Search results for: visual information processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15004

Search results for: visual information processing

13864 Device Control Using Brain Computer Interface

Authors: P. Neeraj, Anurag Sharma, Harsukhpreet Singh

Abstract:

In current years, Brain-Computer Interface (BCI) scheme based on steady-state Visual Evoked Potential (SSVEP) have earned much consideration. This study tries to evolve an SSVEP based BCI scheme that can regulate any gadget mock-up in two unique positions ON and OFF. In this paper, two distinctive gleam frequencies in low-frequency part were utilized to evoke the SSVEPs and were shown on a Liquid Crystal Display (LCD) screen utilizing Lab View. Two stimuli shading, Yellow, and Blue were utilized to prepare the system in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital part. Elements of the brain were separated by utilizing discrete wavelet Transform. A prominent system for multilayer system diverse Neural Network Algorithm (NNA), is utilized to characterize SSVEP signals. During training of the network with diverse calculation Regression plot results demonstrated that when Levenberg-Marquardt preparing calculation was utilized the exactness turns out to be 93.9%, which is superior to another training algorithm.

Keywords: brain computer interface, electroencephalography, steady-state visual evoked potential, wavelet transform, neural network

Procedia PDF Downloads 333
13863 Improving Perceptual Reasoning in School Children through Chess Training

Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

Abstract:

Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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13862 KCBA, A Method for Feature Extraction of Colonoscopy Images

Authors: Vahid Bayrami Rad

Abstract:

In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

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13861 Achieving Flow at Work: An Experience Sampling Study to Comprehend How Cognitive Task Characteristics and Work Environments Predict Flow Experiences

Authors: Jonas De Kerf, Rein De Cooman, Sara De Gieter

Abstract:

For many decades, scholars have aimed to understand how work can become more meaningful by maximizing both potential and enhancing feelings of satisfaction. One of the largest contributions towards such positive psychology was made with the introduction of the concept of ‘flow,’ which refers to a condition in which people feel intense engagement and effortless action. Since then, valuable research on work-related flow has indicated that this state of mind is related to positive outcomes for both organizations (e.g., social, supportive climates) and workers (e.g., job satisfaction). Yet, scholars still do not fully comprehend how such deep involvement at work is obtained, given the notion that flow is considered a short-term, complex, and dynamic experience. Most research neglects that people who experience flow ought to be optimally challenged so that intense concentration is required. Because attention is at the core of this enjoyable state of mind, this study aims to comprehend how elements that affect workers’ cognitive functioning impact flow at work. Research on cognitive performance suggests that working on mentally demanding tasks (e.g., information processing tasks) requires workers to concentrate deeply, as a result leading to flow experiences. Based on social facilitation theory, working on such tasks in an isolated environment eases concentration. Prior research has indicated that working at home (instead of working at the office) or in a closed office (rather than in an open-plan office) impacts employees’ overall functioning in terms of concentration and productivity. Consequently, we advance such knowledge and propose an interaction by combining cognitive task characteristics and work environments among part-time teleworkers. Hence, we not only aim to shed light on the relation between cognitive tasks and flow but also provide empirical evidence that workers performing such tasks achieve the highest states of flow while working either at home or in closed offices. In July 2022, an experience-sampling study will be conducted that uses a semi-random signal schedule to understand how task and environment predictors together impact part-time teleworkers’ flow. More precisely, about 150 knowledge workers will fill in multiple surveys a day for two consecutive workweeks to report their flow experiences, cognitive tasks, and work environments. Preliminary results from a pilot study indicate that on a between level, tasks high in information processing go along with high self-reported fluent productivity (i.e., making progress). As expected, evidence was found for higher fluency in productivity for workers performing information processing tasks both at home and in a closed office, compared to those performing the same tasks at the office or in open-plan offices. This study expands the current knowledge on work-related flow by looking at a task and environmental predictors that enable workers to obtain such a peak state. While doing so, our findings suggest that practitioners should strive for ideal alignments between tasks and work locations to work with both deep involvement and gratification.

Keywords: cognitive work, office lay-out, work location, work-related flow

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13860 The Investigation of Relationship between Accounting Information and the Value of Companies

Authors: Golamhassan Ghahramani Aghdam, Pedram Bavili Tabrizi

Abstract:

The aim of this research is to investigate the relationship between accounting information and the value of the companies accepted in Tehran Exchange Market. The dependent variable in this research is the value of a company that is measured by price coefficients, and the independent variables are balance sheet information, profit and loss information, cash flow state information, and profit quality characteristics. The profit quality characteristic index is to be related and to be on-time. This research is an application research, and the research population includes all companies that are active in Tehran exchange market. The number of 194 companies was selected by the systematic method as the statistics sample in the period of 2018-2019. The multi-variable linear regression model was used for the hypotheses test. The results show that there is no relationship between accounting information and companies’ value (stock value) that can be due to the lack of efficiency of the investment market and the inability to use the accounting information by investment market activists.

Keywords: accounting information, company value, profit quality characteristics, price coefficient

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13859 Ophthalmic Hashing Based Supervision of Glaucoma and Corneal Disorders Imposed on Deep Graphical Model

Authors: P. S. Jagadeesh Kumar, Yang Yung, Mingmin Pan, Xianpei Li, Wenli Hu

Abstract:

Glaucoma is impelled by optic nerve mutilation habitually represented as cupping and visual field injury frequently with an arcuate pattern of mid-peripheral loss, subordinate to retinal ganglion cell damage and death. Glaucoma is the second foremost cause of blindness and the chief cause of permanent blindness worldwide. Consequently, all-embracing study into the analysis and empathy of glaucoma is happening to escort deep learning based neural network intrusions to deliberate this substantial optic neuropathy. This paper advances an ophthalmic hashing based supervision of glaucoma and corneal disorders preeminent on deep graphical model. Ophthalmic hashing is a newly proposed method extending the efficacy of visual hash-coding to predict glaucoma corneal disorder matching, which is the faster than the existing methods. Deep graphical model is proficient of learning interior explications of corneal disorders in satisfactory time to solve hard combinatoric incongruities using deep Boltzmann machines.

Keywords: corneal disorders, deep Boltzmann machines, deep graphical model, glaucoma, neural networks, ophthalmic hashing

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13858 Structured-Ness and Contextual Retrieval Underlie Language Comprehension

Authors: Yao-Ying Lai, Maria Pinango, Ashwini Deo

Abstract:

While grammatical devices are essential to language processing, how comprehension utilizes cognitive mechanisms is less emphasized. This study addresses this issue by probing the complement coercion phenomenon: an entity-denoting complement following verbs like begin and finish receives an eventive interpretation. For example, (1) “The queen began the book” receives an agentive reading like (2) “The queen began [reading/writing/etc.…] the book.” Such sentences engender additional processing cost in real-time comprehension. The traditional account attributes this cost to an operation that coerces the entity-denoting complement to an event, assuming that these verbs require eventive complements. However, in closer examination, examples like “Chapter 1 began the book” undermine this assumption. An alternative, Structured Individual (SI) hypothesis, proposes that the complement following aspectual verbs (AspV; e.g. begin, finish) is conceptualized as a structured individual, construed as an axis along various dimensions (e.g. spatial, eventive, temporal, informational). The composition of an animate subject and an AspV such as (1) engenders an ambiguity between an agentive reading along the eventive dimension like (2), and a constitutive reading along the informational/spatial dimension like (3) “[The story of the queen] began the book,” in which the subject is interpreted as a subpart of the complement denotation. Comprehenders need to resolve the ambiguity by searching contextual information, resulting in additional cost. To evaluate the SI hypothesis, a questionnaire was employed. Method: Target AspV sentences such as “Shakespeare began the volume.” were preceded by one of the following types of context sentence: (A) Agentive-biasing, in which an event was mentioned (…writers often read…), (C) Constitutive-biasing, in which a constitutive meaning was hinted (Larry owns collections of Renaissance literature.), (N) Neutral context, which allowed both interpretations. Thirty-nine native speakers of English were asked to (i) rate each context-target sentence pair from a 1~5 scale (5=fully understandable), and (ii) choose possible interpretations for the target sentence given the context. The SI hypothesis predicts that comprehension is harder for the Neutral condition, as compared to the biasing conditions because no contextual information is provided to resolve an ambiguity. Also, comprehenders should obtain the specific interpretation corresponding to the context type. Results: (A) Agentive-biasing and (C) Constitutive-biasing were rated higher than (N) Neutral conditions (p< .001), while all conditions were within the acceptable range (> 3.5 on the 1~5 scale). This suggests that when lacking relevant contextual information, semantic ambiguity decreases comprehensibility. The interpretation task shows that the participants selected the biased agentive/constitutive reading for condition (A) and (C) respectively. For the Neutral condition, the agentive and constitutive readings were chosen equally often. Conclusion: These findings support the SI hypothesis: the meaning of AspV sentences is conceptualized as a parthood relation involving structured individuals. We argue that semantic representation makes reference to spatial structured-ness (abstracted axis). To obtain an appropriate interpretation, comprehenders utilize contextual information to enrich the conceptual representation of the sentence in question. This study connects semantic structure to human’s conceptual structure, and provides a processing model that incorporates contextual retrieval.

Keywords: ambiguity resolution, contextual retrieval, spatial structured-ness, structured individual

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13857 Testing the Impact of Formal Interpreting Training on Working Memory Capacity: Evidence from Turkish-English Student-Interpreters

Authors: Elena Antonova Unlu, Cigdem Sagin Simsek

Abstract:

The research presents two studies examining the impact of formal interpreting training (FIT) on Working Memory Capacity (WMC) of student-interpreters. In Study 1, the storage and processing capacities of the working memory (WM) of last-year student-interpreters were compared with those of last-year Foreign Language Education (FLE) students. In Study 2, the impact of FIT on the WMC of student-interpreters was examined via comparing their results on WM tasks at the beginning and the end of their FIT. In both studies, Digit Span Task (DST) and Reading Span Task (RST) were utilized for testing storage and processing capacities of WM. The results of Study 1 revealed that the last-year student-interpreters outperformed the control groups on the RST but not on the DST. The findings of Study 2 were consistent with Study 1 showing that after FIT, the student-interpreters performed better on the RST but not on the DST. Our findings can be considered as evidence supporting the view that FIT has a beneficial effect not only on the interpreting skills of student-interpreters but also on the central executive and processing capacity of their WM.

Keywords: working memory capacity, formal interpreting training, student-interpreters, cross-sectional and longitudinal data

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13856 Improvement of Brain Tumors Detection Using Markers and Boundaries Transform

Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

Abstract:

This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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13855 Thermal and Visual Comfort Assessment in Office Buildings in Relation to Space Depth

Authors: Elham Soltani Dehnavi

Abstract:

In today’s compact cities, bringing daylighting and fresh air to buildings is a significant challenge, but it also presents opportunities to reduce energy consumption in buildings by reducing the need for artificial lighting and mechanical systems. Simple adjustments to building form can contribute to their efficiency. This paper examines how the relationship between the width and depth of the rooms in office buildings affects visual and thermal comfort, and consequently energy savings. Based on these evaluations, we can determine the best location for sedentary areas in a room. We can also propose improvements to occupant experience and minimize the difference between the predicted and measured performance in buildings by changing other design parameters, such as natural ventilation strategies, glazing properties, and shading. This study investigates the condition of spatial daylighting and thermal comfort for a range of room configurations using computer simulations, then it suggests the best depth for optimizing both daylighting and thermal comfort, and consequently energy performance in each room type. The Window-to-Wall Ratio (WWR) is 40% with 0.8m window sill and 0.4m window head. Also, there are some fixed parameters chosen according to building codes and standards, and the simulations are done in Seattle, USA. The simulation results are presented as evaluation grids using the thresholds for different metrics such as Daylight Autonomy (DA), spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE), and Daylight Glare Probability (DGP) for visual comfort, and Predicted Mean Vote (PMV), Predicted Percentage of Dissatisfied (PPD), occupied Thermal Comfort Percentage (occTCP), over-heated percent, under-heated percent, and Standard Effective Temperature (SET) for thermal comfort that are extracted from Grasshopper scripts. The simulation tools are Grasshopper plugins such as Ladybug, Honeybee, and EnergyPlus. According to the results, some metrics do not change much along the room depth and some of them change significantly. So, we can overlap these grids in order to determine the comfort zone. The overlapped grids contain 8 metrics, and the pixels that meet all 8 mentioned metrics’ thresholds define the comfort zone. With these overlapped maps, we can determine the comfort zones inside rooms and locate sedentary areas there. Other parts can be used for other tasks that are not used permanently or need lower or higher amounts of daylight and thermal comfort is less critical to user experience. The results can be reflected in a table to be used as a guideline by designers in the early stages of the design process.

Keywords: occupant experience, office buildings, space depth, thermal comfort, visual comfort

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13854 Alignment of Information System Strategy and Green Information System Strategy: Comprehension and A Review of the Literature

Authors: Wartika Memed Purawinata, Kridanto Surendro, Husni Sastramiharja, Iping Supriana S.

Abstract:

The information system is one of the contributors to environmental degradation and pollution are known to be released, such as the increasing of use of IT equipment and energy consumption , life cycles of IT equipment are getting shorter, IT equipment waste disposal and so on, therefore the information system should have a role in related environmental issues. Organization need to develop the ability of green to minimize negative impacts on the environment. Although the green information system is an important topic, many organizations fail to manage the environment in a way that is adequate because they ignore aspect of strategy. Alignment strategy is very important to ensure that all people do the activities of the organization headed in the same direction. Alignment strategy helps organization, determine which is more important for organization, and then make road mad to achieve the organization goal. Therefore, this paper discusses the review of the alignment, information systems strategy, and IS green strategy. With this discussion is expected there is an understanding about the alignment of information systems strategy and strategy of green IS, and its relationship with the achievement of business goals that have commitment to reduce the negative impact of information systems on the environment.

Keywords: alignment, strategy, information system, green

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13853 Human Machine Interface for Controlling a Robot Using Image Processing

Authors: Ambuj Kumar Gautam, V. Vasu

Abstract:

This paper introduces a head movement based Human Machine Interface (HMI) that uses the right and left movements of head to control a robot motion. Here we present an approach for making an effective technique for real-time face orientation information system, to control a robot which can be efficiently used for Electrical Powered Wheelchair (EPW). Basically this project aims at application related to HMI. The system (machine) identifies the orientation of the face movement with respect to the pixel values of image in a certain areas. Initially we take an image and divide that whole image into three parts on the basis of its number of columns. On the basis of orientation of face, maximum pixel value of approximate same range of (R, G, and B value of a pixel) lie in one of divided parts of image. This information we transfer to the microcontroller through serial communication port and control the motion of robot like forward motion, left and right turn and stop in real time by using head movements.

Keywords: electrical powered wheelchair (EPW), human machine interface (HMI), robotics, microcontroller

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13852 Implementation of a Method of Crater Detection Using Principal Component Analysis in FPGA

Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

Abstract:

We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.

Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time

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13851 Agricultural Cooperative Model: A Panacea for Economic Development of Small Scale Business Famers in Ilesha, Osun State, Nigeria

Authors: Folasade Adegbaju, Olusola Arowolo, Olufisayo Onawumi

Abstract:

Owolowo ile – ege garri processing industry which is a small scale cassava processing industry, located in Ilesha, Osun State was purposively selected as a case study because it is a cooperative business. This industry was established in 1991 by eight men (8) who were mostly retirees. A researcher made questionnaire was used to collect information from thirty (30) respondents: the manager, four official staffs and 25 randomly selected processors in the industry. The study found that within twelve years of the utilization of their self raised initial capital of N240, 000 naira (Two hundred and forty thousand naira) this cassava – based industry had impacted on and attracted the involvement of many more people because within the period of the study (i.e. 2007-2011) the processors had quadrupled in number (e.g. 8 to 30), the facilities (equipment) in use had increased from one machine and a frying pot to many, this translated into being able to produce large quantities of fried garri, fufu and also starch for marketing to the people in Ilesha and neighbouring cities like Ibadan, Lagos, etc. This is indicative of economic growth. The industry also became a source of employment for community members in the sense that, as at the time of study four staffs were employed to work and coordinate the industry. It was observed that despite all odds of small-scale industry and the problem of people migrating from rural to urban area, this agro-based industry still existed successfully in the community, and many of such industry can be replicated by such agricultural cooperative groups nationwide so as to further boost the productivity as well as the economy of the area and nation at large. However, government and individual still have major roles to play in ensuring the growth and development of the nation in this respect.The local agricultural cooperative groups should form regional cooperative consortium with more networking for the farmers, in order to create more jobs for the young ones and to increase agricultural productivity in the country thus resulting in a better and more sustainable economy.

Keywords: agricultural cooperative, cassava processing industry, model, small scale enterprise

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13850 Muscle: The Tactile Texture Designed for the Blind

Authors: Chantana Insra

Abstract:

The research objective focuses on creating a prototype media of the tactile texture of muscles for educational institutes to help visually impaired students learn massage extra learning materials further than the ordinary curriculum. This media is designed as an extra learning material. The population in this study was 30 blinded students between 4th - 6th grades who were able to read Braille language. The research was conducted during the second semester in 2012 at The Bangkok School for the Blind. The method in choosing the population in the study was purposive sampling. The methodology of the research includes collecting data related to visually impaired people, the production of the tactile texture media, human anatomy and Thai traditional massage from literature reviews and field studies. This information was used for analyzing and designing 14 tactile texture pictures presented to experts to evaluate and test the media.

Keywords: blind, tactile texture, muscle, visual arts and design

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13849 Using Technology to Enhance the Student Assessment Experience

Authors: Asim Qayyum, David Smith

Abstract:

The use of information tools is a common activity for students of any educational stage when they encounter online learning activities. Finding the relevant information for particular learning tasks is the topic of this paper as it investigates the use of information tools for a group of student participants. The paper describes and discusses the results with particular implications for use in higher education, and the findings suggest that improvement in assessment design and subsequent student learning may be achieved by structuring the purposefulness of information tools usage and online reading behaviors of university students.

Keywords: information tools, assessment, online learning, student assessment experience

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13848 Multi-Granularity Feature Extraction and Optimization for Pathological Speech Intelligibility Evaluation

Authors: Chunying Fang, Haifeng Li, Lin Ma, Mancai Zhang

Abstract:

Speech intelligibility assessment is an important measure to evaluate the functional outcomes of surgical and non-surgical treatment, speech therapy and rehabilitation. The assessment of pathological speech plays an important role in assisting the experts. Pathological speech usually is non-stationary and mutational, in this paper, we describe a multi-granularity combined feature schemes, and which is optimized by hierarchical visual method. First of all, the difference granularity level pathological features are extracted which are BAFS (Basic acoustics feature set), local spectral characteristics MSCC (Mel s-transform cepstrum coefficients) and nonlinear dynamic characteristics based on chaotic analysis. Latterly, radar chart and F-score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96-dimensions.The experimental results denote that new features by support vector machine (SVM) has the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation.

Keywords: pathological speech, multi-granularity feature, MSCC (Mel s-transform cepstrum coefficients), F-score, radar chart

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13847 Post Pandemic Mobility Analysis through Indexing and Sharding in MongoDB: Performance Optimization and Insights

Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

Abstract:

The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyze huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic well being is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that supports the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: big data, COVID-19, health, indexing, NoSQL, sharding, scalability, well being

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13846 A Study on Sentiment Analysis Using Various ML/NLP Models on Historical Data of Indian Leaders

Authors: Sarthak Deshpande, Akshay Patil, Pradip Pandhare, Nikhil Wankhede, Rushali Deshmukh

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Among the highly significant duties for any language most effective is the sentiment analysis, which is also a key area of NLP, that recently made impressive strides. There are several models and datasets available for those tasks in popular and commonly used languages like English, Russian, and Spanish. While sentiment analysis research is performed extensively, however it is lagging behind for the regional languages having few resources such as Hindi, Marathi. Marathi is one of the languages that included in the Indian Constitution’s 8th schedule and is the third most widely spoken language in the country and primarily spoken in the Deccan region, which encompasses Maharashtra and Goa. There isn’t sufficient study on sentiment analysis methods based on Marathi text due to lack of available resources, information. Therefore, this project proposes the use of different ML/NLP models for the analysis of Marathi data from the comments below YouTube content, tweets or Instagram posts. We aim to achieve a short and precise analysis and summary of the related data using our dataset (Dates, names, root words) and lexicons to locate exact information.

Keywords: multilingual sentiment analysis, Marathi, natural language processing, text summarization, lexicon-based approaches

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13845 Expansive-Restrictive Style: Conceptualizing Knowledge Workers

Authors: Ram Manohar Singh, Meenakshi Gupta

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Various terms such as ‘learning style’, ‘cognitive style’, ‘conceptual style’, ‘thinking style’, ‘intellectual style’ are used in literature to refer to an individual’s characteristic and consistent approach to organizing and processing information. However, style concepts are criticized for mutually overlapping definitions and confusing classification. This confusion should be addressed at the conceptual as well as empirical level. This paper is an attempt to bridge this gap in literature by proposing a new concept: expansive-restrictive intellectual style based on phenomenological analysis of an auto-ethnography and interview of 26 information technology (IT) professionals working in knowledge intensive organizations (KIOs) in India. Expansive style is an individual’s preference to expand his/her horizon of knowledge and understanding by gaining real meaning and structure of his/her work. On the contrary restrictive style is characterized by an individual’s preference to take minimalist approach at work reflected in executing a job efficiently without an attempt to understand the real meaning and structure of the work. The analysis suggests that expansive-restrictive style has three dimensions: (1) field dependence-independence (2) cognitive involvement and (3) epistemological beliefs.

Keywords: expansive, knowledge workers, restrictive, style

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13844 Enhancement of Mechanical Properties for Al-Mg-Si Alloy Using Equal Channel Angular Pressing

Authors: W. H. El Garaihy, A. Nassef, S. Samy

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Equal channel angular pressing (ECAP) of commercial Al-Mg-Si alloy was conducted using two strain rates. The ECAP processing was conducted at room temperature and at 250 °C. Route A was adopted up to a total number of four passes in the present work. Structural evolution of the aluminum alloy discs was investigated before and after ECAP processing using optical microscopy (OM). Following ECAP, simple compression tests and Vicker’s hardness were performed. OM micrographs showed that, the average grain size of the as-received Al-Mg-Si disc tends to be larger than the size of the ECAP processed discs. Moreover, significant difference in the grain morphologies of the as-received and processed discs was observed. Intensity of deformation was observed via the alignment of the Al-Mg-Si consolidated particles (grains) in the direction of shear, which increased with increasing the number of passes via ECAP. Increasing the number of passes up to 4 resulted in increasing the grains aspect ratio up to ~5. It was found that the pressing temperature has a significant influence on the microstructure, Hv-values, and compressive strength of the processed discs. Hardness measurements demonstrated that 1-pass resulted in increase of Hv-value by 42% compared to that of the as-received alloy. 4-passes of ECAP processing resulted in additional increase in the Hv-value. A similar trend was observed for the yield and compressive strength. Experimental data of the Hv-values demonstrated that there is a lack of any significant dependence on the processing strain rate.

Keywords: Al-Mg-Si alloy, equal channel angular pressing, grain refinement, severe plastic deformation

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13843 Data Analysis Tool for Predicting Water Scarcity in Industry

Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

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Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

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13842 Dairy Value Chain: Assessing the Inter Linkage of Dairy Farm and Small-Scale Dairy Processing in Tigray: Case Study of Mekelle City

Authors: Weldeabrha Kiros Kidanemaryam, DepaTesfay Kelali Gidey, Yikaalo Welu Kidanemariam

Abstract:

Dairy services are considered as sources of income, employment, nutrition and health for smallholder rural and urban farmers. The main objective of this study is to assess the interlinkage of dairy farms and small-scale dairy processing in Mekelle, Tigray. To achieve the stated objective, a descriptive research approach was employed where data was collected from 45 dairy farmers and 40 small-scale processors and analyzed by calculating the mean values and percentages. Findings show that the dairy business in the study area is characterized by a shortage of feed and water for the farm. The dairy farm is dominated by breeds of hybrid type, followed by the so called ‘begait’. Though the farms have access to medication and vaccination for the cattle, they fell short of hygiene practices, reliable shade for the cattle and separate space for the claves. The value chain at the milk production stage is characterized by a low production rate, selling raw milk without adding value and a very meager traditional processing practice. Furthermore, small-scale milk processors are characterized by collecting milk from farmers and producing cheese, butter, ghee and sour milk. They do not engage in modern milk processing like pasteurized milk, yogurt and table butter. Most small-scale milk processors are engaged in traditional production systems. Additionally, the milk consumption and marketing part of the chain is dominated by the informal market (channel), where market problems, lack of skill and technology, shortage of loans and weak policy support are being faced as the main challenges. Based on the findings, recommendations and future research areas are forwarded.

Keywords: value-chain, dairy, milk production, milk processing

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13841 Functional Neurocognitive Imaging (fNCI): A Diagnostic Tool for Assessing Concussion Neuromarker Abnormalities and Treating Post-Concussion Syndrome in Mild Traumatic Brain Injury Patients

Authors: Parker Murray, Marci Johnson, Tyson S. Burnham, Alina K. Fong, Mark D. Allen, Bruce McIff

Abstract:

Purpose: Pathological dysregulation of Neurovascular Coupling (NVC) caused by mild traumatic brain injury (mTBI) is the predominant source of chronic post-concussion syndrome (PCS) symptomology. fNCI has the ability to localize dysregulation in NVC by measuring blood-oxygen-level-dependent (BOLD) signaling during the performance of fMRI-adapted neuropsychological evaluations. With fNCI, 57 brain areas consistently affected by concussion were identified as PCS neural markers, which were validated on large samples of concussion patients and healthy controls. These neuromarkers provide the basis for a computation of PCS severity which is referred to as the Severity Index Score (SIS). The SIS has proven valuable in making pre-treatment decisions, monitoring treatment efficiency, and assessing long-term stability of outcomes. Methods and Materials: After being scanned while performing various cognitive tasks, 476 concussed patients received an SIS score based on the neural dysregulation of the 57 previously identified brain regions. These scans provide an objective measurement of attentional, subcortical, visual processing, language processing, and executive functioning abilities, which were used as biomarkers for post-concussive neural dysregulation. Initial SIS scores were used to develop individualized therapy incorporating cognitive, occupational, and neuromuscular modalities. These scores were also used to establish pre-treatment benchmarks and measure post-treatment improvement. Results: Changes in SIS were calculated in percent change from pre- to post-treatment. Patients showed a mean improvement of 76.5 percent (σ= 23.3), and 75.7 percent of patients showed at least 60 percent improvement. Longitudinal reassessment of 24 of the patients, measured an average of 7.6 months post-treatment, shows that SIS improvement is maintained and improved, with an average of 90.6 percent improvement from their original scan. Conclusions: fNCI provides a reliable measurement of NVC allowing for identification of concussion pathology. Additionally, fNCI derived SIS scores direct tailored therapy to restore NVC, subsequently resolving chronic PCS resulting from mTBI.

Keywords: concussion, functional magnetic resonance imaging (fMRI), neurovascular coupling (NVC), post-concussion syndrome (PCS)

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13840 Xenografts: Successful Penetrating Keratoplasty Between Two Species

Authors: Francisco Alvarado, Luz Ramírez

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Corneal diseases are one of the main causes of visual impairment and affect almost 4 million, and this study assesses the effects of deep anterior lamellar keratoplasty (DALK) with porcine corneal stroma and postoperative topical treatment with tacrolimus in patients with infectious keratitis. No patient was observed with clinical graft rejection. Among the cases: 2 were positive to fungal culture, 2 with Aspergillus and the other 8 cases were confirmed by bacteriological culture. Corneal diseases are one of the main causes of visual impairment and affect almost 4 million. This study assesses the effects of deep anterior lamellar keratoplasty (DALK) with porcine corneal stroma and postoperative topical treatment with tacrolimus in patients with infectious keratitis. Receiver bed diameters ranged from 7.00 to 9.00 mm. No incidents of Descemet's membrane perforation were observed during surgery. During the follow-up period, no corneal graft splitting, IOP increase, or intolerance to tacrolimus were observed. Deep anterior lamellar keratoplasty seems to be the best option to avoid xenograft rejection, and it could help new surgical techniques in humans.

Keywords: ophthalmology, cornea, corneal transplant, xenografts, surgical innovations

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13839 Algorithm for Information Retrieval Optimization

Authors: Kehinde K. Agbele, Kehinde Daniel Aruleba, Eniafe F. Ayetiran

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When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (

Keywords: information retrieval, document relevance, performance measures, personalization

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13838 How Information Sharing Can Improve Organizational Performance?

Authors: Syed Abdul Rehman Khan

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In today’s world, information sharing plays a vital role in successful operations of supply chain; and boost to the profitability of the organizations (end-to-end supply chains). Many researches have been completed over the role of information sharing in supply chain. In this research article, we will investigate the ‘how information sharing can boost profitability & productivity of the organization; for this purpose, we have developed one conceptual model and check to that model through collected data from companies. We sent questionnaire to 369 companies; and will filled form received from 172 firms and the response rate was almost 47%. For the data analysis, we have used Regression in (SPSS software) In the research findings, our all hypothesis has been accepted significantly and due to the information sharing between suppliers and manufacturers ‘quality of material and timely delivery’ increase and also ‘collaboration & trust’ will become more stronger and these all factors will lead to the company’s profitability directly and in-directly. But unfortunately, companies could not avail the all fruitful benefits of information sharing due to the fear of ‘compromise confidentiality or leakage of information’.

Keywords: collaboration, information sharing, risk factor, timely delivery

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13837 Systematic Literature Review of Therapeutic Use of Autonomous Sensory Meridian Response (ASMR) and Short-Term ASMR Auditory Training Trial

Authors: Christine H. Cubelo

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This study consists of 2-parts: a systematic review of current publications on the therapeutic use of autonomous sensory meridian response (ASMR) and a within-subjects auditory training trial using ASMR videos. The main intent is to explore ASMR as potentially therapeutically beneficial for those with atypical sensory processing. Many hearing-related disorders and mood or anxiety symptoms overlap with symptoms of sensory processing issues. For this reason, inclusion and exclusion criteria of the systematic review were generated in an effort to produce optimal search outcomes and avoid overly confined criteria that would limit yielded results. Criteria for inclusion in the review for Part 1 are (1) adult participants diagnosed with hearing loss or atypical sensory processing, (2) inclusion of measures related to ASMR as a treatment method, and (3) published between 2000 and 2022. A total of 1,088 publications were found in the preliminary search, and a total of 13 articles met the inclusion criteria. A total of 14 participants completed the trial and post-trial questionnaire. Of all responses, 64.29% agreed that the duration of auditory training sessions was reasonable. In addition, 71.43% agreed that the training improved their perception of music. Lastly, 64.29% agreed that the training improved their perception of a primary talker when there are other talkers or background noises present.

Keywords: autonomous sensory meridian response, auditory training, atypical sensory processing, hearing loss, hearing aids

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13836 Robustness of MIMO-OFDM Schemes for Future Digital TV to Carrier Frequency Offset

Authors: D. Sankara Reddy, T. Kranthi Kumar, K. Sreevani

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This paper investigates the impact of carrier frequency offset (CFO) on the performance of different MIMO-OFDM schemes with high spectral efficiency for next generation of terrestrial digital TV. We show that all studied MIMO-OFDM schemes are sensitive to CFO when it is greater than 1% of intercarrier spacing. We show also that the Alamouti scheme is the most sensitive MIMO scheme to CFO.

Keywords: modulation and multiplexing (MIMO-OFDM), signal processing for transmission carrier frequency offset, future digital TV, imaging and signal processing

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13835 Post Mutiny Institutional Buildings of India: A Visual Language of Reconciliation

Authors: Aruna Ramani Grover

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In 1857 the British army in Bengal rose in mutiny. The outcome of a yearlong stifle was the abolition of the East India Company and establishment of Crown rule in 1958. Despite being a political democracy back home, with the declaration of Queen Victoria as Empress of India, the British established themselves as imperialistic successors to the Mughals in India. With the institution of the Crown role in the sub-continent, there was a serious endeavour for systematic governance. This led to infrastructure development and creation of institutions as well. The outcome was many public buildings like courts, railway- stations and headquarters, senates, post offices, banks, libraries, memorial halls, museums, memorials, theatres, government colleges, residential-schools and clock towers. These were built in the old and emerging urban settlements of the sub-continents. In the realm of architecture, like all political masters of the past, the British architects too encountered the living tradition of the sub-continent. A bewildering plethora of buildings in various climatic zones, using local materials and crafted with tools and techniques of the region by local craftsmen had to be understood and assimilated. The19th century British architects who built in India, designed institutional buildings which were functional and responded to the need of the user. In visual terms however, it was a completely different story. Using the manifest elements of the complex and layered indigenous tradition, they fashioned buildings to create an architecture of reconciliation. Treating the traditional architecture as a pattern book, finished buildings was served up to the local population coloured by their understanding of tradition. This paper will discuss a series of building some of which are the Senate House and Law courts at Madras, the Municipal Building and Gateway of India in Bombay, the Muir college in Allahabad, Mayo college Ajmer, the Mubarak Mahal in Jaipur to demonstrate how a visual language of reconciliation was created.

Keywords: infrastructure, British architects, tradition, pattern book, reconciliation

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