Search results for: irreducible sign patterns

Authors: Joanna Dauner, Jan Friedrich, Linda Elsner, Kora Kimpel

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Active materials such as Electroactive Polymers (EAPs) are promising for the development of novel shape-changing interfaces. This paper explores the potential of EAPs in a multilayer unimorph structure from a design perspective to investigate the visual qualities of the material for dynamic data visualization and data physicalization. We discuss various concepts of how the material can be used for this purpose. Multilayer unimorph EAPs are of particular interest to designers because they can be easily prototyped using everyday materials and tools. By changing the structure and geometry of the EAPs, their movement and behavior can be modified. We present the results of our preliminary user testing, where we evaluated different movement patterns. As a result, we introduce a prototype display built with EAPs for dynamic data physicalization. Finally, we discuss the potentials and drawbacks and identify further open research questions for the design discipline.

Keywords: electroactive polymer, shape-changing interfaces, smart material interfaces, data physicalization

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Aula Khatteb Abu-Liel

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The study investigated the effects of diglossia and orthography on reading in Arabic, manipulating reading in Spoken Arabic (SA), using Arabizi, in which it is written using Latin letters on computers/phones, and the two forms of the conventional written form Modern Standard Arabic (MSA): vowelled (shallow) and unvowelled (deep). 77 skilled readers in 8th grade performed oral reading of single words and narrative and expository texts, and silent reading comprehension of both genres of text. Oral reading and comprehension revealed different patterns. Single words and texts were read faster and more accurately in unvoweled MSA, slowest and least accurately in vowelled MSA, and in-between in Arabizi. Comprehension was highest for vowelled MSA. Narrative texts were better than expository texts in Arabizi with the opposite pattern in MSA. The results suggest that frequency of the type of texts and the way in which phonology is encoded affect skilled reading.

Keywords: Arabic, Arabize, computer mediated communication, diglossia, modern standard Arabic

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Authors: J. Bartus, J. Odrobinak

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The paper presents a nonlinear analysis 3D model of composite steel and concrete beams with web openings using the Finite Element Method (FEM). The core of the study is the introduction of basic modeling techniques comprehending the description of material behavior, appropriate elements selection, and recommendations for overcoming problems with convergence. Results from various finite element models are compared in the study. The main objective is to observe the concrete failure mechanism and its influence on the structural performance of numerical models of the beams at particular load stages. The bearing capacity of beams, corresponding deformations, stresses, strains, and fracture patterns were determined. The results show how load-bearing elements consisting of concrete parts can be analyzed using FEM software with various options to create the most suitable numerical model. The paper demonstrates the versatility of Ansys software usage for structural simulations.

Keywords: Ansys, concrete, modeling, steel

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Authors: Rajendra Chetty

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This paper analyses the experiences of teachers of literacy in underprivileged schools in the Western Cape, South Africa. The purpose is to provide teachers in poorly resourced schools within economically deprived areas an opportunity to voice their experiences of teaching literacy. The paper is based on an empirical study using interviews and classroom observation. A descriptive account of the observation data was followed by an interpretive analysis. The content analysis of the interview data led to the development of themes and patterns for the discussion. The study reveals key factors for literacy underachievement that include lack of critical and emancipatory pedagogies, resources, parental support, lack of teacher knowledge, absence of cognitive activities, and the social complexity of poverty. The paper recommends that a new model of literacy that is underpinned by critical pedagogy challenge inequality and provides strategic and sustained teacher support in disadvantaged schools is crucial in a society emerging from oppression and racism.

Keywords: critical pedagogy, disadvantaged schools, literacy, poverty

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Authors: Jocelyne Kenne Kenne

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Previous works in the field of sociolinguistics have explored the various outcomes of linguistic pluralism. One of these outcomes is the creation of new languages. The presentation will focus on one of such languages, Camfranglais, a hybrid language spoken by Cameroonians. It appeared in the 1970s in the francophone area in Cameroon and developed as a result of interactions between French, English, Cameroonian Pidgin English and local Cameroonian languages, all languages spoken in Cameroon. With the migration of Cameroonians to Europe, researches have been conducted to analyze the sociolinguistic profile of Cameroonians in their new environment. The emphasis on this presentation will be on two recent studies that have been conducted to analyze the peculiarity of Camfranglais in two European countries: Germany and Italy. The research involved 59 Cameroonians living in Italy and 49 Cameroonians residing in Germany. The respondents were composed of participants from different linguistic background, students and workers, married and single. A combination of quantitative and qualitative research methods was employed. The field study was divided into three parts. The first part was focused on observing the Cameroonians interact in different places such as in canteens, in the university halls of residence, lecture theatres, at homes, at various Cameroonian meetings. Those observations were accompanied by audio-recordings of the various interactions. The aim was to study communication between Cameroonians to see whether they use Camfranglais or not; if yes, in which domains and what were the speakers’ linguistic profiles. Additionally, questionnaires of different lengths were used to collect biographical information concerning the participants and their sociolinguistic profile and finally, in-depth interviews with Cameroonians were conducted to inquire about the use, the functions and the importance of this language in the migratory context. The results of the research demonstrate how a widespread use of Camfranglais by Cameroonians in Germany and Italy reveal a longing for home on the one hand and a sign of belonging on the other. It also shows the differences that exist between the profiles of Camfranglais speakers in Europe and the speakers in Cameroon notably in terms of age and social class. Finally, it points out some differences in the use, the structure and the functions of this hybrid language in the migratory setting. This study is a contribution to existing research in the field of contact languages and can serve as a comparison for other situations of multilingualism and the creation of mixed languages. Furthermore, with globalization, the study of migrant languages and the contact of these languages with new languages are topics that might be productive for further research in the field of sociolinguistics.

Keywords: interaction, migrants language, multilingualism, mixed languages

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Mohamad Shurair, Fares Almomani, Simon Judd, Rahul Bhosale, Anand Kumar, Ujjal Gosh

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This study evaluated the use of mixed indigenous microalgae (MIMA) as a treatment process for wastewaters and CO2 capturing technology at different temperatures. The study follows the growth rate of MIMA, removals of organic matter, removal of nutrients from synthetic wastewater and its effectiveness as CO2 capturing technology from flue gas. A noticeable difference between the growth patterns of MIMA was observed at different CO2 and different operational temperatures. MIMA showed the highest growth grate when injected with CO2 dosage of 10% and limited growth was observed for the systems injected with 5% and 15 % of CO2 at 30 ◦C. Ammonia and phosphorus removals for Spirulina were 69%, 75%, and 83%, and 20%, 45%, and 75% for the media injected with 0, 5 and 10% CO2. The results of this study show that simple and cost-effective microalgae-based wastewater treatment systems can be successfully employed at different temperatures as a successful CO2 capturing technology even with the small probability of inhibition at high temperatures

Keywords: greenhouse, climate change, CO2 capturing, green algae

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Authors: Misha Nedeljkovich

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In the film’s famous scene (Roma città aperta-1945), Pina (Anna Magnani) collapses in the street when machined-gunned by a German soldier. Her son Marcello (Vito Annchiarico) tries to revive her. Her death is signaling not closure, but the cycle of life; Marcello saves Francesco with the shawl taken from his mother’s corpse. One pivotal scene in Brief Encounter (1945) occurs in the apartment of Alec’s (Trevor Howard) friend Stephen (Valentine Dyall), when Stephen returns to catch Alec and Laura (Celia Johnson) together alone. David Lean directs this scene using her shawl as a sign of in flagrante delicto. In La Strada (1954), Gelsomina (Giulietta Masina) was waving good bye when her mother sensing impending doom changed her mind and desperately tried to stop her waving back with her shawl: Don’t go my daughter! Your shawl! Your shawl! Gelsomina refuses to return, waving back: It’s time to go! Stanley Kubrick’s tale of a boxer who crosses a mobster to win the heart of a lady, Killer’s Kiss (1955), reminds us that Times Square used to contain sweaty boxing gyms and dance halls. The film’s longest Times Square interlude is its oddest: the boxer Davie Gordon played by Jamie Smith has his shawl stolen by two playful men in Shriners’ hats who are silent except for one who blows a harmonica, faintly heard over honking cabs and overheard conversations. This long sequence appears to be joining in on directors’ shawl conversations with Kubrick’s own twist. Principle characters will never know why all this happened to them that evening. Love, death, happiness and everlasting misery all of that is caused by Dave’s shawl. Finally, the decade of cinematic shawl conversations conclude in Betolucci’s Before the Revolution (Prima della rivoluzione–1964). One of his character’s lifts up a shawl asking if this was a Rossellini’s shawl. I argue that exploring complimentary allusions in a film where directors are acknowledging their own great debt to another film or filmmaker will further our knowledge of film history adding both depth and resonance to the great works in cinema.

Keywords: allusions, Bertolucci, Fellini, homage, Kubrick, lean, Rossellini

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Authors: Timor Melamed

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In this study, it consider two methods for synthesizing a pulsed curved beam along a generic beam-axis trajectory. In the first approach, the evaluate the space-time aperture field distribution that radiates the beam along a predefined trajectory by constructing a time-dependent caustic surface around the beam-axis skeleton. it derive the aperture field delay to form a caustic of rays along the beam axis and extend this method to other points over the aperture. In the second approach, the harness the proven capabilities of beam methods to address the challenge of designing curved intensity profiles in three-dimensional free space. By leveraging advanced beam propagation techniques, we create and manipulate complex intensity patterns along arbitrary curved trajectories, offering new possibilities for precision control in various wave-based applications. Numerical examples are presented to demonstrate the robust capabilities of both methods.

Keywords: pulsed Airy beams, pulsed beams, pulsed curved beams, transient fields

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Authors: Nattachote Rugthaicharoencheep

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This paper presents a feeder reconfiguration problem in distribution systems. The objective is to minimize the system power loss and to improve bus voltage profile. The optimization problem is subjected to system constraints consisting of load-point voltage limits, radial configuration format, no load-point interruption, and feeder capability limits. A method based on genetic algorithm, a search algorithm based on the mechanics of natural selection and natural genetics, is proposed to determine the optimal pattern of configuration. The developed methodology is demonstrated by a 33-bus radial distribution system with distributed generations and feeder capacitors. The study results show that the optimal on/off patterns of the switches can be identified to give the minimum power loss while respecting all the constraints.

Keywords: network reconfiguration, distributed generation capacitor placement, loss reduction, genetic algorithm

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Authors: Cher Leng Lee

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The existence of multiple first-person pronouns (1PPs) in classical Chinese is an issue that has not been resolved despite linguists using the grammatical perspective. This paper proposes pragmatics as a viable solution. There is also a lack of research exploring the evolving usage patterns of 1PPs within the historical context of Chinese language use. Such research can help us comprehend the changes and developments of these linguistic elements. To fill these research gaps, we use the diachronic pragmatics approach to contrast the functions of Chinese 1PPs in three representative texts from three different historical periods: The Analects (The Spring and Autumn Period), The Grand Scribe’s Records (Grand Records) (Qin and Han Period), and A New Account of Tales of the World (New Account) (The Wei, Jin and Southern and Northern Period). The 1PPs of these texts are manually identified and classified according to the pragmatic functions in the given contexts to observe their historical changes, understand the factors that contribute to these changes, and provide possible answers to the development of how wo became the only 1PP in today’s spoken Mandarin.

Keywords: Chinese language, classical Chinese, historical linguistics, pragmatics, first-person pronouns

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Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

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As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Qiying Zhang, Panpan Xu, Hui Qian

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Groundwater is an important water resource in the world, especially in arid and semi-arid regions. In the present study, 141 groundwater samples were collected and analyzed for various physicochemical parameters to assess the irrigation water quality using six indicators (sodium percentage (Na%), sodium adsorption ratio (SAR), magnesium hazard (MH), residual sodium carbonate (RSC), permeability index (PI), and potential salinity (PS)). The results show that the patterns for the average cation and anion concentrations were in decreasing orders of Na^＋ > Mg^2＋ > Ca^2＋ > K^＋and SO₄^2－ > HCO₃^－ > Cl^－ > NO₃^－ > CO₃^2－ > F^－, respectively. The values of Na%, MH, and PS show that most of the groundwater samples are not suitable for irrigation. The same conclusion is drawn from the USSL and Wilcox diagrams. PS values indicate that Cl^－and SO₄^2－have a great influence on irrigation water in Jiaokou Irrigation District. RSC and PI values indicate that more than half of groundwater samples are suitable for irrigation. The finding is beneficial for the policymakers for future water management schemes to achieve a sustainable development goal.

Keywords: groundwater chemistry, Guanzhong Basin, irrigation water quality evaluation, Jiaokou Irrigation District

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Authors: (Ted) Edward Holmberg, Mahdi Abdelguerfi, Elias Ioup

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This research details a coverage measure for evaluating the effectiveness of observer node placements in a spatial bipartite network. This coverage measure can be used to optimize the configuration of stationary or mobile spatially oriented observer nodes, or a hybrid of the two, over time in order to fully utilize their capabilities. To demonstrate the practical application of this approach, we construct a SpatioTemporal Bipartite Network (STBN) using real-time crime center (RTCC) camera nodes and NOPD calls for service (CFS) event nodes from New Orleans, La (NOLA). We use the coverage measure to identify optimal placements for moving mobile RTCC camera vans to improve coverage of vulnerable areas based on temporal patterns.

Keywords: coverage measure, mobile node dynamics, Monte Carlo simulation, observer nodes, observable nodes, spatiotemporal bipartite knowledge graph, temporal spatial analysis

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Authors: George Clifford Yamson

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As institutions across the world become more focused on sustainability, academic libraries are considering ways to reduce their environmental impact. One strategy is the use of sustainable online services, which can reduce the need for physical materials and transportation. This study aims to analyze the effectiveness of sustainable online services in reducing the environmental impact of academic libraries. Using a mixed-methods approach, the survey will be used to solicit information from library staff and users to gather data on their attitudes towards sustainable online services and their usage patterns. A comparative analysis will be conducted on the costs of traditional library services versus sustainable online services. The findings of this study will contribute to the growing body of literature on green academic libraries and provide insights into the potential of sustainable online services to reduce the environmental impact of academic libraries.

Keywords: sustainability, environmental sustainability, academic libraries, green printing, green copying, online services

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Iniye Irene Wodi, Allen A. Agih

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Goal theory perspective as an emerging trend in students’ motivation explores reasons why students engage in achievement related behaviour. While previous research typifies students’ goal orientations into two dimensions of mastery and performance orientations in various other parts of the world, not much has been done in this regard in Nigeria and specifically in Bayelsa state to the best of the researcher’s knowledge. To this end, the study explores the achievement goal orientations of schooling adolescents in Bayelsa State. The sample of the study consists of 220 schooling adolescents drawn from four urban schools in the state. A modified form of the Patterns of Adaptive learning survey (PALS) questionnaire was used to elicit data. Results indicated that schooling adolescents in Bayelsa state are mastery as well as performance oriented. The students also did not differ in goal orientations by gender. The implications of this for sustainable development were highlighted.

Keywords: achievement goals, goal orientations, schooling adolescents, sustainable development

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Authors: Chengming Li, Yong Yin, Peipei Guo, Xiaoli Liu

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Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.

Keywords: POI, road network, selection method, spatial information expression, distribution pattern

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Authors: Shokooh Moghadam, Mohammad Taghi Khorasani, Sajjad Seifi Mofarah, M. Daliri

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Through the recent two decades, the use of magnetic-property materials with the aim of target cell’s separation and eventually cancer treatment has incredibly increased. Numerous factors can alter the efficacy of this method on curing. In this project, the effect of magnetic field on adhesion of PDL and L929 cells on nanocomposite of iron oxide/PHB with different density of iron oxides (1%, 2.5%, 5%) has been studied. The nanocamposite mentioned includes a polymeric film of poly hydroxyl butyrate and γ-Fe2O3 particles with the average size of 25 nanometer dispersed in it and during this process, poly vinyl alcohol with 98% hydrolyzed and 78000 molecular weight was used as an emulsion to achieve uniform distribution. In order to get the homogenous film, the solution of PHB and iron oxide nanoparticles were put in a dry freezer and in liquid nitrogen, which resulted in a uniform porous scaffold and for removing porosities a 100◦C press was used. After the synthesis of a desirable nanocomposite film, many different tests were performed, First, the particles size and their distribution in the film were evaluated by transmission electron microscopy (TEM) and even FTIR analysis and DMTA test were run in order to observe and accredit the chemical connections and mechanical properties of nanocomposites respectively. By comparing the graphs of case and control samples, it was established that adding nano particles caused an increase in crystallization temperature and the more density of γ-Fe2O3 lead to more Tg (glass temperature). Furthermore, its dispersion range and dumping property of samples were raised up. Moreover, the toxicity, morphologic changes and adhesion of fibroblast and cancer cells were evaluated by a variety of tests. All samples were grown in different density and in contact with cells for 24 and 48 hours within the magnetic fields of 2×10^-3 Tesla. After 48 hours, the samples were photographed with an optic and SEM and no sign of toxicity was traced. The number of cancer cells in the case of sample group was fairly more than the control group. However, there are many gaps and unclear aspects to use magnetic field and their effects in cancer and all diseases treatments yet to be discovered, not to neglect that there have been prominent step on this way in these recent years and we hope this project can be at least a minimum movement in this issue.

Keywords: nanocomposite, cell attachment, magnetic field, cytotoxicity

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Authors: Umut Arslan, John Sommers Flanagan

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The purpose of this study was to investigate qualifications of ethics training in counselor education programs in Turkey. The survey data were collected from 251 Turkish counseling students to examine differences in ethical judgments between freshmen and seniors. Chi-square analysis was used to analyze the data from an ethical practice and belief survey. This survey was used to assess counselor candidates’ ethical judgments regarding Turkish counseling ethical codes and sources of ethics information. Statistically significant differences were found between university seniors and freshmen on items that are related to confidentiality, dual relationships, and professional relationships. Furthermore, patterns based on demographic information showed significant differences as a result of gender, economic status, and parents’ educational level. Participants gave the highest rating of information sources to Turkish counseling ethical codes.

Keywords: ethics, training, Turkey, counselor, education

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Authors: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

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In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.

Keywords: binary vector quantization (BVQ), DCT coefficients, face recognition, local binary patterns (LBP)

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Authors: Ranajoy Bhattcharyya

Abstract:

We estimate international product cycles as shifting product spaces by using 1976 to 2010 UN Comtrade data on all differentiated tradable products in all countries. We use a product space approach to identify the representative product baskets of high-, middle and low-income countries and then use these baskets to identify the patterns of change in comparative advantage of countries over time. We find evidence of a product cycle in two senses: First, high-, middle- and low-income countries differ in comparative advantage, and high-income products migrate to the middle-income basket. A similar pattern is observed for middle- and low-income countries. Our estimation of the lag shows that middle-income countries tend to quickly take up the products of high-income countries, but low-income countries take a longer time absorbing these products. Thus, the gap between low- and middle-income countries is considerably higher than that between middle- and high-income nations.

Keywords: product cycle, comparative advantage, representative product basket, ex-post data

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Authors: Waqas A. Toor, Anis U. Baig, Nuaman Shafqat, Raafia Irfan, Muhammad Ashraf

Abstract:

A 2.45GHz microwave plasma system and its few applications have been developed. Argon and helium plasma is produced by metallic nozzle and also in a quartz tube at atmospheric pressure, using WR-340 waveguide and its tapered version. The waveguide applicator is also simulated in HFSS and field patterns are analyzed for maximum power absorption in the load. The system is tuned to operate at less than 10% reflected power. Various experimental techniques are used to initiate and sustain the plasma at atmospheric pressure. Plasma of atmospheric air is also produced without using any other shielding gas. The plasma flame is also characterized by its spectrum. Spectral analyses of plasma flame can be used for online analysis of combustion gases produced in industry. The applications of the system include glass and quartz processing, vitrification, emission spectroscopy, plasma coating. Low pressure plasma applications of the system include intense UV light for water purification and ozone generation.

Keywords: HFSS high frequency structure simulator, Microwave plasma, UV ultraviolet, WR rectangular waveguide

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Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring the prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 352

Authors: Amal M. Alrayes, Hayat M. Ali

Abstract:

Since the beginning of distance education with the rapid evolution of technology, the social network plays a vital role in the educational process to enforce the interaction been the learners and teachers. There are many Web 2.0 technologies, services and tools designed for educational purposes. This research aims to investigate instructors’ acceptance towards web-based learning systems in higher educational institutes in Kingdom of Bahrain. Questionnaire is used to investigate the instructors’ usage of Web 2.0 and the factors affecting their acceptance. The results confirm that instructors had high accessibility to such technologies. However, patterns of use were complex. Whilst most expressed interest in using online technologies to support learning activities, learners seemed cautious about other values associated with web-based system, such as the shared construction of knowledge in a public format. The research concludes that there are main factors that affect instructors’ adoption which are security, performance expectation, perceived benefits, subjective norm, and perceived usefulness.

Keywords: Web 2.0, higher education, acceptance, students' perception

Procedia PDF Downloads 338

Authors: Purnomo Yustianto, Robin Doss, Suhardi, Novianto Budi Kurniawan

Abstract:

As a term for characterizing a process of devising a service system, the term ‘service engineering’ is still regarded as an ‘open’ research challenge due to unspecified details and conflicting perspectives. This paper presents consolidated service engineering ontologies in collecting, specifying and defining relationship between components pertinent within the context of service engineering. The ontologies are built by way of literature surveys from the collected conceptual works by collating various concepts into an integrated ontology. Two ontologies are produced: general service ontology and software service ontology. The software-service ontology is drawn from the informatics domain, while the generalized ontology of a service system is built from both a business management and the information system perspective. The produced ontologies are verified by exercising conceptual operationalizations of the ontologies in adopting several service orientation features and service system patterns. The proposed ontologies are demonstrated to be sufficient to serve as a basis for a service engineering framework.

Keywords: engineering, ontology, service, SoaML

Procedia PDF Downloads 191

Authors: Mohammad Ibrahim

Abstract:

The study was conducted at Albasar international foundation ophthalmic hospitals in Sudan to study the burden and patterns of ophthalmic disorder in the sector. Review of the hospitals records revealed that the total number of patient examined in the hospitals and outreached camps conducted by the hospitals is 10,513,874, the total number of surgeries is 694,015 and the total number of pupils at school program is 230,382. The organization working with the highest management system and standards and quality result based planning. The study yielded that the ophthalmic problem in Sudan are of great percentage and the temporal blindness disorder are high since major cases and surgeries were Cataract (57.8%). Retinal problem (2.9%), Glaucoma (2.4%), Orbit and Occulo-plastic disorders (2.2%) other disorders are refractive errors, squint and strabismus, Corneal, Pediatrics and minor ophthalmic disorders.

Keywords: hospitals and outreach ophthalmic services, largest coverage of ophthalmic services, nonprofitable ophthalmic services, strong management system and standards

Procedia PDF Downloads 414