Search results for: message passing neural network

Authors: Barbara Behre, Verolien Cauberghe, Dieneke Van de Sompel

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Sustainable consumption is on the rise, yet it has still not entered the mainstream in several industries, such as the fashion industry. In online fashion contexts, sustainability cues have been used to signal the sustainable benefits of certain garments to promote sustainable consumption. These sustainable cues may focus on the ecological or social dimension of sustainability. Since sustainability, in general, relates to distant, abstract benefits, the current study aims to examine if and how psychological distance may mediate the effects of exposure to different sustainability cues on consumption outcomes. Following the framework of Construal Level Theory of Psychological Distance, reduced psychological distance renders the construal level more concrete, which may influence attitudes and subsequent behavior in situations like fashion shopping. Most studies investigated sustainability as a composite, failing to differentiate between ecological and societal aspects of sustainability. The few studies examining sustainability more in detail uncovered that environmental sustainability is rather perceived in abstract cognitive construal, whereas social sustainability is linked to concrete construal. However, the construal level affiliation of the sustainability dimensions likely is not universally applicable to different domains and stages of consumption, which further suggest a need to clarify the relationships between environmental and social sustainability dimensions and the construal level of psychological distance within fashion brand consumption. While psychological distance and construal level have been examined in the context of sustainability, these studies yielded mixed results. The inconsistent findings of past studies might be due to the context-dependence of psychological distance as inducing construal differently in diverse situations. Especially in a hedonic consumption context like online fashion shopping, the role of visual processing of information could determine behavioural outcomes as linked to situational construal. Given the influence of the mode of processing on psychological distance and construal level, the current study examines the moderating role of verbal versus non-verbal presentation of the sustainability cues. In a 3 (environmental sustainability vs. social sustainability vs. control) x 2 (non-verbal message vs. verbal message) between subjects experiment, the present study thus examines how consumers evaluate sustainable brands in online shopping contexts in terms of psychological distance and construal level, as well as the impact on brand attitudes and buying intentions. The results among 246 participants verify the differential impact of the sustainability dimensions on fashion brand purchase intent as mediated by construal level and perceived psychological distance. The ecological sustainability cue is perceived as more concrete, which might be explained by consumer bias induced by the predominance of pro-environmental sustainability messages. The verbal versus non-verbal presentation of the sustainability cue neither had a significant influence on distance perceptions and construal level nor on buying intentions. This study offers valuable contributions to the sustainable consumption literature, as well as a theoretical basis for construal-level framing as applied in sustainable fashion branding.

Keywords: construal level theory, environmental vs social sustainability, online fashion shopping, sustainable fashion

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Authors: Preetham Shankapal, Jill King, Kori Murray, Corby Martin, Paula Giselman, Jason Hicks, Owen Carmicheal

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Activation of reward and satiety networks in the brain while processing palatable food cues, as well as functional connectivity during rest has been studied using functional Magnetic Resonance Imaging of the brain in various obesity phenotypes. However, functional connectivity within the reward and satiety network during food cue processing is understudied. 14 obese individuals underwent two fMRI scans during viewing of Macronutrient Picture System images. Each scan included two blocks of images of High Sugar/High Fat (HSHF), High Carbohydrate/High Fat (HCHF), Low Sugar/Low Fat (LSLF) and also non-food images. Seed voxels within seven food reward relevant ROIs: Insula, putamen and cingulate, precentral, parahippocampal, medial frontal and superior temporal gyri were isolated based on a prior meta-analysis. Beta series correlation for task-related functional connectivity between these seed voxels and the rest of the brain was computed. Voxel-level differences in functional connectivity were calculated between: first and the second scan; individuals who saw novel (N=7) vs. Repeated (N=7) images in the second scan; and between the HC/HF, HSHF blocks vs LSLF and non-food blocks. Computations and analysis showed that during food image viewing, reward network ROIs showed significant functional connectivity with each other and with other regions responsible for attentional and motor control, including inferior parietal lobe and precentral gyrus. These functional connectivity values were heightened among individuals who viewed novel HS/HF images in the second scan. In the second scan session, functional connectivity was reduced within the reward network but increased within attention, memory and recognition regions, suggesting habituation to reward properties and increased recollection of previously viewed images. In conclusion it can be inferred that Functional Connectivity within reward network and between reward and other brain regions, varies by important experimental conditions during food photography viewing, including habituation to shown foods.

Keywords: fMRI, functional connectivity, task-based, beta series correlation

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Authors: Chakraborty Sudipta, A. R. Kambekar, Sarma Arnab

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Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

Keywords: climate change, Coastal Vulnerability Index, global warming, sea level rise

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Authors: Ali Shareef, Aliha Shareef, Yifeng Zhu

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Energy minimization is of great importance in wireless sensor networks in extending the battery lifetime. One of the key activities of nodes in a WSN is communication and the routing of their data to a centralized base-station or sink. Routing using the shortest path to the sink is not the best solution since it will cause nodes along this path to fail prematurely. We propose a cross-layer energy efficient routing protocol Optrix that utilizes a convex formulation to maximize the lifetime of the network as a whole. We further propose, Optrix-BW, a novel convex formulation with bandwidth constraint that allows the channel conditions to be accounted for in routing. By considering this key channel parameter we demonstrate that Optrix-BW is capable of congestion control. Optrix is implemented in TinyOS, and we demonstrate that a relatively large topology of 40 nodes can converge to within 91% of the optimal routing solution. We describe the pitfalls and issues related with utilizing a continuous form technique such as convex optimization with discrete packet based communication systems as found in WSNs. We propose a routing controller mechanism that allows for this transformation. We compare Optrix against the Collection Tree Protocol (CTP) and we found that Optrix performs better in terms of convergence to an optimal routing solution, for load balancing and network lifetime maximization than CTP.

Keywords: wireless sensor network, Energy Efficient Routing

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Authors: Chaitanya Kanakamedala, Hansa Pradhan, Carter Gilbert

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Social media platforms, such as Twitter, are excellent datasets for understanding human interactions and sentiments. This report explores social dynamics among US Congressional members through a network analysis applied to a dataset of tweets spanning 2008 to 2017 from the ’US Congressional Tweets Dataset’. In this report, we preform network analysis where connections between users (edges) are established based on a similarity threshold: two tweets are connected if the tweets they post are similar. By utilizing the Natural Language Toolkit (NLTK) and NetworkX, we quantified tweet similarity and constructed a graph comprising various interconnected components. Each component represents a cluster of users with closely aligned content. We then preform sentiment analysis on each cluster to explore the prevalent emotions and opinions within these groups. Our findings reveal that despite the initial expectation of distinct ideological divisions typically aligning with party lines, the analysis exposed a high degree of topical convergence across tweets from different political affiliations. The analysis preformed in this report not only highlights the potential of social media as a tool for political communication but also suggests a complex layer of interaction that transcends traditional partisan boundaries, reflecting a complicated landscape of politics in the digital age.

Keywords: natural language processing, sentiment analysis, centrality analysis, topic modeling

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Authors: Wabinyai Fidel Raja, Gideon Lubisa

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Air pollution is becoming a growing concern in Africa due to rapid industrialization and urbanization, leading to implications for public health and the environment. Establishing a comprehensive air quality monitoring network is crucial to combat this issue. However, conventional methods of monitoring are insufficient in African cities due to the high cost of setup and maintenance. To address this, low-cost sensors (LCS) can be deployed in various urban areas through the use of participatory air quality network siting (PAQNS). PAQNS involves stakeholders from the community, local government, and private sector working together to determine the most appropriate locations for air quality monitoring stations. This approach improves the accuracy and representativeness of air quality monitoring data, engages and empowers community members, and reflects the actual exposure of the population. Implementing PAQNS in African cities can build trust, promote accountability, and increase transparency in the air quality management process. However, challenges to implementing this approach must be addressed. Nonetheless, improving air quality is essential for protecting public health and promoting a sustainable environment. Implementing participatory and data-informed air quality monitoring can take a significant step toward achieving these important goals in African cities and beyond.

Keywords: low-cost sensors, participatory air quality network siting, air pollution, air quality management

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Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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Authors: Zhaocheng Shang

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In order to study the topic of cities crossing rivers, a Four-Dimensional Analysis Method consisting of timeline, X-axis, Y-axis, and Z-axis is proposed. Policies, plans, and their implications are summarized and researched along with the timeline. The X-axis is the direction which is parallel to the river. The research area was chosen because of its important connection function. It is proposed that more surface water network should be built because of the ecological orientation of the research area. And the analysis of groundwater makes it for sure that the proposal is feasible. After the blue water network is settled, the green landscape network which is surrounded by it could be planned. The direction which is transversal to the river (Y-axis) should run through the transportation axis so that the urban texture could stretch in an ecological way. Therefore, it is suggested that the work of the planning bureau and river bureau should be coordinated. The Z-axis research is on the section view of the river, especially on the Yellow River’s special feature of being a perched river. Based on water control safety demands, river parks could be constructed on the embankment buffer zone, whereas many kinds of ornamental trees could be used to build the buffer zone. City Crossing River is a typical case where we make use of landscaping to build a symbiotic relationship between the urban landscape architecture and the environment. The local environment should be respected in the process of city expansion. The planning order of "Benefit- Flood Control Safety" should be replaced by "Flood Control Safety - Landscape Architecture- People - Benefit".

Keywords: blue-green landscape network, city crossing river, four-dimensional analysis method, planning order

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Authors: Reza Sirjani, Nobosse Tafem Bolan

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Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

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Authors: Albert W. K. Tan

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This research consolidates a comprehensive array of publications from peer-reviewed journals, case studies, and seminar reports focused on reverse logistics and network design. By synthesizing this secondary knowledge, our objective is to identify and articulate key decision factors crucial to reverse logistics network design for e-commerce. Through this exploration, we aim to present a refined mathematical model that offers valuable insights for companies seeking to optimize their reverse logistics operations. The primary goal of this research endeavor is to develop a comprehensive framework tailored to advising organizations and companies on crafting effective networks for their reverse logistics operations, thereby facilitating the achievement of their organizational goals. This involves a thorough examination of various network configurations, weighing their advantages and disadvantages to ensure alignment with specific business objectives. The key objectives of this research include: (i) Identifying pivotal factors pertinent to network design decisions within the realm of reverse logistics across diverse supply chains. (ii) Formulating a structured framework designed to offer informed recommendations for sound network design decisions applicable to relevant industries and scenarios. (iii) Propose a mathematical model to optimize its reverse logistics network. A conceptual framework for designing a reverse logistics network has been developed through a combination of insights from the literature review and information gathered from company websites. This framework encompasses four key stages in the selection of reverse logistics operations modes: (1) Collection, (2) Sorting and testing, (3) Processing, and (4) Storage. Key factors to consider in reverse logistics network design: I) Centralized vs. decentralized processing: Centralized processing, a long-standing practice in reverse logistics, has recently gained greater attention from manufacturing companies. In this system, all products within the reverse logistics pipeline are brought to a central facility for sorting, processing, and subsequent shipment to their next destinations. Centralization offers the advantage of efficiently managing the reverse logistics flow, potentially leading to increased revenues from returned items. Moreover, it aids in determining the most appropriate reverse channel for handling returns. On the contrary, a decentralized system is more suitable when products are returned directly from consumers to retailers. In this scenario, individual sales outlets serve as gatekeepers for processing returns. Considerations encompass the product lifecycle, product value and cost, return volume, and the geographic distribution of returns. II) In-house vs. third-party logistics providers: The decision between insourcing and outsourcing in reverse logistics network design is pivotal. In insourcing, a company handles the entire reverse logistics process, including material reuse. In contrast, outsourcing involves third-party providers taking on various aspects of reverse logistics. Companies may choose outsourcing due to resource constraints or lack of expertise, with the extent of outsourcing varying based on factors such as personnel skills and cost considerations. Based on the conceptual framework, the authors have constructed a mathematical model that optimizes reverse logistics network design decisions. The model will consider key factors identified in the framework, such as transportation costs, facility capacities, and lead times. The authors have employed mixed LP to find the optimal solutions that minimize costs while meeting organizational objectives.

Keywords: reverse logistics, supply chain management, optimization, e-commerce

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

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Authors: Dhaksha Vivekanandan

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DeFi is a network that avoids reliance on financial intermediaries through its peer-to-peer financial network. DeFi operates outside of government control; hence it is important for us to understand its impacts. This study employs a literature review to understand DeFi and its emergence, as well as its implications on transparency, social impact, and regulation. Further, 3 case studies are analysed within the context of these categories. DeFi’s provision of increased transparency poses environmental and storage costs and can lead to user privacy being endangered. DeFi allows for the provision of entrepreneurial incentives and protection against monetary censorship and capital control. Despite DeFi's transparency issues and volatility costs, it has huge potential to reduce poverty; however, regulation surrounding DeFi still requires further tightening by governments.

Keywords: DeFi, transparency, regulation, social impact

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Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

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Authors: Ramya Rathan, Miral N. F. Salama

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The variations in the arteries have been drawing attention of anatomists for a long time because of their clinical significance. The brachial artery is the principal artery of the arm which is the continuation of the axillary artery from the lower border of the Teres Major. It terminates into the radial and ulnar arteries below the elbow joint at the neck radius. The present study aims at exploring the clinical significance of the high termination of the brachial artery. During the routine cadaveric dissection of the arm, for the undergraduate students of medicine at our university, we observed a high bifurcation of the radial and the ulnar artery at the midshaft of the humerus. The median nerve was seen passing between these two junctions. Further, the course and the relations of this artery were studied. The accurate knowledge regarding these kinds of variation in the blood vessels is mandatory for planning of designing. General physicians, surgeons and radiologists should keep in mind the variations in the branching pattern of the arteries in their daily medical, diagnostic and therapeutic procedures to avoid complications in diagnostic and surgical procedures.

Keywords: brachial artery, high termination, radial artery, ulnar artery

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Authors: Andrew Kurochkin, Kostiantyn Bokhan

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In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: Saikiran Subbagari, Avinash Malladhi

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Anti Money Laundering (AML) regulations are designed to prevent money laundering and terrorist financing activities worldwide. Financial institutions around the world are legally obligated to identify, assess and mitigate the risks associated with money laundering and report any suspicious transactions to governing authorities. With increasing volumes of data to analyze, financial institutions seek to automate their AML processes. In the rise of financial crimes, optical character recognition (OCR), in combination with machine learning (ML) algorithms, serves as a crucial tool for automating AML processes by extracting the data from documents and identifying suspicious transactions. In this paper, we examine the utilization of OCR for AML and delve into various OCR techniques employed in AML processes. These techniques encompass template-based, feature-based, neural network-based, natural language processing (NLP), hidden markov models (HMMs), conditional random fields (CRFs), binarizations, pattern matching and stroke width transform (SWT). We evaluate each technique, discussing their strengths and constraints. Also, we emphasize on how OCR can improve the accuracy of customer identity verification by comparing the extracted text with the office of foreign assets control (OFAC) watchlist. We will also discuss how OCR helps to overcome language barriers in AML compliance. We also address the implementation challenges that OCR-based AML systems may face and offer recommendations for financial institutions based on the data from previous research studies, which illustrate the effectiveness of OCR-based AML.

Keywords: anti-money laundering, compliance, financial crimes, fraud detection, machine learning, optical character recognition

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Authors: Taras Agryzkov, Almudena Nolasco-Cirugeda, Jose L. Oliver, Leticia Serrano-Estrada, Leandro Tortosa, Jose F. Vicent

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This paper aims to represent the commercial activity of a city taking as source data the social network Foursquare. The city of Murcia is selected as case study, and the location-based social network Foursquare is the main source of information. After carrying out a reorganisation of the user-generated data extracted from Foursquare, it is possible to graphically display on a map the various city spaces and venues –especially those related to commercial, food and entertainment sector businesses. The obtained visualisation provides information about activity patterns in the city of Murcia according to the people`s interests and preferences and, moreover, interesting facts about certain characteristics of the town itself.

Keywords: social networks, spatial analysis, data visualization, geocomputation, Foursquare

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Authors: Dennis Caasi

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This study analyzed four knowledge-building elements of channel expansion theory namely: communication media, communication content, communication partner, and communication influence vis-à- vis media richness dimensions among parents working overseas and their left-behind children in the Philippines. Results reveal that both parents and children consumed four out of six mediated communications tested in this research, spent one to four days a week connecting, between 30 minutes to 3 hours per engagement, and media consumption is dependent on the message content and media literacy of parents. Family, academic, household, and health were the common communication topics and parents dictate which channel to use. All six medium tested received high ratings based on the media richness constructs.

Keywords: channel expansion theory, computer-mediated communication, media richness theory, overseas Filipino worker

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Authors: Sabitha Rahim

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In the context of teaching vocabulary of English as Foreign Language (EFL), the confluence of memory and retention is one of the most significant factors in students' language acquisition. The progress of students engaged in foreign language acquisition is often stymied by vocabulary attrition, which leads to learners' lack of confidence and motivation. However, among other factors, little research has investigated the importance of neuroplasticity in Foreign Language acquisition and how underused neural pathways lead to the loss of plasticity, thereby affecting the learners’ vocabulary retention and motivation. This research explored the effect of enhancing vocabulary acquisition of EFL students in the Foundation Year at King Abdulaziz University through various methods and neuroplasticity exercises that reinforced their attention, motivation, and engagement. It analyzed the results to determine if stimulating the brain of EFL learners by various physical and mental activities led to the improvement in short and long term memory in vocabulary retention. The main data collection methods were student surveys, assessment records of teachers, student achievement test results, and students' follow-up interviews. A key implication of this research is for the institutions to consider having multiple varieties of student activities promoting brain plasticity within the classrooms as an effective tool for foreign language acquisition. Building awareness among the faculty and adapting the curriculum to include activities that promote brain plasticity ensures an enhanced learning environment and effective language acquisition in EFL classrooms.

Keywords: language acquisition, neural paths, neuroplasticity, vocabulary attrition

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Authors: Mohammed Bnebaghdad, Feriel Betouche, Malika Semmani

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Image processing become more sophisticated over time due to technological advances, especially artificial intelligence (AI) technology. Currently, AI image processing is used in many areas, including surveillance, industry, science, and medicine. AI in medical image processing can help doctors diagnose diseases faster, with minimal mistakes, and with less effort. Among these diseases is malaria, which remains a major public health challenge in many parts of the world. It affects millions of people every year, particularly in tropical and subtropical regions. Early detection of malaria is essential to prevent serious complications and reduce the burden of the disease. In this paper, we propose and implement a scheme based on AI image processing to enhance malaria disease diagnosis through automated analysis of blood smear images. The scheme is based on the convolutional neural network (CNN) method. So, we have developed a model that classifies infected and uninfected single red cells using images available on Kaggle, as well as real blood smear images obtained from the Central Laboratory of Medical Biology EHS Laadi Flici (formerly El Kettar) in Algeria. The real images were segmented into individual cells using the watershed algorithm in order to match the images from the Kaagle dataset. The model was trained and tested, achieving an accuracy of 99% and 97% accuracy for new real images. This validates that the model performs well with new real images, although with slightly lower accuracy. Additionally, the model has been embedded in a Raspberry Pi4, and a graphical user interface (GUI) was developed to visualize the malaria diagnostic results and facilitate user interaction.

Keywords: medical image processing, malaria parasite, classification, CNN, artificial intelligence

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Authors: Sukran Karatas

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Authentic energy network interrelations between the Creator and the creations as well as from creations to creations are the most important points for the worlds of physics and metaphysic to unite together and work in harmony, both within human beings, on the other hand, have the ability to choose their own life style voluntarily. However, it includes the automated involuntary spirit, soul and body working systems together with the voluntary actions, which involve personal, cultural and universal, rational or irrational variable values. Therefore, it is necessary for human beings to know the methods of existing authentic energy network connections to be able to communicate correlate and accommodate the physical and metaphysical entities as a proper functioning unity; this is essential for complete human psychological, biological and social well-being. Authentic knowledge is necessary for human beings to verify the position of self within self and with others to regulate conscious and voluntary actions accordingly in order to prevent oppressions and frictions within self and between self and others. Unfortunately, the absence of genuine individual and universal basic knowledge about how to establish an authentic energy network connection within self, with the deity and the environment is the most problematic issue even in the twenty-first century. The second most problematic issue is how to maintain freedom, equality and justice among human beings during these strictly interwoven network connections, which naturally involve physical, metaphysical and behavioral actions of the self and the others. The third and probably the most complicated problem is the scientific identification and the authentication of the deity. This not only provides the whole power and control over the choosers to set their life orders but also to establish perfect physical and metaphysical links as fully coordinated functional energy network. This thus indicates that choosing an authentic deity is the key-point that influences automated, emotional, and behavioral actions altogether, which shapes human perception, personal actions, and life orders. Therefore, we will be considering the existing ‘four types of energy wave end boundary behaviors’, comprising, free end, fixed end boundary behaviors, as well as boundary behaviors from denser medium to less dense medium and from less dense medium to denser medium. Consequently, this article aims to demonstrate that the authentication and the choice of deity has an important effect on individual psychological, biological and social health. It is hoped that it will encourage new researches in the field of authentic energy network connections to establish the best position and the most correct interrelation connections with self and others without violating the authorized orders and the borders of one another to live happier and healthier lives together. In addition, the book ‘Deity and Freedom, Equality, Justice in History, Philosophy, Science’ has more detailed information for those interested in this subject.

Keywords: deity, energy network, power, freedom, equality, justice, happiness, sadness, hope, fear, psychology, biology, sociology

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Authors: Donato Maniello, Alessandra Cirafici, Valeria Amoretti

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This paper aims to present a new method that consists in the use of video mapping techniques – that is a particular form of augmented reality, which could produce new tools - different from the ones that are actually in use - for an interactive Museum experience. With the words 'augmented reality', we mean the addition of more information than what the visitor would normally perceive; this information is mediated by the use of computer and projector. The proposed application involves the creation of a documentary that depicts and explains the history of the artifact and illustrates its features; this must be projected on the surface of the faithful copy of the freeze (obtained in full-scale with a 3D printer). This mode of operation uses different techniques that allow passing from the creation of the model to the creation of contents through an accurate historical and artistic analysis, and finally to the warping phase, that will permit to overlap real and virtual models. The ultimate step, that is still being studied, includes the creation of interactive contents that would be activated by visitors through appropriate motion sensors.

Keywords: augmented reality, multimedia, parthenon frieze, video mapping

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Authors: Carlo Gozzelino

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Since the early 2000s, the phenomenon of the two-sided markets has been of growing interest in academic literature as such kind of markets differs by having cross-side network effects and same-side network effects characterizing the transactions, which make the analysis different when compared to traditional seller-buyer concept. Due to such externalities, pricing strategies can be based on subsidizing the participation of one side (i.e. considered key for the platform to attract the other side) while recovering the loss on the other side. In recent years, several players of the Italian financial intermediation industry moved from an integrated landscape (i.e. selling their own products) to an open one (i.e. intermediating third party products). According to academic literature such behavior can be interpreted as a merchant move towards a platform, operating in a two-sided market environment. While several application of two-sided market framework are available in academic literature, purpose of this paper is to use a two-sided market concept to suggest a new framework applied to financial intermediation. To this extent, a model is developed to show how competitors behave when vertically integrated and how the peculiarities of a two-sided market act as an incentive to disintegrate. Additionally, we show that when all players act as a platform, the dynamics of a two-sided markets can allow at least a Nash equilibrium to exist, in which platform of different sizes enjoy positive profit. Finally, empirical evidences from Italian market are given to sustain – and to challenge – this interpretation.

Keywords: financial intermediation, network externalities, two-sided markets, vertical differentiation

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Authors: Elena Petersen, Inna Kornienko, Svetlana Guryeva, Sergey Simakov

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In vitro organoid cultivation requires the simultaneous provision of necessary vascularization and nutrients perfusion of cells during organoid development. However, many aspects of this problem are still unsolved. The functionality of vascular network intergrowth is limited during early stages of organoid development since a function of the vascular network initiated on final stages of in vitro organoid cultivation. Therefore, a microchannel network should be created in early stages of organoid cultivation in hydrogel matrix aimed to conduct and maintain minimally required the level of nutrients perfusion for all cells in the expanding organoid. The network configuration should be designed properly in order to exclude hypoxic and necrotic zones in expanding organoid at all stages of its cultivation. In vitro vascularization is currently the main issue within the field of tissue engineering. As perfusion and oxygen transport have direct effects on cell viability and differentiation, researchers are currently limited only to tissues of few millimeters in thickness. These limitations are imposed by mass transfer and are defined by the balance between the metabolic demand of the cellular components in the system and the size of the scaffold. Current approaches include growth factor delivery, channeled scaffolds, perfusion bioreactors, microfluidics, cell co-cultures, cell functionalization, modular assembly, and in vivo systems. These approaches may improve cell viability or generate capillary-like structures within a tissue construct. Thus, there is a fundamental disconnect between defining the metabolic needs of tissue through quantitative measurements of oxygen and nutrient diffusion and the potential ease of integration into host vasculature for future in vivo implantation. A model is proposed for growth prognosis of the organoid perfusion based on joint simulations of general nutrient diffusion, nutrient diffusion to the hydrogel matrix through the contact surfaces and microchannels walls, nutrient consumption by the cells of expanding organoid, including biomatrix contraction during tissue development, which is associated with changed consumption rate of growing organoid cells. The model allows computing effective microchannel network design giving minimally required the level of nutrients concentration in all parts of growing organoid. It can be used for preliminary planning of microchannel network design and simulations of nutrients supply rate depending on the stage of organoid development.

Keywords: 3D model, consumption model, diffusion, spheroid, tissue organoid

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Authors: Kenji Tanaka, Kazumi Sugita, Yuto Mizushima

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This paper introduces a noteworthy form of English communication training for the officers and operators of the Osaka-Bay Marine Traffic Information Service (Osaka MARTIS) of the Japan Coast Guard working in the congested area at the Akashi Strait in Hyogo Prefecture, Japan. The authors of this paper, Marine Technical College’s (MTC) English language instructors, have been holding about forty lectures and exercises in basic and normal Maritime English (ME) for several groups of MARTIS personnel at Osaka MARTIS annually since they started the training in 2005. Trainees are expected to be qualified Maritime Third-Class Radio Operators who are responsible for providing safety information to a daily average of seven to eight hundred vessels that pass through the Akashi Strait, one of Japan’s narrowest channels. As of 2022, the instructors are conducting 55 remote lessons at MARTIS. One lesson is 90 minutes long. All 26 trainees are given oral and written assessments. The trainees need to pass the examination to become qualified operators every year, requiring them to train and maintain their linguistic levels even during the pandemic of Corona Virus Disease-19 (COVID-19). The vessel traffic information provided by Osaka MARTIS in Maritime English language is essential to the work involving the use of very high frequency (VHF) communication between MARTIS and vessels in the area. ME is the common language mainly used on board merchant, fishing, and recreational vessels, normally at sea. ME was edited and recommended by the International Maritime Organization in the 1970s, was revised in 2002, and has undergone continual revision. The vessel’s circumstances are much more serious at the strait than those at the open sea, so these vessels need ME to receive guidance from the center when passing through the narrow strait. The imminent and challenging situations at the strait necessitate that textbooks’ contents include the basics of the phrase book for seafarers as well as specific and additional navigational information, pronunciation exercises, notes on keywords and phrases, explanations about collocations, sample sentences, and explanations about the differences between synonyms especially those focusing on terminologies necessary for passing through the strait. Additionally, short Japanese-English translation quizzes about these topics, as well as prescribed readings about the maritime sector, are include in the textbook. All of these exercises have been trained in the remote education system since the outbreak of COVID-19. According to the guidelines of ME edited in 2009, the lowest level necessary for seafarers is B1 (lower individual users) of The Common European Framework of Reference for Languages: Learning, Teaching, Assessment (CEFR). Therefore, this vocational ME language training at Osaka MARTIS aims for its trainees to communicate at levels higher than B1. A noteworthy proof of improvement from this training is that most of the trainees have become qualified marine radio communication officers.

Keywords: akashi strait, B1 of CEFR, maritime english communication training, osaka martis

Procedia PDF Downloads 128

Authors: Fatin Khalida Abdul Khadir, Husna Takaijudin

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Bioretention system is one of the alternatives to approach the conventional stormwater management, low impact development (LID) strategy for best management practices (BMPs). Incorporating both filtration and infiltration, initial research on bioretention systems has shown that this practice extensively decreases runoff volumes and peak flows. The LID-BMP treatment train is one of the latest LID-BMPs for stormwater treatments in urbanized watersheds. The treatment train is developed to overcome the drawbacks that arise from conventional LID-BMPs and aims to enhance the performance of the existing practices. In addition, it is also used to improve treatments in both water quality and water quantity controls as well as maintaining the natural hydrology of an area despite the current massive developments. The objective of this paper is to review the effectiveness of the conventional LID-BMPS on hydrologic and hydraulic performances through column studies in different configurations. The previous studies on the applications of LID-BMP treatment train that were developed to overcome the drawbacks of conventional LID-BMPs are reviewed and use as the guidelines for implementing this system in Universiti Teknologi Petronas (UTP) and elsewhere. The reviews on the analysis conducted for hydrologic and hydraulic performances using the artificial neural network (ANN) model are done in order to be utilized in this study. In this study, the role of the LID-BMP treatment train is tested by arranging bioretention cells in series in order to be implemented for controlling floods that occurred currently and in the future when the construction of the new buildings in UTP completed. A summary of the research findings on the performances of the system is provided which includes the proposed modifications on the designs.

Keywords: bioretention system, LID-BMP treatment train, hydrological and hydraulic performance, ANN analysis

Procedia PDF Downloads 121

Authors: Boon Lee

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Research publication is an essential output of universities because it not only promotes university recognition, it also receives government funding. The history of university research culture has been one of ‘publish or perish’ and universities have consistently encouraged their academics and researchers to produce research articles in reputable journals in order to maintain a level of competitiveness. In turn, the United Kingdom (UK) government funding is determined by the number and quality of research publications. This paper aims to investigate on whether more government funding leads to more quality papers. To that end, the paper employs a Network DEA model to evaluate the UK higher education performance over a period. Sources of efficiency are also determined via second stage regression analysis.

Keywords: efficiency, higher education, network data envelopment analysis, universities

Procedia PDF Downloads 119

Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

Procedia PDF Downloads 134

Authors: S. Dhivya, M. Abirami, M. Farjana Parveen, M. Keerthiga

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The development of high-speed railway makes people’s lives more and more convenient; meanwhile, handover is the major problem on high-speed railway communication services. In order to overcome that drawback the architecture of Long-Term Evolution (LTE) femtocell networks is used to improve network performance, and the deployment of a femtocell is a key for bandwidth limitation and coverage issues in conventional mobile network system. To increase the handover performance this paper proposed a multiple input multiple output (MIMO) assisted handoff (MAHO) algorithm. It is a technique used in mobile telecom to transfer a mobile phone to a new radio channel with stronger signal strength and improved channel quality.

Keywords: flawless handover, high-speed train, home evolved Node B, LTE, mobile femtocell, RSS

Procedia PDF Downloads 475