Search results for: sensory processing patterns

Authors: Jiahui Song

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There have been decades of research into the action potential block in nerves. To our best knowledge electrical voltages can reversibly block the conduction of action potentials across whole animal nerves. Blocking biological electrical signaling pathways can have a variety of applications in muscular and sensory incapacitation and clinical research, including urethral pressure reduction and relieving chronic pain relief from a peripheral nerve injury. The cessation ability has been used in muscle activation and fatigue reduction. Ultrashort, high-intensity electric pulses modulate the membrane conductivity to block nerve conduction through the electroporation process. Nanopore formation on the membrane surface would increase the local membrane conductivity and effectively "short-out" the trans-membrane potential of a nerve that inhibits action potential propagation. This block would be similar in concept to stopping the propagation of an air-pressure wave down a "leaky" pipe. This research focuses on a distributed electrical model with an additional time-dependent membrane conductance to calculate the poration induced by the ultrashort, high-intensity electric pulses. The changes in membrane conductivity are used to predict changes in action potential transmission. A "strength-duration (SD)" curve is generated for action potential blockage and would be used as a design guide for benchmarking safety thresholds or setting the pulse voltage and/or durations necessary for neuro-muscular incapacitation.

Keywords: action potential, ultrashort, high-intensity, nerve, strength-duration

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Authors: Ram Mohan, Richard Haney, Ajit Kelkar

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Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.

Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance

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Authors: Abdeljalil Beniiche

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The limitation with smart contracts is that they cannot access external data that might be required to control the execution of business logic. Oracles can be used to provide external data to smart contracts. An oracle is an interface that delivers data from external data outside the blockchain to a smart contract to consume. Oracle can deliver different types of data depending on the industry and requirements. In this paper, we study and describe the widely used blockchain oracles. Then, we elaborate on his potential role, technical architecture, and design patterns. Finally, we discuss the human oracle and its key role in solving the truth problem by reaching a consensus about a certain inquiry and tasks.

Keywords: blockchain, oracles, oracles design, human oracles

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Authors: Archana G. Lamdande, Shyam R. Garud, K. S. M. S. Raghavarao

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Coconut has two edible parts, that is, a white kernel (solid endosperm) and coconut water (liquid endosperm). The white kernel is generally used in fresh or dried form for culinary purposes. Coconut testa, is the brown skin, covering the coconut kernel. It is removed by paring of wet coconut and obtained as a by-product in coconut processing industries during the production of products such as desiccated coconut, coconut milk, whole coconut milk powder and virgin coconut oil. At present, it is used as animal feed component after drying and recovering the residual oil (by expelling). Experiments were carried out on expelling of coconut milk for shredded coconut with and without testa removal, in order to explore the possibility of increasing the milk yield and value addition in terms of increased polyphenol content. The color characteristics of coconut milk obtained from the grating without removal of testa were observed to be L* 82.79, a* 0.0125, b* 6.245, while that obtained from grating with removal of testa were L* 83.24, a* -0.7925, b* 3.1. A significant increase was observed in total phenol content of coconut milk obtained from the grating with testa (833.8 µl/ml) when compared to that from without testa (521.3 µl/ml). However, significant difference was not observed in protein content of coconut milk obtained from the grating with and without testa (4.9 and 5.0% w/w, respectively). Coconut milk obtained from grating without removal of testa showed higher milk yield (62% w/w) when compared to that obtained from grating with removal of testa (60% w/w). The fat content in coconut milk was observed to be 32% (w/w), and it is unstable due to such a high fat content. Therefore, several experiments were carried out for examining its stability by adjusting the fat content at different levels (32, 28, 24, and 20% w/w). It was found that the coconut milk was more stable with a fat content of 24 % (w/w). Homogenization and ultrasonication and their combinations were used for exploring the possibility of increasing the stability of coconut milk. The microscopic study was carried out for analyzing the size of fat globules and the degree of their uniform distribution.

Keywords: coconut milk, homogenization, stability, testa, ultrasonication

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Bouayachi Ali, Alikouss Saida, Baroudi Zouhir, Zerhouni Youssef, Zouhair Mohammed, El Idrissi Assia, Essalhi Mourad

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The world-class Imiter silver deposit is located on the northern flank of the Precambrian Imiter buttonhole. This deposit is formed by epithermal veins hosted in the sandstone-pelite formations of the lower complex and in the basic conglomerates of the upper complex, these veins are controlled by a regional scale fault cluster, oriented N70°E to N90°E. The present work on the contribution of remote sensing on the geological mapping of the Imiter buttonhole and application to the mineralized structures of the Principal Corps B3. Mapping on satellite images is a very important tool in mineral prospecting. It allows the localization of the zones of interest in order to orientate the field missions by helping the localization of the major structures which facilitates the interpretation, the programming and the orientation of the mining works. The predictive map also allows for the correction of field mapping work, especially the direction and dimensions of structures such as dykes, corridors or scrapings. The use of a series of processing such as SAM, PCA, MNF and unsupervised and supervised classification on a Landsat 8 satellite image of the study area allowed us to highlight the main facies of the Imite area. To improve the exploration research, we used another processing that allows to realize a spatial distribution of the alteration mineral indices, and the application of several filters on the different bands to have lineament maps.

Keywords: principal corps B3, teledetection, Landsat 8, Imiter II, silver mineralization, lineaments

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Authors: Jeremy Johnson, Craig Nitschke, Luke Kelly

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Fire regimes, climate and topographic gradients interact to influence ecosystem structure and function across fire-prone, montane landscapes worldwide. Biota have developed a range of adaptations to historic fire regime thresholds, which allow them to persist in these environments. In south-eastern Australia, a signal of fire regime changes is emerging across these landscapes, and anthropogenic climate change is likely to be one of the main drivers of an increase in burnt area and more frequent wildfire over the last 25 years. This shift has the potential to modify vegetation structure and composition at broad scales, which may lead to landscape patterns to which biota are not adapted, increasing the likelihood of local extirpation of some mammal species. This study aimed to address concerns related to the influence of abrupt changes in fire regimes on mammal populations in montane landscapes. It first examined the impact of climate, topography, and vegetation on fire patterns and then explored the consequences of these changes on mammal populations and their habitats. Field studies were undertaken across diverse vegetation, fire severity and fire frequency gradients, utilising camera trapping and passive acoustic monitoring methodologies and the collection of fine-scale vegetation data. Results show that drought is a primary contributor to fire regime shifts at the landscape scale, while topographic factors have a variable influence on wildfire occurrence at finer scales. Frequent, high severity wildfire influenced forest structure and composition at broad spatial scales, and at fine scales, it reduced occurrence of hollow-bearing trees and promoted coarse woody debris. Mammals responded differently to shifts in forest structure and composition depending on their habitat requirements. This study highlights the complex interplay between fire regimes, environmental gradients, and biotic adaptations across temporal and spatial scales. It emphasizes the importance of understanding complex interactions to effectively manage fire-prone ecosystems in the face of climate change.

Keywords: fire, ecology, biodiversity, landscape ecology

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Authors: Mohammad Naseh Nasrollahi Shahri

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The article draws on Michael Bakhtin’s theory of language to examine peer interactions. It represents an analysis of other-repetition in student interactions. Several recent studies have explored various aspects of repetition in multiple contexts. However, other-repetition in peer interactions has not received enough attention. Building on previous studies, this study examines patterns of other-repetition or appropriation in the context of discussion activities performed by EFL learners. The analysis highlights the meaningfulness of other-repetition in a way that distinguishes them from rote-repetition. It is suggested that instances of repetition constitute third spaces between the self and other which provide ideal settings for language learning and demonstrate student agency and engagement.

Keywords: repetition, agency, Bakhtin, dialogue

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Authors: Sachi Nandan Mohanty, Shreya Sinha, Sweeti Sah, Shweta Sharma

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The advancement of natural language processing has majorly influenced the field of medical transcript classification, providing a robust framework for enhancing the accuracy of clinical data processing. It has enormous potential to transform healthcare and improve people's livelihoods. This research focuses on improving the accuracy of medical transcript categorization using Bidirectional Encoder Representations from Transformers (BERT) and its specialized variants, including BioBERT, ClinicalBERT, SciBERT, and BlueBERT. The experimental work employs Optuna, an optimization framework, for hyperparameter tuning to identify the most effective variant, concluding that BioBERT yields the best performance. Furthermore, various optimizers, including Adam, RMSprop, and Layerwise adaptive large batch optimization (LAMB), were evaluated alongside BERT's default AdamW optimizer. The findings show that the LAMB optimizer achieves a performance that is equally good as AdamW's. Synthetic data generation techniques from Gretel were utilized to augment the dataset, expanding the original dataset from 5,000 to 10,000 rows. Subsequent evaluations demonstrated that the model maintained its performance with synthetic data, with the LAMB optimizer showing marginally better results. The enhanced dataset and optimized model configurations improved classification accuracy, showcasing the efficacy of the BioBERT variant and the LAMB optimizer. It resulted in an accuracy of up to 98.2% and 90.8% for the original and combined datasets.

Keywords: BioBERT, clinical data, healthcare AI, transformer models

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Authors: M. N. Baig, F. N. Khan, M. Junaid

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Titanium alloys are widely employed in aerospace, medical, chemical, and marine applications. These alloys offer many advantages such as low specific weight, high strength to weight ratio, excellent corrosion resistance, high melting point and good fatigue behavior. These attractive properties make titanium alloys very unique and therefore they require special attention in all areas of processing, especially welding. In this work, 1.6 mm thick sheets of Ti-5Al-2,5Sn, an alpha titanium (α-Ti) alloy, were welded using electron beam (EBW) and laser beam (LBW) welding processes to achieve a full penetration Bead-on Plate (BoP) configuration. The weldments were studied using polarized optical microscope, SEM, EDS and XRD. Microhardness distribution across the weld zone and smooth and notch tensile strengths of the weldments were also recorded. Residual stresses using Hole-drill Strain Measurement (HDSM) method and deformation patterns of the weldments were measured for the purpose of comparison of the two welding processes. Fusion zone widths of both EBW and LBW weldments were found to be approximately equivalent owing to fairly similar high power densities of both the processes. Relatively less oxide content and consequently high joint quality were achieved in EBW weldment as compared to LBW due to vacuum environment and absence of any shielding gas. However, an increase in heat-affected zone width and partial ά-martensitic transformation infusion zone of EBW weldment were observed because of lesser cooling rates associated with EBW as compared with LBW. The microstructure infusion zone of EBW weldment comprised both acicular α and ά martensite within the prior β grains whereas complete ά martensitic transformation was observed within the fusion zone of LBW weldment. Hardness of the fusion zone in EBW weldment was found to be lower than the fusion zone of LBW weldment due to the observed microstructural differences. Notch tensile specimen of LBW exhibited higher load capacity, ductility, and absorbed energy as compared with EBW specimen due to the presence of high strength ά martensitic phase. It was observed that the sheet deformation and deformation angle in EBW weldment were more than LBW weldment due to relatively more heat retention in EBW which led to more thermal strains and hence higher deformations and deformation angle. The lowest residual stresses were found in LBW weldments which were tensile in nature. This was owing to high power density and higher cooling rates associated with LBW process. EBW weldment exhibited highest compressive residual stresses due to which the service life of EBW weldment is expected to improve.

Keywords: Laser and electron beam welding, Microstructure and mechanical properties, Residual stress and distortions, Titanium alloys

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Ruby Priya, O. P. Pandey

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Herein, we report the structural and luminescent properties of undoped and Eu doped SrY₂O₄ phosphors. The phosphors are synthesized via the combustion synthesis route using glycine as a fuel. The structural, morphological, and optical characterizations are done via X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescent (PL) techniques. The pure phase SrY₂O₄ is obtained at 1100℃, below which impure phases such as Y₂O₃ and SrO were dominant. All the phosphors are excited under UV excitation and exhibited intense emission around 611 nm, which is the typical transition of Eu ions. The phase formation of the synthesized phosphors is studied via analyzing XRD patterns. The as-synthesized phosphors find tremendous applications in optoelectronic devices, light-emitting diodes, and sensors.

Keywords: combustion, europium, glycine, luminescence

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Authors: Moustafa Osman Mohammed

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Integration sustainability outcomes give attention to construction ecology in the design review of urban environments to comply with Earth’s System that is composed of integral parts of the (i.e., physical, chemical and biological components). Naturally, exchange patterns of industrial ecology have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. When engineering topology is affecting internal and external processes in system networks, it postulated the valence of the first-level spatial outcome (i.e., project compatibility success). These instrumentalities are dependent on relating the second-level outcome (i.e., participant security satisfaction). Construction ecology approach feedback energy from resources flows between biotic and abiotic in the entire Earth’s ecosystems. These spatial outcomes are providing an innovation, as entails a wide range of interactions to state, regulate and feedback “topology” to flow as “interdisciplinary equilibrium” of ecosystems. The interrelation dynamics of ecosystems are performing a process in a certain location within an appropriate time for characterizing their unique structure in “equilibrium patterns”, such as biosphere and collecting a composite structure of many distributed feedback flows. These interdisciplinary systems regulate their dynamics within complex structures. These dynamic mechanisms of the ecosystem regulate physical and chemical properties to enable a gradual and prolonged incremental pattern to develop a stable structure. The engineering topology of construction ecology for integration sustainability outcomes offers an interesting tool for ecologists and engineers in the simulation paradigm as an initial form of development structure within compatible computer software. This approach argues from ecology, resource savings, static load design, financial other pragmatic reasons, while an artistic/architectural perspective, these are not decisive. The paper described an attempt to unify analytic and analogical spatial modeling in developing urban environments as a relational setting, using optimization software and applied as an example of integrated industrial ecology where the construction process is based on a topology optimization approach.

Keywords: construction ecology, industrial ecology, urban topology, environmental planning

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Authors: Esha Banerjee, Atul Kumar Ojha, Girish Nath Jha

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This study aims to develop an intonation labeled database for Hindi. Although no single standard for prosody labeling exists in Hindi, researchers in the past have employed perceptual and statistical methods in literature to draw inferences about the behavior of prosody patterns in Hindi. Based on such existing research and largely agreed upon intonational theories in Hindi, this study attempts to develop a manually annotated prosodic corpus of Hindi speech data, which can be used for training speech models for natural-sounding speech in the future. 100 sentences ( 500 words) each for declarative and interrogative types have been labeled using Praat.

Keywords: speech dataset, Hindi, intonation, labeled corpus

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Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Daniel Zaccariello

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Our study explores the usefulness of implementing facial expression recognition capabilities and using the Facial Action Coding System (FACS) in contexts where the other person is wearing a mask. In the communication process, the subjects use a plurality of distinct and autonomous reporting systems. Among them, the system of mimicking facial movements is worthy of attention. Basic emotion theorists have identified the existence of specific and universal patterns of facial expressions related to seven basic emotions -anger, disgust, contempt, fear, sadness, surprise, and happiness- that would distinguish one emotion from another. However, due to the COVID-19 pandemic, we have come up against the problem of having the lower half of the face covered and, therefore, not investigable due to the masks. Facial-emotional behavior is a good starting point for understanding: (1) the affective state (such as emotions), (2) cognitive activity (perplexity, concentration, boredom), (3) temperament and personality traits (hostility, sociability, shyness), (4) psychopathology (such as diagnostic information relevant to depression, mania, schizophrenia, and less severe disorders), (5) psychopathological processes that occur during social interactions patient and analyst. There are numerous methods to measure facial movements resulting from the action of muscles, see for example, the measurement of visible facial actions using coding systems (non-intrusive systems that require the presence of an observer who encodes and categorizes behaviors) and the measurement of electrical "discharges" of contracting muscles (facial electromyography; EMG). However, the measuring system invented by Ekman and Friesen (2002) - "Facial Action Coding System - FACS" is the most comprehensive, complete, and versatile. Our study, carried out on about 1,500 subjects over three years of work, allowed us to highlight how the movements of the hands and upper part of the face change depending on whether the subject wears a mask or not. We have been able to identify specific alterations to the subjects’ hand movement patterns and their upper face expressions while wearing masks compared to when not wearing them. We believe that finding correlations between how body language changes when our facial expressions are impaired can provide a better understanding of the link between the face and body non-verbal language.

Keywords: facial action coding system, COVID-19, masks, facial analysis

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Authors: Shutchapol Chopvitayakun

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Nowadays, especially for the last 5 years, mobile devices, mobile applications and mobile users, through the deployment of wireless communication and mobile phone cellular network, all these components are growing significantly bigger and stronger. They are being integrated into each other to create multiple purposes and pervasive deployments into every business and non-business sector such as education, medicine, traveling, finance, real estate and many more. Objective of this study was to develop a mobile application for seniors or last-year students who enroll the internship program at each tertiary school (undergraduate school) and do onsite practice at real field sties, real organizations and real workspaces. During the internship session, all students as the interns are required to exercise, drilling and training onsite with specific locations and specific tasks or may be some assignments from their supervisor. Their work spaces are both private and government corporates and enterprises. This mobile application is developed under schema of a transactional processing system that enables users to keep daily work or practice log, monitor true working locations and ability to follow daily tasks of each trainee. Moreover, it provides useful guidance from each intern’s advisor, in case of emergency. Finally, it can summarize all transactional data then calculate each internship cumulated hours from the field practice session for each individual intern.

Keywords: internship, mobile application, Android OS, smart phone devices, mobile transactional processing system, guidance and monitoring, tertiary education, senior students, model view controller (MVC)

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Authors: Marina Aferiba Tandoh, Elsie Odei

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Peptic Ulcer Disease (PUD) is amongst the commonest gastrointestinal problems that require emergency treatment in order to preserve life. The prevalence of PUD is increasing within the Ghanaian population, deepening the need to identify factors that are associated with its occurrence. This cross-sectional study assessed the nutritional status, socioeconomic and lifestyle factors associated with PUD among patients attending the Out-Patient Department of the Tema General Hospital of Ghana. A food frequency questionnaire and a three-day, 24-hour recall were used to assess the dietary intakes of study participants. A standardized questionnaire was used to obtain information on the participants’ socio-demographic characteristics, lifestyle as well as medical history. The data was analyzed using SPSS version 22. The mean age of study participants was 32.8±15.41years. Females were significantly higher (61.4%) than males (38.6%) (p < 0.001). All participants had received some form of education, with tertiary education being the highest (52.6%). The majority of them managed their condition with medications only (86%), while 10.5% managed it with a combination of medications and diet. The rest were either by dietary counseling only (1.8%), or surgery only (1.8%). or herbal medicines (29.3%), which were made from home (7.2%) or bought from a medical store (10.8%). Most of the participants experienced a recurrence of the disease (42.1%). For those who had ever experienced recurrences of the disease, it happened when they ate acidic foods (1.8%), ate bigger portions (1.8%), starved themselves (1.8%), or were stressed (1.8%). Others also had triggers when they took certain medications (1.8%) or ate too much pepper (1.8%). About 49% of the participants were either overweight or obese with a recurrence of PUD (p>0.05). Obese patients had the highest rate of PUD recurrences (41%). Drinking alcohol was significantly associated with the recurrence of PUD (χ2= 5.243, p=0.026). Other lifestyles, such as weed smoking, fasting, and use of herbal medicine and NSAIDs did not have any significant association with the disease recurrence. There was no significant correlation between the various dietary patterns and anthropometric parameters except dietary pattern one (salty snacks, regular soft drinks, milk, sweetened yogurt, ice cream, and cooked vegetables), which had a positive correlation with weight (p=0.002) and BMI (p=0.038). PUD patients should target weight reduction actions and reduce alcohol intake as measures to control the recurrence of the disease. Nutrition Education among this population must be promoted to minimize the recurrence of PUD.

Keywords: Dietary patterns, lifestyle factors, nutritional status, peptic ulcer disease

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Authors: Theresa Campbell, Camille Bowen-Forbes, William Aalbersberg

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Differences in the sensory properties of two subtly distinct varieties of Rubus rosifolius lead to the examination of their anthocyanin, essential oil and polyphenol profiles. In both cases, notable differences were identified. Pelargonidin-3-rhutinoside (17.2 mg/100 g FW) and Cyanidin-3-glucoside (66.2 mg/100g FW) proved to be the dominant anthocyanins in the red and wine red varieties respectively. Linalool and terpineol were the major constituents of the essential oil from the red variety; however, those of the wine red variety are unidentified. In regard to phenolic compounds, caffeic acid and quercetin were in a higher concentration in the red variety (1.85 and 0.73 mg/100g FW respectively, compared to 1.22 and 0.34 mg/100g FW respectively in the wine red fruits); while ellagic acid and ferulic acid were of a higher concentration in the wine red variety (0.92 and 0.84mg/100g FW respectively, compared to 0.15 and 0.48 mg/100g FW respectively in the red variety). The methanol extract of both fruit varieties showed great antioxidant activity. Analysis of the antimicrobial activity of the fruit extracts against the growth of drug resistant pathogens revealed that they are active against methicillin resistant S. aureus (MRSA), rifampicin resistant S. aureus (RRSA), wild-type S. aureus (WTSA) and vancomycin-resistant Enterococcus faecium (VREF). Activity was also reported against several food-borne pathogens including two strains of E. coli, L. monocytogenes and Enterobacter aerogenes. The cytotoxicity of the various extracts was assessed and the essential oil extracts exhibited superior activity. The phenolic composition and biological activity of the fruits indicate that their consumption is beneficial to health and also that their incorporation into functional foods and nutraceuticals should be considered.

Keywords: phytochemicals, antimicrobial, cytotoxic, Rubus rosifolius

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Authors: Elragig Aiman, Dreiwi Hanan, Townley Stuart, Elmabrook Idriss

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In this paper, we reconsider the analysis of the Oregonator model. We highlight an error in this analysis which leads to an incorrect depiction of the parameter region in which diffusion driven instability is possible. We believe that the cause of the oversight is the complexity of stability analyses based on eigenvalues and the dependence on parameters of matrix minors appearing in stability calculations. We regenerate the parameter space where Turing patterns can be seen, and we use the common Lyapunov function (CLF) approach, which is numerically reliable, to further confirm the dependence of the results on diffusion coefficients intensities.

Keywords: diffusion driven instability, common Lyapunov function (CLF), turing pattern, positive-definite matrix

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Authors: Abdul Muqsit Abbasi, Ibrahim Chhipa, Asad Anwer, Saad Farooq, Hassan Berry, Sonu Kumar, Sundar Ali, Muhammad Owais Mahmood, Areeb Ur Rehman, Bahram Baloch

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Accurate translation between structurally diverse languages, such as Arabic and English, presents a critical challenge in natural language processing due to significant linguistic and cultural differences. This paper investigates the effectiveness of Facebook’s mBART model, fine-tuned specifically for sequence-tosequence (seq2seq) translation tasks between Arabic and English, and enhanced through advanced refinement techniques. Our approach leverages the Alef Dataset, a meticulously curated parallel corpus spanning various domains to capture the linguistic richness, nuances, and contextual accuracy essential for high-quality translation. We further refine the model’s output using advanced language models such as GPT-3.5 and GPT-4, which improve fluency, coherence, and correct grammatical errors in translated texts. The fine-tuned model demonstrates substantial improvements, achieving a BLEU score of 38.97, METEOR score of 58.11, and TER score of 56.33, surpassing widely used systems such as Google Translate. These results underscore the potential of mBART, combined with refinement strategies, to bridge the translation gap between Arabic and English, providing a reliable, context-aware machine translation solution that is robust across diverse linguistic contexts.

Keywords: natural language processing, machine translation, fine-tuning, Arabic-English translation, transformer models, seq2seq translation, translation evaluation metrics, cross-linguistic communication

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Authors: N. Boudinar, A. Djekoun, A. Otmani, B. Bouzabata, J. M. Greneche

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High-energy ball milling is a solid-state powder processing technique that allows synthesizing a variety of equilibrium and non-equilibrium alloy phases starting from elemental powders. The advantage of this process technology is that the powder can be produced in large quantities and the processing parameters can be easily controlled, thus it is a suitable method for commercial applications. It can also be used to produce amorphous and nanocrystalline materials in commercially relevant amounts and is also amenable to the production of a variety of alloy compositions. Mechanical alloying (high-energy ball milling) provides an inter-dispersion of elements through a repeated cold welding and fracture of free powder particles; the grain size decreases to nano metric scale and the element mix together. Progressively, the concentration gradients disappear and eventually the elements are mixed at the atomic scale. The end products depend on many parameters such as the milling conditions and the thermodynamic properties of the milled system. Here, the mechanical alloying technique has been used to prepare nano crystalline Fe_50 and Fe_64 wt.% Ni alloys from powder mixtures. Scanning electron microscopy (SEM) with energy-dispersive, X-ray analyses and Mössbauer spectroscopy were used to study the mixing at nanometric scale. The Mössbauer Spectroscopy confirmed the ferromagnetic ordering and was use to calculate the distribution of hyperfin field. The Mössbauer spectrum for both alloys shows the existence of a ferromagnetic phase attributed to γ-Fe-Ni solid solution.

Keywords: nanocrystalline, mechanical alloying, X-ray diffraction, Mössbauer spectroscopy, phase transformations

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Cristina Greco

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The spread of the digital and we-based technologies has led to a transformation process, which has coincided with an increase in the number of cases who are beyond the mainstream storytelling and its codes on the interaction with the user. On the base of a previous research on i-docs and virtual museums, this study analyses interactive and immersive online Graphic Novel – one-page, animated, illustrated, and hybrid – to reflect on the transformational implications of this expressive form on the user perception, remembrance, and awareness. The way in which the user experiences a certain level of interaction with the story and immersion in the semantic and figurative universe would bring user’s attention, activating introspection and self-reflection processes, perception, imagination, and creativity. This would have to do with the involvement of different senses – visual, proprioceptive, tactile, auditory, and vestibular – and the activation of a phenomenon of synaesthesia (involuntary cross-modal sensory association) – where, for example, the aural reconnect the user to another sense, providing a multisensory experience. The case studies show specific forms of interactive and immersive graphic novel and reflect on application that has sought to engage innovative ways to communicate different messages and stimulate cultural memory and collective awareness. The visual semiotic and narrative analysis of the distinctive traits of such a complex textuality, along with a study of the user’s experience through observation in naturalistic settings and interviews, allows us to question the functioning of these configurations, with regard to the relationships between the figurative dimension, the perceptive activity, and their impact on the user’s engagement.

Keywords: collective awareness, cultural memory, graphic novel, interactive and immersive storytelling

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Authors: A. Zh. Aupova, A. Ulankyzy, A. Sarsenova, A. Kussayin, Sh. Turarbek, N. Moldagulova, A. Kurmanbayev

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One of the methods of organic waste bioconversion into environmentally-friendly fertilizer is composting. Microorganisms that produce hydrolytic enzymes play a significant role in accelerating the process of organic waste composting. We studied the enzymatic potential (amylase, protease, cellulase, lipase, urease activity) of bacteria isolated from the sewage sludge of Nur-Sultan, Rudny, and Fort-Shevchenko cities, the dacha soil of Nur-Sultan city, and freshly cut grass from the dacha for processing organic waste and identifying active strains. Microorganism isolation was carried out by the cultures enrichment method on liquid nutrient media, followed by inoculating on different solid media to isolate individual colonies. As a result, sixty-one microorganisms were isolated, three of which were thermophiles (DS1, DS2, and DS3). The highest number of isolates, twenty-one and eighteen, were isolated from sewage sludge of Nur-Sultan and Rudny cities, respectively. Ten isolates were isolated from the wastewater of the sewage treatment plant in Fort-Shevchenko. From the dacha soil of Nur-Sultan city and freshly cut grass - 9 and 5 isolates were revealed, respectively. The lipolytic, proteolytic, amylolytic, cellulolytic, ureolytic, and oil-oxidizing activities of isolates were studied. According to the results of experiments, starch hydrolysis (amylolytic activity) was found in 2 isolates - CB2/2, and CB2/1. Three isolates - CB2, CB2/1, and CB1/1 were selected for the highest ability to break down casein. Among isolated 61 bacterial cultures, three isolates could break down fats - CB3, CBG1/1, and IL3. Seven strains had cellulolytic activity - DS1, DS2, IL3, IL5, P2, P5, and P3. Six isolates rapidly decomposed urea. Isolate P1 could break down casein and cellulose. Isolate DS3 was a thermophile and had cellulolytic activity. Thus, based on the conducted studies, 15 isolates were selected as a potential for sewage sludge composting - CB2, CB3, CB1/1, CB2/2, CBG1/1, CB2/1, DS1, DS2, DS3, IL3, IL5, P1, P2, P5, P3. Selected strains were identified on a mass spectrometer (Maldi-TOF). The isolate - CB 3 was referred to the genus Rhodococcus rhodochrous; two isolates CB2 and CB1 / 1 - to Bacillus cereus, CB 2/2 - to Cryseobacterium arachidis, CBG 1/1 - to Pseudoxanthomonas sp., CB2/1 - to Bacillus megaterium, DS1 - to Pediococcus acidilactici, DS2 - to Paenibacillus residui, DS3 - to Brevibacillus invocatus, three strains IL3, P5, P3 - to Enterobacter cloacae, two strains IL5, P2 - to Ochrobactrum intermedium, and P1 - Bacillus lichenoformis. Hence, 60 isolates were isolated from the wastewater of the cities of Nur-Sultan, Rudny, Fort-Shevchenko, the dacha soil of Nur-Sultan city, and freshly cut grass from the dacha. Based on the highest enzymatic activity, 15 active isolates were selected and identified. These strains may become the candidates for bio preparation for sewage sludge processing.

Keywords: sewage sludge, composting, bacteria, enzymatic activity

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Authors: Vedansh Gupta, Allyson Lutz, Ameen Razavi, Fatemeh Shirazi

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The agriculture industry is especially vulnerable to forecasted water shortages. In the fresh and fresh-cut produce sector, conventional flume-based washing with recirculation exhibits high water demand. This leads to a large water footprint and possible cross-contamination of pathogens. These can be alleviated through advanced water reuse processes, such as membrane technologies including reverse osmosis (RO). Water reuse technologies effectively remove dissolved constituents but can easily foul without pre-treatment. Biological treatment is effective for the removal of organic compounds responsible for fouling, but not at the low temperatures encountered at most produce processing facilities. This study showed that the Microvi MicroNiche Engineering (MNE) technology effectively removes organic compounds (> 80%) at low temperatures (6-8 °C) from wash water. The MNE technology uses synthetic microorganism-material composites with negligible solids production, making it advantageously situated as an effective bio-pretreatment for RO. A preliminary technoeconomic analysis showed 60-80% savings in operation and maintenance costs (OPEX) when using the Microvi MNE technology for organics removal. This study and the accompanying economic analysis indicated that the proposed technology process will substantially reduce the cost barrier for adopting water reuse practices, thereby contributing to increased food safety and furthering sustainable water reuse processes across the agricultural industry.

Keywords: biological pre-treatment, innovative technology, vegetable processing, water reuse, agriculture, reverse osmosis, MNE biocatalysts

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Authors: Kamran Yazdanbakhsh, Somayeh Mahmoudi

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Multiple sclerosis is the most common chronic disease of the central nervous system associated with demyelination of neurons and several demyelinated parts of the disease encompasses throughout the white matter and affects the sensory and motor function. This study compared the effectiveness of two methods of cognitive therapy and supportive-expressive therapy on the efficacy and quality of life in MS patients. This is an experimental project which has used developed group pretest - posttest and follow-up with 3 groups. The study included all patients with multiple sclerosis in 2013 that were members of the MS Society of Iran in Tehran. The sample included 45 patients with MS that were selected volunteerily of members of the MS society of Iran and randomly divided into three groups and pretest, posttest, and follow-up (three months) for the three groups had been done.The dimensions of quality of life in patients with multiple sclerosis scale, and general self-efficiency scale of Schwarzer and Jerusalem was used for collecting data. The results showed that there was a significant difference between the mean of quality of life scores at pretest, posttest, and follow-up of the experimental groups. There was no significant difference between the mean of quality of life of the experimental groups which means that both groups were effective and had the same effect. There was no significant difference between the mean of self-efficiency scores in control and experimental group in pretest, posttest and follow-up. Thus, by using cognitive and supportive-expressive group therapy we can improve quality of life in MS patients and make great strides in their mental health.

Keywords: cognitive group therapy, life style, MS, self-efficiency, supportive-expressive group therapy

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Authors: Juan Sepúlveda

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Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Keywords: energy efficiency, MCA, scientometric, trends

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Authors: Anupam Bhatia

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Upon reviewing the literature and the pragmatic work done in the field of E- textiles, it is observed that the applications of wearable technologies have found a steady growth in the field of military, medical, industrial, sports; whereas fashion is at a loss to know how to treat this technology and bring it to market. The purpose of this paper is to understand the practical issues of integration of electronics in garments; cutting patterns for mass production, maintaining the basic properties of textiles and daily maintenance of garments that hinder the wide adoption of interactive fabric technology within Fashion and leisure wear. To understand the practical hindrances an experimental and laboratory approach is taken. “Techno Meets Fashion” has been an interactive fashion project where sensor technologies have been embedded with textiles that result in set of ensembles that are light emitting garments, sound sensing garments, proximity garments, shape memory garments etc. Smart textiles, especially in the form of textile interfaces, are drastically underused in fashion and other lifestyle product design. Clothing and some other textile products must be washable, which subjects to the interactive elements to water and chemical immersion, physical stress, and extreme temperature. The current state of the art tends to be too fragile for this treatment. The process for mass producing traditional textiles becomes difficult in interactive textiles. As cutting patterns from larger rolls of cloth and sewing them together to make garments breaks and reforms electronic connections in an uncontrolled manner. Because of this, interactive fabric elements are integrated by hand into textiles produced by standard methods. The Arduino has surely made embedding electronics into textiles much easier than before; even then electronics are not integral to the daily wear garments. Soft and flexible interfaces of MEMS (micro sensors and Micro actuators) can be an option to make this possible by blending electronics within E-textiles in a way that’s seamless and still retains functions of the circuits as well as the garment. Smart clothes, which offer simultaneously a challenging design and utility value, can be only mass produced if the demands of the body are taken care of i.e. protection, anthropometry, ergonomics of human movement, thermo- physiological regulation.

Keywords: ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology

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Authors: Zhang Songning, Guan Zheng, Ci Yan, Ding Gangyi

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The application of physical simulation engines in collaborative editing systems has an important background and role. Firstly, physical simulation engines can provide real-world physical simulations, enabling users to interact and collaborate in real time in virtual environments. This provides a more intuitive and immersive experience for collaborative editing systems, allowing users to more accurately perceive and understand various elements and operations in collaborative editing. Secondly, through physical simulation engines, different users can share virtual space and perform real-time collaborative editing within it. This real-time sharing and collaborative editing method helps to synchronize information among team members and improve the efficiency of collaborative work. Through experiments, the average model transmission speed of a single person in the collaborative editing system has increased by 141.91%; the average model processing speed of a single person has increased by 134.2%; the average processing flow rate of a single person has increased by 175.19%; the overall efficiency improvement rate of a single person has increased by 150.43%. With the increase in the number of users, the overall efficiency remains stable, and the physical simulation engine running status collaborative editing system also has horizontal scalability. It is not difficult to see that the design and implementation of a collaborative editing system based on physical simulation engines not only enriches the user experience but also optimizes the effectiveness of team collaboration, providing new possibilities for collaborative work.

Keywords: physics engine, simulation technology, collaborative editing, system design, data transmission

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