bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of different exercise therapies on fatigue in maintenance hemodialysis patients:A Bayesian Network Meta-analysis
Authors:   Chengdu University of Traditional Chinese Medicine, Li wanlin , Yun jie , He siying , Zhou ziqi , He ling
Published: November 2022

Review question / Objective: Population: maintenance hemodialysis patients. Intervention: exercise therapy (resistance exercise； aerobic exercise； resistance combined aerobic exercise； muscle relaxation training； Baduanjin ). Comparison: simple routine nursing. Outcome: fatigue； sleep quality. Study design: randomized controlled trial. Eligibility criteria: Inclusion and exclusion criteria： RCT of study type exercise intervention in MHD patients' fatigue； Study subjects： MHD patients ≥18 years old, regardless of gender, nationality or race； The intervention measures were exercise therapy, including resistance exercise, aerobic exercise, resistance combined aerobic exercise, Baduanjin, muscle relaxation training, etc. The control group was conventional nursing measures or the comparison of the above exercise therapy； Outcome indicators： The primary outcome indicator was fatigue score, and the secondary outcome indicator was sleep quality score； Exclusion criteria： Literature using non-exercise intervention; Non-Chinese and English documents; Unable to obtain the full text or repeated publication of literature; The data cannot be extracted or the extraction is incomplete; There are serious defects in the design of the research experiment.
Az emberség értékéről
Authors: Takács Tibor
Published: November 2022

Founded in 1953 and now in its seventieth year, the jubilee edition of the academic journal Belügyi Szemle, entitled "70 years, 70 thoughts", features essays by invited authors.
Köszöntő gondolatok a hetvenéves Belügyi Szemléhez
Authors: Tóth Tamás
Published: November 2022

Founded in 1953 and now in its seventieth year, the jubilee edition of the academic journal Belügyi Szemle, entitled "70 years, 70 thoughts", features essays by invited authors.
A politika értékelvűsége, a tudomány autonómiája
Authors: Felkai László
Published: November 2022

Founded in 1953 and now in its seventieth year, the jubilee edition of the academic journal Belügyi Szemle, entitled "70 years, 70 thoughts", features essays by invited authors.
Útkereső elődök nyomában
Authors: Cieleszky Péter
Published: November 2022

Founded in 1953 and now in its seventieth year, the jubilee edition of the academic journal Belügyi Szemle, entitled "70 years, 70 thoughts", features essays by invited authors.
“PROKRASTINASI MENGHAMBAT TUGASKU” (STUDI KORELASI: RENDAHNYA SELF EFICACY MENINGKATKAN PROKRASTINASI AKADEMIK MAHASISWA DALAM MENYELESAIKAN TUGAS PERKULIAHAN DI MASA PANDEMI COVID-19)
Authors: Anggoro Husni , Agustina Kemilau Senja Berlian , Savitri Eka Ananda Lintang , Firnanda Fikri Ardiansyah , Kusnadi Starry Kireida
Published: November 2022

Tujuan penelitian ini untuk melihat bagaimana hubungan self-efficacy dengan prokrastinasi akademik mahasiswa dalam meyelesaikan tugas perkuliahan dimasa pandemi COVID-19. Self-efficacy merupakan hal terpenting dalam membantu mahasiswa untuk menyelesaikan tugas perkuliahan dimasa pandemic COVID-19, pengaruh self-efficacy pada cara berpikir individu akan mampu mengarahkan dorongan dan tindakan untuk mencapai suatu hasil yang bersifat positif bagi individu sendiri. Sedangkan Prokrastinasi akademik pada mahasiswa dapat menghambat mereka untuk menyelesaikan suatu mata kuliah tertentu. Semakin lama mereka menunda maka semakin lama pula mereka untuk menyelesaikan tugas mata kuliah tersebut. Penelitian ini menggunakan metode kuantitatif. Skala yang digunakan adalah skala self-efficacy yang diadaptasi dari penelitian yang dilakukan oleh Mulia Sulistyowati, dan skala prokrastinasi kademik yang diadaptasi dari penelitian yang dilakukan Nova Emi Aliance Nainggolan. Subjek dalam penelitian ini sebanyak 116 mahasiswa. Hasil penelitian ini menunjukkan bahwa terdapat hubungan yang negatif, artinya semakin rendah self-efficacy, maka prokrastinasi akademik mahasiswa semakin tinggi dan begitupula sebaliknya semakin tinggi self-efficacy, maka prokrastinasi akademik mahasiswa semakin rendah.
STRATEGI PEMBELAJARAN KOSAKATA MELALUI MEMBACA DI TINGKAT PENDIDIKAN SARJANA
Authors: Astutik Ari , Setyowati Yulis
Published: November 2022

Mahasiswa di fakultas Program Sastra Inggris di Universitas Wijaya Putra, tampaknya mengembangkan setiap keterampilan bahasa secara terpisah khususnya keterampilan kosa kata (vocabulary), sehingga ini menghasilkan pembelajaran kosa kata yang kurang maksimal karena tidak sesuai dengan pengetahuan bacaan yang akan atau yang sedang mereka baca. Dengan mengembangkan strategi belajar kosakata melalui membaca, peneliti ingin mengarahkan mahasiswa agar mempunyai motivasi yang tinggi dalam membaca bermacam-macam literatur baik itu dalam bentuk buku ataupun jurnal ilmiah, karena dari membaca bahan-bahan bacaan tersebut maka akan meningkatkan keterampilan kosakata para mahasiswa secara bersamaan ketika proses membaca. Metode kualitatif digunakan untuk mengumpulkan data serta kuesioner dirancang untuk mahasiswa; beberapa kegiatan membaca dirancang untuk mengeksplorasi strategi paling umum yang digunakan mahasiswa program studi sastra Inggris. Pesertanya seluruh mahasiswa semester I tahun ajaran 2022/2023 fakultas sastra inggris. Mereka dipilih secara acak untuk melakukan kegiatan atau kuesioner, mereka berpartisipasi secara bebas dalam prosedur penelitian untuk mengetahui tentang pendekatan mereka terhadap pembelajaran (vocabulary) kosa kata melalui kegiatan membaca. Hasil dalam penelitian ini adalah kebanyakan mahasiswa memilih menggunakan kamus sebagai alat bantu dalam meningkatkan kosakata mereka. Dari tiga strategi belajar vocabulary (kosakata) yaitu menebak dari konteks bacaan,  menganalisis afiks / awalan dan akar kata, serta yang terakhir adalah dengan menggunakan kamus. Strategi menggunakan kamus adalah strategi terbanyak yang dipilih mahasiswa dalam strategi belajar kosakata melalui membaca dengan total jumlah 59. Disusul dengan strategi yang ke dua yang dipilih mahasiswa adalah menebak dari konteks bacaan dengan total jumlah 54 dan strategi yang terakhir dipilih adalah menganalisiss afiks/awalan dan akar kata dengan total jumlah 4. Ketiga strategi belajar kosakata diatas digunakan untuk belajar kosakata dengan membaca bacaan dari tiga genre bacaan yang berbeda yakni academic reading, job related reading dan personal reading. Penelitian ini diharapkan bisa memberikan kontribusi untuk meningkatkan kesadaran tentang strategi yang dapat membantu mahasiswa mengembangkan pembelajaran kosakata melalui keterampilan membaca secara lebih efektif. Keuntungan berbahasa Inggris yang baik dan benar akan membawa para mahasiswa menuju kesejahteraan di dalam hidup. Dengan mempunyai skill berbahasa inggris yang baik maka mereka akan mendapatkan kepuasan ditempat kerja karena dapat meningkatkan jenjang karier nya serta berkesempatan untuk mendapatkan keuntungan secara finansial bahkan dapat mencapai jenjang karir yang lebih tinggi karena mereka dapat bekerjasama lebih mudah dengan perusahaan asing.
MEDIA RELATIONS HUMAS PEMERINTAH KOTA SURABAYA DI MASA PANDEMI
Authors: Farni Nur'annafi , Nur’annafi Nur’annafi , Ahmadi Ahmadi , Farida Farida
Published: November 2022

Humas Pemerintah Kota Surabaya menyadari bahwa peranan media massa sangat penting bagi pemerintah kota dalam memperoleh publisitas. Sebagai rujukan informasi yang akurat bagi masyarakat di masa pandemi, pelaksanaan media relations akan mempermudah Humas Pemerintah Kota Surabaya dalam melakukan publisitas terkait berbagai informasi dan kebijakan pemerintah kota. Maka peneliti tertarik untuk mengkaji tentang bagaimana perbedaan pelaksanaan kegiatan media relations Humas Pemerintah Kota Surabaya sebelum pandemi dan di masa pandemi dalam memperoleh publisitas. Penelitian ini menggunakan metode deskriptif kualitatif. Teknik pengumpulan data primer melalui wawancara, observasi dan dokumentasi. Analisis data yang digunakan yaitu reduksi, deskripsi, dan penarikan kesimpulan. Dari hasil penelitian ini menunjukan bahwa Humas Pemerintah Kota Surabaya memiliki kecenderungan mempraktikan model Two Way Symmetrical dalam menjalankan tugasnya. Kegiatan media relations yang dilakukan oleh Humas Pemerintah Kota Surabaya baik secara penulisan maupun non penulisan di masa pandemi tetap dijalankan dengan beberapa penyesuaian. Seperti kegiatan press release, press conference, press briefing, press interview, undangan peliputan dan media gathering, yang tetap dilakukan dengan jumlah media yang terbatas dan menerapkan protokol kesehatan (memakai masker, menjaga jarak dan mencuci tangan). Berbagai publisitas yang diperoleh adalah hasil dari pelaksanaan kegiatan media relations yang telah dijalankan secara optimal oleh pihak Humas Pemerintah Kota Surabaya di masa pandemi meskipun dengan berbagai penyesuaian.
REPRESENTASI PERILAKU MENYIMPANG DALAM PENDIDIKAN SEKOLAH PADA FILM ‘BAD GENIUS THE SERIES’ (ANALISIS SEMIOTIKA FERDINAND DE SAUSSURE)
Authors: Afifah Mu’alifatul , Yuliatiningtyas Solikhah , Zulaikha Zulaikha , Joko Iwan
Published: November 2022

Film “Bad Genius The Series” yang diproduksi oleh GDH Entertainment asal Thailand. Film yang terinspirasi dari kisah nyata mengenai kecurangan ujian yang dikemas secara kreatif dan menarik. Film yang merupakan gambaran dari realitas kehidupan social atau kondisi masyarakat yang menampilkan isu tentang pendidikan yang terjadi di Thailand serta dapat dirasakan juga di Indonesia. Rumusan masalah dari penelitian ini adalah Bagaimana perilaku menyimpang dalam pendidikan sekolah direpresentasikan dalam film Bad Genus The Series. Tujuan penelitian ini adalah untuk mengetahui bagaimana representasi perilaku menyimpang dalam pendidikan di sekolah yang terdapat dalam film “Bad Genius The Series”. Hasil penelitian ini menunjukkan beberapa bentuk yang merepresentasikan perilaku menyimpang yang dilakukan oleh para siswa dalam “Bad Genius The Series” yaitu Melihat atau Menyontek jawaban milik orang lain, Memberikan jawaban ujian kepada teman yang lain, Menghindari dan tidak mematuhi peraturan yang sudah ditetapkan untuk pelaksanaan ujian.
CRITICAL DISCOURSE ANALYSIS CLARIFICATION OF BEAR BRAND PRODUCT HOAX DURING THE COVID PANDEMIC
Authors: Agustina Maya , Prawiradiredja Sanhari , Nevretia Nevretia
Published: November 2022

Berita hoaks terkait produk bear brand yang diklaim masyarakat dapat menyembuhkan seseorang yang terkena virus covid. Menggunakan teori analisis wacana kritis model Teun A. Van Dijk dengan menggunakan metode deskripsi kualitatif. Dengan objek dua media online dan tiga berita. Hasil penelitian ini menunjukkan adanya wacana didalam dua media online yaitu tempo.co dan kompas.com. Kedua objek media online tersebut dengan tiga jenis berita peneliti terdapat wacana di dalam teks berita yaitu informasi hoaks ini muncul karna dipicu oleh adanya video yang beredar di media sosial “video membagikan 11 tips cepat pulih yang terkena virus covid” dan juga “video berebut susu beruang dipusat perbelanjaan” hingga masyarakat membuat beragam asumsi hingga para pakar dan para ahli dari universitas IPB dan UGM memberikan komentar terkait kasus ini bahwa berita yang beredar di media sosial dan masyarakat itu tidak benar. Susu beruang tidak dapat mengobati, menyembuhkan atau bahkan memulihkan seseorang yang terkena covid-19.  Kandungan nilai gizi yang ada di susu bear sama saja dengan produk susu lainnya dan mengkonsumsi produk susu beruang tidak cukup untuk meningkatkan kekebalan tubuh disamping itu diperlukan asupan pola makan yang sehat dan bergizi, menjaga kebugaran tubuh, dan langkah yang terakhir mematuhi protokol kesehatan dengan cara 5M yaitu mencuci tangan dengan sabun, memakai masker, menjaga jarak, menjauhi kerumunan, dan membatasi mobilisasi dan interaksi. Serta berita online tempo.co lebih tegas dalam memberikan judul berita sedangkan kompas.com memberikan judul berita lebih ke samar-samar sesuai dengan apa yang dirasakan oleh masyarakat.
ANALISIS SEMIOTIKA MAKNA PESAN KEBUDAYAAN DALAM MUSIK VIDEO WONDERLAND INDONESIA BY ALFFY REV
Authors: Raharjo Firman Aulia Setyo , Annafi Nur , Prawiradiredja Sanhari , Syueb Sudono
Published: November 2022

Penelitian ini bertujuan untuk mengetahui makna dalam Musik Video “Wonderland Indonesia by Alffy Rev”. Dengan melalui analisis semiotika kajian dari John Fiske sebagai metode analisis data yaitu tentang kode-kode televisi yang dibagi menjadi 3 level yaitu level realita, level representasi, dan level ideologi. Hasil dari penelitian ini dapat disimpulkan bahwa makna Musik Video “Wonderland Indonesia by Alffy Rev” dibuat dengan tujuan untuk memperkenalkan kembali budaya Indonesia yang mulai dilupakan oleh anak-anak muda Indonesia sendiri.
BUSINESS SUSTAINABILITY THROUGH E-COMMERCE: A MYTH OR REALITY IN NIGERIA
Authors: Akintoye Ishola R. , Ajayi Modupe , Joshua Abimbola , Okunlola Abiodun F.
Published: November 2022

A succinct exploration of business sustainability via an e-commerce platform was examined in the study. Its myth and reality permeate its adoption, use, and acceptability within the context of our economic, social, and environmental assumptions were also validated. To achieve its aim, exploratory methodology, which compared benefits and challenges among the three main elements – business, users, and authority; in the application of the e-commerce platforms and channels in the country was examined. The result showed mixed outcomes. On one side, there are huge benefits to businesses in adopting e-commerce while on the other, challenges such as optimal patronage due to cultural trust gaps, user-confidence, poor connectivity, and government selective policy drive. Based on this outcome, it is concluded that; business sustainability via e-commerce in the country is relatively weak and can be improved upon if, end-users policy drive is taken into serious consideration.
How editors can help authors write better papers: Beyond journals and articles
Authors: Marusic Ana , Marusic Matko
Published: November 2022

We present the experience of journal editors in improving the quality of published papers. As the editors of the Croatian Medical Journal, a journal from the so-called scientific periphery, we realized, very early after the start of the journal in 1991, that our authors needed significant assistance with their articles. We worked individually with journal authors and then moved this activity to the next stage – intensive workshops for authors. The work with the journals enabled us to extend these activities to graduate and postgraduate students – future authors.
GIS-based multi-criteria territorial suitability assessment for insect farms: a case study for North Italy
Authors: Fiorillo E. , Maistrello L. , Chieco C.
Published: November 2022

Although environmental sustainability and economic feasibility frameworks have been developed to evaluate the impact of insect farms, significant studies on the development of territorial suitability methods specifically tailored to insect production have not yet been performed. This work proposes a GIS-based multi criteria decision making analysis to evaluate the suitability of a territory to the installation of insect farms. A case study developed specifically for black soldier flyHermetia illucens(HI) insect farms in Emilia-Romagna region (North Italy) is presented. This is an area which, due to its agro-industrial nature and the consequent large production of related waste and by-products, is an optimal candidate for the installation of insect farms. Nine physical, environmental, and economic criteria were assessed. A raster spatial layer for each criterion was obtained, and their values were standardised. The criteria were weighted using the analytical hierarchical process, based on expert opinion recorded via an online questionnaire. The resulting weights were used to combine the single criterion maps using a weighted linear combination procedure and generate, after reclassification, the final suitability map. This map indicates the areas suitable for insect farms at the local level and provides indications for estimating suitability at regional and provincial level. The results showed that 56.2% of the study area was deemed unsuitable, and 43.8% was determined suitable for an HI insect farm; best locations were found around the main agro-industrial centres of the Po valley. The proposed methodology can be easily adapted to other breeding models, insects or study areas and adds valuable information in the development of guidelines for industrial-scale insect farms.
What Do Women Want? Identifying Life Goals in a Community-Based Sample of Women Aged ≥60 Years
Authors: Terrell Carrie A. , Martins Summer L. , Delkoski Stephanie L. , Torkelson Carolyn J.
Published: November 2022

Few studies have examined women's perspectives on their health and priorities in older age. In the current study, we administered a cross-sectional survey to women aged ≥60 years, recruited at a large community event in 2019. Participants (
N
= 303; mean age = 68 years) reported up to three 12-month life goals in open-text fields (
N
= 1,053 goals). Our qualitative analysis identified 25 themes under four domains: Health and Wellness (
n
= 339 goals), Work and Leisure (
n
= 316 goals), Relationships (
n
= 199 goals), and Personal Growth (
n
= 170 goals). The most frequent themes pertained to family relationships, travel, staying healthy, and physical activity. Findings did not vary by participants' comorbidity status. Women have diverse aspirations as they age, including nurturing relationships, acquiring novel skills and experiences, and maintaining overall health and wellness. Gerontological nurses can better meet the needs of this population by expanding their awareness of patients' life goals and partnering with women to optimize health to achieve these goals. [
Journal of Gerontological Nursing, 48
(12), 25–33.]
Open to the Public: Serbs and Ethnic Crossover in the United States
Authors: Larson Ethan
Published: November 2022

Diasporas are often imagined as impermeable communities. Yet the boundaries of the Serbian diaspora in the United States were surprisingly porous to certain outsiders, such as Ruth Mitchell, who routinely dressed as a Chetnik to address Serbian immigrants. Mitchell’s act of ethnic crossover, this paper argues, fits into a broader pattern of ethnic outsiders joining Serbian organizations in the United States. Four case studies besides Ruth Mitchell are discussed: Eleanor Calhoun, Johann Blose, Charles DeHarrack, and Frank Melford. Diplomats acted as gatekeepers to these Serbophiles, limiting access to emigrant social and political networks as they saw fit—but only rarely was the Serbophiles’ ethnic background a factor.
Analysis of Students’ Cognitive Presence and Perception in a Custom-Designed Virtual Problem Based Learning Assignment
Authors: Choo Chee Yan , Fahrni Mathumalar Loganathan , Long Chiau Ming
Published: November 2022

All the teaching and learning activities except laboratory-based practicals remained conducted virtually during the transition from the Covid-19 pandemic to the endemic phase. The problem-based assignment for Pharmaceutical Analysis was conducted virtually.  This study aims to evaluate students’ level of engagement and perception of virtual engagement to complete an online problem-based assignment on real situations using the cooperative Jigsaw model. Jamboard was used as an online communication tool to connect the students and facilitators. The content of the written discussion posted on the Jamboard and the questionnaire survey were analysed to establish the level of engagement. The student’s perception of virtual engagement was based on a questionnaire survey using descriptive analysis.  Analysis of the student’s opinion posted on the Jamboard showed the presence of cognitive, social, and teaching components in the level of engagement during the virtual discussion.  The information from the internet is borderless and the facilitators need to be knowledgeable to explain, guide, and stimulate higher-order thinking among the students. With careful course design, the Jigsaw cooperative activity on real problem-based questions could use to facilitate collaborative problem-solving skills among the students.
Construction and Adjustment Methods for Teacher-Student Relationship in College Student Management Based on Big Data Analysis
Authors: Xi Limin , Zhang Lei , Chen Buying
Published: November 2022

Building a harmonious Teacher-Student Relationship (TSR) is a necessary work for college student management, because different TSRs can result in different effects in student management and cultivation. However, in existing studies, the definitions of harmonious TSR given by different scholars are dimensionless, the understandings of the nature of TSR is not thorough enough, and the analysis of the influencing factors of TSR often lacks the support of theoretical evidences. To overcome these shortcomings, this paper aims to study the construction and adjustment methods for the TSR in college student management based on big data analysis. At first, the paper investigated the daily behavioral features of college students on online management platforms; then, with the help big data analysis and data processing techniques, this paper calculated the fitness degree of harmonious TSR between college students and the counselors and other administrators who engaged in student management works and have interacted with them. After that, based on the calculation results of the said fitness degree, this paper built a basic interactive network for college student management works, and gave the method for dividing student management groups. At last, experimental results verified the effectiveness of the proposed algorithm.
Suicide Response in American Muslim Communities: A Community Case Study
Authors: Suleiman Kamal , El-Gabalawy Osama , Zia Belal , Awaad Rania
Published: November 2022

This community case study describes the experiences of two neighboring Muslim communities in the United States, following respective incidents of suicide. Case summaries are first presented to contextualize the community response to the suicides. Subsequently, the discussion highlights relevant cultural and religious factors that impacted the responses of mosque leadership, mental health professionals, and the communities at large. Concerns related to the deceased’s afterlife, community connectedness, privacy, shame, and communication barriers were prominent in each case and shaped the courses of response. The COVID-19 pandemic and divergent responses to external support played significant roles in creating disparate outcomes in these communities. The discussion emphasizes the need for dissemination of evidence-based, religiously grounded, and culturally competent curricula for implementing mental health awareness programming and long-term suicide prevention efforts. Insights about cultural and religious factors influencing community responses were derived from the described cases in this paper and informed the development of a comprehensive suicide prevention, intervention, and postvention manual and training program tailored for Muslim communities.
The Relevance of CIER in the Italian Circular Plastics District
Authors: Cuonzo Francesco , Carrassi Paolo , Magnini Giulio , Spinosa Mariavittoria , Cocomero Melania , Casillo Vincenzo , Madonna Marco , Grassi Giorgia
Published: November 2022

The investment process in a circular economy project develops along a path that starts from the identification of the target project in which the preliminary objective and the investment opportunities are defined, consistent with the financial capacity of the company and with the role assigned to the project as part of the company's core business. Secondly, it is necessary to identify the strategic profile that the investment in this project carries out for the activities already progressively carried out by the company: since the objectives are the optimization of the profitability and liquidity of the investment, together with the returns of reputation competence. Therefore, the company's top management must be able to identify growth potential guaranteed by a solid business idea, also guaranteeing the sustainability of the flow of operations. The CIER company, now established in its sector, recycling of plastic materials, fits into this framework. This company is an exemplary example of how it is possible to develop and integrate a business project that is circular.
A Content-Based Approach to Medical Image Retrieval
Authors: K. Anitha , K. Naresh , D. Rukmani Devi
Published: November 2022

Medical images stored in distributed and centralized servers are referred to for knowledge, teaching, information, and diagnosis. Content-based image retrieval (CBIR) is used to locate images in vast databases. Images are indexed and retrieved with a set of features. The CBIR model on receipt of query extracts same set of features of query, matches with indexed features index, and retrieves similar images from database. Thus, the system performance mainly depends on the features adopted for indexing. Features selected must require lesser storage, retrieval time, cost of retrieval model, and must support different classifier algorithms. Feature set adopted should support to improve the performance of the system. The chapter briefs on the strength of local binary patterns (LBP) and its variants for indexing medical images. Efficacy of the LBP is verified using medical images from OASIS. The results presented in the chapter are obtained by direct method without the aid of any classification techniques like SVM, neural networks, etc. The results prove good prospects of LBP and its variants.
Artificial Intelligence and Reliability Metrics in Medical Image Analysis
Authors: G. Yamini , Ganapathy Gopinath
Published: November 2022

Artificial intelligence (AI) in medical imaging is one of the most innovative healthcare applications. The work is mainly concentrated on certain regions of the human body that include neuroradiology, cardiovascular, abdomen, lung/thorax, breast, musculoskeletal injuries, etc. A perspective skill could be obtained from the increased amount of data and a range of possible options could be obtained from the AI though they are difficult to detect with the human eye. Experts, who occupy as a spearhead in the field of medicine in the digital era, could gather the information of the AI into healthcare. But the field of radiology includes many considerations such as diagnostic communication, medical judgment, policymaking, quality assurance, considering patient desire and values, etc. Through AI, doctors could easily gain the multidisciplinary clinical platform with more efficiency and execute the value-added task.
On the Implementation of a Fragile Medical Image Watermarking Technique Using Saliency and Phase Congruency
Authors: Basu Abhishek , Dutta Soumadeb
Published: November 2022

The recent developments of enormous computer networks have invoked insecurities related to copyright theft of digital media. To be precise, the virtual sharing of medical images over networks with a novel desire of improved medical diagnosis has led to the tampering of sensitive patient identity information. In this chapter, the authors have exemplified the need of watermarking with fragile medical image watermarking using saliency and phase congruency. Initially, the saliency and phase congruency methodologies are applied on the original medical image to highlight the object features. Based on the feature map, a mask is generated which segregates the area of interest from the portions containing visual medical information. An encrypted text, containing identity of the patient, is embedded into the area of interest of the image. The results of imperceptibility and fragility criteria are satisfactory towards the implementation of a fragile watermark as the extracted watermark is found to be corrupted upon unfaithful image processing modifications.
Implementation of a Reversible Watermarking Technique for Medical Images
Authors: Karmakar Ranit , Basu Abhishek
Published: November 2022

Electronic health records (EHR) contain patients' medical as well as personal details. With the increased use of digital media, these data are stored and transferred through the electronic media all over the world. This makes it vulnerable to unauthorized people. Digital image watermarking can be a useful process of protecting these data from attacker but causes severe and unrecoverable damage to cover media. In the case of highly sensitive images like medical images, this might creates a problem during further diagnosis. In this chapter, a reversible data hiding algorithm is proposed which also is capable of holding a large chunk of data without affecting the cover media. The main cover image is first reconstructed and hidden behind a bigger media and then the extra pixels are used to hide encrypted forms of EHR data along with an authentication signature. As EHR data and the digital signature is passed through various encryption stages while encoding, it is made more secure. The algorithm is developed on the spatial domain adding some cautious measures which made it fragile as well.
Demystification of Deep Learning-Driven Medical Image Processing and Its Impact on Future Biomedical Applications
Authors: Udendhran R. , M. Balamurugan
Published: November 2022

The recent growth of big data has ushered in a new era of deep learning algorithms in every sphere of technological advance, including medicine, as well as in medical imaging, particularly radiology. However, the recent achievements of deep learning, in particular biomedical applications, have, to some extent, masked decades-long developments in computational technology for medical image analysis. The methods of multi-modality medical imaging have been implemented in clinical as well as research studies. Due to the reason that multi-modal image analysis and deep learning algorithms have seen fast development and provide certain benefits to biomedical applications, this chapter presents the importance of deep learning-driven medical imaging applications, future advancements, and techniques to enhance biomedical applications by employing deep learning.
Effective and Accurate Diagnosis Using Brain Image Fusion
Authors: Rajagopal Sivakumar , Gopal Babu
Published: November 2022

Medical imaging techniques are routinely employed to create images of the human system for clinical purposes. Multi-modality medical imaging is a widely used technology for diagnosis, detection, and prediction of various tissue abnormalities. This chapter is focused on the development of an improved brain image processing technique for the removal of noise from a magnetic resonance image (MRI) for accurate image restoration. Feature selection and extraction of MRI brain images are processed using image fusion. The medical images suffer from motion blur and noise for which image denoising is developed through non-local means (NLM) filtering for smoothing and shrinkage rule for sharpening. The peak signal to noise ratio (PSNR) of improved curvelet based self-similarity NLM method is better than discrete wavelet transform with an NLM filter.
Detection of Tumor From Brain MRI Images Using Supervised and Unsupervised Methods
Authors: S. Kannan , S. Anusuya
Published: November 2022

Brain tumor discovery and its segmentation from the magnetic resonance images (MRI) is a difficult task that has convoluted structures that make it hard to section the tumor with MR cerebrum images, different tissues, white issue, gray issue, and cerebrospinal liquid. A mechanized grouping for brain tumor location and division helps the patients for legitimate treatment. Additionally, the method improves the analysis and decreases the indicative time. In the separation of cerebrum tumor, MRI images would focus on the size, shape, area, and surface of MRI images. In this chapter, the authors have focused various supervised and unsupervised clustering techniques for identifying brain tumor and separating it using convolutional neural network (CNN), k-means clustering, fuzzy c-means grouping, and so on.
Layer-Wise Tumor Segmentation of Breast Images Using Convolutional Neural Networks
Authors: Krishnaraj Nishanth , Mekala A. Mary , M. Bhaskar , Nersisson Ruban , Joseph Raj Alex Noel
Published: November 2022

Early prediction of cancer type has become very crucial. Breast cancer is common to women and it leads to life threatening. Several imaging techniques have been suggested for timely detection and treatment of breast cancer. More research findings have been done to accurately detect the breast cancer. Automated whole breast ultrasound (AWBUS) is a new breast imaging technology that can render the entire breast anatomy in 3-D volume. The tissue layers in the breast are segmented and the type of lesion in the breast tissue can be identified which is essential for cancer detection. In this chapter, a u-net convolutional neural network architecture is used to implement the segmentation of breast tissues from AWBUS images into the different layers, that is, epidermis, subcutaneous, and muscular layer. The architecture was trained and tested with the AWBUS dataset images. The performance of the proposed scheme was based on accuracy, loss and the F1 score of the neural network that was calculated for each layer of the breast tissue.
Cascaded Dilated Deep Residual Network for Volumetric Liver Segmentation From CT Image
Authors: Mourya Gajendra Kumar , Gogoi Manashjit , Talbar S. N. , Dutande Prasad Vilas , Baid Ujjwal
Published: November 2022

Volumetric liver segmentation is a prerequisite for liver transplantation and radiation therapy planning. In this paper, dilated deep residual network (DDRN) has been proposed for automatic segmentation of liver from CT images. The combination of three parallel DDRN is cascaded with fourth DDRN in order to get final result. The volumetric CT data of 40 subjects belongs to “Combined Healthy Abdominal Organ Segmentation” (CHAOS) challenge 2019 is utilized to evaluate the proposed method. Input image converted into three images using windowing ranges and fed to three DDRN. The output of three DDRN along with original image fed to the fourth DDRN as an input. The output of cascaded network is compared with the three parallel DDRN individually. Obtained results were quantitatively evaluated with various evaluation parameters. The results were submitted to online evaluation system, and achieved average dice coefficient is 0.93±0.02; average symmetric surface distance (ASSD) is 4.89±0.91. In conclusion, obtained results are prominent and consistent.
Advanced Object Detection in Bio-Medical X-Ray Images for Anomaly Detection and Recognition
Authors: Modwel Garv , Mehra Anu , Rakesh Nitin , Mishra K. K.
Published: November 2022

The human vision system is mimicked in the format of videos and images in the area of computer vision. As humans can process their memories, likewise video and images can be processed and perceptive with the help of computer vision technology. There is a broad range of fields that have great speculation and concepts building in the area of application of computer vision, which includes automobile, biomedical, space research, etc. The case study in this manuscript enlightens one about the innovation and future scope possibilities that can start a new era in the biomedical image-processing sector. A pre-surgical investigation can be perused with the help of the proposed technology that will enable the doctors to analyses the situations with deeper insight. There are different types of biomedical imaging such as magnetic resonance imaging (MRI), computerized tomographic (CT) scan, x-ray imaging. The focused arena of the proposed research is x-ray imaging in this subset. As it is always error-prone to do an eyeball check for a human when it comes to the detailing. The same applied to doctors. Subsequently, they need different equipment for related technologies. The methodology proposed in this manuscript analyses the details that may be missed by an expert doctor. The input to the algorithm is the image in the format of x-ray imaging; eventually, the output of the process is a label on the corresponding objects in the test image. The tool used in the process also mimics the human brain neuron system. The proposed method uses a convolutional neural network to decide on the labels on the objects for which it interprets the image. After some pre-processing the x-ray images, the neural network receives the input to achieve an efficient performance. The result analysis is done that gives a considerable performance in terms of confusion factor that is represented in terms of percentage. At the end of the narration of the manuscript, future possibilities are being traces out to the limelight to conduct further research.
Performance Analysis of VGG19 Deep Learning Network Based Brain Image Fusion
Authors: Rajangam Vijayarajan , N. Sangeetha , R. Karthik , Mallikarjuna Kethepalli
Published: November 2022

Multimodal imaging systems assist medical practitioners in cost-effective diagnostic methods in clinical pathologies. Multimodal imaging of the same organ or the region of interest reveals complementing anatomical and functional details. Multimodal image fusion algorithms integrate complementary image details into a composite image that reduces clinician's time for effective diagnosis. Deep learning networks have their role in feature extraction for the fusion of multimodal images. This chapter analyzes the performance of a pre-trained VGG19 deep learning network that extracts features from the base and detail layers of the source images for constructing a weight map to fuse the source image details. Maximum and averaging fusion rules are adopted for base layer fusion. The performance of the fusion algorithm for multimodal medical image fusion is analyzed by peak signal to noise ratio, structural similarity index, fusion factor, and figure of merit. Performance analysis of the fusion algorithms is also carried out for the source images with the presence of impulse and Gaussian noise.
Deep Learning and Medical Imaging
Authors: Zayed Nourhan Mohamed , Elnemr Heba A.
Published: November 2022

Deep learning (DL) is a special type of machine learning that attains great potency and flexibility by learning to represent input raw data as a nested hierarchy of essences and representations. DL consists of more layers than conventional machine learning that permit higher levels of abstractions and improved prediction from data. More abstract representations computed in terms of less abstract ones. The goal of this chapter is to present an intensive survey of existing literature on DL techniques over the last years especially in the medical imaging analysis field. All these techniques and algorithms have their points of interest and constraints. Thus, analysis of various techniques and transformations, submitted prior in writing, for plan and utilization of DL methods from medical image analysis prospective will be discussed. The authors provide future research directions in DL area and set trends and identify challenges in the medical imaging field. Furthermore, as quantity of medicinal application demands increase, an extended study and investigation in DL area becomes very significant.
GAN-Based Medical Images Synthesis
Authors: Yang Huan , Qian Pengjiang
Published: November 2022

Medical images have always occupied a very important position in modern medical diagnosis. They are standard tools for doctors to carry out clinical diagnosis. However, nowadays, most clinical diagnosis relies on the doctors' professional knowledge and personal experience, which can be easily affected by many factors. In order to reduce the diagnosis errors caused by human subjective differences and improve the accuracy and reliability of the diagnosis results, a practical and reliable method is to use artificial intelligence technology to assist computer-aided diagnosis (CAD). With the help of powerful computer storage capabilities and advanced artificial intelligence algorithms, CAD can make up for the shortcomings of traditional manual diagnosis and realize efficient, intelligent diagnosis. This paper reviews GAN-based medical image synthesis methods, introduces the basic architecture and important improvements of GAN, lists some representative application examples, and finally makes a summary and discussion.
Detection and Segmentation of Medical Images Using Generic Algorithms
Authors: Khandhar Hardev Mukeshbhai , Bhatt Chintan M. , Fong Simon
Published: November 2022

Image processing plays an indispensable and significant role in the development of various fields like medical imaging, astronomy, GIS, disaster management, agriculture monitoring, and so on. Medical images which are recorded in digital forms are processed by high-end computers to extract whatever information we desire. In the fast-developing modern world of medical imaging diagnosis and prognosis, where manual photo interpretation is time-consuming, automatic object detection from devices like CT-Scans and MRIs has limited potential to generate the required results. This article addresses the process of identifying Region of Interests in cancer based medical images based on combination of Otsuâ€™s algorithm and Canny edge detection methods. The primary objective of this paper is to derive meaningful and potential information from medical image in different scenarios by applying the image segementation in combination with genetic algorithms in a robust manner to detect region of interest.
Automatic Screening of Diabetic Maculopathy Using Image Processing
Authors: Reddy Shweta
Published: November 2022

Retinal imaging is a challenging screening method for detection of retinal abnormalities. Diabetic Maculopathy (DM) is a condition that can result from retinopathy. Regular screening is necessary for diabetic maculopathy in order to identify the risk of vision loss. Maculopathy is damage to macula, the key region responsible for high sharp colour vision. Diabetic Retinopathy and Diabetic Maculopathy needs regular observation in order to indicate visual impairment risk. In this article, the author first presents a brief summary of diabetic maculopathy and its causes. Then, an exhaustive literature review of different automated DM diagnosis systems offered. It is important for ophthalmologists to have an automated system which detects early symptoms of the disease and yields a high accurate result. A vital assessment of the image processing techniques used for DM feature detection is projected in this paper. Various methods have been proposed to identify and classify DM based on severity level.
Innovative Method of Embedding Optical Fiber inside Titanium Alloy Utilizing Friction Stir Forming
Authors: Tabatabaei Hamed Mofidi , Ohashi Takahiro , Nishihara Tadashi
Published: November 2022

The development of FBG (Fiber Bragg Grating) sensors is essential for intelligent parts of airplanes to achieve ultra-lightweight structures and intelligent aviation control. Awaiting solution is embedding technology of optical fiber sensors into the base material of the parts; however, it has been challenging to embed fibers into high melting temperature point alloys like titanium-based materials without having any defects. Present research fulfills the mentioned demands effectively by utilizing Friction Stir Forming (FSF). Precisely, optical fiber has been placed into a guide slit inside the titanium sheet. Then, FSF was applied to the surface of the titanium. As a result, titanium plasticizes and flows into the guide slit. This mechanically interlocks the optical fiber inside the titanium alloy. This solid-state stirring process can bury sensors inside the titanium to protect the sensor from harsh environments. Embedded sensors will detect the strain and temperature of the host titanium in real-time. Moreover, this research can have further considerable effects on the areas like aerospace and artificial intelligence systems that demand real-time condition monitoring systems.
Economic Consequences of Population Aging in Sri Lanka
Authors: Shafna A. M. , Gunaratne L. H. P.
Published: November 2022

The population aging is unprecedented in human history that brings numerous socio-economic consequences. In this context, this study was with the aim of understanding the impact of population aging on the economic growth of Sri Lanka and the role of the current pension system in Sri Lanka in determining the impact of population aging on economic growth. The study applies a growth accounting framework to evaluate the impacts of population aging on per capita output growth in Sri Lanka, from 1960 - 2019. The Structural Equation Model (SEM) and the dynamic regression with error ARIMA model were used to meet the study’s objectives. The findings revealed that the aging population has a significant negative impact on Sri Lanka’s economic growth, while total factor productivity growth and capital deepening have a favorable impact. Further, Sri Lanka’s present pension system greatly tempered the direct association between population aging and total factor productivity increase. Overall, Sri Lanka’s current pension system exacerbates the negative effects of population aging on economic growth. The findings of the study can be used to draw several policy implications for the planning of welfare and economic development programs in Sri Lanka.
Shared Frailty Model for Joint Survival Data - A Simulation Study
Authors: Liyanage J. C. , Karunarathna G. H. S.
Published: November 2022

Performing a survival analysis, allows investigating factors that contribute to outcome over time. Though a considerable amount of literature has addressed this area, analysis of multiple survival responses has not received sufficient attention in past literature. The joint modeling fits well when there are multiple survival responses for the same study unit and it can provide improved results than fitting univariate models separately since the correlation between the responses can be captured through a joint model. Therefore, the aim of this study was to propose a joint modeling approach, in which the linkage between two survival responses(for simplicity, in this research bivariate lifetime data have been considered) was derived by sharing a common random effect under different random effect distributions through parametric forms of the baseline hazard function. In this study, Gamma and Normal random effect distributions and Exponential and Weibull parametric survival distributions were considered. The performance of the Shared Frailty model was compared with two Ordinary Proportional Hazard models through a simulation study, by fitting models for simulated data in three different sample sizes with 20% and 40% censoring proportions in different correlation structures. Bias, Coverage Probability (CP) and Mean Squared Error (MSE) were the performance measures used. Parameter estimates showing relatively low bias, high CP, and minimal MSE under the joint random effect model confirmed the suitability of the proposed model to capture joint survival data, surpassing the fit of two univariate models. Also, the results interpreted, Gamma distributed random effects to be more suitable with Exponential survival times while Normal random effects with Weibull survival times.
Кинетические коэффициенты в формализме временны́х функций Грина при конечной температуре
Authors: Krivorol Viacheslav Aleksandrovich , Nalimov Mikhail Yur'evich
Published: November 2022

Обсуждается микроскопическое обоснование возникновения диссипации в модельной ферми- или бозе-системе со слабым локальным взаимодействием. Рассматривается динамика равновесных флуктуаций в формализме Келдыша-Швингера, обсуждается связь диссипации с пинчевыми сингулярностями диаграмм теории возмущений. С помощью уравнения Дайсона определен и вычислен в двухпетлевом приближении параметр диссипации. Показано, что он является прямым аналогом кинетического коэффициента Онзагера и связан с наличием затухания в квазичастичном спектре.