bluuebunny/crossref_metadata_2025 huggingface dataset:
Wireless sensor network for monitoring irrigation using XBee Pro S2C
Authors: Hapsari Gita Indah , Andriana Mutiara Giva , Rohendi Luky , Mulia Aldy
Published: August 2020

Monitoring irrigation is still the problem of agriculture in Indonesia. During the dry season, the farming fields drought while in the rainy season, floods happened. Since the farm-fields located far from the urban area, it requires an automatic tool for monitoring the availability of water that can help the farmer to monitor the farm-field. Wireless sensor network is an appropriate technology used to overcome problems related to the monitoring system. This research is using a water level sensor, pump, Arduino Nano, and XBee Pro S2C in each monitoring node. The system designed within two modules, an automation irrigation module and a monitoring module, which is connected with the communication configuration of master-slaves between Xbee Pro S2C at each node. The system examined several scenarios in order to test the performance. Based on the testing result, all the performance parameters can be adequately delivered to the user and appropriated with the real condition in the farm field. The delay between nodes only takes 5-10 seconds.
Use of closed loop system using Arduino for different parameters in farming
Authors: Rahman Saifur
Published: August 2020

The GDP (Gross domestic product) of most countries in the world are base on the regular basis of agriculture contribution of that particular country. The current weather conditions in the world and crop loss are the main reason for its contribution to GDP. New technologies and advanced fertilizers are now used in farming though these technologies and advanced fertilizers do not reach farmers till now. In this paper, a concept for the automated watering system in agriculture is introduce which uses wireless sensors technology for the detection of moisture in the soil suitable for agriculture using a smartphone application which will play a critical role in agriculture. The automatic watering to plants using the Arduino system and android app is use. Even this application of Android will provide information to the farmers related to agriculture like costs of seeds, level of moisture required, amount of water needed, which type of soil required, forecast weather, fertilizers to be used and pesticides required.
A quad band planar slotted microstrip patch antenna for wireless applications
Authors: Roy Reshma , Singh Apurva , Kumar Om Prakash , Ali Tanweer , Pai M. M. Manohara
Published: August 2020

This research paper presents two different types of multiband patch antenna. The first design is a dual-band antenna and the second design is a quad-band antenna. Both the antennas have a compact size of , and is designed on FR4 substrate with loss tangent (=0.02, height (h)=1.6 mm, with dielectric constant of 4.4. The dual-band antenna operates at frequencies 3.9 and 5.71 GHz. These dual band operations are accomplished by utilizing L-shaped slot in the ground part and T-shaped slot in the radiating part of the patch antenna. The gain corresponding to the two frequency bands are 1.27 and 1.35 dB, respectively. The quad band antenna operates at frequencies 3.6, 4.9, 7.4 and 8 GHz. The gain corresponding to these frequencies are 0.18, 1.69, 2.25 and 3.99 dB. For achieving quad band operation from the dual band antenna the back plane L-shaped slot is modified by cutting a rectangular strip in the middle, hence dividing it into two different slots. The front plane is also modified by introducing two rectangular strips to the T-shaped patch. The proposed antenna shows multiband and has the advantage of simple structure compact size and good impedance matching. All the simulations of the proposed design are carried out in HFSS v.13.0.
Effective tocotrienol dosage traceability system using blockchain technology
Authors: Kamaruddin Norhaslinda , Wahab Abdul
Published: August 2020

Tocotrienol dosage, especially in vitamin E, is important for treatment and prevention of diseases. To date, the dosage is given based on the physician's knowledge and experience to suit the patient’s needs. The alteration of the dosage is depending on the way the patient’s body reaction and coping mechanism which is different from one to another. Hence, the optimal dosage is very difficult to achieve and may result in undesirable side effects. An alternative solution using blockchain technology to trace and chart the dosage of tocotrienol is proposed to capture the effective measure for the patient. With the advancement of the internet of things (IoT) and big data analytics technologies, an effective tocotrienol dosage is possible by utilizing the data gathered from the individual patient for tocotrienol dosage personalization profiling. Then, the output can be used to assist the physician to diagnose an appropriate amount of tocotrienol dosage for optimum effect. This paper discusses the theoretical framework of using blockchain technology to develop an effective tocotrienol dosage traceability system. It is envisaged that such an approach can be a guide to the health practitioners to administer the correct dosage for the patient and subsequently leads to a better quality of life.
Experiment based comparative analysis of stator current controllers using predictive current control and proportional integral control for induction motors
Authors: Ha Vo Thanh , Minh Tran Trong , Lam Nguyen Tung , Quang Nguyen Hong
Published: August 2020

The stator current control loop plays an important role in ensuring the quality of electric drives interm of producing fast and adequate required torque. When the current controller provides ideal responses, speed control design subsequently is in charge of improving the system performances. Classical PID control is commonly used in current loop design, this paper presents the comparative analysis of current stator controller using proportional integral control and predictive current control (PCC) in field-oriented control-based induction motor drives, with rigidly coupled loads. The experimental results show system responses with PID and PCC. Informative experiment-based analysis provides primary guidance in selection between the two controls.
Indoor and outdoor investigation comparison of photovoltaic thermal air collector
Authors: Bahtiar Bahtiar , Zohri Muhammad , Fudholi Ahmad
Published: August 2020

Photovoltaic technology is one of renewable energy technology very hopeful, especially photovoltaic thermal system or PVT system. A PVT system solar air collector produces hot air and electricity simultaneously. In this study, indoor and outdoor investigation comparison of PVT system solar air collector has tested at the National University of Malaysia. The indoor and outdoor investigation conducted with variation mass flow rates from 0.01 kg/s to 0.05 kg/s at the solar intensity of 820 W/m2. Indoor and outdoor evaluation is conducted to precisely evaluate the performance improvement theorized by the researcher. The comparison between the indoor and outdoor outcome purposed to confirm each testing and attraction decision. The outdoor investigation outcomes were agreement with indoor results. Indoor investigation outcomes reliably with outdoor investigation outcomes indicated by accuracy results.
Performance analysis of the convolutional recurrent neural network on acoustic event detection
Authors: Jung Suk-Hwan , Chung Yong-Joo
Published: August 2020

In this study, we attempted to find the optimal hyper-parameters of the convolutional recurrent neural network (CRNN) by investigating its performance on acoustic event detection. Important hyper-parameters such as the input segment length, learning rate, and criterion for the convergence test, were determined experimentally. Additionally, the effects of batch normalization and dropout on the performance were measured experimentally to obtain their optimal combination. Further, we studied the effects of varying the batch data on every iteration during the training. From the experimental results using the TUT sound events synthetic 2016 database, we obtained optimal performance with a learning rate of 1/10000.  We found that a longer input segment length aided performance improvement, and batch normalization was far more effective than dropout. Finally, performance improvement was clearly observed by varying the starting points of the batch data for each iteration during the training.
Road surface classification based on LBP and GLCM features using kNN classifier
Authors: Fauzi Arthur Ahmad , Utaminingrum Fitri , Ramdani Fatwa
Published: August 2020

Autonomous Ground Vehicle (UGV) technology has shown a fast development this past year and proven to be useful. The use of UGV technology is restricted on a particular road condition. Classification of the road is an essential process in UGV, especially to control the autonomous vehicle. For example, the speed could be adjusted by referring to the road type, these process require a fast computational time. This research focuses on finding the most discriminant feature while keeping the number of features into a minimum to obtain fast computational time and accurate classification result. One can experiences difficulties because the condition of the road varies, this research proposes a combination of Gray Level Co-occurrence Matrix (GLCM) a statistical method to extract feature and Local Binary Pattern (LBP) feature to improve the robustness of the features. The kNN classifier is used to do the classification with the accuracy of 98% and 12 picture processed per second.
Autonomous system to control a mobile robot
Authors: Abu Baker Ayman , Ghadi Yazeed Yasin
Published: August 2020

This paper presents an ongoing effort to control a mobile robot in unstructured environment. Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. Several algorithms have been proposed for obstacle avoidance, having drawbacks and benefits. In this paper, the fuzzy controller is used to tackle the problem of mobile robot autonomous navigation in unstructured environment. The objective is to make the robot move along a collision free trajectory until it reaches its target. The proposed approach uses the fuzzified, adaptive inference engine and defuzzification engine. Also number of linguistic labels is optimized for the input of the mobile robot in order to reduce computational time for real-time applications. The proposed fuzzy controller is evaluated subjectively and objectively with other approaches and also the processing time is taken in consideration.
Investigation on the printability of bioink based on alginate-gelatin hydrogel and liquid crystals
Authors: Abdulmaged Alyaa Idrees , Soon Chin Fhong , A. Talip Balkis , Othman Sheril Amira , Lim Gim Pao , Tee Kian Sek
Published: August 2020

Bioinks of 3D bioprinting have significant potential application in the field of tissue engineering to support cell attachment and proliferation. In this work, the alginate-gelatin-CELC (AGLC) bioink based on different compositions of alginate-gelatin (AG) hydrogel and cholesteryl ester liquid crystals (CELC) was prepared. Primarily, the alginate-gelatin hydrogel with certain concentration of Gelatin (10-50%w/v) was investigated. The printability of the hydrogel reached a minimum width of 1.8 mm at a flow rate of 1 mL/min when the Gelatin concentration was increased to 50 % w/v (AG1050). Subsequently, the respective polymers with 10% w/v Alginate and50% w/v Gelatin blended with 1%, 5%, 10%, 20%, 40%, and 60% w/v of CELC in the preparation of the alginate-gelatin-CELC bioink was further investigated. The printability of the bioink was examined by micro-extrusion based 3D bioprinter. The printability of the bioink enhanced by 27.8% as compared to AG1050 and reached a minimum width of 1.3 mm at a flow rate of 1 mL/min when the CELC concentration was increased to 40% and 60%. The tested properties of the bioink show that the CELC improve shear-thinning and lipid moieties properties to the composite bioink and hence, enhances its printability.
Controller selection in software defined networks using best-worst multi-criteria decision-making
Authors: Amiri Esmaeil , Alizadeh Emad , Rezvani Mohammad Hossein
Published: August 2020

Controllers are the key component of Software-defined Network (SDN) architecture. Given the diversity of open SDN controllers, the following question arises for the network administrators: How can we choose the appropriate SDN controller? Different characteristics of the controllers have greatly increased the complexity of the right decision. Multi-Criteria Decision-making Methods (MCDMs) is a family of robust mathematical tools to address complex problems regarding multiple objectives. In this paper, we study the most important features of SDN controllers. To this end, we compare the well-known SDN controllers including NOX, POX, Beacon, Floodlight, Ryu, ODL, and ONOS. Leveraging a novel MCDM technique called the Best–Worst Multi-criteria (BWM), we find the most appropriate SDN controller. We solve an optimization problem and evaluate its performance in terms of significant criteria such as throughput and latency. Initial evaluation revealed that the ONOS and ODL have the highest throughput, while the lowest throughputs belong to the NOX, POX, and Ryu. However, final evaluation concerning all criteria confirmed the robustness of the ONOS and the ODL compared to other controllers.
Capacitor bank controller using artificial neural network with closed-loop system
Authors: Widjonarko Widjonarko , Avian Cries , Setiawan Andi , Rusli Moch. , Iskandar Eka
Published: August 2020

The problem of power factor in the industry is critical. This is due to the issue of low power factor that can make the vulnerability of industrial equipment damaged. This problem has been resolved in various ways, one of which is the Automatic Power Factor Correction, with the most popular device called capacitor bank. There are also many methods used, but several methods require certain calculations so the system can adapt to the new plant. In this study, researchers proposed a capacitor bank control system that can adapt to plants with different capacitor values without using any calculations by using an Artificial Neural Network with a closed-loop controller. The system is simulated using Simulink Matlab to know the performance with two testing scenarios. The first is changing the value of the power factor on the system and changing the value of the capacitor power at each bank, the second comparing it with the conventional methods. The results show that the system has been able to adapt to different capacitor power values and has a better performance than the conventional method in power factor oscillation due to the extreme power factor interference
Deep convolutional neural network for hand sign language recognition using model E
Authors: Pratama Yohanssen , Marbun Ester , Parapat Yonatan , Manullang Anastasya
Published: August 2020

An image processing system that based computer vision has received many attentions from science and technology expert. Research on image processing is needed in the development of human-computer interactions such as hand recognition or gesture recognition for people with hearing impairments and deaf people. In this research we try to collect the hand gesture data and used a simple deep neural network architecture that we called model E to recognize the actual hand gestured. The dataset that we used is collected from kaggle.com and in the form of ASL (American Sign Language) datasets. We doing accuracy comparison with another existing model such as AlexNet to see how robust our model. We find that by adjusting kernel size and number of epoch for each model also give a different result. After comparing with AlexNet model we find that our model E is perform better with 96.82% accuracy.
Design of a wideband strip helical antenna for 5G applications
Authors: Zeain Mohammed Yousif , Abu M. , Zakaria Z. , Abdullah Al-Gburi Ahmed Jamal , Syahputri R. , Toding A. , Sriyanto Sriyanto
Published: August 2020

This paper presents the design of wideband strip helical antenna for 5G Application. The strip helical antenna is designed for 5G and wideband applications that provide a wide bandwidth and circular polarization. The helical antenna is planned on at 5.8 GHz frequency by using Teflon material. The new designed strip is printed on a substrate then rolled into a helix shape to achieve circular polarization without an impedance matching and that the proposed antenna can be used for potential applications in wideband wireless communication. A wideband bandwidth of 2.41 GHz with a resonant frequency at 5.8 GHz is achieved by the helical antenna on the Teflon substrate. The presented antenna on Teflon substrate has achieved a gain of 11.2 dB. The antenna design parameters and the simulated results are achieved using the commercial software CST. The proposed antenna can be used for various wireless applications such as Wideband, Ultra wideband, 5G and wireless Applications.
Adaptive infill sampling strategy for metamodeling: Challenge and future research directions
Authors: Razali Che Munira Che , Abdullah Shahrum Shah , Parnianifard Amir , Faruq Amrul
Published: August 2020

The widespread use of computer experiments for design optimization has made the issue of reducing computational cost, improving accuracy, removing the “curse of dimensionality” and avoiding expensive function approximation becoming even more important. Metamodeling also known as surrogate modeling, can approximate the actual simulation model allowing for much faster execution time thus becoming a useful method to mitigate these problems. There are two (2) well-known metamodeling techniques which is kriging and radial basis function (RBF) discussed in this paper based on widely used algorithm tool from previous work in modern engineering design of optimization. An integral part of metamodeling is in the method to sample new data from the actual simulation model. Sampling new data for metamodeling requires finding the location (or value) of one or more new data such that the accuracy of the metamodel can be increased as much as possible after the sampling process. This paper discussed the challenges of adaptive sampling in metamodel and proposed an ensemble non-homogeneous method for best model voting to obtain new sample points.
Prediction of surface leakage current of overhead insulators under environmental and electrical stresses
Authors: Abdullah F. S. , Piah M. A. M. , Othman N. A. , Din A.
Published: August 2020

Leakage current is one of the critical aspects to consider for overhead transmission line insulator’s condition and performance assessment. As the leakage current increase, the size of the dry band also will increase leads to the dry band arcing, deteriorate the insulator performance and contribute to the development of insulator flashover. Based on the literature study, other than the existence of contaminations on the surface of insulator combined with moisture, the variation in leakage current is also affected by the environmental and electrical stresses. Previous researches have shown the effect of environmental and electrical stresses on surface leakage current based on experimental and simulation results. This paper outlines an analytical approach based on dimensional analysis to propose a new mathematical model of leakage current under environmental and electrical stresses. To justify the applicability of the derived dimensional model, the new model has been validated using previous researcher’s experimental results. The validation indicated that the proposed model had shown a good agreement with the previous experimental results. The proposed dimensional equation for this research work can be potentially used as a predictive performance model to evaluate and monitor the leakage current and insulator’s performance
A compact triband microstrip antenna utilizing hexagonal CSRR for wireless communication systems
Authors: Baba Murtala Aminu- , A. Rahim Mohamad Kamal , Zubir Farid , Mohd Yusoff Mohd Fairus , Iliyasu Adamu Y , Gajibo Mohammed Mustapha , Majid Huda A. , Jahun K. I
Published: August 2020

In this paper, a compact triband printed antenna with hexagonal complementary split-ring resonators (CSRRs) for 4G applications is proposed. The proposed multiband antenna is comprised of a rectangular patch antenna on the top plane, while on the ground plane, hexagonal CSRRs are etched for size miniaturization (at the lower bands) and multiband generation. Another effect of the CSRR is the shifting of the initial resonance of the patch antenna from 5.17 GHz to the higher band of 6.18 GHz. The triband of 180 MHz 2.4~2.59, 150 MHz 2.79~2.94 and 420 MHz 6.04~6.46 GHz bands acquired can cover WLAN/Wi-Fi and WiMAX operating bands adequately. This can be achieved by choosing the optimal size and position of the CSRR on the ground plane carefully. The design occupies a total size of 45 x 45 mm2 using the low-cost FR-4 substrate. Good agreements are obtained between the measured results and the simulated, which are discussed and presented.
Wideband frequency reconfigurable metamaterial antenna design with double H slots
Authors: Iliyasu Adamu Y. , Hamid Mohamad Rijal , Rahim Mohamad Kamal A. , Yusoff Mohd Fairus Mohd , Baba Murtala Aminu- , Gajibo Mohammed Mustapha
Published: August 2020

This paper presents the design of wideband frequency reconfigurable metamaterial antenna with double H slots. The design is based on the idea of composite right/left-handed transmission line (CRLH-TL) technique. Bandwidth enhancement was achieved by utilizing series left-handed capacitor CL transmission line parameter. The design has several outstanding advantages which include efficient bandwidth to cover many lower Application bands with multi frequency operation characteristics. A comprehensive analysis and simulation were done by using computer simulation technology (CST) software to determine the performance and efficiency of the proposed antenna. From the result obtained, the antenna aquired bandwidth range which covered (2.3-5.2) GHz which is equivalent to 77% fractional bandwidth. The wideband antenna was reconfigured by using frequency reconfiguration technique. From the reconfiguration results, the antenna can be switch from wideband to two single bands which resonate at 2.4 GHz and 4.2 GHz and to dual band which resonate at 2.4 GHz and 4.2 GHz. The realized peak gain at 2.4 GHz is 2.28 dBi and 2.58 dBi for E and H field respectively. The maximum efficiency of 96% was obtained. The antenna can be use for WLAN, proposed lower 5G band and cognitive radio system for frequency sencing.
H∞ mixed sensitivity optimization for high speed tilting trains
Authors: Hassan Fazilah , Zolotas Argyrios , Shah Shaharil Mohd
Published: August 2020

The industrial norm of tilting high speed trains, nowadays, is that of Precedence tilt (also known as Preview tilt). Precedence tilt, although succesfull as a concept, tends to be complex (mainly due to the signal interconnections between vehicles and the advanced signal processing required for monitoring). Research studies of early prior to that of precedence tilt schemes, i.e. the so-called Nulling-type schemes, utilized local-per-vehicle signals to provide tilt action (this was essentially a typical disturbance rejection-scheme) but suffered from inherent delays in the control). Nulling tilt may still be seen as an important research aim due to the simple nature and most importantly due to the more straightforward fault detection compared to precedence schemes. The work in this paper presents a substantial extension conventional to robust H∞ mixed sensitivity nulling tilt control in literature. A particular aspect is the use of optimization is used in the design of the robust controller accompanied by rigorous investigation of the conflicting deterministic/stochastic local tilt trade-off
A gesture recognition system for the Colombian sign language based on convolutional neural networks
Authors: Martínez S. Fredy H. , Betancourt Faiber Robayo , Arbulú Mario
Published: August 2020

Sign languages (or signed languages) are languages that use visual techniques, primarily with the hands, to transmit information and enable communication with deaf-mutes people. This language is traditionally only learned by people with this limitation, which is why communication between deaf and non-deaf people is difficult. To solve this problem we propose an autonomous model based on convolutional networks to translate the Colombian Sign Language (CSL) into normal Spanish text. The scheme uses characteristic images of each static sign of the language within a base of 24000 images (1000 images per category, with 24 categories) to train a deep convolutional network of the NASNet type (Neural Architecture Search Network). The images in each category were taken from different people with positional variations to cover any angle of view. The performance evaluation showed that the system is capable of recognizing all 24 signs used with an 88% recognition rate.
Indonesian language email spam detection using N-gram and Naïve Bayes algorithm
Authors: Vernanda Yustinus , Hansun Seng , Kristanda Marcel Bonar
Published: August 2020

Indonesia is ranked the top 8th out of the total country population in the world for the global spammers. Web-based spam filter service with the REST API type can be used to detect email spam in the Indonesian language on the email server or various types of email server applications. With REST API, then there will be data exchange between the applications with JSON data type using existing HTTP commands. One type of spam filter commonly used is Bayesian Filtering, where the Naïve Bayes algorithm is used as a classification algorithm. Meanwhile, the N-gram method is used to increase the accuracy of the implementation of the Naïve Bayes algorithm in this study. N-gram and Naïve Bayes algorithms to detect spam email in the Indonesian language have successfully been implemented with accuracy around 0.615 until 0.94, precision at 0.566 until 0.924, recall at 0.96 until 1.00, and F-measure at 0.721 until 0.942. The best solution is found by using the 5-gram method with the highest score of accuracy at 0.94, precision at 0.924, recall at 0.96, and F-measure value at 0.942.
Blob adaptation through frames analysis for dynamic fire detection
Authors: Indrabayu Indrabayu , Hardian Putra Rahmat , Nurtanio Ingrid , Areni Intan Sari , Bustamin Anugrayani
Published: August 2020

This study was aiming at helping visually impaired people to detect and estimate the fire distance. Blind people had difficulty knowing the existence of fire at a safe distance; hence the possibility of burning could occur. The color models and blob analysis methods were used to detect the presence of fire in the blind path. Before the fire detection stage, the cascade of the HSV and RGB color models was applied to segment the reddish fire color. The size and shape of a dynamic fire were the parameters used in this paper to distinguish fire from non-fire objects. Changes in the area of the fire object obtained at the Blob analysis stage per 10 frames were the main contributions and novelty in this paper. After the fire is detected, the calculation of the fire distance to a blind person was completed using a pinhole model. This research used 35 data videos with a resolution of 480x640 pixels. The results showed that the fire detection system and the distance estimation achieved an accuracy of 88.86% and the MSE of 0.0358, respectively.
Marketplace affiliates potential analysis using cosine similarity and vision-based page segmentation
Authors: Zulfikar Wildan Budiawan , Irfan Mohamad , Ghufron Muhammad , Jumadi Jumadi , Firmansyah Esa
Published: August 2020

One success factor of an online affiliate is determined by the quality of the content source. Therefore, affiliate marketplaces need to do an objective assessment to retrieve content data that will be used to choose the right product in the appropriate product filter. Usually, the selection is not made using a good and measured system so that the selection of product content is only based on parts that are not in accordance with what is seen or subjective. However, if analyzed using a good and measurable system will produce an objective product content and can have a positive impact on users because the selection is based on factual data. The purpose of this research is to analyze the potential of the affiliate marketplace by combining cosine similarity with vision-based page segmentation. This is a new breakthrough made for optimization to get the best content in accordance with the required criteria. This work will produce a number of product recommendations that are appropriate for publication and then made use of for comparison that matches the required criteria. At the limited evaluation stage, the performance of the proposed model obtained satisfactory results, in which 5 queries tested were all as expected.
LoRa driven medical adherence system
Authors: Sherif Suheib , Tan Wooi Haw , Ooi Chee Pun , Sherif Abubaker , Mansor Sarina
Published: August 2020

Recent discovered technologies have exposed many new theories and possibilities to improve our standard of living. Medical assistance has been a major research topic in the past, many efforts were put in to simplify the process of following treatment prescriptions. This paper summarizes the work done in developing LoRa driven medical adherence system in order to improve medicine adherence for elderlies. The designed system is composed of two sections; embedded hardware device for the use of patients at home and Web application to manage all patients along with their medicines and keep track of their medicine intake history. LoRa wireless communication technology is used for connecting all embedded devices with a central gateway that manages the network. Hardware and software tests have been conducted and showed great performance in terms of LoRa network range and latency. In short, the proposed system shows promising method of improving medicine adherence.
Textile-based electrode for electrocardiography monitoring
Authors: Saleh Syaidah Md , Abdul-Kadir Nurul Ashikin , Che Harun Fauzan Khairi , Wicaksono Dedy H. B.
Published: August 2020

The increasing demand of smart garment for monitoring people’s health is due to comfortability, lightweight and flexibility properties of the textile could offer to the user. The textile-based electrocardiography (ECG) electrode is an alternative of commercially available silver/silver chloride (Ag/AgCl) electrode which could cause skin allergies to certain users and is not suitable for long-term monitoring electrode. In this paper, we report the performance of reduced graphene oxide (rGO) coated cotton fabric electrode to the effect of longevity and temperature. The ECG waveform and signal-to noise ratio (SNR) of the rGO-coated cotton electrodes were compared to that the performance of Ag/AgCl electrodes. The reliability characterization confirmed the rGO-coated cotton fabric conductance maintain at more than 80% even after 100 days of fabrication and the conductance measurement is increasing with respect to the temperature applied. The electrode shows lower in impedance value and the performance in acquiring ECG signal is comparable with the Ag/AgCl electrode. The vertical position rectangle-shaped electrode is recommended in measuring ECG signals. In conclusion, the rGO-coated cotton electrode with flexible dry-type electrode and excellent performance especially reliability and in capturing ECG signal had shown a promising result for further development.
Graphene/PSMA composite for gas sensing application
Authors: Muhar Hanis Camelia , Sahar Noor Syazwana , Che Harun Fauzan Khairi , Abdul-Kadir Nurul Ashikin
Published: August 2020

This paper presents the fabrication of conducting polymer sensor which comprise of graphene-poly styrene-co-maleic acid (PSMA) composite that responds to volatile organic compound (VOC) via a change in the electrical resistance of the sensors. Five sensors composed of different material ratio were fabricated to find out the most prominent weight percentage ratio (wt %) for optimum sensor response. Those materials were deposited onto silver electrode using drop-casting method. NI Card PCIE-6323 measures the voltage obtained from the sensor circuit and the resistance of the gas sensor monitored using LabVIEW instrument. It was observed from the experiments that combination of 60% graphene and 40% PSMA gives the highest sensor response.
On the benefit of logic-based machine learning to learn pairwise comparisons
Authors: Qomariyah Nunung Nurul , Kazakov Dimitar , Fajar Ahmad Nurul
Published: August 2020

In recent years, many daily processes such as internet web searching, e-mail filter-ing, social media services, e-commerce have benefited from machine learning tech-niques (ML). The implementation of ML techniques has been largely focused on blackbox methods where the general conclusions are not easily interpretable. Hence, theelaboration with other declarative software models to identify the correctness and com-pleteness of the models is not easy to perform. On the other hand, the emerge of somelogic-based machine learning techniques with their advantage of white box approachhave been proven to be well-suited for many software engineering tasks. In this paper,we propose the use of a logic-based approach to learn user preference in the form ofpairwise comparisons. APARELL as a novel approach of inductive learning is able tomodel the user’s preferences in description logic representation. This offers a rich, re-lational representation which is then can be used to produce a set of recommendations.A user study has been performed in our experiment to evaluate the implementation ofpairwise preference recommender system when compared to a standard list interface.The result of the experiment shows that the pairwise interface was significantly betterthan the other interface in many ways.
A low complexity partial transmit sequence approach based on hybrid segmentation scheme
Authors: Fadel Ali Hussein , Razzaq Hasanain H. , Mostafa Salama A.
Published: August 2020

The partial transmit sequences (PTS) is regarded as a promising scheme for inhibiting ‎the high peak-to-average power ratio (PAPR) problem in the orthogonal frequency division ‎multiplexing (OFDM) systems. The PTS scheme relies on partitioning the ‎data sequence into subsets and weighting these subsets by a group of the phase rotation ‎factors. Although the PTS can efficiently reduce the high PAPR value, a great ‎computational complexity (CC) level restricts the utilization of the PTS scheme in practical ‎applications. In PTS, there are three common types of segmentation schemes; ‎interleaving (IL-PTS), pseudo-random (PR-PTS), and adjacent (Ad-PTS) schemes. This ‎paper presents a new algorithm named hybrid pseudo-random and interleaving cosine wave shape ‎‎(H-PRC-PTS) by combining the PR-PTS scheme and the symmetrical ‎interleaving cosine wave shape (S-IL-C-PTS) scheme which was proposed in our previous ‎work. The results indicate that the suggested algorithms can ‎diminish the PAPR value like the PR-PTS scheme, whereas the CC level is reduced significantly.
Virtual reality trajectory of modified PUMA 560 by hybrid intelligent controller
Authors: Al Mashhadany Yousif I.
Published: August 2020

The high performance is a goal for all designers to get better, faster, or more efficient than others. This paper proposes a design for virtual reality (VR) of modified PUMA 560 by hybrid controller between adaptive neuro fuzzy inference system (ANFIS) controller and fractional order proportional, integral, derivative (FOPID) controller. The main purpose is to obtain the optimal trajectory by get the best value of controller’s parameters that regulate the manipulator movements smoothly to the desired target. The procedure of design start by obtains the optimal values of the traditional PID controller parameters normally. The next step is applied the FOPID controller with high accuracy. It is high performance to control the perplexing physics system than, the classical integer order of PID controller. The final step to get high performance of the control system under considers is achieved by hybrid between FOPID with ANFIS controller which used the pervious output as predictive point. The whole proposed hybrid controller model was simulated and reproduction by MATLAB Version 2019b and Robotic system Toolbox 9. The optimal design of this controller is applied with 3D model of modified PUMA 560 which design by using VR technique under MATLAB/Simulink.
Development and testing of an FPT.AI-based voicebot
Authors: Tran Duc Chung , Nguyen Duc Long , Hassan Mohd. Fadzil
Published: August 2020

In recent years, voicebot has become a popular communication tool between humans and machines. In this paper, we will introduce our voicebot integrating text-to-speech (TTS) and speech-to-text (STT) modules provided by FPT.AI. This voicebot can be considered as a critical improvement of a typical chatbot because it can respond to human’s queries by both text and speech. FPT Open Speech, LibriSpeech datasets, and music files were used to test the accuracy and performance of the STT module. For the TTS module, it was tested by using text on news pages in both Vietnamese and English. To test the voicebot, Homestay Service topic questions and off-topic messages were input to the system. The TTS module achieved 100% accuracy in the Vietnamese text test and 72.66% accuracy in the English text test. In the STT module test, the accuracy for FPT open speech dataset (Vietnamese) is 90.51% and for LibriSpeech Dataset (English) is 0% while the accuracy in music files test is 0% for both. The voicebot achieved 100% accuracy in its test. Since the FPT.AI STT and TTS modules were developed to support only Vietnamese for dominating the Vietnam market, it is reasonable that the test with LibriSpeech Dataset resulted in 0% accuracy.
Photoacoustic technology for biological tissues characterization
Authors: Chua Hui Ling , Huong Audrey
Published: August 2020

The existing photoacoustics (PA) imaging systems showed mixed performance in imaging characteristic and signal-to-noise ratio (SNR). This work presents the use of an in-house assembled PA system using a modulating laser beam of wavelength 633 nm for two-dimensional (2D) characterization of biological tissues. The differentiation of the tissues in this work is based on differences in their light absorption, wherein the produced photoacoustic signal detected by a transducer was translated into phase value that corresponds to the peak amplitude of optical absorption of tissue namely fat, liver and muscle. This work found fat tissue to produce the strongest PA signal with mean ± standard deviation (SD) phase value = 2.09 ± 0.31 while muscle produced the least signal with phase value = 1.03 ± 0.17. This work discovered the presence of stripes pattern in the reconstructed images of fat and muscle resulted from their structural properties. In addition, a comparison is made in an attempt to better assess the performance of the developed system with the related ones. This work concluded that the developed system may use as an alternative, noninvasive and label-free visualization method for characterization of biological tissues in the future.
Non-invasive glucose monitoring devices: A review
Authors: Mohamad Yunos Muhammad Farhan Affendi , Nordin Anis Nurashikin
Published: August 2020

Diabetes is a growing chronic disease that affect millions of people in the world. Regular monitoring of blood glucose levels in patients is necessary to keep the disease under control. Current methods of blood glucose monitoring devices are typically invasive, causing discomfort to the patients. Non-invasive glucose monitoring devices are a possible game changer for diabetic patients as it reduces discomfort and provides continuous monitoring. This manuscript presents a review of non-invasive glucose biosensors with particular focus on leading technologies available in the market, such as microwave sensing, near-infrared spectroscopy, iontophoresis, and optical methods. This paper intends to describe non-invasive blood glucose monitoring methods using various biological fluids (sweat, saliva, interstitial fluid, urine), highlighting the advantages and drawbacks in latest device development. This review also discusses future trends of glucose detection devices and how it will improve patients’ quality of life.
Automatic whole-body bone scan image segmentation based on constrained local model
Authors: Rachmawati Ema , Jondri Jondri , Ramadhani Kurniawan Nur , Kartamihardja Achmad Hussein Sundawa , Achmad Arifudin , Shintawati Rini
Published: August 2020

In Indonesia, cancer is very burdensome financially for sufferers as well as for the country. Increasing the access to early detection of cancer can be a solution to prevent the situation from worsening. Regarding the problem of cancer lesion detection, a whole-body bone scan image is the primary modality of nuclear medicine for the detection of cancer lesions on a bone. Therefore, high segmentation accuracy of the whole-body bone scan image is a crucial step in building the shape model of some predefined regions in the bone scan image where metastasis was predicted to appear frequently. In this article, we proposed an automatic whole-body bone scan image segmentation based on constrained local model (CLM). We determine 111 landmark points on the bone scan image as the input for the model building step. The resulting shape and texture model are further used in the fitting step to estimate the landmark points of predefined regions. We use the CLM-based approach using regularized landmark mean-shift (RLMS) to lessen the effect of ambiguity, which was struggled by the CLM-based approach. From the experimental result, we successfully show that our proposed image segmentation system achieves higher performance than the general CLM-based approach.
Ambivalent Adpositions and “P-Stranding” in Russian
Authors: Philippova Tatiana
Published: August 2020

P(reposition)-stranding is typologically rare. Nevertheless, many languages exhibit phenomena that look like P-stranding (Campos 1991, Poplack, Zentz, and Dion 2012) or involve P-stranding under common theorizing (see Philippova 2014 and references therein). These studies argue that these are not instances of P-complement movement and provide alternative analyses. This squib addresses Russian prepositions that can be postposed to and apparently stranded by their dependents. They are proposed to be PPs rather than P-heads, with dative dependents adjoined similarly to external possessors. The analysis captures all idiosyncrasies of their nominal dependents and alleviates the need to posit exceptional P-stranding in Russian.
Two new calcicolous species of Pinguicula sect. Pinguicula (Lentibulariaceae) growing on rocky habitats of the Iberian Peninsula

Authors: CRESPO MANUEL B. , MARTÍNEZ-AZORÍN MARIO , ALONSO MARÍA ÁNGELES , SÁEZ LLORENÇ
Published: August 2020

Two new rupicolous species of Pinguicula are described from the limestone and dolomitic mountain ranges of central and southern Iberian Peninsula, which were previously identified as P. submediterranea, P. mundi or P. dertosensis. First, the name P. tejedensis sp. nov. is applied to populations concealed to the high elevation areas of Sierra de Tejeda and Sierra de Almijara, in Granada Province (Andalusia, southern Iberian Peninsula). They resemble P. submediterranea, a name here revived for the Subbetic populations of Jaen Province, but its floral features, fruits and seeds allow easy differentiation. Second, P. casperiana is proposed to name populations occurring in the medium to high elevation areas of Serranía de Cuenca, between Cuenca and Guadalajara Provinces (Castilla-La Mancha, central-eastern Iberian Peninsula). Members of the Castillian species are closer to P. dertosensis and also akin to P. mundi, but again their floral features, fruits and seeds allow safe recognition. Both species are significantly different to each other and with regard to their morphologically close relatives, and they also show molecular divergences that support recognition at species rank. Data on morphological traits, ecology, distribution, biogeography and phylogenetic relationships are also presented.
Peliosanthes nagalandensis and P. tobuensis (Asparagaceae: Nolinoideae)—two new species from Northeastern India

Authors: ODYUO NRIPEMO , ROY DILIP KR. , LYTAN RIKERTRE , TANAKA NORIYUKI , MAO ASHIHO A.
Published: August 2020

Two new species of Asparagaceae (subfamily Nolinoideae), Peliosanthes nagalandensis and P. tobuensis, from the state of Nagaland, Northeastern India, are described and illustrated. P. nagalandensis is most closely related to P. arunachalensis, but differs mainly by the longer leaf blades, distinctly sigmoid flowering stem with a shorter peduncle and longer raceme, more numerous green to purple flowers, distally finely denticulate-erose perianth segments, basally hamately recurved anthers and papillulate pistil with an apically slightly concave ovary and a columnar style. While P. tobuensis is close to P. arunachalensis and P. sinica, but differs mainly by the strongly incurved, entire corona and ovoid pistil with obtusely conical indistinct style.
Nomenclature of Brochoneura and Cephalosphaera (Myristicaceae), with a replacement name, Neobrochoneura, and new combinations in this genus for Madagascan species previously included in Brochoneura

Authors: FIGUEIREDO ESTRELA , SMITH GIDEON F.
Published: August 2020

The genus name Brochoneura Warburg (1895a: 179; also mentioned in Warburg 1895b: 272) was published with a single species described in it, B. usambarensis Warburg (1895a: 180; also mentioned in Warburg 1895b: 272) from East Africa. Note that both Warburg (1895a) and Warburg (1895b) were published in July 1895 (Stafleu & Cowan 1976: 763). The description of Brochoneura was though clearly published by Warburg (1895a: 179). In Warburg (1895a: 179, but not in Warburg 1895b: 272), reference was also made to three unnamed Madagascan species that likely belong in Brochoneura, but without combinations having been made for them in that genus. In a subsequent publication, Warburg (1897) included these three Madagascan species in Brochoneura, as B. madagascariensis (Lamarck 1791: 163) Warburg (1897: 234), B. acuminata (Lamarck 1791: 164) Warburg (1897: 237), and B. vouri (Baillon 1885: 454) Warburg (1897: 238). Warburg (1897) also retained his earlier B. usambarensis, which dates from 1895, in Brochoneura, but indicated it with a “(?)”, as was done by Warburg (1895b: 272).
A new species of Bruchomyiinae (Diptera: Psychodidae) from Baltic amber
Authors: SKIBIŃSKA KORNELIA , SZADZIEWSKI RYSZARD , KANIA IWONA , KRZEMIŃSKI WIESŁAW
Published: August 2020

Bruchomyiinae is one of seven subfamilies of Psychodidae. This small group comprises fewer than 60 extant species distributed mainly in tropical and sub-tropical regions (Wagner & Stuckenberg 2016). All life stages of these flies are closely tied to forest environment (Fairchild 1952; Stuckenberg 1962) and as a result, bruchomyiines are frequently preserved in fossil resins. The first fossil member of this subfamily was described from Baltic amber (45 Ma) (Meunier 1905) and Burmese amber (100 Ma) is the oldest fossil resin in which representatives of Bruchomyiinae have been found (Stebner et al. 2015; Wagner 2017; Skibińska et al. 2019). Due to the relative scarcity of this subfamily in Baltic amber, any new specimens are of great interest. Up till now, there are only 12 bruchomyiine species described from Baltic amber. Wagner (2017) completed a revision of fossil Bruchomyiinae and proposed the genus Hoffeinsodes to include the species having male genitalia with gonocoxites fused with hypandrium. In this genus, he classified six species reported exclusively from Eocene Baltic amber: H. bifida Wagner, 2017, H. cubicula Wagner, 2017, H. longicauda Wagner, 2017, H. obtusa Wagner, 2017, H. reducta Wagner, 2017 and H. hoffeinsi (Wagner, 2006) transferred from Nemopalpus (Wagner, 2006). Here, we describe a new species belonging to this genus.