymerase chain reaction-restriction fragment length polymorphism technology（PCR-RFLP）was used to test gene polymorphisms. Thirdly，SPSS 22.0 was used to explore the interactions of the psycho-social-genetic risk factors of PTSD on the basis of the above results. Results and conclusions: 1．The prevalence of PTSD was 9.70%. 2．The predictive psychosocial factors of PTSD included earthquake exposure, support from others, imagine, abreact, tolerant, powerful others and family support. 3．Synergistic interactions between A1 gene of DRD2 TaqIA and the external locus of control, negative coping style, severe earthquake exposure were found. Antagonism interactions between A1 gene of DRD2 TaqIA and poor social support was found. Synergistic interactions between A1/A1 genotype and the external locus of control, negative coping style were found. Synergistic interactions between 12 gene of 5-HTTVNTR and the external locus of control, negative coping style, severe earthquake exposure were found. Synergistic interactions between 12/12 genotype and the external locus of control, negative coping style, severe earthquake exposure were also found.

Keywords: adolescents, earthquake, PTSD, risk factors

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Authors: Shah Muhammad Butt

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The study aimed to investigate the factors influencing the adoption of e-governance in Pakistan's public universities and how that adoption has affected organizational performance. An online Likert scale survey was utilized to gather information from 350 participants from different public universities in Pakistan. The data were examined using descriptive statistics and correlation analysis. The findings suggest that organizational culture, infrastructure, and leadership support are among the elements impacting the adoption of e-governance at Pakistan's public sector universities. A further finding of the study was that e-governance adoption benefited organizational performance, including effectiveness, efficiency, and customer satisfaction. The study emphasizes the significance of e-governance adoption at public sector universities and the demand for successful policies and strategies to support its implementation. To increase organisational performance and raise the standard of higher education in Pakistan, policymakers and university administrators should use the study's findings to develop and practice e-governance policies and initiatives.

Keywords: e-governance, adoption, public sector universities, Pakistan, organizational performance, higher education, technology, ICT, factors, comparative analysis

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Authors: Lan Wu

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The declared transformation towards a ‘new electricity system dominated by renewable energy’ by China requires a cleaner electricity consumption mix with high shares of renewable energy sourced-electricity (RES-E). Unfortunately, integration of RES-E into Chinese electricity markets remains a problem pending more robust legal support, evidenced by the curtailment of wind and solar power as a consequence of integration constraints. The upcoming energy law of the PRC (energy law) is expected to provide such long-awaiting support and coordinate the existing diverse sector-specific laws to deal with the weak implementation that dampening the delivery of their desired regulatory effects. However, in the shadow of the COVID-19 crisis, it remains uncertain how this new energy law brings synergies to RES-E integration, mindful of the significant impacts of the pandemic. Through the theoretical lens of the interplay between China’s electricity reform and legislative development, the present paper investigates whether there is a paradigm shift in energy law regarding renewable energy integration compared with the existing sector-specific energy laws. It examines the 2020 draft for comments on the energy law and analyses its relationship with sector-specific energy laws focusing on RES-E integration. The comparison is drawn upon five key aspects of the RES-E integration issue, including the status of renewables, marketisation, incentive schemes, consumption mechanisms, access to power grids, and dispatching. The analysis shows that it is reasonable to expect a more open and well-organized electricity market enabling absorption of high shares of RES-E. The present paper concludes that a period of prosperous development of RES-E in the post-COVID-19 era can be anticipated with the legal support by the upcoming energy law. It contributes to understanding the signals China is sending regarding the transition towards a cleaner energy future.

Keywords: energy law, energy transition, electricity market reform, renewable energy integration

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Authors: John Q. Todd

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Given that modern equipment can provide comprehensive health, status, and error condition data via built-in sensors, maintenance organizations have a new and valuable source of insight to take advantage of. This presentation will expose what these data payloads might look like and how they can be filtered, visualized, calculated into metrics, used for machine learning, and generate alerts for further action.

Keywords: condition based maintenance, equipment data, metrics, alerts

Procedia PDF Downloads 171

Authors: Carlos A. C. G. Neto, Natan C. G. e Silva , Thaís de O. Costa, Luciana R. B. Gonçalves, Maria V. P. Rocha

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β-galactosidases (E.C. 3.2.1.23) are enzymes that have attracted by catalyzing the hydrolysis of lactose and in producing galacto-oligosaccharides by favoring transgalactosylation reactions. These enzymes, when immobilized, can have some enzymatic characteristics substantially improved, and the coating of supports with multifunctional polymers is a promising alternative to enhance the stability of the biocatalysts, among which polyethylenimine (PEI) stands out. PEI has certain properties, such as being a flexible polymer that suits the structure of the enzyme, giving greater stability, especially for multimeric enzymes such as β-galactosidases. Besides that, protects them from environmental variations. The use of chitosan support coated with PEI could improve the catalytic efficiency of β-galactosidase from Kluyveromyces lactis in the transgalactosylation reaction for the production of prebiotics, such as lactulose since this strain is more effective in the hydrolysis reaction. In this context, the aim of the present work was first to develop biocatalysts of β-galactosidase from K. lactis immobilized on chitosan-coated with PEI, determining the immobilization parameters, its operational and thermal stability, and then to apply it in hydrolysis and transgalactolisation reactions to produce lactulose using whey as a substrate. The immobilization of β-galactosidase in chitosan previously functionalized with 0.8% (v/v) glutaraldehyde and then coated with 10% (w/v) PEI solution was evaluated using an enzymatic load of 10 mg protein per gram support. Subsequently, the hydrolysis and transgalactosylation reactions were conducted at 50 °C, 120 RPM for 20 minutes, using whey supplemented with fructose at a ratio of 1:2 lactose/fructose, totaling 200 g/L. Operational stability studies were performed in the same conditions for 10 cycles. Thermal stabilities of biocatalysts were conducted at 50 ºC in 50 mM phosphate buffer, pH 6.6 with 0.1 mM MnCl2. The biocatalyst whose support was coated was named CHI_GLU_PEI_GAL, and the one that was not coated was named CHI_GLU_GAL. The coating of the support with PEI considerably improved the parameters of immobilization. The immobilization yield increased from 56.53% to 97.45%, biocatalyst activity from 38.93 U/g to 95.26 U/g and the efficiency from 3.51% to 6.0% for uncoated and coated support, respectively. The biocatalyst CHI_GLU_PEI_GAL was better than CHI_GLU_GAL in the hydrolysis of lactose and production of lactulose, converting 97.05% of lactose at 5 min of reaction and producing 7.60 g/L lactulose in the same time interval. QUI_GLU_PEI_GAL biocatalyst was stable in the hydrolysis reactions of lactose during the 10 cycles evaluated, converting 73.45% lactose even after the tenth cycle, and in the lactulose production was stable until the fifth cycle evaluated, producing 10.95 g/L lactulose. However, the thermal stability of CHI_GLU_GAL biocatalyst was superior, with a half-life time 6 times higher, probably because the enzyme was immobilized by covalent bonding, which is stronger than adsorption (CHI_GLU_PEI_GAL). Therefore, the strategy of coating the supports with PEI has proven to be effective for the immobilization of β-galactosidase from K. lactis, considerably improving the immobilization parameters, as well as, the catalytic action of the enzyme. Besides that, this process can be economically viable due to the use of an industrial residue as a substrate.

Keywords: β-galactosidase, immobilization, kluyveromyces lactis, lactulose, polyethylenimine, transgalactosylation reaction, whey

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Authors: Siti Mariani, Arwin DW Sumari, Retno Gumilang Dewi

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This paper analyzes the necessity of a structured tariff calculation for geothermal electricity in Indonesia. Indonesia is blessed with abundant natural resources and a choices of energy resources to generate electricity among other are coal, gas, biomass, hydro to geothermal, creating a fierce competition in electricity tariffs. While geothermal is inline with energy security principle and green growth initiative, it requires a huge capital funding. Geothermal electricity development consists of phases of project with each having its own financial characteristics. The Indonesian government has set a support in the form of ceiling price of geothermal electricity tariff by 11 U.S cents / kWh. However, the government did not set a levelized cost of geothermal, as an indication of lower limit capacity class, to which support is given. The government should establish a levelized cost of geothermal energy to reflect its financial capability in supporting geothermal development. Aside of that, the government is also need to establish a structured tariff calculation to reflect a fair and transparent business cooperation.

Keywords: load fator, levelized cost of geothermal, geothermal power plant, structured tariff calculation

Procedia PDF Downloads 431

Authors: Riyona Chetty, Raisuyah Bhagwan, Nalini Govender

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Background: A myriad of physical, psychosocial, and environmental sequelae are associated with limb loss. However, there is a paucity of empirical South African data, which focuses on these sequelae, how they interface with the amputee’s quality of life as well as the challenges they experience following amputation. Objective: This study sought to explore the biopsychosocial effects of amputation and how amputation affected the quality of life of transtibial amputees. Setting: Participants were recruited from a medical facility, under the KwaZulu-Natal Department of Health in South Africa. Methods: A qualitative approach guided this study. Data was collected using one-on-one interviews with 14 unilateral transtibial amputees. Data was analysed thematically. Results: Five broad themes emerged from the inquiry, which captured amputees’ experiences of phantom limb pain, body image disturbances, and their challenges related to adapting to daily activities. Participants also expressed the salience of familial support as well as the importance of psychological interventions to cope. Conclusion: The findings suggested that support networks and professional psychological intervention are imperative in facilitating successful adjustment to the amputation experience. Raising awareness of limb loss in both, rural and urban settings may help reduce the stigma attached to it. Contribution: Quality of life comprises several domains, namely physical, psychological, environmental, and social albeit limited local and international data exists regarding the environmental and social effects. This study brought to the fore the positive and negative effects of amputation in each domain, as well as various strategies that facilitate successful adjustment to amputation.

Keywords: amputation, quality of life, biopsychosocial, phantom limb pain, body image, support

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Authors: Muhammad Usman

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Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

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Authors: Jilu David

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Background: Schizophrenia is one of the most misunderstood mental illnesses across the globe. Lack of understanding about mental illnesses often delay treatment, severely affects the functionality of the person, and causes distress to the family. The study, Video-based Psychoeducation for Caregivers of Persons with Schizophrenia, consisted of developing a psychoeducational video about Schizophrenia, its symptoms, causes, treatment, and the importance of family support. Methodology: A quasi-experimental pre-post design was used to understand the feasibility of the study. Qualitative analysis strengthened the feasibility outcomes. Knowledge About Schizophrenia Interview was used to assess the level of knowledge of 10 participants, before and after the screening of the video. Results: Themes of usefulness, length, content, educational component, format of the intervention, and language emerged in the qualitative analysis. There was a statistically significant difference in the knowledge level of participants before and after the video screening. Conclusion: The statistical and qualitative analysis revealed that the video-based psychoeducation program was feasible and that it facilitated a general improvement in knowledge of the participants.

Keywords: Schizophrenia, mental illness, psychoeducation, video-based psychoeducation, family support

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Authors: Gulnara N. Nabiyeva, Stephen M. Wheeler

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Geographic Information Systems (GIS) is a multipurpose computer-based tool that provides a sophisticated ability to map and analyze data on different spatial layers. However, GIS is far more easily applied in some policy areas than others. This paper seeks to determine the areas of sustainable development, including environmental, economic, and social dimensions, where GIS has been used to date to support efforts to implement the United Nations Sustainable Development Goals (SDGs), and to discuss potential areas where it might be used more. Based on an extensive analysis of published literature, we ranked the SDGs according to how frequently GIS has been used to study related policy. We found that SDG#15 “Life on Land” is most often addressed with GIS, following by SDG#11 “Sustainable Cities and Communities”, and SDG#13 “Climate Action”. On the other hand, we determined that SDG#2 “Zero Hunger”, SDG#8 “Decent Work and Economic Growth”, and SDG#16 “Peace, Justice, and Strong Institutions” are least addressed with GIS. The paper outlines some specific ways that GIS might be applied to the SDGs least linked to this tool currently.

Keywords: GIS, GIS application, sustainable community development, sustainable development goals

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Authors: G. Erkomaishvili, M. Kobalava, T. Lazariashvili, M. Saghareishvili

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The article discusses the consumer market of agricultural products and agricultural policy in Georgia. It is noted that development of the strategic areas of the agricultural sector needs a special support. These strategic areas should create the country's major export potential. It is important to develop strategies to access to the international markets, form extensive marketing network etc., which will become the basis for the promotion and revenue growth of the country. The Georgian agricultural sector, with the right state policy and support, can achieve success and gain access to the world market with competitive agricultural products. The paper discusses the current condition of agriculture, export and import of agricultural products and agricultural policy in Georgia. The conducted research concludes the information that there is an increasing demand on the green goods in the world market. Natural and climatic conditions of Georgia give a serious possibility of implementing it. The research presents an agricultural development strategy in Georgia and the findings and based on them recommendations are proposed.

Keywords: agriculture, export-import of agricultural products, agricultural cooperative society, agricultural policy, agricultural insurance

Procedia PDF Downloads 308