bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of obesity, type 2 diabetes mellitus, metabolic syndrome and coronary heart disease using Backpropagation algorithm
Authors: Widiyawati  , Nurrahman A , Darmawan B , Jaya A I , Ratianingsih R 
Published: May 2019

Abstract
Along with the development of increasingly modern life styles, the risk of community healthiness to gain weighted is rising due to the positive and negative impact of social interactions. Many negative impacts of social interaction tend the people of such community member being obese, in other way some positive impacts make the possibility of the obese people being normal weighted. This study discusses the prognosis obesity, metabolic syndrome MS), type 2 diabetes mellitus (DM) and coronary heart disease (CHD) people in point view of some risk factor of it. Obesity is the main stimulator for MS, Type 2 DM and hypertension. These diseases are the main factors for the cardiovascular disease. MS is a metabolic disorder that mostly suffered by obese and raises the risk of heart disease or stroke three times higher. Moreover, it raises the risk of type 2 DM five times higher. The type 2 DM also becomes as the one of the major health problems that causes vascular diseases such as coronary heart disease. The disease is the world’s leading cause of death. A prognostic detection of obese, DM, SM and CHD architecture is constructed in this paper and Backpropagation is proposed to derive the prediction model. The datasets taken from Palu Anutapura Hospital’s patients is trained to get the model. After that the model is tested until having a high accurate prediction. The accuracy of the detection to predict DM or MS is 93.33%, while the accuracy to predict CHD is 90.67%. The accuracy is obtained by identify the variation of the learning rate and hidden layer and got the best value of them are α = 0.5 and 5 hidden layers for not greater than 0.001 and maximum epoch 1000 of error target.
Application of Fuzzy Kernel C-Means in face recognition to identify look-alike faces
Authors: Rustam Zuherman , Faradina Ridhani 
Published: May 2019

AbstractMachine learning has been rapidly evolving and continuously developing. Many problems can be solved by machine learning. One of those is face recognition. There are many application of face recognition. One application that will be discussed in this research is face recognition to identify look-alike faces. Such application can be useful when dealing with huge data. Machine learning method that will be used is Fuzzy Kernel C-Means. This method is the modification of previous method Fuzzy C-Means. The kernel used is Radial Basis Function Kernel. Each image is characterised by its features. It is believed that reducing the number of features can also reduce the cost. Therefore, a feature selection method called Chi-Square was also used. Solving this problem in face recognition using Fuzzy Kernel C-Means resulted in quite high accuracies.
Modeling The Number of Flood Occurrence in Indonesia in 2015 Using Poisson Regression Model
Authors: Savitri Febiyani Okky , Prita Wardhani Laksmi 
Published: May 2019

Abstract
The Poisson regression model is one of the regression models that can show the relationship between the Poisson distributed response variable with predictor variables through the regression parameter. In this paper, the number of flood occurrences in Indonesia in 2015 which is the count data using a Poisson regression model. To obtain the Poisson regression model of the number of flood occurrence are conducted using multicollinearity test on predictor variables, estimation of regression parameters, parameter test, and goodness of fit model test. The method used to estimate parameter values is the Maximum Likelihood Estimation method that is obtained from the iteration results using the Newton-Raphson iterative method. Based on the results of data processing, the Poisson regression model that is obtained for the number of flood occurrences shows that the average of the number of flood occurrences in Indonesia is affected by the number of tornado occurrences, the number of rainy days, and the sun exposure.
Development of trigonometric visualization concepts to increase the study motivations of SMK students
Authors: Isa Irawan Mohammad , Mukhlash Imam , Adzkiya Dieky , Darmadi  , Sanusi  
Published: May 2019

Abstract
The students of SMK Cendekia Madiun are not motivated to learn mathematics especially trigonometry because students do not understand the concepts. The alternative approach offered by the ITS and UNIPMA teams as a form of community service is to develop and apply visualization in learning. Activity implementation methods are adopted from research and development (R&D) methods, namely: initial analysis, development / implementation, and final analysis. The results of the activity addressed that visualization developed is quite effective to increase student’s learning motivation.
Modelling of Short Rate (β2) Parameter Diebold-Li Model Using Vasicek Stochastic Differential Equations
Authors: Sari Meylita , Putri Sndah R.M. , Wahyuningsih Nuri 
Published: May 2019

Abstract
Investment is the activity of investing or allocating money to earn some profit. There are several type of investments, one of which is bond. The interest rate of the bond is called a yield. A yield is considered as a representation of market expectations depends on interest rate movements according to market price at a certain time. The yield’s value will change following a stochastic process. Estimation of a short rate parameter (β
2) of a Diebold-Li model is conducted by applying a least square method. Then, the yield modeling is developed based on the estimated short rate parameter Diebold-li model (β
2) using Vasicek Stochastic Differential Equation. The final result is that modelling of short rate (β
2) parameter Diebold-Li model using Vasicek Stochastic Differential Equation generates prediction values that have a high level of accuracy by MAPE prediction value of 8.65%.
Designing sensor networks to resolve spatio-temporal urban temperature variations: fixed, mobile or hybrid?
Authors: Yang Jiachuan , Bou-Zeid Elie 
Published: May 2019

Abstract
The spatio-temporal variability of temperatures in cities impacts human well-being, particularly in a large metropolis. Low-cost sensors now allow the observation of urban temperatures at a much finer resolution, and, in recent years, there has been a proliferation of fixed and mobile monitoring networks. However, how to design such networks to maximize the information content of collected data remains an open challenge. In this study, we investigate the performance of different measurement networks and strategies by deploying virtual sensors to sample the temperature data set in high-resolution weather simulations in four American cities. Results show that, with proper designs and a sufficient number of sensors, fixed networks can capture the spatio-temporal variations of temperatures within the cities reasonably well. Based on the simulation study, the key to optimizing fixed sensor location is to capture the whole range of impervious fractions. Randomly moving mobile systems consistently outperform optimized fixed systems in measuring the trend of monthly mean temperatures, but they underperform in detecting mean daily maximum temperatures with errors up to 5 °C. For both networks, the grand challenge is to capture anomalous temperatures under extreme events of short duration, such as heat waves. Here, we show that hybrid networks are more robust systems under extreme events, reducing errors by more than 50%, because the time span of extreme events detected by fixed sensors and the spatial information measured by mobile sensors can complement each other. The main conclusion of this study concerns the importance of optimizing network design for enhancing the effectiveness of urban measurements.
Response of ecosystem intrinsic water use efficiency and gross primary productivity to rising vapor pressure deficit
Authors: Zhang Quan , Ficklin Darren L , Manzoni Stefano , Wang Lixin , Way Danielle , Phillips Richard P , Novick Kimberly A 
Published: May 2019

Abstract
Elevated vapor pressure deficit (VPD) due to drought and warming is well-known to limit canopy stomatal and surface conductance, but the impacts of elevated VPD on ecosystem gross primary productivity (GPP) are less clear. The intrinsic water use efficiency (iWUE), defined as the ratio of carbon (C) assimilation to stomatal conductance, links vegetation C gain and water loss and is a key determinant of how GPP will respond to climate change. While it is well-established that rising atmospheric CO2 increases ecosystem iWUE, historic and future increases in VPD caused by climate change and drought are often neglected when considering trends in ecosystem iWUE. Here, we synthesize long-term observations of C and water fluxes from 28 North American FLUXNET sites, spanning eight vegetation types, to demonstrate that ecosystem iWUE increases consistently with rising VPD regardless of changes in soil moisture. Another way to interpret this result is that GPP decreases less than surface conductance with increasing VPD. We also project how rising VPD will impact iWUE into the future. Results vary substantially from one site to the next; in a majority of sites, future increases in VPD (RCP 8.5, highest emission scenario) are projected to increase iWUE by 5%–15% by 2050, and by 10%–35% by the end of the century. The increases in VPD owing to elevated global temperatures could be responsible for a 0.13% year−1 increase in ecosystem iWUE in the future. Our results highlight the importance of considering VPD impacts on iWUE independently of CO2 impacts.
Remote sensing and GIS applications for sustainable food agricultural land mapping and supporting the preparation of regional spatial plans (case study of Badung Regency)
Authors: Lanya Indayati , Netera Subadiyasa N , Sardiana Ketut , Ratna Adi Gst P , Gunasih Made Tri 
Published: May 2019

Abstract
Local Government (LG) provincial and district/city in Bali until now does not have a Regional Regulation (RR) on determination of Sustainable Food Agricultural Land (SFAL). This is related to the provision of land for non-agricultural development permits. Map of SFAL has been established as a condition for the drafting and revision of the Spatial Plan (SP) [1]. Multi-analytical research methods: super impose analysis of thematic maps, ten thematic maps of physical and environmental conditions (river basin area, land use, irrigation, relief, rainfall, elevation, regional spatial planning, land suitability, productivity, and distance from city center) will be analysed and scored to numerically scoring (numerical classification), toolbox - analysis tools-overlay-intersect. Materials and tools: Quick Bird satellite images 2013 and QGIS software 10.3. Field survey to compile a data base of SFAL at each location. Map and data base SFAL obtained from the analysis of thematic maps of physical and environmental conditions. SFAL 9,642.76 ha was recommended for the revision of SP for 2013-2033; SFAL = 8,824.36 ha is recommended to reflect SP year 2034-2054 ha and 6,510.11 ha for the drafting of SP year more than 2055 location are in the. SFAL location are in the upstream and center (Petang, Abian Semal, and Mengwi District). Subak rice field that can be converted 829.41 ha – 3,143.66 ha is located in the districts of Kuta and Nort Kuta. Remote sensing and GIS technology can be used for SFAL mapping, through the classification of numerical thematic maps of the physical and environmental conditions of the region.
Landuse change analysis for hydrology response and planning management of Cibeet Sub-Watershed, West Java, Indonesia
Authors: Nugroho Setyo Pambudi , Handayani Luluk D W , Meidiza Riski , Munggaran Gilang 
Published: May 2019

Abstract
Cibeet Sub-watershed is located in downstream of Citarum watershed and categorized as Priority I. Landuse change is an environmental issue which causes of damageof that watershed ecosystem. Landuse change can also affect the hydrological conditions of the watershed. The results of the SWAT(Soil Water Assessment Assessment) model simulation in the Cibeet Sub-watershed used LISAT (LAPAN IPB Satellite) imagery show is KAT (Coeficient Run off) value is a very high (0.54). Based on landuse in RTRW (Regional Land Use Planning) West Java 2025 the value of KAT decreased to 0.49 in the high category. Application of Soil and Water Conservation (KTA) techniques to land use of the LISAT imagery 2017 by Water Infiltration Wells were able to reduce surface flow by 63.49% and KAT values to 0.4 medium categories.
Characterizing NO2in Indonesia Using Satellite Ozone Monitoring Instruments
Authors: Darmawan Trio Bagoes , Syafei Arie Dipareza 
Published: May 2019

AbstractIndonesia suffers from high annual vehicle ownership growth, resulting in worsening urban air quality. Nitrogen dioxide (NO2) is one of the combustion products of vehicles which needs to be monitored. Unfortunately, few cities have air quality monitoring stations, thus there is an immediate need to tackle this issue. One way to do so is by utilizing remote sensing via satellite. In this study, we utilized a satellite OMI (Ozone Monitoring Instrument) to read patterns in gaseous NO2concentrations. This work was assisted by a Geographical Information System (GIS) program, which used the results from the satellite to create images. Data validation was conducted by comparing the results from the satellite images in the form of color pixels with the results obtained from monitoring stations in Jakarta and Surabaya via linear regression. The results showed a weak correlation. Further research should introduce additional variables to improve accuracy.
Streamflow extreme value analysis using correlation of streamflow data with TRMM derivatives at Bone Watershed Gorontalo, Indonesia
Authors: Prakoso W G , Murtilaksono K , Tarigan S D , Purwanto Y J 
Published: May 2019

Abstract
Most recent studies that have attempted to use rainfall dataset for continuous modelling of rainfall-runoff have found that, without detailed local calibration against traditional rain-gauge measurements, the TRMM data is simply not accurate enough for that purpose. This is partly a result of the coarse spatial resolution of the dataset, with each grid cell being 0.25° x 0.25°, and partly to do with the inherent difficulty in remotely sensing rainfall intensity. For this study, however, it was decided to derive a more general rainfall parameter, the total amount of rainfall calculated to have fallen on each of the delineated catchments, processed as a mean annual total, (in m3), and to see how closely that was correlated with the streamflow data. Considering that most of the streamflow data available is from 2007 – 2010, TRMM V6 3B42 3 hourly data covering this four year period were used. Given the lack of long-term data both discharge and rainfall, at Bone Watershed, Gorontalo Province, Indonesia), the limitations of an Extreme Value Analysis using such a short data set must be stressed from the outset. Most data sets available comprise approximately 3 – 4 years of data, which are insufficient to provide reliable predictions of discharge events with large return periods. A satisfactory hidrological correlation could be achieved using catchments weighted time series of TRMM daily rainfall data after scaling, with streamflow data from Bone River (Alale and Tulabolo) to obtain a time series of simulated discharge. Realatively reliable extrema value estimation on the design flood parameter were produced with resasonable several limitation.
Prediction of potential fishing zones for yellowfin tuna (Thunnus albacares) using maxent models in Aceh province waters
Authors: Siregar E S Y , Siregar V P , Jhonnerie R , Alkayakni M , Samsul B 
Published: May 2019

Abstract
The exploitation of tuna in the Indian Ocean is increasing due to the high demand of its resources. This research aims to predict the fishing ground of the yellowfin tuna (Thunnus albacares) using Maximum entropy models (MaxEnt) based on oceanographic satellite data and tuna fishing data obtained from Aceh waters, from June-August 2015. The highest MaxEnt (AUC) model in the transition season 1 occurred in May with AUC values of 0.9612, followed by March (0.8200) and April (0.6780). The high AUC value shows the potential to know the spatial distribution of tuna yellowfin tuna which can be interpreted as the level of accuracy of the model produced. Environmental parameters have a major contribution to the prediction of tuna fishing ground. In March the SST variable (64.4%) had the largest contribution, followed by SSH (8.4%) and Salinity (7.2%). Then in April the SST variable (62.4%) also had the largest contribution, followed by SSH (22.9%) and Salinity (17.6%). Similar to May SST (60.5%) had the largest contribution, followed by SSH (12.6%) and Salinity (7.0%). Based on the Maxent model, potential fishing grounds in the transition season 1 of 2015 are found in the waters of north and south of the Aceh Province.
Speed acquisition system for reaction wheel of LAPAN-A3 Satellite using field programmable gate array module
Authors: Bahari G H Z , Khairunnisa  
Published: May 2019

Abstract
Reaction wheel is one of the important components in satellite attitude control by employing torque to satellite through command, resulting in the change of the angular momentum (or angular velocity) of the satellite. LAPAN-A3, the third-generation satellite built by LAPAN, utilizes three systems of reaction wheel placed on three coordinate axes. The system consists of two parts; electric motor and wheel drive electronic (WDE) to adjust the motor’s motion by reading input from control center. This research will implement the measurement of reaction wheel system by using field-programmable gate array (FPGA) as the processor. The outcome of this study is expected to obtain more accurate results and lower transient delays in acquiring the speed of wheel than that of generated input signal from PC.
Algorithm Enhancement of STELLAR on LAPAN-A4 Satellite
Authors: Saifudin Muhammad Arif 
Published: May 2019

AbstractThe first LAPAN’s experimental star sensor has onboard on LAPAN-A3/LAPAN-IPB microsatellite that successfully launch on June, 6 2016. The second LAPAN’s experimental star sensor called STELLAR has scheduled to be onboard on LAPAN-A4 satellite. In orbit test of first star sensor provide conclusions. One of the conclusion is the radiation in space has an impact on star sensor performance. Many hot pixels or hotspots appear on CCD sensor temporarily that it causes a failure of star identification since the hotspots are fake stars. In order to solve this problem, an enhancement of algorithm is conducted. The enhancement aims to ignore the fake stars to proceed as stars candidate. This method selects a cloud pixel as star candidate and proceed only clouds pixel. The algorithm was tested and give more reliable result of star identification.
Neuronlike impulses in a travelling wave structure loaded with resonant tunneling diodes and air bridges
Authors: Essimbi B Z , Stöhr A , Jäger I , Jäger D 
Published: June 2019

Abstract
In this paper a coplanar waveguide (CPW) periodically loaded with resonant tunneling diodes (RTDs) and air bridges (AB) is presented as a travelling wave (TW) structure for modelling the FitzHugh-Nagumo (FHN) equation and emulating the behaviour of the nerve axon. Based upon an electrical equivalent circuit, the principle of operation is discussed in the context of a lumped-element circuital model being compared to a distributed structure. The phenomena of wave formation and propagation are studied by computer experiments of the underlying nonlinear ordinary difference-differential equations (ODEs) and that of the approximated model nonlinear partial differential equations (PDEs). A key achievement is that this medium supports stable propagating shock waves (kinks and antikinks) when effects of AB are neglected as well as stable traveling pulses only determined by the parameters of the circuit. As a result, compact electronic circuits with features of real neural systems are developed to be an experimental medium mimicking neural activity and to be applied in ultra-fast signal processing.
Efficacy of Botulinum Toxin Type A in Improving Scar Quality and Wound Healing: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Guo Xiaoshuang , Song Guodong , Zhang Dong , Jin Xiaolei 
Published: June 2019

Abstract

Background
Botulinum toxin type A-induced “chemoimmobilization” has long been utilized for improved scar quality and wound healing; however, current evidence is limited to small studies, and evidence-based information is inadequate to make well-informed decisions.

Objectives
The purpose of this study was to evaluate the efficacy of botulinum toxin type A (BTA) to improve scars and wound healing.

Methods
The authors searched databases, including Pubmed, Embase, and Cochrane Library, to identify randomized clinical trials (RCTs) that compared outcomes of surgical scars and wounds treated with BTA vs those treated with blank or placebo controls. The Visual Analog Scale, Vancouver Scar Score, scar width, and reported patient satisfaction were utilized in evaluating outcomes. Adverse events were also recorded.

Results
Eleven RCTs involved a total of 486 cases (374 patients). Quantitative synthesis suggested that compared with the control group, patients in the BTA treatment group had significantly higher Visual Analog Scale scores (mean difference [MD] = 1.30, 95% confidence interval [CI]: 1.05 to 1.55), lower Vancouver Scar Scores (MD = −1.62, 95% CI: −2.49 to −0.75, P = 0.0003), and thinner scars (MD = −0.15, 95% CI: −0.20 to −0.11, P &lt; 0.00001). Patient satisfaction was higher in the BTA group than in the control group (risk ratio: 1.25, 95% CI: 1.06 to 1.49, P = 0.01). Trivial adverse events were reported.

Conclusions
This meta-analysis of RCTs provides reliable evidence that BTA injection is superior to placebo or blank control group in improving scar quality and wound healing in the face and neck for Asians, and negative outcomes for BTA treatment in these patients include only trivial adverse events. However, inadequate evidence supports utilization of BTA in Caucasians for primary surgical scars or for scars in locations other than the face and neck. Further studies on the standardized injection regimen and technique of BTA are warranted for clinical practice.

Level of Evidence: 1