bluuebunny/crossref_metadata_2025 huggingface dataset:
A Technology-Based Intervention to Help Health Care Provider Parents Manage Stress During the COVID-19 Pandemic: Findings From a Pilot Microrandomized Trial (Preprint)
Authors: Lee Sun-Kyung , Cai Qiyue , Basha Sydni , Gupta Aditi , Gewirtz Abigail
Published: June 2022

BACKGROUND

The COVID-19 pandemic has increased the stress levels of parents, especially health care workers and other COVID-19 frontline workers. Nonetheless, little is known about stress management for this population.

OBJECTIVE

This pilot study tested the impact of a mobile app apt.mind in reducing stress in health care provider parents by delivering a 30-day microrandomized intervention.

METHODS

Participants included 102 parents who work in health care and their coparenting partners. They were given smartwatches and access to a mindfulness app. Each day, all parents were randomly assigned to (1) brief stress reduction messages, (2) meditation audio activities via the app, or (3) no intervention. Stress was evaluated using a self-reported COVID-19 Family Stressor Screener (10 items; 5-point Likert scale) to rate levels of stress regarding food security, job stability, family conflict, mental health, and social isolation. Dosage was measured by the percentage of parents who received any of the activities (app or messages; mean 66%, SD 9.8%), and parents were divided into 3 groups by dosage level: low (below 60%), middle (61%-70%), and high (above 71%).

RESULTS

Using a pre-post test, this study assessed changes in mental health symptoms and parenting by individuals’ dosage levels. Participants who received high levels of intervention reported significant decreases in COVID-19–related family stress (t=–2.50; P=.02) and a significant increase in parenting efficacy (t=2.39; P=.03), while those who received low or middle levels of the intervention did not show those changes.

CONCLUSIONS

This study supports the feasibility and efficacy of technology-based tools to reduce stress and the need to examine just-in-time interventions. Future studies can improve by focusing on microchanges in the parents’ stress level on a daily basis and including physiological data such as heart rate variability to include objective stress data.
The Importance of the ESG Factors and Their Potential Impact on an Audit of a Financial Statement
Authors: Indyk PhD, FCCA Magdalena
Published: June 2022

This review paper aims to determine the potential impact of Environmental, Social, and Corporate Governance (ESG) factors on an audit of a financial statement. For this reason, a triangle of implications has been proposed, i.e., for: (1) audit clients whose business activity is reflected in a financial statement; (2) a financial statement; and (3) audit firms which perform an audit. The evidence represents a collection of a) scientific articles, b) publications offered by professional accounting bodies and consulting firms, and c) relevant standards and legal regulations. The paper finds that ESG has become a factor which must be considered, and the financial world will face multiple changes. For audit clients, the critical aspect will be ESG integration with a business model. Financial reporting will evolve under Exposure Drafts IFRS S1 and IFRS S2. A financial statement will require in-depth knowledge about existing accounting standards to reflect the financial implications of ESG-related products and transactions. Moreover, there is a distinction between “financial audit” and “ESG assurance” in audit and assurance services. However, some ESG-related risks and matters may be considered in the financial audit cycle. The paper’s findings are significant from the scientific research perspective as only a few studies contribute to ESG and auditing. The article also provides some practical implications that might be important for audit clients, firms, and regulators.
Macromolecular crowding enhances fibrillin-1 deposition in the extracellular matrix
Authors:   Department of Orthopaedics, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, USA, Satz-Jacobowitz B , Taye N , Karoulias SZ , Hubmacher D
Published: June 2022

Biochemical and biophysical factors need consideration when modelling in vivo cellular behaviour using in vitro cell culture systems. One underappreciated factor is the high concentration of macromolecules present in vivo, which is typically not simulated under standard cell culture conditions. This disparity is especially relevant when studying biochemical processes that govern extracellular matrix (ECM) deposition, which may be altered due to dilution of secreted macromolecules by the relatively large volumes of culture medium required for cell maintenance in vitro. Macromolecular crowding (MMC) utilises the addition of inert macromolecules to cell culture medium to mimic such high concentration environments found in vivo. The present study induced MMC using the sucrose polymer Ficoll and examined whether fibrillin-1 deposition by human lung fibroblasts could be augmented. Fibrillin-1 forms extracellular microfibrils, which are versatile scaffolds required for elastic fibre formation, deposition of other ECM proteins and growth factor regulation. Pathogenic variants in the fibrillin-1 gene (FBN1) cause Marfan syndrome, where ECM deposition of fibrillin-1 can be compromised. Using immunocytochemistry, significantly enhanced fibrillin-1 deposition was observed when lung fibroblasts were cultured under MMC conditions. MMC also augmented fibrillin-1 deposition in Marfan syndrome patient-derived skin fibroblasts in a cell line- and likely FBN1 variant-specific manner. The ability of MMC to increase fibrillin-1 deposition suggested potential applications for tissue-engineering approaches, e.g. to generate tendon or vascular tissues, where fibrillin-1 microfibrils and elastic fibres are key determinants of their biomechanical properties. Moreover, it suggested the potency of MMC to better mimic in vivo ECM environments in cell culture studies.
Super Predictor of Indian Premier League (IPL) using Various ML techniques with help of IBM Cloud
Authors: Reddy K Rushikesh , A Prem Sai , V Chandrakanth , Reddy Shiva Sumanth
Published: June 2022

Abstract: Indian Premier League matches are one in every of the foremost important events in India. it's professional cricket league in India contested by eight teams representing the various cities in India. The paper focuses on the performance analysis of the eight contesting IPL teams supported the runs of the team, wickets, decisions usurping winning the toss and Duckworth Lewis rule analysis. The IPL data from 2008 to 2019 is used for the player analysis. The team performances are visualized graphically using data analytics to render the interpretation in an exceedingly good manner. The performance data using visual analytics helps in selecting players for future matches and provides additional information on player yet as team profiles. Almost every IPL team’s Management use Analytics for better games. Not only team’s owners, there are several betting and fantasy cricket platform, which are highly rely upon analytics for his or her success. Analytics can help all of them for his or her success. The research paper tries to predict the IPL matches using machine learning models with variables like match id, inning, batting team, bowling team, over, ball, batsman, non-striker, bowler is super over, wide runs, bye runs, leg by runs, bowling runs, penalty runs, batsman runs, extra runs, total runs, player dismissed, dismissal kind fielder. to appear out the result it uses different machine learning models like statistical method model, Random Forest. The results of the study shows that for IPL game, Teams, Venue, Winning Toss, Venue of the Match and Decision after winning the toss are important influencers to win a match. Different Machine Learning helps to predict outcome of a match. Right selection of Machine Learning Model helps to extend Accuracy of Prediction. From Different Classification Models, Support Vector Machine, Decision Tree and Random Forest are best to predict outcome of an IPL games. All of the subsequent gives almost 88% accuracy Level. The study has been conducted from data of Kaggle. Secondary data has been used for the analysis.
Career Recommendation using ANN
Authors: Padmaja S
Published: June 2022

Abstract: There is a pattern among understudies to, for the most part, settle on professional ways in light of their colleagues' choices or, on the other hand, the most significant compensation-paying jobs.They neglect to know their assets and pick their careers randomly, leading to frustration and demoralization. Moreover, while recruiting thecandidates, recruiters need to assess them in all different aspects. Consequently, there is a requirement for a framework that helps students decide on a job role best suited for them based on/her skillset and other evaluation metrics, which is now possible due to advancements in deep learning. This project proposes an automated system using an Artificial Neural Network, which considers the individual's personality traits and personal interests, and academics to predict which computer science job role would be best suited for them.
Product Anti-Counterfeiting Using Blockchain
Authors: C Kiruthika
Published: June 2022

Abstract: Fake Products is a serious issue, as in today’s world we can’t really distinguish between real and fake product. And some people make these fake products just to make some profit without thinking about its impact on user and also affects company’s name, profit and sales. Blockchain technology can be used to detect whether the product is real or fake and assure user about the authenticity of the product. Blockchain technology is the technology where information is stored in the form of blocks in many databases which is connected with the chains and it doesn’t require any third-party users for permission. We can use QR code or an encrypted unique codewhich is a very efficient technique to detect fake product. When the QR code is scanned or theunique code is entered, it will redirect us to the blockchain containing the information of the product and provides us the details of the manufacturer and information of owner to make decision easy for buyer if they are looking to buy the product.
Experimental Investigations on Mechanical Properties of Ricestraw Fiber Reinforced With Polypropylene Matrix Composites
Authors: Raju Kommineedi Ammi , Kodi Sudhakar , Veerendra Palukuri
Published: June 2022

Abstract: The main objective of present work is to investigate the mechanical properties of rice straw fibre reinforced polypropylene composites at different weight fractions (0%, 5%, 10%, 15%, 20% and 25%) of rice straw fibre. Rice straw fibre reinforced polypropylene composites were manufactured according to ASTM standards using injection moulding technique. The developed composites were then tested for their tensile, bending and impact properties. The standard test methods ASTM-D638M for tensile properties, ASTM-D790M for flexural properties and ASTM-D256M for impact properties of rice straw fibre composites, were used.
Steering Controlled Adaptive Headlamps
Authors: Gupta Pawan Kumar , Tailor Naman , Jhamb Sandeep
Published: June 2022

Abstract: The intention is to layout and increase a “Steering Controlled Headlight Mechanism”. This is performed with the aid of using connecting headlights and steerage. Present day cars don`t have powerful lighting fixtures machine. Due to this many injuries are taking area throughout night time instances in particular in mountain sections. The injuries may be prevented with the aid of using incorporating Steering Control Headlight Mechanism. Therefore, the present invention relates to an automobile headlight, more specifically, an automobile headlight direction changing device. This allows the direction to change in synchronization with the rotation of the steering, thus improving safety at night or while driving. darkness. This project implemented the same requirements. Headlight rotation related to steering rotation with a rack and pinion mechanism.
Online Land Registration Using Blockchain
Authors: Anand Panthukala Chetan
Published: June 2022

Abstract: If a person wishes to make purchases properties, an intermediary known as a dealer (as in India's old Land Administration system) would help facilitate the transaction by creating and compiling all the necessary physical papers to support a settlement as proof of ownership. A recognized federal department will document the property, and all its qualities will be recorded in a book by the broker before the contract is made. Files may be lost or tampered with in this situation since anybody who has access can access or edit the papers, and that in turn compromises this physical evidence of land ownership. Our suggested smart contract-based solution, on the other hand, is more efficient in terms of time and security, as well as synchronized and less susceptible to distortion or fraud over the course of completing a purchase or asset management process. As a result of a thorough examination of something like the traditional land application procedure, as well as an evaluation of Blockchain's leadership and integrity repair work, as well as the virtualization factor, we have proposed a solution using Blockchain technology.
CKD Stage Prediction and Suitable Diet Recommendation: A Survey
Authors: D L Prof. Girijamba , N Kavita , Samanvitha N , Patil Rohit , C Aishwarya Gowda
Published: June 2022

Abstract: Chronic kidney disease is one of the world's most complicated illnesses. Renal failure occurs when the kidneys have been afflicted for a long time. Filtration of waste and surplus fluid from the blood is the job of the kidneys. Because waste builds up as kidneys fail, early detection of chronic renal disease and proper treatment are critical in today's medical industry. On the subject of chronic renal disease prediction, there are numerous research studies available. Kidney disease prediction employs a variety of effective approaches and algorithms. A large number of research publications apply data science techniques for renal disease prediction, with promising outcomes. Some studies gathered training datasets from hospitals, which were then trained using efficient machine learning algorithms, yielding positive results. One of the most difficult challenges in the present medical field is identifying this complex kidney illness. Doctors have a difficult time manually identifying the condition. ML algorithms have been used in research to generate appropriate models, and the best model is evaluated to provide better outcomes. Keywords: CKD, Naïve Bayes, Support Vector Machine, Logistic Regression, KNN, CNN
Footstep Power Generation System
Authors: Khandelwal Gaurav Kumar
Published: June 2022

Abstract: We require energy for our day-to-day activities. There are numerous traditional energy-producing methods, but they are rapidly decreasing, thus a non-conventional energy system is critical to our nation at this time. The purpose of this study is to demonstrate how individuals may generate electricity by walking on the floor. Piezoelectricity is recommended as an alternative energy source in this research. The goal is to discover a pollution-free energy source as well as to use and maximize the energy that is now being squandered. A piezoelectric transducer is the type of transducer used to detect vibrations. The mechanical energy is converted into electrical energy by this transducer. When the pressure from a footstep is delivered to a piezoelectric transducer, the pressure or force is converted into electrical energy. A series-parallel connection is used to connect the piezoelectric transducer. It is then put on a wooden tile as a model for a footstep tile to apply pressure to the piezoelectric transducers. This tile may be used in a congested location, on a walking path, or workout equipment. Low-power appliances can be powered by the electric energy generated by this piezoelectric tile.
Quality Analysis and Classification of Rice using Image processing
Authors: Udhay Chityala
Published: June 2022

Abstract: Grain quality analysis is a huge challenge in agricultural industries. Internal control is critical in the food industry because food products are characterized and rated into various categories after quality data has been collected. Grain quality assessment is performed by hand, but the results are subjective, lengthy, and pricey. To overcome the limitations and drawbacks of image processing techniques, different resolutions are used for grain quality analysis. Using image processing techniques, this paper proposes a method for grading and analyzing rice based on grain size and form. An edge detection algorithmic software is used in particular to determine the area of each grain's borders. we discover the endpoints of each grain using this technique, and we can then live the grain's endpoints using caliper.
Features of the Course and Measures for the Correction of Thrombocytopathy in Adolescents
Authors: Makhmatovich Abdiev Kattabek
Published: June 2022

Abstract: This paper discusses features of the course and measures for the correction of thrombocytopathy in adolescents. Thrombocytopathy is a chronic disorder of normal hemostasis, in which the number of formed cells (platelets) remains at an acceptable level, but their functionality decreases significantly, which leads to a catastrophe on the part of the entire hematopoietic system
XGB-Hybrid Fingerprint Classification Model for Virtual Screening of Meningitis Drug Compounds Candidate
Authors: AlFaroby Mohammad Hamim Zajuli , Fadhilah Helisyah Nur , Amiroch Siti , Hidayat Rahmat Sigit
Published: June 2022

Meningitis is an infection of the lining of the brain caused by diffuse inflammation, and this condition is caused by viruses or bacteria that cause Meningitis. Prevention for this disease is still in the form of strengthening antibodies with vaccines. There is no significant compound to relieve or treat Meningitis patients. In previous studies, they got seven proteins vital to Meningitis. We continued to investigate the compounds associated with the seven proteins. We chose the in-silico process by utilizing data in an open database. We use several databases for the data collection process. After that, the compound data were extracted for bonding features and chemical elements using molecular fingerprints. We use two fingerprint methods, where both we combine with three types of combinations. The combined results produce three types of datasets with different matrix sizes. We establish the Extreme Gradient Boosting (XGB) method to form the classification model for the three datasets, select the best classification model, and compare it with other classification algorithms. The XGB model has better quality than the classification model of other algorithms. We used this model to predict and quantify compounds that strongly bind to seven vital meningitis proteins. The compound with the highest predictive score (we found more than 0.99) became a drug candidate to inhibit or neutralize Meningitis.
A Study On The Management Approaches Adopted By Individuals With Osteoarthritis Knee In Karad
Authors: Minal .B. Masekar  , Dr. Smita Patil  , Dr. Chandrakant Patil  , Dr. Khushboo Chotai
Published: June 2022

Osteoarthritis (OA) is a degenerative condition of the joints characterised by focal loss of articular cartilage along with sclerosis of subchondral bone and formation of osteophytes. The purpose of this study was to determine the various management approaches adopted by the people suffering from knee osteoarthritis. As this condition affects a large population the methods use to deal with the symptoms differ which are described in this study highlighting the preference of a physiotherapist by the patients. The study was carried  out  in  Krishna  Hospital,  Karad  with  the  sample  size  of  60  using  purposive  sampling  method,  a  cross  sectional  study was performed using a descriptive study design. Individuals with Osteoarthritis of knee are included based on the inclusion and exclusion criteria. The data collected was analysed qualitatively which resulted in 65% participants who approached General practitioner (GP) as initial approach, with only 6% approaching a physiotherapist. 81% used heat therapy as a measure to manage their symptoms while only 30% used exercises as a modality. The primary finding was that there is no clear pathway for management of Osteoarthritis of knee in Karad. Majority opted for General-Practitioner as their initial approach. Physiotherapists were preferred only by a few, not many were seen utilising exercise modality. Since there is a vast difference in treatments by variety of individuals, this study will thus help in determining the various approaches for knee osteoarthritis and establishing a definitive and effective protocol for the management of the patients symptoms.
Correlative Assessment of Blood Parameters and Periodontal Status in Smokers- A Pilot Project
Authors: Dr Shreya Shetty  , Dr Mawadah  Almehmadi  , Dr Halah Qadah  , Dr Mazen Ismael Zaafrani  , Dr Shrooq Osama Ezzaddin  , Dr Jumanah Khaled Alsaedi  , Khamrunissa Hussain Sheikh
Published: June 2022

Platelets  and leukocytes  activated  in response  to periodontal  microorganisms  during  bacteremia  can  go on  to excite other cells, enhancing the likelihood of atherosclerosis and coronary artery disease. Reports also indicate that decrease in the number of erythrocytes may occur secondary to periodontal disease. Smoking is a known risk factor for periodontal disease by virtue of its adverse effects on the blood cells. It was therefore decided to investigate the relationship between the red blood  cel l(RBC),  white  blood  cell (WBC)  and platelet  counts  and periodontal  parameters  among  smokers  and non- smokers; to subsequently assess any implication of the systemic effects. Blood counts(RBC, WBC, platelets) for the present study were obtained from peripheral venous blood of 126 patients , both male and female aged between 18-45 years, in each group as follows: GROUP 1 :Periodontally healthy (n = 42) (non-smokers) GROUP 2: Chronic periodontitis (n = 42)( non- smokers) GROUP 3: Chronic periodontitis (n = 42) ( smokers) The clinical parameters to assess periodontitis included plaque index(PI), bleeding  index(BI)  and  Clinical  Attachment  Loss(  CAL)  and  history  of  smoking  was  elicited  based  on  amount, frequency  and  duration  of  smoking.  ANOVA  tests  followed  by  post  HOC  –Tukey  HSD  test  revealed  that  there  were significant differences between the 3 groups with respect to PI, BI and RBC counts(p<0.05). Pearson correlation test revealed a significant correlation between plaque index and platelet counts in group 1 only(p<0.05). Additionally, a significant correlation was also observed between  WBC  and platelet counts in  all three groups(p<0.05).Variations in  blood  counts in  different periodontal situations may pose a risk of systemic inflammation in smokers and non- smokers.
Pertanggungjawaban Notaris Terhadap Akta Yang Dinyatakan Batal Demi Hukum Oleh Pengadilan
Authors: Romavita Romavita , Yetniwati Yetniwati , Syamsir Syamsir
Published: June 2022

This study aims to determine and analyze the responsibility of the Notary to the deed which was declared null and void by the Court (Case Study of the Malang District Court Decision Number 227/Pdt.G/2018/PN.Mlg). The results show that the Malang District Court Judge's Decision in Decision Number 227/Pdt.G/2018/PN.Mlg cannot be separated from 3 (three) aspects, namely juridical, philosophical, and sociological. First, the juridical aspect of the Malang District Judge's Decision is irrelevant between the main cases in the decision. Second, the philosophical aspect does not fulfill the sense of justice, especially for Notary S who made the Sale and Purchase Binding Agreement for the parties which was declared null and void by the judge. Third, the sociological aspect of the judge's decision can cause public confidence to decline in the existing judicial process. In Malang District Court Decision Number 227/Pdt.G/2018/PN.Mlg, Notaries are not charged with any responsibility. In this case, the responsibility of the Notary is only limited to the order of the Judge ordering the Notary to submit to the Judge's Decision as stated in the decision. The notary only records what was stated by the parties/appearers and then poured it into the deed. A notary cannot be held responsible for a deed that is canceled due to a violation committed by one of the parties to the agreement.
Abstrak
Penelitian ini bertujuan untuk mengetahui dan menganalisis pertanggungjawaban Notaris terhadap akta yang dinyatakan batal demi hukum oleh Pengadilan (Studi Kasus Putusan Pengadilan Negeri Malang Nomor 227/Pdt.G/2018/PN.Mlg). Hasil penelitian menunjukkan bahwa Putusan Hakim Pengadilan Negeri Malang dalam Putusan Nomor 227/Pdt.G/2018/PN.Mlg tidak lepas dari 3 (tiga) aspek yaitu yuridis, filosofis, dan sosiologis. Pertama, aspek yuridis Putusan Hakim Negeri Malang tidak relevan antar pokok perkara dalam putusan. Kedua, aspek filosofis kurang memenuhi rasa keadilan, khususnya terhadap Notaris S yang membuat Perjanjian Pengikatan Jual Beli bagi para pihak yang dinyatakan batal demi hukum oleh Hakim. Ketiga, aspek sosiologis putusan hakim dapat menyebabkan kepercayaan masyarakat menurun terhadap proses Peradilan yang ada. Dalam Putusan Pengadilan Negeri Malang Nomor 227/Pdt.G/2018/PN.Mlg, Notaris tidak dibebankan tanggungjawab apapun. Dalam hal ini tanggung jawab Notaris hanya terbatas dengan perintah Hakim yang memerintahkan Notaris untuk tunduk pada Putusan Hakim yang tertuang dalam putusan. Notaris hanya mencatat apa yang dikemukakan oleh para pihak/penghadap lalu dituangkannya ke dalam akta. Notaris tidak bisa dimintai pertanggungjawaban terhadap akta yang dibatalkan karena pelanggaran yang dilakukan oleh salah satu pihak dalam perjanjian.
A CHEMICAL/GAS PLUME TRACING ROBOT SIMULATOR FOR QUADROTOR PLATFORMS: A MODIFIED GAUSSIAN-MEANDERING PLUME PROPAGATION MODEL
Authors: Eu Kok Seng , Yap Kian Meng
Published: June 2022

The process of evaluating the performance of chemical/gas plume tracing (CPT) algorithms is difficult because of real-world environmental parameters (i.e. surrounding wind) that are beyond researchers’ control, therefore, a CPT simulator can be useful. In this study, we design a modified Gaussian-meandering plume propagation model that is enhanced with the realistic characteristics of plume propagation such as meandering, internal intermittency, and vortices, which have not been modelled in the previous studies before. Subsequently, we use a computational fluid dynamics (CFD) software to generate the three-dimensional (3D) wind vectors and study the impact of quadrotor’s propellers, and then incorporating into the plume propagation design. On the whole, the study presented a complete CPT simulator for quadrotor platform with the realistic characteristics of plume propagation.
DST ELEMENTS: INFUSION IN THE DEVELOPMENT OF TABLET-BASED TEACHING PRODUCTS (APPS)
Authors: Hussain Hashiroh , Shiratuddin Norshuhada
Published: June 2022

The usage of instructional media (apps) is poorly delivered due to inappropriate content of the presentation. Recent studies showed that perceptions among students and teachers regarding the use of apps are very low. Thus, Digital Storytelling (DST) concept is infused in developing the apps. Nevertheless, students are unable to comprehend DST clearly. The aim of this study is to identify DST elements for the development tablet based teaching products (apps). Critical analysis and comparative analysis are employed based on eight samples of DST tools to formulate generic DST elements. Eleven DST elements are formed and learning theories are adapted based on correct principles and procedures. The elements should contribute a new pedagogical approach for teachers in developing apps with mobile technology.
USABILITY EVALUATION OF A MOBILE PHONE BASED BRAILLE LEARNING APPLICATION "MBRAILLE"
Authors: Nahar Lutfun , Jaafar Azizah , Sulaiman Riza
Published: June 2022

The introduction and evaluation of Braille-learning tools are not receiving attention despite the need for talking books and Braille reading materials. As the Braille learning tools are very limited in developing countries, newly introduced tools and technological solutions need to be properly evaluated for implementation with the required improvements. The current study evaluated a smartphone-based interactive application â€œmBRAILLEâ€ for teaching early Braille-writing skills in English and Bangla. The mBRAILLE is developed to provide a cheap and affordable technology to the visually impaired (VI) students in Bangladesh. The application will help them learn Braille. A two-stage evaluation was performed in Bangladesh to determine the effectiveness of the application. The first stage of evaluation was performed with five school-aged VI children and five teachers from a blind school to determine the satisfaction level of the users while interacting with the application. This evaluation focused on 5 usability criteria, namely, learnability, memorability, efficiency, error, and satisfaction. After using mBRAILLE, participants evaluated the interfaces of the application through a specific questionnaire. Evaluation results showed that mBRAILLE meets the considered usability criteria, indicating that the interaction between application and users was on a desired level of satisfaction. Additionally, teaching ability of the application was evaluated by 5 real users in the second stage of evaluation, with a positive result. Therefore, given that the application is an effective tool to learn and teach English and Bangla Braille, it can be implemented in Bangladesh to assist VI students.
VISUAL ANALYTICS EVALUATION PROCESS: PRACTICE GUIDELINES FOR COMPLEX DOMAIN
Authors: Ya'acob Suraya , Mohamad Ali Nazlena , Mat Nayan Norshita , Liang Hai-Ning , Ahmad Ibrahim , Ibrahim Roslina , Abu Bakar Nur Azaliah
Published: June 2022

Visual analytics fundamentally influences the analytical process. Without proper guidance, the use of visual analytics in complex domain can become an obstacle that hides the usefulness of analytical data. Since evaluation is the only way to identify the effectiveness of visual analytics to represent analytical outcomes, misconception of the evaluation process will bury the relevancy of visualization to support valuable decision. Recently, the nature domain of data has changed and we are now dealing with data that is massive, ambiguous, and dynamic, is often processed in real time. Hence, the data is more complex and cognitive activities that visual analytics facilitates are also getting more complex. Thus, this research revisits the way to evaluate visual analytics in complex cognitive conditions that are natural, uncertain and context dependent. Governed by the Design Science Research Methodology (DSRM), there are three phases involve during the evaluation process; i). demonstration, ii). evaluation and iii). communication. The design process is embedded with the human-activity centered design approach to gain better understanding on the visual analytics users and the complex cognitive activities involved. Thus, the research proposes Focus Group Observation method in conducting the evaluation in authentic setting. By offering a set of evaluation recommendations, this research aims to enhance visual analytics among users. It also recommends the evaluation criteria, sampling strategy and participation, focus group tasks
PIXEL-BASED FOREGROUND DETECTION IN REPETITIVE TIME-SERIES REGION
Authors: Rattanapitak Wirat R , Wangsiripitak Somkiat
Published: June 2022

Currently, many state-of-the-art background subtraction techniques cannot deal properly with the area of periodic changing background, while some continue classifying them as foreground at intervals, others simply mask that area as a non-region of interest. To cope with this issue, a novel method of detecting repetitive temporal patterns based on the image sequences was proposed in this paper. The main emphasis of the proposed approach is on classifying those pixels as a background and identifying foreground objects in their relevant areas. As for the foreground detection, a model of time series pattern found in each pixel is individually built first; and then, any changes beyond the allowance of model periodicity are then determined as foreground objects. The proposed method could be used and run in parallel with any state-of-the-art background subtraction technique, allowing more accurate foreground-background segmentation. Experimental results showed that using Y channel, the proposed method of detecting time-series background area could achieve 92.9% of recall rate with less than 1% false positives. The recall of foreground detection in an area of repetitive time-series pattern was about 87%; while F-measure was about 0.73 on average. The false positives of foreground detection were also less than 1%. Accordingly, the proposed time-delay detection technique could significantly help to suppress the foreground error on time series background area, especially during the change from one sub-pattern to another which causes a camera sensor to capture both sub-pattern values in one frame. Performance comparison with state-of-the-art methods showed that our proposed method was able to reduce 80% of the average false alarm and improve F-measure to 28% while the computational efficiency was reduced by only 1%.
FOG ANALYTICS - A SURVEY
Authors: Prabhu C.S.R. , Jan Tony , Prasad Mukesh , Varadarajan Vijayakumar
Published: June 2022

Fog computing has emerged as an essential alternative to the cloud. Fog computing is the future as it is nearer to the edge where actually the IOT devices and sensors are located. A Fog Server or Fog Node is located near to the IOT devices, connecting directly (wired or wireless) to them. The Fog Server has a functionality of fast accessibility to the data arising out of IOT devices or sensors, as against cloud server which may be located in data centers (near core Network Centers) located far away from the edge resulting in extreme delays in network transmission and latency, especially when the data is large volume as stream (or ‘Big Data’) arising out of IOT devices or sensors including cameras, etc. Real time response after completing the necessary Analytics on the data generated by IOT devices and sensors becomes critically essential for meeting the real time response requirements of critical applications such as in health care and transportation. What are the relevant techniques for Fog Analytics? In this paper we provide a brief survey of Fog Analytics techniques in stream data analytics, machine learning, deep learning techniques and also game theoretical adversarial learning.
SKEM++: SEMANTIC KEYWORD EXTRACTION MODEL USING COLLECTIVE CENTRALITY MEASURE ON BIG SOCIAL DATA
Authors: R Devika , V Subramaniyaswamy
Published: June 2022

In recent times, Online Social Network (OSN) has accumulated a massive volume of user-generated data available in an unstructured format. It consists of user ideas, responses, and opinions on various topics. It extracts essential keywords in OSN, which is endowed with many exciting applications such as information recommendation or viral marketing. This paper emphasizes the importance of semantic graph-based methods for extracting vital keywords experimentally using a novel SKEM++ method. It is an innovative method for keyword extraction from OSN based on centrality measures. It utilizes a distributed computing approach to calculate the network Collective Centrality Measure (CCM) for each node and improve the semantics of keywords. The distributed approach is more scalable and computationally efficient than the conventional system, making it more suitable for large-scale real-time data sets such as the OSN. Experimental outcomes on the real-time Twitter Data set to infer the dominance of the proposed Collective Centrality Measure(CCM) method in evaluation with contemporary schemes in terms of F-score by 81% and recall by 80% and precision by 80% using Semantic Analysis.
B-LSTM-NB BASED COMPOSITE SEQUENCE LEARNING MODEL FOR DETECTING FRAUDULENT FINANCIAL ACTIVITIES
Authors: Karn Arodh Lal , Ateeq Karamath , Sengan Sudhakar , V Indra Gandhi , Ravi Logesh , Sharma Dilip Kumar , V Subramaniyaswamy
Published: June 2022

Deep Learning (DL) in finance is widely regarded as one of the pillars of financial services sectors since it performs crucial functions such as transaction processing and computation, risk assessment, and even behavior prediction. As a subset of data science, DL can learn and develop from their experience, which does not require constant human interference and programming, implying that the technology will improve quickly. By loading an Ensemble Model (EM), a Deep Sequential Learning (DSL)model, and additional upper-layer EM classifier in the correct order, a new “Contained-In-Between (C-I-B)” composite structured DSL model is recommended in this article. In cases like Fraud Detection System (FDS), where the data flow comprises vectors with complex interconnected characteristics, DL models with this structure have proven to be highly efficient. Finally, by utilizing optimized transaction eigenvectors, a NB classifier is trained. This strategy is more effective than most standard approaches in identifying transaction fraud. The proposed model is evaluated for its accuracy, Recall and F-score, and the results show that the model has better performance against its counterparts.
DESIGNING A DEEP LEARNING-BASED FINANCIAL DECISION SUPPORT SYSTEM FOR FINTECH TO SUPPORT CORPORATE CUSTOMER’S CREDIT EXTENSION
Authors: Karn Arodh Lal , Sachin V. , Sengan Sudhakar , V Indra Gandhi , Ravi Logesh , Sharma Dilip Kumar , V Subramaniyaswamy
Published: June 2022

In the banking business, Machine Learning (ML) is critical for averting financial losses. Credit risk evaluation is perhaps the most important prediction task that may result in billions of dollars in damages each year (i.e., the risk of default on debt). Gradient Boosted Decision Tree (GBDT) models are now responsible for a large portion of the improvements in ML for predicting credit risk. However, these improvements begin to stagnate without adding pricey new data sources or carefully designed features. In this work, we describe our efforts to develop a unique Deep Learning (DL)-based technique for assessing credit risk that does not rely on additional model inputs. We present a new credit decision support approach with Gated Recurrent Unit (GRU) and Convolutional Neural Networks (CNN) that uses lengthy historical sequences of financial data while requiring few resources. We show that our DL technique, which uses Term Frequency-Inverse Document Frequency (TF-IDF) pre-classifiers, outperforms the benchmark models, resulting in considerable cost savings and early credit risk identification. We also show how our method may be utilized in a production setting, where our sampling methodology allows sequences to be effectively kept in memory and used for quick online learning and inference.
Estado psicológico y social en esclerosis múltiple durante la cuarentena por COVID-19
Authors: Lopera-Vásquez Juan Pablo , Múnera-Rodríguez Yeiran Camilo
Published: June 2022

Objetivo: Dado que el COVID-19 se extendió por el mundo, afectando principalmente a las personas que padecían de enfermedades previas y crónicas, como la esclerosis múltiple (EM). Al respecto en este estudio se buscó explorar el estado emocional, el apoyo familiar, el cumplimiento de las medidas de autocuidado y el acceso a los sistemas de salud durante la cuarentena, de un grupo de pacientes colombianos con esclerosis múltiple, debido a que esta condición de salud tiene especial relevancia, debido a que afecta a los sistemas inmune y nervioso. Materiales y Métodos: Se realizó un estudio retrospectivo y descriptivo, de enfoque mixto y corte transversal, en el que participaron 31 pacientes con diagnóstico de EM, quienes se abordaron por medio de entrevistas semi-estructuradas vía teleasistencia. Resultados: Más de la mitad de los pacientes tienden a permanecer emocionalmente estables durante la cuarentena y la mayoría sostiene vínculos familiares favorables. Por otra parte, para la mayoría de los participantes no les fue posible seguir la cuarentena de forma estricta, debido a necesidades económicas y de salud; casi las tres cuartas partes no presentó problemas para acceder al sistema de salud. Conclusión: La estabilidad emocional de los pacientes evaluados está relacionada con el adecuado apoyo familiar, así como por la posibilidad de continuar accediendo a los servicios de salud requeridos. Sin embargo, el incumplimiento del aislamiento estricto está asociado a que los participantes eran adultos jóvenes y activos laboralmente en su mayoría.
Complicaciones de traqueotomías asociadas a intubaciones prolongadas. Revisión sistemática
Authors: Espinoza-González Carlos Francisco
Published: June 2022

Objetivo: Determinar las complicaciones detalladas de traqueotomías asociadas a intubaciones prolongadas en el adulto. Metodología: Revisión sistemática de los 5 años anteriores con base en los lineamientos PRISMA. Se recurrió a las bases de datos Scopus, Web of Science, Taylor and Francis y el Portal Regional de la Biblioteca Virtual en Salud. Además, se seleccionó la información a través de palabras clave, tales como: traqueotomía, intubación prolongada, UCI, adulto, complicaciones. Las publicaciones estaban en idioma español e inglés. La información se catalogó según criterios de inclusión y exclusión. Análisis: 24 artículos fueron elegidos. El momento de la traqueotomía (TQ) por intubación prolongada sigue siendo incierto. La TQ temprana demostró mayores beneficios que la TQ tardía. La TQ percutánea demostró menores tasas de estancia en la UCI y en los hospitales, con menos complicaciones. La hemorragia y la desaturación fueron complicaciones registradas asociadas a TQ tardía. Conclusión: La TQ percutánea fue la que se eligió en la mayoría de casos por ser eficaz, rápida y segura; además, disminuye la estancia hospitalaria y en la UCI, con menos complicaciones. Se debe precisar que en la mayoría de las publicaciones, al menos uno de estos beneficios no alcanzó significancia estadística. La complicación con mayor frecuencia fue la hemorragia en el sitio de punción.
Anomalous origin of right coronary artery from the left coronary sinus in association with type A interrupted aortic arch
Authors: Pu Jianfeng , Luo Shuhua , An Qi
Published: June 2022

In this case, we reported a 24-day-old infant with a rare combination of
the anomalous origin of coronary artery and the type A interrupted
aortic arch, who presented with significant shortness of breath. Besides
these anomalies, further cardiac examination including transthoracic
echocardiography and CT angiogram revealed ventricular septum defect,
patent foramen ovale and patent ductus arteriosus at the same time.
Surgical procedures including repair of ventricular septum defect,
ligation of patent ductus arteriosus, unroofing of right coronary artery
and end-to-side aortic anastomosis were performed to cure the infant.
This patient stayed in ICU for few days without any major complications
and discharged from hospital at the tenth day after surgery.
Malignant Transformation of Tailgut Cyst to Squamous Cell Carcinoma, a rare case with poor outcome
Authors: Moshtaghian Mahsa , Shahsiah Reza , Jafari Fatemeh , Aghili Mahdi
Published: June 2022

Tailgut cyst, a type of retro-rectal cyst, is a rare condition requiring
evaluation for malignant transformation. We report a case of squamous
cell carcinoma arising in the retro-rectal cyst, in a 51-year-old female
who underwent incomplete resection of the cyst and chemo-radiotherapy,
subsequently became locally recurred and metastatic.
Sigmoid volvulus as a cause of Intestinal obstruction in pregnancy: A case report
Authors: Naseef Paul , Elnour Ayman Abou , Ramy Ahmed
Published: June 2022

Sigmoid volvulus is one of the rare causes of intestinal obstruction in
pregnancy and can result in significantly increased maternal and fetal
mortality rates, especially in case of delayed diagnosis. In this
report, we present a 34 week-pregnant lady presenting with intestinal
obstruction due to sigmoid volvulus and her management.
Successful desensitization after hypersensitivity reaction to cisplatin in a patient with nasopharyngeal carcinoma
Authors: Kinouchi Arisa , Ishii Hiroki , Sakamoto Kaname , Sakurai Daiju
Published: June 2022

Hypersensitivity reaction (HSR) to cisplatin can result in
discontinuation of chemoradiotherapy in patients with head and neck
squamous cell carcinoma (HNSCC). We present a nasopharyngeal carcinoma
patient with cisplatin hypersensitivity successfully treated with
cisplatin-desensitization. Desensitization therapy may be safe and
beneficial in patients with HNSCC who develop HSR to cisplatin.
Pattern and Predictors of Medication Use among Adults in Southwestern Nigeria: A Community-based Cross-sectional study
Authors: Adedeji Waheed , Dairo David , Nguku Patrick , Oyemakinde Akin , Fehintola Fatai
Published: June 2022

Aim: The aim was to determine the pattern and predictors of medication
use among adults in the communities of Southwestern Nigeria. Methods: A
cross-sectional study was conducted among adults selected by multi-stage
sampling from Oyo State communities. The questionnaires, adapted from
the WHO Students’ Drug Use Questionnaire and previous studies, were
pretested and interviewer-administered. The respondents’
socio-demographic characteristics, the pattern of medication use,
prescribers and sources of drug acquisition were obtained. Binary
logistic regression was used to determine the predictor of medications
used. Results: Of the 999 respondents, 501 resided in rural communities
while 498 dwelled in urban areas. The mean (±SD) age of the respondents
was 38±15years. The median (range)% prevalence of medication use were:
lifetime use, 58.2(17.7-81.0), current use, 31.2(8.9-65.9) and past use,
20.3(9.2-28.9). Medications were mainly obtained from patent medicine
stores, median (range%), 71(65-80). The commonly used drugs were
paracetamol,626(67.6), Nonsteroidal anti-inflammatory drugs, 174(18.8),
artemether/lumefantrine, 422(68.2), Ampicillin/cloxacillin, 220(48.6),
and chlorpheniramine, 59(40.4). Factors predictive of current medication
use, AOR (95% CI) were: antimalarial [male, 0.7(0.5, 0.9)];
antibacterial [male, 0.6(0.4-0.9)]; analgesics [married,
1.5(1.1-2.2), presence of health facilities, 0.5(0.3-0.7), and shorter
distance to health facility, 1.5(1.1-2.1)]. Conclusion: Antimalarials,
antibacterial and analgesics were commonly used and inappropriately
obtained by adults in Southwestern Nigeria. Factors predictive of
current medication use were gender, marital status, the presence of
health facilities and distance to health facilities. There is a need for
more extensive countrywide medication use studies and enlightenment
programs to ensure the appropriate use of medications.
Incarcerated Men’s Perceptions of the Prison Environment: An Exploratory Study
Authors: Stacer Melissa
Published: June 2022

The punitiveness of prisons is considered necessary for deterrence, but there is also a societal expectation that prisons will also rehabilitate. Scholars have examined whether prisons are ideal environments for rehabilitation from the perspective of the inmate, though this work largely focuses on measurement issues related to the scales used to measure offenders’ perceptions. The current research expands upon this by asking a sample of 154 incarcerated men from three different correctional facilities in the Midwestern United States what they think about their current correctional environment using the Prison Environment Scale (PES) and focusing on the answers provided by those incarcerated individuals. These results are presented descriptively, giving a voice to the incarcerated and their perceptions of the prison environment. Results from this exploratory study indicate incarcerated individuals feel negatively about the social and physical environment of prisons, noting the existence of hierarchies, possessions being used as currency, lack of physical space, and the lack of meaningful activities. Devising ways to promote a prosocial prison environment is important for effective rehabilitation, improved institutional conduct, and positive post-release outcomes.