Search results for: record to record algorithm

Authors: Y. Zhang, J. Perez, S. Marnier

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To date, no study on goaltending butterfly motion has been completed in real conditions, during an ice hockey game or training practice, to the author's best knowledge. This motion, performed to save score, is unnatural, intense, and repeated. The target of this research activity is to identify representative biomechanical criteria for this goaltender-specific movement pattern. Determining specific physical parameters may allow to will identify the risk of hip and groin injuries sustained by goaltenders. Four professional or academic goalies were instrumented during ice hockey training practices with five inertial measurement units. These devices were inserted in dedicated pockets located on each thigh and shank, and the fifth on the lumbar spine. A camera was also installed close to the ice to observe and record the goaltenders' activities, especially the butterfly motions, in order to synchronize the captured data and the behavior of the goaltender. Each data recorded began with a calibration of the inertial units and a calibration of the fully equipped goaltender on the ice. Three butterfly motions were recorded out of the training practice to define referential individual butterfly motions. Then, a data processing algorithm based on the Madgwick filter computed hip and knee joints joint range of motion as well as angular specific angular velocities. The developed algorithm software automatically identified and analyzed all the butterfly motions executed by the four different goaltenders. To date, it is still too early to show that the analyzed criteria are representative of the trauma generated by the butterfly motion as the research is only at its beginning. However, this descriptive research activity is promising in its ecological assessment, and once the criteria are found, the tools and protocols defined will allow the prevention of as many injuries as possible. It will thus be possible to build a specific training program for each goalie.

Keywords: biomechanics, butterfly motion, human motion analysis, ice hockey, inertial measurement unit

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Authors: Sathapath Kilaso

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Attendance checking in the classroom for student is object to record the student’s attendance in order to support the learning activities in the classroom. Despite the teaching trend in the 21st century is the student-center learning and the lecturer duty is to mentor and give an advice, the classroom learning is still important in order to let the student interact with the classmate and the lecturer or for a specific subject which the in-class learning is needed. The development of the system prototype by applied the microcontroller technology and embedded system with the “internet of thing” trend and the web socket technique will allow the lecturer to be alerted immediately whenever the data is updated.

Keywords: arduino, embedded system, classroom, raspberry PI

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Authors: Karolina Wieczorek, Sophie Wiliams

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Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

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Authors: Nurten Tasdemir, Busra Baloglu, Zeynep Cingoz, Can Demirel, Zeki Gezer, Barıs Efe

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Student nurses are increasingly exposed to technology in the workplace after graduation with the growing numbers of electric health records (EHRs), handheld computers, barcode scanner medication dispensing systems, and automatic capture of patient data such as vital signs. Internationally, electronic health records (EHRs) systems are being implemented and evaluated. Students will inevitably encounter EHRs in the clinical learning environment and their professional practice. Nursing students must develop competency in the use of EHR. Aim: The study aimed to examine nursing students’ experiences of learning to use electronic health records (EHR) in clinical placements. Method: This study adopted a descriptive approach. The study population consisted of second and third-year nursing students at the Zonguldak School of Health in the West Black Sea Region of Turkey; the study was conducted during the 2015–2016 academic year. The sample consisted of 315 (74.1% of 425 students) nursing students who volunteered to participate. The students, who were involved in clinical practice, were invited to participate in the study Data were collected by a questionnaire designed by the researchers based on the relevant literature. Data were analyzed descriptively using the Statistical Package for Social Sciences (SPSS) for Windows version 16.0. The data are presented as means, standard deviations, and percentages. Approval for the study was obtained from the Ethical Committee of the University (Reg. Number: 29/03/2016/112) and the director of Nursing Department. Findings: A total of 315 students enrolled in this study, for a response rate of 74.1%. The mean age of the sample was 22.24 ± 1.37 (min: 19, max: 32) years, and most participants (79.7%) were female. Most of the nursing students (82.3%) stated that they use information technologies in clinical practice. Nearly half of the students (42.5%) reported that they have not accessed to EHR system. In addition, 61.6% of the students reported that insufficient computers available in clinical placement. Of the students, 84.7% reported that they prefer to have patient information from EHR system, and 63.8% of them found more effective to preparation for the clinical reporting. Conclusion: This survey indicated that nursing students experience to learn about EHR systems in clinical placements. For more effective learning environment nursing education should prepare nursing students for EHR systems in their educational life.

Keywords: electronic health record, clinical placement, nursing student, nursing education

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Authors: Rafael Ricieri, Rogerio Barros, Francisco Clovis

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Objective– The Objective of this is study is to report a rare case of dermoid cyst, with a sublingual location and cutaneous fistula in a 4 year-old child.Methods: This study is a case report. The main study instrument was the medical record and the radiological and intraoperative image bank. Results: Infants with congenital cervical lesions eventually need tomography for diagnostic elucidation, and health services should be structured to perform sedation and thin tomographic sections in order to reduce morbidity.

Keywords: congenital, sublingual dermoid cyst, fistula, pediatric surgery, head and kneck surgery

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Authors: Nassiri Khalid, El Hibaoui Abdelaaziz et Hajar Moha

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In this paper, we introduce and analyse a probabilistic distributed algorithm for a construction of a minimum spanning tree on network. This algorithm is based on the handshake concept. Firstly, each network node is considered as a sub-spanning tree. And at each round of the execution of our algorithm, a sub-spanning trees are merged. The execution continues until all sub-spanning trees are merged into one. We analyze this algorithm by a stochastic process.

Keywords: Spanning tree, Distributed Algorithm, Handshake Algorithm, Matching, Probabilistic Analysis

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Authors: Tonguc Basaran

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History is a record of a people’s past based on a critical examination of documents and other facts. The essentials of this historical method are not beyond the grasp of even young children. Concrete examples, such as the story of the Rosetta stone, which enabled Champollion to establish the first principles of the deciphering of Egyptian hieroglyphics, vividly illustrate the fundamental processes involved. This search for the facts can be used to illustrate one side of the search for historic truth. The other side is the truth of historic interpretation. The facts cannot be changed, but the interpretation of them can and does change.

Keywords: history, primary education, teaching methods, social studies

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Authors: Prateek Rastogi, Jenash Acharya

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Histopathology examination has been a boon to forensic experts all around the world since its implication in autopsy cases. Whenever a case of sudden death is encountered, forensic experts clandestinely focus on cardiovascular, respiratory, gastrointestinal or cranio-cerebral causes. After ruling out poisoning or trauma, they are left with the only option available, histopathology examination. Besides preserving thoracic and abdominal organs, brain tissues are very less frequently subjected for the analysis. Based on provisional diagnosis documented on hospital treatment record files, one hemisphere of grossly unremarkable cerebrum was confirmatively diagnosed by histopathology examination to be a case of cerebral toxoplasmosis.

Keywords: cerebral toxoplasmosis, sudden death, health information, histopathology

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Authors: Eric Lee G. Escobedo-Wu, Nidhi Rohatgi, Fouzel Dhebar

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It is challenging for patients to navigate through healthcare systems after-hours. This leads to delays in care, patient/provider dissatisfaction, inappropriate resource utilization, readmissions, and higher costs. It is important to provide patients and providers with effective clinical decision-making tools to allow seamless connectivity and coordinated care. In August 2015, patient-centric Stanford Health Care established Clinical Advice Services (CAS) to provide clinical decision support after-hours. CAS is founded on key Lean principles: Value stream mapping, empathy mapping, waste walk, takt time calculations, standard work, plan-do-check-act cycles, and active daily management. At CAS, Clinical Assistants take the initial call and manage all non-clinical calls (e.g., appointments, directions, general information). If the patient has a clinical symptom, the CAS nurses take the call and utilize standardized clinical algorithms to triage the patient to home, clinic, urgent care, emergency department, or 911. Nurses may also contact the on-call physician based on the clinical algorithm for further direction and consultation. Since August 2015, CAS has managed 228,990 calls from 26 clinical specialties. Reporting is built into the electronic health record for analysis and data collection. 65.3% of the after-hours calls are clinically related. Average clinical algorithm adherence rate has been 92%. An average of 9% of calls was escalated by CAS nurses to the physician on call. An average of 5% of patients was triaged to the Emergency Department by CAS. Key learnings indicate that a seamless connectivity vision, cascading, multidisciplinary ownership of the problem, and synergistic enterprise improvements have contributed to this success while striving for continuous improvement.

Keywords: after hours phone calls, clinical advice services, nurse triage, Stanford Health Care

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Authors: Darawan Augsornwan, Artitaya Sabangbal, Maneewan Srijan, Kanokarn Kongpitee, Lalida Petphai, Palakorn Surakunprapha

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Background: Srinagarind Hospital, Ward 3C, has patients with head and neck cancer, congenital urology anomalies such as hypospadis, cleft lip and cleft palate and congenital megacolon who need surgery. Undergoing surgery is a difficult time for patients/ family; they feel fear and anxiety. Nurses work closely with patients and family for 24 hours in the process of patients care, so should have the good nursing ability, innovation and an efficient nursing care system to promote patients self-care ability reducing suffering and preventing complications. From previous nursing outcomes we found patients did not receive appropriate information, could not take care of their wound, not early ambulation after the operation and lost follow-up. Objective: to develop the nursing system for patients who were undergoing an operation. Method: this is a participation action research. The sample population was 11 nurses and 60 patients. This study was divided into 3 phase: Phase 1. Situation review In this phase we review the clinical outcomes, the process of care from documents such as nurses note and interview nurses, patients and family about the process of care by nurses. Phase 2: focus group with 11 nurses, searching guideline for specific care, nursing care system then establish the protocol. This phase we have the protocol for giving information, teaching protocol and teaching record, leaflet for all of top five diseases, make video media to convey information, ambulation package and protocol for patients with head and neck cancer, patients zoning, primary nurse, improved job description for each staff level. Program to record number of patients, kind of medical procedures for showing nurses activity each day. Phase 3 implementation and evaluation. Result: patients/family receive appropriate information about deep breathing exercise, cough, early ambulation after the operation, information during the stay in the hospital. Patients family satisfaction is 95.04 percent, appropriate job description for a practical nurse, nurse aid, and worker. Nurses satisfaction is 95 percent. The complications can be prevented. Conclusion: the nursing system is the dynamic process using evidence to develop nursing care. The appropriate system depends on context and needs to keep an eye on every event.

Keywords: development, nursing system, patients undergoing operation, 3C Ward

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Authors: Hafiz Gulfam Ahmad, Chuangdong Li, Zeeshan Ahmad

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In this paper, we proposed a parallel IDS and honeypot based approach to detect and analyze the unknown and known attack taxonomy for improving the IDS performance and protecting the network from intruders. The main theme of our approach is to record and analyze the intruder activities by using both the low and high interaction honeypots. Our architecture aims to achieve the required goals by combing signature based IDS, honeypots and generate the new signatures. The paper describes the basic component, design and implementation of this approach and also demonstrates the effectiveness of this approach reducing the probability of network attacks.

Keywords: network security, intrusion detection, honeypot, snort, nmap

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Authors: Enrique Barra, Abel Carril, Aldo Gordillo, Joaquin Salvachua, Juan Quemada

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Computers and multimedia equipment have improved a lot in the last years. They have reduced costs and size while at the same time has increased their capabilities. These improvements allowed us to design and implement a portable recording system that also integrates the teacher´s tablet PC to capture what he/she writes on the slides and all that happens in it. This paper explains this system in detail and the validation of the recordings that we did after using it to record all the lectures of a course in our university called “Communications Software”. The results show that pupils used the recordings for different purposes and consider them useful for a variety of things, especially after missing a lecture.

Keywords: recording system, capture dynamic presentations, lecture recording

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Atefeh Abdollahi, Maryam Bahreini, Babak Choobi Anzali, Fatemeh Rasooli

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Introduction: Triage becomes the main part of organization of care in Emergency department (ED)s. It is used to describe the sorting of patients for treatment priority in ED. The accurate triage of injured patients has reduced fatalities and improved resource usage. Besides, the nurses’ knowledge and skill are important factors in triage decision-making. The ability to define an appropriate triage level and their need for intervention is crucial to guide to a safe and effective emergency care. Methods: This is a prospective cross-sectional study designed for emergency nurses working in four public university hospitals. Five triage workshops have been conducted every three months for emergency nurses based on a standard triage Emergency Severity Index (ESI) IV slide set - approved by Iranian Ministry of Health. Most influential items on triage performance were discussed through brainstorming in workshops which then, were peer reviewed by five emergency physicians and two head registered nurses expert panel. These factors that might distract nurse’ attention from proper decisions included patients’ past medical diseases, the natural tricks of triage and system failure. After permission had been taken, emergency nurses participated in the study and were given the structured questionnaire. Data were analysed by SPSS 21.0. Results: 92 emergency nurses enrolled in the study. 30 % of nurses reported the past history of chronic disease as the most influential confounding factor to ascertain triage level, other important factors were the history of prior admission, past history of myocardial infarction and heart failure to be 20, 17 and 11 %, respectively. Regarding the concept of difficulties in triage practice, 54.3 % reported that the discussion with patients and family members was difficult and 8.7 % declared that it is hard to stay in a single triage room whole day. Among the participants, 45.7 and 26.1 % evaluated the triage workshops as moderately and highly effective, respectively. 56.5 % reported overcrowding as the most important system-based difficulty. Nurses were mainly doubtful to differentiate between the triage levels 2 and 3 according to the ESI VI system. No significant correlation was found between the work record of nurses in triage and the uncertainty in determining the triage level and difficulties. Conclusion: The work record of nurses hardly seemed to be effective on the triage problems and issues. To correct the deficits, training workshops should be carried out, followed by continuous refresher training and supportive supervision.

Keywords: assessment, education, nurse, triage

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Authors: Dipak Subedi, Anil Giri, Christine Whitt, Tia McDonald

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This study aims to understand the impact of the pandemic on the overall economic well-being of the agricultural sector of the United States. The two key metrics used to examine the economic well-being are the bankruptcy rate of the U.S. farm operations and the operating profit margin. One of the primary reasons for farm operations (in the U.S.) to file for bankruptcy is continuous negative profit or a significant decrease in profit. The pandemic caused significant supply and demand shocks in the domestic market. Furthermore, the ongoing trade disruptions, especially with China, also impacted the prices of agricultural commodities. The significantly reduced demand for ethanol and closure of meat processing plants affected both livestock and crop producers. This study uses data from courts to examine the bankruptcy rate over time of U.S. farm operations. Preliminary results suggest there wasn’t an increase in farm operations filing for bankruptcy in 2020. This was most likely because of record high Government payments to producers in 2020. The Federal Government made direct payments of more than $45 billion in 2020. One commonly used economic metric to measure farm profitability is the operating profit margin (OPM). Operating profit margin measures profitability as a share of the total value of production and government payments. The Economic Research Service of the United States Department of Agriculture defines a farm operation to be in a) a high-risk zone if the OPM is less than 10 percent and b) a low-risk zone if the OPM is higher than 25 percent. For this study, OPM was calculated for small, medium, and large-scale farm operations using the data from the Agriculture Resource Management Survey (OPM). Results show that except for small family farms, the share of farms in high-risk zone decreased in 2020 compared to the most recent non-pandemic year, 2019. This was most likely due to higher commodity prices at the end of 2020 and record-high government payments. Further investigation suggests a lower share of smaller farm operations receiving lower average government payments resulting in a large share (over 70 percent) being in the critical zone. This study should be of interest to multiple stakeholders, including policymakers across the globe, as it shows the resilience of the U.S. agricultural system as well as (some) impact of government payments.

Keywords: U.S. farm sector, COVID-19, operating profit margin, farm bankruptcy, ag finance, government payments to the farm sector

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Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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Authors: Vishnu Pratap Singh Kirar

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Artificial Neural Network (ANN) can be trained using backpropagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a two-term algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: neural network, backpropagation, local minima, fast convergence rate

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Authors: Adeyemo Abduljeeel Taiwo

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This research is an attempt that creates a conducive atmosphere of a phonological and morphological compendium of Arabic language in Modern Standard Arabic (MSA) for modern day communications. The research is carried out with the chief aim of grammatical analysis of the two broad fields of Arabic linguistics namely: Applied and Socio-Linguistics. It draws a pictorial record of Applied and Socio-Linguistics in Arabic phonology and morphology. Thematically, it postulates and contemplates to a large degree, the theory of concord in contemporary modern Arabic language acquisition. It utilizes an analytical method while it portrays Arabic as a Semitic language that promotes linguistics and syntax among the scholars of the fields.

Keywords: Arabic language, applied linguistics, socio-linguistics, modern communications

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Authors: P. Treyer, M. Kujda, H. Urs

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The purpose of this paper is to digitally compensate for the apparent discharge time constant of the coaxial cable so that the current step response is flat and can be used to calibrate current transducers using the convolution method. For proper use of convolution, the step response record length is required to be at least the same as the waveform duration to be evaluated. The current step generator based on the cable discharge is compared to the Blumlein generator. Moreover, the influence of each component of the system on the performance of the step is described, which allows building the appropriate measurement set-up. In the end, the calibration of current viewing resistors dedicated to high current impulse is computed.

Keywords: Blumlein generator, cable attenuation, convolution, current step generator

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Authors: Kevin Worrall, Euan McGookin

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The use of optimization algorithms is common across a large number of diverse fields. This work presents the use of a hybrid optimization algorithm applied to a mobile robot tasked with carrying out a search of an unknown environment. The algorithm is then applied to the multiple robots case, which results in a reduction in the time taken to carry out the search. The hybrid algorithm is a Random Search Algorithm fused with a Tabu mechanism. The work shows that the algorithm locates the desired points in a quicker time than a brute force search. The Tabu Random algorithm is shown to work within a simulated environment using a validated mathematical model. The simulation was run using three different environments with varying numbers of targets. As an algorithm, the Tabu Random is small, clear and can be implemented with minimal resources. The power of the algorithm is the speed at which it locates points of interest and the robustness to the number of robots involved. The number of robots can vary with no changes to the algorithm resulting in a flexible algorithm.

Keywords: algorithms, control, multi-agent, search and rescue

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Authors: Loretta Baryeh

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Unprecedented disruptions to world economies unfolded consequently to the pandemic that hit the globe in 2020. The severe sickness with no cure at the time led to record deaths, and this affected everyday life for most people, stifling production, hospitality, entertainment, and most sectors of the economy. This paper was an extension of Baryeh 2021, that studied the pandemic effect on economic growth and if that was exacerbated by corruption. It was found that there was a positively high significant correlation between countries that reported high cases of the virus and countries that reported more deaths due to the virus. Furthermore, it was shown that countries with high COVID-19 cases were highly corrupt. Additionally, there was a negative association between high COVID-19 cases and economic development.

Keywords: COVID-19, corruption, economic, performance

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Authors: Sayor Ajfar Aaron, Sajjat Hossain Abir, Ashif Newaz, Md Mushfiqur Rahman

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Investigating the convergence of blockchain technology and artificial intelligence, this paper examines their synergistic effects on data integrity and decision-making within smart contracts. By implementing AI-driven analytics on blockchain-based platforms, the research identifies improvements in automated contract enforcement and decision accuracy. The paper presents a framework that leverages AI to enhance transparency and trust, while blockchain ensures immutable record-keeping, culminating in significantly optimized operational efficiencies in various industries.

Keywords: artificial intelligence, blockchain, data Integrity, smart contracts.

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Authors: Thomas Yeboah

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Cloud Computing is newly paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). As Cloud Computing is a newly style of computing on the internet. It has many merits along with some crucial issues that need to be resolved in order to improve reliability of cloud environment. These issues are related with the load balancing, fault tolerance and different security issues in cloud environment.In this paper the main concern is to develop an effective load balancing algorithm that gives satisfactory performance to both, cloud users and providers. This proposed algorithm (hybrid Bee Ant Colony algorithm) is a combination of two dynamic algorithms: Ant Colony Optimization and Bees Life algorithm. Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues whiles the Bees Life algorithm is used for optimization of job scheduling in cloud environment. The results of the proposed algorithm shows that the hybrid Bee Ant Colony algorithm outperforms the performances of both Ant Colony algorithm and Bees Life algorithm when evaluated the proposed algorithm performances in terms of Waiting time and Response time on a simulator called CloudSim.

Keywords: ant colony optimization algorithm, bees life algorithm, scheduling algorithm, performance, cloud computing, load balancing

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Authors: Diaa Ahmed Mohamed Ahmedien

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Nowadays, it cannot be denied that the most important interactive arts trends have appeared as a result of significant scientific mutations in the modern sciences, and holographic art is not an exception, where it is considered as a one of the most important major contemporary interactive arts trends in visual arts. Holographic technique had been evoked through the modern physics application in late 1940s, for the improvement of the quality of electron microscope images by Denis Gabor, until it had arrived to Margaret Benyon’s art exhibitions, and then it passed through a lot of procedures to enhance its quality and artistic applications technically and visually more over 70 years in visual arts. As a modest extension to these great efforts, this research aimed to invoke extraordinary attempt to enroll sample of normal people in Egyptian community in holographic recording program to record their appreciated objects or antiques, therefore examine their abilities to interact with modern techniques in visual communication arts. So this research tried to answer to main three questions: 'can we use the analog holographic techniques to unleash new theoretical and practical knowledge in interactive arts for public in Egyptian community?', 'to what extent holographic art can be familiar with public and make them able to produce interactive artistic samples?', 'are there possibilities to build holographic interactive program for normal people which lead them to enhance their understanding to visual communication in public and, be aware of interactive arts trends?' This research was depending in its first part on experimental methods, where it conducted in Laser lab at Cairo University, using Nd: Yag Laser 532 nm, and holographic optical layout, with selected samples of Egyptian people that they have been asked to record their appreciated object, after they had already learned recording methods, and in its second part on a lot of discussion panel had conducted to discuss the result and how participants felt towards their holographic artistic products through survey, questionnaires, take notes and critiquing holographic artworks. Our practical experiments and final discussions have already lead us to say that this experimental research was able to make most of participants pass through paradigm shift in their visual and conceptual experiences towards more interaction with contemporary visual arts trends, as an attempt to emphasize to the role of mature relationship between the art, science and technology, to spread interactive arts out in our community through the latest scientific and artistic mutations around the world and the role of this relationship in our societies particularly with those who have never been enrolled in practical arts programs before.

Keywords: Egyptian community, holographic art, laser art, visual art

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Authors: Sardar Ameer Akram Khan, Shahzad Amin Sheikh

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Blind equalization is an important technique amongst equalization family. Multimodulus algorithms based on blind equalization removes the undesirable effects of ISI and cater ups the phase issues, saving the cost of rotator at the receiver end. In this paper a new algorithm combination of recursive least square and Multimodulus algorithm named as RLSMMA is proposed by providing few assumption, fast convergence and minimum Mean Square Error (MSE) is achieved. The excellence of this technique is shown in the simulations presenting MSE plots and the resulting filter results.

Keywords: blind equalizations, constant modulus algorithm, multi-modulus algorithm, recursive least square algorithm, quadrature amplitude modulation (QAM)

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Authors: Safa Adi

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This paper will consider the problem of sequential mining patterns embedded in a database by handling the time constraints as defined in the GSP algorithm (level wise algorithms). We will compare two previous approaches GTC and PSP, that resumes the general principles of GSP. Furthermore this paper will discuss PG-hybrid algorithm, that using PSP and GTC. The results show that PSP and GTC are more efficient than GSP. On the other hand, the GTC algorithm performs better than PSP. The PG-hybrid algorithm use PSP algorithm for the two first passes on the database, and GTC approach for the following scans. Experiments show that the hybrid approach is very efficient for short, frequent sequences.

Keywords: database, GTC algorithm, PSP algorithm, sequential patterns, time constraints

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Authors: Ali Nourollah, Mohsen Movahedinejad

Abstract:

In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The merge algorithm has the time complexity of O ((r+s) *l) where r and s are the size of merging polygons and l shows the number of intersecting edges removed from the polygonal chain. It will be shown that 1 < l < r+s. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

Procedia PDF Downloads 507

Authors: Hussah Alotaishan

Abstract:

In today’s globally-driven modern cities diverse groups of new visitors face various challenges when attempting to find their desired location if culture and language are barriers. The most common way-showing tools such as directional and identificational signs are the most problematic and their usefulness can be limited or even non-existent. It is argued new methods should be implemented that could support or replace such conventional literacy and language dependent way-finding aids. It has been concluded in recent research studies that local urban features in complex pedestrian spaces are worthy of further study in order to reveal if they do function as way-showing clues. Some researchers propose a more comprehensive approach to the complex perception of buildings, façade design and surface patterns, while some have been questioning whether we necessarily need directional signs or can other methods deliver the same message but in a clearer manner for a wider range of users. This study aimed to test to what extent do existent environmental and urban features through the city center area of Swansea in the UK facilitate the way-finding process of a first time visitor. The three-hour experiment was set to attempt to find 11 visitor attractions ranging from recreational, historical, educational and religious locations. The challenge was attempting to find as many as possible when no prior geographical knowledge of their whereabouts was established. The only clues were 11 pictures representing each of the locations that had been acquired from the city of Swansea official website. An iPhone and a heart-rate tracker wristwatch were used to record the route was taken and stress levels, and take record photographs of destinations or decision-making points throughout the journey. This paper addresses: current limitations in understanding the ways that the physical environment can be intentionally deployed to facilitate pedestrians while finding their way around, without or with a reduction in language dependent signage; investigates visitor perceptions of their surroundings by indicating what urban elements manifested an impact on the way-finding process. The initial findings support the view that building facades and street features, such as width, could facilitate the decision-making process if strategically employed. However, more importantly, the anticipated features of a specific place construed from a promotional picture can also be misleading and create confusion that may lead to getting lost.

Keywords: pedestrian way-finding, environmental features, urban way-showing, environmental affordance

Procedia PDF Downloads 141

Authors: Divya Pradip Roy, Md. Zahirul Alam Chowdhury

Abstract:

Electromyography (EMG) sensors are generally used to record the electrical activity produced by skeletal muscles. The conventional EMG sensors available in the market are expensive. This research suggests a low cost EMG sensor design which can be built with simple devices within our reach. In this research, one instrumentation amplifier, two high pass filters, two low pass filters and an inverting amplifier is connected sequentially. The output from the circuit exhibits electrical potential generated by the muscle cells when they are neurologically activated. This electromyography signal is used to control prosthetic devices, identifying neuromuscular diseases and for various other purposes.

Keywords: EMG, high pass filter, instrumentation amplifier, inverting amplifier, low pass filter, neuromuscular

Procedia PDF Downloads 147

Authors: Ying Li, Yan Li

Abstract:

A new algorithm for single hidden layer feedforward neural networks (SLFN), Orthogonal Basis Extreme Learning (OBEL) algorithm, is proposed and the algorithm derivation is given in the paper. The algorithm can decide both the NNs parameters and the neuron number of hidden layer(s) during training while providing extreme fast learning speed. It will provide a practical way to develop NNs. The simulation results of function approximation showed that the algorithm is effective and feasible with good accuracy and adaptability.

Keywords: neural network, orthogonal basis extreme learning, function approximation

Procedia PDF Downloads 505