bluuebunny/crossref_metadata_2025 huggingface dataset:
Aktif Spor Yapan Üniversite Öğrencilerinin Beden Memnuniyeti, Mental İyi Oluş ve Özgüven Düzeylerinin İncelenmesi
Authors: YILMAZ Ahmet , AĞGÖN Eser
Published: April 2023

Sporun psikososyal alanlarla olan ilişkisi yadsınamaz bir gerçektir. Spor ile psikososyal alanların ilişkisini saptamak amacıyla çalışmadan elde edilecek bulguların literatüre katkı sağlayacağı düşünülmektedir. Bu araştırmanın amacı; aktif spor yapan üniversite öğrencilerinin beden memnuniyeti, mental iyi oluş ve öz güven düzeylerini ve aralarındaki ilişkiyi tespit etmektir. Araştırmanın örneklemini 168 erkek, 217 kadın üniversite öğrencisi oluşturmaktadır. Araştırmada; “Kişisel Bilgi Formu”, Avolos, Tylka ve Wood-Barcalow (2005) tarafından geliştirilen, Bakalım ve Taşdelen (2016) tarafından Türkçeye uyarlaması yapılan “Beden Memnuniyeti Ölçeği”, Warwick-Edinburg (2007) tarafından geliştirilmiş, Keldal (2015) tarafından Türkçeye çevrilmiş Mental İyi Oluş Ölçeği, Akın (2007) tarafından geliştirilen “Öz Güven Ölçeği” kullanılmıştır. Verilerin analizinde tanımlayıcı istatistiklerin yanında, bağımsız iki grup karşılaştırmalarına ilişkin farkları belirlemek amacıyla Bağımsız Örneklem t-Testi ve değişkenler arasındaki ilişkiyi belirlemek amacıyla ise Pearson Korelasyon Analizi kullanılmıştır. Aktif spor yapan üniversite öğrencilerinin beden memnuniyeti, mental iyi oluş ve öz güven düzeylerinin, aktif spor yapmayan üniversite öğrencilerinin mental iyi oluş düzeylerine göre anlamlı olarak daha yüksek olduğu istatistiki açıdan tespit edilmiştir. Bunun yanında beden memnuniyeti, mental iyi oluş ve öz güven düzeyleri arasında pozitif yönde bir ilişki olduğu tespit edilmiştir. Araştırma sonuçlarına göre aktif spor yapmanın beden memnuniyeti, mental iyi oluş ve öz güven düzeylerini pozitif yönde etkilediği, ayrıca beden memnuniyeti ile öz güven düzeyi, mental iyi oluş ile öz güven düzeyi ve beden memnuniyeti ile mental iyi oluş düzeyi arasında pozitif düzeyde ilişkiler olduğu tespit edilmiştir.
The Anthropologist as Audience: Engaged Listening among Khmer Rouge Survivors and Ukrainian War Refugees
Authors: Lesley Elena
Published: April 2023

Although the Khmer Rouge regime was responsible for the deaths of roughly 2.2 million Cambodians—and the persecution and abuse of millions more—only a handful of survivors have been able to testify at the tribunal established to prosecute former leaders of the regime. Partly to address this gap, an NGO affiliated with the tribunal has been offering ‘Testimonial Therapy’ for the past decade as a form of reparation for survivors with symptoms of psychological distress. For 16 months, I followed survivors undergoing this therapy, during which they developed a testimonial narrative of their life story in collaboration with a local mental health worker. In this Position Piece, I consider Myers’ conception of ‘moral agency’ (2015) in relation to this process of personal narrative creation, and the critical importance of audience engagement. I then reflect on my own positionality as both ethnographer and active listener, tracing how this affective posture has been formed not only through fieldwork, but also through engagement with family narratives of loss in the context of war-torn Ukraine.
​​Fleshy Entanglements in Development Aspirations​: Birth Position as a Site of Contestation in Bangladesh
Authors: Perkins Janet Elaine
Published: April 2023

Encouraging women to adopt a position of their choice during birth has long been among the calls of scholars and activists challenging medicalised models of childbirth rooted in patriarchy to allow women to own their birthing experiences rather than accept the passivity of a lithotomy position. The encouragement of women to adopt a position of their choosing is now integrated within global health policy. Based on fieldwork conducted in Dhaka and Kushtia district, Bangladesh, this article examines the promotion of non-supine birth positions promoted through international development entities in Bangladesh. It argues that despite its emancipatory appeal, when subsumed by international development logics, the birth position operates as a site of political contestation in which women are rendered peripheral within a broader constellation of development imaginaries and ends. Within this constellation, the birth position is circumscribed as a technical intervention amenable to metricisation. Rather than a ‘return’ to more ‘natural’ forms of birth, ‘non-supine’ birth positions when instrumentalised in this context, are broadly conceived of as ‘foreign’, and serve to expand the medicalisation of childbirth.
An Ethical Question: Acknowledging Contentious Ethics in Medical Anthropology and Allied Fields
Authors: Editorial Collective MAT
Published: April 2023

Editorial to the April issue of 2023.
Growth Performance, Molting Frequency and Carapace Coloration of Two Different Size Classes of Red Swamp Crayfish (Procambarus clarkii) Fed with Different Diets
Authors: AMANYAZOV Vepa , KARADAL Onur
Published: April 2023

In this study, the effects of three different commercial aquarium feeds were tested on the growth performance, molting frequency and carapace coloration of red swamp crayfish (Procambarus clarkii) in two different size classes (4 and 5 cm). For this purpose, six experimental groups were formed according to crayfish size (S1: Size 1 and S2: Size 2) and feed type (BF: bottom fish food, CF: cichlid food and CG: crustacean granules) as S1BF, S1CF, S1CG, S2BF, S2CF and S2CG, and the crayfish were fed with these diets for 12 weeks. The final mean weight (FMW) of the S1CG was higher than the S1BF (P<0.05). The final mean total length (FMTL) and final mean carapace length (FMCL) of S2BF were the lowest (P<0.05). No significant differences were recorded in the feed conversion ratios (FCR), specific growth rates (SGR) and survival rates (SR) of red swamp crayfish in two different size classes (P>0.05). The lowest cheliped injury and cannibalism rates were found in the crayfish fed with crustacean feed in both size classes. The mean molting frequencies (MMF) of the S1CG and S2CG were statistically higher than the S1CF and S2BF, respectively (P<0.05). S2CG has the highest final lightness (L*) value (P<0.05). The final redness (a*) and final yellowness (b*) values of the S1BF and S2BF groups were the lowest (P<0.05). The results showed the positive effects of crustacean feed on all the tested parameters in both size classes. Further studies are needed to investigate the efficient use of species-specific rations in the crayfish species.
Using photographs in consumer research of agricultural and livestock products
Authors: Manfroi Julia Vettori , Franco Mariane Ferreira , Garcia Pedro Henrique de Melo , Pinheiro Rafael Silvio Bonilha
Published: April 2023

Photographs provide momentary visual data that facilitate consumer understanding, thus visual research methods have been used to obtain their perceptions and experiences. We aimed to conduct a literature review using studies related to the theme of this paper, to obtain an overview of sustainability, animal welfare, consumer behaviour, and the use of photographs in animal science research. The analysis method considered was qualitative and the information was obtained from scientific articles from Google Scholar, Scientific Electronic Library Online (SciELO) and Elsevier research platform databases, published in the last seven years, as well as from classical bibliographies to carry out a bibliographic survey related to the theme of the study. It was concluded that during the meat buying process, consumers' choices are determined mainly by the lowest price, origin, brand, product information, color, marbling, amount of fat, texture, freshness, type of cut and product conservation. The consumption of products from sustainable production and with animal welfare is still very low, mainly due to socioeconomic issues and lack of knowledge about the production process of animal products. The adoption of photographs in consumer research is capable of increasing the information load with reduced cognitive effort, reducing uncertainties during decision making. There is still a scarcity of works with photographs related to animal science and the increase would be opportune to avoid possible misinterpretations by consumers during the survey questionnaires.
How Do Corporate Governance Factors Influence Banks’ Value? Evidence from Russia
Authors: Ускова Наталия
Published: April 2023

In this research study we built 3 models that evaluate the panel data of 30 Russian banks with the largest assets and highest reliability. Comparison of all three models by means of specification tests led us to the conclusion that the OLS model with the explanatory power of 67% is optimal.

The presence of women on the board of directors negatively affects the banks’ valuation, while the number of the board of directors’ meetings, number of directors and presence of an audit committee have a positive impact on the net asset value of banks. If the share of women increases by 1%, the bank’s net asset value will decrease by 86%. If the board of directorshas a functioning risk management committee, the bank’s net asset value will grow by 225%. In case of an increase in the number of the board of directors’ members by 1%, the bank’s net asset value will grow by 4.4%. If the number of meetings of the board of directors per year grows twofold, the bank’s net asset value will increase by 118%.
CEO`s education and investments in R&D
Authors: Хмелева Полина
Published: April 2023

The paper evaluates influence of CEO`s education and her experience on amounts invested in R&D in pharmaceutical industry. The sample consists of 270 pharmaceutical high-tech companies from S&P BMI index in 1999-2018 from 23 countries, both developed and emerging. The pharmaceutical industry is of particular interest since the projects there require specialized education to understand and manage the process. Therefore, the payback period of investments is long. As a result, in pharmaceuticals there is a high rate of intangible assets comparing to other sectors.

At the first glance, according to the results of regression analysis, business education, financial, managerial and economic education has no significant impact on investments. However, education in specific sphere, like physics, chemistry, biology, mathematics, has a significant positive impact on R&D expenses. We can see the similar effect for the CEO`s with two or more degrees in different fields. These results are in line with the findings of previous studies regarding CEO`s education.

At the next stage, educational level of CEO and its field are analyzed simultaneously. A degree obtained in the industry-specific field or a degree supplemented by a financial or managerial education has a positive impact on R&D expenses, while standalone financial degree, by contrast, has a negative effect.

So, we contribute to the academic literature with the idea that to get the unbiased results in similar studies we should account for not only degree but also the field. In practical sphere, the results can be useful for those who choose the educational track on their career path to CEO position as well as for HRs, Boards of directors, and other stakeholders while making decision on CEO turnover. Moreover, the results provide insights that could be useful for market analyst`s and investors` predictive models.
Validation and mutation of the names of some syntaxa from the class Phragmito-Magnocaricetea
Authors:   Institute of Biology FRC Komi SC UB RAS, Teteryuk Boris Yu.
Published: April 2023

In this article, the association Alismato-Scirpetum sylvatici was validated according to the requirements of article 5 of the Code of Phytosociological Nomenclature (edition 4) (CPSN 4th edition). Also the mutation of names (article 45 of CPSN-IV) of five syntaxa: Schoenoplectetum lacustris, Bolboschoeno fluviatilis–Zizanietum latifoliae, Petasition radiatae, Petasitetum radiatae and Arctophiletum fulvae was performed.
Notes on distribution and habitat preferences of Sphagnum inexspectatum and S. mirum in Western Siberia
Authors:   Yugra State University, Lapshina Elena D. , Maksimov Anatoliy I. ,   Institute of Biology, Karelian Research Centre RAS, Lamkowski Paul ,   Institute of Applied Science, Neubrandenburg University,   Ernst Moritz Arndt University
Published: April 2023

New records of two rare moss species, Sphagnum inexspectatum Flatberg (4) and S. mirum Flatberg & Thingsgaard (9) are reported from Western Siberia, and discuss them in context of their habitat preferences in region as well as general range. Their distribution in Russia is considered and re-assessed. Geobotanical relevés of plant communities with Sphagnum inexspectatum and S. mirum from Western Siberia are presented. It is shown that in the taiga zone S. inexspectatum occurence is closely related to communities of the alliance Stygio-Caricion limosae Nordhagen 1943, class Scheuchzerio-Caricetea nigrae Tx. 1937, and similar Sphagnum carpets in meso-oligotrophic mires, where it grows as single stems among other peat mosses in poor conditions on slightly acidic substrates. In forest tundra and southern tundra this species occurs only in communities of the alliance Caricion stantis Matveyeva 1994. More diverse communities with S. mirum are assigned mainly to the alliance Sphagno-Caricion canescentis Passarge (1964) 1978, which comprises sedge-Sphagnum vegetation located in fens and transitional bogs in a wide variety of habitats from moderately poor to moderately rich in mineral nutrients and with slightly acidic substrate. This species occurs both with low (as single stems) and high abundance (frequently being dominant) in moss layer.
Designing Situated Vocabularies to Counter Social Polarizations: A Case Study of Nolo Neighbourhood, Milan
Authors: Tassinari Virginia , Vergani Francesco
Published: April 2023

Many neighbourhoods are currently serving as laboratories where new methods are being explored for collaboratively redesigning cities and tackling the social, environmental, and cultural issues affecting them. These redesign processes are often supported by local communities who increasingly develop bottom-up initiatives to innovate and preserve the neighbourhood’s “common goods.” This is certainly the case of Nolo, an area in the city of Milan (Italy) that has recently undergone an urban regeneration process thanks to the presence of a proactive community of actors living and working in the neighbourhood. Despite effective social innovation practices enacted by part of the local community, several “voices” in Nolo—mainly belonging to marginalized communities—are still excluded from the current process of urban regeneration. This lack of attention is rather problematic for the whole community, as it is leading to increasing rather than mitigating social polarization. To address this issue, we approached Nolo and its community through a participatory design experimentation, generating a series of collaborative platforms to enable those marginalized voices—humans as well as non-humans—to be heard, to enter into agonistic conversations with one another, and to question what they (should) all care about. What this (still ongoing) experimentation is currently showing is that to co-design collaborative platforms to counter polarization needs to be carefully balanced, negotiating between all the actors involved and acknowledging their thick entanglements to finally unravel how they radically inter-depend on one another. This kind of “ontologizing” practice is currently proving to be pivotal to counter “antagonisms” (and, therefore, mitigate social polarizations), and re-framing them in “agonistic” terms. This article reports how we operated this “ontologizing” practice in a particularly debated area of the neighbourhood by embracing the perspective of marginalized actors, encouraging them to collaborative and transformative actions for their own situated context.
Plant Health Prediction and Monitoring Based on convolution Neural Network in North-East India
Authors: Meena Bhagwan Sahay
Published: April 2023

Agriculture is the main backbone of any society. In this modern era as the population continuously increases, resources for farming are also decreasing. If the health condition of the plant’s determined at a regular interval, farmers can take action timely to improve the plant’s health condition. Plant monitoring and plant health status at regular intervals may lead to better growth of foods. But the regular physical visit to the crop field to monitor plants and plant health is a critical task for a large crop field. To overcome this situation, we need to shift from a traditional cropping system to smart agriculture. Now, these days, a smart agriculture-based approach can use the internet of things, machine learning, and deep learning to predict the health condition of plants. In this paper, the internet of things (IoT) based smart agriculture system has been presented along with machine learning, deep learning, and transfer learning to monitor and health prediction of plants. The IoT-based system has been used to monitor the plant’s surrounding parameters such as humidity, temperature, light intensity, and soil water moisture. The leaf images of plants have been used in deep learning (DL), machine learning (ML), and transfer learning (TL) to predict the health condition of plants. In this paper, the convolution neural network (CNN) based model has been proposed and it has been compared with the support vector machine (SVM), random forest (RF), VGG19, and mobilenet model. It has been concluded that the accuracy of the proposed CNN model is 81.5 %, which is the highest among SVM, RF, VGG19, and mobilenet..
A Detailed Analysis of Air Pollution Monitoring System and Prediction Using Machine Learning Methods
Authors: Thanagaraju Vinoth , Nagarajan Kothalam Krishnan
Published: April 2023

Predicting air quality is a complex task due to the dynamic nature, volatility, and high variability in the time and space of pollutants and particulates.Due to the presence of governing factors, varying land uses, and many sources for the elaboration of pollution, the forecast and analysis of air pollution is a difficult procedure. At the same time, being able to model, predict, and monitor air quality is becoming more and more relevant, especially in urban areas, due to the observed critical impact of air pollution on citizens’ health and the environment. In this paper, various air pollution monitoring and prediction models with respect to hardware interfacing modules and various classification approaches. The Air Quality Index (AQI) parameter is used in this paper to monitor the quality of air pollution in various regions of the world. The drawbacks of the conventional air pollution monitoring and prediction models have been stated in this paper with the methodologies used for air pollution prediction.
An Approach for Mining Top-k High Utility Item Sets (HUI)
Authors: Ramana K. Venkata , Muralidhar A , Balusa Bhanu Chander , Bhavsingh M. , Majeti Sravanya
Published: April 2023

Itemsets have been extracted by utilising high utility item (HUI) mining, which provides more benefits to the consumer. This could be one of the significant domains in data mining and be resourceful for several real-time implementations. Even though modern HUI mining algorithms may identify item sets that meet the minimum utility threshold, However, fixing the minimum threshold utility value has not been a simple task, and often it is intricate for the consumers when we keep the minimum utility value low. It might generate a massive amount of itemsets, and when the value is at its maximum, it might provide a smaller amount of itemsets. To avoid these issues, top-k HUI mining, where k represents the number of HUIs to be identified, has been proposed. Further, in this manuscript, the authors projected an algorithm called the top-k exact utility (TKEU) algorithm, which works without computing and comparing transaction weighted utilisation (TWU) values and deliberates the individual utility item values for deriving the top-k HUI. The datasets are pre-processed by the proposed algorithm to lessen the system memory space and to provide optimal outcomes for condensed datasets.
Comparison of Imputation Methods for Univariate Time Series
Authors: Chhabra Geeta
Published: April 2023

In order to predict and forecast with greater accuracy, handling “missing values” in “time series” information is crucial. Complete and accurate historical data are essential. There are many research studies on multivariate time series imputation, however due to the lack of associated factors, imputation in univariate time series data is rarely taken into consideration. It is natural that “missing values” could arise because almost all scientific disciplines that collect, store, and monitor data use "time series" observations. Therefore, time series characteristics must be considered in order to develop an effective and acceptable method for dealing with missing data. This work uses the statistical package R to assess and measure the effectiveness of imputation methods in the context of "univariate time series" data. The “imputation algorithms” explored are evaluated using “root mean square error”, “mean absolute error” and “mean absolute percent error”. Four types of “time series” are taken into consideration. According to experimental findings, “seasonal decomposition” performs better on the time series having seasonality characteristic, followed by “linear interpolation”, and “kalman smoothing” provides values that are more similar to the original time series data set and have lower error rates than other imputation techniques.
Enhancing Microcomputer Edge Computing for Autonomous IoT Motion Control
Authors: Kamatchi S. Bangaru , Agme Vaishali N. , Premkumar S. , Prasad KDV , V Dankan Gowda , Gugan I
Published: April 2023

Devices microprocessors, microcontrollers, and Field Programmable Gate Arrays (FPGA) play the core rule at the IoT edge level and it should be right provisioned. For proper controller performance, control algorithms should be implemented near the actuator eliminating the delay effects. In the IoT domain, this means to implement the mentioned algorithm at the edge level and prior data transmitting. The efficient IoT-enabled motion control can be obtained by considering two main factors; the first factor is from the actuator design point of view and the second factor is from the controller performance point of view. Therefore, in this article, the two mentioned factors are treated concerning the microprocessor rule and importance as a core for proper prototype design and as the main platform to implement the control algorithms. A comparison of controller performance indices for both prototypes is done using previously distributed motion control schemes and newly developed schemes after tuning the respective schemes gains in an optimal manner. The scheme with better behavior of both prototypes are selected for the IoT integration process, this scheme ensures optimal edge computing for the distributed motion control, making the implementation of all control computation take place at the IoT-edge level. As a result, the dynamic pipeline stages (DPS) based prototype gives better controller performance indices for most strategies, less power consumption, and optimally utilized resources encouraging the use of the microprocessors with reconfigurable components at the IoT-edge level.
Rapidly Convergent Series from Positive Term Series
Authors: Nair Kumari Sreeja S
Published: April 2023

In this paper we shall give description about the extraction of a rapidly decaying remainder from Euler series and telescoping series. Then we apply the procedure to generalised telescoping series. The new positive term series obtained with rapidly decaying remainder will converge faster than the original series. We shall apply the procedure to generalised telescoping series also. The introduction of such remainder will give a better approximation for the series.
Stock Price Prediction using Bat Algorithm
Authors: K.P Shailaja , C S Akhil Yadav , M Manjunath
Published: April 2023

There is no such thing as a safe path of investment in the stock market because it is highly unpredictable, which has been a major concern of investors globally. As a result, stock market or stock price prediction has been a hot topic for scholars and researchers and a popular topic for investors worldwide.
Enhanced Deep Learning Models for Efficient Stroke Detection Using MRI Brain Imagery
Authors: Patil Anitha , Govindaraj Suresh Kumar
Published: April 2023

Deep learning models are widely used for solving problems in different applications. Especially Convolutional Neural Network (CNN) based models are found suitable for medical image analysis. As brain stroke is increasing in alarming rate, it is essential to have better approaches to detect it in time. Brain MRI is one of the medical imaging technologies widely used for brain imaging.we proposed certain advancements to well-known deep learning models like VGG16, ResNet50 and DenseNet121 for enhancing brain stroke detection performance. These models are optimized based on the brain stroke detection problem in hand as they are not specialized for a specific problem. We proposed an algorithm, named Deep Efficient Stroke Detection (ESD), that exploids enhanced deep learning models in pipeline. The experimental results revealed that there is performance improvement with optimized models. Highest accuracy is achieved by ResNet50 with 95.67%.
Children’s Perspective on Digital Picure Book: A Brief Analysis
Authors: Yang Li , Daimin Ghazali
Published: April 2023

Early exposure to symbolic media, such as pictures, drawings, paintings, photos, and videos, is common in western countries. Modern picture books coexist with electronic storybooks and other digital literature, expanding the environment in which young children develop and learn. Since the advent of new technologies, recommendations for kids' use of these gadgets have been covered in numerous papers. Young children and adults can engage in social interaction through picture books, which creates a wonderful chance for learning and teaching. This paper makes an analysis on children’s digital story book reading behavior. Initially, the features (considered questions) are clustered using k means clustering model. In order to analyze the children’s digital story book reading behavior, the questions are made on different drivers such as (i) Characteristics of story book, (ii) Interaction level and (iii) Child learning ability level. The questions are analyzed based upon the responses obtained from 100 respondents with 46 males and 54 females. Here, the study is done using ANOVA, regression analysis along with MSE, correlation and variance computation. Based upon the clustering outputs, the regression analysis is made on correlation and covariance metrics.
An Intelligent Approach to Reducing Plant Disease and Enhancing Productivity Using Machine Learning
Authors: Banerjee Saikat , Mondal Abhoy Chand
Published: April 2023

Plant diseases are a normal part of the natural world, and they are one of the many ecological processes that work together to keep the vast number of living organisms in the world in a state of equilibrium with one another. Each plant cell has its own set of signalling pathways that help the plant fight off viruses, animals, and insects. Concerns have been raised about whether or not it is possible to use machine learning to make crop predictions based mostly on weather data. The goal of the research is to help users choose the right crop to grow so that they can maximise their yield and, as a result, the money they make from the project. In a rural area where almost half the people work in agriculture, one of the most important problems is when farmers can't use traditional or other non-scientific methods to choose a crop that will grow well in their soil. Researchers can't make use of case studies as well as they could because there isn't enough correct and up-to-date information available. With the resources at our disposal, we have proposed a model that makes use of random forests and the genetic algorithm. This model has the potential to solve this problem by providing predictive insights on the long-term viability of crops and recommendations based on machine-reading models that have been trained to take important environmental parameters into consideration..
Effective Feature Selection Methods for User Sentiment Analysis using Machine Learning
Authors: Mujawar Sofiya S. , Bhaladhare Pawan R.
Published: April 2023

Text classification is the method of allocating a particular piece of text to one or more of a number of predetermined categories or labels. This is done by training a machine learning model on a labeled dataset, where the texts and their corresponding labels are provided. The model then learns to predict the labels of new, unseen texts. Feature selection is a significant step in text classification as it helps to identify the most relevant features or words in the text that are useful for predicting the label. This can include things like specific keywords or phrases, or even the frequency or placement of certain words in the text. The performance of the model can be improved by focusing on the features that are most important to the information that is most likely to be useful for classification. Additionally, feature selection can also help to reduce the dimensionality of the dataset, making the model more efficient and easier to interpret. A method for extracting aspect terms from product reviews is presented in the research paper. This method makes use of the Gini index, information gain, and feature selection in conjunction with the Machine learning classifiers. In the proposed method, which is referred to as wRMR, the Gini index and information gain are utilized for feature selection. Following that, machine learning classifiers are utilized in order to extract aspect terms from product reviews. A set of customer testimonials is used to assess how well the projected method works, and the findings indicate that in terms of the extraction of aspect terms, the method that has been proposed is superior to the method that has been traditionally used. In addition, the recommended approach is contrasted with methods that are currently thought of as being state-of-the-art, and the comparison reveals that the proposed method achieves superior performance compared to the other methods. In general, the method that was presented provides a promising solution for the extraction of aspect terms, and it can also be utilized for other natural language processing tasks.
Resource Allocation Energy Efficient Algorithm for H-CRAN in 5G
Authors: G Manjula , Deshmukh Pratibha , N. L. Udaya Kumar , Macedo Víctor Daniel Jiménez , K B Vikhyath , N Achyutha Prasad , Tiwari Amit Kumar
Published: April 2023

In today's generation, the demand for data rates has also increased due to the rapid surge in the number of users. With this increasing growth, there is a need to develop the next fifth generation network keeping in mind the need to replace the current 4G cellular network. The fifth generation (5G) design in mobile communication technology has been developed keeping in mind all the communication needs of the users. Heterogeneous Cloud Radio Access Network (H-CRAN) has emerged as a capable architecture for the newly emerging network infrastructure for energy efficient networks and high data rate enablement. It is considered as the main technology. Better service quality has been achieved by developing small cells into macro cells through this type of network. In addition, the reuse of radio resources is much better than that of homogeneous networks. In the present paper, we propose the H-CRAN energy-efficient methods. This energy-efficient algorithm incorporates an energy efficient resource allocation management design to deal to heterogeneous cloud radio access networks in 5G. System throughput fulfillment is elevating by incorporating an efficient resource allocation design by the energy consumption model. The simulation results have been demonstrated by comparing the efficiency of the introduced design with the existing related design.
Quantum Inspired Evolutionary Algorithm with a Novel Elitist Local Search Method for Scheduling of Thermal Units
Authors: Singh Jitender , Mani Ashish , Singh H.P. , Rana Dinesh Singh
Published: April 2023

The unit commitment problem is a complex and essential problem in the power generation field, which is solved to obtain the schedule of a large number of generating units to minimize the operating cost and the fulfillment of consumer load demand. The present work solves the unit commitment problem using quantum-inspired evolutionary algorithms with a novel elitist local search method (QIEA-ELS). The proposed algorithm solves the unit commitment problem efficiently and its applicability is verified on various unit test systems. The constraints are satisfied efficiently to find a feasible solution, the novel elitist search method is used to locally explore the search area around the fittest individual to find a better solution in its vicinity in genotype space represent by qubits. The solution of the unit commitment is carried out considering two small population sizes as suggested in earlier work by other authors using QIEA, though it can be extended using larger population size also. The computational time is also reduced by using the suggested method with a novel elitist local search (ELS) method. The results obtained after applying the proposed algorithm are found to better as compared to other well-known solution techniques.
Study of the effectiveness of the combined use of physical training and normobaric hypoxia in optimizing the functional state of people whose activities are associated with the use of high-speed vehicles
Authors: Buynov Leonid G. , Glaznikov Lev A. , Sorokina Lyudmila A. , Nigmedzyanov Ravil A.
Published: April 2023

Background. Currently, not only an increase in the number of various high-speed vehicles, but also the unlimited accessibility of the population to them in terms of gender, age and price parameters, are noted, which contributes to an increase in injuries, the root cause of which is often the insufficiency of the human statokinetic stability system.
Aim. To determine the effectiveness of the course use of physical exercises in combination with normobaric hypoxia in increasing the statokinetic stability of people with symptoms of statokinetic instability when traveling on high-speed public transport.
Material and methods. The study was performed with the participation of 47 practically healthy men (32 experimental group, 15 control) aged 1822 years, who were potential participants of the traffic. In order to increase statokinetic stability, the subjects of the experimental group trained the vestibular apparatus for 2 weeks using a modified test of A.I. Yarotsky in combination with normobaric hypoxia. The subjects of the control group received false courses of normobaric hypoxia, without physical training. Statistical processing of the obtained data was carried out using Student's parametric t-test.
Results. As a result of the studies, it was found that the subjects of the experimental group had a 101.0% increase in the tolerance time of continuous cumulation of Coriolis accelerations test while reducing the severity of the sensory, vegetative, somatic components of statokinetic reactions (by 50.0% feelings of heat, 25.0% heaviness in the head, 33.4% dizziness, 40.0% discomfort in the stomach). The obtained results were also confirmed by the positive dynamics of the indicators of the static stabilometric test of the complex functional computer stabilography.
Conclusion. The use of modified A.I. Yarotskys training in combination with normobaric hypoxia helps to optimize the functional state and increase the statokinetic stability of people whose activities involve driving high-speed vehicles.
Strategi Pemasaran Jasa Pendidikan dalam Membangun Citra di Sekolah Dasar Islam
Authors: Jannah Afika Nur , Ulfatin Nurul , Gunawan Imam
Published: April 2023

Abstract: This study aims to describe; (1) image of Islamic Elementary School Mohammad Hatta; (2) educational services marketing strategy for image to the community at SD Islam Mohammad Hatta; (3) the success of the results of the marketing strategy for image to the public. This study used a qualitative approach with descriptive case study research. The location of this research is in Mohammad Hatta Islamic Elementary School, Malang City. The data collection techniques used observation, interview, and observation techniques. This study uses a key informant, the principal of SD Islam Mohammad Hatta. The results of the study show that the educational services marketing strategy in building the image of the school in the eyes of the community is successful, as seen from a positive assessment of the image of the school and the increase in the number of students from year to year.

Abstrak: Penelitian ini bertujuan untuk mendeskripsikan; (1) gambaran citra SD Islam Mohammad Hatta; (2) strategi pemasaran jasa pendidikan untuk citra kepada masyarakat di SD Islam Mohammad Hatta; (3) keberhasilan hasil strategi pemasaran untuk citra kepada masyarakat. Penelitian ini menggunakan pendekatan kualitatif dengan jenis penelitian studi kasus deskriptif. Lokasi penelitian ini berada di SD Islam Mohammad Hatta kota Malang. Teknik pengumpulan data menggunakan teknik observasi, wawancara, dan observasi. Penelitian ini menggunakan informan kunci Kepala sekolah SD Islam Mohammad Hatta. Hasil dari penelitian menunjukkan strategi pemasaran jasa pendidikan dalam membangun citra sekolah dimata masyarakat berhasil, dilihat dari penilaian yang positif mengenai citra sekolah dan peningkatan jumlah peserta didik dari tahun ke tahun.
Knowledge, Attitude and Practice among Girls ’ in Schools towards Depression, Khamis Maushyt, the Governate of Aseer Region, 2015, Kingdom of Saudi Arabia
Authors: Essa Mariam Saeed Ibrahim , Khan Rosina , Shehri M. A. Al , Shahrani W.S Al , Abdalmagid M.A.
Published: April 2023

Background: Depression is an illness that involves the body, mind, and, thoughts that affect the way a person eats, sleep, feels about him/ her and thinks about things.

Objectives: The study aimed to assess knowledge, attitude and practice among girls in schools toward Depression, King Saudi Arabia, Khamis Maushyt, the Governate of Aseer Region.

Methods: Community based cross–sectional descriptive study was conducted in Khamis Mushayt School to identify knowledge, attitude and practice among girls towards depression. A total of 207 students (girls) were involved in the study. They were selected by using simple random sampling techniques. Data were collected through a questionnaire and analyzed using SPSS software version 20.

Result: The study showed that 180 (87%) students knew what depression means, 151(72.9%) of study group did not feel depressed, while 79 (38.2%) of the study group sometimes felt lonely. In the study, 50 (24.2%) of students go to the physician when they feel depressed and 53 (25.6%) students in the study group think that depression has medical treatment while 109 (52.7%) of study group believed that depression might have other treatment such as Holy Qur’an.

Conclusion: There is a need for a national intervention program to promote of adolescent mental health in schools. The program should include the screening of students using psychometric scales.
Assessment of Personal Hygiene Attitudes among Primary School Pupils in Umbada Locality, Khartoum state (2018-2020), Sudan
Authors: Essa Mariam Saeed Ibrahim , Abdalmajed M.A.
Published: April 2023

Background:  Personal hygiene is the behaviors that must be practiced in daily life, starting from morning to sleep time to protect our health.

Objectives: The current study aimed to assess personal hygiene attitudes among Primary School Pupils in Umbada Locality, Khartoum state, Sudan (2018-2020).

Materials and methods: An observational interventional study was conducted besides a pre- & post-assessment was done. Pre-test and post-test intervention was used to determine the practices of  hygiene among primary school Pupils in some selected schools of Umbada locality Alaemir unit. The targeted populations were primary school Pupils in Government schools only.  The study populations were the pupils in the Primary public schools by a total number of 37850 Pupils (grade 5, grade 6 and grade7) distributed among 180 public primary schools in the locality. The sample size   consisted of (800) pupils during the period of the study. A pre- and post- questionnaire was carefully prepared, tested and directed to the pupils. It covers pupil’s age, sex, and the classroom., source of water supply and latrine in the house there, and to obtain data regarding knowledge, attitudes, and practices (as regards personal hygiene in both pre and post intervention phases. Data was analyzed using Statistical Package for Social Sciences SPSS Computer Program Version (19.0). 

Results: The study revealed that the overall attitude of pupils, about personal hygiene was increased from 45.8% to 54.2 % after intervention of health education sessions. 

Conclusion: Health education has a significant role in promoting attitude of school pupils regarding personal hygiene. The need for more health education concerning personal hygiene to ensure that all children learn at an early age how to protect themselves and others from preventable exposure to  illness and other hazards related to poor hygiene. This can be carried out through formal (as a part of the curriculum) and informal health education messages.
Agua si, agua tampoco
Authors: Pastor Oscar
Published: April 2023

Para las autoridades y los representantes de la Sociedad Civil de la ciudad de Arequipa, la firma del convenio con la SMCV1 a mediados del año 2006, fue un hecho histórico, unos años más y se producirá el 100% de agua potable y se tratará el 100% de las aguas residuales de toda la ciudad. El documento suscrito con el aval del Premier de la República, no hizo mención a la ampliación de cobertura, llevar el agua potable y los servicios de saneamiento hasta el domicilio. La prensa en general y la escrita en particular actúo como correa de trasmisión entre las diferentes ideas, intereses y posiciones de los grupos que se van definiendo de acuerdo al desarrollo de los hechos. La historia reciente, construida públicamente nos muestra esta particularidad. Para analizar un hecho sin interés manifiesto, donde el investigador es simultáneamente informante, se requiere dejar de lado la subjetividad y asumir el convencimiento que la investigación no tiene como propósito presentar juicios de valor, son otros los que deben construirlos. Es natural que cada actor defienda sus ideas y es natural también que tenga estos argumentos presentes cuando evalúe su participación. Recurrir a los periódicos y extraer de allí los hechos es una forma de evitar la subjetividad.
Status of Lake Tana Commercial Fishery, Ethiopia
Authors: Tewabe Dereje
Published: April 2023

The status of Lake Tana Fishery was evaluated from analysis of commercial catch data of number I fishers cooperative. The data collection has been carried out from September 2003 to September 2009. Results indicated that Nile tilapia (Oreochromis niloticus), African catfish (Clarias gariepinus) and species flock of endemic, large Labeobarbus spp. were the three main species groups targeted by commercial gillnet fishery of Lake Tana and form 65 %, 20 % and 15 % of the annual catch compositions of fish species during the study period respectively. There was significant variability among sampling years encompassing temporal aspects. Especially, commercial catch of O. niloticus were significantly booming up to 2007 and declining after wards. The most likely explanations for the declining catch of O. niloticus and others are the illegal use of undersized monofilament gillnet imported from Sudan town (Gelabat) and the harmful increase of the commercial gillnet fishery targeting the spawning aggregations of L. barbus spp. and C. gariepinus in the river mouths and littoral areas. The observed decline in the commercial catch of O. niloticus and others stress the need for the urgent development of a management plan focusing on controlling import of undersized monofilament gillnet ,fishing effort and gear restrictions in the river mouths and major tributaries during the breeding seasons and implementing the regional fishery legislation.
Assessing the Impact of Core Banking and Service Quality on Customer Satisfaction in Commercial Bank of Ethiopia (A case of Bishofftu Branch)
Authors: Abebe Endalkachew
Published: April 2023

This research project focuses on identifying the impacts of core banking and service quality on customer satisfaction in commercial bank of Ethiopia Bishoftu branch. The main objective of this project is to assess the impact of core banking and services quality on customer satisfaction in commercial bank of Ethiopia. A sample of 220 customers was selected using stratified sampling technique, and among these 200 was considered. For the purpose of the study primary data were collected using likert scale based questionnaire. And the data was analyzed using descriptive statistics and inferential statistics. The result of this study shows that, there was significant relationship between all service quality dimension and customer satisfaction in commercial bank of Ethiopia. At the same time, there was significant relationship between core banking and customer satisfaction. The three service quality dimension (reliability, assurance, empathy) have positive and significant impact on customer satisfaction at the bank. However, the rest two dimensions (responsiveness and tangibility) have no impact on customer satisfaction Core banking also have positive and significant impact on customer satisfaction. Based on these, it is recommended that the bank should work more on the two service quality dimension (reliability and empathy) to enhance customer satisfaction.
The Prevalence of Diarrheal Disease in under Five Children and associated Risk Factors in Wolitta Soddo Town, Southern, Ethiopia
Authors: Alambo Kedir Addisu
Published: April 2023

Though the relationship between environmental risk factors and the occurrence of diarrhea in children have been documented elsewhere, there are limited studies in Ethiopia in general and in Soddo Town in particular. The present study assessed the prevalence and associated risk factors of under-five children diarrheal disease Community-based cross-sectional study was conducted in Soddo town, Southern Ethiopia. Nine hundred seventy (970) mothers/ care takers of index under-five children living in the households selected by systematic random sampling from Kebeles in the town constituted the study population. Data were collected using structured and pre-tested questionnaire, entered into a computer, edited and cleaned by using Epi info version 3.5.4 and analyzed using SPSS for windows version 16.0. Binary logistic regression model was used to calculate the Odds ratios and 95% confidence interval for the different risk factors and the level of significance was set at P < 0.05. Out of 970 sampled mother/caretaker-child pairs, 954 participated in the study and giving a response rate of 98.4%. The mean ages of the respondents and the index children were 27.62 (+5.03SD) years and 26.41(+15.89 SD) months, respectively. Prevalence of diarrheal disease over a period of two weeks preceding the study was about 11%. In the Bivariate analysis, a number of risk factors including monthly income less than five hundred birr and age of the child (P<0.05) appeared to be significantly associated with under-five childhood diarrheal disease and number of siblings under 5 years in a household, monthly income less than 500Birr and the age 12-23 months of the child were the only significant variables on multivariate analyses (P< 0.05). As diarrheal disease was major problem among under-five children in Soddo town. Appropriate intervention programs targeting Child birth spacing and improving the monthly income of households should be designed.