bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection of passageways in natural foliage using biomimetic sonar
Authors: Wang Ruihao , Liu Yimeng , Müller Rolf 
Published: June 2022

Abstract
The ability of certain bat species to navigate in dense vegetation based on trains of short biosonar echoes could provide for an alternative parsimonious approach to obtaining the sensory information that is needed to achieve autonomy in complex natural environments. Although bat biosonar has much lower data rates and spatial (angular) resolution than commonly used human-made sensing systems such as LiDAR or stereo cameras, bat species that live in dense habitats have the ability to reliably detect narrow passageways in foliage. To study the sensory information that the animals may have available to accomplish this, we have used a biomimetic sonar system that was combined with a camera to record echoes and synchronized images from 10 different field sites that featured narrow passageways in foliage. The synchronized camera and sonar data allowed us to create a large data set (130 000 samples) of labeled echoes using a teacher–student approach that used class labels derived from the images to provide training data for echo-based classifiers. The performance achieved in detecting passageways based on the field data closely matched previous results obtained for gaps in an artificial foliage setup in the laboratory. With a deep feature extraction neural network (VGG16) a foliage-versus-passageway classification accuracy of 96.64% was obtained. A transparent artificial intelligence approach (class-activation mapping) indicated that the classifier network relied heavily on the initial rising flank of the echoes. This finding could be exploited with a neuromorphic echo representation that consisted of times where the echo envelope crossed a certain amplitude threshold in a given frequency channel. Whereas a single amplitude threshold was sufficient for this in the previous laboratory study, multiple thresholds were needed to achieve an accuracy of 92.23%. These findings indicate that despite many sources of variability that shape clutter echoes from natural environments, these signals contain sufficient sensory information to enable the detection of passageways in foliage.
Past and projected climate change impacts on heat-related child mortality in Africa
Authors: Chapman Sarah , Birch Cathryn E , Marsham John H , Part Chérie , Hajat Shakoor , Chersich Matthew F , Ebi Kristie L , Luchters Stanley , Nakstad Britt , Kovats Sari 
Published: June 2022

Abstract
Children (<5 years) are highly vulnerable during hot weather due to their reduced ability to thermoregulate. There has been limited quantification of the burden of climate change on health in sub-Saharan Africa, in part due to a lack of evidence on the impacts of weather extremes on mortality and morbidity. Using a linear threshold model of the relationship between daily temperature and child mortality, we estimated the impact of climate change on annual heat-related child deaths for the current (1995–2020) and future time periods (2020–2050). By 2009, heat-related child mortality was double what it would have been without climate change; this outweighed reductions in heat mortality from improvements associated with development. We estimated future burdens of child mortality for three emission scenarios (SSP119, SSP245 and SSP585), and a single scenario of population growth. Under the high emission scenario (SSP585), including changes to population and mortality rates, heat-related child mortality is projected to double by 2049 compared to 2005–2014. If 2050 temperature increases were kept within the Paris target of 1.5 °C (SSP119 scenario), approximately 4000–6000 child deaths per year could be avoided in Africa. The estimates of future heat-related mortality include the assumption of the significant population growth projected for Africa, and declines in child mortality consistent with Global Burden of Disease estimates of health improvement. Our findings support the need for urgent mitigation and adaptation measures that are focussed on the health of children.
Plant Distance Effect on Rice Cultivation System of Rice Intensification (SRI) Method on Tillers and Yield Numbers in East Sumba Regency
Authors: Nugroho B D A , Arif C , Nihayah B , Hapsari U , Suryandika F 
Published: June 2022

Abstract
SRI is known as a set of methods to increase the productivity of paddy fields by changing the management of yields, soil, and fertilizers/nutrients. The main components of using the SRI method include: transferring young seedlings, planting one seed per hole, wide spacing, keeping the soil moist and not stagnant, controlling weeds by manual weeding, and adding soil organic matter. The study aims to determine the number of SRI rice tillers based on different spacing treatments and their effect on yield productivity. The results of the two treatments of plant spacing, namely 30 x 30 cm (A) and 20 x 10 cm (B) based on statistical tests using the T-Test, showed no significant difference between the two treatments on the number of tillers produced. While the yield showed that treatment A produced 4.27 tons/ha and treatment B was 4.7 tons/ha, so it concludes that spacing (A) had higher crops than spacing (B).
Exploring the effect of different number of periods in Thailand natural rubber supply forecasting models
Authors: Pumkaesorn P , Paoprasert N H 
Published: June 2022

Abstract
To dates, many studies attempted to forecast the price of natural rubber while many others also attempted to forecast the amount. The objective of this study was to explore the effect of different number of periods used in various forecasting models for the amount of natural rubber in Thailand. Monthly data from the Office of Agricultural Economics in the years 2007-2019 were obtained. Then the data were classified into 12 data sets; each of which had different number of periods including 12, 24, 36, 48, 60, 72, 84, 96, 108, 120, 132 and 144 months. Decomposition forecasting methods consisted of the addition divide and the multiplicative divide methods were adopted. Model accuracy indicators were the mean absolute deviation, the mean square error and the mean absolute percentage error. The results showed that the amount of natural rubber and time were positively correlated at 99% confidence level. The most suitable model for forecasting the amount of natural rubber in Thailand found in our study was the multiplicative divide method by using the number of periods at 36 months yielding the mean absolute deviation of 66,264.61, the mean square error of 7,988,871,007.41 and the mean absolute percentage error of 24.66%.
Effect of Production Technique on Corncob Biochar Quality
Authors: Anika Nova , Mahardika Melbi , Panjaitan Jabosar Ronggur Hamonangan , Achmad Feerzet , Bindar Yazid , Azizah Intan N. , Anggraini Riska , Ramadhani Dhiya A. 
Published: June 2022

Abstract
Lampung Selatan Regency is one of the centers of corn production in Lampung, Indonesia. Along with the increase in corn production, the resulting corn biomass waste also increases. Corn biomass waste such as cobs can be utilized into more useful products such as biochar which is useful as a soil amendment. The purpose of this research was to evaluate the quality of biochar based on its production technique. The three biochar production techniques used were traditional soil pit, closed drum kilns, and open drum kilns.. The quality of biochar was determined by the temperature and period of the pyrolysis process, which was greatly influenced by the selected production technique. The results showed that the closed drum kiln technique produces biochar with better properties for increasing soil fertility because it produces the biochar with the highest fixed carbon and CEC.
Development Software to Evaluate Environmental Impact for Palm Oil (Elaeis guineensis Jacq) Industry using Life Cycle Assessment Approach in Indonesia
Authors: Siregar Kiman , Supriyanto  , Susanto Dwi , Setiawan Arief AR. , Sofiah Intan , Solihati  
Published: June 2022

Abstract
Palm oil in Indonesia are producing the Crude Palm Oil (CPO) with the highest export in the world. CPO production in Indonesia are increasing from 17,77 million to 31,49 million tons from 2013 to 2013 and still increases. Currently Indonesian government projected to use palm oil as source to produce biodiesel to replace the fossil fuel. However, to evaluate the production of biodiesel from palm oil should consider the environmental aspect. Life cycle assessment are appropriate tools to evaluate the overall productions environmental impact in palm oil industry. In this research, we proposed a software to life cycle assessment application in palm oil industry in Indonesia. The method was used in this study are prototyping that consist of the iteration analysis, design, coding and testing. The result of this study was the software to evaluate the environmental impact using life cycle assessment approach. Software was able to perform life cycle assessment activity such as goal scope definition, inventory data, life cycle impact assessment and interpretations.
Artificial Neural Network Models to Estimate Growth of Melon (Cucumis melo L.) at Vegetative Phase in Greenhouse with Evaporative Cooling
Authors: Erniati  , Suhardiyanto Herry , Hasbullah Rokhani , Supriyanto  
Published: June 2022

Abstract
Currently, melon is a high economic value product in Indonesia. To optimize the production of melon, cultivation in greenhouses equipped with evaporative cooling system is implemented in some locations. However, growth of melon in greenhouse with evaporative cooling is characterized by complexity in its relation with environmental parameters inside the greenhouse. Therefore, it is important to establish stochastic model to explain the relation between the growth of melon with environmental parameters inside the greenhouse. This paper presents an Artificial Neural Network (ANN) model to predict the growth of melon during vegetative stage of melon in a greenhouse with evaporative cooling in Bogor, Indonesia. Data was collected from October to December 2020 during vegetative stage of melon. The ANN model was developed using six input parameters that are air temperature (°C), air relative humidity (%), radiometric intensity of sunlight (watt/m2), plant age (day), leaf area (cm2), plant height (cm) to predict leaf area (cm2) and plant height (cm) for the next two days. The results showed that the designed seven hidden nodes-ANN model achieved a high prediction accuracy with R2 of 0.9 for leaf area validation and plant height validation.
Coconut shell bio-oil distillation: Its characteristic and product distribution
Authors: Amrullah Apip , Eko Teguh S. 
Published: June 2022

Abstract
The properties of bio-oil distillation and product distribution are critical for parameter optimization and reaction conditions. In this work, low-reaction temperature of 96, 97, 98, 99, and 100 °C was conducted. The slow pyrolysis process at 500 °C with a 1 hour holding period yielded the coconut shell bio-oil employed in this research. The characteristic components of bio-oil were thoroughly evaluated using gas chromatography-mass spectrometry (GC-MS). The research founded that during the distillation reaction process, a similar critical point was thoroughly established, which might be attributed to the steady system created by the hydroxyl group. As a result, bio-oil distillation might be divided into 3 stages: steady, explosive, and heating. The content of acetic acid, 2-Furancarboxaldehyde, and phenol are dominated. Acetic acid yield showed an increase, followed by the distillation reaction temperature. Phenol yield was also observed as a dominant product in the bio-oil. The higher phenol yield was observed at a temperature of 98 °C is 38 %. The observed phenomena could be related to the oxidation of hemicellulose, cellulose, and lignin to form phenol, the bio-major oil component. The specific distillation properties and product distribution provide a great look at the reaction process and component enrichment patterns, which can aid formulation and parameter adjustment.
Delignification of Cassava Peel as Bioethanol Raw Material using Combined Alkali and Microwave Heating Methods
Authors: Hartulistiyoso Edy , Farobie Obie , Zaky M 
Published: June 2022

Abstract
Indonesia is ranked fourth as the largest cassava producing country with a total production of around 20 million tons per year. As much as 15-20% per kilogram of cassava is waste in the form of cassava peel which contains starch and allows it to be converted into alternative energy such as bioethanol. The bioethanol production process is carried out through the stages of pretreatment (delignification) to obtain cellulose used in the hydrolysis process, hydrolysis, fermentation, and purification. This paper discussed the use of combined alkali and microwave heating methods to increase the cellulose content and reduce the lignin content of cassava peel. Delignification was carried out by varying the NaOH concentration of 0.5, 0.75, and 1 M and microwave exposure of 5, 10, and 15 min. The data of the pretreatment variation were statistically tested using a completely randomized design. The results shows that combined alkali and microwave heating methods was able to increase cellulose content from 39.78 to 59.01 %, decrease hemicellulose content from 24.75 to 12.79 %, and decrease lignin content from 23.28 to 14.66 %. The combination of 1 M NaOH and 15 min microwave exposure showed the best results.
Design and performance test of biodiesel reactor using hellical screw agitator and baffles
Authors: Wulandani D , Ibrahim Z A 
Published: June 2022

Abstract
Biodiesel reactor model using hellical screw agitator and baffles have been designed. The hellical screw type is chosen based on the agitation ability on viscous liquid with low energy, while baffles is purposed to generate homogeneous mixing. The objectives of the research was to obtained biodiesel reactor model and determined the best operation of reactor in producing biodiesel. Performance test of biodiesel reactor was done at 10 rotation speed levels of agitator, at range of 100 rpm until 1000 rpm. Biodiesel was produced by catalytical method, with 1.5 % w/w KOH catalyst at temperature ranging from 60 °C to 65 °C, for 60 minutes. The research obtained the model of cylindrical biodiesel reactor with the height of 300 mm and 168 mm diameter. The helical screw agitator has 4 screws and is equipped 4 baffles installed at the reactor wall. Based on the saponification value analysis, the biodiesel contained 99 % w/w methyl ester. The best operation of biodiesel production is resulted at 100 rpm which fulfil the quality standard of biodiesel and has the lowest energy consumption.
Comparison of engine performance and emissions for fuels of diesel-biodiesel blends and pure biodiesel
Authors: Firdaus NK , Aunillah A , Wardiana E , Pranowo D , Herman M , Syafaruddin  
Published: June 2022

Abstract
Biodiesel is a substitute or replacement petroleum diesel fuel used to reduce pollution without modifying engines. This study aimed to investigate the engine performance and emissions characteristics of a passenger car engine (Hilux 2.4G Double cabin (4x4) M/T) fuelled by two different fuels, which is biodiesel (B100) and diesel-biodiesel fuel blend (B20). The study was conducted at the Bioenergy Laboratory of Balittri, the Thermodynamics and Propulsion Engine Research Center of BPPT, and the Research Center for Oil and Gas Technology Development (LEMIGAS), from November 2019 to February 2020. The result showed that the traction and power for diesel-biodiesel fuel blends were obtained slightly higher than biodiesel. Biodiesel has marginally higher fuel consumption than diesel-biodiesel fuel blends. According to the emission analysis, biodiesel produces lower exhaust emissions of unburned fuel emissions, carbon monoxide, and carbon dioxide content in the exhaust gas than diesel-biodiesel fuel blends.
Development of a real-time wireless sensor network-based information system for efficient irrigation of upland and lowland crop production systems
Authors: Ramirez R C , Agulto E S , Glaser S D , Zhang Z , Hermocilla J A C , Ella V B 
Published: June 2022

Abstract
This study developed a real-time web-and WSN-based information system for efficient irrigation water management and automation of drip-irrigated upland crop and intermittently-irrigated lowland crop production systems. The web-based system uses Flutter and DART to accommodate multiple end user platforms, while the WSN-based system uses state-of-the-art hardware and sensors for real-time monitoring of soil moisture, water level and weather conditions. The sensors are wirelessly connected in a low-power mesh network that sends data to a central server. The sensor readings are uploaded to the web application via MQTT, which generates charts and graphs for data analysis. The sensor readings compared well with measurements from conventional instruments. The system in this study provides a sustainable solution for improving irrigation efficiencies under both upland and lowland crop production systems, in minimizing water losses and in improving the overall agricultural crop productivity.
Development of Low-cost Soil Moisture Monitoring System for Efficient Irrigation Water Management of Upland Crops
Authors: Aringo M Q , Martinez C G , Martinez O G , Ella V B 
Published: June 2022

Abstract
With the advancement of information and communication technology, various types of soil moisture sensors have been developed. Coupled with data loggers, these sensors could prove useful in monitoring soil moisture in upland crop production areas which in turn could be used for efficient irrigation water management. However, most of these sensors are costly and unaffordable to most farmers in developing countries. Hence, a low-cost soil moisture monitoring system intended to facilitate irrigation water management in upland crop production systems was developed in this study. The device was built with a capacitive soil moisture sensor, an ESP8266 Wi-Fi mini board, and a datalogging shield with RTC. Soil moisture measurements are transmitted via ESP-NOW to a server which also uses an ESP8266 Wi-Fi mini board. The low-cost soil moisture monitoring system was evaluated based on its measurement of volumetric water content and transmission of data via ESP-NOW. The performance of the capacitive soil moisture sensor was compared with the ICT International MP306 soil moisture sensor. Statistical analyses showed that volumetric water contents measured by the capacitive soil moisture sensor are comparable to those of the MP306 soil moisture sensor, thus conceived as a low-cost alternative to the high-end sensor. Moreover, test results on the range of ESP-NOW showed that data can be successfully transmitted over long distances. With regards to this, the low-cost soil moisture monitoring system may be integrated with other technologies to enable irrigation scheduling and automation for efficient irrigation water management in upland crop production systems.
Discrimination between arabica and robusta coffees using NIR-integrating sphere spectroscopy coupled with hierarchical clustering analysis
Authors: Suhandy D , Kusumiyati  , Yulia M 
Published: June 2022

Abstract
In Indonesia, coffee farmers preferred to produce arabica and robusta coffee. Regarding its superior quality and commercial values, now the demand for specialty arabica and fine robusta coffee is increasing. In this research, discrimination between the two coffees was evaluated using NIR-integrating sphere spectroscopy coupled with the hierarchical clustering analysis (HCA) method. NIR spectral data in the region of 1175-1650 nm was measured using a portable fiber optic NIR spectrometer equipped with an integrating sphere from Ocean Optics (NIR-Quest, Ocean Optics, USA). Arabica (n=10) and robusta (n=10) ground roasted coffee (with mesh 50) was prepared as samples. The principal component analysis (PCA) and hierarchical cluster analysis (HCA) were utilized in data analysis to discriminate between the specialty arabica and fine robusta coffee samples. The PCA and HCA results confirmed the good separation between the two coffees with arabica and robusta coffee samples were grouped in two distinct clusters. This result reveals that NIR-integrating sphere spectroscopy seems to be a potential analytical method dedicated to the discrimination of arabica and robusta coffee with minimum sample preparation.
Assessment of Water Availability for Rice Cultivation in South Lampung Regency
Authors: Anika N. , Wijaya L. , Ramadhani D. A. , Fauzi A. I. 
Published: June 2022

Abstract
Climatic conditions influence the availability of water for rice cultivation. Climate change will significantly impact rice production in areas where water resource infrastructure is inadequate. South Lampung Regency is primarily a rain-fed rice production region. As a result, an assessment of water availability for rice cultivation is required for sustainable rice production. This study aims to provide recommendations to the government in carrying out the necessary infrastructure development. This study uses secondary data such as rainfall, temperature, solar radiation, evaporation, and humidity from 2010 to 2020. The study’s findings provide information on the sufficiency of water availability for rice cultivation in each sub-district in the South Lampung Regency, as well as scenarios for developing water resources infrastructure.
Estimating the ripeness level of avocado (Persea americana) by using ultraviolet reflection
Authors: Bayu M F , Pertiwi S 
Published: June 2022

Abstract
Avocado (Persea americana) is one of popular fruits in Indonesia because of its taste and high antioxidant content. However, research on avocado in Indonesia is still limited. Grading avocados is still undertaken manually by squeezing the fruit to find its hardness and determine the ripeness level while it is already well known that image processing may play an important role in maintaining consistency in grading fruits. This study aims to determine the ripeness level of avocado by using Total Dissolved Solids (TDS), moisture content, and hardness as the parameters, and to determine the correlation between the ultraviolet (UV) reflection and the ripeness level of avocado. The study consists of non-destructive method and destructive method. The first was done by taking pictures/images of avocados surrounded by 4 UV lamps using a Digital Single Lens Reflex (DSLR) camera. There were 120 samples of avocado fruit with 4 levels of ripeness, 30 each, which were obtained from the Puncak area, Bogor. Immediately after completing the image taking, the destructive method was carried to determine the TDS, moisture content, and hardness of each sample. The lab test results were then used to obtain an equation that estimates the ripeness level, expressed in age (days) before ripening, by using multiple linear regression analysis. The resulted equation is having R-Square of 0.81, which mean that the parameters can be used to determine the ripeness level. The image data were processed further to get the values of Hue (H), Saturation (S) and Intensity (I) at each ripeness level, and from those values their determination coefficient which show the feasibility of the value to represent the ripeness of the avocado were determined. The result shows that the highest determination coefficient was that of I (intensity) of about 0.8191. The results of non-destructive and destructive method then was correlated each other to show the feasibility of using nondestructive method in estimating the ripeness level of avocado. The result shows that the usage of UV reflection, especially the value of intensity, for determining the ripeness level of avocado is feasible.