bluuebunny/crossref_metadata_2025 huggingface dataset:
Quality Analysis and Key Factor Research in Japan’s Economic Growth Based on Factor Analysis
Authors: Zhao Qiang
Published: August 2022

Factor analysis is suitable for the conditions of complex correlation, large sample size, many influencing factors, and many selected indicators; able to conduct research on a variety of subjects; and can better apply multivariate statistical methods to the evaluation of financial performance. Among other common methods of evaluating financial performance, factor analysis methods can reduce dimensionality and simplify data basically design weights. Factor analysis can reduce the dimensionality of data even with large sample sizes. It avoids a lot of complicated calculations, reduces the difficulty of calculation, and solves the problem of overlapping factor information, reflecting the advantages of multivariate statistics. Based on the factor analysis method, this study analyzes the quality analysis and key factors in Japan’s economic growth: (1) integrity principle residents’ financial risk is composed of multiple factors, not only unilateral factors but also the following factors: determine the influencing factors, select indicators, and identify risks and potential hazards. Financial risk itself is comprehensive, and the assessment of risk arising from a single factor is less important. (2) The requirements for the selected financial indicators are that the unit and order of magnitude should not only be accurate but also consistent, the financial information reflected by the selected financial indicators should be direct and clear, and financial data should be obtained in multiple ways, through annual reports and the Internet, to collect financial data. The analysis of financial performance based on scientific principles can show the current operating conditions, so the selection of financial indicators must be true, effective, and objective, so as to correctly reflect the real situation, and it is beneficial to combine the analysis results and carry out the following steps. (3) Financial risks may arise in the process of financing or in the process of investment. Financial risk in a broad sense is more in line with the characteristics of risk, and it arises in every link related to financial activities. The analysis is carried out in terms of financial risk in a broad sense. It can be seen that the economic quality scores were higher in 2011 and 2017. (4) Use several representative factors to replace the original variables for analysis, and explain the problems existing in the Japanese economy according to the results. The results show that the key factors of economic growth include gross national product, inflation, employment rate, and the balance of payments.
Software Simulation in English Translation Platform Based on Gaussian Hybrid Model
Authors: Peng Nan , Wei Yingying , Liu Lu , Zou Junzhong
Published: August 2022

In this article, we will first try to create a general development platform for embedded systems. The goal of this step is to establish an experimental platform that can support various peripheral modules and can be reused. The connection between the modules can be reconfigured to meet the different needs of embedded research and learning. On this basis, the system uses the audio frequency spectrum program as an input function to represent the dispersion pattern of signal energy, which can be tested with characteristic nodes simulated by convolutional neural network software. In addition, the auxiliary neural network software simulation core can continuously learn the detailed characteristics of the audio frequency spectrum, making it easy to recognize environmental sounds. In addition, the sound signal and the neural cycle are related in time. The neural network can study the relationship between different frames in the time domain to compensate for the defects caused by the complex neural network in modeling time series. Finally, this article focuses on the process of building an English translation platform based on the mobile cloud data model. The client is targeted at the Android platform, while the server is based on the laaS system. According to the model of mobile cloud data processing, the calculation of mobile phones in computer-intensive programs is studied. Through the hardware design and distribution of the system, we are able to use mobile cloud technology as a desktop-intensive program to solve the problem of effectiveness in the solution. The article promotes the development of an English translation platform by applying the research results of environmental sound recognition based on embedded system software simulation to the design of the English translation platform.
Organisierte sexualisierte Gewalt – Herausforderungen und Chancen in der Diagnostik und Psychotherapie für Betroffene
Authors: Nick Susanne , Grundmann-Tuac Johanna , Schäfer Ingo , Gysi Jan
Published: August 2022

Hintergrund: Schwere sexualisierte Gewalt erfolgt meist in Verbindung mit körperlicher und psychischer Gewalt an Kindern, Jugendlichen und Erwachsenen. In den letzten Jahren wurde deutlich, dass einige Formen von sexualisierter Gewalt systematisch und durch untereinander bekannte Täter:innen oder Netzwerke organisiert ausgeübt werden und mehrere Opfer betreffen. Betroffene leiden meist unter komplexen Traumafolgen und gelten als schwer erkennbar. Die mit der ICD-11 verbesserten Möglichkeiten in der Dia­gnostik von schweren Traumafolgen bergen auch für diese Zielgruppe Chancen auf eine frühere Einleitung störungs­spezifischer Behandlung und mehr fachliche Anerkennung. Methodik: In diesem Fachbeitrag werden unterschiedliche Kontexte von organisierter sexualisierter Gewalt und mögliche psychische Folgen im Überblick dargestellt. Zudem werden damit verbundene Implikationen für Diagnostik, psychosoziale Versorgung und Psychotherapie der Betroffenen erläutert. Dabei wird das Ziel verfolgt, bisherige Erkenntnisse aus Fachliteratur und klinischer Praxis in Bezug zu setzen und in psychotraumatologische Diskurse zu integrieren. Ergebnisse: Betroffene mit Erfahrungen von organisierter sexuali­sierter Gewalt haben einen vielseitigen Hilfebedarf und stellen Gesundheitssystem, Opferschutz und Ermittlungsbehörden gleichermaßen vor komplexe Herausforderungen. Fachliche Weiterentwicklungen und Kooperationen der unterschiedlichen Hilfesysteme sind erforderlich. Nur so kann der bestehende Mangel an systematisch erfassten Erkenntnissen und Studien sowie an Behandlungs- und Versorgungsstrukturen für diese Zielgruppe behoben werden.
Practice Dilemma: Expanding Melanonychia in the Paediatric Setting
Authors: Huang Cheng , Bullpitt Peter , Nabarrro Mark , Murrell Dedee Frances
Published: August 2022

Introduction: Differentiating between benign and malignant pathology in melanonychia can be challenging, particularly in paediatric patients as nail biopsies often require general anaesthesia. Case Presentation: An 11-year-old healthy Vietnamese female presented with a pigmented right third fingernail. It was first noticed at age 1 and had gradually involved the whole nail plate by age 4. On examination, Hutchinson’s sign was thought to be positive. Dermatoscopy revealed a variation of colours and spacing of the pigmentation. Due to the concerning clinical findings, nail removal was performed. Histology of the nail matrix squamous epithelium showed prominent melanin pigmentation. Both SOX10 and Melan A stain showed an increase in the melanocytes within the nail bed epithelium. There was no confluence of melanocytes or melanocytic nests within the nail matrix epithelium. Overall, a benign process (lentigo with melanocyte hyperplasia) was favoured given the young age of the patient, lack of cell atypia, lack of confluence or expansile growth, and a lack of significant pagetoid spread of the melanocytes. Conclusion: Ascertaining the cause of melanoychia can be challenging, and histology may not clearly differentiate between benign and malignant causes. Careful clinical evaluation and detailed discussion with the patient and family should be thoroughly undertaken in those cases.
Safety of Endoscopy Units during the COVID-19 Pandemic
Authors: Gonçalves Margarida , Guimarães Andreia , Carvalho Tânia , Antunes Pedro , Mendes Sofia , Soares João , Gonçalves Raquel , Arroja Bruno , Rebelo Ana
Published: August 2022

Introduction: The COVID-19 pandemic drastically changed the daily routine of all healthcare systems worldwide, and endoscopy units were no exception. Endoscopic exams were considered to have a high risk of transmission, and therefore, the safety of endoscopy units and the consequent need for pre-endoscopy SARS-CoV-2 screening were questioned early on. The aim of our study was to assess the safety of endoscopy units during the COVID-19 pandemic, as well as the effectiveness/necessity for SARS-CoV-2 screening prior to endoscopies. Material and Methods: This is a retrospective and single-center study carried out in a Portuguese tertiary hospital. All patients who underwent endoscopic procedures between September 1, 2020 and February 28, 2021 were included. The pre-endoscopy screening consisted of a specific questionnaire or a RT-PCR test for SARS-CoV-2 (nasal and oropharyngeal swab). Data were obtained through patient’s clinical records and the Trace COVID platform. Results: A total of 2,166 patients were included. Patients had a mean age of 61.8 years and were predominantly male (56.2%, n = 1,218). Eighty-one (3.7%) patients had previous SARS-CoV-2 infection, with a median difference of 74 days (IQ 40.5:160.5) between infection and endoscopy. Most patients (70.2%, n = 1,521) underwent PCR screening for SARS-CoV-2 up to 72 h before the procedure, with the remaining patients (29.8%, n = 645) answering a questionnaire of symptoms and risk contacts up to 3 days before endoscopy. Of the patients who underwent RT-PCR screening for SARS-CoV-2, 21 (1.4%) tested positive, and all were asymptomatic at the time of the screening. The evaluation for SARS-CoV-2 infection up to 14 days after the endoscopic exams identified 9 positive patients (0.42%) for SARS-CoV-2. The median difference in days between endoscopy and the diagnosis of infection was 10 days. Discussion/Conclusion: Pre-endoscopy screening with RT-PCR test for SARS-CoV-2 identified a very small number of patients with COVID-19 infection as well as patients with COVID-19 infection in the following 14 days. Therefore, the risk of infection in endoscopy units is negligible if screening of symptoms and risk contacts is applied and individual protective equipment is used.
Neurosarcoidosis Presenting with Prominent Periventricular White-Matter Lesions during Steroid Treatment for Autoimmune Hepatitis
Authors: Shibahara Tomoya , Yoshino Fumitaka , Matsuoka Mikiaki , Tachibana Masaki , Nakamura Kuniyuki , Ago Tetsuro , Kuroda Junya , Nakane Hiroshi
Published: August 2022

A 63-year-old woman under treatment of autoimmune hepatitis presented with headache, memory loss, and somnolence. Three months before admission, the patient experienced liver inflammation relapse after prednisolone (PSL) cessation. Consequently, PSL was resumed and then tapered. Cerebrospinal fluid (CSF) examination showed lymphocytic pleocytosis with remarkably reduced glucose and elevated angiotensin-converting enzyme and soluble interleukin-2 receptor levels. Magnetic resonance imaging (MRI) revealed prominent bilateral periventricular white-matter lesions, hydrocephalus, ischemic stroke with gadolinium enhancement of frontoparietal and basilar meninges on contrast-enhanced fluid-attenuated inversion recovery. Magnetic resonance angiography (MRA) showed narrowing of the bilateral middle cerebral arteries. Based on these findings, we diagnosed the patient with neurosarcoidosis. Re-increment of PSL improved the neurological symptoms, CSF findings, and abnormalities found on MRI and MRA. This case suggests that neurosarcoidosis may occur as a complication of some autoimmune diseases during immunotherapy administration.
Multimodale Schmerzbehandlung nach Thorakotomie oder VATS: Eine mögliche Option für die Fast-Track-Chirurgie
Authors: Hekmat Khosro
Published: August 2022

Various regional anesthesia (RA) techniques were shown to reduce pain after lung surgery, but controversies remain regarding the best technique to use to improve recovery. In this observational prospective study, the aim was to assess the efficacy of an RA strategy depending on the surgical approach. Patients who underwent lung surgery were included if an RA was planned following our unit procedure (erector spinae plane block (ESP) for video-assisted thoracic surgery (VATS) and thoracic epidural analgesia (TEA) or intrathecal analgesia (IA) for thoracotomy). Patients were compared according to the RA used. In total, 116 patients were included, 70 (60%), 32 (28%), 14 (12%) in the ESP, TEA and IA groups, respectively. Between Day 1 and Day 3, median NRS values were ≤4 at rest, and <50% patients experienced moderate-to-severe pain in each group. There were no significant differences in opioid consumption and in pain at rest or during chest physiotherapy on Days 1 and 2 between groups. However, patients who received an IA had lower NRS than other groups on Day 0 and 3 and a shorter length of hospital stay in comparison with those who received a TEA. Thus, in our institution, a strategy combining ESP for VATS and TEA, or IA for thoracotomy, allowed for effective analgesia after a lung resection. Interestingly, IA appeared to be more effective than TEA in reducing the length of hospital stay and pain on Day 0 and 3.
Idiopathic Multifocal Choroiditis and Punctate Inner Choroidopathy – Evaluation of Risk Factors for Increased Relapse Rate: A 2-Year Prospective Observational Cohort Study
Authors: de Groot Evianne L. , de Boer Joke H. , Ossewaarde-van Norel Jeannette
Published: August 2022

Introduction: The aim of this study was to describe the course of disease in patients with idiopathic multifocal choroiditis (MFC) and punctate inner choroidopathy (PIC) and to identify risk factors associated with an increased relapse rate of disease activity. Methods: In this prospective observational cohort study, demographical and clinical data were collected concerning the relapses rate of disease activity, the conclusions of the multimodal imaging results, treatment, complications, and self-reported quality of life. Disease activity was defined as new inflammatory lesions or active inflammation in preexisting chorioretinal lesions either with or without active choroidal neovascularization (CNV). Linear regression analysis was performed to identify risk factors associated with an increased relapse rate. Results: In total, 122 eyes of 82 patients (93% females) were included with a median age (IQR) of 45 (37–54) years. A history of secondary CNV was present in 66% of the eyes. During follow-up, the best-corrected visual acuity remained stable despite a median relapse rate (IQR) of 1.0 (0.25–3). Cycles of oral corticosteroids were given in 59% of the patients, 72% were treated at baseline or started treatment during follow-up with a disease-modifying antirheumatic drug (DMARD), and 35% with a biological agent in addition to the DMARD. Both a history of secondary CNV (B = 1.2, 95% CI: 0.7–1.7, p = 3.6 × 10−5) and high myopia (<−6 diopters) (B = 0.6, 95% CI: 0.1–1.1, p = 0.02) independently increased the relapse rate of disease activity. Discussion/Conclusion: A history of secondary CNV and high myopia were associated with an increased relapse rate of disease activity. Moreover, the results of this study emphasize the challenging character of treating patients with MFC/PIC.
State and output feedback control for Lipschitz nonlinear systems in reciprocal state space: synthesis and real-time validation
Authors: Thabet Assem , Haj Frej Ghazi Bel , Gasmi Noussaiba , Mansouri Karim , Chauveau Eric
Published: August 2022

In industrials process and many studies cases, state and output derivative variables can be easily modeled in reciprocal state space (RSS) form than the standard one. Formulation of stabilization problem with a guaranteed cost control using feedback principle for Lipschitz nonlinear systems (LNS) in RSS is presented in this brief. The asymptotic stability, using the proper Lyapunov functions of the closed-loop system, is guaranteed. The control design problem is guaranteed through a resolution of linear matrix inequalities (LMI) technique under certain lemmas and minimization of non-standard cost control. Experimental validation shows the good performances of the proposed method using real-time implementation (RTI) with a digital signal processing (DSP) device (Arduino MEGA 2560).
A generic and smart automation system for home using internet of things
Authors: Iyappan Perumal , Loganathan Jayakumar , Kumar Verma Manoj , Dumka Ankur , Singh Rajesh , Gehlot Anita , Vaseem Akram Shaik , Kaur Sukhdeep , Joshi Kapil
Published: August 2022

Home automation systems are expanding increasingly popular because they can conveniently be employed to manage devices and appliances via voice or focused on physical activity utilizing sensor. From the various research, it shows that affording cost in bringing smartness to small organizations as well as normal users is challenging and there is a requirement for a better obvious and convenient method of connecting and managing equipment with mobile applications. The proposed system is created and built with the aim of enhancing control system performance and reliability. This technology may operate on any system and manage devices by connecting with home appliances and connected devices via a Wi-Fi device. The system involves a central processing module to manage devices via a home Wi-Fi connection that is linked to the internet for internet of things operations. It is recommended that an application be developed to connect, and configure new and current home appliances for control, which will lead to the connection and handling of other third-party devices via their software development kits. The suggested system enables additional features via a mobile application that allows the user to install new features created by the user to execute any activity with the system.
In Malang, Indonesia, a techno-economic analysis of hybrid energy systems in public buildings
Authors: Junus Mochammad , Marjono Marjono , Aulanni’am Aulanni’am , Wahyudi Slamet
Published: August 2022

Because of the fickle nature of the renewable sources of energy production, professionals in this sector have developed hybrid renewable energy systems (HRES) that offer a constant and stable load supply. This research intends to build off-grid hybrid energy systems (HES) in Malang, Indonesia, that uses a solar generator, wind turbine, and biogas to power public buildings. The HOMER program was used to construct this model. Following the computations, multiple hybrid renewable energy system models are used to analyze each component’s capital cost and also cost of energy (COE). Furthermore, energy output, gas emissions, and a thermoeconomic assessment of several HRES models have been explored. Two ideal HRES models were evaluated: one with a biogas generator and one without. According to the research, employing a generator of biogas would reduce fuel consumption and emissions by 68.3%. This HRES model is impressive in light of Malang’s severe air pollution. Switching from diesel to biogas generator decreases NPC by 6.84%, according to the data.
Vehicular impact analysis of driving for accidents using on board diagnostic II
Authors: Kumar Singh Siddhanta , Kumar Singh Ajay
Published: August 2022

A large number of people meet with an accident everyday around the world. One of the leading causes of death is traffic accidents. The reasons behind India's rising number of road accidents contribute to bad driving behavior, poor road design and infrastructure, lack of enforcement of traffic laws. The post accidental investigation report is very important to know the actual reason of collision for the concerned parties and the insurance company and the police. The proposed work effectively extracts interpretable features describing complex driving patterns. It will provide analytical report of the accidents to various parties involved in process. This work analyzes the type and cause of accident. The experiment has been simulated using on board diagnostic II (OBD II) and smart phone accelerometer for post accidental analysis of collision. As the electronic control unit (ECU) does not provide accelerometer sensor, so the smart phone accelerometer has been utilized in conjunction with another parameter of OBD II device. The gravitational force (G-force) values observed from accelerometer sensor along the different axes and speed, acceleration, fuel consumption rate, and are retrieved from OBD II device. The result shows that the parameters recorded are very helpful in finding the actual accidental status of the vehicle.
Chaotic-DNA system for efficient image encryption
Authors: Rashid Shakir Huda , Aziz Mehdi Sadiq Abdul , Abbas Hattab Anwar
Published: August 2022

In order to prevent unwanted access to sensitive data by unauthorized individuals, color images are encoded. Because chaotic-deoxyribonucleic acid (chaotic-DNA) encoding can make information highly secure, it is often employed in image encryption. In this study, a new image encryption technique has been proposed based on a new 4D-chaotic system and DNA computing. The algorithm consists of two phases: in the first phase, the pixel positions are permuted by chaotic sequences. In the second phase, according to the concept of DNA cryptography, a set of operations (like DNA addition, DNA XOR, DNA subtraction, shift right, and shift left) are performed on the DNA encoding sequence. The performance of the suggested algorithm is evaluated through analyses like correlation coefficient, entropy, histogram, and key space. The results show that the encryption method that was exhibited has good encryption performance and high security. For encrypted images, the histogram is fairly uniform, the correlation values between adjacent pixels are very small and close to zero, and the entropy is near to the ideal value of eight. In addition, the proposed system has a very large key space that is equal to 2627 keys, which makes it resistant to brute-force, differential, and statistical attacks.
Comparison between boost and positive output super lift Luo converters to improve the performance of photovoltaic system
Authors: Mohammed Jassim Ream , H. Hassan Kadhim , Ahmed Abed Issa
Published: August 2022

Employment DC-DC switching power converters in many different areas become is very important. In this paper, three different models of the photovoltaic solar module were proposed in order to designing, implementation, and simulated them in MATLAB/Simulink with the boost converter circuit first and then with the positive output super lift Luo (POSLL) converter circuit again. A comparison was made between the two circuits, as well as a theoretical and simulation values were made and compared between them (in the same standard conditions) for each of these selected models. So as to improving solar system performance and clarify the functions played by POSLL in power electronic circuits.
A predictive analysis framework of heart disease using machine learning approaches
Authors: Molla Shourav , Mehedi Shamrat F. M. Javed , Islam Rafi Raisul , Umaima Umme , Islam Arif Md. Ariful , Hossain Shahed , Mahmud Imran
Published: August 2022

Heart diseaseis among the leading causes for death globally. Thus, early identification and treatment are indispensable to prevent the disease. In this work, we propose a framework based on machine learning algorithms to tackle such problems through the identification of risk variables associated to this disease. To ensure the success of our proposed model, influential data pre-processing and data transformation strategies are used to generate accurate data for the training model that utilizes the five most popular datasets (Hungarian, Stat log, Switzerland, Long Beach VA, and Cleveland) from UCI. The univariate feature selection technique is applied to identify essential features and during the training phase, classifiers, namely extreme gradient boosting (XGBoost), support vector machine (SVM), random forest (RF), gradient boosting (GB), and decision tree (DT), are deployed. Subsequently, various performance evaluations are measured to demonstrate accurate predictions using the introduced algorithms. The inclusion of Univariate results indicated that the DT classifier achieves a comparatively higher accuracy of around 97.75% than others. Thus, a machine learning approach is recognize, that can predict heart disease with high accuracy. Furthermore, the 10 attributes chosen are used to analyze the model's outcomes explainability, indicating which attributes are more significant in the model's outcome.
MPPT implementation and simulation using developed P&O algorithm for photovoltaic system concerning efficiency
Authors: A. AlZubaidi Asaad , Abdul Khaliq Laith , Salman Hamad Hassan , Khalid Al-Azzawi Waleed , Sameer Jabbar Mohanad , Abdulwahhab Shihab Thaer
Published: August 2022

The great development witnessed by investments in renewable energy has made it the focus of researchers’ attention in order to increase its efficiency. This is due to the increase in demand for electrical energy due to rapid technological growth, increase in population numbers, and high fuel prices that are used in the production of traditional electrical energy, but it suffers from a problem that is greatly affected by two factors, namely, the change in the intensity of solar irradiation and temperature, which makes its electrical characteristics non-linear, which causes a decrease in its efficiency. To address the efficiency problem, the researchers developed several techniques for tracking the MPP point and extracting the maximum energy from the solar panels under various measurement conditions. Maximum power point tracking technology (MPPT) technology is the most widely used technology in solar energy systems. In this article, MPPT technology is simulated using MATLAB/Simulink for the purposes of extracting maximum power and managing the duty cycle of a DC-DC buck converter. The performance of the photovoltaic system under various irradiance fluctuations and settings of constant temperature could well be determined using simulation results. Under standard and varied test settings, allowing the inverter to convert over 99% of the electricity provided by the solar panels.
Effect of peak sun hour on energy productivity of solar photovoltaic power system
Authors: Megantoro Prisma , Syahbani Muhammad Akbar , Sukmawan Irfan Helmi , Perkasa Sigit Dani , Vigneshwaran Pandi
Published: August 2022

A solar cell is a type of renewable energy engineering technology that can convert photons coming from the sun to be converted into electrical energy. The amount of energy that can be converted by a solar cell is determined by the effective insolation time. Peak sun hours (PSH) are the focus of this research. This PSH analysis aims to determine the potential for solar energy obtained in geographical locations throughout the year. Geographical location and the position of the astronomical coordinates of a certain area affect PSH. Therefore, the orientation of solar panel installation, including the height, slope, and latitude of the solar panel surface needs to be considered in order to get maximum solar energy. The results of this study can be used by technicians in determining the orientation of solar panel development in an area.
A methodology for transforming BPMN to IFML into MDA
Authors: Sajji Abir , Rhazali Yassine , Hadi Youssef
Published: August 2022

Responding to rising information system complexity and the high expense of technological migration, model driven architecture (MDA) was created. As a result, the OMG advocates raising the abstraction level to overcome technological limitations. MDA seeks to describe the functional and performance requirements of an application on a platform independently. Using the MDA approach, the business process model and notation (BPMN), and interaction flow modeling language (IFML) standards, we represent a methodology that allows transforming semi-automatically from the computation independent model (CIM) level to the platform independent model (PIM) level; to achieve this a collection of unique rules for transforming in a semi-automatic manner from CIM to PIM were developed. At the CIM level, we create models of business process using the notation standard BPMN, and IFML is used to adapt PIM models with web-oriented graphical user interfaces (GUI). To properly demonstrate the transformation procedure from CIM to PIM models a case study of the order management process was presented.
Nutrition information estimation from food photos using machine learning based on multiple datasets
Authors: Al-Saffar Mustafa , R. Baiee Wadhah
Published: August 2022

Bodyweight, blood pressure, and cholesterol are all risk variables that can aid people in making educated decisions regarding their health promotion activities. Food choices are among the most effective methods for preventing chronic illnesses, including heart disease, diabetes, stroke, and some malignancies. Because various meals give varying amounts of energy and minerals, good eating necessitates keeping track of the nutrients we ingest. Furthermore, there is a paucity of information on whether understanding food constituents might aid in more accurate nutrition calculations. Therefore, this research suggests processing food images on social media to anticipate the contents of each food and extracting nutrition information for each food image to serve as healthy implicit feedback to take advantage of the rapid accumulation of rich photos on social media. The proposed methodology is a framework based on a machine-learning model for predicting food ingredients. We also compute critical health metrics for each ingredient and combine them to obtain nutrition data for the food. The result revealed a promising way of extracting food components and nutrition information. Compared with other researchs, our proposed prediction and attribute extraction strategy achieves a remarkable accuracy of 85%.
The qualities of dyed YAG:Ce3+@SiO2 for WLEDs via energy conversion
Authors: Ton That Phung , Le Phan Xuan
Published: August 2022

Y3Al5O12:Ce3+ (YAG:Ce3+), the most common yellow phosphor for WLEDs, has a red insufficiency in its light spectrum. The Ce3+ spectral profile is modified in this research using surface-located ATTO-Rho101 dye molecules, which have powerful, wide impregnation in the greenish-yellow spectroscopic zone of Ce3+ radiation and vivid red-emitting radiation. To create a spherical shell and evenly dispersed micro and nanometer YAG:Ce3+, a modified solvothermal technique is applied. Surface SiO2 covering and synchronized dye embedding are accomplished using solvothermally generated YAG:Ce3+, temperature-stimulated micro-YAG:Ce3+, plus commercialized phosphorus. Upon blue light excitation, the accumulated YAG:Ce3+@SiO2+dye powder exhibits efficient radiative conversion/reintake from Ce3+ within the internal structure of YAG to the pigment particles from the SiO2 external shell, despite the phosphors' diameter; which likely boosts its red radiation. Fluorescence microscopy would be a suitable way to determine the reabsorption of powdered substances.
DDoS attack detection in software defined networking controller using machine learning techniques
Authors: Jasem Altamemi Abbas , Abdulhassan Aladdin , Turki Obeis Nawfal
Published: August 2022

The term software defined networking (SDN) is a network model that contributes to redefining the network characteristics by making the components of this network programmable, monitoring the network faster and larger, operating with the networks from a central location, as well as the possibility of detecting fraudulent traffic and detecting special malfunctions in a simple and effective way. In addition, it is the land of many security threats that lead to the complete suspension of this network. To mitigate this attack this paper based on the use of machine learning techniques contribute to the rapid detection of these attacks and methods were evaluated detecting DDoS attacks and choosing the optimum accuracy for classifying these types within the SDN, the results showed that the proposed system provides the better results of accuracy to detect the DDos attack in SDN network as 99.90% accuracy of Decision Tree (DT) algorithm.
Estimation of concrete compression using regression models
Authors: Admassu Assegie Tsehay , Olalekan Salau Ayodeji , Uthman Badrudeen Tayo
Published: August 2022

The objective of this study is to evaluate the effectiveness of different regression models in concrete compressive strength estimation. A concrete compressive strength dataset is employed for the estimation of the regressor models. Regression models such as linear regressor, ridge regressor, k-neighbors regressor, decision tree regressor, random forest regressor, gradient boosting regressor, AdaBoost regressor, and support vector regressor are used for developing the model that predicts the concrete strength. Cross-validation techniques and grid search are used to tune the parameters for better model performance. Python 3.8 programming language is used to conduct the experiment. The Performance evaluation result reveals that the gradient boosting regressor has better performance as compared to other models using root mean square error (RMSE).
Integration of ontology with machine learning to predict the presence of covid-19 based on symptoms
Authors: El Massari Hakim , Gherabi Noreddine , Mhammedi Sajida , Ghandi Hamza , Qanouni Fatima , Bahaj Mohamed
Published: August 2022

Coronavirus (covid 19) is one of the most dangerous viruses that have spread all over the world. With the increasing number of cases infected with the coronavirus, it has become necessary to address this epidemic by all available means. Detection of the covid-19 is currently one of the world's most difficult challenges. Data science and machine learning (ML), for example, can aid in the battle against this pandemic. Furthermore, various research published in this direction proves that ML techniques can identify illness and viral infections more precisely, allowing patients' diseases to be detected at an earlier stage. In this paper, we will present how ontologies can aid in predicting the presence of covid-19 based on symptoms. The integration of ontology and ML is achieved by implementing rules of the decision tree algorithm into ontology reasoner. In addition, we compared the outcomes with various ML classifications used to make predictions. The findings are assessed using performance measures generated from the confusion matrix, such as F-measure, accuracy, precision, and recall. The ontology surpassed all ML algorithms with high accuracy value of 97.4%, according to the results.
Improved Benders decomposition approach to complete robust optimization in box-interval
Authors: Cipta Hendra , Suwilo Saib , Sutarman Sutarman , Mawengkang Herman
Published: August 2022

Robust optimization is based on the assumption that uncertain data has a convex set as well as a finite set termed uncertainty. The discussion starts with determining the robust counterpart, which is accomplished by assuming the indeterminate data set is in the form of boxes, intervals, box-intervals, ellipses, or polyhedra. In this study, the robust counterpart is characterized by a box-interval uncertainty set. Robust counterpart formulation is also associated with master and subproblems. Robust Benders decomposition is applied to address problems with convex goals and quasiconvex constraints in robust optimization. For all data parameters, this method is used to determine the best resilient solution in the feasible region. A manual example of this problem's calculation is provided, and the process is continued using production and operations management–quantitative methods (POM-QM) software.
Simulated computer adaptive testing method choices for ability estimation with empirical evidence
Authors: Oladele Jumoke I. , Ndlovu Mdutshekelwa , Spangenberg Erica D.
Published: August 2022

Computer adaptive testing (CAT) is a technological advancement for educational assessments that requires thorough feasibility studies through computer simulations to ensure strong testing foundations. This advancement is especially germane in Africa being adopters of technology, and this should not be done blindly without empirical evidence. A quasi-experimental design was adopted for this study to establish methodological choices for CAT ability estimation. Five thousand candidates were simulated with 100 items simulate through the three-parameter logistic model. The simulation design stipulated a fixed-length test of 30 items, while examinee characteristics were drawn from a normal distribution with a mean of 0 and a standard deviation of 1. Also, controls for the simulation were set not to control item exposure or to use the progressive restricted method. Data gathered were analyzed using descriptive statistics (mean and standard deviation) and inferential statistics (Two-way multivariate analysis of variance: MANOVA) for testing the generated hypotheses. This study provided empirical evidence for choosing ability estimation methods for CAT as part of the efforts geared towards designing accurate testing programs for use in higher education.
Relationship between emotional motivation and academic performance in second language learning
Authors: Abad Mancheño Alfonso , León Mejía Ana Cristina , Sánchez Cabrero Roberto
Published: August 2022

This article presents the results of a research study on the role that affective motivation plays in learning a second language (L2). There were 171 American university students of Spain, German, Italy, and Japan as a second language participated in the study. This was an ex post facto, cross-sectional, and correlational quantitative study that informs us of which is the type of motivation most beneficial for learners and considers variables such as age, gender, academic performance, and the intention to continue studying a second language. An online questionnaire based on the Dörnyei motivational model was administered. The results show that the variables ideal self and “projection of intended effort” of the learners are positively and significantly related to the academic performance of the students and to the intention of enrollment in future foreign language classes. At the opposite extreme, the deontic self or ought-to-self does not correlate significantly with any of the rest of the variables considered. Regarding the cross-sectional analysis of age and gender, no significant differences were found in gender. However, there was a negative and significant correlation between age and academic performance. Furthermore, there was positive and significant correlation between age and projected effort.
Madrasa teacher professionalism: Effects of gender and teaching experience in learning
Authors: Tambak Syahraini , Ahmad Muhammad Yusuf , Amril Amril , Sukenti Desi , Hamzah Hamzah , Marwiyah St.
Published: August 2022

Developing professional madrasa teachers are increasingly popular in the classroom, but of these teachers, mixed results (without clear reasons) are reported. This article addresses the impact of gender and teaching experience (duration) on developing professional madrasa teachers, using the two factors as references. Research with a questionnaire was conducted in 75 public and private Aliyah Madrasas, with data collected from 325 teachers. Data analysis is differentiated based on madrasa teachers’ type (public or private), gender, and teaching experience in the competencies assessed. Results showed that developing professional teachers’ proficiency is low and related to gender, that males perceive themselves more highly developed professionally than females, and that even teaching experience does not necessarily ensure development of professional competence and implementation in the classroom. The development of professional madrasa teachers with more than 30 years’ experience is less proficient than that of teachers with experience from 21–30, 10–20, and <10 years. However, the significant relationship between gender and professional development of madrasa teachers who have taught for more than 30 years is revealed: the development of male madrasa teachers who have taught for more than 30 years is less proficient than that of females. Reasons behind this difference must be examined and competencies differentiated to improve development of professional madrasa teachers’ professionalism.
Comparative Evaluation of Wear of Natural Enamel Antagonist Against Glazed Monolithic Zirconia Crowns and Polished Monolithic Zirconia Crowns: An In Vivo Study
Authors: Dondani Jay , Pardeshi Vikrant , Gangurde Arti , Shaikh Almas , Mahule Aushili , Deval Prachi
Published: August 2022

Purpose: To comparatively evaluate the amount of wear of natural enamel against a glazed full coverage monolithic zirconia crown and a polished monolithic zirconia crown at 6 and 12 months. Materials and Methods: Thirty subjects within the age range of 18 to 35 years participated in this study. The subjects received a total of 60 single crowns, which were divided into two groups: (1) 30 glazed monolithic zirconia crowns opposed by natural enamel (group A); and (2) 30 polished monolithic zirconia crowns opposed by natural enamel (group B). Each subject received a crown from both groups, placed bilaterally in endodontically treated maxillary or mandibular first molars. An impression was made of the opposing arch at 24 hours, 6 months, and 12 months. The resulting casts were scanned with a 3D optical scanner. The recall scans were superimposed and compared to baseline scans using 3D AutoCAD software. A control group was included to compare the wear values to natural enamel against natural enamel. Results: No significant difference (P = .855) was found in enamel wear between groups A (42.80 μm) and B (42.50 μm) after 6 months of use. However, a significant difference (P < .05) in enamel wear was found between group A (81.87 μm) and group B (71.43 μm) after 12 months of use. Conclusion: Glazed monolithic zirconia crowns cause more wear to the opposing enamel than polished monolithic zirconia crowns after 12 months of clinical use.
Patients Are Humans Too: The Emergence of Medical Humanities
Authors: Wailoo Keith
Published: August 2022

This essay describes the origins, growth, and transformation of the medical humanities over the past six decades, drawing on the insights of ethicists, physicians, historians, patients, activists, writers, and literature scholars who participated in building the field. The essay traces how the original idea of “humanizing physicians” evolved and how crises from death and dying, to AIDS and COVID-19, expanded humanistic inquiry into health, illness, and the human condition. It examines how a wide array of scholars, professional organizations, disciplinary approaches, academic units, and intellectual agendas came to define the vibrant field. This remarkable growth offers a counterpoint to narratives of decline in the humanities. It is a story of growing relevance shaped by tragedy, of innovative programs in medical schools and on undergraduate campuses, and vital new configurations of ethics, literature, the arts, and history that breathed new life into the study of health and medicine.
A Pragmatic Account of the Weak Evidence Effect
Authors: Barnett Samuel A. , Griffiths Thomas L. , Hawkins Robert D.
Published: August 2022

Language is not only used to transmit neutral information; we often seek to persuade by arguing in favor of a particular view. Persuasion raises a number of challenges for classical accounts of belief updating, as information cannot be taken at face value. How should listeners account for a speaker’s “hidden agenda” when incorporating new information? Here, we extend recent probabilistic models of recursive social reasoning to allow for persuasive goals and show that our model provides a pragmatic account for why weakly favorable arguments may backfire, a phenomenon known as the weak evidence effect. Critically, this model predicts a systematic relationship between belief updates and expectations about the information source: weak evidence should only backfire when speakers are expected to act under persuasive goals and prefer the strongest evidence. We introduce a simple experimental paradigm called the Stick Contest to measure the extent to which the weak evidence effect depends on speaker expectations, and show that a pragmatic listener model accounts for the empirical data better than alternative models. Our findings suggest further avenues for rational models of social reasoning to illuminate classical decision-making phenomena.
What Do We Mean When We Say “Presence”?
Authors: Murphy Dooley , Skarbez Richard
Published: August 2022

Characterizations of presence are many and various. The first part of this article applies philosophical and psychological lenses to three common descriptions: Presence as (or as following from) “the suspension of disbelief,” presence as the “illusion of nonmediation,” and presence as “(the feeling of) being there.” These construals of presence—the assumptions and commitments they make—are compared with one another, their plausibility and utility appraised. The second, shorter part of the article is not so much interested in definitions as distinctions that may help us ask better questions moving forward. We briefly consider the role of attention in presence, whether, when, or how presence is “binary,” and whether it is helpful to speak of presence in unmediated physical reality. A recurring theme throughout the article is whether a given understanding of presence (mis)construes the mind as monolithic: That is, as uniformly rational and consciously accessible. In closing, we suggest that researchers specify precisely what type of presence they're referring to whenever the concept is evoked; and that states such as involvement, absorption, and engagement be kept conceptually separate from presence, since they speak to “higher” cognitive functioning than simply feeling self-located in virtual environments, and indeed need not presuppose placeness or spatiality at all.
Fuscoporia hainanensis sp. nov. (Hymenochaetales, Basidiomycota), a new member of the F. contigua group
Authors: CHEN QIAN , LIU LU , ZHANG DE-SHUN , DONG LI-LI
Published: August 2022

A new species, Fuscoporia hainanensis sp. nov. (Hymenochaetaceae, Basidiomycota), is decribed based on specimens from China. Phylogenetic analyses on the nLSU and ITS+nLSU+TEF1 datasets revealed that the new species was nested within the F. contigua group and formed a strongly supported lineage distinct from other species. The new species is characterized by annual, resupinate basidiocarps with medium pores (4–6 per mm), aseptate skeletal hyphae, presence of mycelial setae, hymenial setae and cystidioles, and cylindric basidiospores (5.0–6.2 × 2.3–3.0 μm). A key to the accepted period species of resupinate and mycelial setae present species of Fuscoporia is provided.