bluuebunny/crossref_metadata_2025 huggingface dataset:
Economic Transition, Creating Opportunities and Establishing Resilience of Post-Covid Era in the Latin America and the Caribbean
Authors: Guerrero Felix Julca , Ramirez-Asis Edwin , Allauca-Castillo Wendy , Maldonado-Leyva Hugo , Peláez-Díaz Guillermo , Fernandez-Lopez Carlos
Published: January 2022

Latin America and the Caribbean has started adopting the various policy measure to develop the economic status of the region. The Covid-19 situation has impacted significantly on various sectors and structures of the region such as poverty, unemployment, economic and social inequalities among the people. The LAC region is navigating the various challenging atmosphere during the Covid-19 era, which has been affected directly in the contraction of gross domestic product of the region. Because of the lockdown procedures has impacted significantly on all economic activities, reduced the global demand especially the trade, and affected the entire tourism sector. Subsequently, the Covid-19 lockdown measures hit the poor people who lives under the poverty and those working in the low-paid wages workers in the informal sector. The informal sector workers are already not receiving any kind of social security measures. It is also noticed that 38 percent of the total workforce in the informal sector are not having any form of social security and affected a lot during the lockdown. According to OECD, this pandemic crisis made the micro, medium and small industries in vulnerable situation of the LAC region countries. It affected 2.7 million companies in LAC and influenced for the loss of 8.5 million jobs. Many of the LAC policy makers and the government responded in a very effective manner to protect and safe-guard the people from extreme poverty and vulnerability. Various monetary and fiscal policy measures have been taken and the crisis and revive the economy. The immediate action is taken on important segment such as supporting the poor household by creation of new jobs, generating employment through industries and firms. The necessary economic policy formulation supported the transition of the economy from the crisis to prosperity.
Purchase Intention of Indian Customers in Omnichannel Retail: Development of Conceptual Framework and Empirical Analysis
Authors: Singla Babita , K.P. Jaheer Mukthar , Huerta-Soto Rosario , Medina-Gutierrez Maria , Tomas-Aguilar Segundo , Salazar-Gonzales Fernando
Published: January 2022

The rise of the Internet technology and other technological breakthroughs in the last decade have altered the retail landscape. An ever-increasing number of outlets is emerging, causing purchasers' preferences and buying habits to shift. Customers can shop across channels from any place using an omnichannel method, which enables real-time collaboration and provides customers with an engaging, complete, and consistent purchase experience that bridges the lying channel gap in between. The objective of the study is to figure out what influences omnichannel purchasers' behavior by recognizing and aiming to use technological advancements within the purchasing cycle. To that end, a new framework was conceptualized based on factors, Social Influence, Habits Influence, Hedonic Motivation, Personal innovativeness and perceived security. The impact of these factors on the purchase intentions of customers in the omnichannel retail was analyzed using the data of sample size 314. The results of the study confirm positive influence of all factors mentioned in the framework on customers purchase intention in omnichannel retail. The study concludes with important implication for both scholarly field and practitioners beside mentioning its limitations.
A Survey on IoT Security: Attacks, Challenges and Countermeasures
Authors: H.J. Felcia Bel , S. Sabeen
Published: January 2022

IoT technology grows enormously now-a-days in various fields and it is a need to achieve high security requirements. IoT produces more amounts of data to communicate to each other which may undergo various issues like low processor speed, power, and memory. The IoT devices undergoing these barriers along with crucial information will get into different types of security attacks in IoT layers. An outline of IoT, it’s architecture, state-of-the-art technologies, security attacks in layers and analysis of security threats are studied and the countermeasures have been reported in this survey. The challenges and goals facing IoT security have also been discussed. The security threats on the IoT devices have been briefly introduced. The security challenges, giving research directions and finding security solution for each and every challenge have been also discussed.
Using a Hybrid Algorithm with Intrusion Detection System based on Hierarchical Deep Learning for Smart Meter Communication Network
Authors: Alghazali Ahmed , Hanoosh Zaid
Published: January 2022

Smart meters are central for renewable electricity generation and distributed integration. Smart metering concerns some intelligent metering devices use at the location of customer as well as processing, reading giving the information regular process on consumption to customer. Smart meters are Advanced Metering Infrastructure crucial element that they suggest two-way communication among the utilities of provider and consumers. Meter data modification could result in financial loss while physical damage to equipment, billing, required energy false prediction and so on. Data disclosing aids for monitoring activities of customer which cause attacks indirectly such as theft and so on. The proposed method is utilizing the new hybrid algorithm ACO-ABC Hybrid based on Swarm that integrates Ant Colony and Artificial Bee Colony (ABC) algorithms features for optimizing hyper-parameters and selection of feature. Algorithm of ACO-ABC is employed for implementing selection of feature and optimization of parameter before Intrusion Detection System based on Hierarchical Deep Learning (HDL). The results which are achieved from system of simulation proves that the proposed IDS based on DL detects attacks accurately. The comparison of proposed system with methods given in base paper and other papers using CICIDS2017 dataset ensures the efficiency of proposed system.
Stress Coping Skills and English Language Attitude of College-Going Students in Chennai
Authors: M. Samuel Finny , P. Dr.Suresh , A.A. Dr.Jayashree Prabakhar
Published: January 2022

Stress and stress coping skills of college students during their learning process are novel topics among the research scholars searching for the psychological reasons behind the problems of adolescents in educational institutions. As adolescents are in an age of transition, stress-related problems are very common among them and their developmental process in cultivating their identity in adjusting to the environment. This paper provides the link between the stress coping skills of college students in their English learning process. This has proved that a moderate correlation exists between stress coping skills and the English learning attitude. The alarming rate of suicides among college students has motivated the researcher to bring out the facts between these two variables. The differences, associations, and relationships between these two variables are statistically proven with gender, community, Location, Residence, etc. The teaching communities, parents, and educators need to understand this fact to help the students cope with their learning process.
Comparative Study of Sentiment Analysis of Type 1 and Type 2 Diabetic Patients Using Apache Flume and Hive
Authors: Singh Harbhajan , Dhir Vijay
Published: January 2022

The Hadoop ecosystem platform has been used to perform sentiment analysis of the opinion regarding type 1 and type 2 diabetes. This research work concentrates on exploring the public opinion about assumptions, thinking and behavior towards the condition of type 1 and type 2 diabetes. Tweets from twitter have been taken as dataset for sentiment analysis for the research. After conducting a set of repetitive experiments, it has been concluded that people feel more negative about type 2 diabetes. They are more pessimistic about the diet and treatment of type 2 diabetes. Present paper is divided mainly into four sections. The first section, gives an overview of the sentiment analysis and diabetes. The proposed work and methodology have been included in the second section. The third section contains the whole experiment work to support the results. In the fourth section, results regarding opinions about type 1 and type 2 diabetes have been illustrated using bar charts obtained from the experiments followed by concluding remarks, future scope and significance of the research.
Decision Making Capability of Management & Its Optimum Effectiveness with Competent Technical Skills in Business Process Management
Authors: Mohamed Sajid Ahmed , D. Dr. Kinslin , R. Dr. Jubi
Published: January 2022

Decision-making is one of the vital roles of competent technical skills that helps in the effective functioning of business management. The development in business strategy has made a way to develop the technical and non-technical skills of both managers and employees. The analysis of the technical and non-technical skills of the manager is essential in the growth of business management. This article aims to analyse the competent technical skills of the managers those aid in taking efficient decisions. The analysed competent skills of managers included technical skills, listening skills, documentation, external support in solving the issues, standard decision, lesson learned, and correct decisions. The data was collected through an online survey from 90 respondents and analysed in SPSS using frequency analysis and factor analysis. The study finds that the manager's competent and technical skill is vital in the decision-making process. The study identified the nine most influential factors that contribute to a manager’s competent and technical skills. Further, the compliance and non-compliance rate on identified factors were explored and interesting results were obtained. The effectiveness of these skills leads to a successful organization.
Distributed Denial of Service Attack Alleviated and Detected by Using Mininet and Software Defined Network
Authors: Al-Mashadani Abdulrahman Khalid Abdullah , Ilyas Muhammad
Published: January 2022

The network security and how to keep it safe from malicious attacks now days is attract huge interest of the developers and cyber security experts (SDN) Software- Defined Network is simple framework for network that allow programmability and monitoring that enable the operators to manage the entire network in a consistent and comprehensive manner also used to detect and alleviate the DDoS attacks the SDN now is the trending of network security evolution there many threats that faces the networks one of them is the distributed Denial of Service (DDoS) because of the architecture weakness in traditional network SDN use new architecture and the point of power in it is the separation of control and data plane the DDoS attack prevent the users from access into resource of the network or make huge delays in the network this paper shows the impact of DDoS attacks on SDN, and how to use SDN applications written in Python and by using OpenFlow protocol to automatically detect and resist attacks with average time to response to the attack between 95-145 second.
Replicated Data Management Using Scaled Segment Chain in Unstable IoT Environments
Authors: Byun Siwoo
Published: January 2022

IoT edge gateway reduces cloud computing's overload that redirect sensor data to remote servers. For reliable and efficient IoT gateway, column-based flash memory has become a reasonable storage due to its space efficiency and compression performance. This paper introduces recent IoT network and edge computing technology. It proposes efficient replication management called Context-mapped Segment Submirroring to support stable data services for sensor data in the edge-based IoT environment. Sensor context scaling and chained segment submirroring schemes are presented to improve the reliability and performance using IoT edge gateway. In the chained submirroring scheme, the sensor data are kept in the space-efficient storage of IoT edge. Consequently, sensor data transmission and mirroring storage cost can be minimized. The simulation results show that the proposed scheme outperforms the traditional scheme in respect of operation throughput and its response time.
Mobile Digital Forensics Framework for Smartphone User Analysis
Authors: Lee Sang Young
Published: January 2022

Blockchain-based digital forensics technology is an efficient way to prevent forgery/modulation of evidence including collecting and analyzing evidential data using the technology in compliance with smartphone forensics procedures after a smartphone is seized. Moreover, the use of large-capacity storage devices and various digital devices have become a realistic solution for its development of IT in situations where the existing digital forensics analysis methods are regarded as limitations. This paper analyzed user’s status on smartphone application and implemented a smartphone user analysis framework that may extract significant digital evidence in a digital forensic way based on a blockchain perspective. In this paper researched a system that may provide important information to digital forensic analysts through these frameworks. It is expected that the proposed system will be expanded by much more structured data and online unstructured data such as SNS reports.
A Study on the Development of Deepfake-Based Deep Learning Algorithm for the Detection of Medical Data Manipulation
Authors: Kim Yong Suk , Song Ho Jung , Han Ju Hyuck
Published: January 2022

In the medical field, the abuse of manipulation data through image processing technology of deep learning is fatal. Therefore, research on detection of modulation on medical images is essential. The data set for fundus data manipulation used 356 right fundus images of 4 lesions (normal, diabetic retinopathy, glaucoma, macular degeneration) out of about 6,000 data collected by Shangong Medical Technology Co., Ltd. The training and verification dataset of the manipulation detection model used original data and U-Net manipulation data. In addition, data manipulated in the Cycle General Adversarial Network (GAN) model were used for the diversity of verification. In this paper, three ophthalmologists and two general doctors were asked to verify the above modulation data. Verification was requested for each lesion, and the verification results were shown through the Receiver operating characteristic (ROC) curve and the Area Under the Curve (AUC). The verification of this study evaluated a total of 100 randomly extracted manipulation data and original data as Observer Performance Test (OPT) for each group. When the evaluation results were digitized as average scores, the scores of ophthalmologists group: 0.72 and general doctors group: 0.67 were recorded. The manipulated images were so similar that both ophthalmologists and general doctors could not find about 30%. However, the manipulation detection model studied in this paper was excellent in about 20% of the group OPT score with a lesion average of 0.913 in the same data group. Therefore, it can be seen that the manipulation detection model of this study finds the manipulated image and the original image well. The future plan is to expand the scope of manipulation detection data to conduct research on various medical data. After that, it will verify its availability at the actual site.
A Network Federation Scheme for Inter-Domain SDN Communications
Authors: Kim Dongkyun , Kim Yong-Hwan
Published: January 2022

Recently, a variety of the integrated service platforms demand the innovative network technologies such as software-defined networking (SDN). However, it is problematic and complicated to provide interconnectivity and reachability between inter-domain SDNs. Thus, this paper proposes a scheme for the inter-SDN federation and communication based on the abstracted network information exchange and automated peer network configuration for the integrated network services. The proposed scheme is implemented and verified over the de-facto wide-area SDN infrastructure (KREONET-S) which is deployed on Korea Research Environment Open Network (KREONET), a representative national research network in Korea. The proposed method is implemented and experimented based on the distributed and layer-2 oriented network architecture by using the abstracted message exchanges between local SDN controllers in order to provide low message overheads and high federation scalability. Our research work contributes to more efficient inter-SDN communications by means of the data modeling abstraction of the local SDN network information and the simplified interactions between individual controllers by the automated configurations through the specific application interfaces. The proposed scheme also contributes to the development of the integrated service platforms which are demanded to provide IoT, Big Data, AI, and cloud services in the tightly coupled manner over the inter-SDN domains.
1-Dimentional Convolutional Neural Network based Heart Rate Estimation Using Photoplethysmogram Signals
Authors: Kim Seong-Hyun , Jeong Eui-Rim
Published: January 2022

Recently, as the importance of healthcare has increased, researches are being conducted to measure health status in real time. Heart Rate (HR) measurement is one of the important health conditions that measure heart beat rates. HR measurement can be performed using Photoplethysmogram (PPG) or Electrocardiogram (ECG) signals. Since the PPG or ECG signals are different from people to people, conventional HR estimator occasionally results in large errors. To develop a reliable HR estimator, an HR estimation technique using PPG is proposed in this paper, based on a deep learning technique. The proposed HR estimation technique has the following key features. We develop a new artificial neural network which is 1-Dimensional Convolutional Neural Network (1D-CNN) composed of ten convolutional layers and two fully connected layers. To assess the estimation performance, cross validation is used. The training and verification of the proposed 1D-CNN technique are performed on Python 3.7.5 with Keras 2.0 library. The proposed HR estimation technique performs training and verification using field PPG data. Overfitting is prevented by increasing the limited training data by data augmentation. In training, the loss function is the Mean Square Error (MSE), which is commonly used in regression problems. In the verification, the error between the predicted HR and the actual HR is compared using Mean Absolute Error (MAE). As a result of the final performance verification through cross validation, the proposed technique shows an MAE of 1.23 Beats Per Minute (BPM). This results indicate that the proposed technique enables quick and accurate HR estimation with only PPG signals. Therefore, if this technique is applied to medical and wearable devices, the proposed technique can replace the existing HR monitors.
Evaluating the Effectiveness of e-Learning Students of the College of Nursing
Authors: Shihab Luay Abdulwahid , Kareem Afkar Fadhil , Abbas Shahd Atheer , Hussein Shahd Abdul Amir
Published: January 2022

A descriptive study Evaluating the Effectiveness of e-Learning students of the College of Nursing Governorate, 6/1/2021 to 23/6/2021. Face-to-face classes have been canceled and moved online, bringing about the rise of online learning that has allowed learners to continue their education. The sudden transition from face-to-face to online learning has, however, posed numerous challenges for students, teachers, administrators, and education leaders. E- Learning can be viewed as computer assisted learning, and as pedagogy for student centered and collaborative learning. Early developments in e-learning focused on computer assisted learning, where part or all of the learning content is delivered digitally. More recently the pedagogical dimension of e learning has become prominent. E-learning comprises all forms of electronically supported learning and teaching.
Motivational Quotes from Teacher Junior High School in Indonesia during Online Learning
Authors: Sholihah Imro’atus , . Dawud , . Suparno , Hadi Nur
Published: January 2022

Covid 19 has an impact on the implementation of traditional-based learning. Pavlo v and Albert Bandura's traditional Behavioristic learning was directly impacted. This study was to take data triangulation between teachers, students, and the achievement of meaning using the Lyn Richard qualification model classification. Found decline delivery the meaning of the words motivation of teachers to students segmented new students, active students, and students who before end study. There is consistently a decrease in teacher focus which can be analyzed from the delivery of meaning as much as 37.9%. For the time during online learning to be efficient, this traditional Behavioristic learning model must be revised immediately.
Evaluation of COVID-19 Cases based on Classification Algorithms in Machine Learning
Authors: Atiyah Oqbah Salim , Thalij Saadi Hamad
Published: January 2022

COVID-19 has appeared in china, spread rapidly the world wide and caused with many injuries, deaths between humans. It is possible to avoid the spread of the disease or reduce its spread with the machine learning and the diagnostic techniques, where the use classification algorithms are one of the fundamental issues for prediction and decision-making to help of the early detection, diagnose COVID-19 cases and identify dangerous cases that need admit Intensive Care Unit to provide treatment in a timely manner. In this paper, we use the machine learning algorithms to classify the COVID-19 cases, the dataset got from dataset search on google and used four algorithms, as (Logistic Regression, Naive Bayes, Random Forest, Stochastic Gradient Descent), the result of algorithms accuracy was 94.82%, 96.57%, 98.37%, 99.61% respectively and the execution time of each algorithm were 0.7s, 0.04s, 0.20s,0.02s respectively, and with the mislabeling Stochastic Gradient Descent algorithm was better.
Red Monkey Optimization and Genetic Algorithm to Solving Berth Allocation Problems
Authors: Hameed Musa Abdullah , Abed Woud M. , Mohammed Raghad K. , Yousaf Mohamed
Published: January 2022

In the past two decades, maritime transport traffic has increased, especially in the case of container flow. The BAP (Berth Allocation Problem) (BAP) is a main problem to optimize the port terminals. The current manuscript explains the DBAP problems in a typical arrangement that varies from the conventional separate design station, where each berth can simultaneously accommodate several ships when their entire length is less or equal to length. Be a pier, serve. This problem was then solved by crossing the Red Colobuses Monkey Optimization (RCM) with the Genetic Algorithm (GA). In conclusion, the comparison and the computational experiments are approached to demonstrate the effectiveness of the proposed method contrasted with other methods that were existing in the other studies. The capacity of the container in terminal was also discussed in the current based on the diverse scenarios that possibly will occur.
ICT Effects and Enhancing Risk Management Information System (RMIS) in Medical Sector in Vietnam
Authors: Le Kien
Published: January 2022

Measuring risk in medical sector in order to propose recommendation s is among concerns of scientists in recent years. In specific, using quantitative and analytical methods, author analyze ICT effects and IT applications in medical sector an hospitals, as well as analyze risk information to propose solutions to enhance risk management information system for Vietnam medical sector. Research findings show us that in order to give suitable suggestions for policy implications, firstly, study recognized that lower risks shown by beta values (< 1) among 57% of listed firms with lower risk. Last but not least, study stated that technology applications in medical sector can help doctors and nurses to manage, store and access better data and documents of patients. And Vietnam hospitals need to enhance more Risk management information system with strong support from IT (information technology) so that we could constantly improve service quality patient services, as well as build a favorable working environment for staff both professionally and professionally, etc.
Application of Theory of Reasoned Action (TRA) to Explain Continued Intention to Adopt (CIA) MHealth Services
Authors: Asvinigita Luh Rai Maduretno , Piartrini Putu Saroyini , Suprapti Ni Wayan Sri , K I Gusti Ngurah Jaya Agung Widagda
Published: January 2022

MHealth is a digital healthcare technology with big data adoption. Identification of the factors that encourage consumers CIA mHealth application needs to be considered. The study aimed to describe influence of service quality perception (SQP), perceived vulnerability (PV), TRA toward CIA mHealth. Sampling was done online using an e-questionnaire and analyzed with PLS (partial Least Square) using SEM. A total of 429 respondents were involved, and 170 of them were met the inclusion criteria. The existent result implies that SQP and attitude significantly affect CIA. Meanwhile, PV and subjective norm (SN) not significantly influence the CIA. Effects of attitudes were able to partially mediate SQP and CIA. On the other hand, attitude cannot mediate perceived vulnerability and CIA. Empirical substation was expected to provide future analysis about CIA. Furthermore, improvements of service quality would induce the frequent use of mHealth application.
Efficient Eye Recognition for Secure Systems Using Convolutional Neural Network
Authors: Abbass Ahmed Abdulrudah , Hussein Hussein Lafta , Shukur Wisam Abed , Kaabi Jasim , Tornai Robert
Published: January 2022

Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The main aim of this paper is innovation in eye recognition phase. In this paper, a new and fast method is proposed for human eye recognition that can quickly specify the human eye location in an input image. In the proposed method, eyes will be specified in an input image with a CNN neural network. This proposed method is tested on different images and provided highest accuracy for the image recognition which used in security systems.
Factors Affecting Personal Branding in Accounting
Authors: Moradi Dr. Majid
Published: January 2022

Personal branding is an investment in personal professional development in a world where marketing can increasingly determine the fate of businesses and jobs more than ever. To have the desired personal brand, people should learn various characteristics through the acquisition of knowledge, skills, and experiences and apply them. Without professional, human, and perceptual skills, people cannot develop their personal brand domain. Branding is an approach for gaining power, differentiating between competitors, and maintaining customer loyalty. In today's environment, having a professional reputation or brand is considered a very important asset. A personal brand is something that saves people from professional anonymity and exposes them in a particular circle for a specific reason. Personal branding is broader than corporate (organizational) branding, which is influenced by complex factors and conditions and is not just a professional marketing process. Accounting is one of the most organized and disciplined professions in the world. Due to the type and nature of the services it provides, it has a special reputation and trustfulness. Since accounting and auditing firms are among small and medium-sized companies, they are very much influenced by their founders and partners, and the role of branding in these firms is very important. Companies need a well-known and trustable person to do their accounting affairs (in fact, such a person can be an accounting brand) so that they can trust him/her with ease; so, the factors that affect accountants' personal branding are presented here to determine what can be done and how to turn accountants into strong brand staffs in the professional and practical field to solve the problems of companies in choosing strong accountants or financial managers. Companies need professional accountants for staying in the survival triangle. Accountants can also create a competitive advantage for themselves and outperform their counterparts by developing their own brand. In this article, the factors affecting branding in accounting are presented in a model.
An Efficient Hybrid Classifier for Prognosing Cardiac Disease
Authors: Sharma Richa , Singh Shailendra Narayan
Published: January 2022

Machine learning (ML) is a powerful tool which empowers the practitioners for predictions upon any existing or real- time data. Here, the Machine first understands the valuable patterns from the dataset and then uses that information to make predictions on the unknown data. Further, classification is the commonly used machine learning approach (ML-Approach) to make such predictions. The objective of this work aims to design and development of an ensemble classifier for prognosing cardiovascular disease (heart disease). The developed classifier integrates Support Vector Machine (SVM), K–Nearest Neighbor (K-NN), and Weighted K-NN. The applicability of ensemble classifier is evaluated on the Cleveland Heart disease dataset. Some other classifiers such as Logistic Regression (LR), Sequential Minimal Optimization (SMO), K-NN+Weighted K-NN are also implemented on the same dataset to make the performance analysis. The results of this study depict the significant improvement in the Sensitivity and Specificity parameter.
A Proposed Technique for Gray Image Colorization
Authors: Edan Salam Jabbar , Rasoul Maryam Nadhim , Aljarrah Amir A.
Published: January 2022

The colorization of the gray-scale image is the process of using color image (has a similar "mood") to add color to a grayscale image. In this paper, we proposed new approach for colorization gray-scale images depending on Singular Value Decomposition (SVD). We used SVD to add color to a grayscale image by determining the best pixel value in the reference image, based on comparing the first column values from the left singular vector matrix of 3x3 block and the pixel value in the center of block of the gray image with other corresponding values in the reference image. Finally, use the best match to transfer color from color image to gray-scale image. The results of the proposed colorization approach are good and plausible.
The Challenges of Applying the International Financial Reporting Standard (IFRS9) and its Impact on Bank Credit Strategies
Authors: L. Dr. Awatef Globe Mohsen
Published: January 2022

The application of the International Financial Reporting Standard (IFRS9) represents a major challenge for the banking sector in the areas of granting credit and financing, as the study dealt with a presentation of the standard (IFRS9) and the requirements for classification and measurement of obligations, in addition to focusing on the differences between it and the international standard (IAS39), and the study also focused on challenges facing the application of the standard on the banking sector and its impact on credit strategies through the study of expected credit losses Expected Credit Losses (ECL), as recognizing these losses is one of the problems that lead to financial crises that are reflected in the economy in general (Mahgoub et al., 2017), as the delay in recognizing expected losses from credit and waiting until they actually occur leads to an exacerbation of the crises that the banking sector may be exposed to, and the study reached a set of results, the most important of which are: The banking sector needs to review strategies related to transparency and disclosure of weak credit In a manner that requires the application of accounting methods to prove credit losses in the financial statements by updating the methods of accounting measurement and presentation according to the classification of financial assets. Which were identified by the international standard (IFRS9) in addition to some recommendations made by the study.
2019 Election Campaign Model in Indonesia Using Social Media
Authors: Widayat Rossi Maunofa , Nurmandi Achmad , Rosilawati Yeni , Qodir Zuly , Usman Sunyoto , Baharuddin Tawakkal
Published: January 2022

The presence of social media platforms, especially Twitter, in Indonesia since the 2014 and 2019 elections have been used as a campaign media used by political parties to change conventional campaign strategies into virtual campaigns that are more informative, interactive, and participatory. This paper will analyze Twitter social media used by political parties, including @PDI_Perjuangan, @Gerindra, @DPP_PPP, @PKSejahtera during the campaign from January to April in the 2019 General Election, with analysis tools using Nvivo 12Plus. Using big data analysis from the Twitter of political parties, we found several things: first, the various news posted during the campaign with the amount and intensity of the news and becoming a trending topic will affect the number of followers owned by political parties, the more often political parties post news it will affect voter segmentation, the number of likes for the message content, the number of followers, and the number of retweets. Second, the popularity of public figures can also be a measure of the success of the campaign strategy made through the news on Twitter social media. Third, the 2019 election campaign produced an effective campaign model when compared to previous campaigns on social media.
Analysis or Design of Composite Column by Using Etabs Software
Authors: Abbas Dr. Hajer Satih , Kharnoob Dr. Majid M. , Atia Dr. Noor Salim , Bassam Dr. Bassam Farman
Published: January 2022

As the world business enlarging day by day, and designing of the buildings are getting complex and demanding more technology to enhance its stability, performances, cost, duration and its uniqueness of designing. At the later part of development in civil engineer majority of the work was transformed from conventional system to a well organized and computerized system, most of the time the company employees and owners were in live risk, due to non availability of technology. As time goes technology develops, having this in mind we had also suggested using Etabs software in our design. Etabs is a 3D analysis and designing of the buildings, it is engineering software which is used in construction and designing or analysis of complex multi stored buildings. Composite column is actually the amalgamation of two traditionally methodologies structure steel and structure concrete, their design could be based on concrete or steel methodology. Any method can be used to develop composite column approach. Composite columns are designed by applying different components of structure steel and concrete in according to use the advantages and property of each material. The outer and inner behavior of the concrete and structural steel ingredients make the Composite column is very unbending, enough squashy, cost effective and generally makes it efficient partner of the building and bride constructions. Normally three kinds of composite column sections are using in high risky building construction. The building was analyzed by using Etabs and designed according to the needed requirement. Composite column technology for construction of building is now a day’s very popular and has more advantages over the conventional designing of buildings, currently we see tall buildings with great advantages such as less space more accommodation, parking, and many more, these all can only be achieved if we implement the concept and idea of composite construction. This is why composite construction is so good; the one line reason behind this is that it combines both steel and concrete into one unit. By combining these materials can strengthen and provide best result in extremely enough and light weight design. Composite by column can also save our time and we can construction the complex buildings in short term. One of the biggest achievement if is done in construction by composite column is the cost reduction, because most of the constructions companies are being lost and dropped its position due to non profitability.
Enhanced Edge Detection Technique in Digital Images Using Optimised Fuzzy Operation
Authors: Ranjan Rakesh , Avasthi Dr. Vinay
Published: January 2022

In image processing, edge detection is a critical issue. Edge detection is a key approach for evaluating the edge of various objects in a digital image. These edges are found using the gradients, which are present in the image. The intensity and value of pixels determine the gradients. In digital images, edge detection lowers the quantity of data and filters out irrelevant data while maintaining the image's key structural features. In this paper, a new edge detection approach based on a fuzzy rule-based system is proposed. In digital image processing, the proposed method typically depends on fuzzy logic systems. The main goal of this system is to show how fuzzy logic may be used in image processing. This paper provides a fuzzy logic-based edge detection technique that uses a sharpening Gabor filter to regulate edge quality and a Gaussian filter to reduce noise caused by sharpening. This is determined by utilizing applications such as “Peak Signal to Noise Ratio (PSNR) F-Measure, and Hausdorff distance (HoD) to prove that fuzzy logic outperforms the proposed system. The findings for edge detection approaches are included in high quality. The proposed approach outperforms most commonly used traditional edge detection methods. The proposed method also reduces the number of noisy features and may be used for a wide range of images.
Multi Criteria-based Decision Making of Affiliative Orchestration Capability of Balinese Tourism Management
Authors: I Ketut Santra , I Wayan Sukarta , Sumetri Ni Wayan
Published: January 2022

The study analyzes what tasks are carried out and how the tourism village manager harmonizes the differences in interests between stakeholders in the tourist village. This research was conducted by examining the practice of governance competencies carried out by tourism village managers in Bali by conceptualizing Affiliative Orchestration Capability (AOC). By using multiple criteria of stakeholders as the basis for decision making, this study formulates a set of competency models for tourism village managers. The results underline the importance of affiliative orchestration ability as a set of competencies for tourism village managers who are able to harmonize all stakeholder interests in Bali. Stakeholder decision making shows that tourism village managers who practice affiliative orchestration skills tend to be better able to manage tourist villages that meet the criteria for sustainable tourism villages.
Sign Language Converter Using Feature Extractor and PoseNet
Authors: M.N. Pushpalatha , A. Parkavi , R.S. Sachin , Vadakkan Amy S , Khateeb Aakifha , K.P Deeksha
Published: January 2022

Human beings commune with each other to convey thoughts, expressions, experiences and so on to the people around them. But this case is not the same when it comes to the deaf and mute people. Sign language paves the way for people with such difficulties to communicate with one another. The aim of this paper is to facilitate easy and accurate communication between people who have hearing and speaking disabilities, and those who do not. This paper shows how the communication gap can be bridged using sign language to text and audio converter with the help of Feature Extractor and Posenet with an accuracy of 92%. A webcam is used to capture the sign language shown by a person. Posenet with Artificial Neural Network is used to classify essential words used in day to day life. Various parts of the body are tracked by the webcam and then converted to text and audio to convey what the person is trying to express in real time.
Review of Cyber Attack Detection: Honeypot System
Authors: M.R. Amal , P. Venkadesh
Published: January 2022

The number of connected devices in the network is growing day by day, and as the number of linked devices grows, so will the number of cyberattacks. All devices connected to the Internet has become a target of cyberattacks as network attack methods have developed. As a result, the security of network data cannot be neglected. To handle the future threats in this way, we employ honeypots, which are conceptual framework traps designed to block unauthorized access to both PCs and data. Every day, a large number of people access the internet throughout the world. Honeypot, also known as Intrusion Detection Technology, is a type of security technology that screens devices to prevent unwanted activities. This article will provide an overview of cyber security as well as a discussion of machine learning, cyber threats, and honeypot system-based techniques. This review paper was the result of a lot of research, and in assessing honeypots, the researchers found that they are becoming more of a concern for experts as an important security tool that can halt or limit system attacks and provide analysts with insights into the origins and behaviours of such attacks.
Absolute magnitudes of white dwarfs and discovery of new white dwarfs from FBS Blue Stellar Objects by means of Gaia EDR3 data
Authors: Mickaelian Areg M. , Mikayelyan Gor A. , Abrahamyan Hayk V. , Paronyan Gurgen M. , Malkov Oleg Yu.
Published: January 2022

This article is a presentation of a project which is a statistical study of white dwarfs’ properties carried out based on the sample of the First Byurakan Survey Blue Stellar Objects (FBS BSOs) and the Catalogue of White Dwarfs. Using these results, we have searched and will continue to search for new white dwarfs by means of Gaia accurate astrometry. The discovery and study of new White Dwarfs (WDs) is extremely important for understanding the kinematics and dynamics of the local stellar population. They are evolutionary signatures of the Milky Way, as most of stars pass through this evolutionary stage. We have carried out a statistical analysis of the White Dwarfs Catalogue to establish their average physical properties. Based on these data, we have searched for new WDs using Gaia EDR3 accurate astrometry. It provides huge amount of data to confirm WDs and reveal many more such objects. Gaia’s astrometric accuracy allows more detailed studies of WDs and many other stars. Using Gaia accurate data in combination with SDSS and DFBS low-dispersion spectra and additional multiwavelength data, we have revealed many new WDs. Many of them are subject for studies on binarity and variability (including a number of subtypes, e.g. ZZ Ceti stars (pulsating WDs), cataclysmic variables, etc.). WDs among FBS blue stellar objects at high galactic latitudes have been searched and revealed. Search for high galactic latitude WDs in DFBS have also been carried out. Using the revealed and calculated characteristics, a statistical study of WD properties is being done.
Probing the rotation rate of solar active regions: the comparison of methods
Authors: Kutsenko Alexander S. , Abramenko Valentina I.
Published: January 2022

Sunspot groups are often used as tracers to probe the differential rotation of the Sun. However, the results on the rotation rate variation obtained by different authors are not always in agreement. The reason for this might be a number of effects. In particular, faster decay of the following part of a sunspot group results in a false apparent shift of the area-weighted center of the group toward the leading part. In this work we analyze how significantly this effect may contribute to the derived rotation rate. For a set of 670 active regions, we compare the rotation rate derived from continuum intensity images to that derived from line-of-sight magnetograms. We found that the difference between the calculated rotation rates is 0.45° day−1 on average. This value is comparable to the difference between the rotation rate of the solar surface near the equator and at 30° latitude. We conclude that the accuracy of the rotation rate measurements using white-light images is not satisfactory. Magnetograms should be used in future research on the differential rotation of the Sun.
Mixed convection around a circular cylinder in a buoyancy-assisting flow
Authors: Majdi Hasan Shakir , Mashkour Mahmoud A. , Habeeb Laith Jaafer , Ilic Marko
Published: January 2022

In this paper, the effect of mixed convection on the flow behavior and heat transfer around a circular cylinder disclosed to a vertically upward laminar air stream is numerically examine. The buoyancy-aided flow is utilized to eliminate and control the vortex shedding of the cylinder. The influence of the Grashof number, 0 ≤ Gr ≤ 6000, the flow and thermal patterns, as well as the local and mean Nusselt number, is investigated at a constant Reynolds number of 100. The unsteady Navier-Stokes’s equations are solved employing a finite-volume method to simulate numerically the velocity and temperature fields in time and space. The results showed periodic instability in the flow and thermal fields for a range of Grashof number Gr ≤ 1300. Also, there is critical value of Grashof number for stopping this instability and the vortex shedding formed behind the cylinder, by the effect of heating. Thus, by increasing Grashof number between 1400 ≤ Gr ≤ 4000, the periodic flow vanishes and converts into steady flow with twin eddies attached to the cylinder from the back. Furthermore, as Grashof number increases behind Gr ≥ 5000, the flow becomes completely attached to the cylinder surface without any separation.
Necessary and sufficient conditions of optimality for second order discrete and differential inequalities
Authors: Mahmudov Elimhan N. , Demir Sağlam Sevilay
Published: January 2022

The present paper studies the optimization of the Bolza problem with a system of convex and nonconvex, discrete and differential state variable second-order inequality constraints by deriving necessary and sufficient conditions of optimality. The problem with a system of discrete-approximation inequalities is investigated using the proposed method of discretization and equivalence theorems for subdifferential inclusions, which greatly contributes to the derivation of adjoint discrete inclusions generated by a given system of nonlinear inequality constraints. Furthermore, we formulate sufficient conditions of optimality for the continuous problem by passing to the case of limit. A numerical example is provided to illustrate the theoretical approach’s effectiveness.
Photochemical protein modification in complex biological environments: recent advances and considerations for future chemical methods development
Authors: Taylor Michael T.
Published: January 2022

The development of organic reactions that covalently modify biological matter in complex biological mixtures has become an invaluable asset in drug discovery. Out of the techniques developed to date, optically controlled chemistries are of particular utility owing to both the spatiotemporal control afforded by optical control as well as the impressive array of transformations that are driven by the highly reactive intermediates generated upon excitation. This minireview discusses recent advances in the development of photochemical reactions for use in complex mixtures and highlights key considerations for future photochemical reaction designs.