Search results for: conceptual network formalism

Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Peter J. Glinos

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The Alternative Education Resource Organization (AERO), one of the largest international hubs for alternative educators led by Jerry Mintz, has had a major impact on the global alternative education movement. The organization’s publications, like the AERO-Gramme Newsletter and its successor, the Education Revolution Magazine, allowed members across the globe to discuss issues, share support, and submit writings on policies and reforms. Stored on AERO's online digital archive, this work uses these publications from 1989 to 2011 to investigate the network's entanglements with America, Canada, Russia, Ukraine, Israel, Palestine, Japan, India, and Guatemala. Inspired by Reinhart Koselleck, this historical analysis will trace AERO’s entanglements within the United States, Japan, and Russia, contextualizing each of these multiple temporalities within the history of each nation’s education system, the developments within AERO, and the global geo-political climate at the time of AERO’s expansion. To help remedy the lack of attention paid by global historians to the role state organizations play supporting global networks, as noted in What is Global History? by Sebastian Conrad, this work will focus on the relationship between AERO and state actors.

Keywords: global history, history of education, neoliberalism, transnational history, alternative education

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Authors: Salha Abdullah Ali Al-Shamrani, Maha Muhammad Dhaher Aljuhani, Eman Ali Ahmed Aldhaheri

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With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: internet of things, spoofing, IoT, access control, blockchain, raspberry pi

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Authors: Richard Maguire

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This research evaluates the efficiency of using mobile HEPA filters to reduce localized Particulate Matter (PM), Total Volatile Organic Chemical (TVOC) and Formaldehyde (HCHO) Air Pollution. The research is being performed using a standard HEPA filter that is tube fitted and attached to a motor vehicle. The velocity of the vehicle is used to generate the pressure difference that allows the filter to remove PM, VOC and HCOC pollution from the localized atmosphere of a road transport traffic route. The testing has been performed on a sample of traffic routes in Non-Sparse and Sparse urban environments within the UK. Pre and Post filter measuring of the PM2.5 Air Quality has been carried out along with demographics of the climate environment, including live filming of the traffic conditions. This provides a base line for future national and international research. The effectiveness measurement is generated through evaluating the difference in PM2.5 Air Quality measured pre- and post- the mobile filter test equipment. A series of further research opportunities and future exploitation options are made based on the results of the research.

Keywords: high efficiency particulate air, HEPA filter, particulate matter, traffic pollution

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Authors: Marvin Ricardo Awarab

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There has never been a greater need for telecom services. The Internet of Things (IoT), 5G networking, and edge computing are the driving forces behind this increased demand. The fierce demand offers communications service providers significant income opportunities. The telecom sector is centered on automation, and realizing a digital operation that functions as a real-time business will be crucial for the industry as a whole. Automation in telecom refers to the application of technology to create a more effective, quick, and scalable alternative to the conventional method of operating the telecom industry. With the promotion of 5G and the Internet of Things (IoT), telecom companies will continue to invest extensively in telecom automation technology. Automation offers benefits in the telecom industry; developing countries such as Namibia may not fully tap into such benefits because of the lack of funds and infrastructural resources to invest in automation. This paper fully investigates the benefits of automation in the telecom industry. Furthermore, the paper identifies hiccups that developing countries such as Namibia face in their quest to fully introduce automation in the telecom industry. Additionally, the paper proposes possible avenues that Namibia, as a developing country, adopt investing in automation infrastructural resources with the aim of reaping the full benefits of automation in the telecom industry.

Keywords: automation, development, internet, internet of things, network, telecom, telecommunications policy, 5G

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Authors: Rowan P. Martnishn

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During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.

Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding

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Authors: Mardiana Ahamad Zabidi, Akmalluddin Md. Yunus

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Soursop (Anona muricata) is one of the underutilized tropical fruits containing nutrients, particularly dietary fibre and antioxidant properties that are beneficial to human health. This objective of this study is to investigate the feasibility of matured soursop pulp flour (SPF) to be substituted with high-protein wheat flour in bread. Bread formulation was substituted with different levels of SPF (0%, 5%, 10% and 15%). The effect on physicochemical properties and sensory attributes were evaluated. Higher substitution level of SPF resulted in significantly higher (p<0.05) fibre, protein and ash content, while fat and carbohydrate content reduced significantly (p<0.05). FESEM showed that the bread crumb surface of control and 5% SPF appeared to distribute evenly and coalesced by thin gluten film. However, higher SPF substitution level in bread formulation exhibited a deleterious effect by formation of discontinuous gluten network. For texture profile analysis, 5% SPF bread resulted in the lowest value of hardness. The score of sensory evaluation showed that 5% SPF bread received good acceptability and is comparable with control bread.

Keywords: soursop pulp flour, bread, physicochemical properties, sensory attributes, scanning electron microscopy (SEM)

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

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Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

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Authors: Rahul Agarwal, Ashutosh Singh

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Cervical cancer is one of the women related cancers which starts from the pre-cancerous cells and a fraction of women with pre-cancers of the cervix will develop cervical cancer. Cervical pre-cancers if treated in pre-invasive stage can prevent almost all true cervical squamous cell carcinoma. The present study investigates the genes and pathways that are involved in the progression of cervical cancer and are responsible in transition from pre-invasive stage to other advanced invasive stages. The study used GDS3292 microarray data to identify the stage specific genes in cervical cancer and further to generate the network of the significant genes. The microarray data GDS3292 consists of the expression profiling of 10 normal cervices, 7 HSILs and 21 SCCs samples. The study identifies 70 upregulated and 37 downregulated genes in HSIL stage while 95 upregulated and 60 downregulated genes in SCC stages. Biological process including cell communication, signal transduction are highly enriched in both HSIL and SCC stages of cervical cancer. Further, the ppi interaction of genes involved in HSIL and SCC stages helps in identifying the interacting partners. This work may lead to the identification of potential diagnostic biomarker which can be utilized for early stage detection.

Keywords: cervical cancer, HSIL, microarray, SCC

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Authors: Maria Areias, Diogo Simões, Ana Figueiredo, Anishur Rahman, Filipa Figueiredo, João Nunes

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It is expected that close to 7 billion people will live in urban areas by 2050. In order to improve the sustainability of the territories and its transition towards circular economy, it’s necessary to understand its metabolism and promote and guide the entrepreneurship answer. The study of a macroeconomic metabolism involves the quantification of the inputs, outputs and storage of energy, water, materials and wastes for an urban region. This quantification and analysis representing one opportunity for the promotion of green entrepreneurship. There are several methods to assess the environmental impacts of an urban territory, such as human and environmental risk assessment (HERA), life cycle assessment (LCA), ecological footprint assessment (EF), material flow analysis (MFA), physical input-output table (PIOT), ecological network analysis (ENA), multicriteria decision analysis (MCDA) among others. However, no consensus exists about which of those assessment methods are best to analyze the sustainability of these complex systems. Taking into account the weaknesses and needs identified, the CiiM - Circular Innovation Inter-Municipality project aims to define an uniform and globally accepted methodology through the integration of various methodologies and dynamic approaches to increase the efficiency of macroeconomic metabolisms and promoting entrepreneurship in a circular economy. The pilot territory considered in CiiM project has a total area of 969,428 ha, comprising a total of 897,256 inhabitants (about 41% of the population of the Center Region). The main economic activities in the pilot territory, which contribute to a gross domestic product of 14.4 billion euros, are: social support activities for the elderly; construction of buildings; road transport of goods, retailing in supermarkets and hypermarkets; mass production of other garments; inpatient health facilities; and the manufacture of other components and accessories for motor vehicles. The region's business network is mostly constituted of micro and small companies (similar to the Central Region of Portugal), with a total of 53,708 companies identified in the CIM Region of Coimbra (39 large companies), 28,146 in the CIM Viseu Dão Lafões (22 large companies) and 24,953 in CIM Beiras and Serra da Estrela (13 large companies). For the construction of the database was taking into account data available at the National Institute of Statistics (INE), General Directorate of Energy and Geology (DGEG), Eurostat, Pordata, Strategy and Planning Office (GEP), Portuguese Environment Agency (APA), Commission for Coordination and Regional Development (CCDR) and Inter-municipal Community (CIM), as well as dedicated databases. In addition to the collection of statistical data, it was necessary to identify and characterize the different stakeholder groups in the pilot territory that are relevant to the different metabolism components under analysis. The CIIM project also adds the potential of a Geographic Information System (GIS) so that it is be possible to obtain geospatial results of the territorial metabolisms (rural and urban) of the pilot region. This platform will be a powerful visualization tool of flows of products/services that occur within the region and will support the stakeholders, improving their circular performance and identifying new business ideas and symbiotic partnerships.

Keywords: circular economy tools, life cycle assessment macroeconomic metabolism, multicriteria decision analysis, decision support tools, circular entrepreneurship, industrial and regional symbiosis

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Authors: Rohini Sharma, Chandan Kumar Sahoo, Rama Krishna Gupta Potnuru

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Strong competitive forces and requirements to achieve efficiency are forcing the organizations to realize the necessity and inevitability of change. What's more, the trend does not appear to be abating. Researchers have estimated that about two thirds of change project fails. Empirical evidences further shows that organizations invest significantly in the planned change but people side is accounted for in a token or instrumental way, which is identified as one of the important reason, why change endeavours fail. However, whatever be the reason for change, organizational change readiness must be gauged prior to the institutionalization of organizational change. Hence, in this study the influence of employee voice and employee involvement on organizational change readiness via commitment-to-change is examined, as it is an area yet to be extensively studied. Also, though a recent study has investigated the interrelationship between leadership, organizational change readiness and commitment to change, our study further examined these constructs in relation with employee voice and employee involvement that plays a consequential role for organizational change readiness. Further, integrated conceptual model weaving varied concepts relating to organizational readiness with focus on commitment to change as mediator was found to be an area, which required more theorizing and empirical validation, and this study rooted in an Indian public sector organization is a step in this direction. Data for the study were collected through a survey among employees of Rourkela Steel Plant (RSP), a unit of Steel Authority of India Limited (SAIL); the first integrated Steel Plant in the public sector in India, for which stratified random sampling method was adopted. The schedule was distributed to around 700 employees, out of which 516 complete responses were obtained. The pre-validated scales were used for the study. All the variables in the study were measured on a five-point Likert scale ranging from “strongly disagree (1)” to “strongly agree (5)”. Structural equation modeling (SEM) using AMOS 22 was used to examine the hypothesized model, which offers a simultaneous test of an entire system of variables in a model. The study results shows that inter-relationship between employee voice and commitment-to-change, employee involvement and commitment-to-change and commitment-to-change and organizational change readiness were significant. To test the mediation hypotheses, Baron and Kenny’s technique was used. Examination of direct and mediated effect of mediators confirmed that commitment-to-change partially mediated the relation between employee involvement and organizational change readiness. Furthermore, study results also affirmed that commitment-to-change does not mediate the relation between employee involvement and organizational change readiness. The empirical exploration therefore establishes that it is important to harness employee’s valuable suggestions regarding change for building organizational change readiness. Regarding employee involvement, it was found that sharing information and involving people in decision-making, leads to a creation of participative climate, which educes employee commitment during change and commitment-to-change further, fosters organizational change readiness.

Keywords: commitment-to-change, change management, employee voice, employee involvement, organizational change readiness

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Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

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In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: blockchain, decentralized system, fingerprint impression, identity management, iris scan

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Authors: Konstantinos Kottikas, Vlasis Stathakopoulos, Ioannis G. Theodorakis, Efthymia Kottika

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Theorists have argued that Market Orientation is comprised of two facets, namely the Market Driven and the Market Driving components. The present theoretical paper centers on the latter, which to date has been notably under-investigated. The term Market Driving (MD) pertains to influencing the structure of the market, or the behavior of market players in a direction that enhances the competitive edge of the firm. Presently, the main objectives of the paper are the specification of key antecedents and outcomes of Market Driving behavior. Market Driving firms behave proactively, by leading their customers and changing the rules of the game rather than by responding passively to them. Leading scholars were the first to conceptually conceive the notion, followed by some qualitative studies and a limited number of quantitative publications. However, recently, academicians noted that research on the topic remains limited, expressing a strong necessity for further insights. Concerning the key antecedents, top management’s Transformational Leadership (i.e. the form of leadership which influences organizational members by aligning their values, goals and aspirations to facilitate value-consistent behaviors) is one of the key drivers of MD behavior. Moreover, scholars have linked the MD concept with Entrepreneurship. Finally, the role that Employee’s Creativity plays in the development of MD behavior has been theoretically exemplified by a stream of literature. With respect to the key outcomes, it has been demonstrated that MD Behavior positively triggers firm Performance, while theorists argue that it empowers the Competitive Advantage of the firm. Likewise, researchers explicate that MD Behavior produces Radical Innovation. In order to test the robustness of the proposed theoretical framework, a combination of qualitative and quantitative methods is proposed. In particular, the conduction of in-depth interviews with distinguished executives and academicians, accompanied with a large scale quantitative survey will be employed, in order to triangulate the empirical findings. Given that it triggers overall firm’s success, the MD concept is of high importance to managers. Managers can become aware that passively reacting to market conditions is no longer sufficient. On the contrary, behaving proactively, leading the market, and shaping its status quo are new innovative approaches that lead to a paramount competitive posture and Innovation outcomes. This study also exemplifies that managers can foster MD Behavior through Transformational Leadership, Entrepreneurship and recruitment of Creative Employees. To date, the majority of the publications on Market Orientation is unilaterally directed towards the responsive (i.e. the Market Driven) component. The present paper further builds on scholars’ exhortations, and investigates the Market Driving facet, ultimately aspiring to conceptually integrate the somehow fragmented scientific findings, in a holistic framework.

Keywords: entrepreneurial orientation, market driving behavior, market orientation

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Authors: Ebenezer Joseph

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Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

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Authors: Giovanna Bimonte, Luigi Senatore, Francesco Saverio Tortoriello, Ilaria Veronesi

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The education process considers capabilities not only to be seen as a means to a certain end but rather as an effective purpose. Sen's capability approach challenges human capital theory, which sees education as an ordinary investment undertaken by individuals. A complex reality requires complex thinking capable of interpreting the dynamics of society's changes to be able to make decisions that can be rational for private, ethical and social contexts. Education is not something removed from the cultural and social context; it exists and is structured within it. In Italy, the "Mathematical High School Project" is a didactic research project is based on additional laboratory courses in extracurricular hours where mathematics intends to bring itself in a dialectical relationship with other disciplines as a cultural bridge between the two cultures, the humanistic and the scientific ones, with interdisciplinary educational modules on themes of strong impact in younger life. This interdisciplinary mathematics presents topics related to the most advanced technologies and contemporary socio-economic frameworks to demonstrate how mathematics is not only a key to reading but also a key to resolving complex problems. The recent developments in mathematics provide the potential for profound and highly beneficial changes in mathematics education at all levels, such as in socio-economic decisions. The research project is built to investigate whether repeated interactions can successfully promote cooperation among students as rational choice and if the skill, the context and the school background can influence the strategies choice and the rationality. A Laboratory on Game Theory as mathematical theory was conducted in the 4th year of the Mathematical High Schools and in an ordinary scientific high school of the Scientific degree program. Students played two simultaneous games of repeated Prisoner's Dilemma with an indefinite horizon, with two different competitors in each round; even though the competitors in each round will remain the same for the duration of the game. The results highlight that most of the students in the two classes used the two games with an immunization strategy against the risk of losing: in one of the games, they started by playing Cooperate, and in the other by the strategy of Compete. In the literature, theoretical models and experiments show that in the case of repeated interactions with the same adversary, the optimal cooperation strategy can be achieved by tit-for-tat mechanisms. In higher education, individual capacities cannot be examined independently, as conceptual framework presupposes a social construction of individuals interacting and competing, making individual and collective choices. The paper will outline all the results of the experimentation and the future development of the research.

Keywords: game theory, interdisciplinarity, mathematics education, mathematical high school

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Sufia Khowaja, Nishat Fatima

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Social networking sites are significant for visually impaired to overcome the unique challenges they face and access the resources they need to succeed in their education and beyond which might be difficult to obtain through traditional means. It provides them an opportunity to build relationships, stay connected with their support network as well as to develop social skills which give them emotional support to fell less isolated. In this connection the study is conducted with the aim to determine the use of social networking sites, purpose of using and activities performed by visually impaired at Delhi University, Delhi, Jawaharlal Nehru University, Delhi and Jamia Milia Islamia, Delhi. The study followed survey technique in which structured interview is followed to collect data from 137 visually impaired students and analysed using ‘SPSS ver23’. The findings of the study revealed that mostly used social networking sites are whatsapp by 89.23% students of DU, 95.12% of JNU, 87.09% of JMI, followed by e-mail by 78.46% of DU, 78.04% of JNU, 64.51%; youtube by 73.84% DU, 90.24% JNU, 80.64% JMI. Purpose for using these sites is for academics mentioned by 96.92% DU, 100% JNU, 93.54% JMI. Activities performed on sites are sending and receiving messaging 96.92% DU, 92.68% JNU, 93.55% JMI, communicating with friends and family as well as getting academic information. Findings of the study will be helpful for libraries to disseminate their services and resources as well as latest updates to their visually impaired users with the help of most used tools.

Keywords: social networking sites, visually impaired, Delhi University, Jawaharlal Nehru University, Jamia Milia Islamia

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Hassan Hussin Zwida

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The liquified LPG (Liquefied Petroleum Gas) drying system at the Complex is designed to remove water and mercaptans from the LPG stream. Upon saturation of the desiccant beds, a regeneration cycle becomes necessary. The original design routed the regeneration gas, produced during the LPG dryer heating cycle, to the sulfur recovery unit to the incineration. However, concerns regarding high temperatures and potential unit disruptions led to a modification where the gas is currently vented to the acid flare for the initial hour before being diverted to the LP network fuel gas system. While this addresses the temperature concerns, it generates significant smoke due to the presence of liquid hydrocarbons. This paper proposes an approach to recover the regeneration gas and redirect it back to the gas plant's (off-gas compressors) instead of sending it to the AC (Acid Flare), by utilizing the existing pipe 6” and connected to off gas compressor KO (Knock-Out ) Drums . This option is simple to operate, flexible, environment-friendly solution as long-term solution, lower in capital expenditure and increase the company's profitability. The feasibility of this proposal is supported by dynamic simulations. The simulations suggest the possibility of operating two out of the three off-gas compressors and LPG (Liquefied petroleum gas) as a liquid phase, is foreseen to be carried over and gathered at the bottom level of the KO (Knock-Out) Drum.

Keywords: thermal incinerator, off-gas compressors, environment, knock-out drums, acid flare

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Bandar Alahmadi, Lethia Jackson

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Machine Learning model is used today in many real-life applications. The safety and security of such model is important, so the results of the model are as accurate as possible. One challenge of machine learning model security is the adversarial examples attack. Adversarial examples are designed by the attacker to cause the machine learning model to misclassify the input. We propose a method to generate adversarial examples to attack image classifiers. We are modifying the successfully classified images, so a classifier misclassifies them after the modification. In our method, we do not update the whole image, but instead we detect the important region, modify it, place it back to the original image, and then run it through a classifier. The algorithm modifies the detected region using two methods. First, it will add abstract image matrix on back of the detected image matrix. Then, it will perform a rotation attack to rotate the detected region around its axes, and embed the trace of image in image background. Finally, the attacked region is placed in its original position, from where it was removed, and a smoothing filter is applied to smooth the background with foreground. We test our method in cascade classifier, and the algorithm is efficient, the classifier confident has dropped to almost zero. We also try it in CNN (Convolutional neural network) with higher setting and the algorithm was successfully worked.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

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The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

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Authors: Emelia Noronha, Milind Malshe

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The phatic function of communication is a vital element of any conversation. This research paper looks into this function with respect to personal blogs maintained by Indian bloggers. This paper is a study into the phenomenon of phatic communication maintained by bloggers through their blogs. Based on a linguistic analysis of the posts of twenty eight Indian bloggers, writing in English, studied over a period of three years, the study indicates that though the blogging phenomenon is not conversational in the same manner as face-to-face communication, it does make ample provision for feedback that is conversational in nature. Ordinary day to day offline conversations use conventionalized phatic utterances; those on the social media are in a perpetual mode of innovation and experimentation in order to sustain contact with its readers. These innovative methods and means are the focus of this study. Though the personal blogger aims to chronicle his/her personal life through the blog, the socializing function is crucial to these bloggers. In comparison to the western personal blogs which focus on the presentation of the ‘bounded individual self’, we find Indian personal bloggers engage in the presentation of their ‘social selves’. These bloggers yearn to reach out to the readers on the internet and the phatic function serves to initiate, sustain and renew social ties on the blogosphere thereby consolidating the social network of readers and bloggers.

Keywords: personal blogs, phatic, social-selves, blog readers

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Authors: O. A. Ajigini, E. N. Mwim

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Cybersecurity is the protection of computers, programs, networks, and data from attack, damage, unauthorised, unintended access, change, or destruction. Organisations collect, process and store their confidential and sensitive information on computers and transmit this data across networks to other computers. Moreover, the advent of internet technologies has led to various cyberattacks resulting in dangerous consequences for organisations. Therefore, with the increase in the volume and sophistication of cyberattacks, there is a need to develop models and make recommendations for the management of cybersecurity threats in organisations. This paper reports on various threats that cause malicious damage to organisations in cyberspace and provides measures on how these threats can be eliminated or reduced. The paper explores various aspects of protection measures against cybersecurity threats such as handling of sensitive data, network security, protection of information assets and cybersecurity awareness. The paper posits a model and recommendations on how to manage cybersecurity threats in organisations effectively. The model and the recommendations can then be utilised by organisations to manage the threats affecting their cyberspace. The paper provides valuable information to assist organisations in managing their cybersecurity threats and hence protect their computers, programs, networks and data in cyberspace. The paper aims to assist organisations to protect their information assets and data from cyberthreats as part of the contributions toward community engagement.

Keywords: confidential information, cyberattacks, cybersecurity, cyberspace, sensitive information

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an artificial neural network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study includes granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R²), Root mean square error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: national development, granite, profitability assessment, ANN models

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Authors: L. Edirisinghe, P. Mukherjee, H. Edirisinghe

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Virtual Container Yard (VCY) is a modern concept that helps to reduce the empty container repositioning cost of carriers. The concept of VCY is based on container interchange between shipping lines. Although this mechanism has been theoretically accepted by the shipping community as a feasible solution, it has not yet achieved the necessary momentum among container shipping lines (CSL). This paper investigates whether there is any legal influence on this industry myopia about the VCY. It is believed that this is the first publication that focuses on the legal aspects of container exchange between carriers. Not much literature on this subject is available. This study establishes with statistical evidence that there is a phobia prevailing in the shipping industry that exchanging containers with other carriers may lead to various legal implications. The complexity of exchange is two faceted. CSLs assume that offering a container to another carrier (obviously, a competitor in terms of commercial context) or using a container offered by another carrier may lead to undue legal implications. This research reveals that this fear is reflected through four types of perceived components, namely: shipping associate; warehouse associate; network associate; and trading associate. These components carry eighteen subcomponents that comprehensively cover the entire process of a container shipment. The statistical explanation has been supported through regression analysis; INCO terms were used to illustrate the shipping process.

Keywords: virtual container yard, legal, maritime law, inventory

Procedia PDF Downloads 159

Authors: Prashansa Singh, Manjot Kaur, Rohit Bajaj

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The proliferation of wireless sensor networks and Internet of Things (IoT) devices in the quickly changing digital landscape has highlighted the urgent need for strong security solutions that can handle these systems’ limited resources. A key solution to this problem is the emergence of ultralightweight security protocols, which provide strong security features while respecting the strict computational, energy, and memory constraints imposed on these kinds of devices. This in-depth analysis explores the field of ultralightweight security protocols, offering a thorough examination of their evolution, salient features, and the particular security issues they resolve. We carefully examine and contrast different protocols, pointing out their advantages and disadvantages as well as the compromises between resource limitations and security resilience. We also study these protocols’ application domains, including the Internet of Things, RFID systems, and wireless sensor networks, to name a few. In addition, the review highlights recent developments and advancements in the field, pointing out new trends and possible avenues for future research. This paper aims to be a useful resource for researchers, practitioners, and developers, guiding the design and implementation of safe, effective, and scalable systems in the Internet of Things era by providing a comprehensive overview of ultralightweight security protocols.

Keywords: wireless sensor network, machine-to-machine, MQTT broker, server, ultralightweight, TCP/IP

Procedia PDF Downloads 68