bluuebunny/crossref_metadata_2025 huggingface dataset:
Information Technology in Healthcare: A Systematic Literature Review
Authors: Reza Asadi Amir , P Akinremi Taiwo , Said Hazem
Published: June 2024

Aim/Purpose.
The aim of this study is to recognize the factors that contributed to the development of IT in the healthcare industry.

Background.
The healthcare Information Technology (IT) solutions market has experienced remarkable growth, with the healthcare sector emerging as a $303 billion industry. However, despite its substantial size, the healthcare industry has faced criticism for its slow adoption of innovative technologies. This study aims to explore factors driving the evolution of IT in the healthcare sector.

Methodology.
The researchers conducted a systematic literature review, searching the PubMed and Emerald databases for relevant peer-reviewed articles. After filtering based on defined criteria, 433 articles were included for analysis. Thematic analysis was applied to the abstract of articles which spanned the period of 1997 to 2023.

Contribution.
This study provides a conceptual framework elucidating the key factors driving the evolution of IT in the healthcare industry. By systematically analyzing the existing literature, the research identifies four overarching themes – government policies, technological potentials, healthcare delivery needs, and organizational motivations – that have propelled the development and adoption of healthcare IT solutions.
Provide a conceptual model for understanding, and design of the healthcare it solutions.

Findings.
Based on the analysis in this paper, four themes emerged: government policies promoting IT adoption through initiatives like incentives for electronic health records; technological breakthroughs enabling new healthcare IT capabilities; healthcare delivery needs to drive IT integration for improved quality and safety; and patient experience and organizational motivations to leverage IT for streamlining processes and knowledge management.

Recommendations for Practitioners.
The conceptual model can guide practitioners in developing IT solutions aligned with policy drivers, technological capabilities, care delivery needs, and organizational imperatives.

Recommendations for Researchers.
The conceptual framework developed in this study offers a lens for researchers across disciplines to continue investigating the role of information technology in the healthcare industry.

Impact on Society.
Examining the evolution of IT in the healthcare industry revealed the importance of information technology in enhancing the delivery and affordability of healthcare services and addressing issues of accessibility and inequality.

Future Research.
Future research will explore global perspectives showcasing the successful impact of IT on healthcare, as emerging technologies impact healthcare delivery and patient outcomes.
Table of Contents: Issues in Informing Science and Informing Technology. Volume 21, 2024
Authors: Cohen Eli
Published: June 2024

Table of Contents for IISIT Volume 21, 2024
Stability Assessment of an Ore Mill Electric Drive Using Machine Learning
Authors: Baghdasaryan Marinka , Hovhannisyn Vardan
Published: June 2024

The relevance of the study is due to the need to improve electric drive systems operated in harsh conditions. The goal of the study is to create a model for assessing the state of stability of the electric drive of an ore mill using machine learning capabilities, which will provide high performance and the ability to work consistently in different systems. Various sustainability assessment models have been developed based on 6 machine learning algorithms. The study and comparison of models built using artificial neural networks (ANN) of different architectures was carried out using various learning methods. The expediency of using the Tree and ANN algorithms to develop a model for assessing electric drive stability is substantiated. The novelty of the results obtained lies in the fact that the model has high accuracy, high speed, and the ability to detect instability in uncertain operating modes of the electric motor of an electric drive, as well as the possibility of coordinated operation with various systems. The practical value is that the model allows, at an intellectual level, to provide effective control and fault diagnosis of complex electric drive systems, which cannot be achieved using the known methods. Doi: 10.28991/HIJ-2024-05-02-01 Full Text: PDF
Innovative Date Fruit Classifier Based on Scatter Wavelet and Stacking Ensemble
Authors: Al-Kharaz Ali A. , Alwahhab Ahmed B. A. , Sabeeh Vian
Published: June 2024

Dates are essential fruits loaded with vital nutrients that keep bones healthy and prevent bone-related disorders. Approximately 8.46 million tons of different types of dates are cultivated and produced annually around the globe. There are more than 400 types of dates that are time-consuming and expensive to produce. Classifying them using conventional methods is labor-intensive, and this is one of the biggest problems for the date industry. Dataset fruit classification plays a vital role in the food industry. Dates can be classified from a luxury class to a less quality class. Accordingly, the food industry needs an automotive date fruit classifier that can work in food factories. This study proposes a pioneering method to classify date fruit that relies on extracting features from the texture of dates using Scattering Wavelet Transformation (SWT). The SWT yields in numeric coefficients were found to be immune to the deformation of invariants. This feature set trains an ensemble classifier that combines a voting mechanism to eliminate overfitting. The ensemble classifier consists of a random forest, a support vector machine classifier, and a logistic regression hyper-learner. Our novel approach was tested on two benchmarked datasets. The first data set scored F1 between 0.95 and 1.0 at the same time. The second dataset registered F1 between 0.96 and 1.0 in each of the 20 date classes. Some dates are close to each other in texture, resulting in high false positives or recall, causing a lower F1 score accuracy degree. The novelty of this approach comes from the featured representative of each date class, relying on the texture of the fruit as a discriminative feature, not on the fruit shape or color, which may not be robust enough as distinguishable features, especially in date classes that are close to each other in shape. Doi: 10.28991/HIJ-2024-05-02-010 Full Text: PDF
Students’ Flow Experience of Using AI-Powered Online English Learning Platforms
Authors: Wu Chang-Hong , Fan Wei-Shang
Published: June 2024

Objectives: This research aims to explain the impact of flow’s antecedents on flow experience. Furthermore, this research explores the intention of students to continue using online AI-powered English learning platforms. Methodology: This study gathered data from 300 online students enrolled in AI-powered English learning platforms in Taiwan, with data collection facilitated by a research company in the country. Findings: According to the findings, flow was significantly associated with continuous intention. In terms of antecedents of flow, information quality, service support quality, and intrinsic motivation were significant, whereas confirmation, service quality, and instructor quality were not significant. Flow was found to have significant associations with perceived usefulness and satisfaction. Furthermore, confirmation significantly impacted perceived usefulness and satisfaction. Moreover, perceived usefulness was significantly associated with satisfaction but had no association with continuous intention. Lastly, both intrinsic motivation and satisfaction were associated with continuous intention. Novelty/Improvement:This research delves into the dynamic interplay between students' experiences and the adoption of AI-powered online English learning platforms. The study employed a comprehensive framework, including flow, a technology acceptance model, motivation, and an expectation confirmation model. Doi: 10.28991/HIJ-2024-05-02-011 Full Text: PDF
Preventing Impaired Driving Using IoT on Steering Wheels Approach
Authors: Abdul Razak Siti Fatimah , Yogarayan Sumendra , Ullah Arif
Published: June 2024

To drive safely, one must be attentive, coordinated, have good judgment, and be able to respond quickly to changing conditions. In certain countries, improving safety may depend largely on reducing the number of impaired drivers on the road. Therefore, solutions are required to reduce the risk that is posed on the road by drivers who have been consuming alcohol while driving. Previous research has proposed the use of sensors for detecting driver impairment caused by alcohol intoxication. However, relying on a gas sensor alone may not be appropriate for detection. To reduce drunk driving, this study proposes an Internet of Things (IoT)-based tool that measures heart rate and analyzes the breath of a driver for traces of alcohol. The tool represents a vehicle that is made up of a DC motor. In the circumstance that the tool detects a higher than resting heart rate in the driver as well as an amount of alcohol in the driver’s breath sample, the tool will immediately power down the DC motor and send an SMS to the registered emergency contact with the driver’s precise position using the GPS module. The initial prototype demonstrates the tool as a potential aftermarket accessory for vehicles. The implication of this paper is that the designed tool might be of practical use to researchers in their attempts to determine and obtain information on alcohol intoxication. Doi: 10.28991/HIJ-2024-05-02-012 Full Text: PDF
A Consumer Data Privacy Protection Model Based on Non-Parametric Statistics for Dynamic Data Publishing in e-Commerce Platforms
Authors: Jia Jiao
Published: June 2024

Objectives: Consumer data privacy on e-commerce platforms is increasingly crucial. This study aims to investigate privacy protection mechanisms, particularly focusing on personal and corporate secrets. It seeks to understand individual perspectives on privacy and preferences for data disclosure. The primary objective is to explore methods for safeguarding personal information while maintaining data integrity. Methods/Analysis: We employ non-parametric statistical techniques to analyze consumer behavior and preferences on e-commerce platforms. This involves examining patterns of data disclosure and identifying sensitive information shared by users. By studying communication dynamics and recording practices, we assess the efficacy of current privacy protection measures. Novelty/Improvement: This study contributes to the understanding of consumer privacy protection by emphasizing the importance of non-parametric statistical methods in e-commerce research. Our findings underscore the need for enhanced privacy measures. We advocate for further research and development of innovative privacy-enhancing technologies to address evolving privacy challenges in online commerce. Findings:Our research highlights the significance of personal privacy concerns in e-commerce settings. We identify a spectrum of privacy attitudes among users, ranging from strict confidentiality to selective disclosure. Furthermore, our analysis reveals potential vulnerabilities in current privacy safeguards, particularly regarding the collection and storage of sensitive data on e-commerce platforms. Doi: 10.28991/HIJ-2024-05-02-013 Full Text: PDF
The Measurement of Blockchain Technology in Financial Reports in Commercial Banks
Authors: Zaqeeba Nidal , Alqudah Hamza , Rawashdeh Badi S. , Lutfi Abdalwali , Alrawad Mahmaod , Almaiah Mohammed A.
Published: June 2024

The objective of the present study is to measure the impact of blockchain technology on financial reports. The study utilizes a time series analysis covering eleven commercial banks listed on the Amman Stock Exchange from 2009 to 2019. Two key measures, namely other operating expenses and customer deposits are employed in the Return on Assets (ROA). The findings indicate that blockchain technology can be quantified by 0.038 of other operating expenses. However, there are no discernible indications of measuring blockchain technology through customer deposits. The study suggests that blockchain technology is a double-edged sword; when not utilized as required, it leads to increased expenses, and conversely, its effective exploitation can have cost-reducing effects. In other words, operational inefficiencies or heterogeneity are associated with elevated costs associated with implementing blockchain technology. Doi: 10.28991/HIJ-2024-05-02-014 Full Text: PDF
Social Media Data Privacy Related to Security Awareness and Student Trust Regarding Data on Instagram
Authors: Kurniawan Yohannes , Natalia Bella , Pratama Windy , Devi Ni Luh Gede Aninda Kesuma
Published: June 2024

Instagram, as one of the most popular social media sites, has brought many new trends. Many people use Instagram to express themselves or share content through photos and videos. While social media data privacy is important, many people still share their daily activities and personal data. This causes a lot of personal information disclosure, which can lead to the potential for crime or misuse of the scattered data, considering that data is crucial today. Therefore, this research was conducted to determine people's social media data privacy and security awareness on Instagram, especially those with a data-related educational background. This research uses quantitative descriptive methods, distributing questionnaires through Google Forms in group chats, personal chats, or questionnaires to respondents directly. The population in this study is made up of students with a computing program background. It also used purposive sampling to determine the number of 153 samples. From the descriptive analysis, it is known that most respondents are aware of the vulnerability of social media data privacy on Instagram. This can be seen from respondents who know what data is used by Instagram, where they also monitor login activity. Respondents also secure their Instagram accounts by not using the same password as other social media accounts. However, in certain cases, some respondents still need to realize this awareness, so education is still needed regarding the importance of social media data privacy, especially on Instagram. Doi: 10.28991/HIJ-2024-05-02-015 Full Text: PDF
Optimizing Container Fill Rates for the Textile and Garment Industry Using a 3D Bin Packing Approach
Authors: Thi Xuan Hoa Nguyen
Published: June 2024

The scarcity of empty containers presents a significant logistical challenge globally. To address this issue, this study proposes the application of the optimal box arrangement in a container with a 3D bin packing problem to enhance fill rates and accommodate the complex packing criteria of the textile and garment industry. The study’s objective is to optimize box stacking into containers by considering various factors such as multiple product types, diverse box sizes, varying container sizes, and prioritizing stacking according to purchase orders (PO). In tackling the NP-hard problem with the added constraint of PO-based stacking, this study advocates employing a genetic algorithm combined with a wall-building algorithm to address practical challenges. The genetic algorithm demonstrates optimal efficacy in solving large-scale optimization problems within specified timeframes, yielding high-quality results. In addition, normalization methods are applied to convert box sizes to pallet sizes, expediting problem-solving and facilitating the selection of appropriate container sizes, namely 20- or 40-feet. The research findings indicate that the proposed method achieved a container fill rate of up to 91.67% and minimized the number of containers used. Doi: 10.28991/HIJ-2024-05-02-017 Full Text: PDF
Analysis of Factors Influencing Online Learning Using the Decision Tree Method
Authors: Li Xiaojie , Tang Huili
Published: June 2024

Objective: With the continuous development of online learning, the analysis of students' online learning has become increasingly important. Understanding which factors can influence students' engagement in online learning plays a crucial role in improving their learning performance. Methods: By utilizing web crawling techniques, students' online learning behavior data was collected from the Chinese University’s massive open online courses (MOOC) platform. To address the imbalance in the dataset, a synthetic minority oversampling technique (SMOTE) was used. Course progress was used to reflect students' online learning status, which was categorized into interruptions and completions. Furthermore, to tackle the issue of low computational efficiency in the C4.5 decision tree algorithm, its calculation formula was improved to develop an improved version of C4.5. Findings: Of the several factors analyzed, the number of course chapters had the greatest impact on students' online learning, followed by the number of course evaluations and overall course scores. The classification of students’ online learning situations based on an improved C4.5 algorithm revealed that the improved method achieved the highest accuracy rate of 0.942 and the shortest classification time of 0.165 s compared to methods such as the naive Bayesian and random forest algorithms. Novelty: This study designed an improved version of C4.5 to analyze the influencing factors in online learning, and its reliability was demonstrated through experiments, providing a new effective method for data analysis in online learning. Doi: 10.28991/HIJ-2024-05-02-018 Full Text: PDF
Evaluating Household Consumption Patterns: Comparative Analysis Using Ordinary Least Squares and Random Forest Regression Models
Authors: Lee En , Ong Thian Song , Lee Yvonne
Published: June 2024

This research aims to decompose the contribution of socioeconomic factors towards household consumption expenditure using a regression approach, with log per capita expenditure as the dependent variable. Our study stands out as the first to utilise SHAP analysis and Machine Learning models to analyse household consumption expenditure. We select both OLS (linear) and Random Forest (nonlinear) models to compare how they estimate consumption expenditure differently. Both models explain about 85% of the variation in log per capita expenditure. The SHAP analysis reveals the nonlinear relationships inside the Random Forest model. Several insightful findings were suggested that can be integrated into current policy-making. The results are as follows: (1) Both models agree that income, household size, and educational level are major factors in the purchasing power of household heads. (2) The Random Forest model demonstrated a nonlinear contribution of age and household size towards log per capita expenditure, contrasting with previous studies that treated them as linear. (3) Household heads with a higher income and educational level tend to spend more. (4) Current policy should consider focusing on households with larger sizes and lower incomes, who tend to spend more despite earning less, primarily by assisting them with non-cash transfers and subsidies. Doi: 10.28991/HIJ-2024-05-02-019 Full Text: PDF
An Adaptive Differential Evolution with Multiple Crossover Strategies for Optimization Problems
Authors: Farda Irfan , Thammano Arit
Published: June 2024

The efficiency of a Differential Evolution (DE) algorithm largely depends on the control parameters of the mutation strategy. However, fixed-value control parameters are not effective for all types of optimization problems. Furthermore, DE search capability is often restricted, leading to limited exploration and poor exploitation when relying on a single strategy. These limitations cause DE algorithms to potentially miss promising regions, converge slowly, and stagnate in local optima. To address these drawbacks, we proposed a new Adaptive Differential Evolution Algorithm with Multiple Crossover Strategy Scheme (ADEMCS). We introduced an adaptive mutation strategy that enabled DE to adapt to specific optimization problems. Additionally, we augmented DE with a powerful local search ability: a hunting coordination operator from the reptile search algorithm for faster convergence. To validate ADEMCS effectiveness, we ran extensive experiments using 32 benchmark functions from CEC2015 and CEC2016. Our new algorithm outperformed nine state-of-the-art DE variants in terms of solution quality. The integration of the adaptive mutation strategy and the hunting coordination operator significantly enhanced DE's global and local search capabilities. Overall, ADEMCS represented a promising approach for optimization, offering adaptability and improved performance over existing variants. Doi: 10.28991/HIJ-2024-05-02-02 Full Text: PDF
5G Opportunities in the South Pacific: Leveraging Low-Band Spectrum for Socio-Economic Development
Authors: Singh Satyanand , Singh Pragya , Rosak-Szyrocka Joanna , Vasa Laszlo
Published: June 2024

This paper explores the potential for deployment of 5G communication in the South Pacific, with a particular focus on leveraging the low-band spectrum for socio-economic development. The purpose of this study is to assess the feasibility of deploying 5G infrastructure in the South Pacific region, analyze the socio-economic benefits it may bring, and propose strategies to maximize these benefits. The research methodology includes a comprehensive review of existing literature on 5G deployment strategies, the socio-economic impacts of telecommunications infrastructure, and case studies of similar initiatives in other regions. The findings show that the deployment of 5G technology using low-band spectrum has the potential to significantly improve connectivity, healthcare, education, and economic opportunities in the South Pacific. Additionally, the paper proposes innovative approaches to address challenges such as infrastructure development in remote areas and affordability for marginalized communities. This study contributes to existing literature by providing tailored recommendations for leveraging 5G technology to address socio-economic inequalities in the South Pacific, thereby contributing to the development of telecommunications infrastructure in the region. Provides a new perspective on the possibilities of structure. Doi: 10.28991/HIJ-2024-05-02-020 Full Text: PDF
Prediction of Dust Emissions in Highway Subgrade-Filling Construction Based on Deep Neural Network
Authors: Wang Zhibin , Feng Lei , Li Yanwei , Du Qunle , Zhao Lin , Wang Xingju
Published: June 2024

Dust pollution can harm the urban environment and the health of citizens. Each stage in highway construction generates unorganized dust emissions to varying degrees, which complicates their quantification. To precisely forecast dust emissions during the construction of highway subgrades and reduce the associated pollution risks, this study introduces a predictive model based on a deep neural network (DNN) for dust emissions during highway subgrade-filling operations. Dust concentration is treated as a nonlinear multivariate problem, with predictive indicators encompassing particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), ground surface temperature, wind speed, air temperature, surface pressure, and relative humidity. Using a DNN model, this study forecasts the concentrations of PM2.5 and PM10 at highway construction sites. Based on a highway project in Hebei Province, this study predicts dust-emission concentrations via field monitoring conducted using self-developed equipment. The model’s predictions exhibit a small mean-absolute-percentage error and root-mean-square error compared with the actual values, and the model’s accuracy significantly surpasses that of conventional regression models. Accurate forecasting can facilitate the timely control of dust concentrations at construction sites, thus facilitating more environmentally friendly and efficient construction. Doi: 10.28991/HIJ-2024-05-02-03 Full Text: PDF
Analysis of Seasonal Wind Energy Potential on Zanzibar Coastal Island
Authors: Shame Buruhan Haji , Tjahjana Dominicus D. D. P. , Ubaidillah . , Aziz Mohammad , Mbumba Manala T.
Published: June 2024

The main objectives of this research were to numerically analyze the potential for seasonal wind power (WP), assess wind direction, and select the most effective wind turbine (WT) for installation at the research site. Wind data were collected half-hourly from a branch of the Tanzania Meteorological Authority nearest to the research site. The collected data were analyzed using a double-parameter Weibull distribution (WD) model, where the standard deviation (SD) method was used to fit the WD. The results revealed that the site experienced strong winds within the range of 4.5–7 m/s between the hours of 05:00 - 20:00, with the most likely seasonal wind speed (WS) ranging from 5–7 m/s, while the mean seasonal WS was 9.07–12.14 m/s. The highest possible wind energy density (wED) of 23.3 GWh/m2 at a hub height of 10 m occurred during winter, followed by spring, autumn, and summer, with 6.39, 6.32, and 3.33 GWh/m2, respectively. The annual wED was > 13.52 GWh/m2, with a typical month-to-month energy of 1.13 GWh/m2. Finally, the study concluded that the recommended WT model (POLARIS P62-1000) was the best choice for installation at the study site due to its sustainable WS and WP potential. Based on the findings of this research, which show that the site has sustainable seasonal wind resources, it is suggested that future wind research be carried out to extend the dataset to ensure the long-term seasonal wind pattern at the site. Doi: 10.28991/HIJ-2024-05-02-08 Full Text: PDF
Application of Smart Model in the Analysis of Opera Heritage Archiving and Protection
Authors: Liu Xueying , Zhou Wei , Dong Yuting , Zhu Libing , Chen Naijia
Published: June 2024

Objective: Opera Heritage in China is a rich and diverse cultural tradition passed down through generations. Today, Opera Heritage remains an essential part of Chinese culture and is celebrated through performances, festivals, and other cultural events. Efforts are being made to preserve and promote Opera Heritage through innovative technologies and approach such as digital archives, virtual reality, and community-based heritage management. Analysis: In this study, we suggested the SMART model that seeks to integrate these technologies and approaches into the preservation and promotion of Opera Heritage, ensuring that this rich cultural tradition can be enjoyed by future generations. We employed an ‘opera heritage’ using the Smart model in this study. In this research, "Smart Heritage" was defined as heritage experiences that used the word "Smart Heritage" or "similar terms" to describe the smart model. Findings: Opera Heritage analysis paid close attention to cutting-edge tools to record developments that showcase technical independence. Due to language barriers, this article could only interpret a clear convergence between SMART and opera heritage protection. For China's Opera Heritage to be properly archived and protected, a holistic and cooperative strategy that incorporates cutting-edge technologies and community-based heritage management practises are essential. Conclusion:Innovating technologies such as virtual reality and digital archives have been employed in efforts to promote and preserve China's rich Opera Heritage. This study emphasises the necessity for an extensive strategy for the efficient preservation and protection of Opera Heritage and suggests the SMART model to incorporate these methods. Doi: 10.28991/HIJ-2024-05-02-09 Full Text: PDF
A Book Review of Lissette Lopez Szwydky and Glenn Jellenik’s Edited Collection Adaptation Before Cinema: Literary and Visual Convergence from Antiquity Through the Nineteenth Century
Authors: Çetiner-öktem Züleyha
Published: June 2024

Adaptation Before Cinema: Literary and Visual Convergence from Antiquity Through the Nineteenth Century is one of the latest additions to the Palgrave Studies in Adaptation and Visual Culture, an outstanding series dedicated to exploring new ways of reflecting on the dialogue between adaptation and visual culture. With an underlying impulse to obliterate the unidirectional perception of adaptation as a derivative version of a source text, the series encompasses a broad range of media as symbolic spaces of multiplicity that generate connections and continuities between all forms of texts and narratives. Adaptations are treated as “complexly multiple” texts that are connected to “other pervasive plural forms” such as “sequels, series, genres, trilogies, authorial oeuvres, appropriations, remakes, reboots, cycles and franchises” (Szwydky & Jellenik, 2023, blurb). As such, the books published in this series offer a rich and thought-provoking ground not only for scholars of adaptation studies but also for scholars of literary studies, cultural studies and film studies who seek fresh perspectives and like to think outside the box.
Çingenelerin Kültürel Doku Analizi
Authors: Eken Hurigül
Published: June 2024

Bu çalışma, Çingenelerin kökenleri ve kültürel yapıları üzerine derinlemesine bir inceleme sunmaktadır. Tarihsel ve coğrafi çeşitlilikleri ele alınarak, Çingenelerin Hindistan, Mısır ve Orta Doğu gibi yerlerden etkilenmiş olabilecekleri ve bu etkileşimlerin onların kültürel dokularını nasıl şekillendirdiği üzerinde durulmuştur. Çalışma aynı zamanda, Çingenelerin sosyal marjinalleşme süreçlerini ve bu süreçlerin toplumsal algılara etkisini sosyolojik çalışmalar ve Quora gibi blog platformlarındaki yorumlar aracılığıyla irdeler. Çingenelerin karşılaştıkları zorluklar ve ayrımcılıklara rağmen kültürel geleneklerini nasıl korudukları ve toplumla olan etkileşimlerini sürdürdükleri vurgulanırken, medyanın bu topluluğa yönelik olumsuz temsillerinin de ele alındığı görülmektedir. Çalışma, Çingenelerin toplumsal entegrasyonunun kültürel özellikleriyle uyumlu bir şekilde gerçekleşmesi gerektiğini savunmakta ve onların kültürel zenginliklerinin tanınması gerektiğini öne sürmektedir.
Kerim Tinçurin’in Amerikan Adlı Eserinde Tatar Burjuvazisinin Eleştirisi
Authors: Güngör Gözde
Published: June 2024

Zengin repertuara ve köklü bir geleneğe sahip Tatar tiyatrosu modern anlamda ilk örneklerini XIX. yüzyılın sonlarında vermeye başlamıştır. Tatar tiyatro tarihinin bilinen ilk eseri A. İlyasi’nin kaleme aldığı Biçare Kız’dır. F. Halidi, M. El-Kazani, A. İshaki gibi edipler vasıtasıyla Tatar tiyatrosu megrifetçĕlĕk (aydınlanma) realizmi adı verilen yönelimin etkisinde 1905’e dek önemli bir ilerleme kaydeder. 1905 meşrutiyetinin getirdiği özgürlükçü ortamla beraber Tatar tiyatrosu da repertuar açısından zenginleşmeye başlar. 1917 Ekim devrimine kadarki süreçte Tatar tiyatrosu, aydınlanma realizmi ve onun biçimlendirdiği tenkitçi realizmin etkisinde zengin halk kültüründen, Doğu, Rus ve Batı klasiklerinden, Türk dünyasının geleneksel temaşa kültüründen ve devrin siyasi gelişmelerinden beslenir. Tatar rönesansı olarak da adlandırılan bu devrin oyun yazarlığında öne çıkan isimleri Galiasgar Kamal ve Ayaz İshaki’dir. 1917 devrimi sonrasında ise yeni rejimin ideolojisi doğrultusunda bir repertuar oluşmaya başlar. İç savaş devrinde kaleme alınan agitprop oyunlar 1920’li yıllarda yerini sosyal sınıf mücadelesini öne çıkaran eserlere bırakır. Sovyet Tatar dramaturjisinin bu ilk döneminin en kudretli kalemlerinden biri Kerim Tinçurin’dir. Tinçurin esasında tiyatro dünyasına 1910’lu yıllarda adım atmış olmakla birlikte asıl etkinliğini 1920’li yıllarda göstermiştir. Bu yıllarda art arda kaleme aldığı piyesleri ve tiyatroya yönelik kuramsal çalışmalarıyla adından söz ettiren dramaturg bugün G. Kamal ile birlikte Tatar tiyatrosunun kurucusu olarak addedilmektedir. Bu çalışmada yazarın 1923’te yayımladığı Amerikan adlı komedisine odaklanılmıştır. Giriş bölümünde başlangıçtan 1917 devrimine dek Tatar tiyatrosunun gelişimi özetlenmiş ardından Ekim devriminin tiyatro repertuarı üzerinde etkisi ve Tinçurin’in devrimin ilk yıllarındaki faaliyetleri ele alınmıştır. Son bölümde ise çalışmanın ana konusu olarak belirlenen Amerikan adlı piyeste burjuva sınıfının temsili ve milli burjuvazisinin eleştirisi değerlendirilmiştir.
Drop Size Distribution in Agitated Contactor: A Review
Authors: Hamed Marwa S. , Hasan Basim O. , Znad Hussein T. , Al-Zuraiji Sahir M.
Published: June 2024

The breakage rate of liquid drops in the dispersed phase is a key way to improve the heat and mass transfer between the continuous/dispersed phases. This work includes a review of experimental results of liquid drop breakage in an agitated tank. The study highlighted the experimental conditions that were investigated as well as the important findings about the impact of operating conditions on some breakup parameters. The conflicts and discrepancies in the findings of those studies were identified and analyzed. The review found that many experimental parameters affect the drop breakage rate. The breakage probability (BP), number of fragments, and breakage time (BT) are direct functions of power input.
A Practical Guide to Virtual Planning of Orthognathic Surgery and Splint Design Using Virtual Dentoskeletal Model
Authors: Mahmood Reem Sh. , Hamandi Sadiq J. , Al-Mahdi Akmam H.
Published: June 2024

The present work is a manual that describes the practical aspects of optimizing dental precision by virtual dentoskeletal modeling, use the precises model in virtual planning, and splint design of orthognathic surgery. A single case study is used to demonstrate the stages involved in this approach, which include acquiring CBCT scan data and digital dental models, incorporating this data into developing a virtual dentoskeletal model using superimposition process to replace the unclear teeth. Utilizes virtual assessment and three-dimensional cephalometry to diagnose the maxillofacial deformity of the patient correctly. The results of the diagnosis played a crucial role in formulating a comprehensive plan for dental alignment, which involved osteotomy and correction of bone positions. The final step is to create a personalized splint. The importance of virtual tools is highlighted in our work to optimizing dental precision, diagnose and treat maxillofacial deformities. Present a virtual planning methodology for orthognathic surgeons as well as researchers.
A Portable Non-Invasive System for Detecting Blood Glucose Levels Using a Laser-Based Sensor
Authors: Ibrahim Fatima , Mustafa Zaid , Lateef Ahmed
Published: June 2024

Diabetes is a long-term medical condition that impacts the way your body converts food into energy, it has the potential to lead to several severe health complications, such as heart disease, stroke, vision impairment, kidney issues, and nerve damage. Nevertheless, individuals with diabetes can lead extended and healthy lives with effective management. The goal of diabetes treatment is to keep your blood sugar levels within a healthy range. So Glucose measurement is an important part of diabetes management. It allows people with diabetes to track their blood sugar levels and make adjustments to their diet and medication as needed. Morning fasting blood glucose typically falls within the range of (70 mg/dL) to (110 mg/dL), while after a meal, blood glucose levels should ideally be below (140 mg/dL). In this proposed work an Arduino-based noninvasive glucose measurement device is proposed. Non-invasive glucose measurement devices do not require the user to prick their finger to draw blood. A Red Laser (RL) technique, is employed, this method surpasses the other invasive approach and non-invasive methods in terms of superiority. Since invasive techniques can be painful and expensive. This paper describes a new way to measure blood sugar levels without having to prick your finger. The method uses a red laser to shine light through the skin and measure how much the light is bent. The amount of bending tells the device how much sugar is in the blood. Numerous tests and experimental outcomes have been produced to demonstrate the exceptional accuracy of the proposed method.
Performance of Single Degree of Freedom (SDOF) Systems Subjected to The Near-Fault Earthquakes
Authors: Mhawish Ayah Hameed , Reisn Hussam K.
Published: June 2024

This paper aims to assess the structures' seismic response with a system of Single-degree-of-freedom exposed to near-fault earthquakes, taking into account the effect of pulse period, shear wave velocity (VS30), and fault mechanism. Strong ground motion data were taken for different events in different places around the world and the prism software program is used for the analysis of seismic response for structures recognized as single-degree-of-freedom systems. Results show that the ground motion with a higher value of (VS30) provides an acceleration response higher than that of the lower value of (VS30). However, the findings revealed that the peak displacement requirements are observed in a nearby of the pulse period limits. In addition, it is noticed that there is an obvious increase in spectrum demand with longer pulse periods. Finally, results show at short vibration periods (T? 0.6sec) for both types (strike slip and dip slip) comparable results while an increment is observed in the results of the strike-slip for vibration periods more than (0.6sec) of the acceleration response spectrum. Nonetheless, for the velocity response spectrum dip-slip continuous in flocculating with a significant increase.
Review of Polymer MFD Manufacturing Using Laser Technology
Authors: Salman Safa N. , Rajab Fatima H. , Issa Ahmed A.
Published: June 2024

This paper provides a comprehensive overview of microfluidic device (MFD) manufacturing processes. The review starts with an introduction elucidating the significance and advantageous of MFDs. Subsequently, a brief description about the materials that employed in MFD fabrication is presented. The manufacturing process used to create MFDs is then thoroughly examined, with a focus on the application of laser technology.
Laser Produced Hydrophilic and Hydrophobic Silicon Surfaces
Authors: Hatem A. A. , Rasheed B. G. , Ahmed Naser M.
Published: June 2024

Two lasers were utilized for silicon processing using photoelectrochemical etching and laser texturing in order to produce nano/micro structures, respectively. Photoelectrochemical etching process utilizes a CW diode laser of 532 nm wavelength was used to support electrochemical etching for both n-type and p-type conductivity. While laser texturing process was employed using pulsed fiber laser of 1064 nm wavelength. Various characterization methods were devoted to examine silicon micro/nanostructures surfaces produced by lasers. These methods include AFM, SEM and Raman scattering to provide clear evidence about formation of micro/nanostructures abundant at silicon surfaces.  Moreover, FTIR analysis for the laser produced silicon surfaces could emphasize whether the resultant silicon surface is hydrophilic or hydrophobic. Image analysis software adopted a side view micro image was used to measure the contact angle between the water droplet and silicon micro/nano-surfaces. It is found that the laser produced silicon nanostructure by photoelectrochemical etching creates a hydrophobic surface and even super hydrophobic with contact angle of 130 degrees for 50 nm average size. In addition, utilizing fiber laser of high repetition rate for laser texturing produces microstructures that are super hydrophilic with contact angle could reach 8 degrees for a surface dimension of 50 μm.
Toward Seven-Band Coherent WDM System Covering T to U Bands: Predictions of Transmission and BER Performance
Authors: Moosa Arwa A. , Fyath Raad Sami
Published: June 2024

This paper discusses the development of a seven-band coherent wavelength-division multiplexing (WDM) system covering the T to U systems, aiming to enhance the capacity and system efficiency. Seven multiband systems (C+L, S+C+L, S+C+L+U, E+S+C+L, E+S+C+L+U, O+E+S+C+L+U, and T+O+E+S+C+L+U) are designed with 40 GBaud symbol rate, 50 GHz channel spacing, and dual-polarization (DP)-16QAM signaling. The analysis adopted the enhanced Gaussian noise model, considering the amplified spontaneous emission of inline optical amplifiers and nonlinear interference (NLI) from fiber nonlinear optics, including Kerr effect and stimulated Raman scattering (SRS) which it implemented using Matlab (Ver. 2020b) program. The results show that the optimal powers are -4, -5, -5, -4.5, -3.5, -6, and -4.5 dBm for the seven WDM systems, respectively. Further, with a fiber span length of 100 km, the C+L system has the longest transmission reach of 20 span. However, using S+C+L+U system gives the highest bit rate-distance product of 1619 Tbps.km. The O+E+S+C+L+U and T+O+E+S+C+L+U systems are designed with 50 km-span length to reduce the effect of NLI caused by the large numbers of channels (1060 and 1200, respectively).
A complementary Diagnostic Tool for Diabetic Peripheral Neuropathy Through Muscle Ultrasound and Machine Learning Algorithms
Authors: Kamal Kadhim , Al-Timemy Ali Hussein , Kadhim Zahid M. , Raoof Kosai
Published: June 2024

Diabetic peripheral neuropathy represents one of the common long-terms complications that effect about fifty percentage?of diabetes patients. The habitual diagnosis tool based on nerve conduction study that examine the nerve damage and classify the patient status into normal and diabetic peripheral neuropathy with degree of severity without considering the effect on skeletal muscle and take on patient data. A complementary diagnostic tool proposed, in this study integrates the patient’s data including body mass index, age and duration of diabetic, average blood glucose levels, nerve conduction study that involves amplitude and latency of peroneal and tibial nerves and muscle ultrasound alongside the machine learning algorithms to facilitate the clinicians for a precise diagnosis. A group of control and diabetic patients utilized to gather the data with calculating the muscle thickness and statistical properties from the gray-level ultrasound images of six skeletal muscles. Support vector machine, naïve bayes, ensemble of bagged tree and artificial neural network supervised machine learning algorithms categorize each class with a high classification accuracy, 98.1% for tibialis anterior with naïve bayes algorithm. The outcomes of this study show a promising complementary diagnostic tool that will help the clinicians to perform an exact diagnosis and disclose the side effect on both nerves and muscles of diabetic patients.
The Effect of Flow Velocity on Corrosion and Corrosion Mitigation of Carbon Steel in Wide Range of Sulfuric Acid Concentration
Authors: Alzuraiji Saher , Maha H. Kazem  , Basim O. Hasan  , Hussein T. Znad
Published: June 2024

The impact of flow velocity (0-900 rpm) on the corrosion rate of carbon steel in a wide range of sulfuric acid concentrations (0-90% in H2O) at 30 °C and 1 h was studied and discussed. In addition, the efficiency of corrosion inhibitor (dimethyl disulfide, DMD) was evaluated in hardest corrosion conditions for the range of velocity investigated. The results revealed that increasing the flow velocity of H2SO4 solution, increases the corrosion rate depending on the acid concentration. When the flow velocity is increased of H2SO4 solution, the corrosion potential was shifted to more negative. The DMD inhibitors showed significant inhibition efficiency at high velocities, where the highest percentage of inhibitor efficiency reached 98% at 900 rpm.
A Study of the Effect of the Difference in Energy Stored in Two Prosthetic Feet Made of Carbon Fiber Amputated Below the Knee on the Efficiency of Walking
Authors: Basim Noor , Kahtan Yassr Y.
Published: June 2024

ESAR feet are prosthetic feet with carbon fiber parts that store mechanical energy while standing and release it during propulsion. It is believed to reduce the metabolic energy needed for walking, and to promote the economy of walking. However, there is little scientific evidence to support this claim. This study aimed to compare the energy storage properties of two prosthetic feet made of carbon fiber using the P-Walk, G-Walk, and Podium devices developed for gait analysis, which is a systematic examination of human movement, enabling phasing, estimation of musculoskeletal performance, and determination of kinematic and motor parameters. The amount of energy was calculated for each of the feet using the load deflection test, and the results showed that the new artificial foot with an energy of 6.186 joules showed a great improvement in the results of the tests compared to the old artificial foot with an energy of 3.403 joules. The Podium device tests showed a significant improvement in walking patterns and pressure distribution after using a new foot. The pressure distribution became almost equal on both sides, and the angular deviation of COP decreased from -7 to 1.3 degrees. Ground reaction force vector tilt results also improved, with a body angle of 0 degrees and inclination varying slightly depending on the tibiofemoral angle for males. P-Walk results reveal left-sided static test pressure distribution, exposing amputees to osteoarthritis risk and revealing lack of confidence in prosthetic foot. After use the new prosthetic foot, amputees press more on right foot, indicating balance restoration. The G-Walk device shows the effectiveness of both healthy left and prosthetic foot when walking on an amputated right leg when use the new prosthetic foot. The amputated side's performance is similar to a healthy limb, with minimal difference and within normal limits. Walking cadence and speed values are within normal ranges, while stride length and step length are outside normal ranges for both sides. Obliquity results show a small difference in pelvic angles due to weak pelvic muscles, but these are close to standard values for prosthetic foot use. The amputee's opinions about the evaluation of the new prosthetic foot were good when using the T-score by 61.0 with a rate of 86.4%. It was a significant improvement compared to the old foot with an evaluation of 53.6 by 63.9%.
Characterization and Fabrication of Ankle Foot Orthoses using Composite with Titanium Nanoparticles
Authors: Khalaf N.J. , Ben Amor Sabrine , Louhichi Borhen
Published: June 2024

Orthoses and prostheses were Chosen and laminated based on their high Yield, ultimate stresses, bending stresses, and fatigue limit. Response Surface Methodology (RSM) was utilized to find the best values for two parameters reinforcement perlon fiber and percent of Titanium Nanoparticle coupled with the matrix resin during optimization. The response surface methodology combined the expertise of mathematicians and statisticians to construct and analyze experimental models. Using this method, we identified 13 different lamination samples comprising a wide range of perlon number and Ti nano Wt% in their Perlon layer composition. All lamination materials defined by RSM methods and produced by a vacuum system were subjected to a battery of tests, with fatigue tests performed on the ideal laminating material in contrast to laminations created in the first study (Tensile test, Bending test, and Fatigue tests according to the ASTM D638 and D790 respectively). In comparison to the other 12 laminations tested using Design Expert version 10.0.2, the lamination with ten perlon layers and 0.75 percent Ti nano proved to be the strongest overall in terms of Yield, ultimate, and bending loads. This study used composite materials and titanium nanoparticles to characterize and fabricate ankle foot orthoses. Strength in bending should amount to about 70 MPa, around 85 MPa in tensile tension. Two empirical quadratic equations for the models of peak bending strength and maximum tensile stress with 95% confidence were created using the response surface approach and analysis of variance within the design of experiments software.