Search results for: classification system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19010

Search results for: classification system

18170 A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments

Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

Abstract:

In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.

Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction

Procedia PDF Downloads 509
18169 The Design and Construction of the PV-Wind Autonomous System for Greenhouse Plantations in Central Thailand

Authors: Napat Watjanatepin, Wikorn Wong-Satiean

Abstract:

The objective of this research is to design and construct the PV-Wind hybrid autonomous system for the greenhouse plantation, and analyze the technical performance of the PV-Wind energy system. This design depends on the water consumption in the greenhouse by using 24 of the fogging mist each with the capability of 24 liter/min. The operating time is 4 times per day, each round for 15 min. The fogging system is being driven by water pump with AC motor rating 0.5 hp. The load energy consumed is around 1.125 kWh/d. The designing results of the PV-Wind hybrid energy system is that sufficient energy could be generated by this system. The results of this study can be applied as a technical data reference for other areas in the central part of Thailand.

Keywords: PV-Wind hybrid autonomous system, greenhouse plantation, fogging system, central part of Thailand

Procedia PDF Downloads 307
18168 Assessing Online Learning Paths in an Learning Management Systems Using a Data Mining and Machine Learning Approach

Authors: Alvaro Figueira, Bruno Cabral

Abstract:

Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

Procedia PDF Downloads 120
18167 A Development of a Weight-Balancing Control System Based On Android Operating System

Authors: Rattanathip Rattanachai, Piyachai Petchyen, Kunyanuth Kularbphettong

Abstract:

This paper describes the development of a Weight- Balancing Control System based on the Android Operating System and it provides recommendations on ways of balancing of user’s weight based on daily metabolism process and need so that user can make informed decisions on his or her weight controls. The system also depicts more information on nutrition details. Furthermore, it was designed to suggest to users what kinds of foods they should eat and how to exercise in the right ways. We describe the design methods and functional components of this prototype. To evaluate the system performance, questionnaires for system usability and Black Box Testing were used to measure expert and user satisfaction. The results were satisfactory as followed: Means for experts and users were 3.94 and 4.07 respectively.

Keywords: weight-balancing control, Android operating system, daily metabolism, black box testing

Procedia PDF Downloads 469
18166 Simulation and Analysis of Different Parameters in Hydraulic Circuit Due to Leakage

Authors: J.Das, Gyan Wrat

Abstract:

Leakage is the main gradual failure in the fluid power system, which is usually caused by the impurity in the oil and wear of matching surfaces between parts and lead to the change of the gap value. When leakage occurs in the system, the oil will flow from the high pressure chamber into the low pressure chamber through the gap, causing the reduction of system flow as well as the loss of system pressure, resulting in the decreasing of system efficiency. In the fluid power system, internal leakage may occur in various components such as gear pump, reversing valve and hydraulic cylinder, and affect the system work performance. Therefore, component leakage in the fluid power system is selected as the study to characterize the leakage and the effect of leakage on the system. Effect of leakage on system pressure and cylinder displacement can be obtained using pressure sensors and the displacement sensor. The leakage can be varied by changing the orifice using a flow control valve. Hydraulic circuit for leakage will be developed in Matlab/Simulink environment and simulations will be done by changing different parameters.

Keywords: leakage causes, effect, analysis, MATLAB simulation, hydraulic circuit

Procedia PDF Downloads 395
18165 An Ensemble Deep Learning Architecture for Imbalanced Classification of Thoracic Surgery Patients

Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

Abstract:

Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

Procedia PDF Downloads 139
18164 The Management Information System for Convenience Stores: Case Study in 7 Eleven Shop in Bangkok

Authors: Supattra Kanchanopast

Abstract:

The purpose of this research is to develop and design a management information system for 7 eleven shop in Bangkok. The system was designed and developed to meet users’ requirements via the internet network by use of application software such as My SQL for database management, Apache HTTP Server for Web Server and PHP Hypertext Preprocessor for an interface between web server, database and users. The system was designed into two subsystems as the main system, or system for head office, and the branch system for branch shops. These consisted of three parts which are classified by user management as shop management, inventory management and Point of Sale (POS) management. The implementation of the MIS for the mini-mart shop, can lessen the amount of paperwork and reduce repeating tasks so it may decrease the capital of the business and support an extension of branches in the future as well.

Keywords: convenience store, the management information system, inventory management, 7 eleven shop

Procedia PDF Downloads 472
18163 GSM Based Smart Patient Monitoring System

Authors: Ayman M. Mansour

Abstract:

In this paper, we propose an intelligent system that is used for monitoring the health conditions of Patients. Monitoring the health condition of Patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will Improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to Faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The propose system will provide an intelligent system that will generate initial diagnosing to the patient case. This will assist and advice clinicians at the point of care. The decision is based on demographic data and laboratory test results of patient data. Using such system with the ability of making medical decisions, the quality of medical care in Jordan and specifically in Tafial is expected to be improved. This will provide more accurate, effective, and reliable diagnoses and treatments especially if the physicians have insufficient knowledge.

Keywords: GSM, SMS, patient, monitoring system, fuzzy logic, multi-agent system

Procedia PDF Downloads 563
18162 Role of Water Supply in the Functioning of the MLDB Systems

Authors: Ramanpreet Kaur, Upasana Sharma

Abstract:

The purpose of this paper is to address the challenges faced by MLDB system at the piston foundry plant due to interruption in supply of water. For the MLDB system to work in Model, two sub-units must be connected to the robotic main unit. The system cannot function without robotics and water supply by the fan (WSF). Insufficient water supply is the cause of system failure. The system operates at top performance using two sub-units. If one sub-unit fails, the system capacity is reduced. Priority of repair is given to the main unit i.e. Robotic and WSF. To solve the problem, semi-Markov process and regenerative point technique are used. Relevant graphs are also included to particular case.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

Procedia PDF Downloads 72
18161 Automated Marker Filling System

Authors: Pinisetti Swami Sairam, Meera C. S.

Abstract:

Marker pens are widely used all over the world, mainly in educational institutions due to their neat, accurate and easily erasable nature. But refilling the ink in these pens is a tedious and time consuming job. Besides, it requires careful handling of the pens and ink bottle. A fully automated marker filling system is a solution developed to overcome this problem. The system comprises of pneumatics and electronics modules as well as PLC control. The system design is done in such a way that the empty markers are dumped in a marker container which then sent through different modules of the system in order to refill it automatically. The filled markers are then collected in a marker container. Refilling of ink takes place in different stages inside the system. An ink detecting system detects the colour of the marker which is to be filled and then refilling is done. The processes like capping and uncapping of the cap as well as screwing and unscrewing of the tip are done with the help of robotic arm and gripper. We make use of pneumatics in this system in order to get the precision while performing the capping, screwing, and refilling operations. Thus with the help of this system we can achieve cleanliness, accuracy, effective and time saving in the process of filling a marker.

Keywords: automated system, market filling, information technology, control and automation

Procedia PDF Downloads 492
18160 Analysis of Big Data on Leisure Activities and Depression for the Disabled

Authors: Hee-Jung Seo, Yunjung Lee, Areum Han, Heeyoung Park, Se-Hyuk Park

Abstract:

The purpose of this study was to analyze the relationship between happiness and depression among people with disabilities and to analyze the social phenomenon of leisure activities among them to promote physical and leisure activities for people with disabilities. The research methods included analyzing differences in happiness according to depression classification. A total of 281 people with disabilities were analyzed using SPSS WIN Ver. 29.0. In addition, the SumTrend platform was used to analyze terms related to 'leisure activities for the disabled.' The findings can be summarized into two main points: First, there were significant differences in happiness according to depression classification. Second, there were 20 mentions before COVID-19, 34 mentions after COVID-19, and currently 43 mentions, with high positive rates observed in each period. Based on these results, the following conclusions were drawn: First, measures for people with disabilities include strengthening online resources and services, social distancing response policies, improving accessibility, and providing support and financial assistance. Second, measures for non-disabled individuals emphasize the need for education and information provision, promoting dialogue and interaction, ensuring accessibility, and promoting inclusive cultural awareness and attitude change.

Keywords: leisure activities, individuals with disabilities, COVID-19 pandemic, depression

Procedia PDF Downloads 45
18159 Proteomic Analysis of Excretory Secretory Antigen (ESA) from Entamoeba histolytica HM1: IMSS

Authors: N. Othman, J. Ujang, M. N. Ismail, R. Noordin, B. H. Lim

Abstract:

Amoebiasis is caused by the Entamoeba histolytica and still endemic in many parts of the tropical region, worldwide. Currently, there is no available vaccine against amoebiasis. Hence, there is an urgent need to develop a vaccine. The excretory secretory antigen (ESA) of E. histolytica is a suitable biomarker for the vaccine candidate since it can modulate the host immune response. Hence, the objective of this study is to identify the proteome of the ESA towards finding suitable biomarker for the vaccine candidate. The non-gel based and gel-based proteomics analyses were performed to identify proteins. Two kinds of mass spectrometry with different ionization systems were utilized i.e. LC-MS/MS (ESI) and MALDI-TOF/TOF. Then, the functional proteins classification analysis was performed using PANTHER software. Combination of the LC -MS/MS for the non-gel based and MALDI-TOF/TOF for the gel-based approaches identified a total of 273 proteins from the ESA. Both systems identified 29 similar proteins whereby 239 and 5 more proteins were identified by LC-MS/MS and MALDI-TOF/TOF, respectively. Functional classification analysis showed the majority of proteins involved in the metabolic process (24%), primary metabolic process (19%) and protein metabolic process (10%). Thus, this study has revealed the proteome the E. histolytica ESA and the identified proteins merit further investigations as a vaccine candidate.

Keywords: E. histolytica, ESA, proteomics, biomarker

Procedia PDF Downloads 338
18158 Contribution to Energy Management in Hybrid Energy Systems Based on Agents Coordination

Authors: Djamel Saba, Fatima Zohra Laallam, Brahim Berbaoui

Abstract:

This paper presents a contribution to the design of a multi-agent for the energy management system in a hybrid energy system (SEH). The multi-agent-based energy-coordination management system (MA-ECMS) is based mainly on coordination between agents. The agents share the tasks and exchange information through communications protocols to achieve the main goal. This intelligent system can fully manage the consumption and production or simply to make proposals for action he thinks is best. The initial step is to give a presentation for the system that we want to model in order to understand all the details as much as possible. In our case, it is to implement a system for simulating a process control of energy management.

Keywords: communications protocols, control process, energy management, hybrid energy system, modelization, multi-agents system, simulation

Procedia PDF Downloads 328
18157 BIM-Based Tool for Sustainability Assessment and Certification Documents Provision

Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

Abstract:

The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

Procedia PDF Downloads 322
18156 The Framework of System Safety for Multi Human-in-The-Loop System

Authors: Hideyuki Shintani, Ichiro Koshijima

Abstract:

In Cyber Physical System (CPS), if there are a large number of persons in the process, a role of person in CPS might be different comparing with the one-man system. It is also necessary to consider how Human-in-The-Loop Cyber Physical Systems (HiTLCPS) ensure safety of each person in the loop process. In this paper, the authors discuss a system safety framework with an illustrative example with STAMP model to clarify what point for safety should be considered and what role of person in the should have.

Keywords: cyber-physical-system, human-in-the-loop, safety, STAMP model

Procedia PDF Downloads 319
18155 Study and Experimental Analysis of a Photovoltaic Pumping System under Three Operating Modes

Authors: Rekioua D., Mohammedi A., Rekioua T., Mehleb Z.

Abstract:

Photovoltaic water pumping systems is considered as one of the most promising areas in photovoltaic applications, the economy and reliability of solar electric power made it an excellent choice for remote water pumping. Two conventional techniques are currently in use; the first is the directly coupled technique and the second is the battery buffered photovoltaic pumping system. In this paper, we present different performances of a three operation modes of photovoltaic pumping system. The aim of this work is to determine the effect of different parameters influencing the photovoltaic pumping system performances, such as pumping head, System configuration and climatic conditions. The obtained results are presented and discussed.

Keywords: batteries charge mode, photovoltaic pumping system, pumping head, submersible pump

Procedia PDF Downloads 504
18154 Emotion Classification Using Recurrent Neural Network and Scalable Pattern Mining

Authors: Jaishree Ranganathan, MuthuPriya Shanmugakani Velsamy, Shamika Kulkarni, Angelina Tzacheva

Abstract:

Emotions play an important role in everyday life. An-alyzing these emotions or feelings from social media platforms like Twitter, Facebook, blogs, and forums based on user comments and reviews plays an important role in various factors. Some of them include brand monitoring, marketing strategies, reputation, and competitor analysis. The opinions or sentiments mined from such data helps understand the current state of the user. It does not directly provide intuitive insights on what actions to be taken to benefit the end user or business. Actionable Pattern Mining method provides suggestions or actionable recommendations on what changes or actions need to be taken in order to benefit the end user. In this paper, we propose automatic classification of emotions in Twitter data using Recurrent Neural Network - Gated Recurrent Unit. We achieve training accuracy of 87.58% and validation accuracy of 86.16%. Also, we extract action rules with respect to the user emotion that helps to provide actionable suggestion.

Keywords: emotion mining, twitter, recurrent neural network, gated recurrent unit, actionable pattern mining

Procedia PDF Downloads 164
18153 Microwave Security System in Museums: Design and Implementation

Authors: Dalia Elsheakh, Hala Elsadek

Abstract:

The objective of this paper is to propose a competitive microwave security system that can be applied with reasonable price at museums in Egypt, considering the priceless elements in 23 Egyptian museums countrywide and the lack of good recent security systems even in big ones. The system main goal is to detect valuable targets to ensure their presence in the pre-defined positions in order to protect them from being stolen. The system is based on real time microwave scanning for the required space volume through transmitting RF waves at consecutive angles and detecting the back scattered waves from required objects to detect their existence at pre-specified locations.

Keywords: microwave security system, object locating system, real time locating system (RTLS), antenna array, array electronic scanning

Procedia PDF Downloads 343
18152 Dynamical Systems and Fibonacci Numbers

Authors: Vandana N. Purav

Abstract:

The Dynamical systems concept is a mathematical formalization for any fixed rule that describes the time dependence of a points position in its ambient space. e.g. pendulum of a clock, the number of fish each spring in a lake, the number of rabbits spring in an enclosure, etc. The Dynamical system theory used to describe the complex nature that is dynamical systems with differential equations called continuous dynamical system or dynamical system with difference equations called discrete dynamical system. The concept of dynamical system has its origin in Newtonian mechanics.

Keywords: dynamical systems, Fibonacci numbers, Newtonian mechanics, discrete dynamical system

Procedia PDF Downloads 488
18151 RFID Based Student Attendance System

Authors: Aniket Tiwari, Ameya London

Abstract:

Web-based student attendance management system is required to assist the faculty and the lecturer for the time-consuming process. For this purpose, GSM/GPRS (Global System for Mobile Communication/General Packet Radio Service) based student’s attendance management system using RFID (Radio Frequency Identification) is a much convenient method to take the attendance. Student is provided with the RFID tags. When student comes near to the reader, it will sense the respective student and update attendance. The whole process is controlled using the microcontroller. The main advantage of this system is that it reduced the complexity comparison to student attendance system using RF technology. This system requires only one microcontroller for the operation, it is real time process. This paper reviews some of these monitoring systems and proposes a GPRS based student attendance system. The system can be easily accessed by the lecturers via the web and most importantly, the reports can be generated in real-time processing, thus, provides valuable information about the students’ commitments in attending the classes.

Keywords: RFID reader, RFID tags, student, attendance

Procedia PDF Downloads 500
18150 Optimal Location of the I/O Point in the Parking System

Authors: Jing Zhang, Jie Chen

Abstract:

In this paper, we deal with the optimal I/O point location in an automated parking system. In this system, the S/R machine (storage and retrieve machine) travels independently in vertical and horizontal directions. Based on the characteristics of the parking system and the basic principle of AS/RS system (Automated Storage and Retrieval System), we obtain the continuous model in units of time. For the single command cycle using the randomized storage policy, we calculate the probability density function for the system travel time and thus we develop the travel time model. And we confirm that the travel time model shows a good performance by comparing with discrete case. Finally in this part, we establish the optimal model by minimizing the expected travel time model and it is shown that the optimal location of the I/O point is located at the middle of the left-hand above corner.

Keywords: parking system, optimal location, response time, S/R machine

Procedia PDF Downloads 407
18149 Transarterial Chemoembolization (TACE) in Hepatocellular Carcinoma (HCC)

Authors: Ilirian Laçi, Alketa Spahiu

Abstract:

Modality of treatment in hepatocellular carcinoma (HCC) patients depends on the stage of the disease. The Barcelona Clinic Liver Cancer Classification (BCLC) is the preferred staging system. There are many patients initially present with intermediate-stage disease. For these patients, transarterial chemoembolization (TACE) is the treatment of choice. The differences in individual factors that are not captured by the BCLC framework, such as the tumor growth pattern, degree of hypervascularity, and vascular supply, complicate further evaluation of these patients. Because of these differences, not all patients benefit equally from TACE. Several tools have been devised to aid the decision-making process, which have shown promising initial results but have failed external evaluation and have not been translated to the clinic aspects. Criteria for treatment decisions in daily clinical practice are needed in all stages of the disease.

Keywords: hepatocellular carcinoma, transarterial chemoembolization, TACE, liver

Procedia PDF Downloads 96
18148 NSBS: Design of a Network Storage Backup System

Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

Abstract:

The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

Procedia PDF Downloads 455
18147 A New Approach of Preprocessing with SVM Optimization Based on PSO for Bearing Fault Diagnosis

Authors: Tawfik Thelaidjia, Salah Chenikher

Abstract:

Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

Procedia PDF Downloads 434
18146 Real-Time Implementation of Self-Tuning Fuzzy-PID Controller for First Order Plus Dead Time System Base on Microcontroller STM32

Authors: Maitree Thamma, Witchupong Wiboonjaroen, Thanat Suknuan, Karan Homchat

Abstract:

First order plus dead time (FOPDT) is a high dynamic system. Therefore, the controller must be intelligent. This paper presents the development and implementation of self-tuning Fuzzy-PID controller for controlling the FOPDT system. The water level process used represented FOPDT system and the mathematical model of the system was approximated by using System Identification toolbox in Matlab. The control programming and Fuzzy-PID algorithm used Matlab/Simulink and run on Microcontroller STM32.

Keywords: real-time control, self-tuning fuzzy-PID, FOPDT system, the water lever process

Procedia PDF Downloads 287
18145 Development of an Omaha System-Based Remote Intervention Program for Work-Related Musculoskeletal Disorders (WMSDs) Among Front-Line Nurses

Authors: Tianqiao Zhang, Ye Tian, Yanliang Yin, Yichao Tian, Suzhai Tian, Weige Sun, Shuhui Gong, Limei Tang, Ruoliang Tang

Abstract:

Introduction: Healthcare workers, especially the nurses all over the world, are highly vulnerable to work-related musculoskeletal disorders (WMSDs), experiencing high rates of neck, shoulder, and low back injuries, due to the unfavorable working conditions. To reduce WMSDs among nursing personnel, many workplace interventions have been developed and implemented. Unfortunately, the ongoing Covid-19 (SARS-CoV-2) pandemic has posed great challenges to the ergonomic practices and interventions in healthcare facilities, particularly the hospitals, since current Covid-19 mitigation measures, such as social distancing and working remotely, has substantially minimized in-person gatherings and trainings. On the other hand, hospitals throughout the world have been short-staffed, resulting in disturbance of shift scheduling and more importantly, the increased job demand among the available caregivers, particularly the doctors and nurses. With the latest development in communication technology, remote intervention measures have been developed as an alternative, without the necessity of in-person meetings. The Omaha System (OS) is a standardized classification system for nursing practices, including a problem classification system, an intervention system, and an outcome evaluation system. This paper describes the development of an OS-based ergonomic intervention program. Methods: First, a comprehensive literature search was performed among worldwide electronic databases, including PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), between journal inception to May 2020, resulting in a total of 1,418 scientific articles. After two independent screening processes, the final knowledge pool included eleven randomized controlled trial studies to develop the draft of the intervention program with Omaha intervention subsystem as the framework. After the determination of sample size needed for statistical power and the potential loss to follow-up, a total of 94 nurses from eight clinical departments agreed to provide written, informed consent to participate in the study, which were subsequently assigned into two random groups (i.e., intervention vs. control). A subgroup of twelve nurses were randomly selected to participate in a semi-structured interview, during which their general understanding and awareness of musculoskeletal disorders and potential interventions was assessed. Then, the first draft was modified to reflect the findings from these interviews. Meanwhile, the tentative program schedule was also assessed. Next, two rounds of consultation were conducted among experts in nursing management, occupational health, psychology, and rehabilitation, to further adjust and finalize the intervention program. The control group had access to all the information and exercise modules at baseline, while an interdisciplinary research team was formed and supervised the implementation of the on-line intervention program through multiple social media groups. Outcome measures of this comparative study included biomechanical load assessed by the Quick Exposure Check and stresses due to awkward body postures. Results and Discussion: Modification to the draft included (1) supplementing traditional Chinese medicine practices, (2) adding the use of assistive patient handling equipment, and (3) revising the on-line training method. Information module should be once a week, lasting about 20 to 30 minutes, for a total of 6 weeks, while the exercise module should be 5 times a week, each lasting about 15 to 20 minutes, for a total of 6 weeks.

Keywords: ergonomic interventions, musculoskeletal disorders (MSDs), omaha system, nurses, Covid-19

Procedia PDF Downloads 176
18144 Masked Candlestick Model: A Pre-Trained Model for Trading Prediction

Authors: Ling Qi, Matloob Khushi, Josiah Poon

Abstract:

This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

Procedia PDF Downloads 120
18143 Application of Principle Component Analysis for Classification of Random Doppler-Radar Targets during the Surveillance Operations

Authors: G. C. Tikkiwal, Mukesh Upadhyay

Abstract:

During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

Procedia PDF Downloads 342
18142 Conceptual Design of Suction Cup Lifting System

Authors: Mohammed Aijaz

Abstract:

In industries, to transfer fragile materials like glasses, a holding, lifting, and manipulation system are required. In this report, we designed and analysed a suction cup holding, lifting, and manipulation system that is attached to a head plate and must be able to grip/hold securely, the largest glass panel with 3m x 2.5m x 20mm thick with a mass of 115 kg. The system is able to rotate the panel through 180 degrees in the X, Y, and Z axis in any direction from the outer reach of the robotic arm. The structural analysis is performed to verify the structural strength of the suction cup’s head plate system.

Keywords: designing, mechanical, engineering, suction

Procedia PDF Downloads 92
18141 Comparative Assessment of ABS and Disk Brake Systems

Authors: Saleh Mobasseri, Mohammad Mobasseri

Abstract:

The article refers to the history of the rise of brake system and described it’s importance in passenger’s lives. The disc brake system performance and ABS are also compared with each other by the kinetic and kinematic analysis of the braking system,and evaluate the impact of each parameters is checked on the vehicle stopping distance. Anti−lock braking system (ABS) is one of the most important features that affect on vehicle safety and for this reason much efforts have been made to improve this system. The objectives of the anti−lock system (ABS) are as follows: Preventing the wheels from locking, achieving maximum technical momentum in terms of braking,stability,reducing stopping distances. In this paper,we study the comparative of ABS brake and disc brake.

Keywords: anti−lock braking System (ABS), stopping distances, booster, car stability, force exerted on the brake pedal

Procedia PDF Downloads 393