Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

31,456 Article Results

Analysis and potential use of Google Trends as a monitoring tool for risk communication during COVID-19 pandemic

10.11591/ijphs.v9i4.20512
Nindya Mahfuza , Rizma Adlia Syakurah , Resiana Citra
COVID-19 Pandemic has become a major problem in various infected countries, including Indonesia. The proper risk communication strategy during this outbreak was important to reduce the impact. Therefore, this research was intended to assess the potential use of Google Trends as a tool to monitor risk communication during COVID-19 pandemic in Indonesia. Search patterns were analyzed using the terminology used to identify COVID-19 in Indonesia, followed by information-finding keywords 'gejala (symptoms)', 'mencegah (preventing)', and 'obat (drug)' keywords compared to the number of newly confirmed COVID-19 cases in Indonesia using time-lagged correlation analysis from December 31th, 2019 to April 20th, 2020. Peaks within respective timelines were qualitatively described according to current COVID-19 related events. ”Corona” was the terminology mostly used in Indonesia to identify COVID-19. There were five spikes observed from “corona” keyword timeline, which each spike was dependent on the media coverage and regulation by the Government. Validation using time-lagged correlation yields significant results between corona, corona symptoms, preventing corona and corona drugs compared to newly confirmed COVID-19 cases in Indonesia. Google Trends can potentially be used to maximize the improvement of risk communication and as a tool to monitor public restlessness during the COVID-19 pandemic in Indonesia by Government.
Volume: 9
Issue: 4
Page: 399-405
Publish at: 2020-12-01

Medical vision: web and mobile medical image retrieval system based on google cloud vision

10.11591/ijece.v10i6.pp5974-5984
I Ketut Gede Darma Putra , Dewa Made Sri Asra , I Gusti Ngurah Dwiva Hardijaya , I Gede Galang Surya Prabawa , I Made Aris Satia Widiatmika
The application of information technology is rapidly utilized in the medical system. There is also a massive development in the automatic method for recognizing and detecting objects in the real world. In this study, we present a system called Medical Vision which is designed for people who has no expertise in medical. Medical Vision is a web and mobile-based application to give an initial knowledge in a medical image. This system has 5 features; object detection, web detection, object labeling, safe search, and image properties. These features are run by embedding Google Vision API in the system. We evaluate this system by observing the result of some medical images which inputted into the system. The results showed that our system presents a promising performance and able to give relevant information related to the given image.
Volume: 10
Issue: 6
Page: 5974-5984
Publish at: 2020-12-01

Students’ perceptions toward vocational education on online learning during the COVID-19 pandemic

10.11591/ijere.v9i4.20766
Khusni Syauqi , Sudji Munadi , Mochamad Bruri Triyono
The impact of the Covid-19 pandemic has spread almost throughout the world. It makes all educational institutions in Indonesia experienced a lockdown in an undetermined time. As a result, teachers must switch to online teaching methods, while students must adapt to the online learning environment in a short time. Vocational education emphasizes not only the mastery of knowledge but also skills. In the learning process, students' perceptions can be used as evaluations to improve the quality of learning. This study aimed to provide an overview of students' perceptions of Mechanical Engineering Education on online learning as a result of the impact of the Covid-19 pandemic. This study used survey methods and data collection in the form of instruments with a Likert scale with a sample of 56 students. The results of this study indicate that teachers in managing online learning are not in line with student expectations. Students feel that online learning has not provided better experience and productivity in mastering competencies, but can provide motivation and ease in their learning. Some students stated that they had the ease of access to resources, but students were still reluctant to use it sustainably in the future.
Volume: 9
Issue: 4
Page: 881-886
Publish at: 2020-12-01

Implementation of anti-collision train prototype based on arduino microcontroller

10.11591/ijaas.v9.i4.pp270-275
Ahmed R. Ibrahim , Ziad M. Abood
Because the electrical train become a popular mode and Eco-Friendly of transport in largest cities in the world in our day life and due to increase in the train accidents.  In this paper a train collision avoidance system is designed and implemented using Arduino NANO and an ultrasonic sensor. A prototype is used to explain the system function using; two train samples on single track. The ultrasonic sensor is connected to the Arduino NANO to transmit the measured distance to the microcontroller and make the decision to stop the train. The ultrasonic sensor on both trains from the front end and continually measures the distance between them and when they reach the decided distance a signal to the trains engines will slow down or stop both trains to avoid a collision while when the ultrasonic sensors from the rear-end continually measure the distance between them and when it reaches the decided distance a signal to the train engine will slow down and stop the first train to avoid a collision.
Volume: 9
Issue: 4
Page: 270-275
Publish at: 2020-12-01

Dynamic real-time capacity constrained routing algorithm for evacuation planning problem

10.11591/ijeecs.v20.i3.pp1388-1396
Jawad Abusalama , Sazalinsyah Razali , Yun-Huoy Choo , Lina Momani , Abdelrahman Alkharabsheh
Usually, disasters occur over a relatively short time anytime and anywhere. Most occupancies do not have absolute knowledge about the prevention or safety consciousness to deal with disasters. During disaster occurrence, evacuation processes are conducted to save people’s life, and if there is no appropriate evacuation plan, the situation will become worse. Thus, finding an optimal planning technique to evacuate occupants is critical in many cases i.e. emergency evacuation. In this paper, a Dynamic Real-Time Capacity Constrained Routing (DRTCCR) Algorithm has been proposed and analyzed. Such algorithm will investigate the capacity constraints of the evacuation network in real time by modelling the capacities based on time series to improve current solutions of the Emergency Route Planning (ERP) problem.  Such algorithm will produce an optimal solution for the ERP problem. Performance evaluation on many network models illustrates that the DRTCCR algorithm improves the previous evacuation planning by reducing the evacuation time as well as the computational cost. In addition, DRTCCR algorithm has the ability to recalculate and find out the optimal path dynamically in real time irrespective of the number of trapped people as well as the transportation network size. Analytical experiments have been carried out, which illustrates the efficiency of the proposed algorithm.
Volume: 20
Issue: 3
Page: 1388-1396
Publish at: 2020-12-01

Disturbance rejection using IMC tuned PID controller with improved filter

10.11591/ijeecs.v20.i3.pp1261-1270
B. Mabu Sarif , D. V. Ashok Kumar , M. Venu Gopala Rao
IMC-PID controllers supply exceptional set point tracking but slow disturbance refutation, because of introduction of slow process pole introduced by the conventional filter. Disturbance rejection is important in many industrial applications over set point tracking. An enhanced IMC filter cascaded with PID controller with internal model control tuning system (IMC-PID) is presented right now for efficient disruption rejection and reliable first order process operation with time delay (FOPTD). The optional filter does away with the sluggish dominant pole. The present learning shows that the recommended IMC filter provide excellent trouble rejection irrespective of where the trouble enters the procedure and provide high-quality robustness to duplicate deviation in surroundings of accepting in difference with other method cited in the text. Reenactment study was led to show the feasibility of the suggested approach on processes with different 0/r ratios by measuring the controller parameters while retaining the same robustness as regards maximal sensitivity. His efficiency of the closed loops was assessed utilizing integral error parameters. Viz. ISE, ITAE, IAE. The recommended filter provides excellent response pro lag dominant processes.
Volume: 20
Issue: 3
Page: 1261-1270
Publish at: 2020-12-01

Hormonal profile and characteristics of polychistic ovarium syndrome among Madurese tribe, Indonesia

10.11591/ijphs.v9i4.20408
Zakkiyatus Zainiyah , Eny Susanti , Mustofa Haris
Polycystic ovarium syndrome (PCOS), the most common endocrine disorders in women of reproductive age, characterized by menstrual disorders (amenorrhea/oligomenorrhea), hirsutism, the appearance of acne, alopecia and the results of biochemical tests that show increased androgens (testosterone). Increased serum luteinizing hormone (LH) and follicle stimulating hormone (FSH) serve as diagnostic tests for PCOS over the years, but from several research results obtained inconsistent results that need further research. The purpose of this study is to analyze the hormonal profile and characteristics of polycystic ovary syndrome (PCOS) in Madura. Case-control study conducted in March-August 2019 in the Madura tribe. There were 32 subjects with PCOS and 32 healthy women participated in this study. Hormonal examination was using a serum and followed by enzyme-linked immune sorbent assay (ELISA kit). Levels Follicle-stimulating hormone (FSH) average was 8.74 and SHBGs were 10.02 lower in PCOS patients and LH levels were higher in PCOS patients; ratio LH/FSH was 0.76. The results of the Madurese study showed that levels of FSH, LH, weight significantly related to PCOS sex hormone binding globulin (SHBG), however body mass index (BMI) levels were not related to PCOS.
Volume: 9
Issue: 4
Page: 333-337
Publish at: 2020-12-01

Performance analysis of flow-based attacks detection on CSE-CIC-IDS2018 dataset using deep learning

10.11591/ijeecs.v20.i3.pp1413-1418
Rawaa Ismael Farhan , Abeer Tariq Maolood , Nidaa Flaih Hassan
The emergence of the internet of things (IOT) as a result of the development of the communications system has made the study of cyber security more important. Day after day, attacks evolve and new attacks are emerged. Hence, network anomaly-based intrusion detection system is become very important, which plays an important role in protecting the network through early detection of attacks. Because of the development in  machine learning and the emergence of deep learning field,  and its ability to extract high-level features with high accuracy, these systems have been included to work with real network traffic CSE-CIC-IDS2018 for a wide range of intrusions and normal behavior as an ideal method of testing and evaluation. In this paper, we test and evaluate our deep model (DNN) which has achieved a good detection accuracy of about 90%.
Volume: 20
Issue: 3
Page: 1413-1418
Publish at: 2020-12-01

Correlation of body mass index on waist circumference and blood pressure

10.11591/ijphs.v9i4.20443
Yoni Astuti , Ikhlas Muhammad Jenie
The increasing number of elderly on these recent days demands an improved quality of health for the elderly. Independence of the elderly is important in order to be happy and not to be a burden on their families. Health monitoring continuously is an effort to prevent disruption on the health conditions of the elderly. The health status of elderly people is important to know to follow up on prevention programs for the emergence of certain diseases in the elderly. This study aims to look for potential health problems for elderly people in Gamping, Sleman, DIY, Indonesia. The method of this research was cross sectional analysis using secondary data. Sample collection is consecutive subjects. Subjects were 158 people with a mean age of men (67.8 ± 7.1) years while women were 67.5 ± 7.3 years. The data was analyzed using the bivariate correlation test with CI 99%. The results of the analysis showed that the average body mass index with an average waist circumference was positively correlated (r= 0.66; p: 0.000), but did not correlate with systole pressure (r= -0.009; p= 0.97) diastole (r= 0.093; p= 0.477), age (-0.05; p= 0.71), and gender (r= -0.146; p= 0. 27). The potential health problems among the elderly is the risk of high BMI due to the larger waist circumference
Volume: 9
Issue: 4
Page: 373-378
Publish at: 2020-12-01

Design and implementation a network mobile application for plants shopping center using QR code

10.11591/ijece.v10i6.pp5940-5950
Saja Nasir , Salih Al-Qaraawi , Muayad Croock
During the revolution of developing mobile phone applications, they can be used in different fields like business, health, transportation, communications and tourism, and other uses. This paper presents QR based information management system for plants shopping centers. This system includes two main sides: mobile and server. The proposed application is used as a substitute for the human guide that each visitor needs in the plants shopping center. The complete information can be provided on any seedling displayed in the shop depending on the QR code technology. Each branch of the same enterprise includes sub-server that is linked to the main server using a private computer network. The server side contains information of all plants and all branches for such enterprise in the form of text and image in different languages. The proposed application facilitates the movement of the customer inside the place, the ease in preparing bills electronically that helps the visitor to save the time of queue to preparing the bill and paying. The proposed system is tested over different case studies to prove the efficiency in terms of information and selling management.
Volume: 10
Issue: 6
Page: 5940-5950
Publish at: 2020-12-01

An approach for a multi-stage under-frequency based load shedding scheme for a power system network

10.11591/ijece.v10i6.pp6071-6100
Mkhululi Elvis Siyanda Mnguni , Yohan Darcy Mfoumboulou
The integration of load shedding schemes with mainstream protection in power system networks is vital. The traditional power system network incorporates different protection schemes to protect its components. Once the power network reaches its maximum limits, and the load demand continue to increase the whole system will experience power system instability. The system frequency usually drops due to the loss of substantial generation creating imbalance. The best method to recover the system from instability is by introducing an under-frequency load shedding (UFLS) scheme in parallel with the protection schemes. This paper proposed a new UFLS scheme used in power systems and industry to maintain stability. Three case studies were implemented in this paper. Multi-stage decision-making algorithms load shedding in the environment of the DIgSILENT power factory platform is developed. The proposed algorithm speeds-up the operation of the UFLS scheme. The load shedding algorithm of the proposed scheme is implemented as a systematic process to achieve stability of the power network which is exposed to different operating conditions. The flexibility of the proposed scheme is validated with the modified IEEE 39-bus New England model. The application of the proposed novel UFLS schemes will contribute further to the development of new types of engineers.
Volume: 10
Issue: 6
Page: 6071-6100
Publish at: 2020-12-01

Design of frequency selective surface comprising of dipoles using artificial neural network

10.11591/ijaas.v9.i4.pp276-283
Monojit Rudra , P Soni Reddy , Rajatsubhra Chakraborty , Partha Pratim Sarkar
This paper depicts the design of Frequency Selective Surface (FSS) comprising of dipoles using Artificial Neural Network (ANN). It has been observed that with the change of the dimensions and periodicity of FSS, the resonating frequency of the FSS changes. This change in resonating frequency has been studied and investigated using simulation software. The simulated data were used to train the proposed ANN models. The trained ANN models are found to predict the FSS characteristics precisely with negligible error. Compared to traditional EM simulation softwares (like ANSOFT Designer), the proposed technique using ANN models is found to significantly reduce the FSS design complexity and computational time. The FSS simulations were made using ANSOFT Designer v2 software and the neural network was designed using MATLAB software.
Volume: 9
Issue: 4
Page: 276-283
Publish at: 2020-12-01

Mothers’ perception and management preference of acute diarrheal disease

10.11591/ijphs.v9i4.20503
Terefe Keto , Yalfal Alemu , Aklilu Mamo
Globally, diarrheal disease is one of the leading causes of morbidity and mortality among under-five years of children. Every day, approximately 2195 children die due to diarrheal diseases, which accounts for 1 in 9 child deaths worldwide. Many interventions that attempt to reduce childhood diarrhea are often fail because they are programed without understanding the problem in the target community and are culturally unsuitable. Therefore, this study aimed to assess perception and management preference of acute diarrheal disease among mothers who attend under five clinics. An institution based descriptive cross sectional study was conducted from May 1-May 30/2019. A total of 276 respondents were included in the study and consecutive sampling technique was used to identify the study participants. The results show that 47% of respondents perceive childhood diarrhea is caused by teething, 47.8% of the respondents perceive that diarrhea cannot be transmitted from one child to other. Majority of care givers prefer to give home remedies to their child, and also a substantial proportion of mothers and caregivers were not adequately knowledgeable on the use of oral rehydration salt which resulted in many of them using traditional medicine. There is need for increased health education focused on increasing caregivers‟ knowledge about the cause of diarrhea and enhancing adoption of appropriate prevention practices of diarrhea among children under five years.
Volume: 9
Issue: 4
Page: 338-346
Publish at: 2020-12-01

Do descendants of families contribute to type 2 diabetes mellitus?

10.11591/ijphs.v9i4.20586
Fatma Nuraisyah , Solikhah Solikhah , Rochana Ruliyandari
Diabetes is a public health problem in Indonesia that has been increasing in recent decades. Screening for diabetes was usually identified as pregnant women, adolescents, adults, children, older and obesity, while based on investigation descendent was yet. This cross-sectional study aimed to know the random level blood glucose of family history type 2 diabetes mellitus (T2DM). The target group for screening was people with a family history in one of their descent of T2DM with age >20 years in Kulon Progo, DIY, Indonesia. We conducted a detection of random level blood glucose from a venous blood sample. A high level of blood glucose was diagnosed when random blood glucose reaches ≥200 mg/dl. The participant with high level of blood glucose was 29.0%, while borderline blood glucose (≥110-199 mg/dl) was revealed 38.7% of 15.3% subject indicated with mother history. Descendant screening of family history T2DM is early detected respondent with high glucose level and reduced the severe complication.
Volume: 9
Issue: 4
Page: 303-306
Publish at: 2020-12-01

The LSTM technique for demand forecasting of e-procurement in the hospitality industry in the UAE

10.11591/ijai.v9.i4.pp757-765
Elezabeth Mathew , Sherief Abdulla
The hospitality industry is growing at a faster pace across the world which has resulted in the accumulation of a huge amount of data in terms of employee details, property details, purchase details, vendor details, and so on. The industry is yet to fully benefit from these big data by applying ML and AI. The data has not been fully investigated for decision-making or revenue/budget forecasting. In this research data is collected from a chain hotel for advanced predictive analytics. Descriptive and diagnostic analytics is done to an extent across the hotel industry, whereas predictive and prescriptive analysis is done rarely. Demand forecasting for spend and quantity is done using the LSTM technique in e-procurement within the hospitality industry in the UAE. Five years of historical data from a chain hotel in the UAE is used for deep learning in this study. The results confirm the ability of LSTM model to predict e-procurement spend and order forecast for six months. LSTM time series analysis is considered the most suitable technique for demand forecasting to optimize e-procurement.
Volume: 9
Issue: 4
Page: 757-765
Publish at: 2020-12-01
1 2 3
...
2097 2098
Show 1156 of 2098

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration