bluuebunny/crossref_metadata_2025 huggingface dataset:
Flash-based in-memory computing for stochastic computing in image edge detection
Authors: Sun Zhaohui , Feng Yang , Guo Peng , Dong Zheng , Zhang Junyu , Liu Jing , Zhan Xuepeng , Wu Jixuan , Chen Jiezhi
Published: May 2023

The “memory wall” of traditional von Neumann computing systems severely restricts the efficiency of data-intensive task execution, while in-memory computing (IMC) architecture is a promising approach to breaking the bottleneck. Although variations and instability in ultra-scaled memory cells seriously degrade the calculation accuracy in IMC architectures, stochastic computing (SC) can compensate for these shortcomings due to its low sensitivity to cell disturbances. Furthermore, massive parallel computing can be processed to improve the speed and efficiency of the system. In this paper, by designing logic functions in NOR flash arrays, SC in IMC for the image edge detection is realized, demonstrating ultra-low computational complexity and power consumption (25.5 fJ/pixel at 2-bit sequence length). More impressively, the noise immunity is 6 times higher than that of the traditional binary method, showing good tolerances to cell variation and reliability degradation when implementing massive parallel computation in the array.
Multi-Resolution Patch Algorithm for Detection of Non-Small Cell Lung
Authors: Arkah Zinah Mohsin , Alwan Jwan K. , Al-Jumaily Abdulmajeed
Published: May 2023

Today’s healthcare system relies heavily on medical imaging to carry out non-invasive diagnostic treatments. For clinical analysis, it entails the development of graphical and functional models of the human body and organs. In order to diagnose non-small cell lung cancer, the Multi-resolution patch (MSP) approach is introduced in this study. The model can enhance detection performance by utilizing an atrous convolution network, however caution must be used while selecting the atrous rate. More data from many institutions is needed to improve the generalization of the model because the validation CT data was only collected at one center; this dataset included lung CT imaging data from healthy individuals. The outcome indicates that the model’s performance can be further enhanced by include data from healthy individuals in the training process. Additionally, two sets of experiments show the value of the pre-processing module and the superiority of the suggested network.
A novel two-stage Lung nodule detection in medical images based on deep learning
Authors: Ahmed zwaid Jassim Mohammed , Murad Masrah Azrifah Azmi , Khalid Fatimah binti , Manshor Noridayu
Published: May 2023

In order to solve the problems of low detection rate and high false positive of nodules in lung CT images by traditional computer-aided diagnosis systems. This paper introduces the real-time detection algorithm of medical images using the deep learning method. According to the three-dimensional nature of lung CT images, 3DFasterR-CNN is used to extract features to detect candidate nodules; then, the 3D convolutional neural network is used to remove false positive nodules. That saves the operation of filtering and difference map construction. The detection process mainly includes four steps: building a deep neural network, constructing suitable samples, training the network, and detecting. The results show that the algorithm has a good effect on the real-time change detection of medical images and can improve detection accuracy and efficiency. The average FROC value was 82.8%, compared with the traditional diagnosis and treatment. The recognition rate of the method has been significantly improved. The model can be used to assist doctors in diagnosing lung nodules and has a certain clinical application value.
Medical Image Analysis of Lung Tumor Diagnosis Based on Generalized Fuzzy C-Means Clustering Algorithm
Authors: zwaid Jassim Mohammed Ahmed , Murad Masrah Azrifah Azmi , Khalid Fatimah binti , Manshor Noridayu , Al-Jumaily Abdulmajeed
Published: May 2023

In recent years, the rapid development of medical imaging technology has brought medical image analysis into the era of big data. CT imaging technology is one of the most common imaging methods for disease screening. This paper introduces medical image analysis of lung tumor diagnosis based on Generalized fuzzy c - means clustering algorithm was proposed. Brief introduce lung CT imaging to diagnose lung tumors requires a huge workload, which is often accompanied by long-term image reading and subjective evaluation. The experimental data comes from 15 patient samples which include two groups of samples are selected as test objects. The result shows the positive rate is high, resulting in misdiagnosis. In addition, great success of deep learning technology in the field of computer vision has made it possible to realize computer-aided diagnosis and screening of lung cancer.
A Non-Intrusive Load Decomposition Method Based on Generative Adversarial Networks and Asynchronous Federated Learning
Authors: Wang Dan , Fan Kaiyu
Published: May 2023

The non-intrusive load decomposition method is an essential approach of appreciating the water requirements of consumers. Traditional techniques of load breakdown have a number of drawbacks, including a poor level of water identification precision. In order to do this, a model for load decomposition based on generative adversarial networks has been developed. By applying a convolutional autoencoder to the total power noise, the generative network constructs the power breakdown sequence of the given home appliance. The discriminant network is then utilized to determine whether or not the created sequence is legitimate. In order to achieve a more natural and authentic sequence, the participants compete against one another. In light of the shortcomings of the centralized model training method, the network model implementation scheme based on asynchronous federated learning is utilized to replace the traditional convolution in order to realize the model’s lightweight nature. This allows the model to be applied to terminal devices such as smart water meters, and it is carried out in a cloud-edge collaborative manner. In addition, the model is carried out in a manner that is collaborative between the cloud and the edge. Training not only eases the strain of communication transmission but also protects the privacy of users and the integrity of their data.
Roller Bearing Fault Diagnosis Using Deep Transfer Learning and Adaptive Weighting
Authors: Liu Yan , Fan Kaiyu
Published: May 2023

A fault diagnosis approach for roller bearings utilizing deep transfer learning and adaptive weighting is suggested to address the issue that extra fault state samples in the target domain data of roller bearings impair the fault diagnostic accuracy. CNN-LSTM is a network model proposed by Lecun et al., which has good performance in image processing and image processing. It can effectively apply predictive local perception of time series and weight sharing of CNN, which can greatly reduce the number of networks and improve the efficiency of model learning. The method first establishes a feature extraction module, and uses a deep convolutional neural network to map bearing samples to a high-dimensional feature space. Secondly, uses the transfer learning concept to design a weighted domain discriminator, and adaptively weights the samples; and finally, through the confrontation in the feature space, the bearing samples are classified. Training to increase the domain similarity of the healthy state samples shared by the target domain and the source domain. Then measuring the similarity between these samples based on the sample weight size, and setting a threshold to label the additional fault state samples of the target domains as unknown. The suggested technique is validated using gearbox bearing data, roller bearing data from Case Western Reserve University, and locomotive wheel bearing data. The diagnostic accuracy of the samples is less than 80%, suggesting that the suggested approach can successfully overcome the effects of extra fault state samples and diagnose roller bearing faults.
Dynamic collaborative optimization coverage algorithm of UAV based on trajectory prediction in Internet of Vehicles
Authors: Zheng Maoxing , Hai Tao
Published: May 2023

This research presents a dynamic pre-deployment strategy based on vehicle trajectory prediction information to address the issues of coverage gaps of base stations and local traffic congestion in urban vehicle networking. Under the architecture of distributed federated learning and blockchain, numerous UAVs equipped with edge computing servers eliminate the central aggregation node and use an enhanced Raft method to train a unified Seq2Seq-GRU trajectory prediction model. In the training cycle, the scheme selects the nodes to perform parameter aggregation and model update based on the quantity of data given. Second, based on the model’s prediction findings, this study offers an enhanced virtual force guide deployment method that directs the UAV to dynamically deploy across each virtual force in order to increase the vehicle’s access rate and communication quality.
Three-phase fault analysis of power system transient stability based on TCSC controller using FPA for its location
Authors: Otuo-Acheampong Duku , Rashed Ghamgeen Izat , Mensah Akwasi Amoh , Haider Hussain
Published: May 2023

Preventing the power system from becoming overloaded and under stress to the point where it is on the verge of reaching the limits of its transient stability due to high power consumption. This paper proposed the dynamic security assessment for transient stability using Thyristor controlled series capacitor (TCSC) devices controller. The stability criteria are based on the severity indices for analyzing the fault in the power system. The index uses the time domain analysis simulation, making it easier and simpler to implement for the system operators to better prepare for potential disturbances by anticipating how power systems will behave. The optimal location and parameters setting of the TCSC was determined by Flower Pollination Algorithm (FPA) due to its higher convergence rate. The proposed index is tested on the IEEE 14-bus system and further discusses the effect of a three-phase short circuit fault, different fault locations, and fault clearing method. An analysis is done to determine how the short circuit faults on lines affect the transient voltage stability of the load bus and generator bus in the system. The findings show that by employing TCSC, the voltage drop was acceptable improved and stability margins were greatly increased.
Vibration Signal for Bearing Fault Detection using Random Forest
Authors: Abedin Tarek , Koh S. P. , Yaw Chong Tak , Phing Chen Chai , Tiong Sieh Kiong , Tan Jian Ding , Ali Kharudin , Kadirgama K. , Benedict F.
Published: May 2023

Based on the chosen properties of an induction motor, a random forest (RF) classifier, a machine learning technique, is examined in this study for bearing failure detection. A time-varying actual dataset with four distinct bearing states was used to evaluate the suggested methodology. The primary objective of this research is to evaluate the bearing defect detection accuracy of the RF classifier. First, run four loops that cycle over each feature of the data frame corresponding to the daytime index to determine the bearing states. There were 465 repetitions of the inner race fault and the roller element fault in test 1, 218 repetitions of the outer race fault in test 2, and 6324 repetitions of the outer race in test 3. Secondly, the task is to find the data for the typical bearing data procedure to differentiate between normal and erroneous data. Out of 3 tests, (22-23) % normal data was obtained since every bearing beginning to degrade usually exhibits some form of a spike in many locations, or the bearing is not operating at its optimum speed. Thirdly, to display and comprehend the data in a 2D and 3D environment, Principal Component Analysis (PCA) is performed. Fourth, the RF algorithm classifier recognized the data frame’s actual predictions, which were 99% correct for normal bearings, 97% accurate for outer races, 94% accurate for inner races, and 97% accurate for roller element faults. It is thus concluded that the proposed algorithm is capable to identify the bearing faults.
UAV-based edge computing system used in energy-saving offloading method
Authors: Abdulazeez Hussein Amer , Shaker Ahmed Maher
Published: May 2023

This paper proposes an offloading strategy based on unmanned aerial vehicle (UAV) managed computer resources to provide dependable communication and intensive processing power in complicated terrain. In order to reduce compute and offload user terminal energy consumption, a UAV-assisted edge computing model is built, taking into account the computing requirements of user terminals, the delay restrictions of computing jobs, and the energy limits of UAVs. The trajectory can be used to reduce the user terminal’s energy usage in the allotted amount of time. The simulation results demonstrate that the suggested approach is appropriate for various channel circumstances, allowing the user terminal to accomplish the work while outperforming existing benchmark systems in terms of energy usage. Optimizing the flight trajectory of the UAV will have a substantial impact when the signal-to-noise ratio SNR=20dB. The results demonstrate that, at T=5s, the UAV’s flying trajectory optimization strategy reduces energy consumption by 56.26%.
Novel cartographer using an OAK-D smart camera for indoor robots location and navigation
Authors: Han Yunpeng , Ali Mokhtarzadeh Amir , Xiao Shaozhang
Published: May 2023

In recent years, service robots have been widely used in people’s daily life, and with the development of more and more intelligence, people put forward higher requirements for autonomous positioning and navigation functions of robots. Like outdoor navigation, indoor navigation also needs the support of navigation data. Although the indoor positioning and navigation scheme based on cameras, lidars and other sensors is gradually developing, due to the complexity of the indoor structure, manual production of indoor navigation data is time-consuming and laborious, and the efficiency is relatively low. In order to solve the problem of low productivity and improve the accuracy of robot automatic navigation, we added a new type of intelligent camera, called OpenCV AI kit or OAK-D, and proposed a method to automatically build data files that can be used for indoor navigation and location services using indoor 3D point cloud data. This intelligent camera performs neural reasoning on chips that do not use GPUs. It can also use stereo drills for depth estimation, and use 4K color camera images as input to run the neural network model. Python API can be called to realize real-time detection of indoor doors, windows and other static objects. The target detection technology uses an artificial intelligence camera, and the robot can well identify and accurately mark on the indoor map. In this paper, a high-performance indoor robot navigation system is developed, and multisensor fusion technology is designed. Environmental information is collected through artificial intelligent camera (OAK-D), laser lidar, and data fusion is carried out. In the experiment part of this paper,The static fusion map module is created based on the laser sensor information and the sensor information of the depth camera, the hierarchical dynamic cost map module is created in the real-time navigation, and the global positioning of the robot is realized by combining the word bag model and the laser point cloud matching. Then a software system is realized by integrating each module. The experiment proves that the system is practical and effective, and has practical value.
Probabilistic Analysis of RC Buildings Based on Incremental Dynamic Analysis
Authors: Mathews Merin , Jayalekshmi B R , Venkataramana Katta
Published: May 2023

Earthquake is a natural disaster that can induce immense damage to properties and human lives. Fragility curve, defined as the probability of reaching or exceeding a specific damage state under an earthquake excitation, provides a prediction of damage that may occur during an earthquake. Incremental Dynamic Analysis Curve (IDA curve) developed from Incremental Dynamic analysis can be considered as the initial step of fragility curve development. The present study summarises the development of IDA curve for a RC building considering maximum roof displacement and storey drift as Damage Measure (DM) and peak ground acceleration as Intensity Measure (IM). The fragility curves developed using incremental dynamic analysis provide an overview of the probability of exceedance of damage limits in an existing building when acted upon by different levels of earthquake excitations and the performance level can be improved by incorporating appropriate design changes.
Mechanical and Microstructure Properties of Plain and Blended Cement Structural Lightweight Aggregate Concrete Using Sintered Fly Ash Aggregates
Authors: Dhemla Pankaj , Somani Prakash , Satankar Raj Kumar , Swami B L
Published: May 2023

Infrastructure and industry have grown dramatically as a result of globalization and urbanization. However, there are certain challenges, such as meeting infrastructural needs that require a large amount of extraction of natural aggregates and disposal of waste generated as a result of industrialization. Both of these challenges have an adverse impact on the environment. Deforestation, erosion, contamination of nearby streams, and increase in noise, dust, and emissions are all consequences of aggregate extraction. The industrial waste can contaminate groundwater, lakes, streams, rivers and coastal waterways and harm the land and neighboring water bodies. Hence these challenges must be addressed as a priority for environmental sustainability. The current study developed structural lightweight aggregate concrete (SLWAC) using sintered fly ash aggregate (SFA). The investigation was done with the use of different binders such as Portland Pozzolana Cement (PPC), Ordinary Portland Cement (OPC), and Micro Fibre Cement (MFC). The present study explores the suitable binder to produce SLWAC at different water-cement ratios of 0.4, a0.44, and 0.48. The performance evaluation of SLWAC was investigated by mechanical behavior like compressive strength, split tensile, flexural strength, and impact test. Microstructure analysis is also included in this study to validate the mechanical experiment results. SLWAC made from OPC shows more mechanical strength than PPC and MFC, due to faster hydration and early strength gain. SLWAC made from microfiber cement, has more strength as compared to PPC. This could be due to fibers in MFC, acting as a reinforcing agent, which reduces micro cracks. The microstructure of SLWAC shows that the wall effect does not exist in SLWAC compared to normal aggregate concrete. It has a uniform and continuous microstructure of hydration products and partially penetrates the SFA. It could be associated with the superior interfacial transition zone having a lower w/c ratio because of the higher absorption of SFA. The findings show that all developed SLWAC can be used in structural members like beams, columns, and slabs.
A Comparative Study on Dynamic Response of Buildings Resting on Coir and Rubber mat Reinforced Soil Bed
Authors: Sreya M V , Jayalekshmi B R , Venkataramana Katta
Published: May 2023

Geotechnical seismic isolation has emerged as an efficient technique for mitigating the severe effects of earthquakes by providing smooth synthetic liners beneath foundations or between soil layers for dissipating seismic energy through sliding. This study investigates the efficacy of using a rubber mat and a natural coir mat as reinforcement materials within the soil to act as a seismic soil-isolation medium. A three-dimensional finite element simulation of five-storey buildings resting on raft foundations in soft soil with and without the soil-isolation mechanism has been performed. The reinforced soil-structure system was exposed to two different earthquake motions, such as the ground motions corresponding to the elastic design spectrum for Zone III as per the Indian standard code (IS 1893 (Part 1): 2016) and the Northridge earthquake (1994). The proposed study deals with the analysis of dynamic responses of buildings when the soil is reinforced with a coir mat and rubber mat under earthquake motions. The findings show that the seismic responses of low-rise buildings are significantly reduced by a novel technique proposed in this work to reinforce the soil with isolation materials in their mat form to reduce the seismic responses under earthquake loads.
Characterization of rhizobacteria secondary metabolites on maize (Zea mays) in marginal land
Authors: Ikhwan A , Septia ED , Sholihah A
Published: May 2023

Maize is one of the strategic food crops and has economic value and could be developed because of its position as the main carbohydrate and protein source after rice. This could be a reference for us to increase maize cultivation, seeing the role of maize is quite large, and the availability of maize is less stable every year. maize can grow optimally on productive land and marginal land, but at this time more productive land is used for rice production. One alternative for maize production is on marginal land especially dryland. The main problem in dryland is limited water. One way to overcome this is by inoculating Rhizobacteria which can increase the growth and resistance of maize to drought. Rhizobacteria possess tremendous potential for modulating the physiological response to water deprivation, thus ensuring plant survival under such stressful conditions. The research aimed to find rhizobacteria have secondary metabolite for resistance to drought. Rhizobacteria exploration and secondary metabolite isolation was conducted at University of Muhammadiyah Malang. The research results have obtained 10 isolates capable of synthesizing extracellular secondary metabolites: osmoprotectants, phytohormones, and organopesticides that can be used by plants. The results of the analysis by GS-MS (Gas Chromatography-Mass Spectrometry) rhizobacteria showed that three compounds were synthesized. The osmoprotectants compound synthesize ware found namely: (a) (2E)-3,7-dimethylocta-2,6-dienal 16.66%;(b) (E)-hept-2-enal12.55%;(c)2-methylsulfanylethanamine 5.34%; (d) 1,3,5-trimethoxybenzene 4.42%. It is also capable of synthesizing phytohormones: (a) cinnolino [4,3-b] quinoxaline 6.00%; (b) 1-methyl-2-phenylindole 5.90%; (c) 1H-Indole 3.64%; (d) N-2-Fluorenylperfluorpropionamid 3.02%. These rhizobacteria were also able to synthesize: (a) 2-chloro-4-methoxy phenol 11.32%; (b) (E)-non-2-enal 9.87%; (c) 4-chloro-2,6-dipyridin-2-ylpyridine 7.07%; (d) 2-(4-chlorophenyl) hexane nitrile 6.45%. The Osmprotectant compounds aim to protect cells from drought conditions, phytohormones to stimulate plant growth and organopesticides to overcome pests and diseases.
Corn (Zea mays L.) productivity in acid dry land used zigzag planting method
Authors: Meithasari D , Endriani  , Wibawa W , Suretno N D , Tambunan R D
Published: May 2023

Zigzag planting method technology was an alternative technology to increase plant population without affecting plant growth and development. The purpose of this study was to determine the productivity of corn with different planting methods, such as the zigzag and the linear planting method applied by farmers on acid dry land in the Lampung area. The research was conducted at the Natar Experimental Station in Negara Ratu Village, Natar District, South Lampung Regency, Indonesia from March to June 2020. The study used a two-factor randomized block design, namely the hybrid corn varieties (NK Sumo, NK 22 Jumbo, and NK Super) and the planting methods (zigzag and linear planting methods). Observations were made on ten plants per sampling plot, which were determined randomly. The results showed that the zigzag planting method produces a higher yield (8.16 tons/ha) compared to the linear planting method (4-5 tons/ha grain yield). Moreover, the zigzag planting method increased the plant population by 80% without disturbing plant growth and development. The zigzag planting method was able to increase corn production by 30-40%.
The utilization of apical rooted cuttings for the seed production of potato varieties for processing
Authors: Handayani T , Kusmana  , Sahat J P , Pertiwi M D , Waryat
Published: May 2023

Potato development, especially processing varieties, is constrained by the availability of seeds. Acceleration of seed supply can be done by planting apical rooted cuttings directly in the field to obtain seeds equivalent to extension seeds class. Field activity has been carried out in Brebes Regency, Central Java, in 2021, to study the opportunities for using apical rooted cuttings in the potato seed production. Apical rooted cuttings from seven potato varieties for processing purposes (i.e. AR 08, Spudy, Ventury Agrihorti, Golden Agrihorti, Medians, and Atlantik M) were transplanted in a completely randomized design with 4 replications. Plant growth and tuber production characters were influenced by genotypic factor, indicated by the variation of those characters between varieties. The tuber number per plant ranged from 8.53 (Medians) to 22.80 (Spudy). Meanwhile, the tuber weight per plant was between 215.13 g (Golden Agrihorti) to 702.67 g (Spudy). In this study, Spudy showed the highest growth performance and tuber production compared to the other six varieties. In general, plants grown from apical rooted cuttings produced tuber which is appropriate for seed purposes. It is hoped that the apical rooted cuttings can support the sustainability of potato production, and furthermore, support the domestic potato-based industry.
Effect of Different Types of Medium and Fertilizer on Acclimatization of Vanda tricolor
Authors: Rineksane I A , Nu’imah M N K , Astuti A
Published: May 2023

Vanda tricolor is an orchid endemic to Mount Merapi whose existence is threatened by the eruption of Mount Merapi which can occur at any time and the community has taken it directly from nature. Several attempts have been made to preserve the Vanda tricolor orchid, one of which is through in vitro culture. In vitro culture studies of Vanda tricolor have been carried out and large numbers of shoots have been obtained through multiplication and then raised by subculture. Plantlets obtained must be acclimatized to adapt and be returned to their original habitat. Growing medium and fertilizer application are important factors in the acclimatization process. This study aims to determine the best type of medium and fertilizer for acclimatization of Vanda tricolor orchids. This research was conducted using an experimental method in the preparation of a Factorial Completely Randomized Block Design. The first factor is the type of medium, namely coconut husk, moss and coconut husk + moss, the second factor is the type of fertilizer, namely without fertilizer, foliar fertilizer and liquid organic fertilizer. From the two treatment factors, 9 treatment combinations were obtained. Each treatment was repeated 3 times and each replication consisted of 3 samples. The results showed that there was a mutual influence between the type of medium and fertilizer. The coconut husk + moss is the best medium for acclimatization of Vanda tricolor orchids. Meanwhile, foliar fertilizer and liquid organic fertilizer compared to without fertilization, can increase the growth of Vanda tricolor orchids during acclimatization.
Effectiveness of Eucalyptus Nano Formulation against Phytophthora capsici the Causal of Foot Rot Disease on Black Pepper
Authors: Noveriza R , Manohara D
Published: May 2023

Nanoemulsion is a form of nano pesticide that has been widely developed as a pesticide. Several reports state that the main compound contained in Eucalyptus essential oil, namely 1,8 cineol (C10H18O) or Eucalyptol can inhibit the growth of bacteria and fungi. The objective of this study was to assess the effectiveness of two types of Eucalyptus oil formulations with nano scale on the growth of the fungus Phytophthora capsici in vitro. This study was conducted in the plant pathology laboratory, at Indonesian Spices and Medicinal Crops Research Institute (ISMCRI), from January 2021 to June 2022. Chemical analysis of eucalyptus oil formulations with nano scale using Gas Chromatography and Mass Spectroscopy methods. The antifungal assay was carried out by adding a formulation with a specific concentration on Potato Dextrose Agar (PDA) medium and measuring its effect on the growth of P. capsici. The result showed that the particle size of the two eucalyptus oil formulations with nano scale range between 139.87-150.4 nm. The main chemical components of Nano E. urophylla West Java (NE-JB) are alpha-Pinene (13.92%), Eucalyptol (29.17%), p-Cymene (6.03%), and glycerin (20.45%). In contrast, Nano E. grandis North Sumatra (NE-SU) consisted of (1R)-2,6,6-Trimethylbicyclo [3.1.1]hept-2-ene (17.80%), Eucalyptol (10.90%), p-Cymene (6.50%), L-alpha Terpineol (6.69%), and glycerin (39.67%). The NE-SU formulation showed the ability to inhibit the growth of P. capsici better than NE-JB. The percentage inhibition of NE-SU at the 1.5% concentration was 91.47% while NE-JB was only 33.5%.
The adaptation new superior varieties and planting ways to arthropode diversity and rice yields
Authors: Resiani N M D , Sutami N P , Kamandalu A A N B
Published: May 2023

The impact of climate change is the biggest challenge for the agricultural sector, especially the food crops sub-sector. The research was conducted in Jembrana Bali. The aim was to obtain new high yielding varieties of rice and location-specific adaptive planting methods. The research time April - August 2021. Used a factorial randomized block design. The first factor consists of the type of variety (V) and the second factor is the method of planting (T). The type of variety (V) consists of 3 levels, namely V1=Bioni 63; V2= Inpari 32; and V3 = Inpari 30, while the method of planting (T) consists of 2 levels, namely T1 = direct seed planting, and T2 = transplanting. Data were analyzed using analysis of variance and further test with LSD 5%. The results showed that the treatment of varieties and planting methods had no significant effect on the diversity of carnivorous arthropods. Four types of carnivorous arthropods were found, namely odonata, araneae, coccinellidae, and paederinae with a low species diversity index of 0.4985; 0.5210; 0.5172; 0.4976; 0.5205, and 0.5057 in V1T1; V1T2; V2T1; V2T2; V3T1, and V3T2. Dominant herbivorous arthropods were Scirpophaga incertulas Walker, Cnaphalocrocis medinalis, Nilaparvata lugens Stal, and Leptocorisa oratorius. The highest yield was shown in V1T2 at 9.44 tons/ha. It was concluded that the new high yielding varieties of rice and location-specific adaptive planting methods were Bioni 63 Agritan transplanting. The use of the new high-yielding variety Bioni 63 Agritan also contributed to the reduction in the use of chemical pesticides, with data supporting low yellow rice stem borer attack.The relationship between research results and sustainable agriculture is supports sustainable agriculture.
Bioinsecticide activity of ethyl acetate extract of Nothaphoebe coriacea Kosterm bark against Spodoptera exigua larvae in a laboratory
Authors: Humaida U , Pambayun Y G , Pribadi T , Dewanto H A , Zuhro R K
Published: May 2023

Spodoptera exiguais a cosmopolitan and polyphagous pest. Botanical pesticides are an alternative technique to controlS. exigua. This study aimed to evaluate the effect of an ethyl acetate extract ofNothaphoebe coriaceaKosterm bark (EEN) on the biological activity ofS. exigualarvae and to determine the most effective concentration to manageS. exigua. This experiment was arranged on a single factor completely randomized design with the concentration level as a factor. Botanical pesticide formulated from ethyl acetate solvent in maceration extraction. The test was carried out by dipping the leaf mustard into the treatment solution and then feeding it to 10S. exigualarvae. The result showed the EEN had an 0.5% extract content with bioactive from the alkaloids and tannins groups. Mortality and feeding inhibition showed good responses to the biological activity test. However, the mortality rate test revealed different responses the most effective concentration of EEN was 0.5%. This concentration has a mortality of 92% and kill 3.6 individuals per hour, but has a low feeding inhibition of 72.82%. A botanical pesticide from EEN can be developed to controlS. exigua. The LC50obtained from the application of the EEN toS. exigualarvae was 0.062%. EEN has the potential to be developed as a botanical pesticide.
Pesticides effect on growth of dark septate endophytes in vitro
Authors: Widyaningsih S , Triasih U
Published: May 2023

Pesticides are the necessary agrochemicals used in agricultural practice for the prevention of crops from pests and diseases. Pesticides may have direct effects on the non-target organisms, particularly these saprobic and symbiotic soilborne fungi. Dark septate endophytes (DSE) are endophytic fungi that colonize living plant roots without causing a negative impact. DSE might function as mutualistic fungi taking part in nutrients and altering the environmental tolerance of host plants, especially in stressed environments. The research was aimed to study the effect of pesticides on the growth, spore production, and morphology of DSE fungi isolated from citrus. This test used three active ingredients of pesticides namely Propineb 70%, Mancozeb 80 % (fungicides), and Glyphosate (herbicide). Dosage of pesticides in the treatments were 0.5 times, 1-time, 2-times of the recommended doses, and control (without pesticides). Three isolates of DSE fungi used were 5, 19, and TLG 2 isolates. The study showed that the growth of three isolates of DSE fungi on PDA containing various doses of Propineb 70% was significantly different from the control, as well as the spore density. Mancozeb 80% affects the growth of all fungi isolates compared to the control. DSE isolate 19 was more susceptible to the concentration of Mancozeb in the growth medium compared to 5 and TLG 2 isolates. The spore density in isolate 5 was significantly different compared to the control. The use of Glyphosate showed a relatively mild inhibitory effect on the growth and sporulation of DSE. Differences in the DSE isolates and the active ingredients of pesticides affected the growth and sporulation of DSE fungi.
Increasing productivity of acid sulphate soil for rice through application of ameliorant in Banyuasin South Sumatera
Authors: Ratmini NP. Sri , Herwenita  , Suprihatin Agus
Published: May 2023

Soil acidity, high solubility of Al, Fe and S as well as low soil fertility are obstacles to rice production in acid sulphate soil. However, rice production can be increase by improving land quality through application of ameliorant. The study was carried out on acid sulphate soil in Banyu Urip Village, Banyuasin Regency, South Sumatra during wet season of 2020. The study aimed to determine the effect of ameliorant to rice production in acid sulphate soil. The study used Randomized Block Design with 6 replications. The ameliorant tested were P1 = control (without ameliorant), P2 = Dolomite [CaMg(CO3)2] (2 t.ha−1), P3 = Agricultural lime/Calcium Carbonate [CaCO3] (2 t.ha−1), P4 = Manure (2 t.ha−1), P5 = Biochar (5 t.ha−1), P6 = dolomite + manure + biochar (1/3 of each dose) and P7 = agricultural lime + manure + biochar (1/3 of each dose); in which Swampland Soil Test Kit was used to determine the ameliorant doses. The ameliorant was spread across the soil surface two weeks before planting, then mixed using hoe at the same time with the second tillage. Parameters observed were agronomic characteristics including plant growth and yield components. Results showed that the provision of ameliorant was able to increase plant growth and productivity of rice in acid sulphate soil. The highest productivity was found in treatment P7 (3.96 t.ha−1 dry unhusked grain) which applied combination of agricultural lime, manure, and biochar.
Determination of the limiting factors for sugarcane (Saccharum officinarum L.) productivity with Leaf Sampling Unit (LSU) method in sandy soil
Authors: Kusumawati A , Satrio F B , Kautsar V
Published: May 2023

Sugarcane is one of the important plantation commodities that is widely cultivated in Indonesia as a raw material for the sugar industry. One type of land that is commonly used for sugarcane cultivation is sandy soil, however, this soil has shortcomings due to nutrients availability which affects the productivity of sugarcane. This study aims to determine the limiting factor of sugarcane productivity in sandy soil through the Leaf Sampling Unit (LSU) analysis. Foliar nutrient levels of Nitrogen (N), Phosphorus (P), Potassium (K), Calcium (Ca), and Magnesium (Mg) were determined. The parameters of plant growth observed included stalk height, stalk diameter, number of internodes per stalk, number of green leaves, number of stalk per clump, stalk fresh weight, and sugarcane productivity. Data were analyzed using correlation and descriptive tests. LSU analysis indicated that the levels of N and Ca were under sufficient conditions, at 1.98% and 0.33%, respectively. Meanwhile, the P, K, and Mg were in critical condition, with values of 0.03%, 0.09%, and 0.12%, respectively. Sugarcane stem diameter had a correlation with sugarcane productivity (r=0.985). Increasing the dose of fertilizers, especially P, K, and Mg is needed to overcome these nutrient deficiency conditions; thus the productivity of sugarcane can be optimized and sustainable.
Comparative Advantage of Productivity and Soil Properties on Corn-Soybean Intercropping to Monoculture System in Marginal Dry Land of Gunungkidul
Authors: Riyanto D , Cahyono T , Anshori A , Yustisia  , Udiarto B K
Published: May 2023

Most of agricultural land in Gunungkidul Regency is in the form of dry land. The appropriate cropping pattern in term of optimizing land in secondary planting season is intercropping system. The aim of this study was to show the comparison between corn or soybean monoculture with corn-soybean intercropping of two different varieties on growth, yield, LER value and soil properties on dry land of Gunungkidul. This study was conducted on Kampung, Ngawen, Gunungkidul. Soybean seeds were planted 14 days before corn seeds to avoid hindering the irradiation of soybean plant. Soybean seeds were planted 5 rows between two rows of corn with a spacing 40 cm x 20 cm. The soybean varieties were used Dena-1 and Grobogan, while corn varieties used Pioneer 35 and Bisi-2. The planting distance of corn were used the legowo system, that was (65-50) cm x 30 cm. Results of the study was shown that the highest corn productivity was achieved by Pioneer 35 variety, which intercropped with Dena-1 variety, that yielded 6.73 ton. ha−1 dry corn and 1.65 ton.ha−1 soybean seeds.. This yield was lower 9.11% and 10.13%, respectively compare to monoculture system on the same corn or soybean cultivation. The advantage of intercropping corn-soybean system was added biomass of soybean, which can be used as animal feed. The chemical soil properties of corn-soybean intercropping increased on N total about 33.33%, P and K available increased 25.71% and 23.62%, respectively. Soil CEC increased about 19.53%, while soil pH did not significantly different compared to monoculture.
Semi Pilot Scale Study on Production of Silica from Rice Husk Ash
Authors: Hidayat T , Setyawan N , Hoerudin
Published: May 2023

Silica is a versatile material that has many uses in various industrial fields such as the rubber, ceramics, pharmaceuticals, catalysts, absorbents, and electronics. Rice husk ash (RHA) is one of the potential natural materials as a source of silica. Various studies to produce silica from RHA have been carried out by sol-gel method but are still on a laboratory scale. This research aims to study the production of silica from RHA using the sol-gel method on a semi pilot scale (3 kg raw material per process). The treatments studied were addition of boiling water to the reaction product after extraction during the filtration step (before the gelation process) and the gel drying methods. The characterization of silica was determined using X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), and Scanning Electron Microscope (SEM). The best treatment with the highest yield (70.07%) and purity of silica (95.41%) was obtained by addition of boiling water to the reaction product and drying the gel using a mechanical dryer. The XRD results show that the silica produced has an amorphous phase, while the SEM results show an aggregate structure without cavities and tends to be wavy. The yield and purity of silica is relatively high so this process can be developed on a pilot scale. The utilization of RH or RHA into silica can reduce environmental problems caused by the accumulation of RH or RHA in very large quantities.
Effect of maturity stage on physico-chemical properties of Garifta-merah mango fruit
Authors: Widayanti S M , Mulyawanti I , Dewandari K , Winarti C , Hayuningtyas M
Published: May 2023

Garifta-merah is one of the mango varieties released by the Ministry of Agriculture in 2009 with the advantage of having red-yellow peel when it reaches full maturity. The distinctive taste of the fruit flesh makes it one of the types of mangoes favored by consumers in local and foreign countries. As a new variety, there is not much data regarding the Garifta-merah mango, especially regarding the optimal maturity stage to harvest. This study aims to determine the physico-chemical character of the Garifta merah mango harvested at 4 different maturity stage (70%, 75%, 80% and 90%). The study was conducted using a completely randomized design with 2 replications. The parameters observed included fruit peel color, fruit flesh color, total soluble solids (TSS) and fruit firmness. The results showed that the stage fruit maturity determines the physico-chemical character of the fruit. The maturity level of the Garifta-merah mangoes affects the color of the peel and flesh of the fruit, the firmness of the fruit as well as the total soluble solid. Garifta-merah mango fruit can be harvested at maturity level above 75%.
Use of Chitosan and Essential Oils as Edible Coating for Sapodilla Fruit (Manilkara zapota)
Authors: Widyastuti T , Dewi S S , Mudawy A A
Published: May 2023

Sapodilla fruit (Manilkara zapota) is one of the annual tropical fruit plants that have a shelf life of only 3-4 days at room temperature. One way to extend the shelf life of fruit is by coating. Chitosan has an excellent potential to be applied as an edible coating. The addition of essential oils, namely Vanilla and Betel, is expected to improve the characteristics of the edible coating and act as an antimicrobial and antioxidant. This research was conducted to extend the shelf life of Sapodilla fruit using Chitosan, adding Vanilla and Betel as a coating material. This research was arranged in a Completely Randomized Design (CRD) with a single factor design consisting of four treatments with three replications. The treatments included: K0 = Control, K1 = Chitosan, K2 = Chitosan+Vanilla, K3 = Chitosan+Betel. The results showed that using edible coatings can reduce fruit weight loss, maintain vitamin C levels, and lower reduced sugar levels. And did not reveal its effect on the fruit hardness, total titrated acid, and total dissolved solids. Edible coating with Chitosan+Vanilla is the most effective treatment to extend the shelf life of Sapodilla fruit, maintaining a shelf life of seven days.
Environmental reporting by Indonesian agricultural companies around the spread of the COVID-19 epidemic
Authors: Widagdo A K , Ika S R , Dhani C N , Putri L F , Sumbodo B T
Published: May 2023

The purpose of this article is to see if there was a change in the amount of environmental reporting by agricultural firms after the COVID-19 epidemic spread in Indonesia. This study also examines the difference in the degree of environmental reporting between companies that publish sustainability reporting and those that do not in the period pre- and post-COVID-19. In addition, determinant factors for the extent of environmental reporting are also explored. This study utilizes 23 companies as a sample, i.e., the Indonesia Stock Exchange-listed agricultural enterprises in 2019 and 2020. The paired sample t-test results show that environmental reporting rose following the spread of the COVID-19 pandemic compared to reporting levels before the pandemic. In addition, the environmental reporting of companies that publish sustainability reporting is significantly higher than that of those that do not. This finding implies that despite the hard time facing COVID-19, the companies keep maintaining incentives to care more about the environment, which is marked by increased environmental reporting. Meanwhile, the factor that affects the amount of environmental exposure is the firm’s size. Hence, a company’s level of environmental reporting will increase as its assets grow in size.
Influencing people for good: Waste bank and social marketing communication strategies
Authors: Alkhajar E N S , Luthfia A R , Sofyan A
Published: May 2023

Waste bank is one of mitigation strategies to reduce climate change impacts. This research focuses to examine the social marketing communication strategies used by the opinion leaders as social marketers to persuade people in Pendulan Hamlet to actively participate in the implementation of the waste bank. The study employed descriptive qualitative method. The data were collected using field observation, interviews, and documentation. The results found there were two main strategies to persuade people: (1) face-to-face communication; and (2) group communication. In addition, the characteristics of rural areas are important factors that influence the successful of social marketing communication strategies.
Visitors’ Awareness to Maintain and Preserve the Biodiversity and Environment at Bantimurung Nature Tourism Object, Bantimurung Bulusaraung National Park
Authors: Putri I A S L P , Ansari F
Published: May 2023

Bantimurung Nature Tourism Object is one of the famous destinations in South Sulawesi Province. This research aims to determine the level of visitor awareness to preserve this destination’s biodiversity and environment. Data collection about the levels of visitor awareness was conducted using the interview method. The result of the study showed that most visitors are aware of the biodiversity and the environment. However, the lack of knowledge and fewer visitors information about protected butterfly species declined their environmentally friendly behavior and awareness. Therefore, persuading visitors that their behavior will affect the destination’s biological and non-biological natural resources is necessary. Moreover, it is required to improve visitors’ knowledge about friendly environmental behavior and how to maintain this potential so they can enjoy it sustainably.