bluuebunny/crossref_metadata_2025 huggingface dataset:
STUDI KUALITATIF TENTANG STRATEGI KOMUNIKASI PEMASARAN PADA BAKSO RANTE SIDOARJO
Authors: Nashiroh Listiatun , Yuliatiningtyas Solikhah , Zulaikha Zulaikha , Abror Dhimam
Published: November 2022

Penelitian ini bertujuan untuk mengetahui bagaimana strategi komukasi pemasaran bakso rantai yang dilakukan selama masa pandemi untuk menarik pelanggan. Landasan toeri yang digunakan dalam penelitian ini yaitu menggunakan Teori dari Kotler dan Amstrong (2012) yang menjelaskan teori mengenai bauran promosi atau promotion mix yang terdiri dari lima bauran, yaitu advertising, sales promosi, penjualan personal, hubungan masyarakat, dan pemasaran langsung. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah dengan menggunakan metode observasi, wawancara, dokumentasi, dengan teknik analisis deskriptif kualitatif. Disimpulkan bahwa Bakso Rante menggunakan strategi komunikasi pemasaran bauran promosi dalam memperkenalkan produknya. Akan tetapi dalam pelaksanaannya, Bakso Rante masih kurang berjalan dengan baik dilihat dari belum digunakan dengan baiknya metode bauran promosi.
SEMIOTIKA PESAN MORAL DALAM FILM PENDEK PITUTUR PRODUKSI PANIRADYA KAISTIMEWAN D.I.YOGYAKARTA
Authors: Ahmadi Ahmadi , Mulyono Denan Ihsan Putra , Panuju Redi , Harliantara Harliantara
Published: November 2022

Tulisan ini membahas mengenai pesan moral dalam sebuah film pendek yang ditinjau melalui tanda yang selanjutnya dikaji melalui kacamata semiotika. Film yang menjadi objek tulisan ini merupakan film pendek dengan judul “Pitutur” atau yang dalam Bahasa Indonesia memiliki arti “Nasihat” yang diproduksi oleh Paniradya Kaistimewan, sebuah lembaga pemerintahan di bawah lingkup pemerintah Daerah Istiemwa Yogyakarta. Film merupakan buah cermin kehidupan manusia yang tercitrakan melalui medium audio dan visual. Film menampilkan sebuah tanda, dan tanda merujuk pada suatu makna. Lebih jauh, film juga membawa pesan tertentu yang coba disebar-luaskan kepada audiennya. Film pendek Pitutur menceritakan tentang dua orang sahabat dengan karakter dan latar kehidupan yang berbeda. Terdapat beberapa konflik yang terjadi antara para pemain. Puncaknya, terjadi sesuatu yang tidak diinginkan buah dari tindakan yang telah dilakukan sebelumnya. Terdapat petuah yang menjadi dasar film ini, disebutkan: “Pituture wong tuwo kuwi, nek kok tindakke, uripmu bakal becik. Yen ning pituture wong tuwo ki ora tok gatekke, opo meneh ora kok tindakke, uripmu bakal jungkel-jungkel” atau dalam Bahasa Indonesia dapat diartikan “Pitutur (nasihat) orang tua itu jika didengarka
The Dynamics of Learning Management System Assessment: A Case of Undergraduate Mathematics
Authors: Tatira Benjamin
Published: November 2022

The purpose of this study was to elaborate on the different dimensions to conduct an online assessment in undergraduate mathematics. Mathematics assessment using digital technologies is unique because it has special symbols and multi-step solutions. The sudden shift to full online learning necessitated Learning Management System-based online assessment as part of learning and for certification. The research design for this study was a qualitative case study. The case considered for this study was a calculus course and the 180 students registered for the course in 2021 at a South African university. The researcher was the instructor for this course. After explaining the details of conducting the online assessment of mathematics, data was collected on students’ experiences in online assessment using questionnaires and interviews. A conveniently chosen sample of 13 students completed the online questionnaire. A further ten students took part in the telephonic interviews and these were selected conveniently again. Data was composed of written responses to the questionnaires and the transcriptions of the interview audio recordings. After sitting both quizzes and assignments on Blackboard, students preferred the assignment format. This was also suitable for mathematics where there is a need to show steps and proofs in the solution process for both formative and summative assessment. Course instructors hence can effectively administer appropriate formative online assessments on the Learning Management System that has the potential to propel the teaching and learning of mathematics.

Keywords: Learning Management System; undergraduate mathematics; online assessment; quizzes; assignments; Blackboard; formative assessment
A Study of John 21:15-17: Toward a Shepherd Model of Christian Ministry
Authors: Boaheng Isaac , Osei Isaac Justice
Published: November 2022

Leadership is one of the key challenges facing the contemporary society despite many seminars, conferences and workshops organized on this subject. The political crises in many organizations and societies are the result of poor leadership. The subject of leadership is so important that no amount of scholarship dedicated to it can be considered too much. In a predominantly Christian society like Africa (and some other parts of the world) many people look up to Christianity to offer a leadership model that can promote quality leadership. The purpose of this paper is to provide biblical principles for leadership through a textual analysis of John 21:15-17. A literature-research methodology was used to gather data from books, journal articles and dissertations. A key finding is that shepherd leaders must show deep concern, compassion, acceptance and empathy for their followers in order to heal, sustain, nurture, and empower them. The paper ends with implications of the shepherding model of leadership for contemporary Christian ministry.

Keywords: Christ, Christian, Leadership, Shepherd
IMPACT OF COVID 19 ON PERFORMANCE OF GOLD ETFS IN INDIA
Authors: Garg Dr. Sandeep
Published: November 2022

People invest in gold because they view it as a valuable economic resource, they can use to supplement their income. COVID-19 pandemic and economic lockdowns are likely to support consumer demand for gold performance in the short term. If the economy recovers quickly and the stimulus measures are in place for a long period of time, Gold’s behaviour may be affected. The GDP growth rate in India has been trending downward. Consumer spending on non-essentials fell in this environment. COVID19's outbreak in March only served to amplify this trend. People are becoming more cautious with their money. Indian and international gold demand is expected to be high, according to a recent study. The Covid -19 pandemic lowered the demand for gold for a short period of time. The demand for investment is increased as a result. This paper is a study of the Performance Evaluation of Gold ETFs in India during the Covid-19 Pandemic Situation. Knowing how behavioural biases affect investor preference for gold exchangetraded funds (ETFs), Investing in gold requires an understanding of the psychological aspects of the process. Assessing how gold ETFs demand changes during the pandemic is essential for figuring out why investors are becoming so irrationally bullish on gold.
THE CONNECTION BETWEEN AN AIRPORT TYPE AND REVENUE STRUCTURE AT BALTIC STATES AIRPORTS
Authors: Uzule Kristine , Kuzmina-Merlino Irina
Published: November 2022

Airports are not only engines of transportation of passengers and cargo, but also commercial enterprises offering services far beyond transportation, which is why their revenues are formed by both aeronautical and non-aeronautical sales. Aeronautical revenues of some large European airports are higher than non-aeronautical revenues, whereas some regional and secondary European airports demonstrate the opposite trend. The aim of this research was to determine if there is a connection between an airport type and the ratio of aeronautical and non-aeronautical revenues at Baltic States airports in way that is consistent with the previous research. The aim was attained in three stages. The first, the definitions of the main and secondary airports were constructed via discourse analysis. The second, the structure of airport revenues of the selected Baltic States airports was analysed. The third, conclusions were made regarding a connection between an airport type and the revenue structure of these Baltic States airports. On the one hand, the research results suggested there might be a connection between an airport type and the revenue structure although this question requires further research, and on the other hand, the financial analysis showed that airports with a higher share of non-aeronautical revenues than aeronautical revenues were more resilient to crises.
MAPPING OF DEFORESTATION AND FOREST DEGRADATION ASSOCIATED WITH RESPONSIBLE DRIVERS IN THE MAN RIVER BASIN, CENTRAL INDIA
Authors: Thakur Jitendra
Published: November 2022

In developing countries, both deforestation and forest degradation are of serious environmental concern due to various driving factors. This can be more difficult to manage due to the lack of quality data and the unavailability of appropriate mapping techniques. Based on remote sensing data, this study examined an integrated approach to improve the mapping capability of forest change monitoring for data deficient areas. The study is carried out integrating ground-based information with Landsat 5 TM, Landsat 8 OLI and TIRS in the Man River Basin, India. The findings of the current study suggest that the integrated approach enhances the ability of modeling to estimate deforestation and forest degradation associated with responsible drivers, especially in countries such as India where grassroots data are infrequent.
A SUB-PIXEL VISUALIZATION METHOD TO DISPLAY FUZZY PHENOMENA USING RGB COLOR COMPOSITE (CASE STUDY: MANGROVES FOREST)
Authors: Toomanian Ara
Published: November 2022

Natural phenomena boundaries and complexity of features in an urban area due to the low spatial resolution, lead to more pixels of satellite images included in reflectance of multiple land-cover/object components. The sub-pixel information extracting model outputs are fractional cover maps of interested class (end-member), with membership values between zero and one. These maps represented gradient change in only one fuzzy phenomenon boundaries such as vegetation cover. However, in multiple fuzzy class area or complex fuzzy phenomena such as mangrove forests, in the northwest of the Qeshm Island, Hormozgan, Iran, displaying several fractional covers may cause confusion and misunderstanding for the end-user. In this study, an additive color composite and spectral mixture analysis method is utilized for multiple fractional cover representation. The proposed method is implemented on images acquired from Operational Land Imager (OLI) sensor in the Landsat 8 satellite to extract three fractional covers (water, vegetation, and soil). An RGB color composite was used for each type and percentage of fractional cover for given pixel to display fractional cover separately. Based on such RGB color composite represented both quantitative and qualitative information, we used the RGB color solid cube as map legend for better understanding and map interpretation. The result of this study showed that suggested sub-pixel visualization method, gives new vision to the end-user understanding of fuzzy phenomena.
X-Ray Sources in the SSA22 Chandra Field
Authors: Radzom Brandon T. , Taylor A. J. , Barger A. J. , Cowie L. L.
Published: November 2022

The Hawaii Survey Field SSA22 is the fourth deepest Chandra X-ray field. To allow for the fullest exploration of this field, we present new optical spectroscopy from Keck/DEIMOS and Keck/LRIS, which, in combination with the literature, brings the spectroscopic completeness of the 2–8 keV sample to 62%. We also make optical spectral classifications and estimate photometric redshifts for the sources without spectroscopic redshifts. We then determine hard X-ray luminosity functions (XLFs) for the full sample of active galactic nuclei (AGNs), as well as for the broad-line AGNs (BLAGNs) and the non-BLAGNs separately. Our XLF for the full sample is in good agreement with the literature, showing relatively strong evolution over the redshift range 0.25 ≤ z < 4. The XLFs for the BLAGNs and the non-BLAGNs imply distinct evolution with redshift, with BLAGNs becoming increasingly dominant at higher redshifts and X-ray luminosities.
A 16 hr Transit of Kepler-167 e Observed by the Ground-based Unistellar Telescope Network
Authors: Perrocheau Amaury , Esposito Thomas M. , Dalba Paul A. , Marchis Franck , Avsar Arin M. , Carrera Ero , Douezy Michel , Fukui Keiichi , Gamurot Ryan , Goto Tateki , Guillet Bruno , Kuossari Petri , Laugier Jean-Marie , Lewin Pablo , Loose Margaret A. , Manganese Laurent , Mirwald Benjamin , Mountz Hubert , Mountz Marti , Ostrem Cory , Parker Bruce , Picard Patrick , Primm Michael , Randolph Justus , Runge Jay , Savonnet Robert , Sharon Chelsea E. , Shih Jenny , Shimizu Masao , Silvis George , Simard Georges , Simpson Alan , Sivayogan Thusheeta , Stein Meyer , Trudel Denis , Tsuchiyama Hiroaki , Wagner Kevin , Will Stefan
Published: November 2022

More than 5000 exoplanets have been confirmed and among them almost 4000 were discovered by the transit method. However, few transiting exoplanets have an orbital period greater than 100 days. Here we report a transit detection of Kepler-167 e, a “Jupiter analog” exoplanet orbiting a K4 star with a period of 1071 days, using the Unistellar ground-based telescope network. From 2021 November 18 to 20, citizen astronomers located in nine different countries gathered 43 observations, covering the 16 hr long transit. Using a nested sampling approach to combine and fit the observations, we detected the midtransit time to be UTC 2021 November 19 17:20:51 with a 1σ uncertainty of 9.8 minutes, making it the longest-period planet to ever have its transit detected from the ground. This is the fourth transit detection of Kepler-167 e, but the first made from the ground. This timing measurement refines the orbit and keeps the ephemeris up to date without requiring space telescopes. Observations like this demonstrate the capabilities of coordinated networks of small telescopes to identify and characterize planets with long orbital periods.
The Giant Low Surface Brightness Galaxy Malin 1: New Constraints for Its Molecular Gas Mass from GBT/ARGUS Observations
Authors: Galaz Gaspar , Frayer David T. , Blaña Matías , Howk J. Christopher , Puzia Thomas , Johnston Evelyn J. , Ordenes-Briceño Yasna , Church Sarah , Gil Santiago , Joachimi Katerine , Mora Marcelo
Published: November 2022

We report on results from GBT/ARGUS 12CO(1-0) observations for the giant low surface brightness galaxy Malin 1, which allow us to determine an upper limit for its CO mass, and hence its molecular gas mass and molecular gas mass surface density

Σ

H

2

. Although we performed very deep observations through 17 hr on-source integration time, reaching a noise level of ∼0.2 mK (T

A

*

) with a corresponding extended source CO limit (3σ) of 0.09 K km s−1, 19 times more sensitive than previous works, we do not detect the 12CO(1-0) emission line. However, the observations allow us to estimate an upper limit (3σ) for the CO mass of about 7.4 × 109
M
⊙ for the extended emission, and 1.4 × 108
M
⊙ for the central part of the galaxy. With these figures we conclude that the molecular gas surface density is lower than 0.3 M
⊙ pc−2, and the corresponding molecular to atomic gas mass ratio is lower than 0.13. The evidence suggests quite different physical conditions for the interstellar medium in Malin 1 compared to that of normal, high surface brightness spirals. This, in one way to another, keeps an usual molecular gas tracer as CO hidden from our observations, in spite of the diverse stellar and structural properties of Malin 1 observed by several authors since more than 30 yr.
Challenges of ubiquitous and wearable solutions to address active ageing in the Andalusian community
Authors: Polo-Rodríguez Aurora , Dionisio Pietro , Agnoloni Francesco , Gómez Ana Perandrés , Paggetti Cristiano , González López Lucía , Lendínez Alfonso Cruz , Espinilla-Estévez Macarena , Medina-Quero Javier
Published: November 2022

Active ageing is a multidimensional process for achieving the potential quality of life and meaning in the life cycle. In the context of the Andalusian region in Spain, where the majority of the population is over 60 years old and lives in rural areas, it has become a key challenge. That is why the European projects within the Framework Programme for Research and Innovation, such as Pharaon - Pilots for Active and Healthy Ageing, promote technologies adapted by and for our elders. In the case of the Andalusian pilot, part of this project, we have selected a social network adapted to them, enabling them to communicate with the community at home and share their experiences. In addition, to improve their physical fitness, a device to count active minutes and steps is included, which provides users and caregivers with a visible and objective metric of daily health status. The technology has been evaluated following a well-defined methodology, which is described in this work to promote the deployment of technology in large-scale pilots. A specific architecture (Information System for Active Ageing in Andalusia - ISA3) and the components evaluated within a common ecosystem (Pharaon Project) are presented.
Discrétion managériale et enjeux de gouvernance : quelle relation avec les investissements en R&D dans les entreprises tunisiennes
Authors: Bentaleb Sfar Dorsaf , Ben Hassine Anissa
Published: November 2022

Cet article étudie la relation entre les investissements en R&D, la discrétion managériale et la gouvernance des entreprises. L’étude de 75 entreprises tunisiennes observées durant 7 ans, de 2008 à 2014, a été l’occasion de souligner la relation ; d’abord positive entre les investissements en R&D et les variables de la discrétion managériale dans une première phase, puis négative avec l’accroissement de l’espace discrétionnaire, avec un point d’inflexion à l’étape de mi- carrière des dirigeants. Les tests statistiques démontrent en partie la modération exercée par certains mécanismes de contrôle sur la relation entre discrétion managériale et investissements en R&D.
LC-MS-based detection of silkworm pupae in feed with and without prior immunoaffinity enrichment
Authors: Stobernack T. , Zarske M. , Niedzwiecka A. , Zagon J. , Steinhilber A. , Poetz O. , Herfurth U.M.
Published: November 2022

Due to their advantageous nutrient composition and high feed conversion efficiency, insects may be an alternative protein source for human and animal nutrition. Recently authorised for feeding purposes in the European Union, silkworm pupae are vastly and cheaply available by-products from sericulture that have been successfully replacing fish meal in aquaculture feed. In order to enable silkworm detection by official control, we firstly identified potential, easily detectable peptide targets from dried silkworm pupae subjected to a standard mass spectrometry (MS)-based bottom-up proteomic workflow. Secondly, a targeted method with an optional immunoaffinity enrichment (IAE) step was developed. Method validation provided a highly reproducible limit of detection of 0.05% (w/w) silkworm pupae in various feeds (aquaculture, poultry, pig) that proved independent from the experimenter and whether IAE was included in sample preparation or not. Furthermore, the method’s specificity and robustness were assessed.
The Economic Factors Impacting the Viability of Pediatric Ophthalmology
Authors: Lee Karen E. , Sussberg Jake A. , Nelson Leonard B. , Thuma Tobin
Published: November 2022

Purpose:

To create a survey that assesses the economic factors impacting the viability of pediatric ophthalmology between January 2021 and July 2022.

Methods:

A 12-question survey was distributed to United States–based pediatric ophthalmologists on the American Association for Pediatric Ophthalmology and Strabismus discussion board and various social media fora. Demographic, economic, and workforce pattern data were collected and analyzed.

Results:

A total of 243 pediatric ophthalmologists completed the survey. One hundred seven (44.0%) respondents reported a surgical revenue decrease between 10% and 25%, 117 (48.1%) a clinical revenue decrease of less than 10%, 111 (45.6%) an overall income decrease of less than 10%, and 127 (52.2%) an overhead cost increase between 10% and 25%. Seventy-two (29.6%) respondents reported subsidizing income with pursuits outside of pediatric ophthalmology, 27 (11.1%) stopped operating due to reimbursement cuts, 75 (30.8%) limited the number of Medicaid or other public funded patients, 16 (6.5%) retired in the past 3 years, and 92 (37.8%) would not recommend a resident pursue a pediatric ophthalmology fellowship.

Conclusions:

There is a potential upheaval in the field of pediatric ophthalmology marked by increasing levels of disillusionment among current providers, a progressive decline in the number of trainees pursuing fellowship programs, and workforce issues suggestive of diversification of practice patterns outside of pediatric ophthalmology. The current economic crisis, in conjunction with these complex workforce issues, is and will continue to create a shortage of practicing pediatric ophthalmologists, seriously limiting access to pediatric and adult strabismus eye care.

[
J Pediatr Ophthalmol Strabismus
. 2022;59(6):362–368.]
On the Role of Social Media in Spanish Language Learning in Indian Context
Authors: Ahsan Ahmad  , Gaurav Kumar  , Ranjan Ranjeeva , Andrew Philominraj
Published: November 2022

Research on social media in the foreign language classroom has grown significantly in the last decade. The usage of social media has increased many times during the pandemic due to known reasons. The aim of the present study is to examine the perception of the use of social media in learning Spanish as a foreign language in a non-native context. The research was carried out in Indian Higher Education Institutions (HEIs) where Spanish is taught as a foreign language at graduate and undergraduate levels. The objective was to explore the attitudes and perceptions of the students towards the use of social media platforms for learning Spanish as a foreign language and examine the differences in its use concerning gender, background and year of study. The research study was developed in the quantitative framework with the use of a comprehensive questionnaire as an instrument in this study. The results showed that the students tend to use social media for enhancing and reinforcing their communication skills and language learning capabilities including reading, writing, and learning new phrases and structures. Moreover, the study also found the benefits of collaborative learning embedded during the use of social media, which helped in improving the learning process sophistically.
Influence of the Affordance of Online Learning Platform Technology on the Entrepreneurial Behaviors of Students in Engineering and Technology Universities
Authors: Zhang Jing
Published: November 2022

Information technology-based online teaching guarantees sustained teaching activities and ensures the sharing of abundant online educational resources and the convenient use of various online teaching tools. Online learning platforms possess massive teaching resources and solid teacher qualifications, which evidently enhance the learning efficiency of online learners, exert a direct effect on creating entrepreneurial knowledge of students in engineering and technology universities, and motivate their entrepreneurial behaviors. In this research, the scientific problem raised was the influence mechanism of the technological availability of online learning platforms on the entrepreneurial behaviors of students in engineering and technology universities. A questionnaire regarding the influence of the affordance of online learning platform technology on entrepreneurial behaviors was designed on the basis of technology affordance theory. Next, the influencing degrees of two component factors (educational and social affordability) of technology affordance on entrepreneurial behaviors were analyzed via a quantile regression model. Then, the moderating role played by online learning interaction in the positive promoting effect of technology affordance on entrepreneurial behaviors was measured. Results revealed that the overall Cronbach’s α coefficient of the questionnaire was 0.905, and the Kaiser–Meyer–Olkin value was 0.853, indicating their favorable validity and reliability. The technology affordance (social and educational affordances) of online education platforms exerted a positive promoting effect on the entrepreneurial behaviors of students in engineering and technology universities. Learning interaction regulated such a promoting effect. Our results are of important reference values for extending the technology affordance perspective generated under the background of organizational reform, fulling mining the potentials of emerging technical tools on online education platforms and determining the influencing mechanism of the technology affordance of online education platforms on the entrepreneurial behaviors of students in engineering and technology universities.
World Assumptions and Coping Related to Trauma as Predictors of General Mental Health and Acute Stress Symptoms Among Iranian Muslims During the COVID-19 Outbreak
Authors: Khanipour Hamid , Pourali Mahsan , Atar Mojgan , Akbari Mehdi
Published: November 2022

The COVID-19 outbreak is a new potentially traumatic event that may have some unknown effects on mental health. The aim of this study was to examine how two theoretical frameworks related to coping with trauma, including shattered assumptions and coping with trauma, could explain mental health and acute stress symptoms among the general population during the COVID-19 outbreak. The participants included 212 Iranian Muslims who filled out the online survey. Women and people with non-fixed jobs reported more mental health deterioration and acute stress symptoms. There were no significant differences between people with or without COVID-19 in terms of mental health symptoms, experiencing acute stress symptoms, and world assumptions. Results showed that world assumption and forward-focused coping could predict mental health symptoms and acute stress symptoms beyond COVID-19 specific stress. Assumptions related to the meaningfulness of the world and trauma-focused coping were associated with a higher score in general mental health symptoms and acute stress, but assumptions related to the benevolence of the world, self-worth, and forward-focused coping were associated with lower mental health and acute stress symptoms. This could suggest that world assumptions could buffer or endanger mental health during crises such as the pandemic. In addition, it seems that forward-focus coping is effective for managing new life challenges during the COVID-19 outbreak. In contrast, the more people address the negative and catastrophic effects of COVID-19 (such as trauma-focused coping), the more they are prone to developing mental health symptoms. This study showed that among Iranian Muslims, some world assumptions (for example, the meaningfulness of world) and some kinds of coping (for example, trauma-focused coping) were not as protective factor as in non-Muslim countries.
COMPARISON OF MACHINE LEARNING TECHNIQUES FOR PREDICTING NLR PROTEINS
Authors: Nadia  , Gandotra Ekta , Kumar Narendra
Published: November 2022

The nucleotide-binding domain leucine-rich repeat-containing (NLR) proteins plays significant role in the intestinal tissue repair and innate immunity. It recently added to the members of innate immunity effectors molecules. It also plays an essential role in intestinal microbiota and recently emerged as a crucial hit for developing ulcerative colitis (UC) and colitis-associated cancer (CAC). A machine learning-based approach for predicting NLR proteins has been developed. In this study, we present a comparison of three supervised machine learning algorithms. Using ProtR and POSSUM Packages, the features are extracted for the dataset used in this work. The models are trained with the input compositional features generated using dipeptide composition, amino acid composition, etc., as well as Position Specific Scoring Matrix (PSSM) based compositions. The dataset consists of 390 proteins for the negative and positive datasets. The five-fold cross-validation (CV) is used to optimize Sequential Minimal Optimization (SMO) library of Support Vector Machine (LIBSVM) and Random Forest (RF) parameters, and the best model was selected. The proposed work performs rationally well with an accuracy of 90.91% and 93.94% for RF as the best classifier for the Amino Acid Composition (AAC) and PSE_PSSM-based model. We believe that this method is a reliable, rapid and useful prediction method for NLR Protein.
Battery Swapping Business Model
Authors: Singh Nandan Kumar , Ramani Vinay
Published: November 2022

Lithion Power is India's leading provider of battery as a service, supplying lithium-ion batteries for e-bikes and three-wheelers. They use the battery swapping technology to power electric vehicles. Lithion's omni-charging technology allows electric vehicles to either charge at home, at public chargers or at a Lithion Swapping Point (LSP), primarily spread across North Delhi and the nearby state of Haryana. At these LSPs, a customer can drive in with their existing battery and in a less-than-five-minute walk away with a charged battery. Lithion is collaborating with major operators and original equipment manufacturers (OEMs) to make an all-electric India a reality by 2030. Key to Lithion's business model is a battery management system (BMS) that allows the optimal use of the battery, thereby extending its use life. This chapter discusses Lithion's battery swapping service model and puts it in the context of circular economy.
The Waste Cascade in Dell Reconnect With a Focus on Plastic Packaging
Authors: De Giovanni Pietro
Published: November 2022

The Dell Reconnect program is a clear example of a how the circular economy aims at social development and inclusion through a tripartite of strategies consisting of reuse, refurbish, and recycle. Hence, this chapter explores the peculiarities of the circular economy implemented by Dell Reconnect, as well as all unexploited areas, such as the adoption of public funds and the use of digital technologies for smart circular economy systems.
Application of Content-Based Image Retrieval in Medical Image Acquisition
Authors: Majhi Vinayak , Paul Sudip
Published: November 2022

Content-based image retrieval is a promising technique to access visual data. With the huge development of computer storage, networking, and the transmission technology now it becomes possible to retrieve the image data beside the text. In the traditional way, we find the content of image by the tagged image with some indexed text. With the development of machine learning technique in the domain of artificial intelligence, the feature extraction techniques become easier for CBIR. The medical images are continuously increasing day by day where each image holds some specific and unique information about some specific disease. The objectives of using CBIR in medical diagnosis are to provide correct and effective information to the specialist for the quality and efficient diagnosis of the disease. Medical image content requires different types of CBIR technique for different medical image acquisition techniques such as MRI, CT, PET Scan, USG, MRS, etc. So, in this concern, each CBIR technique has its unique feature extraction algorithm for each acquisition technique.
Segmentation of Optic Disc From Fundus Image Based on Morphology and SVM Classifier
Authors: Luo Jiamin , Raj Alex Noel Joseph , Ruban Nersisson , Mahesh Vijayalakshmi G. V.
Published: November 2022

Color fundus image is the most basic way to diagnose diabetic retinopathy, papillary edema, and glaucoma. In particular, since observing the morphological changes of the optic disc is conducive to the diagnosis of related diseases, accurate and effective positioning and segmentation of the optic disc is an important process. Optic disc segmentation algorithms are mainly based on template matching, deformable model and learning. According to the character that the shape of the optic disc is approximately circular, this proposed research work uses Kirsch operator to get the edge of the green channel fundus image through morphological operation, and then detects the optic disc by HOUGH circle transformation. In addition, supervised learning in machine learning is also applied in this chapter. First, the vascular mask is obtained by morphological operation for vascular erasure, and then the SVM classifier is segmented by HU moment invariant feature and gray level feature. The test results on the DRIONS fundus image database with expert-labeled optic disc contour show that the two methods have good results and high accuracy in optic disc segmentation. Even though seven different assessment parameters (sensitivity [Se], specificity [Sp], accuracy [Acc], positive predicted value [Ppv], and negative predicted value [Npv]) are used for performance assessment of the algorithm. Accuracy is considered as the criterion of judgment in this chapter. The average accuracy achieved for the nine random test set is 97.7%, which is better than any other classifiers used for segmenting Optical Disc from Fundus Images.
Jaya Algorithm-Assisted Evaluation of Tooth Elements Using Digital Bitewing Radiography Images
Authors: Manic Kesavan Suresh , Al Naimi Imad Saud , Hasoon Feras N. , Rajinikanth V.
Published: November 2022

A considerable number of heuristic procedures are widely implemented to evaluate biomedical images. This chapter proposes an evaluation procedure for digital bitewing radiography (DBR) images using the Jaya algorithm. The proposed procedure implements an image processing technique by integrating of the multi-thresholding and segmentation procedure to extract the essential tooth elements recorded with DBR. In this paper, 80 dental x-ray images are considered for the evaluation. The performance of the proposed procedure is confirmed using a relative assessment between the extracted section and its corresponding ground-truth. The results of this study confirm that, for most of the DBR cases, the proposed approach offers better values of picture likeliness measures. Hence, this technique can be considered for the automated detection of tooth elements from the DBR obtained from clinics.
Lesions Detection of Multiple Sclerosis in 3D Brian MR Images by Using Artificial Immune Systems and Support Vector Machines
Authors: Merzoug Amina , Benamrane Nacéra , Taleb-Ahmed Abdelmalik
Published: November 2022

This paper presents a segmentation method to detect multiple sclerosis (MS) lesions in brain MRI based on the artificial immune systems (AIS) and a support vector machines (SVM). In the first step, AIS is used to segment the three main brain tissues white matter, gray matter, and cerebrospinal fluid. Then the features were extracted and SVM is applied to detect the multiple sclerosis lesions based on SMO training algorithm. The experiments conducted on 3D brain MR images produce satisfying results.
Implementation of Deep Learning Neural Network for Retinal Images
Authors: Murugan R.
Published: November 2022

The retinal parts segmentation has been recognized as a key component in both ophthalmological and cardiovascular sickness analysis. The parts of retinal pictures, vessels, optic disc, and macula segmentations, will add to the indicative outcome. In any case, the manual segmentation of retinal parts is tedious and dreary work, and it additionally requires proficient aptitudes. This chapter proposes a supervised method to segment blood vessel utilizing deep learning methods. All the more explicitly, the proposed part has connected the completely convolutional network, which is normally used to perform semantic segmentation undertaking with exchange learning. The convolutional neural system has turned out to be an amazing asset for a few computer vision assignments. As of late, restorative picture investigation bunches over the world are rapidly entering this field and applying convolutional neural systems and other deep learning philosophies to a wide assortment of uses, and uncommon outcomes are rising constantly.
Segmentation of Spine Tumour Using K-Means and Active Contour and Feature Extraction Using GLCM
Authors: M. Malathi , Kesavan Sujatha , K. Praveen
Published: November 2022

MRI imaging technique is used to detect spine tumours. After getting the spine image through MRI scans calculation of area, size, and position of the spine tumour are important to give treatment for the patient. The earlier the tumour portion of the spine is detected using manual labeling. This is a challenging task for the radiologist, and also it is a time-consuming process. Manual labeling of the tumour is a tiring, tedious process for the radiologist. Accurate detection of tumour is important for the doctor because by knowing the position and the stage of the tumour, the doctor can decide the type of treatment for the patient. Next, important consideration in the detection of a tumour is earlier diagnosis of a tumour; this will improve the lifetime of the patient. Hence, a method which helps to segment the tumour region automatically is proposed. Most of the research work uses clustering techniques for segmentation. The research work used k-means clustering and active contour segmentation to find the tumour portion.
Intensity Inhomogeneity Correction in Brain MR Images Based on Filtering Method
Authors: Sulochana C. Helen , Blessy S. A. Praylin Selva
Published: November 2022

Brain tumor is a mass of abnormal growth of cells in the brain which disturbs the normal functioning of the brain. MRI is a powerful diagnostic tool providing excellent soft tissue contrast and high spatial resolution. However, imperfections arising in the radio frequency field and scanner-related intensity artifacts in MRI produce intensity inhomogeneity. These intensity variations pose major challenges for subsequent image processing and analysis techniques. To mitigate this effect in the intensity correction process, an enhanced homomorphic unsharp masking (EHUM) method is proposed in this chapter. The main idea of the proposed EHUM method is determination of region of interest, intensity correction based on homomorphic filtering, and linear gray scale mapping followed by cutoff frequency selection of low pass filter used in the filtering process. This method first determines the ROI to overcome the halo effect between foreground and background regions. Then the intensity correction is carried out using homomorphic filtering and linear gray scale mapping.
Deep Learning Techniques for Biomedical Image Analysis in Healthcare
Authors: A. Sivakami , K. S. Balamurugan , Shanmugam Bagyalakshmi , Pitchaimuthu Sudhagar
Published: November 2022

Biomedical image analysis is very relevant to public health and welfare. Deep learning is quickly growing and has shown enhanced performance in medical applications. It has also been widely extended in academia and industry. The utilization of various deep learning methods on medical imaging endeavours to create systems that can help in the identification of disease and the automation of interpreting biomedical images to help treatment planning. New advancements in machine learning are primarily about deep learning employed for identifying, classifying, and quantifying patterns in images in the medical field. Deep learning, a more precise convolutional neural network has given excellent performance over machine learning in solving visual problems. This chapter summarizes a review of different deep learning techniques used and how they are applied in medical image interpretation and future directions.
Useful Features for Computer-Aided Diagnosis Systems for Melanoma Detection Using Dermoscopic Images
Authors: Vocaturo Eugenio , Zumpano Ester
Published: November 2022

The development of performing imaging techniques is favoring the spread of artificial vision systems as support tools for the early diagnosis of skin cancers. Epiluminescence microscopy (ELM) is currently the most adopted technique through which it is possible to obtain very detailed images of skin lesions. Over time, melanoma spreads quickly, invading the body's organs through the blood vessels: an early recognition is essential to ensure decisive intervention. There are many machine learning approaches proposed to implement artificial vision systems operating on datasets made up of dermatoscopic images obtained using ELM technique. These proposals are characterized by the use of various specific features that make understanding difficult: the problem of defining a set of features that can allows good classification performance arises. The aim of this work is to identify reference features that can be used by new researchers as a starting point for new proposals.
Border Detection in Skin Lesion Images Using an Improved Clustering Algorithm
Authors: Jayalakshmi D.  , Dheeba J.
Published: November 2022

The incidence of skin cancer has been increasing in recent years and it can become dangerous if not detected early. Computer-aided diagnosis systems can help the dermatologists in assisting with skin cancer detection by examining the features more critically. In this article, a detailed review of pre-processing and segmentation methods is done on skin lesion images by investigating existing and prevalent segmentation methods for the diagnosis of skin cancer. The pre-processing stage is divided into two phases, in the first phase, a median filter is used to remove the artifact; and in the second phase, an improved K-means clustering with outlier removal (KMOR) algorithm is suggested. The proposed method was tested in a publicly available Danderm database. The improved cluster-based algorithm gives an accuracy of 92.8% with a sensitivity of 93% and specificity of 90% with an AUC value of 0.90435. From the experimental results, it is evident that the clustering algorithm has performed well in detecting the border of the lesion and is suitable for pre-processing dermoscopic images.
Center Line Globular Structure of Strip Cast Using High Speed Twin Roll Caster
Authors: Haga Toshio
Published: November 2022

Formation of a centerline globular structure in an aluminum alloy strip cast using a vertical type high-speed twin-roll caster was investigated. The theory that the crystals form at tip of the nozzle and are conveyed to the roll gap was investigated by roll casting using a cooling slope and clad-strip-casting in this study. In high-speed roll casting, the center of the strip thickness is semisolid, and the temperature gradient in the thickness direction is small. The latent heat of the semisolid metal heats the dendrite structure, which is divided by melting. The dendrite structure was divided as in thixocasting, which is the mechanism of formation of a globular crystal form. The zone of the semisolid metal becomes narrow as the roll load increases or the pouring temperature of the molten metal decreases. As result, the zone containing globular crystal structures becomes thinner.
Mechanical and Metallurgical Characteristics of Rotary Friction Welded Low Carbon Steel Plate/Rod Joints
Authors: Dhamotharakannan Thirumalaikkannan , Sivaraj Paramasivam , Seeman M. , Balasubramanian Visvalingam
Published: November 2022

This work aims to study the mechanical properties and microstructural characteristics of rotary friction welding of the unsymmetrical (plate/rod) joints of AISI 1018 low carbon steel plate and AISI 1020 low carbon steel rod. The mechanical properties (tensile properties and hardness) were studied. The fractured surface of the tensile specimen was examined by Scanning Electron Microscope (SEM). The tesnile properties (strength and elongation) are higher than the AISI 1018 plate but slightly lower than the AISI 1020 rod due to coarse ferrite grains in the HAZ region of the AISI 1018 plate. The hardness varied from the fully deformed zone (FDZ) to the base metal. The average value of the ultimate tensile strength of the friction welded joint is about 452 MPa. The average value of hardness at fully deformed zone is about 252 Hv, which 32% higher than the base metal.
Investigation of End Milling Process by Machine Tool Equipped with an Idling-Stop Function in a Feed Driving System
Authors: Mizuguchi Yuto , Hirogaki Toshiki , Aoyama Eiichhi
Published: November 2022

In recent years, as global environmental problems have become more serious, the concept of sustainable development, such as the 3Rs, has become increasingly important. Against this backdrop, machinery and equipment are becoming smaller, lighter, and more sophisticated and multifunctional, and highly integrated products increasingly require the machining and assembly of minute mechanical parts. However, the fact that small machine tools generate relatively large amounts of servo standby power during operation calls for proposals for machining methods that reduce power consumption. In this paper, we have developed a novel 5-axes controlled machine tool equipped with an idling-stop function in a feed driving system to reduce the power consumption of machining processes. A problem has been emerged that start-up power increased as the velocity increased. In the present report, we therefore investigate the influence of various programing paths on the power consumption using an idling-stop function when the end milling process is operated in the X-Y plane. As a result, it can be seen that a suitable programing route is occurs for each feed velocity to reduce the power consumption with a developed machine tool.
Analysis of Thermal Fields, Weld Strength and Microstructural Studies of Friction Stir Dissimilar Weldments of AA6082 and AA7075
Authors: Ramakrishna M.V.A. , Srinivas K.
Published: November 2022

This research work aims to investigate thermal fields, weld strength and microstructural analyses of dissimilar welded structures of AA6082 and AA7075 developed using friction stir welding process. Three different tool shapes were used for joining of these plates to study the effect tool profiles on thermal cycles and their behavior on weld strength. The process parameters were considered same for three tool weldments. During welding, peak temperatures and their distribution towards along transverse direction and cooling temperature were recorded using Infra-Red (IR) thermography. The samples were inspected were X-ray radiography test to examine the defects. The tensile strength of the welded structures was evaluated by conducted tension test according to ASTM E/8 standards. Further, the microstructural behavior for three tool profile pins was studied using optical microscopy. The tool profile with cylindrical shape exhibiting higher tensile strength than the other two samples due to lower temperatures and uniformity of heat distribution during welding process. Also, the microstructural studies revealed that the fine grains with proper mixing zones were observed when cylindrical tool was employed. From this research work, IR thermography is most suitable for measuring In-situ temperature profiles even at weld vicinity during welding.
Solvent Effects on the UV-Visible Absorption and Emission of Tris[4-Diethylamino)Phenyl]amine
Authors: Singh Sardul , Singh Nain Abhimanyu , Kumar Amit
Published: November 2022

Tris [4-(diethylamino) phenyl] amine (TDAPA) is an organic molecular semiconductor generally used to enhance the charge transport of the devices for some time now. TDAPA is dissolved in various Polar and Non-polar solvents like DMF, Acetone, Acetonitrile, Ethanol, Methanol, Toluene and Chloroform. Absorption spectrum of solution is recorded using UV-Vis spectroscopy and absorption peak for different solvents were observed in UV and Near-UV region. PL study and Pl Excitation study is also carried out for these solvents. Results for absorption and photoluminescence show some interesting phenomenon of Stokes’ shift. The colour coordinates for respective emission are represented by CIE 1931. The study is successfully carried out for better understanding of effect of these solvents on the optical properties of TDAPA.