bluuebunny/crossref_metadata_2025 huggingface dataset:
The Ethnomathematics Practices of Eskaya Tribe
Authors: Et.al Fe R. Janiola
Published: April 2021

This research sought to describe the Ethno-mathematical practices of the Eskaya tribe of Taytay, Duero, Bohol using the ethnographical research design to explore the ethnomathematics practices through the lived experiences of the informants. Employing purposive sampling, selected teachers, parents, and students from the tribe served as the key informants of the study. Data collection took almost a year of observation, lived experiences documentation, and interviews. The study was able to describe some of the ethnomathematical practices of the Eskaya tribe such as the skills and processes of the Eskaya tribe commonly use in their daily life in counting, measuring, ciphering, ordering, classifying, inferring, and modeling patterns. These skills and techniques were used in studying their Eskaya numeration systems such as the Eskaya numbers and numerals, the Eskaya name of the basic shapes and the four fundamental operations, and the use of Eskaya numbers in measuring time, days, and months.
The “self-learning query” algorithm for searching scientific publications across specialized search engines
Authors: Et.al Nikolay V. Kovalev
Published: April 2021

Typically, a search operation on Big Data is complicated task due to different formats and different nature of the data. To simplify it the user may implement special algorithms to process different data for uncertain criteria. The “self-learning query” algorithm presented in this work allows to search in Big Data either for certain or uncertain search criteria’s with minimum attention from the data programmer. It uses accumulated search statistics as the basis to make the result set more precisely according to the search criteria, so as long the user work with the system as more precise will be the results. The algorithm presented in this work allows data scientists to search for uncertain data and potentially discover results faster by offloading the burdens of data management and provenance to the expert system.
An Ad Hoc Movement Monitoring Algorithm for Indoor Tracking During Examinations
Authors: Et.al Sibghatullah H M Sediq
Published: April 2021

Academic dishonesty includes cheating in examinations tests and any academic assignments, plagiarism, fabrication of information or citations, facilitation of acts of academic studies by others, unauthorized possession of examination materials, and tampering with the academic work of other researchers or scholars. These acts can be done before, during, and after the actual examination. This paper proposes a holistic algorithm for setting up an ad-hoc monitoring system to track candidates who leave the examination hall during the examination for either toilet breaks, medical breaks, or otherwise. Since most examinations are held indoors it is especially difficult to use existing GPS and GPRS based methods. We submit a proposal to deploy an indoor monitoring system based on the RSS of carefully placed receivers as they communicate with active tags held by the candidates. This paper outlines an algorithm that is used to place the receivers in such a way as to avoid any blind spots which may be utilized as cheating spots. The algorithm was deployed into a testbed system which was 100% foul proof. The proposed algorithm can be used to set up the deployment of the monitoring system in any environment where a clearly defined path is identified.
Adaptive Data Hiding Based Telephony Speech Enhancement
Authors: Et.al N Prasad
Published: April 2021

Public telephone systems transmit speech across a limited frequency range, about 300–3400 Hz, called narrowband (NB) which results in a significant reduction of quality and intelligibility of speech. This paper proposes a fully backward compatible novel method for bandwidth extension of NB speech. The method uses adaptive data hiding technique to provide a perceptually better wideband speech signal. The spectral envelope parameters are extracted from the high frequency components of speech signal existing above NB, which are then spread by using spreading sequences, and are embedded in the NB speech signal using adaptive data hiding technique. The embedded information is extracted at the receiving end to reconstruct the wideband speech signal. Theoretical and simulation analyses show that the proposed method is robust to quantization and channel noises. The log spectral distortion test clearly show that the reconstructed wideband signal gives a much better performance in terms of speech quality when compared to the conventional speech bandwidth extension methods employing data hiding.
A New Way To Prevent Colorectal Cancer Using Supervised Learning Technique
Authors: Et.al Balaji Vicharapu
Published: April 2021

The Colorectal cancer prompts to more number of death as of late. The diagnosis of colorectal cancer as early is protected to treat the patient. To distinguish and treat this type of cancer, Colonoscopy is applied ordinarily. Several risk prediction models for colorectal cancer have been created and approved in various populations but colon cancer effecting the young adults. In this research, we projected a Supervised Learning Technique for detecting colorectal cancer in high dimensional information.One of the most important and very popular tool for performing the machine learning tasks that includesnovelty detection,classificationorregression is Support vector machine (SVM). Training the SVM requires large quantity of quadratic programming. Due to memory constraints conventional methods are not directly applied. To overcomethese inadequacies,we introduced, Least Square (LS), Particle Swarm Optimization (PSO), Quadratic Programming and Quantum-behave PSO methods for training SVM.To corroborate the competence and proficiency of our predictable system, it is developed in open source called NCSS Software.The acquiredoutcomesof these approaches are verified on a CCG1.11 Colorectal dataset and related with the particularresolution model.
Design and Implementation of Missing Data Classification Technique for IoT Applications Using Artificial Intelligence
Authors: Et.al Gopal Patil
Published: April 2021

The combination of various sensors with different data methods is a common technique used to increase precision in the classification of IoT health data. However, for even the assessment outcomes, all modalities are barely available and this scarcity of evidence poses significant barriers to multimodal education. Driven by recent developments in deep education, we are providing a cross-neural network for the segmentation of the IoT Health Data Classification, which is trained on data modalities not all available during trials. In IoT Health Data Classification, we train our architecture with a cost function that is especially tailored to unbalanced classes. We are providing the device with a benchmark data set with incomplete data. Assuming that they are not present in the research process, our methodology goes beyond both the CNN training and the collection of two CNNs trained in the missing modality by utilising time data
A Survey on “Machine translation Approaches for Indian Languages”
Authors: Et. al. Pooja P. Walke
Published: April 2021

Translation has always helped India to knit Indians together with respect to its rich culture and literature. Ideas and concepts like ‘Indian ancient literature’,’Indian rich culture’,’Indian philosophy’ and ‘Indian knowledgeable systems’ would have been impossible in the absence of translations with their natural integrationist mission.Machine Translation assist to translate Information presented in one language to other language. Information can be present in form of text, speech and image translating this information helps for sharing of information and ultimately information gain.Translation process is an extremely complex & challenging process. It requires an in-depth knowledge about grammar of both the languages i.e. Source language and Target language to frame the rules for target language generation. Marathi is a regional Indian language and consists of a lot of literature that could be useful if projected in the universal English language. As manual translation is a tedious task, we propose a literature survey about machine translation systems that translates Indian Languages into English Language using various Machine translation approaches like RBMT, SMT, NMT, Hybrid translation
Cost Optimization of Food Diet for Adult Filipino Patients With Stage 1 or Stage 2 Chronic Kidney Diseases
Authors: Et. al. Rolan J. Malvar
Published: April 2021

Chronic kidney disease (CKD) is a very common disease in the Philippines. Some of its main causes are hypertension and diabetes. This study is aimed to develop an optimal food dietary model from ninety (90) combinations of linear programming models for adult Filipino patients with Stage 1 or Stage 2 Chronic Kidney Disease. This process will search for the lowest possible cost of their daily food plan while satisfying their daily nutritional requirements. The diet contains six nutritional requirements which are protein, sodium, potassium, phosphorous, calcium and calories. The thirteen cooked food commodities are the following: pork, milkfish, chicken, tilapia, egg, white rice, roasted green beans with garlic, sautéed cabbage, stir-fry bitter gourd, coconut meat, avocado, mango, and oat bran. Using the selected linear programming model which consist of chicken, tilapia, white rice, roasted green beans with garlic, stir-fry bitter gourd, coconut meat, and oat bran, the minimized daily dietary plan cost for adult male is ₱134.23, and adult female with ₱133.2
A Study on the impact of Coping Strategies over Stress Management – An Empirical Study
Authors: Et. al. Ch.Narahari
Published: April 2021

In the present study we analyze the employees’ perception towards coping measures adopted byfirms in software industry. The considered coping constructs adopted for the study in stress abatement areVenting of Emotions,Problem Focused, Seeking Information and emotional support, Positive Emotion-Focused, were, employee perception was acquired by a systematic survey.A total sample of 800 employees’perceptions have been collected through simple random technique and out of which survey respondents, irregular responses are eliminated finally 756 samples are determined for statistical analysis. Chi-square test was performed to determine the association between perceptions and model constructs. Results are reported and discussions are made as per the results and in correlation between results of previous literature.Finally, suggestions and future indication for extension of the study are proposed.
Current Conceptual Problems of the Russian Agrarian-Industrial Complex Digitalization in the Globalization Content
Authors: Et. al. Volostnov N.S
Published: April 2021

The modern global economy is becoming more digital, and at great speed, intensity, and scale. Its international universal ‘language’ is information technology. Only this ‘language’ is objectively possible to ‘understand’, to interact concerning isolated, national reproductions taking place in many states. It is the need for this understanding, as well as for its practical use, that act as the criteria reasons for digitalization of the national economy of Russia as a whole, and its organic component - the agro-industrial complex.

Another reason, is the economic necessity of the above-mentioned phenomenon, which allows receiving, store and transmit information about counterparties, tariffs and make contracts, make fuller use of limited resources, and in the best way satisfy both production and personal needs of various subjects in real-time [1].

The article reveals the content of the modern stage of the Russian agro-industrial complex digitalization in its integrity and specificity
Effective Instructions by Novice Teacher to Improve Teaching Repertoire in School
Authors: Et.al Maria Shu Hong Bee Abdullah
Published: April 2021

This paper highlights a review on the importance of giving clear instructions and strategies to improve oral instruction by novice teachers as they improve their teaching repertoires in schools. Essentially, this will help teachers to develop a clear oral instruction for good class management. It is an agreeable fact that giving instruction is a skill that takes many years of experience to master and meets the ideal set of practice that teachers set for themselves. Novice teachers face a lot of challenges to master the skill of giving instruction effectively and that is a mark of great quality of a teacher. An effective instructional strategy will deliver the lesson clearly and help learners to understand the focus, engage actively and take ownership of their learning.
Formulaic Sequences in Mainland China over the Past Decade – A Review
Authors: Et.al Sara Wang
Published: April 2021

In this paper, Formulaic Sequences (FS) over the past ten years are reviewed to provide some insights on its usage in the process of teaching and learning English language in China. It identifies three main features. Firstly, the general trends of FS, Secondly, the characteristics of development of FS in various fields. Thirdly, the use of FS and the teaching of FS. Finally, the paper puts forward some suggestions on the use of formulaic sequence on teaching and learning foreign language in mainland China．
Muslim Workers’ Perceptions of Performing Prayers at Workplaces and Its Impacts on Their Work Performances
Authors: Et.al Abdul Munir Ismail
Published: April 2021

Purpose: Studies have shown that employees performing prayers at workplaces has raised several controversial issues relating to their working performances. As such, this study was carried out to examine Muslim workers’ perceptions of the positive impacts of performing obligatory prayers at their workplaces.

Methodology: This study was based on a quantitative approach using an online survey based on Google form through which 200 Muslim workers, whose ages ranged from 18 to 50 years, were randomly selected to be the respondents. The Statistical Package for the Social Science (SPSS) (version 23.00) was used to analyze the data descriptively in terms of frequency and percentage.

Findings:Revealingly, the findings showed that most Muslim workers perceived performing obligatory prayers had significant impacts on making them more disciplined, punctual, able to work more independently, productive, and competitive. Equally revealing, they perceived strict observance of obligatory prayers had profound impacts on their perseverance to adhere to rules and to avoid committing a breach of trust. Such promising findings should inform employers the inalienable rights of Muslim employees to pray in their premises, which is enshrined in Malaysia’s federal constitution, and the positive impacts of prayers on their workers’ discipline, motivation, and ability, which collectively can help improve the productivity and profitability of their organizations.

Significance:On a positive note, the above findings can help dispel several negative perceptions of some employers that Muslim workers performing prayers at workplaces will adversely affect their productivity, which was found in this study to be completely unfounded and untrue.
Mastery Level of Historical Thinking Skills (KPS) among Form Two Students
Authors: Et.al Baharuddin Jabar
Published: April 2021

This study aimed to explore the Historical Thinking Skills among Form Two students. This study involved five aspects of the historical thinking skills: understanding chronology, exploring evidence, making interpretations, imagining and rationalizing while the focus of content standard referred to the four Content Standards in DSKP KSSM Form One History subject which are Introduction to Knowledge of History, Prehistoric Age, Ice Age and World Civilization and Its Contributions. The research instrument used in this study was a set of questionnaires in a form of multiple choice objective items about the History subject. The research participants involved were 388 Form Two students. Data were analysed descriptively to identify the level of students' historical thinking skills. The following findings revealed the level of historical thinking skills among Form Two students in all five aspects: 60.7% for understanding chronology, 46.7% for exploring evidence, 65.4% for making interpretations, 68.5% for imagining and 64.9% for rationalizing.
Community Service as an Alternative Form of Punishment under the Domestic Violence Act 1994 in Malaysia
Authors: Et.al Daleleer Kaur Randawar
Published: April 2021

This article intends to explore the punishment meted under the law relating to domestic violence in Malaysia.  The investigation extended to an analysis with the need to implement and introduce community service as a form of punishment for domestic violence offences. A comparative legal research methodology is employed in comparing the positions in Malaysia and certain selected jurisdiction. It is expected that the findings of this paper will look into the need to introduce and implement community service as a form of punishment which will optimisticallyencourage repentance by the offender and preserve the sanctity of marriage. Community service as a form of punishment will be a great intervention that will more likely emphasize the responsibility of the wrongdoer in healing a family relationship. The article seeks to suggest legislative reforms which will involve a comparative study of other comparable jurisdictions.
Towards Achieving Long-Term Debt Sustainability: A Systematic Review of the Key Determinants of Personal Bankruptcy
Authors: Et.al Aqilah Nadiah MD SAHIQ
Published: April 2021

Purpose: This systematic review aimed to assess previous research about financial and non-financial causes of personal bankruptcy among individual households. Additionally, the paper aimed to provide an insight into the key determinants of personal bankruptcy and to determine their relationship with individual characteristics. The fundamental causes of bankruptcy and its effects on financial status were also discussed. Through understanding the causes of bankruptcy, we hope to help financial institutions to minimise the number of personal bankruptcies.

Design/methodology/approach: A comprehensive systematic search was conducted to identify articles on determinants of personal bankruptcy. The selected articles were then analysed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol.

Findings: We identified several themes that emerged as the key determinants of personal bankruptcy filings. These determinants were demographic indicators, socioeconomic status indicators, debt indicators, financial indicators, social stigma indicators, behavioural indicators, and macroeconomic indicators.

Research implications: The key determinants of personal bankruptcy that were identified in this systematic review are renowned factors in the personal bankruptcy literature. Therefore, these determinants should be studied extensively to examine their effects in other studies and using a different type of datasets.

Practical implications: The findings of this study help the financial institutions to predict the likelihood of consumer default by developing an effective credit scoring model. Additionally, the development of an effective credit scoring model could serve as an early warning indicator to identify “high risk” client.

Originality/value: Bankruptcy is a long-term process that does not occur instantly. Therefore, a longitudinal and comprehensive approach is required to understand bankruptcy. Our findings contribute to the current literature by providing a better understanding of the causes of personal bankruptcy. We recommend developing an effective credit scoring model to predict the likelihood of personal bankruptcy.
Analysis of Emotion Recognition Model Using Electroencephalogram (EEG) Signals Based on Stimuli Text
Authors: Et.al Khodijah Hulliyah
Published: April 2021

Recognizing emotions through the brain wave approach with facial or sound expression is widely used, but few use text stimuli. Therefore, this study aims to analyze the emotion recognition experiment by stimulating sentiment-tones using EEG. The process of classifying emotions uses a random forest model approach which is compared with two models, namely Support Vector Machine and decision tree as benchmarks. The raw data used comes from the results of scrapping Twitter data. The dataset of emotional annotation was carried out manually based on four classifications, specifically: happiness, sadness, fear, and anger. The annotated dataset was tested using an Electroencephalogram (EEG) device attached to the participant's head to determine the brain waves appearing after reading the text. The results showed that the random forest model has the highest accuracy level with a rate of 98% which is slightly different from the decision tree with 88%. Meanwhile, in SVM the accuracy results are less good with a rate of 32%. Furthermore, the match level of angry emotions from the three models above during manual annotation and using the EEG device showed a high number with an average value above 90%, because reading with angry expressions is easier to perform.

For this reason, this study aims to test the emotion recognition experiment by stimulating sentiment-tones using EEG. The process of classifying emotions uses a random forest model approach which is compared with two models, namely SVM and decision tree as benchmarks. The dataset used comes from the results of scrapping Twitter data.
IoT Technology with Fuzzy Logic Control Integrated System to Achieve Comfort Environment
Authors: Et.al A Miqdad
Published: April 2021

Internet of Thing technology is known for its capability to collect and store a massive amount of data for further research development. Researcher widely utilizes this technology as it has become a very convenient tool with a cost-effective advantage. Practically, the calculation is made before determining the best cooling device for every room with temperature, humidity and power consumption being an important element to be taken into account. This paper present the practical approach to acquire data using WSN and IoT technology which then lead to the development of fuzzy logic control of the air conditioner with the aim to reduce its overall power consumption. Classroom equipped with two non-inverter air-conditioners with 4HP each used as a testbed.
Review on Foreign Object Debris Detection Technologies and Advancement for Airport Safety and Surveillance
Authors: Et.al G. Fizza
Published: April 2021

The rapid growth of air traffic worldwide leads to frequent landing and takeoff of airplanes at busy airports. Therefore, the airport runway must be safe and clean from any tiny size and shape of foreign object debris that is very hard to detect by visual inspection. For successful and fast removal of foreign object debris, an efficient system capable of precisely detecting foreign object debris is required. This paper presents a review of the available technologies to detect foreign object debris and compares commercially available foreign object debris detection technologies. The review has revealed that millimeter-wave radar technology is one of the most efficient foreign object debris detection techniques as it is weather resilient. Furthermore, millimeter-wave radar integrated with radio over fiber technology provides a cost-effective solution to detect foreign object debris within 10 seconds at 96 GHz frequency. A pilot test has been carried out at Narita International Airport, Japan and Kuala Lumpur International Airport, Malaysia, to detect foreign object debris either in a mobile or immobile position.
Measuring the Effectiveness of Exergames among Gen Z using Kinect Sensor and EEG
Authors: Et.al Nurhafizah Moziyana Mohd Yusop
Published: April 2021

Nowadays, generation Z are not interested in applying the traditional method in sports or learning activity. General observation found that primary students nowadays are eagerly using technology during learning or sports activity. Exergames using Kinect is one of the solutions to encourage the interest of generation z. This research focusses on the Effectiveness of Exergames using Kinect Sensor among primary students. The research also uses EEG measurement to prove the attention level of students during this activity. The emphasis of this paper is the student's performance and their level of focus. The signals from the EEG set are acquired while the students are playing the games and the Kinect sensor will be able to sense their movements during the session. The Kinect sensor can sense the users' whole body movement and physical activity that makes it more flexible in terms of area of monitoring. Finding from previous research shows that Exergames using Kinect Sensor is more fun and relaxing to increase the attention level of primary students.
Assessment of Facial Homogeneity with Regard to Genealogical Aspects Based on Deep Learning Approach
Authors: Et.al Ravi Kumar Y B
Published: April 2021

The current research work encompasses the assessment of similarity based facial features of images with erected method so as to determines the genealogical similarity. It is based on the principle of grouping the closer features, as compared to those which are away from the predefined threshold for a better ascertainment of the extracted features. The system developed is trained using deep learning-oriented architecture incorporating these closer features for a binary classification of the subjects considered into genealogic non-genealogic. The genealogic set of data is further used to calculate the percentage of similarity with erected methods. The present work considered XX datasets from XXXX source for the assessment of facial similarities. The results portrayed an accuracy of 96.3% for genealogic data, the salient among them being those of father-daughter (98.1%), father-son(98.3%), mother-daughter(96.6%), mother-son(96.1%) genealogy in case of the datasets from “kinface W-I”. Extending this work onto “kinface W-II” set of data, the results were promising with father-daughter(98.5%), father-son(96.7%), mother-daughter(93.4%) and mother-son(98.9%) genealogy. Such an approach could be further extended to larger database so as to assess the genealogical similarity with the aid of machine-learning algorithms.
Optical Transport Network to support Digital Communications
Authors: Et. al. Marco Rosario Villareal,
Published: April 2021

The objective of this work is to propose a solution to the problem of the lack of telecommunication services, with adequate quality of service and coverage, in the town of Choclococha, Huancavelica-Peru. For this purpose, the design and evaluation of an optical link as a backbone network and a wireless access network is presented. It is an applied and experimental research in which performance parameters were evaluated. The independent variable is the optical transport network and the dependent variable is data communication. The latter is defined by two indicators: throughput and signal reception power at the users. Both indicators were measured in a sample of the population, obtaining results that were validated with respect to the expected values according to specifications and regulations. Thus, the measured throughput exceeds the 40% data rate guaranteed by the telecommunications operator. As for the reception power, it exceeds the sensitivity level of the receiving equipment. Therefore, it is concluded that the proposed solution supports communications with optimum speed and coverage.
Disruption in the consumer decision-making? Critical analysis of the consumer's decision making and its possible change by the COVID-19
Authors: Et. al. Ríos Lama Cristian Armando,
Published: April 2021

A multidisciplinary concept of consumer science and a disruptive pandemic. How are these elements intertwined? In this sense the purpose of this article is to know how the purchase decision could be changed by the covid-19. A holistic analysis of both the psychological and economic effects of a pandemic, impacts from the generational theory, and how this could cause security to become more relevant was carried out. It was carried out a systematic review of scientific literature consulting 304 articles, being 106 the selected ones, under high impact criteria. It is presumed that consumers will make slightly more rational decisions, although this will be subject to factors inherent to specific scenarios, so it is necessary to perform multivariate empirical research
Financial Analysis Method Based On Astrology, Fibonacci, And Astronacci To Find A Date Of Direction Inversion Base Information Technology - Jci And Future Gold Prices
Authors: Et. al. Gema Merdeka Goeyardi,
Published: April 2021

The purpose of this research is to analyze and obtain empirical evidence knowing the exact time to be predicted determining the reversal date of the JCI (Jakarta Composite Index) price and Gold prices can use the method of Astrology, Fibonacci, Astronacci. The method used in this research is descriptive and explanatory methods. Descriptive method is used to make steps Astrology, Fibonacci, and Astronacci methods to find the reversal date of the JCI and the price of Gold in the future. While the explanatory method is used to apply Astrology, Fibonacci, and Astronacci methods using historical data (in 2008-2017), JCI and Gold prices. Data used in this study for 1 decade is January 1, 2008 to December 31, 2017. Based on the three methods, the reversal opportunity of both the JCI and the highest Gold price using the Astronacci method rather than astrology or Fibonacci alone.
The Model of Intellectual Capital based Information Technology and Its Implication on Employees Performance
Authors: Et. al. Odang Kusmayadi,
Published: April 2021

This research  focused on  higher of job rejection result and low of coordination among unit in problem solving of all the projects which is tend to decline of employees performance. The main issues discussed  in this reseach is factors influence it, namely human procurement ,development  and  intellectual capital based information technology.The research aims to analyze, describe and test the impact of   human procurement, development on intellectual capital and its implication on employees performance at  Indonesian Aerospace,Ltd. The research used was descriptive and explanatory survey method, so the research attempts to collect, present, analyze, and test hypotheses,  to make a consclusions were used  Structural Equation Model (SEM) approach. The design of  study is a survey reseach, the unit analysis selected were  core knowledge worker with a sample size of 303 from 1245 employees, based on Slovin’s formula. The results indicated  that human procurement, development have a simultaneously positive and significant effect on intellectual capital based information technology, and human procurement, development are either partialy or simultaneously have a positive and significant effect on employees performance level throught intellectual capital based information technology. The findings  are:(1) human procurement indicates low contribution on either  intellectual capital based information technology or employees performance, the highest score of human procurement dimension is selection and the lowest is recruitment dimension. 2) human development indicates low contribution on either intellectual capital or employees performance, the highest score of human development  dimension is education and the lowest is training dimension (3) intellectual capital based information technology  indicates moderate scores on employees performance level, the highest score of intellectual capital dimension is social capital  and the lowest is structure capital dimension. (4) the highest score size of employees performance dimension based on  employees perception  is goal and the lowest is motive dimension.
A Wireless Intelligent System Construction For Measuring And Control Of Liquid Product Level In Reservoir Parks
Authors: Et. al. Nodirbek Rustambekovich Yusupbekov,
Published: April 2021

The article is devoted to a system construction for measuring and controlling the liquid materials level in remote reservoirs. The hardware solution is based on Wi-Fi technology with radio frequency data transmission and level measurement using an ultrasonic sensor. An internet server is used to collect data in a database and present the data to users in the web pages form. The developed system provides high accuracy, low power consumption and low cost.
Using Transformations to Predict and Smooth Time Series
Authors: Et. al. Jassim N Hussain,
Published: April 2021

Time series has a leading position in statistical Analysis.  Nowadays, many economic and industrial operations have been built based on time series. These operations include predicting the product demand variation, the future product prices oscillation, the stock storing control etc. This paper presents a study to show the effect of transformation and smoothing on the performance of the time series. The research results have shown a significant improvement in time-series operation can be noticed when the principles of transformation and smoothing are applied on time series.
How the Organizational Envy Effects on Organization's Brilliance? The Moderating Role of Contextual Leadership Intelligence
Authors: Et. al. Ali Razzaq Al-Abedi,
Published: April 2021

The present paper aims to identify the impact of organizational Envy on organizations' brilliance through the interactive role of intelligent contextual leadership in universities and private colleges in the province of Najaf. The approach was relied on (descriptive - exploratory), and the questionnaire was used as a measurement tool. The study population was the teaching bodies working in universities and private colleges in Najaf, who numbered (811) teaching staff. Whereas the research sample is (257) teachers, and several statistical programs (Smart PLS) (SPSS v.23) have been used to analyze the data and test the primary and sub-hypotheses emanating from it. The results show a significant effect of organizational Envy on organizations' brilliance through the intelligence of contextual leadership, and the results showed acceptance of most of the leading and sub-hypotheses emanating from it.
Effects of REACT Learning Model Based on Riau–Malay Culture Towards Mathematical Problem-Solving Ability and Achievement Motivation amongst High School Students
Authors: Et. al. Zulkarnain,
Published: April 2021

This quasi-experimental study was conducted to determine the effects of the Relating, Experiencing, Applying, Cooperating and Transferring (REACT) teaching model, which was based on the Riau–Malay cultural context, on the ability of high school students to solve mathematics problem and their motivation to achieve high performance. A total of 287 high school students were involved in this study. The treatment group consisted of 143 students, whereas the control group comprised 144 students. Data were analysed using the SPSS 25.0 software. Findings showed that students in the treatment and control groups had significantly different abilities to solve mathematical problems and motivations to achieve high performance. Students who underwent the REACT teaching model had better ability and higher motivation than those who learned conventionally. Findings imply the importance of using the REACT model based on the Riau–Malay cultural context to enhance students’ mathematical problem-solving ability and motivation for improved performance.
Risk Management in Moroccan Healthcare Organizations: An Overview
Authors: Et. al. En-Naaoui
Published: April 2021

The institute of medicine asserts that to err is human: building a safer health system (Linda T et al, 2000). For this reason risk management takes an important place in healthcare decision-making process within the objective of ensuring the management of emergencies, which cannot always be anticipated in advance, but will cause serious consequences if they occur (Li Guo, 2015). In fact, risk management is defined as a set of activities and processes of identification, analysis, evaluation, treatment, reducing, communication and monitoring potential failures and adverse events in purpose to provide a better quality of service and a system able to insure protection of patients, workers, equipment, stakeholders and the environment. Thus, this paper aims to present a structured review of publications that highlight risk management topic in healthcare sector by proposing new approaches, applying existed techniques or implementing risk assessment plans in Moroccan healthcare organizations especially Moroccan hospitals.
A Review of Machine Translation for South Asian Low Resource Languages
Authors: Et. al. Syed Abdul Basit Andrabi,
Published: April 2021

Machine translation is an application of natural language processing. Humans use native languages to communicate with one another, whereas programming languages communicate between humans and computers. NLP is the field that involves a broad set of techniques for analysis, manipulation and automatic generation of human languages or natural languages with the help of computers. It is essential to provide access to information to people for their development in the present information age. It is necessary to put equal emphasis on removing the barrier of language between different divisions of society. The area of NLP strives to fill this gap of the language barrier by applying machine translation. One natural language is transformed into another natural language with the aid of computers. The first few years of this area were dedicated to the development of rule-based systems. Still, later on, due to the increase in computational power, there was a transition towards statistical machine translation. The motive of machine translation is that the meaning of the translated text should be preserved during translation. This research paper aims to analyse the machine translation approaches used for resource-poor languages and determine the needs and challenges the researchers face. This paper also reviews the machine translation systems that are available for poor research languages.
Controlled Converter AC/DC through Small Input and Output Current
Authors: Et. al. K. Bhaskar,
Published: April 2021

A high controlled converter one form to another form of supply like (AC/DC) is displayed in this article. The system is planned converter become 2 shifted fundamental restricted Converter in this work-controlled method for boosting its knowledge power. In these, the present weight of the guideline switches in the presented converter can be diminished. What is more, the present influx of yield and contribution to it in like manner can be lessened. Additionally, every progression fundamental circuit is showed converter is operated four changes to give execution the capacity of voltage guideline and force factor (pf). Frequency modulation with secured on and off time intermissions are discard, now this converter. A 1kW indicated the converter exists to see its display.
WTO and India’s Agricultural Trade Potential
Authors: Et. al. Raghav Bansal,
Published: April 2021

India is an agrarian economy, which contributes about 15 percent of GDP and provides livelihood to more than 50 percent of the total population of the country. WTO has shown a momentous part in the expansion of the export market for developing and developed economy. Several measures are taken by WTO in order to reduce trade restrictions and trade barriers. In this study, we have been analyzed India’s agriculture trade, composition, direction and potential. The study is dependent on secondary data which is gathered from International Trade Centre, Department of Agriculture and Co-operation. Two-digits HS code products range from 01-24 were taken for the study. Few specific two and four-digit HS code products were taken to analyze the Revealed Comparative Advantage (RCA). Data were taken for the period 2001-2018. The export potential of India in international market was identified using reckoning of Balassa’s index of RCA. Study reveals that there has been a positive agricultural trade balance since 1990-91. In some agriculture commodities like coffee, oilseeds, tea and wheat India has a comparative advantage in export and India have both developed and developing countries such as UAE, USA, Saudi Arabia, Vietnam and Iran are exporting partner. In the last, study suggest that the government of India should focus more on producing agriculture products which has a country comparative advantage in trade like tea, oilseeds, coffee and wheat. Study suggests that EXIM bank should provide adequate credit to encourage agricultural export. The farming should be export-oriented to meet international standards.
Advanced Controllers Implementation for Speed Control Analysis of Two Mass Drive System
Authors: Et.al D.Devasena
Published: April 2021

The speed control of two mass drive systems is presented in this paper. For the purpose of analysis, PI, Linear Matrix Inequality controller and Internal Model Controller are chosen. Tuning of PI controller is achieved by Zeigler Nichols method, whereas the LMI and IMC are adapted with the conventional method of tuning. The various simulations are carried out in order to analyze the performance index of these controllers and to fix the best controller, and the results are compared
Analysis of Bitcoin Prices using Deep Learning Techniques
Authors: Et.al P Ravindhar Reddy
Published: April 2021

Project training - these projects are done for specific subjects without discussing methods that require knowledge and level of technical material. This paper discusses the design and implementation of project training in information technology as a major project that requires student creativity and describes the project clearly and concisely. These projects not only develop basic or technical skills but also practical skills. The goal of the modern student project is to show how trained machine models can predict cryptocurrency security if we allow appropriate levels of information and computing power. The diagram shows the approximate value. Conventional technology is way out of technology that can help people predict future events. With so much data being generated and stored daily, we are finally approaching an age where predictions are made from accurate and accurate data. Besides, with the advent of the digital currency era, more and more leaders have entered the digital investment market. This allows us to create models that can predict cryptocurrencies, especially Bitcoin. This can be done through several types of machine learning methods and in-depth learning and learning methods.
Analysis of Employee Attrition using for Machine Learning Techniques
Authors: Et.al Sadineni Sanjeetha
Published: April 2021

Nowadays, the daily forecast for employee losses becomes a major issue. Staff participation is an important issue for the organization, especially when professional technical staff and key people in the organization come from good positions. This leads to a loss of finances to replace skilled labor. Therefore, we use data from current and former employees to analyze common causes of employee access or influence. To avoid employment, we use several planning methods, namely: Decision Tree, Log-log of Backlog, SVM, KNN, Random Forest, Bayes Naive. To do this, we use the method to select employment information and analyze the results to avoid employee income. Companies need to anticipate employee incentives and contribute to economic growth by reducing manpower.
Deep Neural Networks Techniques using for Learning Automata Based Incremental Learning Method
Authors: Et.al C. Swetha Reddy
Published: April 2021

Surprisingly comprehensive learning methods are implemented in many large learning machine data, such as visual recognition and visual language processing. Much of the success of advanced training in recent years is due to leadership training, which requires a set of information for specific tasks, before such training. However, in reality, selected tasks related to personal study are gradually accumulated over time as it is difficult to collect and submit training data manually. It provides a way to continue learning some information columns and examples of steps that are specific to the new class and called additional learning. In this post, we recommend the best machine training method for further training for deep neural networks. The basic idea is to learn a deep system with strong connections that can be "activated" or "turned off" at different stages. The approach you suggest allows you to reduce the distribution of old services as you learn new for example new training, which increases the effectiveness of training in the additional training phase. Experiments with MNIST and CIFAR-100 show that our approach can be implemented in other long-term phases in deep neuron models and achieve better results from zero-base training.
Performance Analysis of Diabetes Mellitus Using Machine Learning Techniques
Authors: Et.al Kandala Srujana Kumari
Published: April 2021

Diabetes is a common disease in the human body caused by a set of metabolic disorders in which blood sugar levels are very long. It affects various organs in the human body and destroys many-body systems, especially the kidneys and kidneys. Early detection can save lives. To achieve this goal, this study focuses specifically on the use of machine learning techniques for many risk factors associated with this disease. Technical training methods achieve effective results by creating predictive models based on medical diagnostic data collected on Indian sugar. Learning from such data can help in predicting diabetics. In this study, we used four popular machine learning algorithms, namely Support Vector Machine (SVM), Naive Bayes (NB), Near Neighbor K (KNN), and Decision Tree C4.5 (DT), based on statistical data. people. adults in sugar. , preview. The results of our experiments show that the C4.5 solution tree has greater accuracy compared to other machine learning methods.
The E-Learning Utilization On Attitudes And Behavior Of Diarrhea Prevention During Pandemic
Authors: Et.al Zul Fikar Ahmad
Published: April 2021

Diarrhoea is a health problem that is often experienced by infants and toddlers and in almost every country. One of the efforts to prevent diarrhoea was through counselling. Due to the pandemic situation, face-to-face counselling was not possible. This study aimed to assess the use of e-learning in increasing knowledge, attitudes, and behaviours to prevent diarrhoea. This research was an analytical observational study with the design of The One Group Pre-test Post-test Design. Samples were select used the purposive sampling technique. The sample size in this study was 54 students. The eLearning model used in this research was Google Class. The data were obtained by using google form then analyzed using McNemar Test. The results of the analysis showed that there were differences in knowledge (p-value = 0.000), attitudes (p-value = 0.031), and behaviour (p-value = 0.016) to prevent diarrhea before and after treatment. The utilization of online learning (e-learning) significantly affected increasing knowledge, attitudes, and behaviour in preventing diarrhea. In the future, e-learning can be an alternative to prevent diarrhea during a pandemic.