Search results for: motion data acquisition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26760

Search results for: motion data acquisition

25230 Single-Cell Visualization with Minimum Volume Embedding

Authors: Zhenqiu Liu

Abstract:

Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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25229 Cloud Data Security Using Map/Reduce Implementation of Secret Sharing Schemes

Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

Abstract:

Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

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25228 Development of an Optimization Method for Myoelectric Signal Processing by Active Matrix Sensing in Robot Rehabilitation

Authors: Noriyoshi Yamauchi, Etsuo Horikawa, Takunori Tsuji

Abstract:

Training by exoskeleton robot is drawing attention as a rehabilitation method for body paralysis seen in many cases, and there are many forms that assist with the myoelectric signal generated by exercise commands from the brain. Rehabilitation requires more frequent training, but it is one of the reasons that the technology is required for the identification of the myoelectric potential derivation site and attachment of the device is preventing the spread of paralysis. In this research, we focus on improving the efficiency of gait training by exoskeleton type robots, improvement of myoelectric acquisition and analysis method using active matrix sensing method, and improvement of walking rehabilitation and walking by optimization of robot control.

Keywords: active matrix sensing, brain machine interface (BMI), the central pattern generator (CPG), myoelectric signal processing, robot rehabilitation

Procedia PDF Downloads 386
25227 The Effects of Dynamic Training Shoes Exercises on Isokinetic Strength Performance

Authors: Bergun Meric Bingul, Yezdan Cinel, Murat Son, Cigdem Bulgan, Mensure Aydin

Abstract:

The aim of this study was to determination of the effects of knee and hip isokinetic performance during the training with the special designed roller-shoes. 30 soccer players participated as subjects and these subjects were divided into 3 groups randomly. Training groups were; with the dynamic training shoes group, without the dynamic training shoes group and control group. Subjects were trained speed strength trainings during 8 weeks (3 days a week and 1 hour a day). 6 exercises were focused on the knee flexors and extensors, also hip adductor and abductor muscles were chosen and performed in 3x30secs at each sets. Control group was not paticipated to the training program. Before and after the training programs knee flexor and extensor muscles and hip abductor and adductor muscles’ peak torques were measured by Biodex III isokinetic dynamometer. Isokinetic strength data were analyzed by using SPSS program. A repeated measures analysis of variance (ANOVA) was used to determine differences among the peak torque values for three groups. The results indicated that soccer players’ peak torque values that the group of using the dynamic training shoes, were found higher. Also, hip adductor and abductor peak torques that the group of using the dynamic training shoes, were obtained better than the other groups. In conclusion, the ground friction forces are an important role of increasing strength. With these shoes, using rollers, soccer players were able to move easily because of the friction forces were reduced and created more range of motion. So, exercises were performed faster than before and strength movements in all angles, it ensured that the active state. This was resulted in a better use of force.

Keywords: isokinetic, soccer, dynamic training shoes, training

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25226 A Model for Analyzing the Startup Dynamics of a Belt Transmission Driven by a DC Motor

Authors: Giovanni Incerti

Abstract:

In this paper the dynamic behavior of a synchronous belt drive during start-up is analyzed and discussed. Besides considering the belt elasticity, the mathematical model here proposed also takes into consideration the electrical behaviour of the DC motor. The solution of the motion equations is obtained by means of the modal analysis in state space, which allows to obtain the decoupling of all equations of the mathematical model without introducing the hypothesis of proportional damping. The mathematical model of the transmission and the solution algorithms have been implemented within a computing software that allows the user to simulate the dynamics of the system and to evaluate the effects due to the elasticity of the belt branches and to the electromagnetic behavior of the DC motor. In order to show the details of the calculation procedure, the paper presents a case study developed with the aid of the abovementioned software.

Keywords: belt drive, vibrations, startup, DC motor

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25225 Thermosalient Effect of an Organic Aminonitrile and its Derivatives

Authors: Lukman O. Alimi, Vincent J. Smith, Leonard J. Barbour

Abstract:

The thermosalient effect is an extremely rare propensity of certain crystalline solids for self-actuation by elastic deformation or a ballistic event1. Thermosalient compounds, colloquially known as ‘jumping crystals’ are promising materials for fabrication of actuators that are also being considered as materials for clean energy conversion because of their capabilities to convert thermal energy into mechanical motion directly. Herein, an organic aminonitrile and its derivatives have been probed by a combination of structural, microscopic and thermoanalytical techniques. Crystals of these compounds were analysed by means of single crystal XRD and hotstage microscopy in the temperature range of 100 to 298 K and found to exhibit the thermosalient effect. We also carried out differential scanning calorimetric analysis at the temperature corresponding to that at which the crystal jumps as observed under a hotstage microscope.

Keywords: aminonitrile, jumping crystal, self actuation, thermosalient effect

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25224 Geometrically Linear Symmetric Free Vibration Analysis of Sandwich Beam

Authors: Ibnorachid Zakaria, El Bikri Khalid, Benamar Rhali, Farah Abdoun

Abstract:

The aim of the present work is to study the linear free symmetric vibration of three-layer sandwich beam using the energy method. The zigzag model is used to describe the displacement field. The theoretical model is based on the top and bottom layers behave like Euler-Bernoulli beams while the core layer like a Timoshenko beam. Based on Hamilton’s principle, the governing equation of motion sandwich beam is obtained in order to calculate the linear frequency parameters for a clamped-clamped and simple supported-simple-supported beams. The effects of material properties and geometric parameters on the natural frequencies are also investigated.

Keywords: linear vibration, sandwich, shear deformation, Timoshenko zig-zag model

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25223 Wh-Movement in Second Language Acquisition: Evidence from Magnitude Estimation

Authors: Dong-Bo Hsu

Abstract:

Universal Grammar (UG) claims that the constraints that are derived from this should operate in language users’ L2 grammars. This study investigated this hypothesis on knowledge of Subjacency and resumptive pronoun usage among Chinese learners of English. Chinese fulfills two requirements to examine the existence of UG, i.e., Subjacency does not operate in Chinese and resumptive pronouns in English are very different from those in Chinese and second L2 input undermines the knowledge of Subjacency. The results indicated that Chinese learners of English demonstrated a nearly identical pattern as English native speakers do but the resumptive pronoun in the embedding clauses. This may be explained in terms of the case that Chinese speakers’ usage of pronouns is not influenced by the number of embedding clauses. Chinese learners of English have full access to knowledge endowed by UG but their processing of English sentences may be different from native speakers as a general slow rate for processing in their L2 English.

Keywords: universal grammar, Chinese, English, wh-questions, resumption

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25222 An Ergonomic Handle Design for Instruments in Laparoscopic Surgery

Authors: Ramon Sancibrian, Carlos Redondo-Figuero, Maria C. Gutierrez-Diez, Esther G. Sarabia, Maria A. Benito-Gonzalez, Jose C. Manuel-Palazuelos

Abstract:

In this paper, the design and evaluation of a handle for laparoscopic surgery is presented. The design of the handle is based on ergonomic principles and tries to avoid awkward postures for surgeons. The handle combines the so-called power-grip and accurate-grip in order to provide strength and accuracy in the performance of surgery. The handle is tested using both objective and subjective approaches. The objective approach uses motion capture techniques to obtain the angles of forearm, arm, wrist and hand. The muscular effort is obtained with electromyography electrodes. On the other hand, a subjective survey has been carried out using questionnaires. Results confirm that the handle is preferred by the majority of the surgeons.

Keywords: laparoscopic surgery, ergonomics, mechanical design, biomechanics

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25221 A Modular Framework for Enabling Analysis for Educators with Different Levels of Data Mining Skills

Authors: Kyle De Freitas, Margaret Bernard

Abstract:

Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

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25220 Using Audit Tools to Maintain Data Quality for ACC/NCDR PCI Registry Abstraction

Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

Abstract:

Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

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25219 Artificial Intelligence Based Comparative Analysis for Supplier Selection in Multi-Echelon Automotive Supply Chains via GEP and ANN Models

Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

Abstract:

Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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25218 Electronically Controlled Motorized Steering System (E-Mo Steer)

Authors: M. Prasanth, V. Nithin, R. Keerthana, S.Kalyani

Abstract:

In the current scenario, the steering system in automobiles is such that the motion from the steering wheel is transferred to driving wheel by mechanical linkages. In this paper, we propose a method to design a steering mechanism using servomotors to turn the wheels instead of linkages. In this method, a steering angle sensor senses the turn angle of the steering wheel and its output is processed by an electronical control module. Then the ECM compares the angle value to that of a standard value from a look-up database. Then it gives the appropriate input power and the turning duration to the motors. Correspondingly, the motors turn the wheels by means of bevel gears welded to both the motor output shafts and the wheel hubs. Thus, the wheels are turned without the complicated framework of linkages, reducing the driver’s effort and fatigue considerably.

Keywords: electronic control unit, linkage-less steering, servomotors, E-Mo Steer

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25217 Nanomechanical Characterization of Healthy and Tumor Lung Tissues at Cell and Extracellular Matrix Level

Authors: Valeria Panzetta, Ida Musella, Sabato Fusco, Paolo Antonio Netti

Abstract:

The study of the biophysics of living cells drew attention to the pivotal role of the cytoskeleton in many cell functions, such as mechanics, adhesion, proliferation, migration, differentiation and neoplastic transformation. In particular, during the complex process of malignant transformation and invasion cell cytoskeleton devolves from a rigid and organized structure to a more compliant state, which confers to the cancer cells a great ability to migrate and adapt to the extracellular environment. In order to better understand the malignant transformation process from a mechanical point of view, it is necessary to evaluate the direct crosstalk between the cells and their surrounding extracellular matrix (ECM) in a context which is close to in vivo conditions. In this study, human biopsy tissues of lung adenocarcinoma were analyzed in order to define their mechanical phenotype at cell and ECM level, by using particle tracking microrheology (PTM) technique. Polystyrene beads (500 nm) were introduced into the sample slice. The motion of beads was obtained by tracking their displacements across cell cytoskeleton and ECM structures and mean squared displacements (MSDs) were calculated from bead trajectories. It has been already demonstrated that the amplitude of MSD is inversely related to the mechanical properties of intracellular and extracellular microenvironment. For this reason, MSDs of particles introduced in cytoplasm and ECM of healthy and tumor tissues were compared. PTM analyses showed that cancerous transformation compromises mechanical integrity of cells and extracellular matrix. In particular, the MSD amplitudes in cells of adenocarcinoma were greater as compared to cells of normal tissues. The increased motion is probably associated to a less structured cytoskeleton and consequently to an increase of deformability of cells. Further, cancer transformation is also accompanied by extracellular matrix stiffening, as confirmed by the decrease of MSDs of matrix in tumor tissue, a process that promotes tumor proliferation and invasiveness, by activating typical oncogenic signaling pathways. In addition, a clear correlation between MSDs of cells and tumor grade was found. MSDs increase when tumor grade passes from 2 to 3, indicating that cells undergo to a trans-differentiation process during tumor progression. ECM stiffening is not dependent on tumor grade, but the tumor stage resulted to be strictly correlated with both cells and ECM mechanical properties. In fact, a greater stage is assigned to tumor spread to regional lymph nodes and characterized by an up-regulation of different ECM proteins, such as collagen I fibers. These results indicate that PTM can be used to get nanomechanical characterization at different scale levels in an interpretative and diagnostic context.

Keywords: cytoskeleton, extracellular matrix, mechanical properties, particle tracking microrheology, tumor

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25216 Energy Management Techniques in Mobile Robots

Authors: G. Gurguze, I. Turkoglu

Abstract:

Today, the developing features of technological tools with limited energy resources have made it necessary to use energy efficiently. Energy management techniques have emerged for this purpose. As with every field, energy management is vital for robots that are being used in many areas from industry to daily life and that are thought to take up more spaces in the future. Particularly, effective power management in autonomous and multi robots, which are getting more complicated and increasing day by day, will improve the performance and success. In this study, robot management algorithms, usage of renewable and hybrid energy sources, robot motion patterns, robot designs, sharing strategies of workloads in multiple robots, road and mission planning algorithms are discussed for efficient use of energy resources by mobile robots. These techniques have been evaluated in terms of efficient use of existing energy resources and energy management in robots.

Keywords: energy management, mobile robot, robot administration, robot management, robot planning

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25215 Effects of Array Electrode Placement on Identifying Localised Muscle Fatigue

Authors: Mohamed R. Al-Mulla, Bader Al-Bader, Firouz K. Ghaaedi, Francisco Sepulveda

Abstract:

Surface electromyography (sEMG) is utilised in numerous studies on muscle activity. In the beginning, single electrodes were utilised; however, the newest approach is to use an array of electrodes or a grid of electrodes to improve the accuracy of the recorded reading. This research focuses on electrode placement on the biceps brachii, using an array of electrodes placed longitudinal and diagonally on the muscle belly. Trials were conducted on four healthy males, with sEMG signal acquisition from fatiguing isometric contractions. The signal was analysed using the power spectrum density. The separation between the two classes of fatigue (non-fatigue and fatigue) was calculated using the Davies-Bouldin Index (DBI). Results show that higher separability between the fatigue content of the sEMG signal when placed longitudinally, in the same direction as the muscle fibers.

Keywords: array electrodes, biceps brachii, electrode placement, EMG, isometric contractions, muscle fatigue

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25214 AI-Driven Solutions for Optimizing Master Data Management

Authors: Srinivas Vangari

Abstract:

In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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25213 Genetic Data of Deceased People: Solving the Gordian Knot

Authors: Inigo de Miguel Beriain

Abstract:

Genetic data of deceased persons are of great interest for both biomedical research and clinical use. This is due to several reasons. On the one hand, many of our diseases have a genetic component; on the other hand, we share genes with a good part of our biological family. Therefore, it would be possible to improve our response considerably to these pathologies if we could use these data. Unfortunately, at the present moment, the status of data on the deceased is far from being satisfactorily resolved by the EU data protection regulation. Indeed, the General Data Protection Regulation has explicitly excluded these data from the category of personal data. This decision has given rise to a fragmented legal framework on this issue. Consequently, each EU member state offers very different solutions. For instance, Denmark considers the data as personal data of the deceased person for a set period of time while some others, such as Spain, do not consider this data as such, but have introduced some specifically focused regulations on this type of data and their access by relatives. This is an extremely dysfunctional scenario from multiple angles, not least of which is scientific cooperation at the EU level. This contribution attempts to outline a solution to this dilemma through an alternative proposal. Its main hypothesis is that, in reality, health data are, in a sense, a rara avis within data in general because they do not refer to one person but to several. Hence, it is possible to think that all of them can be considered data subjects (although not all of them can exercise the corresponding rights in the same way). When the person from whom the data were obtained dies, the data remain as personal data of his or her biological relatives. Hence, the general regime provided for in the GDPR may apply to them. As these are personal data, we could go back to thinking in terms of a general prohibition of data processing, with the exceptions provided for in Article 9.2 and on the legal bases included in Article 6. This may be complicated in practice, given that, since we are dealing with data that refer to several data subjects, it may be complex to refer to some of these bases, such as consent. Furthermore, there are theoretical arguments that may oppose this hypothesis. In this contribution, it is shown, however, that none of these objections is of sufficient substance to delegitimize the argument exposed. Therefore, the conclusion of this contribution is that we can indeed build a general framework on the processing of personal data of deceased persons in the context of the GDPR. This would constitute a considerable improvement over the current regulatory framework, although it is true that some clarifications will be necessary for its practical application.

Keywords: collective data conceptual issues, data from deceased people, genetic data protection issues, GDPR and deceased people

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25212 Neurological Complications of HIV/AIDS: Case of Meningitis Caused by Cryptococcus neoformans and Tuberculous Meningitis

Authors: Ndarusanze Berchmans

Abstract:

This research work focused on the analysis of the observations of tuberculous meningitis in HIV-positive patients who were treated by the Prince Regent Charles Hospital in Bujumbura. A number of 246 seropositive patients were examined by the laboratory of Prince Regent Charles in the period between 2010 and 2015. We did a retrospective study; we used data from the registers of the laboratories mentioned above; the objective was to approach the epidemiological, biological, clinical, and therapeutic characteristics of tuberculosis meningitis infection: 124 women (50.40% of AIDS patients) and 122 men (49.59% of AIDS patients) were subject to the diagnosis by identification of cerebrospinal fluid (CSF). The average age of the patients was 30 years for this period. The population at risk has an average age of between 34 and 42 years for the years between 2010-2015. From 2010 to 2012, cases of opportunistic diseases (e.g., tuberculous meningitis and Cryptococcus neoformans meningitis), often found in immunocompromised, were observed at a high rate; in this period, there was a disturbance of the rhythm providing antiretroviral drugs to people with AIDS. The rate of the two meningitis (tuberculous meningitis and Cryptococcus neoformans meningitis) remained above 10% to gradually decrease until 2015, with the gradual return of antiretrovirals. This period records an overall average of 25 cases of tuberculous meningitis, or a percentage of 10.16%. For the year 2015, there were 4 cases of tuberculous meningitis out of a total of 35 seropositive examined (11.42%). This year's percentage shows that the number of tuberculous meningitis cases has fallen from the rate in previous years. This is the result of the care given by associations against HIV/AIDS to HIV-positive people. This decrease in cases of tuberculous meningitis is due to the acquisition of antiretrovirals by all HIV-positive people treated by hospitals. For the moment, these hospitals are taking care of many AIDS patients by providing them permanently with antiretrovirals; Besides that, there are many patients who are supported by associations whose activities are directed against HIV/AIDS.

Keywords: Cryptococcus neoformans meningitis, tuberculosis meningitis, neurological complications, epidemiology of meningitis

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25211 Teacher Knowledge: Unbridling Teacher Agency in the Context of Professional Development for Transformative Teaching and Learning

Authors: Bernice Badal

Abstract:

This article addresses a persistent challenge related to teacher agency in knowledge acquisition in professional development (PD) workshops in contexts of educational change, given that scholarship identifies a need for more teacher involvement and amplification of teacher's voices. Theoretical concepts are drawn from Bandura’s Social cognitive theory, incorporating the triadic causation model of agency to examine the reciprocal nature of the context, teacher characteristics, and systemic influences that shape how knowledge is transmitted and acquired in PD workshops. This qualitative study, using a mix of classroom observations and interviews, explored the political, contextual, and personal characteristics of teacher agency in PD through an analysis of data extracted from a PhD study. The narratives of six teachers from three township schools are examined to show how PD efforts in South Africa have failed to take account of the holistic development of teacher agency in knowledge dissemination and how this shapes teacher self-efficacy beliefs about being able to masterfully apply the tenets of the reform. Agency, teacher voice, and contextual considerations were used as markers of the quality of the training provided to understand how knowledge is acquired and meaning is made. The findings suggest that systemic influences of institutionally imposed PD offer partial understandings of the reform, which is offered in traditional formats that do not consider teacher empowerment in knowledge production and the development of teacher agency. Common in all the participants’ responses is the need for more information and training on the prescribed approach for teaching English as a second language; however, this paper holds the view that more information may not solve teachers’ dilemmas. Accordingly, it recommends a restructuring of the programme with facilitators being more cognisant of teacher agency for the development of transformative teachers. The findings of the study contribute to the field of teacher knowledge, teacher training, and professional development in the context of educational reforms.

Keywords: teacher professional development, teacher voice, teacher agency, educational reforms, teacher knowledge

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25210 Steps towards the Development of National Health Data Standards in Developing Countries

Authors: Abdullah I. Alkraiji, Thomas W. Jackson, Ian Murray

Abstract:

The proliferation of health data standards today is somewhat overlapping and conflicting, resulting in market confusion and leading to increasing proprietary interests. The government role and support in standardization for health data are thought to be crucial in order to establish credible standards for the next decade, to maximize interoperability across the health sector, and to decrease the risks associated with the implementation of non-standard systems. The normative literature missed out the exploration of the different steps required to be undertaken by the government towards the development of national health data standards. Based on the lessons learned from a qualitative study investigating the different issues to the adoption of health data standards in the major tertiary hospitals in Saudi Arabia and the opinions and feedback from different experts in the areas of data exchange and standards and medical informatics in Saudi Arabia and UK, a list of steps required towards the development of national health data standards was constructed. Main steps are the existence of: a national formal reference for health data standards, an agreed national strategic direction for medical data exchange, a national medical information management plan and a national accreditation body, and more important is the change management at the national and organizational level. The outcome of this study can be used by academics and practitioners to develop the planning of health data standards, and in particular those in developing countries.

Keywords: interoperabilty, medical data exchange, health data standards, case study, Saudi Arabia

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25209 Child-Friendly Digital Storytelling to Promote Young Learners' Critical Thinking in English Learning

Authors: Setyarini Sri, Nursalim Agus

Abstract:

Integrating critical thinking and digital based learning is one of demands in teaching English in 21st century. Child-friendly digital storytelling (CFDS) is an innovative learning model to promote young learners’ critical thinking. Therefore, this study aims to (1) investigate how child-friendly digital storytelling is implemented to promote young learners’ critical thinking in speaking English; (2) find out the benefits gained by the students in their learning based on CFDS. Classroom Action Research (CAR) took place in two cycles in which each of the cycle covered four phases namely: Planning, Acting, Observing, and Evaluating. Three classes of seventh graders were selected as the subjects of this study. Data were collected through observation, interview with some selected students as respondents, and document analysis in the form individual recorded storytelling. Sentences, phrases, words found in the transcribed data were identified and categorized based on Bloom taxonomy. The findings from the first cycle showed that the students seemed to speak critically that can be seen from the way they understood the story and related the story to their real life. Meanwhile, the result investigated from the second cycle likely indicated their higher level of critical thinking since the students spoke in English critically through comparing, questioning, analyzing, and evaluating the story by giving arguments, opinions, and comments. Such higher levels of critical thinking were also found in the students’ final project of individual recorded digital story. It is elaborated from the students’ statements in the interview who claimed CFDS offered opportunity to the students to promote their critical thinking because they comprehended the story deeply as they experienced in their real life. This learning model created good learning atmosphere and engaged the students directly so that they looked confident to retell the story in various perspectives. In term of the benefits of child-friendly digital storytelling, the students found it beneficial for some enjoyable classroom activities through watching beautiful and colorful pictures, listening to clear and good sounds, appealing moving motion and emotionally they were involved in that story. In the interview, the students also stated that child-friendly digital storytelling eased them to understand the meaning of the story as they were motivated and enthusiastic to speak in English critically.

Keywords: critical thinking, child-friendly digital storytelling, English speaking, promoting, young learners

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25208 A Design System for Complex Profiles of Machine Members Using a Synthetic Curve

Authors: N. Sateesh, C. S. P. Rao, K. Satyanarayana, C. Rajashekar

Abstract:

This paper proposes a development of a CAD/CAM system for complex profiles of various machine members using a synthetic curve i.e. B-spline. Conventional methods in designing and manufacturing of complex profiles are tedious and time consuming. Even programming those on a computer numerical control (CNC) machine can be a difficult job because of the complexity of the profiles. The system developed provides graphical and numerical representation B-spline profile for any given input. In this paper, the system is applicable to represent a cam profile with B-spline and attempt is made to improve the follower motion.

Keywords: plate-cams, cam profile, b-spline, computer numerical control (CNC), computer aided design and computer aided manufacturing (CAD/CAM), R-D-R-D (rise-dwell-return-dwell)

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25207 Agile Methodology for Modeling and Design of Data Warehouses -AM4DW-

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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25206 X-Ray and DFT Electrostatics Parameters Determination of a Coumarin Derivative Compound C17H13NO3

Authors: Y. Megrous, A. Chouaih, F. Hamzaoui

Abstract:

The crystal structure of 4-Methyl-7-(salicylideneamino)coumarin C17H13NO3has been determined using X-ray diffraction to establish the configuration and stereochemistry of the molecule. This crystal is characterized by its nolinear activity. The molecular electron charge density distribution of the title compound is described accurately using the multipolar model of Hansen and Coppens. The net atomic charge and the molecular dipole moment in-crystal have been determined in order to understand the nature of inter-and intramolecular charge transfer. The study present the thermal motion and the structural analysis obtained from the least-square refinement on F2,this study has also allowed us to determine the electrostatic potential and therefore locate the electropositive part and the electronegative part in molecular scale of the title compound.

Keywords: electron charge density, net atomic charge, molecular dipole moment, X-ray diffraction

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25205 Identifying Model to Predict Deterioration of Water Mains Using Robust Analysis

Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

Abstract:

In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

Procedia PDF Downloads 744
25204 Automated Testing to Detect Instance Data Loss in Android Applications

Authors: Anusha Konduru, Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

Abstract:

Mobile applications are increasing in a significant amount, each to address the requirements of many users. However, the quick developments and enhancements are resulting in many underlying defects. Android apps create and handle a large variety of 'instance' data that has to persist across runs, such as the current navigation route, workout results, antivirus settings, or game state. Due to the nature of Android, an app can be paused, sent into the background, or killed at any time. If the instance data is not saved and restored between runs, in addition to data loss, partially-saved or corrupted data can crash the app upon resume or restart. However, it is difficult for the programmer to manually test this issue for all the activities. This results in the issue of data loss that the data entered by the user are not saved when there is any interruption. This issue can degrade user experience because the user needs to reenter the information each time there is an interruption. Automated testing to detect such data loss is important to improve the user experience. This research proposes a tool, DroidDL, a data loss detector for Android, which detects the instance data loss from a given android application. We have tested 395 applications and found 12 applications with the issue of data loss. This approach is proved highly accurate and reliable to find the apps with this defect, which can be used by android developers to avoid such errors.

Keywords: Android, automated testing, activity, data loss

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25203 Developing Confidence of Visual Literacy through Using MIRO during Online Learning

Authors: Rachel S. E. Lim, Winnie L. C. Tan

Abstract:

Visual literacy is about making meaning through the interaction of images, words, and sounds. Graphic communication students typically develop visual literacy through critique and production of studio-based projects for their portfolios. However, the abrupt switch to online learning during the COVID-19 pandemic has made it necessary to consider new strategies of visualization and planning to scaffold teaching and learning. This study, therefore, investigated how MIRO, a cloud-based visual collaboration platform, could be used to develop the visual literacy confidence of 30 diploma in graphic communication students attending a graphic design course at a Singapore arts institution. Due to COVID-19, the course was taught fully online throughout a 16-week semester. Guided by Kolb’s Experiential Learning Cycle, the two lecturers developed students’ engagement with visual literacy concepts through different activities that facilitated concrete experiences, reflective observation, abstract conceptualization, and active experimentation. Throughout the semester, students create, collaborate, and centralize communication in MIRO with infinite canvas, smart frameworks, a robust set of widgets (i.e., sticky notes, freeform pen, shapes, arrows, smart drawing, emoticons, etc.), and powerful platform capabilities that enable asynchronous and synchronous feedback and interaction. Students then drew upon these multimodal experiences to brainstorm, research, and develop their motion design project. A survey was used to examine students’ perceptions of engagement (E), confidence (C), learning strategies (LS). Using multiple regression, it¬ was found that the use of MIRO helped students develop confidence (C) with visual literacy, which predicted performance score (PS) that was measured against their application of visual literacy to the creation of their motion design project. While students’ learning strategies (LS) with MIRO did not directly predict confidence (C) or performance score (PS), it fostered positive perceptions of engagement (E) which in turn predicted confidence (C). Content analysis of students’ open-ended survey responses about their learning strategies (LS) showed that MIRO provides organization and structure in documenting learning progress, in tandem with establishing standards and expectations as a preparatory ground for generating feedback. With the clarity and sequence of the mentioned conditions set in place, these prerequisites then lead to the next level of personal action for self-reflection, self-directed learning, and time management. The study results show that the affordances of MIRO can develop visual literacy and make up for the potential pitfalls of student isolation, communication, and engagement during online learning. The context of how MIRO could be used by lecturers to orientate students for learning in visual literacy and studio-based projects for future development are discussed.

Keywords: design education, graphic communication, online learning, visual literacy

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25202 Big Data: Appearance and Disappearance

Authors: James Moir

Abstract:

The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

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25201 From Data Processing to Experimental Design and Back Again: A Parameter Identification Problem Based on FRAP Images

Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

Abstract:

FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

Procedia PDF Downloads 278