bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Ideological and Political Education under Deep Learning Neural Network
Authors: Li Binqiang , Wang Huizhen
Published: August 2022

Under the background of the rapid development of the new generation of information technology, artificial neural networks (ANNs) have made some progress in the evaluation research of various courses in colleges and universities. However, there is little research on the application of ANNs in Ideological and Political Education (IPE) courses. Based on this, this work attempts to introduce the Backpropagation Neural Network (BPNN) into the evaluation system of IPE courses. Firstly, the structure and characteristics of the BPNN are given, and it is optimized by the genetic algorithm based on its characteristics. Secondly, the theoretical framework of IPE course evaluation is established, and the corresponding evaluation model is constructed using the optimized BPNN. Finally, a questionnaire survey is designed to analyze the current situation of IPE evaluation in colleges and universities, and a simulation experiment is set up to test the BPNN evaluation model before and after optimization. The results are as follows. First, there are mainly five evaluation methods for IPE courses in Chinese colleges and universities: 6/4, 3/7, 2/2/6, 5/5, and 3/3/4. Second, the training error value of the BPNN model is in the interval (−2.3, 2.2), and when the number of cycles is 552, the error is infinitely close to zero. Thirdly, the training error value of the optimized BPNN model is in the interval (−0.22, 1.2), and when the number of cycles is 775, the error is infinitely close to zero. Fourthly, the error between the output value of the optimized BPNN model and the expert score value is generally smaller than the error value before optimization. This work aims to provide a theoretical reference for the further application of neural network technology in the evaluation of IPE.
Application and Research of Computer Intelligent Technology in Modern Agricultural Machinery Equipment
Authors: Zhou Hongyu , Liu Jinqi , Huang Fan
Published: August 2022

Every country, including China, is deeply concerned and interested in the topic of agricultural machinery automation. The world’s population is growing at an astronomical rate, and as a result, the need of food is also growing at an astronomical rate. Farmers are forced to apply more toxic pesticides since traditional methods are not up to the task of meeting the rising demand. This has a major impact on agricultural practices, and in the long run, the land becomes barren and unproductive. Intelligent technologies such as Internet of Things, wireless communication, and machine learning can help with crop disease and pesticide storage management, as well as water management and irrigation. In this paper, we design and analyze an intelligent system that automatically predicts the agricultural land features for irrigation purpose. Initially, the dataset is collected and preprocessed using normalization. The features are extracted using principal component analysis (PCA). For automatic prediction by the equipment, we propose heterogeneous fuzzy-based artificial neural network (HF-ANN) with genetic quantum spider monkey optimization (GQ-SMO) algorithm. Analyses and comparisons are made between the proposed approach and current methodologies. The findings indicate the effectiveness of the proposed system.
Alternative Lengthening of Telomeres in Cancer Confers a Vulnerability to Reactivation of p53 Function
Authors: Macha Shawn J. , Koneru Balakrishna , Burrow Trevor A. , Zhu Charles , Savitski Dzmitry , Rahman Rakhshanda L. , Ronaghan Catherine A. , Nance Jonas , McCoy Kristyn , Eslinger Cody , Reynolds C. Patrick
Published: August 2022

A subset of cancers across multiple histologies with predominantly poor outcomes use the alternative lengthening of telomeres (ALT) mechanism to maintain telomere length, which can be identified with robust biomarkers. ALT has been reported to be prevalent in high-risk neuroblastoma and certain sarcomas, and ALT cancers are a major clinical challenge that lack targeted therapeutic approaches. Here, we found ALT in a variety of pediatric and adult cancer histologies, including carcinomas. Patient-derived ALT cancer cell lines from neuroblastomas, sarcomas, and carcinomas were hypersensitive to the p53 reactivator eprenetapopt (APR-246) relative to telomerase-positive (TA+) models. Constitutive telomere damage signaling in ALT cells activated ataxia-telangiectasia mutated (ATM) kinase to phosphorylate p53, which resulted in selective ALT sensitivity to APR-246. Treatment with APR-246 combined with irinotecan achieved complete responses in mice xenografted with ALT neuroblastoma, rhabdomyosarcoma, and breast cancer and delayed tumor growth in ALT colon cancer xenografts, while the combination had limited efficacy in TA+ tumor models. A large number of adult and pediatric cancers present with the ALT phenotype, which confers a uniquely high sensitivity to reactivation of p53. These data support clinical evaluation of a combinatorial approach using APR-246 and irinotecan in ALT patients with cancer.

Significance:

This work demonstrates that constitutive activation of ATM in chemotherapy-refractory ALT cancer cells renders them hypersensitive to reactivation of p53 function by APR-246, indicating a potential strategy to overcome therapeutic resistance.
The More Extensive the Spread through Air Spaces, the Worse the Prognosis Is: Semi-Quantitative Evaluation of Spread through Air Spaces in Pulmonary Adenocarcinomas
Authors: Zombori-Tóth Noémi , Paróczai Dóra , Lantos Judit , Almási Szintia , Sejben Anita , Tiszlavicz László , Cserni Gábor , Furák József , Zombori Tamás
Published: August 2022

Introduction: The extent of spread through air spaces (STAS) is less investigated among patients with lung adenocarcinoma who underwent sublobar resection. Therefore, we aimed to evaluate the extent of STAS semi-quantitatively, to assess its prognostic impact on overall survival (OS) and recurrence-free survival (RFS), and to investigate the reproducibility of this assessment. Methods: The number of tumour cell clusters and single tumour cells within air spaces was recorded in three different most prominent areas (200x field of view). The extent of STAS was categorized into three groups, and the presence of free tumour cluster (FTC) was recorded. Results: Sixty-one patients were included. Recurrence was more frequent with higher grade (p = 0.003), presence of lymphovascular invasion (p = 0.027), and presence of STAS of any extent (p = 0.007). In multivariate analysis, presence of FTC (HR: 5.89; 95% CI: 1.63–21.26; p = 0.005) and more pronounced STAS (HR: 7.46; 95% CI: 1.60–34.6; p = 0.01) had adverse impact on OS and RFS, respectively. Concerning reproducibility, excellent agreement was found among STAS parameters (ICC range: 0.92–0.94). Discussion: More extensive STAS is an unfavourable prognostic factor in adenocarcinomas treated with sublobar resection. As the evaluation of extent of STAS is reproducible, further investigation is required to gather more evidence.
Subarachnoid and Intraventricular Hemorrhage in a Patient with a Pure Arterial Malformation and Two Associated Aneurysms in the Posterior Inferior Cerebellar Artery: A Case Report and Literature Review
Authors: Wójtowicz Katarzyna , Przepiórka Łukasz , Kunert Przemysław , Marchel Andrzej
Published: August 2022

Introduction: Pure arterial malformations (PAMs) are rare vascular abnormalities defined as dilated, tortuous arterial loops without any associated venous compartment. PAMs are thought to be benign developmental anomalies that can be safely managed conservatively. Methods: We present a case of life-threatening hemorrhage in a patient with a PAM associated with two aneurysms and review the literature describing hemorrhages associated with PAMs. Results: A 65-year-old female presented with subarachnoid and intraventricular hemorrhage. A digital subtraction angiography revealed a posterior inferior cerebellar artery PAM associated with two saccular aneurysms, which were subsequently microsurgically clipped. At the 1-year follow-up, the patient was neurologically intact. In our literature review, we identified 21 papers describing a total of 37 PAMs. Patients were predominantly female (64.9%) and their median age was 35 years. Almost half (48.6%) of PAMs were associated with aneurysms. In the group of PAMs that were not associated with an aneurysm, the intracranial hemorrhage rate was 15.8%, while in cases of coexisting PAM and aneurysm it was 44.4% (p = 0.0789). Conclusions: PAM natural history remains unknown, particularly in cases of coexistence with aneurysms. Patients so affected require careful observation. The description of PAMs as benign vascular malformations should be revised. Surgical management of hemorrhagic PAMs coexisting with aneurysms is possible and should be considered.
Linear Low-Intensity Extracorporeal Shockwave Therapy as a Method for Penile Rehabilitation in Erectile Dysfunction Patients after Radical Prostatectomy: A Randomized, Single-Blinded, Sham-Controlled Clinical Trial
Authors: Motil Igor , Macik Daniel , Sramkova Katerina , Jarkovsky Jiri , Sramkova Tatjana
Published: August 2022

Introduction: The objective of this study was to investigate the effect and feasibility of linear low-intensity extracorporeal shockwave therapy (LI-LiESWT) as a penile rehabilitation method for erectile dysfunction (ED) after bilateral nerve-sparing (NS) radical prostatectomy (RP). Methods: Patients who had undergone bilateral NS RP (either radical retropubic prostatectomy or robot-assisted laparoscopic RP), 3 or more months prior to the study, and who had no ED preoperatively and were suffering from mild to severe postoperative ED were included in the study. Four treatments were given over a 4-week period, using the PiezoWave2 device with a linear shockwave applicator and the linear shockwave tissue coverage (LSTC-ED®) technique. If the improvement in erectile function was still considered insufficient (less than an IIEF-5 score of 22–25) at 2 months after the start of LI-LiESWT, penile rehabilitation was supplemented by pharmacological penile rehabilitation. The final effect of treatment was evaluated after 12 months. The main outcome measure was changes in the five-item International Index of Erectile Function (IIEF-5) score. Results: Between September 2019 and September 2020, a total of 40 patients were included in the study and randomly divided into 2 groups: treatment group and sham group. Eight patients were excluded from the study and were not evaluated due to other conditions which required additional treatment (COVID-19 disease, postoperative incontinence, urethral stricture, and ischemic stroke). Thirty-two patients were included in the final analysis: 16 in the control group and 16 in the intervention group. At 6 months from the end of treatment, patients in both the treatment and the sham group achieved physiological IIEF-5 values, and the beneficial effect persisted for 12 months after the end of treatment. Conclusions: LI-LiESWT using the LSTC-ED® technique is a suitable and safe method for penile rehabilitation in patients with ED after bilateral NS RP, not only because of the vasculogenic effect of LI-LiESWT but also because of its neuroprotective and/or regenerative effects.
Impact of Prosthetic Valve Regurgitation Assessed by Echocardiography and Magnetic Resonance Imaging on Long-Term Clinical Outcomes after TAVR
Authors: Abdelghani Mohammad , Hemetsberger Rayyan , Landt Martin , Zachow Dirk , Beurich Hans-Wilko , Toelg Ralph , Abdel-Wahab Mohamed , Richardt Gert , Merten Constanze
Published: August 2022

Background: Prosthetic valve regurgitation (PVR) impairs early and mid-term outcomes after transcatheter aortic valve replacement (TAVR). We explored the impact of PVR assessed by transthoracic echocardiography (TTE) and magnetic resonance imaging-regurgitation fraction (MRI-RF) on long-term clinical outcomes. Methods: PVR was assessed by TTE applying the Valve Academic Research Consortium criteria and MRI-RF (from velocity-encoded phase contrast magnetic resonance sequence) in 424 patients. Results: MRI-RF correlated modestly with the echocardiographic grades of PVR (Spearman’s rank correlation coefficient = 0.32, p < 0.001). Using an MRI-RF ≥20% to define ≥ moderate PVR, echocardiography and MRI-RF agreed on PVR classification in 412 patients (97.2%; kappa statistic = 0.56, p < 0.001). Five-year mortality or reintervention was higher in patients with echocardiographic ≥ moderate PVR (83.3% vs. 45.0%, log rank p value = 0.002; HR [95% CI]: 3.18 [1.48–6.84]) as well as in patients with MRI-RF ≥20% (79.3% vs. 43.2%, log rank p value <0.001; HR [95% CI]: 2.68 [1.53–4.70]), while the outcomes of patients with echocardiographic mild PVR were not significantly different from those with none-trace PVR. In the two latter groups (echocardiographic < moderate PVR), MRI-RF ≥20% was associated with a significantly higher 5-year mortality or reintervention as compared with MRI-RF <20% (79.5% vs. 42.2%, log rank p value = 0.023; HR [95% CI]: 2.26 [1.10–4.65]). Conclusions: Greater than mild PVR as defined by TTE or MRI-RF is associated with impaired long-term clinical outcomes after TAVR. MRI-RF can be used to further risk-stratify patients with echocardiographic less-than-moderate PVR.
Prolonged QT Interval in Athletes: Distinguishing between Pathology and Physiology
Authors: Christou Georgios A. , Vlahos Antonios P. , Christou Konstantinos A. , Mantzoukas Stefanos , Drougias Chronis A. , Christodoulou Dimitrios K.
Published: August 2022

Background: The physiological QT prolongation in athletes is expected to widen the gray zone between physiology and pathology of QT, increasing the diagnostic challenges encountered in athletes with QT prolongation. Summary: According to international recommendations for electrocardiogram in athletes, further evaluation for long QT syndrome (LQTS) is indicated in male athletes with corrected QT (QTc) ≥470 ms and in female athletes with QTc ≥480 ms. Apart from QTc ≥500 ms, diagnostic challenges arise in borderline cases of QTc prolongation, where further clinical investigations are needed to be performed to clarify whether LQTS exists. Clinical diagnostic investigations, including exercise testing, are more readily available, convenient, and easily interpretable, as well as less costly than genetic testing for LQTS. The main findings on exercise testing that are suggestive of LQTS can be the paradoxical prolongation of QTc during exercise and QTc ≥480 ms at fourth min of recovery. Key Messages: Exercise testing appears to have an important role in the diagnostic evaluation of athletes with prolonged QT interval, when genetic testing is not available.
Uncertainty and sensitivity analysis applied on commercial tariff with off-peak tariff rider: a case study
Authors: Nizam Ibrahim Mohammad , Mohamad Anuar , @ Salleh Zainol Asri Abdul Sani , Jumidali Mohd Muzafa , Taib Azahar
Published: August 2022

Commercial Tariff with Off-Peak Tariff Rider (C1 OPTR) is one type of time-based electricity tariff. The C1 OPTR charges electricity consumers with different electricity rates instead of a flat rate tariff. This paper investigates the C1 OPTR tariff adopted recently by Universiti Teknologi MARA Cawangan Pulau Pinang (UiTMCPP) from its previous flat rate tariff. The investigation involves applying the uncertainty and sensitivity analysis to the average load factor (ALF) model of the UiTMCPP. The ALF model consists of two major factors, namely kilowatt-hour (kWh) and maximum demand (kW). The analysis aims to identify the most contributing factor between the kWh and kW to the uncertainty of the ALF in a systematic way using Monte Carlo simulation. The factor identified is important for improvement by UiTMCPP to ensure that the suitable target ALF can be easily achieved. Based on Sobol uncertainty and sensitivity analysis technique, 60,000 samples for the respective kWh and kW have been generated and executed to produce the output of the ALF model. The result of the uncertainty analysis shows that the ALF output is uncertain between 0.195 and 0.343. Furthermore, the applied sensitivity analysis discovers that the kW is the most contributing factor to the ALF output uncertainty, with the sensitivity index indicating 0.8853.
Advanced compensation scheme for enhancing photovoltaic power quality
Authors: Ehtesham Mohammad , Junaid Md
Published: August 2022

With the photovoltaic (PV) system becoming highly popular in distribution network, there is also a growing concern regarding its adverse impacts over the power quality (PQ) of integrated system. This deterioration in PQ hassparked a new interest in the filtering techniques used in the power systemfor mitigating these problems. In contrast to conventional passive filters now active power filters (APFs) are being looked as the predominant solution.This paper presents a state-estimation based effective compensation strategy for enhancing performance of employed APF scheme. A novel control technique for PQ enhancement is proposed where Kalman filtering approach has been applied for generating the reference signals. Also, an adaptive hysteresis band technique has been applied here in the switching strategy. Thus an enhanced filter performance is achieved with reduced complexity and better elimination of distortions. Simulated results obtained in MATLAB/Simulink platform have been analyzed completely, where the superiority of filtering algorithm has been also demonstrated through leasttotal harmonic distortion (THD) achieved in source current among all the existing Kalman filters.
Improving optical properties of white light-emitting diodes using triple-layer remote structure
Authors: Binh Ly Thanh , Xuan Le Phan
Published: August 2022

Inrecent efforts to improve the performance ofwhite light-emitting diode (WLEDs), researchers have focused on angular color uniformity (ACU), an effective index for evaluating the light quality of WLEDs. Inthis article, we also aim for the WLED development by applying three phosphor layers in the remote phosphor structure. The dual-layer phosphor (DLP) remote structure is also included in the research for comparison with the triple-layer phosphor (TLP) in terms of their impacts on the lighting quality of WLEDs. To ensure the diversity and applicability in different scenarios, performancesof multi-layer phosphor structures in WLED devices with average correlatedcolor temperatures (ACCTs) from 5600 K to 8500K are measured. The experimental results have proved that both TLP and DLP structures are suitable to enhance WLEDs’ performance as each structure excels at specific qualities. In particular, at all ACCTs, the DLP structure is getting better in improvingthe color rendering index (CRI), while the TLP is more advantageous to color quality scale (CQS) and light output. The TLP also presents a lower color deviation than the DLP does, which leads to a better color uniformity in WLEDs at all ACCTs.
The application of phosphor Sr4La(PO4)3O:Ce3+,Tb3+,Mn2+ on the white-LEDs: luminescence and power transmission characteristics
Authors: Nguyen Thi My Hanh , Xuan Le Phan
Published: August 2022

Using a high temperature solid-state technique, various phosphors Sr4La(PO4)3O:Ce3+, Tb3+,Mn2+ (SLPO:Ce,Tb,Mn) were produced. In Sr4La(PO4)3O, the luminescence characteristics, thermal stability, and energy conversion between Ce3+ and Tb3+-Mn2+ have been thoroughly studied. The sensitizer Ce3+ particles inclusion could considerably improve the feeble Tb3+ green radiation and Mn2+ red radiation via energy transfer. By adjusting the scale of Ce3+/Tb3+ over Ce3+/Mn2+ atoms, the color of the emission may be changed. White light was produced in the Sr4La(PO4)3O:0.12Ce3+,0.3Mn2+ specimen with chromatism coordinates of (0.3326, 0.3298), showing that the phosphors SLPO:Ce,Tb,Mn possess promising application on WLEDs. The conclusion is supported by Mie-scattering theory and Lambert-Beer's law.
Synthesis and photoluminescence properties in white light-emitting diodes of oxynitride green phosphor Ba3Si6O12N2
Authors: Nguyen Thi Dieu An , Xuan Le Phan
Published: August 2022

Utilizing boron-coated Eu2O3, highly effective Ba3Si6O12N2 green-emitting phosphors were made using a gas reduction nitridation technique under flowing NH3 gas. We found that the synthesized phosphor is a pure phase of Ba3Si6O12N2 based on X-ray diffraction patterns. By modifying an alumina boat crystallized, the Ba3Si6O12N2 green-emitting phosphors from the result were considerably better and had higher emission intensity. Under stimulation at 405 nm, the radiation spectra revealed a typical wide green radiation band attributable to the 4f65d → 4f7 electronic transfer of Eu2+ ions. Generally, the green-emitting Ba3Si6O12N2 phosphors that were created by that method with boron-coated Eu2O3 is a potential phosphor-transformed diodes which emit white illumination white light emitting diodes(pc-WLEDs') element.
Ca9La(PO4)7:Eu2+,Mn2+: a radiation-adjustable phosphor usable for high-perfomance white light-emitting diodes
Authors: Dang Huu Phuc , Ton That Phung , Xuan Le Phan , Le Thai Nguyen
Published: August 2022

We used solid-condition processes to make a sequence of radiation-adjustable phosphors Eu2+/Mn2+ co-doped Ca9La(PO4)7 (shortened as CaLa:EM), which show a consistently variable hue from green to yellow and red via an efficient resonance-form energy transition as well as the strength of green and red radiations may be controllable through altering the Mn2+concentration. We examined the transition of energy (Eu2+®Mn2+) for CaLa:EM. It is proved to be a resonant kind using a dipole-quadrupole process, having power shift critical range calculated to be 11.36 Å by using the spectral overlap techniques. Mixing a 365 nm UV-InGaN chip as well as one phosphor combination containing (Ca0.98Eu0.005Mn0.015)9La(PO4)7 in yellow with BaMgAl10O17:Eu2+in blue produced a warming WLED having CIE color coordinates measured at (0.35, 0.31), better CRI value (Ra)measured at 91.5 along with smaller CCT value of 4,496 K.
Specific absorption rate distribution evaluation in a different substrate for hyperthermia treatment
Authors: Sarpinah Sh Naimullah Bibi , Lias Kasumawati , Buniyamin Norlida , Jobli Ahmad Tirmizi , Hassan Mazlina Mansor
Published: August 2022

Hyperthermia treatment procedure (HTP) isatreatment that uses high heatgenerated from electromagnetic (EM) waves, which is about 42 °C to 45 °C within a particular duration. However, poor focus position distance on the treated tissue has become a significant concern among the researchers since it may contribute to a wide area of unwanted hot spots, which lead to severe adverse health effects on healthy tissue.This paper presents a specific absorption rate (SAR) distribution evaluation of different microstrip antenna substrates with different electrical permittivities, contributing to different sizes of microstrip antenna patches, which then provide different attainment of the SAR distribution on the treated tissue. Operating frequencies of 434MHz, 915 MHz, and 2,450 MHz with 10 W operating powerare utilized. ASEMCAD X is used to conduct a simulation in obtaining the SAR distribution, which determines the focus position distance on different tumour (malignant tissue) sizes. Based on the results, the suitable substrate for frequency 915 MHz and 2,450MHz is RT5880, and RT5870, while RO3210 and RT6010 performed their best at 434MHz and 2,450MHz. The finding of this study can be used for further research in optimizing microstrip antenna development for HTP.
Optical absorbance of RGB LEDs in pH measurement of colorimetric solution with phenol red reagent
Authors: Dali Mohd Rumaizan Maidan , Azam Aiman Shahmi , Rahma Mohamad Faizal Abd , Ahmad Khairul Azman , Othman Nor Azlan , Abdullah Mohd Hanapiah , Omar Ahmad Fairuz
Published: August 2022

The use of red, green, and blue ( RGB ) light-emitting-diode ( LED ) is a new trend in monochromatic colorimetric sensing due to cost-effective implementation. However, the application of RGB LED in pH measurement depends on the performance of the LED colour towards the colorimetric solution of interest, hence, needs to be evaluated. This work evaluated the performance of RGB LED for pH measurement system based on colorimetric approach using phenol red as a reagent. The main objective was to identify the LED colour with the best performance in terms of signal response and a bsorbance behavior. In this work, LED and photodiode were used as optical components and NI USB DAQ with LabView as the processing software. Four samples with known pH values were prepared and tested to obtain the voltage and absorbance behavior of each LED colour. Among all, the blue LED with wavelength ranged between 450 - 495 nm showed the best sensing behavior based on its linearity and error. Both voltage response and absorbance produced linear correlation with R 2=0.883 and R 2=0.9803, respectively. The significant finding from this study is useful in selecting the best RGB LED that is suitable for colorimetric pH measurement with phenol red as its colorimetric reagent.
Development of a low-cost teleoperated and semi-autonomous robotic arm
Authors: Yaacob Megat Satria Zainuddin , Jalani Jamaludin , Sadun Amirul Syafiq , Zulkarnain Abang Muhammad Zaid Abang
Published: August 2022

A safe human-robot physical interaction is required when the robot is used to help humans. This can be achieved by introducing a teleoperated robotic arm in which a human can teach the robot before performing tasks remotely. This paper develops and establishes a three-degree-of-freedom robotic arm and teaching pendant. In particular, a flexible robotic arm is operated in two different modes, namely, the teleoperated mode and the semi-autonomous mode. The teleoperated mode is a manual control using a teaching pendant, where the robot arm replicates various movements of the teaching pendant. On the contrary, the semi-autonomous mode allows the robot to execute a task from one point to another point repetitively after at least one training of the teaching pendant. The Arduino Uno board is employed as a microcontroller, and the integrated development environment ( IDE ) software is used to write and upload the computer code. A series of tests in which the robot performs different tasks is recorded to evaluate the accuracy and consistency of the semi-autonomous and teleoperated modes. The results show that the performance of the proposed low-cost teleoperated robotic arm is reliable and safe to perform various tasks based on the teaching pendant.
A Ppreliminary study on the intelligent model of k-nearest neighbor for agarwood oil quality grading
Authors: Huzir Siti Mariatul Hazwa Mohd , Mahabob Noratikah Zawani , Amidon Aqib Fawwaz Mohd , Ismail Nurlaila , Yusoff Zakiah Mohd , Taib Mohd Nasir
Published: August 2022

Essential oils extracted from trees has various usages like perfumes, incense, aromatherapy and traditional medicine which increase their popularity in global market. In Malaysia, the recognition system for identifying the essential oil quality still does not reach its standard since mostly graded by using human sensory evaluation. However, previous researchers discovered new modern techniques to present the quality of essential oils by analyse the chemical compounds. Agarwood essential oil had been chosen for the proposed integrated intelligent models with the implementation of k-nearest neighbor (k-NN) due to the high demand and an expensive natural raw world resource. k-NN with Euclidean distance metrics had better performance in terms of its confusion matrix, sensitivity, precision accuracy and specificity. This paper presents an overview of essential oils as well as their previous analysis technique. The review on k-NN is done to prove the technique is compatible for future research studies based on its performance.
Hall sensor-based speed control of a 3-phase permanent-magnet synchronous motor using a field-oriented algorithm
Authors: Shallal Abidaoun H. , Salman Saad Abdulmajeed , Sabry Ahmad H.
Published: August 2022

To achieve optimum torque per amp, we retain the angle of the stator-current-vector with respect to the rotor-flux at 90 degrees, rather than controlling the amplitude of the stator-current-vector. Without or with the load torque, the proportional integral (PI) controller produced better results in the speed control loop. A controller is required to maintain a consistent speed and improve system performance as the load changes. This work develops an auto-tuning PI speed controller for 3-phase permanent-magn et synchronous motors using field oriented algorithm. The 3-phase voltage from the grid is converted to DC through a transformer and a grid-side rectifier. The DC voltage is converted back into AC through a machine-side inverter, which drives the motor with time-varying loud. The objective of field oriented control (FOC) in this work is to control the semiconductor switches in the machine-side power inverter to achieve the desired torque and flux. The stator-currents are measured and fed into the flux observer to obtain the direct-quadrature-zero (DQ-axis) current, the rotor magn etizing current, and the angle of the synchronously rotating reference frame. The results show that the motor's speed response has an earlier transient response and a less steady-state inaccuracy after tuning the controllers during acceleration and torque load adjustments.
Optimization of ground plane antenna gain by increasing the inductance of loading coil based on silver material
Authors: Suyanta Suyanta , Marwanto Arief , Alifah Suryani
Published: August 2022

To overcome the attenuation due to signal distortion in the telex model antenna transmitter, the copper and silver coil loading materials for gain have been tested. The parameters include standing wave ratio (SWR) value≈1, the antenna impedance (ZL), return loss (RL), reflection coefficient (ρ) which measured the bandwidth (BW) and quality factor (Q). In this experiment a telex model ground antenna is used, a coaxial feeder cable with 50 Ω and an operating frequency of 144.280 MHz was used. The feeder cable is tuned to approximate pure resistive with minimum impedance to reach maximum resonance frequency. The field strength effective radiated power (ERP) is measure based on 4 measurement points which has different distances within 100 km areas. The results show that the antenna based on copper loading coil (CLC) has a bandwidth is BW=5.166 MHz and Q=27.929, moreover, the silver loading coil (SLC) antenna the bandwidth is BW=4.500 MHz and Q=32.062. Therefore, SLC material could provide a good reduction in attenuation of signal distortion when signal radiation occurs from the antenna to the air.
Design, fabrication and performance analysis of floodlight shaped microstrip antenna for Wi-Fi/IoT applications
Authors: Colaco John , Cotta Jillian
Published: August 2022

This paper proposes a design and fabrication of a floodlight-shaped microstrip patch antenna using flame-retardant (FR)-4 substrate within the frequency band of 1-6 GHz. The proposed antenna resonating at a multi-frequency band (2.01-2.2 GHz, 3.7-3.8 GHz, 4.82-4.96 GHz, and 5.61-6 GHz) is suitable for Wi-Fi and IoT applications. The proposed antenna has a size of 50×60×1.6 mm 3. The design was implemented using CADFEKO software, and the same was fabricated and measured using a vector network analyzer. Further, the performance analysis of the structure is carried out using the CADFEKO software, firstly by shifting the location of the microstrip feed line along the width of the patch and secondly by amending the structure. The verdicts show that the proposed antenna provides high impedance matching at multi-frequency bands and shows a very good agreement between simulated and fabricated results. The changed feed-line location and modified structure provide improved performance, which can be utilized for various other wireless communication channels.
Performance evaluation of chi-square and relief-F feature selection for facial expression recognition
Authors: Mahmood Mayyadah Ramiz , Abdulrazzaq Maiwan Bahjat
Published: August 2022

Pattern recognition is a crucial part of machine learning that has recently piqued scientists' interest. The feature selection method utilized has an impact on the dataset's correctness and learning and training duration. Learning speed, comprehension and execution ease, and properly chosen features influence all high-quality outcomes. The two feature selection methods, relief-F and chi-square, are compared in this research. Each technique assesses and ranks attributes based on distinct criteria. Six of the most important features with the highest ranking have been chosen. The six features are utilized to compare the performance accuracy ratios of the four classifiers: k-nearest neighbor (KNN), naive Bayes (NB), multilayer perceptron (MLP), and random forests (RF) in terms of expression recognition. The final goal of the proposed strategy is to employ the least number of features from both feature selection methods to distinguish the four classifiers' accuracy performance. The proposed approach was trained and tested using the CK+ facial expression recognition dataset. According to the findings of the experiment, RF is the best accurate classifier on chi-square feature selection, with an accuracy of 94.23 %. According to a dataset utilized in this study, the relief-F feature selection approach had the best classifier, KNN, with an accuracy of 94.93 %
Document classification using term frequency-inverse document frequency and K-means clustering
Authors: Al-Obaydy Wasseem N. Ibrahem , Hashim Hala A. , Najm Yassen AbdelKhaleq , Jalal Ahmed Adeeb
Published: August 2022

Increased advancement in a variety of study subjects and information technologies, has increased the number of published research articles. However, researchers are facing difficulties and devote a significant time amount in locating scientific research publications relevant to their domain of expertise. In this article, an approach of document classification is presented to cluster the text documents of research articles into expressive groups that encompass a similar scientific field. The main focus and scopes of target groups were adopted in designing the proposed method, each group include several topics. The word tokens were separately extracted from topics related to a single group. The repeated appearance of word tokens in a document has an impact on the document's weight, which is computed using the term frequency-inverse document frequency (TF-IDF) numerical statistic. To perform the categorization process, the proposed approach employs the paper's title, abstract, and keywords, as well as the categories' topics. We exploited the K-means clustering algorithm for classifying and clustering the documents into primary categories. The K-means algorithm uses category weights to initialize the cluster centers (or centroids). Experimental results have shown that the suggested technique outperforms the k-nearest neighbors algorithm in terms of accuracy in retrieving information.
Modification of the new conjugate gradient algorithm to solve nonlinear fuzzy equations
Authors: Abdullah Zeyad M. , M. Khudhur Hisham , Khairulla Ahmed Amera
Published: August 2022

The conjugate gradient approach is a powerful tool that is used in a variety of areas to solve problems involving large-scale reduction. In this paper, we propose a new parameter in nonlinear conjugate gradient algorithms to solve nonlinear fuzzy equations based on Polak and Ribiere (PRP) method, where we prove the descent and global convergence properties of the proposed algorithm. In terms of numerical results, the new method has been compared with the methods of Fletcher (CD), Fletcher and Reeves (FR), and Polak and Ribiere (PRP). The proposed algorithm has outperformed the rest of the algorithms in the number of iterations and in finding the best value for the function and the best value for the variables.
Remote laser welding simulation for aluminium alloy manufacturing using computational fluid dynamics model
Authors: Al-Aloosi Raghad Ahmed , Farhan Zainab Abdul-Kareem , Sabry Ahmad H.
Published: August 2022

The process of remote laser welding is simulated in this study to identify the keyhole-induced porosity generation mechanisms and keyhole. Three processes are simulated and discussed: laser power levels, laser-beam shaping configurations, and laser keyhole process. The simulation finding reveals that pore development is caused by strong melt flow behind the keyhole. As verification, the equivalent experimental test is also carried out. According to the findings, a welding speed with a high level helps to keep the keyholes released and prevents the flow of strong melt; a big advanced leaning-angle also provides inactive molten pool flow, making it difficult for bubbles to float to the backside of the molten pool. The conclusions of this study offer crucial insight into the method of porosity of aluminum (Al) alloys laser welding, as well as advice on how to avoid keyhole-induced porosity. It is also obtained that a smaller laser beam with constant power raises the velocity, welding pool depth, and liquid metal temperature.
Entropy-based distributed denial of service attack detection in software-defined networking
Authors: Kareem Mohammed Ibrahim , Jasim Mahdi Nsaif
Published: August 2022

Software defined networking (SDN) is a new network architecture that allows for centralized network control. The separation of the data plane from the control plane, which establishes a programmable network environment, is the key breakthrough underpinning SDN. The controller facilitates the deployment of services that specify control policies and delivers these rules to the data plane using a common protocol such as OpenFlow at the control plane. Despite the many advantages of this design, SDN security remains a worry because the aforementioned chapter expands the network's attack surface. In fact, denial of service (DoS) assaults pose a significant threat to SDN settings in a variety of ways, owing to flaws in the data and control layers. This work shows how distributed denial of service (DDoS) attack detection is based on the entropy variation of the destination IP address. The study takes advantage of the OpenFlow protocol's (OFP) flexibility and an OpenFlow controller (POX) to apply the proposed method. An entropy computation to determine the distributed features of DDoS traffic is developed and it is capable of detecting a user datagram protocol (UDP) flood attack after 0.445 seconds this type of attack occurred.
Machine learning classification of infectious disease distribution status
Authors: Arief Wisky Irzal , Yanto Musli , Wiyandra Yogi , Syahputra Hadi , Hadi Febri
Published: August 2022

Infectious diseases are common diseases and are caused by microorganisms such as viruses, bacteria, and parasites. Indicators of the spread of this disease can be seen based on the population level and the number of confirmed cases. This study aims to develop a machine learning (ML) analysis model using the K-means cluster, artificial neural network (ANN), and decision tree (DT) methods. The dataset used in this study was obtained based on the number of confirmed patients and the distribution of the population. The analysis process is divided into two stages, namely preprocessing and the classification process. The pre-processing stage aims to produce a classification pattern that can describe the level of distribution status. The classification pattern will be continued at the classification analysis stage using ANN and DT. Classification analysis gave significant results with an accuracy rate of 99.77%. The results of the classification analysis can also describe the level of knowledge distribution based on the decision tree. Overall, the contribution of this research is to develop a classification analysis model that presents the latest information and knowledge. The results of the research presented also have an impact on the control process in environmental management and public health.
Towards an approach based on particle swarm optimization for Arabic named entity recognition on social media
Authors: Ben Ali Brahim Ait , Mihi Soukaina , Bazi Ismail El , Laachfoubi Nabil
Published: August 2022

Named entity recognition is an essential task for various applications related to natural language processing (NLP). It aims to retrieve a variety of named entities (NEs) from text and categorize them according to predetermined target categories. In many cases, using the entire feature set can be time-consuming and negatively impact the performance. Moreover, it is challenging to find the relevant subsets of features for a particular task due to the high number. The feature selection technique is an unsupervised process for selecting informative features by creating a new subset of informative features. This technique is used to enhance the underlying algorithm's performance. This article implements an effective feature selection algorithm using particle swarm optimization (PSO) to identify and classify the Arabic NEs in the text from social media. PSO is a search algorithm that utilizes a population of particles in a multidimensional space. The proposed method is evaluated using two publicly available Arabic Dialect social media datasets. It is demonstrated through comparisons with both baselines and previous models that the new approach achieves significant accuracy with considerably reduced feature sets in all parameters.
Development of a mobile expert system for the diagnosis on motorcycle damage using forward chaining algorithm
Authors: Fitri Naryanto Rizqi , Delimayanti Mera Kartika , Kriswanto Kriswanto , Musyono Ari Dwi Nur Indriawan , Sukoco Imam , Aditya Mohamad Naufal
Published: August 2022

Indonesia is an ASEAN country with the most motorcycle users, where one-third of its population own motorcycles. The automatic motorcycle is the most widely used type due to its agility and fuel-efficient abilities. Sudden motorcycle damage could hamper the users' activities. However, most of these users do not know the reason for the damage. This paper presents the development of expert system for diagnosing the damage of motorcycle using forward chaining method. This system was implemented in mobile application. Through a mobile application, a solution for these users can be obtained. This application immediately discovers the damaged location and repair process. Furthermore, it acts as the first solution before motorcycle repair is carried out in a shop. In this study, the forward chaining method was implemented. It is based on a pattern-matching algorithm whose primary objective is to match facts (input data) with appropriate rules from the rule base. Various test results showed that the diagnostic application used for automatic motorcycle damages 100% worked.
Cloud computing security for e-learning during COVID-19 pandemic
Authors: Najm Yassen AbdelKhaleq , Alsamaraee Suray , Jalal Ahmed Adeeb
Published: August 2022

The demand for e-learning services increased during the developments of the COVID-19 virus and its rapid spread, and the recommendations of the World Health Organization (WHO) that social distancing should be required. The rapid transition to the e-learning environment quickly led to the neglect of some security aspects, which led to an increase in cyber attacks targeting computer accounts, which is one of the most important pillars of e-learning. In these papers, the attacks that target the cloud computer used in the most important e-learning have been studied and classified according to the victim using an inductive methodology based on global statistics related to cyber attacks and recent research. And suggest appropriate solutions to avoid its occurrence in the near future and raise the level of protection for those computer clouds.
DIA-English-Arabic neural machine translation domain: sulfur industry
Authors: Hameed Diadeen Ali , Faisal Tahseen Ameen , Abbas Alaa Khudhair , Abdullah Ali Harith , Hasan Ghanim Thiab
Published: August 2022

The aim of this paper is the design and development a new English-Arabic neural machine translation (NMT) called DIA translation system. The main purpose of the designing system is to study translator limited sulfur industry domain as a stand-alone tool in order to improve the translation quality. Machine translation (MT) are very sensitive to the domains they were trained on and can be integrated with general (English-Arabic) MT systems. The proposed system has mainly four directions: supports chemical symbols, terms, phrase, and text and it is evaluated by using (1,200) various English declarative sentences which written by English Language experts. The obtained results indicate that this system is high effective and has an accuracy of 79.33% in comparison with Google translator which has 38.67% for the same test samples.
Internet of things based real-time electric vehicle and charging stations monitoring system
Authors: A. Mohammed Emad , Qahtan Mahmood Hameed , J. Ali Ahmed
Published: August 2022

Due to a shortage of fuel sources and the increment in environmental pollution, efficient techniques should be introduced. The best solution is to move to the use of electric vehicles. The article aims to develop a solution for electric vehicle (EV) charging station locations that utilize the internet of things (IoT) technology. The IoT is a paradigm that uses sensors and transmitting networks to provide current facilities with a real-time global communication perspective of the physical world. This paper proposes a real-time system to provide a real-time update to EV location and charging stations (CSs) location to reduce time lost by users searching CSs, and provides real-time charging station (CS) recommendations for EV users by displaying the nearest CS, provide estimation arrival time to the nearest CS, display distance between nearest CS and EV real-time updated. The work of the proposed system was tested, and the most significant error rate (17 meters) is represented by the difference in the distance obtained from the system and the distance obtained from Google Map. The total accuracy of the design for the tested case is (98.014%).
Puzzle optimization algorithm with capsule networks based Telugu character recognition model
Authors: Siva Phaniram Josyula , Babu Reddy Mukkamalla
Published: August 2022

Recently, Telugu character recognition (TCR) becomes a hot research topic because of drastic increase in technological advancements such as multimedia, and smartphones. Though numerous works have been concentrated on offline TCR models, it is still needed to develop automated and intelligent online TCR models. This paper presents a novel puzzle optimization algorithm with capsule networks-based Telugu character recognition (POACN-TCR) model. The presented POACN-TCR model intends to effectively identify and recognize distinct Telugu characters online. To accomplish this, the POACN-TCR model primarily undergoes pre-processing in different ways such as normalization, smoothing, and interpolation. In addition, the POACN-TCR model designs an effective capsule network (CapsNet) model to generate feature vectors and hyperparameter optimization takes place using puzzle optimization algorithm (POA). Finally, the C4.5 decision tree classifier is utilized for the effectual recognition of Telugu characters. The utilization of POA for hyperparameter optimization of the CapsNet model helps in achieving improved recognition performance. For ensuring the enhanced outcomes of the POACN-TCR model, a wide-ranging experimental analysis is performed and the outcomes pointed out the betterment of the POACN-TCR model on the recent approaches.