bluuebunny/crossref_metadata_2025 huggingface dataset:
Universal Verification Methodology Based Verification of UART Protocol
Authors: Kashyap Bidisha , Ravi V
Published: January 2021

Verification today acts as a constriction of any complex VLSI design. Bringing out improved verification efficiency is a must. Most of the computers and microcontrollers contain a number of serial data ports. These data ports are used to connect with devices such as keyboards and printers which are basically serial input and output devices. Transmission and reception of serial data from an isolated location can be done with the help of a modem connected to the serial port. UART- Universal Asynchronous Receiver and transmitter is a hardware device which facilitates serial transmission and reception of data. In this work presented here, the UART has been designed with the use of the industry standard Verilog HDL code and the verification of the protocol has been done using system Verilog code in UVM environment. The UVM based verification methodology can significantly reduce the time needed for verification.
Efficient fault diagnosis for CORDIC Algorithm by using Hamming Codes
Authors: Jain Prachi , Durai Dr. Ananiah
Published: January 2021

The attractiveness of CORDIC Algorithm lies in the fact that by simple shift-add operations, it can perform several computing tasks such as the calculation of logarithmic, hyperbolic and trigonometric functions, real and complex multiplications, square-root, Eigen value estimation and many others. As a consequence, CORDIC has been used diversely for applications in diverse areas such as communication systems, 3- D graphics, signal and image processing apart from general scientific and technical computation. The digital computation is very much prone to errors; hence the error detection and correction became important for this algorithm. In this work it is achieved by integrating the Hamming codes to the CORDIC algorithm and hence achieving the error-free CORDIC algorithm. The proposed design are benchmarked through Xilinx FPGA and hence the reliability constraints be achieved.
Design of 9:2 compressor using FinFET
Authors: Kolluru Jyotsna , Viswanadhapalli Teja , Annis Fathima A
Published: January 2021

Multiplier is an essential component that is used commonly in any digital circuits. In general, for any digital circuits, multipliers occupy larger area; have long latency and their power consumption is more. Thereby, enhancing the performance of multipliers is quite important. Compressors are used to reduce the partial products so that the improved performance of multipliers can be achieved. In this paper, a new structure of 9:2 compressor is proposed in which the circuit is implemented with different combinations of 3:2, 4:2, 5:2 and 6:2 compressors. In this work, instead of bulk CMOS technology, circuits are implemented using FINFETs as they provide better gate control property, lower short channel effects. All the compressor circuits have been implemented using Cadence Virtuoso Simulator with FINFET 32nm technology. All the circuits are implemented to analyze the performance in terms of power, delay and transistor count.
Design and Implementation of 16bit SRAM Using Quantum Dot Cellular Automata
Authors: Janardan N , Guruviah Velmathi
Published: January 2021

The era of CMOS technology at the nanoscale will be going to replace with an unimaginable future by the opportunity of Quantum-dot cellular automata (QCA). The largest possible scope for constructing an elegant and efficient memory design is there with QCA technology. The suggested methodology and execution of a brand-new reminiscence cell shape primarily depends on QCA with a minimum delay, area, and complications is provided to develop a static random-access memory. This paper affords the circuit diagram and its execution of a 16-bit Static RAM with a new shape in QCA. Because of having powerful pipelining structure with in the QCA, this SRAM is very fast in executing operations. With a new shape of 4-bit width design for the 16-bit SRAM has applied in QCA. The ability of resulting read/write operations often with minimal delay is possible with this kind of SRAM design. Having a smaller number of majority gates and cells, the design of 16-bit decoders and multiplexers are represented. For getting rid from the adjoining hassle of intersecting labels, the new signal distribution network has been used to implement the SRAM with 2-to-4 decoders and 4-to-1 mux’s. The Quantum do CA-primarily depend on Static RAM cell turned into comparison with the Static RAM cell depended totally on CMOS. Consequences observed that the suggested Static RAM is more systematic in phrases of area, complexity, clock frequency, latency, throughput, and power in take.
A Hybrid Approach to Enhance Underwater Images
Authors: Tyagi Aryan , Graceline Jasmine S
Published: January 2021

Underwater pictures are barely visible due to effects of dispersion and absorption. Due to poor visibility it is very difficult to study underwater environment. Many Techniques have been used to increase the quality of degraded underwater images. This research paper follows the approach which has two major steps. First step is color correction based on grey world hypothesis. The second step is dehazing technique which is used to eradicate camera haziness. The approach suggested is ideal for use in real time application.
Efficiënt load balancing by optimized flexi max-min algorithm
Authors: Praveen Kumar P , Kanchana Devi V
Published: January 2021

Load Balancing is required to distribute tasks across Virtual Machines on one hand and on the other hand in a cloud Environment. Here, a new task scheduling algorithm: ‘Optimized Flexi Max-Min Scheduling Algorithm’ is proposed. The algorithm maintains a data structure which is modeled after a Binary Search Tree (BST) for estimations, enhanced searching, task allocation, and migration of tasks. Cloud-Sim is used to model and simulate the cloud computing environment in order to obtain simulated data. The result of this experiment shows that the proposed algorithm outperforms the traditional Max-Min task scheduling algorithms.
Comparative analysis of Human Activity Recognition and object detection
Authors: Sunil Suthar M. , Nithya Darisini P.S.
Published: January 2021

Human Activity Recognition (HAR) is the ability to interpret human body gesture or motion and determine human activity or action. Most of the tasks can be done automatically if they can be recognized via HAR system. HAR is an essential part of various scientific research contexts and the daily defence system i.e. surveillance, healthcare and human computer interaction (HCI). In computer vision, images and videos are analysed using different techniques. While recognition of activity in the real time environment the speed of the technique matters because if the system can detect the object in the images and videos at real time then it can be forwarded for the activity recognition process. How correctly the technique detects the object and differentiates the human object and other object and how much time it is taking to give the correct object, the number of frames it processes per second all matters. This paper deals with the comparison of the performance of YOLO (You Only Look Once) and Faster R-CNN in recognizing the human activity and detecting object.
Detection of DDoS Attacks Using Supervised Learning Technique
Authors: Prriyadarshini M A , Renuka Devi S
Published: January 2021

The development in digital technologies has been amplified by the drastic growth in the field of digital media applications and it changes the entire life style of the people. The electronic devices and digital contents are becoming more notable and popular among the users. As an emerging research area, security has attracted a lot of attention towards security professionals, experts and practitioners. In spite of this increased interest, this field still faces manifold challenges and issues. Such a fast development in digitization contains a block with attacks from an indirect security attack called Distributed Denial of service. An attack that damages the targets, services or network. The main objective of this paper is to improve the detection rate of the DDoS attacks and to overcome these threats in order to provide a safe network. So, a novel method is proposed in this paper to detect the DDoS attacks using support vector machine. A simulation of a network traffic is created to track and capture the patterns from any type of DDoS attacks with the help of rule creation and blacklisting. Further, using rule creation and SVM model, the simulation result based on different instances of time shows the observations of the real time requests that improves the efficiency of detecting the DDoS attacks.
Predictive analysis on hyperspectral images using deep learning
Authors: Sarah Rajkumar E , Pattabiraman V
Published: January 2021

In the field of remote sensing, identification of hyperspectral images (HSI) has become a trending topic. Hyperspectral visualization also struggles with a non-linear relationship between the spectral data obtained and the actual material in the image. In the recent years new machine learning algorithms have been established as an efficient feature extraction method to tackle non-linear hitches efficiently and commonly cast-off in a variety of image classification tasks. In addition, deep learning was applied to identify the features of the HSI and demonstrated good performance inspired by various positive applications. This research paper provides us with an ordered review of deep learning Hyperspectral image classification literature available and it compares multiple propositions. Exclusively, we summarize the main HSI classification challenges that conventional machine learning approaches have not been able to solve successfully, and also incorporate the benefits of deep learning to address these issues. This study improved data abstraction with minimized uncertainty and enhanced HSI classification performance. Firstly, a CNN model is built to understand the HSI“s spectral functionality. The CNN is used as a pixel classifier; therefore, it operates only in the spectral domain.
Disaster Management in Smart Cities using IoT and Big Data
Authors: Ramesh Akil , Rajkumar S , Jenila Livingston L M
Published: January 2021

Disasters are the most vulnerable factors which are affecting the human life and environment. Smart cities are mainly affected by disasters. This shows the requirement of an efficient disaster management system in smart cities. This paper deals with disaster management technique used in smart cities to detect disasters like building fire, pollution in atmosphere, route blockage using Big Data Analysis and Internet of Things (IoT). A combination of Hadoop environment is used in disaster reliant smart cities. IoT is used as a front end for collecting real time data sets and Big data analysis for data pre-processing and aggregation. This work evaluates the threshold capacity of each data which is collected for these disasters using Z-score normalization and if collected parameter exceed above the threshold value, then alert message is sent to public service sector such as fire station, police station and hospital. Different challenges faced by this evaluation are discussed in this manuscript.
Snippet generation using textbook corpus - an NLP approach based on BERT
Authors: Moses Andrew , Bharadwaja Kumar G.
Published: January 2021

In today’s technology-driven world, most millennials are tech-savvy. They have neither the time nor the interest in reading textbooks, newspapers or journals. They would like to immediately get instant answers and clarifications for all their doubts and questions. On many occasions, we are unable to find the exact word or meaning which we are searching for. So, if we have a clear, concise summary of a piece of literature, and we could understand what it contains with just a glimpse, we would be able to save a lot of time. This paper dwells about utilizing Natural Language Processing (NLP) to summarize a given text/textbook/paper. The state-of-the-art technology in this field has been demonstrated by Google’s Bidirectional Encoder Representations from Transformers (BERT), one of the latest developments in NLP. BERT is believed to understand English better than other models because of its underlying bidirectional architecture. The present proposal is to use BERT as a sentence similarity extractor. By applying the TextRank algorithm, the sentences holding the most important information are extracted. This comes under the domain of extractive summarization. Abstractive summarization is much talked about, but since Google BERT is not built for generating text, we are utilizing it in a different way to achieve the requirement. This paper intends to discuss the use of BERT for the gen-next kids which will save time and initiate further interest for researchers in developing new programs continuously in the future.
Discrimination between the final state of t

t¯

H and t

t¯

A using neural network
Authors: Pratama H P , Sumowidagdo S , Primulando R , Mart T
Published: January 2021

The Higgs Boson discovered in 2012 at the Large Hadron Collider (LHC) is still assumed to be the Standard Model Higgs Boson -a scalar particle. But there are still possibilities for a pseudo-scalar Higgs Boson. Currently, LHC has not been able to discriminate whether the particle is a scalar, pseudo-scalar, or mixed-scalar-pseudoscalar particle. The focus of this research is in the formulation of the neural network algorithm to discriminate between event signals from a scalar Higgs Boson and pseudo-scalar Higgs Boson in the Higgs production channel of associate production of Higgs Boson with a pair of top-antitop quark in a proton-proton collision pp → t

t

¯

H with center of mass energy

s

=
13
 Tev

with only Higgs decaying to a pair of bottom-antibottom quark had been considered. The set of discriminating variables used is the 3-momentum of all the final state particles. Discriminating efficiency of 0.412 was obtained which showed relatively small discriminating power.
Synthesis and characterization of Fe-doped ZnO/Graphene nanocomposites and their photocatalytic efficiency to degrade methyl orange
Authors: Pratiwi M I , Afifah N , Saleh R
Published: January 2021

Various amounts (3, 5, and 10 wt.%) of graphene were coupled with Fe-doped ZnO nanoparticles by the co-precipitation method. The Fe:ZnO/G nanocomposites structural and vibration modes were studied using X-ray Diffraction (XRD), Raman, and Fourier Transform Infrared (FTIR) spectroscopies. The spectra showed that the intensity of graphene increased with its amount. The thermal stability of the nanocomposites was examined by the Differential Thermal/Thermogravimetric Analysis (DTA/TGA). The DTA curves indicated that increasing graphene’s loading could increase their thermal stability. Their photocatalytic activities were also checked under UV light irradiation where methyl orange was used as the model of organic pollutant.
Prediction model of exacerbations in patients with Chronic Obstructive Pulmonary Disease (COPD) at RSCM
Authors: Amelia V , Siswantining T , Kamelia T
Published: January 2021

Chronic Obstructive Pulmonary Disease (COPD) is a worldwide health problem. COPD has a tendency for exacerbations. Exacerbations are worsening of acute respiratory symptoms resulting in additional therapy. Exacerbations in COPD increase the risk of death. The objective of this study is to determine the prediction model of exacerbations in patients with COPD based on factors affecting exacerbations in patients with COPD at RSCM (Rumah Sakit Cipto Mangunkusumo). The data used in this study is secondary data from the medical records of patients with COPD in RSCM. The sample was chosen using purposive sampling technique. The samples in this study are 107 patients with COPD. The method used is binary logistic regression analysis. The results of this study indicate that the factors that significantly influence the exacerbations of COPD are breathlessness, history of ICS use, and history of antibiotics use. Appropriate logistic regression model has been obtained. The result indicates that patients with COPD who have breathlessness, have history of ICS use, and have history of antibiotics use are more at risk of exacerbations than those who don’t. Accuracy test has been conducted with classification table at cut point 0.5. The prediction model has an accuracy rate of 74.77 %.
Properties of Burr distribution and its application to heavy-tailed survival time data
Authors: Hakim A R , Fithriani I , Novita M
Published: January 2021

Burr distribution is Burr Type XII distribution which is one among the twelve types of the continuous distributions in Burr system. It has two positive shape parameters, namely k and c. It is implied from the probability density function which can be either decreasing or unimodal, and the hazard rate function which can be either decreasing or upside-down bathtub-shaped. The other distributional properties and the moment properties of Burr distribution will be discussed in more detail. By considering these properties, we will study its tail behaviour. To estimate the parameters k and c, the maximum likelihood method will be considered. Based on the properties of the data representing the remission time of bladder cancer patients, we infer that Burr distribution is suitable to model the data. The goodness-of-fit using the Kolmogorov–Smirnov test shows that Burr distribution fits well to the data.
Application of credible value at risk in predicting Indonesia’s stock market return
Authors: Pangestika R , Novita M , Nurrohmah S
Published: January 2021

Risk is a probability of loss. In financial terms, loss can be interpreted as a possibility that an actual return on an investment will be lower than expected returns. Recent studies develop a new type of risk measures called credible value at risk (CrVaR). Credible value at risk is a model obtained by combining credibility theory and one of the most used risk measures, value at risk (VaR). Credibility theory is a model which gives a proper weight for both information and VaR is used to calculate maximum loss with the specific level of certainty and specific time frame. The combination of credibility theory and VaR is required to get a better value at risk estimation based on individual and group experiences. This paper discusses the model of credible value at risk, its parameter estimation, and focuses on the implementation of credible value at risk to predict the future rate of return from Indonesia’s stock market data.
Forecasting tuberculosis morbidity rate in Indonesia using autoregressive integrated moving average (ARIMA) method
Authors: Lesmono W D , Mardiyati S , Lestari D , Zili A H A
Published: January 2021

Tuberculosis is a disease that can affect socio-economic development. Based on data from the World Health Organization, there were 810,918 tuberculosis cases in Indonesia, which is noted as the third-highest number of tuberculosis cases in Asia in 2016. Prevention and control of tuberculosis are of considerable importance, especially in the insurance field, to cover the cost of treatment, so an accurate model of tuberculosis morbidity is needed. The method used in forecasting the tuberculosis morbidity rate is Autoregressive Integrated Moving Average (ARIMA) method. The ARIMA method is a time series method that is widely used to predict morbidity rates in the future. The data used in this study is the number of incidence morbidity tuberculosis rates that occurred in Indonesia from 2000 to 2017, which is obtained from the World Bank. The results showed that ARIMA (1, 2, 0) is the best and very accurate model to forecast the morbidity rate in Indonesia from 2018 to 2027, with the mean absolute percentage error (MAPE) is 0.1682 % and Akaike Information Criterion (AIC) values is -181.0120. The results of forecasting tuberculosis morbidity rate are expected to help insurance companies in determining the amount of premium paid by customers who suffer tuberculosis diseases.
Psittacidae community in Mbeliling landscape, Flores
Authors: Tumakaka J P , Winarni N L , Pradana D H , Junaid A R
Published: January 2021

A study of Psittacidae community has been conducted in the area of Mbeliling landscape, Flores, East Nusa Tenggara. The purpose of this study was to asses the community ofPsittacidaewhich includes the relative abundance, dominance and species composition in three locations with their different representations of habitats and altitudes. Data were collected in May and July 2013 from three locations, namely Lengkong Ra’beng, Dencang Mese and Wae Ndae. The data collection method used is Point Count. As many as 330 individual Psittacidae were found which are included in 4 different species;Tanygnathus megalorynchos,Geoffroyus geoffroyi,Trichoglossus haematodus weberiandLoriculus flosculus. Amongst the four species found,Loriculus flosculusis listed as Flores’s endemic species andTrichoglossus haematodus weberiis listed as Flores’s endemic sub-species. The relative abundance of each species are expressed in encounter rates. The dominance index value of Mbeliling region is at 0.547. Results shows that these four species are dispersed in different group clusters in composition dependant to the type of habitats represented at three sampling sites. Results pointed out the importance of Mbeliling Landscape area for Psittacidae conservation in Flores.
Diversity of dragonflies and damselflies in lakes of Universitas Indonesia, Depok, West Java
Authors: Akbar L A , Basukriadi A
Published: January 2021

We investigated the diversity and distribution of Odonata inhabiting lakes at Universitas Indonesia, Depok, West Java in November 2017. The Study aimed to characterize the lakes based on the occurrence of some Odonata species. There were six study sites: Lake Agathis, Lake Kenanga, Lake Mahoni, Lake Puspa, Lake Salam, and Lake Ulin. Species of Odonata encountered within the study sites were caught using sweep nets, photographed and then released. A total of 16 species of Odonata were found including 12 dragonflies and 4 damselflies. The dragonflies were represented by two families. Of the 12 species of dragonflies recorded, 11 were from the family Libellulidae and 1 was from the family Gomphidae. Brachydiplax chalybea and Orthetrum testaceum (Fam. Libellulidae) were the most widely distributed species. However, the abundant species were O. testaceum and Zyxomma obtusum. Damselflies were poorly represented, with only four species from two families, Coenagrionidae and Platycnemididae. Based on the species composition of Odonata from six lakes at Universitas Indonesia we conclude that most species are eurytopic or generalist that are widespread and tolerant to a wide range of environmental variables. In the current study, we consider that all lakes at Universitas Indonesia are disturbed habitats which are generally unsuitable for specialist or stenotopic species.
Variations in the morphology of Hibiscus rosa-sinensis crested peach flowers in nature
Authors: Saifudin  , Salamah A
Published: January 2021

Hibiscus rosa-sinensishas a wide variety of flowers. The variations even can be observed in one hybrid only. The hybrid is known as crested flower (double type I), one of four categories ofH. rosa-sinensisflower shapes in nature. This study purpose was to categorize the variation in crested flowers based on morphological observation using 200 samples. The observations showed the form of crested peach could be divided into three groups: crested peach that resembles a single flower (crested single-like), which resembles a double flower (crested double-like), and a transitional between single-like and double-like flower (crested intermediate-like). Groupings are based on the length of the staminal column which measured at the closest distance between the corolla position and the additional stamen or petal. The length of the staminal column on acrested single-likeis more than 4 cm (a > 4 cm), whereas thecrested double-likeis less than 1 cm (a < 1 cm), and thecrested intermediate-likeis 1–4 cm (1 ≤ a ≤ 4). Groupings are also reinforced by comparing the average number of staminodium petaloid, stamen-petal intermediate, and stamen. Thecrested single-likehas a 1:2:2 ratio, thecrested intermediate-likehas a 2:1:1 ratio, while thecrested double-likedhas a 5:1:1 ratio. Of the total 200 crested samples used in the study, 89.5 % of them hadintermediate-likeforms, while 6.5 % weredouble-like, and 4 %single-like. It can be concluded that the real crested ofH. rosa-sinensisis anintermediate-likeform.
Abundance of microplastic in green mussel Perna viridis, water, and sediment in Kamal Muara, Jakarta Bay
Authors: Fathoniah I , Patria M P
Published: January 2021

Research on the abundance of microplastic in green mussel Perna viridis, water and sediments in Kamal Muara, North Jakarta in September 2017 has been done. The research determined the abundance of microplastic in water, sediment and green mussel (base on the sizes and microplastic storage organs), also the correlation between abundance of microplastic in green mussel, water and sediments. Samples of green mussel, water and sediments were taken from 3 different stations with a distance of about 500 meters. Analysis of abundance of microplastic was done by isolating microplastic in each sample. The isolation of the green mussel samples was done by dissolving the mussels in the HNO3 solutionfor 24 hours and added saturated NaCl solution. The microplastics from water and sediment samples were separated by immersion of samples in a saturated NaCl solution. The results obtained were, on average, abundance of microplastic in green mussel size 3, 6, and 9 cm i.e., 5.35; 24.99; and 39 particles/gram. The microplastic fiber was dominant in mussel sample. The average abundance of microplastic in water and sediment are 13.15 particles/L of sea water and 0.92 particles/gram of dry sediment respectively. The microplastic film was dominant in water and sediment samples. Meanwhile, pellet was not found in all three samples. There was a correlation between abundance of microplastic with green mussel size, as well as with abundance of microplastic of film and fiber in water and sediment.
Optimization of annealing temperature for detection of lipase gene in Bacillus subtilis using polymerase chain reaction (PCR) method
Authors: Sugiarti S A , Nurhayati N , Abinawanto
Published: January 2021

Enzyme lipase (EC 3.1.1.3, triacylglycerol acylhydrolase) is a group of enzymes that hydrolyzes fat into fatty acids and glycerol. In addition, the lipase enzyme plays a role in various reactions, such as esterification, interesterification, and transesterification reactions. Lipase can be obtained from microbes, plants, and animals. The most important source of lipase is microorganisms that are produced by fermentation of different bacteria. Microbial Lipases are easy to produce and cost of production is low. Bacteria like Bacillus are commercially used for lipase production. Recombinant lipase enzyme can be expressed by lipase gene (lip gene) and secreted in the bacterial Bacillus subtilis. Polymerase Chain Reaction (PCR) is in vitro amplification Deoxyribonucleic acid (DNA) method. The purity and yield of the reaction products depend on several parameters, one of which is the annealing temperature. The aim of this research was to optimize an annealing temperature for lip gene amplification using PCR. The success in amplifying a gene by PCR technique using a specially designed primer is determined by the precision of the primary attachment temperature with the DNA. Two Primer pairs are designed to successfully amplify DNA sequence fragment, namely xynlip_for_41_nt_and xynlip_rev_38_nt_. The primer combination produced the best results regarding band intensity and relative absence of unspecific bands, producing the expected amplicons of approximately 792 bp. Regarding the annealing temperatures, the best amplification was obtained at 60 °C.
Study of Heat Shock Protein (Hsp) 70 gene expression of Emilia sonchifolia L. and Sphagneticola trilobata L. in Universitas Indonesia, Depok and Kebun Raya Cibodas
Authors: Syadewi M , Salamah A , Maryanto A E , Andayani N
Published: January 2021

The temperature of earth surface is generally different according to altitude. Universitas Indonesia (UI) is located at 50–140 masl with an average temperature of 28.6 °C, while Kebun Raya Cibodas (KRC) located at 1.300–1.425 masl with an average temperature of 20.06 °C. Temperature differences are thought to affect plant responses, such as the expression of heat shock protein (Hsp) 70 genes. The research aims to find out the expression of Hsp70 genes on Emilia sonchifolia and Sphagneticola trilobata collected from UI and KRC. The study was conducted by isolating RNA from young leaves, which then converted into cDNA. The cDNA product was further amplified by polymerase chain reaction (PCR) using Hsp70 Arabidopsis thaliana primer. The amplification products were then sequenced and analyzed by in-silico. The results of amplification show that there is a band with approximately 250 bp in all samples which is thought to be a partial product of the Hsp70 gene. The sequencing results show that PCR amplification product is Hsp70 partial gene with a nucleotide variation in the 65th base which has no effect on amino acid changes. The results indicate that Hsp70 gene is expressed in Emilia sonchifolia and Sphagneticola trilobata grown in UI and KRC.
The effect of addition glutathione antioxidant on vitrification medium to the viability of Garut sheep (Ovis aries) oocytes
Authors: Gunawan M , Pratiwi P A , Kaiin E M , Sjahfirdi L
Published: January 2021

Research has been conducted to investigate the viability of Garut sheep oocyte to evaluate the effect of glutathione antioxidants addition with a concentration of 0.5 mM, 1 mM, and 1.5 mM in the vitrification medium to the viability of Garut sheep oocytes. The oocytes was freezed at -196 °C for 7 days. A total of 135 oocytes first were matured in vitro with the addition of 1 mM glutathione for 24 hours. The oocyte were vitrified using 15 % ethylene glycol, 15 % dimethyl sulfoxide, 0.5 M sucrose and divided into four treatments group with the addition of 0 mM (KK), 0.5 mM (KP 1), 1 mM (KP 2), and 1.5 mM (KP 3) glutathione. Viability was evaluated through the luminescence produced by Hoechst and Propidium Iodide dyes. The percentage of viable oocytes are 69.70 % (0 mM), 72.73 % (0.5 mM), 76.47 % (1 mM), and 77.14 % (1.5 mM). The results tends to increase along with the addition of glutathione concentration. However, statistically, ANOVA were not significantly different among treatment groups (P > 0.05). The conclusion of the study is that the addition of glutathione antioxidants in the vitrification medium are able to maintain the viability of Garut sheep oocytes during vitrification, although the ANOVA test were not significant.
Microplastic abundance in anchovy Stolephorus indicus (Van Hasselt, 1823) in the Lada Bay, Pandeglang, Banten
Authors: Hardianti E , Wardhana W , Patria M P
Published: January 2021

Currently, microplastic is one of the serious threats to the marine environment. This research aims to investigate the abundance and types of microplastics contained in anchovies Stolephorus indicus and water from Teluk Lada (Lada Bay), Tanjung Lesung, Pandeglang, Banten. Anchovy samples were extracted with 1M NaOH and 5 % sodium dodecyl sulphate (SDS). Meanwhile, water samples were treated by mixing it into NaCl concentrate solution. The results show that 246.10 ± 32.25 ind−1 and 156 ± 13.46 L−1 microplastic particles were found in the anchovies and water, respectively. In addition, 216.30 ± 30.13 ind−1 microplastics were found in the anchovies taken from traditional market as a control. The types of microplastics found in anchovies were fibers (77.41 %), films (16.64 %), fragments (5.6 %) and a little amount of granules (0.35 %). Meanwhile, the water samples were contained with fibers (81.03 %), films (11.92 %), fragments (7.0 %) and a little amount of granules (0.05 %). Our study found that fibers were the dominant pollutant in all samples and the amount of microplastics contained in water is strongly related to the amount of microplastics found in anchovies.
The effect of giving corncob (Zea mays) on the growth of sludge worm (Tubifex sp.)
Authors: Khaerunnisa S , Safitri S D , Ikhsan C , Purwanti D , Lestari R
Published: January 2021

One of the best feed choices for aquaculture is sludge worms (Tubifex sp.). Sludge worms need enough protein for worm growth. Corncob is a waste that is not utilized in the environment. Corncob has protein content that can be used for sludge worm growth. Complex carbohydrates are broken down through fermentation. The purpose of this study was to optimize the development of sludge worm cultivation media based on corncobs. Sludge worms are cultured in a series of culture containers by recirculating watering. There are 3 variations of treatment, namely, treatment-I (10 %), treatment-II (20 %) and treatment-III (30 %). The parameters measured are water quality, dissolve oxygen, water flow rate, mass, number of individuals in the population, total organic matter. The results prove using corncob as a medium enrichment material prov idegood environmental results and is suitable for sludge worm. The range of temperature, pH and DO values are at the optimal conditions needed for the best fermentation process.
Lignocellulolytic enzyme activity pattern of three white oyster mushroom (Pleurotus ostreatus (Jacq.) P. Kumm.) strains during mycelial growth and fruiting body development
Authors: Nurfitri N , Mangunwardoyo W , Saskiawan I
Published: January 2021

Pleurotus ostreatus is one of the edible mushrooms that can utilize lignocellulose as substrate because of their ability to secrete the lignocellulolytic enzyme. The purpose of this research is to investigate and compare the lignocellulolytic enzymes production of P. ostreatus InaCC F209, F216 and LIPI on solid-state fermentation using sawdust during 70 days of mycelial growth (vegetative phase) and fruiting body development (reproductive phase). Supernatant of the extracted enzyme solutions were employed to investigate the reducing sugar, soluble protein, and enzyme activities. The results revealed that reducing sugar concentration of the three P. ostreatus strains subjected increased during growth and reached the maximum concentration on the reproductive phase, while the total protein content fluctuated during the growth but reached the maximum concentration on the reproductive phase. Laccase, LiP, and MnP activities of three P. ostreatus strains were higher on the vegetative phase, while the endoxylanase and endoglucanase activities were higher on the reproductive phase. β-glucosidase activity showed different variations between three P. ostreatus strains. Pleurotus ostreatus InaCC F209 produced the highest and most stable laccase, β-glucosidase, endoglucanase, and endoxylanase than two others.
fshr and lhr mRNA expression in granulosa cells of poor responder
Authors: Hanifah N , Wiweko B , Bowolaksono A
Published: January 2021

In Vitro Fertilization (IVF) is one of the most commonly used procedures to help pregnancies in couples who have infertility problems. One of the problems of infertility is poor ovarian response and the woman who experiences it is known as poor responder. Poor responders do not have an adequate ovarian response to gonadotropin in ovarian stimulation. The success of fertilization in poor responders tends to be low due to low quantity and is generally followed by low oocyte quality. Gonadotropins consisting of FSH and LH, play a role in follicle development and ovulation. The follicle response in capturing gonadotropins depends on the exact bond between the hormone and its receptor (FSHR and LHR) in the granulosa cells surrounding the oocyte. The purpose of this research is to know the expression level of fshr and lhr mRNA in granulosa cells of poor responders through real-time PCR method which then tested statistically using t-test. Fourteen samples of each poor responders and normal women were used in this research. The results showed insignificant differences between expression level of fshr and lhr mRNA in granulosa cells of poor responders and normal women (p > 0.05).
Production of antimicrobial compound from two potential actinomycetes SRM 2 and SD 17 using soluble and local starch
Authors: Prasetiyo H D , Santoso I , Maryanto A E
Published: January 2021

Fermentation of antimicrobial compound from two potential actinomycetes, SRM 2 and SD 17, has been carried out using a local carbon source and commercial soluble starch. Three local carbon sources, rice, corn, and tapioca starch were screened to determine the best local carbon source for growth medium of actinomycetes. Determination was based on Amylolytic Index Activity (AIA) using Iodine test. Result from screening local starch test of both actinomycetes SRM 2 dan SD 17 showed that rice starch was the best carbon source with AIA value (0.87 and 2.30) higher than corn starch (0.50 and 1.43) and tapioca starch (0.38 and 1.71). Antimicrobial compound of actinomycetes SRM 2 and SD 17 was produced in CSM medium containing soluble starch (CSMs) and rice starch (CSMb). Filtrate of the growth medium was tested for antimicrobial activity by using cylinder method against certain Gram positive and negative bacteria or yeasts. The results showed that filtrate of medium CSMs and CSMb from actinomycetes SRM 2 were most effective to inhibit Kocuria rhizophila with Antimicrobial Index (AI) 2.79 and 2.66, respectively. The filtrate was less effective against to Escherichia coli with AI 0.92 and 0.89. Filtrates of medium CSMs and CSMb from actinomycetes SD 17 were also most effective to inhibit K. rhizophila with AI 1.75 and 3.16 respectively. Meanwhile, the filtrates were less effective to inhibit Candida albicans with IA 0.67 for CSMs and 0.95 for CSMb, but not effective to inhibit Saccharomyces cerevisiae.
Pseudo 3D seismic using kriging interpolation
Authors: Abdullah F , Yulianto E , Novrizal  , Riyanto A
Published: January 2021

Seismic method is one of geophysical method that is used to determine subsurface condition of the earth. There are two types of seismic data, 2D seismic and 3D seismic. The advantages of using 3D seismic data is it has less uncertainty for imaging the earth subsurface. However, the cost to acquire 3D data is higher than producing 2D data, thus some company needs to invest more money to be able to get a better data quality. One of the ways to have 3D seismic data without having to spend a lot of money is by creating a 3D pseudo seismic data from 2D seismic data. The purpose of this research is to create a 3D pseudo seismic data by using a geostatistical method. The geostatistical method that is used in this research is Kriging interpolation. By the help of Petrel software, kriging interpolation is done to create the 3D seismic. The pseudo 3D seismic results show a good image such as difference in amplitude, also structural geology features of subsurface. In conclusion, the use of kriging interpolation in pseudo 3D seismic still needs more work and development so the results will be good for the next interpretation steps.
Evaluation study on the effect of production and fluid reinjection towards reservoir using micro gravity in Kamojang geothermal field
Authors: Dwikorianto T , Hendriansyah T , Sastranegara R M T , Nugroho S I
Published: January 2021

Geothermal fluid exploitation is expected to cause physical as well as chemical changes to the reservoir of a geothermal field. This is what happened to Kamojang Geothermal Field which has been producing for four periods, starting from the initial production capacity of 30 MW (1983) which became 140 MW (1987), then 200 MW (2008) and 235 MW since 2015 up to now. To observe changes of subsurface condition, Microgravity, is called time-lapse gravity as well, as one of geophysical survey activity is carried out in order to obtain the reservoir changes in a wider view based on the changes of gravity value as a reflection of rock density changes due to the extracted fluid mass. Generally, the microgravity study result from 1984 until 2018 shows the existence of microgravity value changes which correlates to the amount of fluid mass produced and the water mass which was reinjected back into the reservoir. This can be observed from the Time-lapse Anomaly Map in accordance to each of the production period of Geothermal Power Plant (GPP) Unit 1, 2, 3, 4 and 5.
Sandstone diagenesis interpretation of Cipacar formation based on outcrop data in Banjarsari District, Lebak Regency, Banten
Authors: Mahesa F G , Riyanto A , Indraswari A O
Published: January 2021

The diagenesis of sediments is profoundly impacted by porosity and permeability since these parameters control the flow of fluids through rocks that build up mineral authigenesis, cementation, and dissolution. Porosity in rock is available in sedimentary rock, particularly in sandstone in Cipacar formation located in Banjarsari, Lebak, Banten. This research aims to examine sandstone characteristics, porosity value, diagenesis process, and implication between porosity and diagenesis. The data of this study were obtained from surface outcrops and petrographic analysis. Results of this research show that sandstones in Cipacar formation have porosity values between 8–14 % and have undergone diagenesis processes such as compaction, cementation, and dissolution which are classified in the mesogenesis regime.
Processing of noise contaminated magnetotelluric data using digital filters based on MATLAB
Authors: Sulaiman F A , Ismail M L , Daud Y
Published: January 2021

Magnetotelluric (MT) method is known as an effective geophysical method for imaging the condition of the subsurface resistivity distribution, especially in the geothermal system. However, this method is very sensitive to noise. The noise can occur due to mechanical activity such as vibration and electrical activity generated by powerline electric current near the point of measurement. To eliminate this noise is used digital filter consisting of despike filter and notch filter. Despike filter is used to eliminate irregular spike noise, while the notch filter is used to remove regular powerline noise. Furthermore, D+ can be applied to enhance the impedance data trend. Both of filters and D+ feature are built and then arranged into MTFilter program. The result of data processing using MTFilter program shows the improvement of MT data quality. Moreover, the inversion processing results of MT field data shows the resistivity distribution of structure which is more reliable with the characteristics of the geothermal system.
Simulation of mortality immunization for life insurance companies in Indonesia using duration and convexity approach
Authors: Wibisana A , Novita M
Published: January 2021

Duration and convexity are two important factors in interest rate immunization. These two factors used to be very closely related to financial assets immunization towards change in interest rate, but some of the latest studies had applied the concept of duration and immunization in terms of mortality immunization. This paper examines 24 mortality immunization strategies that applied the duration and convexity concept in insurance portfolios which consist of life insurance and annuity products. The outcome of this study is the optimal proportion of the life insurance and annuity products for life insurance companies in Indonesia. Numeric simulations had been done using Indonesia Mortality Table 2011 (TMI-2011) to obtain the value and characteristics of the optimal proportion for two portfolios which is affected by several factors, namely the implemented strategy, mortality model, mortality model change type, age of policy holder, year of application, payment paying period, and term policies.
Parameter estimation for binary time series using partial likelihood
Authors: Nadiya I , Widyaningsih Y , Sarwinda D
Published: January 2021

A time series with binary response variable is called a binary time series. Binary time series can be modelled using the Autoregressive general model and nonlinear regression approach. Kedem & Fokianos introduced a binary time series model through the Autoregressive and logistic regression approach. The parameters of binary time series are estimated using the Partial Likelihood method. The Partial Likelihood method is performed by determining the Partial Likelihood function derived from the marginal probability density function (pdf) of Bernoulli distribution. However, in the process of parameter estimation using this method, the form of final function to obtain parameters is not in the closed form equation. To face this problem, Fisher scoring iterations are performed. The application of parameter estimation of the model uses the data about boat racing competition between the University of Cambridge and Oxford University from 1946 to 2011. Based on the data application, parameter estimation of the binary time series model using partial likelihood with different amounts of data resulting in a relatively same or no significant parameter estimator.
Lindley–exponential slash distribution
Authors: Dwiki M , Nurrohmah S , Novita M
Published: January 2021

There is a problem arising when Lindley distribution is used to model right–skewed and unimodal data, which lies in its inability to model data with its peak farther from 0. A modification is required to increase the flexibility of this distribution, with “transformed–transformer” being one of the proposed method. This method is done by making a composition of two random variables through their respective distribution functions, with random variable T being the “transformed”, and random variable X being the “transformer”. In this paper, Lindley distribution was chosen to be the “transformed” and exponential distribution was chosen to be the “transformer”, constructing the Lindley–exponential distribution. However, there is a trouble using distribution if the data has a heavier tail. An alternative distribution is required while maintaining the properties of the Lindley-Exponential Distribution. Through transformation of variables method, a new distribution, Lindley-Exponential Slash Distribution is introduced, which is unimodal, right–skewed, heavier tailed. This paper covered some of its statistical characteristics, such as pdf, cdf, survival function, hazard rate,kthmoment, mean, variance, skewness, and kurtosis. Parameter estimation was carried out with maximum likelihood estimation through numerical method. An application of distribution was illustrated on maximum annual precipitation data of Durham City.
The size Ramsey and connected size Ramsey numbers for matchings versus paths
Authors: Vito V , Nabila A C , Safitri E , Silaban D R
Published: January 2021

Given simple graphs F, G, and H, we write F → (G, H) if for every red-blue coloring of the edges of F, there exists either a red subgraph G or a blue subgraph H in F. The size Ramsey number for G and H, denoted by

r

^

(G, H), is the smallest size of a graph F which satisfies F → (G, H). If in addition F must be connected, then the resulting number is called the connected size Ramsey number for G and H, denoted by

r

^

c

(G, H). In this paper, we obtain upper bounds for

r

^

(
t

K

2

,

P

m

)

,

r

^

c

(
t

K

2

,

P

m

)

,

r

^

(
t

K

2

,

P

4

+
 a leaf 
)

, and

r

^

c

(
t

K

2

,

P

4

+
 a leaf 
)

for t ≥ 1 and m ≥ 3. We also determine the exact values of

r

^

c

(
2

K

2

,

P

m

)

and

r

^

(
t

K

2

,

P

3

)

. In addition, the exact values of

r

^

c

(
t

K

2

,

P

3

)

for t = 3,4 are given.