Search results for: learning assessment

Authors: Kehinde, Taye Adetutu

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The fact that Nigeria as a nation is faced by myriads of problems associated with religious crises and political insecurity is no news, the spoken statement and actions of most political giant were the major cause of this unrest. The 'unlearnt' youth within the regions has encompassed the situation. This scenario is further compounded by multilingual nature of the country as it is estimated that there exists amount 400 indigenous languages in Nigeria. It is an indisputable fact that english language which has assumed the status of an official language in Nigeria, given its status has a language of power and captivity by a few with no privilege to attend school. However, educating people in their indigenous language; crises can be averted through the proper orientation and mass literacy campaign, especially for the timid illiterate one, so as to live in unity, peace, tranquillity, and harmony as indivisible nation. In investigating the problem in this study with an emphasis on three major Nigerian language (Yoruba, Igbo and Hausa), participants observations and survey questionnaire were administered to about one hundred and twenty (120) respondents who were randomly selected throughout the three major ethnic groups in Nigeria. Findings from this study reveals that teaching and learning of cognitive words and information are more effective in ones mother tongue and helps in stimulating new ideas and changes. This paper was able to explore and critically examine the current state of affairs in Nigeria and proffer possible solutions to the prevailing situations by identifying how indigenous languages and linguistics can be used to ameliorate the present political and religious crisis for Nigeria, thus providing a proper recommendation to achieve meaningful stability and coexistence within a nation.

Keywords: multilingualism, political crisis, religious, Nigeria

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Sharareh Khodami, Misni Surif, Wan Maznah Wan Omar, Parto Bahreini

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Over the past three decades, Penang Island, Malaysia, has experienced rapid development across the industrial, urban, tourism, and aquaculture sectors. Consequently, wastewater from the Bayan Lepas Free Industrial Zone (FIZ) is discharged into a network of drainage canals and the Keluang River, which ultimately releases into the open sea near Jerjak Island. Among these waterways, the Keluang River is the largest canal receiving effluent from the Bayan Lepas FIZ. This study investigated the spatial and temporal variability of key physicochemical parameters water temperature, dissolved oxygen, salinity, pH, and nutrients (NO₃⁻, NO₂⁻, NH₄⁺, and PO₄³⁻) in the Bayan Lepas area. Water samples were collected from ten sampling stations (upstream, housing area, factory area, and coast) during low tide under both wet and dry seasonal conditions. The parameters were analyzed, and the spatial distribution of them were mapped using Geographic Information System (GIS) techniques. The observed ranges were 26–31.7 °C for water temperature, 0.3–9 mg/L for dissolved oxygen, 6.95–8.56 for pH, 0–30.1 ppt for salinity, 0.2–0.820 mg/L for nitrate, 0.002–0.090 mg/L for nitrite, 0.4–6.33 mg/L for ammonia, and 0.033–1.110 mg/L for phosphate. The selected stations exhibited characteristics ranging from fresh to saline water. One-way ANOVA showed that each parameter significantly differed among the stations during the two seasons (P < 0.05). The parameter values were evaluated against Malaysia's National Water Quality Standards (NWQS) and Marine Water Quality Criteria and Standards (MWQCS), and stations for each parameter were categorized from Class I to V. Results indicated that the Keluang River is polluted with high levels of ammonia and phosphate and low dissolved oxygen. The phosphate and ammonium concentrations at the river mouth of the Keluang River were 47.60 and 18.8 times higher than the standard values (0.056 mg/L and 0.024 mg/L), respectively. In light of the ongoing industrial expansion in the Bayan Lepas area, it is imperative to prioritize environmental protection and sustainable development practices to mitigate nutrient pollution and preserve the ecological health of the Keluang River and adjacent coastal regions.

Keywords: industrial impact, Keluang River, nutrient pollution, water quality

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Authors: T. Almutairi, K. Naudi, N. Nairn, X. Ju, B. Eng, J. Whitters, A. Ayoub

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Purpose: At present Cone Beam Computed Tomography (CBCT) imaging does not record dental morphology accurately due to the scattering produced by metallic restorations and the reported magnification. The aim of this pilot study is the development and validation of a new method for the replacement of the distorted dentition of CBCT scans with the dental image captured by the digital intraoral camera. Materials and Method: Six dried skulls with orthodontics brackets on the teeth were used in this study. Three intra-oral markers made of dental stone were constructed which were attached to orthodontics brackets. The skulls were CBCT scanned, and occlusal surface was captured using TRIOS® 3D intraoral scanner. Marker based and surface based registrations were performed to fuse the digital intra-oral scan(IOS) into the CBCT models. This produced a new composite digital model of the skull and dentition. The skulls were scanned again using the commercially accurate Laser Faro® arm to produce the 'gold standard' model for the assessment of the accuracy of the developed method. The accuracy of the method was assessed by measuring the distance between the occlusal surfaces of the new composite model and the 'gold standard' 3D model of the skull and teeth. The procedure was repeated a week apart to measure the reproducibility of the method. Results: The results showed no statistically significant difference between the measurements on the first and second occasions. The absolute mean distance between the new composite model and the laser model ranged between 0.11 mm to 0.20 mm. Conclusion: The dentition of the CBCT can be accurately replaced with the dental image captured by the intra-oral scanner to create a composite model. This method will improve the accuracy of orthognathic surgical prediction planning, with the final goal of the fabrication of a physical occlusal wafer without to guide orthognathic surgery and eliminate the need for dental impression.

Keywords: orthognathic surgery, superimposition, models, cone beam computed tomography

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: K. Anas, M. Selvakumar, Samson David, R. R. Babu, S. Chattopadhyay

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The dynamic deformation of a visco elastic material can cause heat generation. This heat generation is aspect energy dissipation. The present work investigates the contribution of various factors like; elastomer structure, cross link type and density, filler networking, reinforcement potential and temperature at energy dissipation mechanism. The influences of these elements are investigated using very high frequency analyzer (VHF ) and dynamical mechanical analysis(DMA).VHF follows transmissibility and vibration isolation principle whereas DMA works on dynamical mechanical deformation principle. VHF analysis of different types of elastomers reveals that elastomer can act as a transmitter or damper of energy depending on the applied frequency ratio (ω/ωn). Dynamic modulus (G') of low damping rubbers like natural rubber does not varies rapidly with frequency but vice-versa for high damping rubber like butyl rubber (IIR). VHF analysis also depicts that polysulfidic linkages has high damping ratio (ζ) than mono sulfidic linkages due to its dissipative nature. At comparable cross link density, mono sulfidic linkages shows higher glass transition temperature (Tg) than poly sulfidic linkages. The intensity and location of loss modulus (G'') peak of different types of carbon black filled natural rubber compounds suggests that segmental relaxation at glass transition temperature (Tg) is seldom affected by filler particles, but the filler networks can influence the cross link density by absorbing the curatives. The filler network breaking and reformation during a dynamic strain is a thermally activated process. Thus, stronger aggregates are highly dissipative in nature. Measurements indicate that at lower temperature regimes polymeric chain friction is highly dissipative in nature.

Keywords: damping ratio, natural frequency, crosslinking density, segmental motion, surface activity, dissipative, polymeric chain friction

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Authors: Emilie Zimet

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During networking and NCCD moderation meetings, best practices for identifying students who require Literacy Intervention are often discussed. Once these students are identified, consideration is given to the most effective process for prioritising those who have the greatest need for Literacy Support and the allocation of resources, tracking of intervention effectiveness and communicating with teachers/external providers/parents. Through a workshop, the group will investigate best practices to identify students who require literacy support and strategies to communicate and track their progress. In groups, participants will examine what they do in their settings and then compare with other models, including the researcher’s model, to decide the most effective path to identification and communication. Participants will complete a worksheet at the beginning of the session to deeply consider their current approaches. The participants will be asked to critically analyse their own identification processes for Literacy Intervention, ensuring students are not overlooked if they fall into the borderline category. A cut-off for students to access intervention will be considered so as not to place strain on already stretched resources along with the most effective allocation of resources. Furthermore, communicating learning needs and differentiation strategies to staff is paramount to the success of an intervention, and participants will look at the frequency of communication to share such strategies and updates. At the end of the session, the group will look at creating or evolving models that allow for best practices for the identification and communication of Literacy Interventions. The proposed outcome for this research is to develop a model of identification of students requiring Literacy Intervention that incorporates the allocation of resources and communication to key stakeholders. This will be done by pooling information and discussing a variety of models used in the participant's school settings.

Keywords: identification, student selection, communication, special education, school policy, planning for intervention

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Authors: Priyanka Govender, S. Mtshali, Theresa Moonsamy, Zanele Mkwanazi, L. Mthembu

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Chemically enhanced primary treatment (CEPT) can be used at wastewater works to improve the quality of the final effluent discharge, provided that the plant has spare anaerobic digestion capacity. CEPT can transfer part of the organic load to the digesters thereby effectively relieving the hydraulic loading on the plant and in this way can allow the plant to continue operating long after the hydraulic capacity of the plant has been exceeded. This can allow a plant to continue operating well beyond its original design capacity, requiring only fairly simple and inexpensive modifications to the primary settling tanks as well as additional chemical costs, thereby delaying or even avoiding the need for expensive capital upgrades. CEPT can also be effective at plants where high organic loadings prevent the wastewater discharge from meeting discharge standards, especially in the case of COD, phosphates and suspended solids. By increasing removals of these pollutants in the primary settling tanks, CEPT can enable the plant to conform to specifications without the need for costly upgrades. Laboratory trials were carried out recently at the Umbilo WWTW in Durban and these were followed by a baseline assessment of the current plant performance and a subsequent full scale trial on the Conventional plant i.e. West Plant. The operating conditions of the plant are described and the improvements obtained in COD, phosphate and suspended solids, are discussed. The PST and plant overall suspended solids removal efficiency increased by approximately 6% during the trial. Details regarding the effect that CEPT had on sludge production and the digesters are also provided. The cost implications of CEPT are discussed in terms of capital costs as well as operation and maintenance costs and the impact of Ferric chloride on the infrastructure was also studied and found to be minimal. It was concluded that CEPT improves the final quality of the discharge effluent, thereby improving the compliance of this effluent with the discharge license. It could also allow for a delay in upgrades to the plant, allowing the plant to operate above its design capacity. This will be elaborated further upon presentation.

Keywords: chemically enhanced, ferric, wastewater, primary

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Authors: Ebrahim Panah, Muhammad Yasir Babar

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Thanks to the development of online technology and social networks, people are able to communicate as well as learn. WhatsApp is a popular social network which is growingly gaining popularity. This app can be used for communication as well as education. It can be used for instructor-learner, learner-learner, and learner-content interactions; however, very little knowledge is available on these potentials of WhatsApp. The current study was undertaken to investigate university students’ perceptions of WhatsApp used as a tool for instructor-learner dialogue, learner-content dialogue, and learner-learner dialogue. The study adopted a survey approach and distributed the questionnaire developed by Google Forms to 54 (11 males and 43 females) university students. The obtained data were analyzed using SPSS version 20. The result of data analysis indicates that students have positive attitudes towards WhatsApp as a tool for Instructor-Learner Dialogue: it easy to reach the lecturer (4.07), the instructor gives me valuable feedback on my assignment (4.02), the instructor is supportive during course discussion and offers continuous support with the class (4.00). Learner-Content Dialogue: WhatsApp allows me to academically engage with lecturers anytime, anywhere (4.00), it helps to send graphics such as pictures or charts directly to the students (3.98), it also provides out of class, extra learning materials and homework (3.96), and Learner-Learner Dialogue: WhatsApp is a good tool for sharing knowledge with others (4.09), WhatsApp allows me to academically engage with peers anytime, anywhere (4.07), and we can interact with others through the use of group discussion (4.02). It was also found that there are significant positive correlations between students’ perceptions of Instructor-Learner Dialogue (ILD), Learner-Content Dialogue (LCD), Learner-Learner Dialogue (LLD) and WhatsApp Application in classroom. The findings of the study have implications for lectures, policy makers and curriculum developers.

Keywords: instructor-learner dialogue, learners-contents dialogue, learner-learner dialogue, whatsapp application

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Authors: Chan Hui-Ya, Ding Shin-Tan

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Background and Aim: The discharge planning is considered helpful to reduce the hospital length of stay and readmission rate, and then increased satisfaction with healthcare for patients and professionals. In order to decrease the waiting time of long-term care and boost the care quality of patients after discharge from the hospital, the Ministry of Health and Welfare department in Taiwan initiates a program “discharge planning connects with long-term care 2.0 services” in 2017. The purpose of this study is to investigate the outcome of the pilot of this program in a medical center. Methods: By purpose sampling, the study chose five wards in a medical center as pilot units. The researchers compared the beds of service, the numbers of cases which were transferred to the long-term care center and transferred rates per month between the pilot units and the other units, and analyze the basic data, the long-term care service needs and the approval service items of cases transfer to the long-term care center in pilot units. Results: From June to September 2017, a total of 92 referrals were made, and 51 patients were enrolled into the pilot program. There is a significant difference of transferring rate between the pilot units and the other units (χ = 702.6683, p < 0.001). Only 20 cases (39.2% success rate) were approved to accept the parts of service items of long-term care in the pilot units. The most approval item was respite care service (n = 13; 65%), while it was third at needs ranking of service lists during linking services process. Among the reasons of patients who cancelled the request, 38.71% reasons were related to the services which could not match the patients’ needs and expectation. Conclusion: The results indicate there is a requirement to modify the long-term care services to fit the needs of cases. The researchers suggest estimating the potential cases by screening data from hospital informatics systems and to hire more case manager according the service time of potential cases. Meanwhile, the strategies shortened the assessment scale and authorized hospital case managers to approve some items of long-term care should be considered.

Keywords: discharge planning, long-term care, case manager, patient care

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Authors: Abdul Rahmat

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Community-based education in the economic empowerment of the family is an attempt to accelerate human development index (HDI) Dumbo Kingdom District of Gorontalo economics (purchasing power) program developed in this activity is the manufacture of functional skills shredded fish, fish balls, fish nuggets, chips anchovies, and corn sticks fish. The target audience of this activity is fishing se mothers subdistrict Dumbo Kingdom include Talumolo Village, Village Botu, Kampung Bugis Village, Village North and Sub Leato South Leato that each village is represented by 20 participants so totaling 100 participants. Time activities beginning in October s/d November 2014 held once a week on every Saturday at 9.00 s/d 13:00/14:00. From the results of the learning process of testing the skills of functional skills of making shredded fish, fish balls, fish nuggets, chips anchovies, fish and corn sticks residents have additional knowledge and experience are: 1) Order the concept include: nutrient content, processing food with fish raw materials , variations in taste, packaging, pricing and marketing sales. 2) Products made: in accordance with the wishes of the residents learned that estimated Eligible selling, product packaging logo creation, preparation and realization of the establishment of Business Study Group (KBU) and pioneered the marketing network with restaurant, store / shop staple food vendors that are around CLC.

Keywords: community development, functional skills, gender, HDI

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Authors: Abel Olusegun Egunjobi, Olusegun Oyeleye Adesanya

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Teaching effectiveness of lecturers in a tertiary institution in Nigeria is one of the determinants of the lecturer’s productivity. In this study, therefore, lecturers’ teaching effectiveness was examined vis-à-vis their multimedia technologies utilisation in Colleges of Education (CoE) in South-West, Nigeria. This is for the purpose of ascertaining the relationship and contribution of multimedia technologies utilisation to lecturers’ teaching effectiveness in Nigerian colleges of education. The descriptive survey research design was adopted in the study, while a multi-stage sampling procedure was used in the study. A stratified sampling technique was used to select colleges of education, and a simple random sampling method was employed to select lecturers from the selected colleges of education. A total of 862 lecturers (627 males and 235 females) were selected from the colleges of education used for the study. The instrument used was lecturers’ questionnaire on multimedia technologies utilisation and teaching effectiveness with a reliability coefficient of 0.85 at 0.05 level of significance. The data collected were analysed using descriptive statistics, multiple regression, and t-test. The findings showed that the level of multimedia technologies utilisation in colleges of education was low, whereas lecturers’ teaching effectiveness was high. Findings also revealed that the lecturers used multimedia technologies purposely for personal and professional developments, so also for up to date news on economic and political matters. Also, findings indicated that laptop, Ipad, CD-ROMs, and computer instructional software were the multimedia technologies frequently utilised by the lecturers. There was also a significant difference in the teaching effectiveness between lecturers in the Federal and State COE. The government should, therefore, make adequate provision for multimedia technologies in the COE in Nigeria for lecturers’ utilisation in their instructions so as to boost their students’ learning outcomes.

Keywords: colleges of education, lecturers’ teaching effectiveness, multimedia technologies utilisation, Southwest Nigeria

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Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

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Authors: Buhari Samaila, Buhari Maidamma

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Background: The use of ionizing radiation in medical diagnostics and treatment is indispensable for accurate imaging and effective cancer therapies. However, radiation exposure carries inherent risks, necessitating strict protection measures to safeguard both patients and healthcare workers. This review critically examines the existing radiation protection measures in diagnostic radiology and radiotherapy, highlighting technological advancements, regulatory frameworks, and challenges. Objective: The objective of this review is to critically evaluate the effectiveness of current radiation protection measures in diagnostic and therapeutic radiology, focusing on minimizing patient and staff exposure to ionizing radiation while ensuring optimal clinical outcomes and propose future directions for improvement. Method: A comprehensive literature review was conducted, covering scientific studies, regulatory guidelines, and international standards on radiation protection in both diagnostic radiology and radiotherapy. Emphasis was placed on ALARA principles, dose optimization techniques, and protective measures for both patients and healthcare workers. Results: Radiation protection measures in diagnostic radiology include the use of shielding devices, minimizing exposure times, and employing advanced imaging technologies to reduce dose. In radiotherapy, accurate treatment planning and image-guided techniques enhance patient safety, while shielding and dose monitoring safeguard healthcare personnel. Challenges such as limited infrastructure in low-income settings and gaps in healthcare worker training persist, impacting the overall efficacy of protection strategies. Conclusion: While significant advancements have been made in radiation protection, challenges remain in optimizing safety, especially in resource-limited settings. Future efforts should focus on enhancing training, investing in advanced technologies, and strengthening regulatory compliance to ensure continuous improvement in radiation safety practices.

Keywords: radiation protection, diagnostic radiology, radiotherapy, ALARA, patient safety, healthcare worker safety

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Authors: Lizhi Ma, Dan Liu

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Pipeline parallelism has been widely used to accelerate distributed deep learning to alleviate GPU memory bottlenecks and to ensure that models can be trained and deployed smoothly under limited graphics memory conditions. However, in highly heterogeneous distributed clusters, traditional model partitioning methods are not able to achieve load balancing. The overlap of communication and computation is also a big challenge. In this paper, HePipe is proposed, an efficient pipeline parallel training method for highly heterogeneous clusters. According to the characteristics of the neural network model pipeline training task, oriented to the 2-level heterogeneous cluster computing topology, a training method based on the 2-level stage division of neural network modeling and partitioning is designed to improve the parallelism. Additionally, a multi-forward 1F1B scheduling strategy is designed to accelerate the training time of each stage by executing the computation units in advance to maximize the overlap between the forward propagation communication and backward propagation computation. Finally, a dynamic recomputation strategy based on task memory requirement prediction is proposed to improve the fitness ratio of task and memory, which improves the throughput of the cluster and solves the memory shortfall problem caused by memory differences in heterogeneous clusters. The empirical results show that HePipe improves the training speed by 1.6×−2.2× over the existing asynchronous pipeline baselines.

Keywords: pipeline parallelism, heterogeneous cluster, model training, 2-level stage partitioning

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Authors: M. Achemo, O. Saito

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Jefoure land use system is one of the traditional landscape human settlement patterns, and it is a cultural design and peculiar art of the people of Gurage in Ethiopia via which houses and trees flank roads left and right. Assessment of the multiple benefits of the traditional road that benefit society and development could enhance the understanding of the land use planners and decision makers to pay attention while planning and managing the land use system. Recent trend shows that the Jefoure land use is on the threshold of change as a result of flourishing road networks, overgrazing, and agricultural expansion. This study aimed to evaluate the multiple ecosystem services provided by the Jefoure land use system after characterization of the socio-ecological landscape. Information was compiled from existing data sources such as ordnance survey maps, aerial photographs, recent high resolution satellite imageries, designated questionnaires and interviews, and local authority contacts. The result generated scientific data on the characteristics, ecosystem services provision, and drivers of changes. The cultural landscape has novel characteristics and providing multiple ecosystem services to the community for long period of time. It is serving as road for humans, livestock and vehicles, habitat for plant species, regulating local temperature, climate, runoff and infiltration, and place for meeting, conducting religious and spiritual activities, holding social events such as marriage and mourning, playing station for children and court for football and other traditional games. As a result of its aesthetic quality and scenic beauty, it is considered as recreational place for improving mental and physical health. The study draws relevant land use planning and management solution in the improvement of socio-ecological resilience in the Jefoure land use system. The study suggests the landscape needs to be registrar as heritage site for recognizing the wisdom of the community and enhancing the conservation mechanisms.

Keywords: cultural landscape, ecosystem services, Gurage, Jefoure

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Authors: Loonibha Manandhar, Rajendra Bhandari, Kumud Raj Kafle

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Nepal’s Terai region is a part of the Ganges river basin which is one of the most disaster-prone areas of the world, with recurrent monsoon flooding causing millions in damage and the death and displacement of hundreds of people and households every year. The vulnerability of human settlements to natural disasters such as floods is increasing, and mapping changes in land use practices and hydro-geological parameters is essential in developing resilient communities and strong disaster management policies. The objective of this study was to develop a flood hazard zonation map of Orai Khola watershed and map the decadal land use/land cover dynamics of the watershed. The watershed area was delineated using SRTM DEM, and LANDSAT images were classified into five land use classes (forest, grassland, sediment and bare land, settlement area and cropland, and water body) using pixel-based semi-automated supervised maximum likelihood classification. Decadal changes in each class were then quantified using spatial modelling. Flood hazard mapping was performed by assigning weights to factors slope, rainfall distribution, distance from the river and land use/land cover on the basis of their estimated influence in causing flood hazard and performing weighed overlay analysis to identify areas that are highly vulnerable. The forest and grassland coverage increased by 11.53 km² (3.8%) and 1.43 km² (0.47%) from 1996 to 2016. The sediment and bare land areas decreased by 12.45 km² (4.12%) from 1996 to 2016 whereas settlement and cropland areas showed a consistent increase to 14.22 km² (4.7%). Waterbody coverage also increased to 0.3 km² (0.09%) from 1996-2016. 1.27% (3.65 km²) of total watershed area was categorized into very low hazard zone, 20.94% (60.31 km²) area into low hazard zone, 37.59% (108.3 km²) area into moderate hazard zone, 29.25% (84.27 km²) area into high hazard zone and 31 villages which comprised 10.95% (31.55 km²) were categorized into high hazard zone area.

Keywords: flood hazard, land use/land cover, Orai river, supervised maximum likelihood classification, weighed overlay analysis

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Authors: S. Sandri, G. M. Contessa, C. Poggi

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An experimental nuclear fusion device could be seen as a step toward the development of the future nuclear fusion power plant. If compared with other possible solutions to the energy problem, nuclear fusion has advantages that ensure sustainability and security. In particular considering the radioactivity and the radioactive waste produced, in a nuclear fusion plant the component materials could be selected in order to limit the decay period, making it possible the recycling in a new reactor after about 100 years from the beginning of the decommissioning. To achieve this and other pertinent goals many experimental machines have been developed and operated worldwide in the last decades, underlining that radiation protection and workers exposure are critical aspects of these facilities due to the high flux, high energy neutrons produced in the fusion reactions. Direct radiation, material activation, tritium diffusion and other related issues pose a real challenge to the demonstration that these devices are safer than the nuclear fission facilities. In Italy, a limited number of fusion facilities have been constructed and operated since 30 years ago, mainly at the ENEA Frascati Center, and the radiation protection approach, addressed by the national licensing requirements, shows that it is not always easy to respect the constraints for the workers' exposure to ionizing radiation. In the current analysis, the main radiation protection issues encountered in the Italian Fusion facilities are considered and discussed, and the technical and legal requirements are described. The licensing process for these kinds of devices is outlined and compared with that of other European countries. The following aspects are considered throughout the current study: i) description of the installation, plant and systems, ii) suitability of the area, buildings, and structures, iii) radioprotection structures and organization, iv) exposure of personnel, v) accident analysis and relevant radiological consequences, vi) radioactive wastes assessment and management. In conclusion, the analysis points out the needing of a special attention to the radiological exposure of the workers in order to demonstrate at least the same level of safety as that reached at the nuclear fission facilities.

Keywords: fusion facilities, high energy neutrons, licensing process, radiation protection

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Authors: Ishith Seth, Lyndel Hewitt, Takako Yabe, James Wykes, Jonathan Clark, Bruce Ashford

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Background: Vastus lateralis (VL) can be used to reconstruct defects of the head and neck. Whilst the advantages are documented, donor-site morbidity is not well described. This study aimed to assess donor-site morbidity after VL flap harvest. The results will determine future directions for preventative and post-operative care to improve patient health outcomes. Methods: Ten participants (mean age 55 years) were assessed for the presence of donor-site morbidity after VL harvest. Musculoskeletal (pain, muscle strength, muscle length, tactile sensation), quality of life (SF-12), and lower limb function (lower extremity function, gait (function and speed), sit to stand were assessed using validated and standardized procedures. Outcomes were compared to age-matched healthy reference values or the non-operative side. Analyses were conducted using descriptive statistics and non-parametric tests. Results: There was no difference in muscle strength (knee extension), muscle length, ability to sit-to-stand, or gait function (all P > 0.05). Knee flexor muscle strength was significantly less on the operated leg compared to the non-operated leg (P=0.02) and walking speed was slower than age-matched healthy values (P<0.001). Thigh tactile sensation was impaired in 89% of participants. Quality of life was significantly less for the physical health component of the SF-12 (P<0.001). The mental health component of the SF-12 was similar to healthy controls (P=0.26). Conclusion: There was no effect on donor site morbidity with regards to knee extensor strength, pain, walking function, ability to sit-to-stand, and muscle length. VL harvest affected donor-site knee flexion strength, walking speed, tactile sensation, and physical health-related quality of life.

Keywords: vastus lateralis, morbidity, head and neck, surgery, donor-site morbidity

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Authors: Sukjai Charoensuk, Penphan Pitaksongkram, Michael Christopher

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Preliminary evidences supported the effectiveness of mindfulness-based interventions in reducing symptoms associated with a variety of medical and psychological conditions. However, the measurements of mindfulness are questionable since they have not been developed based-on Buddhist experiences. The purpose of this qualitative study was to describe meaning and cultivating factors of mindfulness as experienced by Thai females who practice Dhamma. Participants were purposively selected to include 2 groups of Thai females who practice Dhamma. The first group consisted of 6 female Buddhist monks, and the second group consisted of 7 female who practice Dhamma without ordaining. Data were collected using in-depth interview. The instruments used were demographic data questionnaire and guideline for in-depth interview developed by researchers. Content analysis was employed to analyze the data. The results revealed that Thai women who practice Dhamma described their experience in 2 themes, which were meaning and cultivating factors of mindfulness. The meaning composed of 4 categories; 1) Being Present, 2) Self-awareness, 3) Contemplation, and 4) Neutral. The cultivating factors of mindfulness composed of 2 categories; In-personal factors and Ex-personal factors. The In-personal cultivating factors included 4 sub-categories; Faith and Love, the Five Precepts, Sound body, and Practice. The Ex-personal cultivating factors included 2 sub-categories; Serenity, and Learning. These findings increase understanding about meaning of mindfulness and its cultivating factors. These could be used as a guideline to promote mental health and develop nursing interventions using mindfulness based, as well as, develop the instrument for assessing mindfulness in Thai context.

Keywords: cultivating factor, meaning of mindfulness, practice Dhamma, Thai women

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: angle of internal friction, cone penetrating test, general regression neural network, soil modulus of elasticity

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Authors: Yarhands Dissou Arthur, Samuel Asiedu Addo, Jonathan Annan

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Interest in subject specific is very essential in the quest to ensure effective teaching and learning. In building interest in subject specific areas requires certain factors and strategies well-spelled out.The factors such as the gender of the student, the type of basic school attended, the parent interest as well as the scare of the basic school mathematics teacher is very important to consider. The relational effect and the contribution these above mentioned variables on student have not been fully investigated and this paper address the effect of these factors on the student interest. In the attainment of this goal, the current paper addresses the effect of parent interest, the type of basic school attended, the scare by basic school mathematics teacher and its effect on student’s interest in mathematics. A cross sectional data collected from two hundred and sixty post-secondary school student were analyzed using descriptive and inferential statistical methods by aid of SPSS version 16. The study found that parent interest and value for mathematics significantly influenced students interest and joy in solving mathematical problems. Moreover, we also observed that the fear imposed by basic school mathematics teachers was found to significantly influence students’ interest. The study further found that the type of basic school attended and gender are factors that do not influence students’ interest in mathematics. In addition to concluding that a student’s interest is influenced by both parent interest and the fear of basic school mathematics teacher, the study also showed that the type of basic school attended and gender does not affect the students’ interest in mathematics.

Keywords: gender, mathematics interest, teacher interest, teacher interest, student interest

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Authors: Gizachew Assefa Tessema, Mohammad Afzal Mahmood, Judith Streak Gomersall, Caroline O. Laurence

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Introduction: Improving access to quality family planning services is the key to improving health of women and children. However, there is currently little evidence on the quality and scope of family planning services provided by private facilities, and this compares to the services provided in public facilities in Ethiopia. This is important, particularly in determining whether the government should further expand the roles of the private sector in the delivery of family planning facility. Methods: This study used the 2014 Ethiopian Services Provision Assessment Plus (ESPA+) survey dataset for comparing the structural aspects of quality of care in family planning services. The present analysis used a weighted sample of 1093 primary health care facilities (955 public and 138 private). This study employed logistic regression analysis to compare key structural variables between public and private facilities. While taking the structural variables as an outcome for comparison, the facility type (public vs private) were used as the key exposure of interest. Results: When comparing availability of basic amenities (infrastructure), public facilities were less likely to have functional cell phones (AOR=0.12; 95% CI: 0.07-0.21), and water supply (AOR=0.29; 95% CI: 0.15-0.58) than private facilities. However, public facilities were more likely to have staff available 24 hours in the facility (AOR=0.12; 95% CI: 0.07-0.21), providers having family planning related training in the past 24 months (AOR=4.4; 95% CI: 2.51, 7.64) and possessing guidelines/protocols (AOR= 3.1 95% CI: 1.87, 5.24) than private facilities. Moreover, comparing the availability of equipment, public facilities had higher odds of having pelvic model for IUD demonstration (AOR=2.60; 95% CI: 1.35, 5.01) and penile model for condom demonstration (AOR=2.51; 95% CI: 1.32, 4.78) than private facilities. Conclusion: The present study suggests that Ethiopian government needs to provide emphasis towards the private sector in terms of providing family planning guidelines and training on family planning services for their staff. It is also worthwhile for the public health facilities to allocate funding for improving the availability of basic amenities. Implications for policy and/ or practice: This study calls policy makers to design appropriate strategies in providing opportunities for training a health care providers working in private health facility.

Keywords: quality of care, family planning, public-private, Ethiopia

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Uliana N. Tumanova, Viacheslav M. Lyapin, Vladimir G. Bychenko, Alexandr I. Shchegolev, Gennady T. Sukhikh

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All cases of stillbirth undoubtedly subject to postmortem examination, since it is necessary to find out the cause of the stillbirths, as well as a forecast of future pregnancies and their outcomes. Determination of the time of death is an important issue which is addressed during the examination of the body of a stillborn. It is mean the period from the time of death until the birth of the fetus. The time for fetal deaths determination is based on the assessment of the severity of the processes of maceration. To study the possibilities of postmortem magnetic resonance imaging (MRI) for determining the time of intrauterine fetal death based on the evaluation of maceration in the kidney. We have conducted MRI morphological comparisons of 7 dead fetuses (18-21 gestational weeks) and 26 stillbirths (22-39 gestational weeks), and 15 bodies of died newborns at the age of 2 hours – 36 days. Postmortem MRI 3T was performed before the autopsy. The signal intensity of the kidney tissue (SIK), pleural fluid (SIF), external air (SIA) was determined on T1-WI and T2-WI. Macroscopic and histological signs of maceration severity and time of death were evaluated in the autopsy. Based on the results of the morphological study, the degree of maceration varied from 0 to 4. In 13 cases, the time of intrauterine death was up to 6 hours, in 2 cases - 6-12 hours, in 4 -12-24 hours, in 9 -2-3 days, in 3 -1 week, in 2 -1,5-2 weeks. At 15 dead newborns, signs of maceration were absent, naturally. Based on the data from SIK, SIF, SIA on MR-tomograms, we calculated the coefficient of MR-maceration (M). The calculation of the time of intrauterine death (MP-t) (hours) was performed by our formula: МR-t = 16,87+95,38×М²-75,32×М. A direct positive correlation of MR-t and autopsy data from the dead at the gestational ages 22-40 weeks, with a dead time, not more than 1 week, was received. The maceration at the antenatal fetal death is characterized by changes in T1-WI and T2-WI signals at postmortem MRI. The calculation of MP-t allows defining accurately the time of intrauterine death within one week at the stillbirths who died on 22-40 gestational weeks. Thus, our study convincingly demonstrates that radiological methods can be used for postmortem study of the bodies, in particular, the bodies of stillborn to determine the time of intrauterine death. Postmortem MRI allows for an objective and sufficiently accurate analysis of pathological processes with the possibility of their documentation, storage, and analysis after the burial of the body.

Keywords: intrauterine death, maceration, postmortem MRI, stillborn

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Authors: Sakda Loetpiparwanich, Preecha Vichitthamaros

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Nowadays, poor data quality is considered one of the majority costs for a data project. The data project with data quality awareness almost as much time to data quality processes while data project without data quality awareness negatively impacts financial resources, efficiency, productivity, and credibility. One of the processes that take a long time is defining the expectations and measurements of data quality because the expectation is different up to the purpose of each data project. Especially, big data project that maybe involves with many datasets and stakeholders, that take a long time to discuss and define quality expectations and measurements. Therefore, this study aimed at developing meaningful indicators to describe overall data quality for each dataset to quick comparison and priority. The objectives of this study were to: (1) Develop a practical data quality indicators and measurements, (2) Develop data quality dimensions based on statistical characteristics and (3) Develop Composite Indicator that can describe overall data quality for each dataset. The sample consisted of more than 500 datasets from public sources obtained by random sampling. After datasets were collected, there are five steps to develop the Dataset Quality Index (SDQI). First, we define standard data quality expectations. Second, we find any indicators that can measure directly to data within datasets. Thirdly, each indicator aggregates to dimension using factor analysis. Next, the indicators and dimensions were weighted by an effort for data preparing process and usability. Finally, the dimensions aggregate to Composite Indicator. The results of these analyses showed that: (1) The developed useful indicators and measurements contained ten indicators. (2) the developed data quality dimension based on statistical characteristics, we found that ten indicators can be reduced to 4 dimensions. (3) The developed Composite Indicator, we found that the SDQI can describe overall datasets quality of each dataset and can separate into 3 Level as Good Quality, Acceptable Quality, and Poor Quality. The conclusion, the SDQI provide an overall description of data quality within datasets and meaningful composition. We can use SQDI to assess for all data in the data project, effort estimation, and priority. The SDQI also work well with Agile Method by using SDQI to assessment in the first sprint. After passing the initial evaluation, we can add more specific data quality indicators into the next sprint.

Keywords: data quality, dataset quality, data quality management, composite indicator, factor analysis, principal component analysis

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Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

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Authors: Abubakar Maitama Yusuf Hotoro, Olokpo Israel Olofu, Yusuf U. Tarauni, Mudassir A. Umar, Aliyu A, Dahiru Garba Diso, Usman H. Jamoh, M. Sale

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The study assessed the impact of environmental pollution on groundwater potential at Tudun Murtala waste land fill using electrical resistivity, induced polarization and Physiochemical methods. The study area is located between latitude 12.023678N and longitude 8.573676 E. Geophysical data were collected at maximum length of 140m along twelve profiles using ABEM Terrameter SAS 1000. Results from the Geophysical analysis showed that the profiles were underlain by three lithological layers; the top layer consisting of Loamy and Sand soils, alluvium, granite, shale and sandstone. The second and third layers were predominantly made of weathered and fractured basements respectively. The potential groundwater water bearing zones of the study area occurred at VES2, VES4, VES5, VES6 and VES7. The thicknesses of the sounding points were found to be 20.8m at VES2; 25.2m at VES4; 13.2m at VES5; 50.8m at VES6 and 13.3m at VES7. The corresponding depths for the sounding points were 20.8m at VES2; 27.9m at VES4; 26.7m at VES5; 51.6m at VES6 and 24.9m at VES7 respectively. The Physiochemical study of selected groundwater samples assessed parameters such as the Electrical Conductivity, EC (288dS/m to 1365dS/m), TDS (170.8mg/L to 820mg/L) Pb (0.546mg/l to 0.629mg/l), Cu (-0.001mg/l to 0.004mg/l), and Cd (0.031mg/l to 0.092mg/l). The physiochemical results showed that the groundwater around the dumpsite may have been contaminated, especially in Dumpsite Hole 1 and Hole 2 at VES4 and VES6 respectively. There are indications for suspected leachate mitigation around the two VES points. Even though, the pH values of 6.4 and 6.2 at the two sounding points were considered to be within the permissible pH range (6.5 to 6.8). The values of other elements present in the groundwater for the samples at other VES points were found to be above permissible WHO and Nigerian Standards for Drinking Water.

Keywords: resistivity induced polarization, chargeability, landfill, leachate, contamination

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