Miracle-dz/UniFAR-FTUs huggingface dataset:
ARABIC TEXT

Title of Dissertation: Probabilistic Methods for Searching OCR-Degrad ed Arabic Text Kareem Darwish, Doctor of Philosophy, 2003 Dissertation directed by: Dr. Bruce Jacob Department of Electrical and Computer Engineering Dr. Douglas W. Oard College of Information Studies Since many Arabic documents are available only in print, automating retri eval from collections of scanned Arabic document images using Optical Character Recogni tion (OCR) is an important problem. This dissertation addresses retrieval of Ara bic document images based on OCR, with emphasis on probabilistic methods to improve retrieval effectiveness. Arabic’s rich morphology (word construction) and complex orthograph y (writing system) present unique challenges for OCR and Information Ret rieval (IR) systems. New probabilistic structured query methods that leverage replacement probabi lities were developed in this research to improve retrieval effectiveness in OCR degraded te xt retrieval and their generality has been shown in cross-language inform ati n retrieval. For the OCR-degraded text retrieval, the probabilistic structured query methods w ere applied using the most effective index terms for OCR-degraded text, with replacement probabilities estimated using an OCR degradation model. Overlapping character n-grams and combinations of character n-grams with terms obtained through morphological analysis were found to be the most effective indexing terms for Arabic colle ti ns of varying sizes, genres, and degradation levels. For index terms requiring morphol ogical analysis, existing automated Arabic morphological analysis techniques wer adapted to make them more suitable for IR applications. Different OCR models were devel op d to account for the complex Arabic orthography and a group of tests were crafted to veri fy that modeled and real OCR degradation have similar effects on IR. One of the models was also used to synthetically degrade a large document collection. The techniques presented in this dissertation offer the potential to unlock access t o printed documents of Arabic and other languages with similar orthographic characteristics. PROBABILISTIC METHODS FOR SEARCHING OCR-DEGRADED ARABIC TEXT
Systematic Review and Meta-analysis of Real-time Polymerase Chain Reaction assay for the detection of COVID-19 from clinical samples in low-and middle-income countries: Protocol

Background: COVID-19 has spread globally since its discovery in Hubei province, China in December 2019 and became pandemic in 2020. COVID-19 is a new betacoronavirus and a variant of severe acute respiratory syndrome coronavirus 2 (SARA- CoV-2). Rapid, accurate and reliable diagnosis of COVID-19 will prevent the spread and allow for appropriate management. The main objective of this systematic review is to identify, appraise and summarise the published evidence on the diagnostic performance and effectiveness of SARS-CoV-2 virus in the diagnosis of current or previous COVID-19 using real-time polymerase chain reaction (RT-PCR) assay in low-and middle-income countries (LMICs). Methods: We will search MEDLINE/PubMed, EMBASE, BIOSIS, LILACS, Cochrane Infectious Diseases Group Specialised Register (CIDG SR), Global Health, and CINAHL for published studies for the diagnosis of COVID-19 using real-time polymerase chain reaction assay in LMICs There will be no restriction regarding the language, date of publication, and publication status. We will include retrospective, cross-sectional and cohort observational studies will be included in the review. Selection of studies, data extraction and management, assessment of risk of bias, and quality of evidence will be performed by two independent reviewers (EB and BC). A third researcher (GM) will be consulted in case of discrepancies. Depending on the availability and quality of the data, a meta-analysis will be performed. Otherwise, findings will be qualitatively reported. Discussion: To our knowledge, this is the first systematic review and meta-analysis to assess the uptake of RT-PCR assay for SARS-CoV-2 detection from clinical samples in human in LMICs. This review will make available evidence on the uptake, accuracy, approach, and interpretation of results of this assay in the context of COVID-19 diagnosis which will meet an urgent need, considering the diagnostic challenges of RT-PCR assay for COVID-19 diagnosis in humans. Systematic review registration: PROSPERO CRD42021271894
Numerical study of the heat transfer effect on a centrifugal compressor performance

This paper presents a study of the heat transfer influence on the centrifugal compressor performance. The compressor studied in this paper is based on the scale-up of a turbocharger compressor equipped with a shroudless impeller. To account for the heat transfer effect, a conjugate heat transfer analysis is performed with computational fluid dynamics techniques. The heat transfer phenomena not only externally but also internally are investigated at the design point. The grids adopted in the study are verified at the baseline, with an excellent agreement found between numerical simulations and measurements. The results provide an insight into the dependence of the heat transfer influences on the heat flux paths. The path of the external heat flux passing through the impeller shaft is found to have a great impact on the compressor performance. The study of internal heat transfer shows that the shroud surface dominates the internal heat transfer effect on the efficiency loss. Furthermore, the heat transfer influence is also investigated on the compressor performance at other operating points. The results imply a positive potential margin for the improvement of compressor efficiency by means of heat transfer control.
Experimental Studies of Pipeline Uplift Resistance in Frozen Ground

A buried pipeline is subject to a variety of internal and external loads, one of which is the load induced by relative movements between the pipeline and the surrounding soils. Frost heave is one of the potential mechanisms that induce the relative movement for buried pipelines of chilled gas. The magnitude of the loads due to frost heave depends upon the amount of heaving and the load-displacement characteristics of the surrounding frozen soils, i.e., the uplift resistance of the frozen soils. Under the sponsorship of Pipeline Research Council International (PRCI), laboratory uplift tests have been carried out to study the load-displacement characteristics of a frozen soil and to assess the impact of loading rate, ice content and freezing direction. In addition to the measurements of the load and displacement of the pipe, deformations of the soil surface were also monitored at various locations. Parallel to the uplift tests, a series of laboratory geo-mechanical tests were conducted to define stiffness, tensile strain limits and time-dependent behavior of the frozen soil. Examples of the uplift test results are presented in the paper, together with detailed descriptions of soil material and test conditions. It is noted that quantitative data on uplift resistance are considered proprietary and will not be presented in this paper; however, detailed data may be obtained from technical publications of PRCI. Observations during the test with respect to the development of cracks in the frozen soil will be discussed. The load-displacement relationships measured in the uplift tests, together with the geo-mechanical properties of the frozen soil, will be used to the development and calibration of a numerical model, which will be presented in a separate technical paper to IPC2004.Copyright © 2004 by ASME
A new model for manufacturing supply chain networks: A multiagent approach

Abstract Participating members in a manufacturing supply chain usually make use of an information system like enterprise resources planning (ERP) for planning and scheduling activities independently. Recent research indicates that there is a need to handle such distributed activities in an integrated manner, especially under uncertain and fast changing environments. A multiagent system, a branch of distributed artificial intelligence, is a contemporary modelling technique for a distributed system in the manufacturing domain. This distributed modelling technique is suitable for integrating supply chain networks, which have distributed entities within the system, and each of them makes decision locally, i.e. a local information system. By adopting a multiagent modelling technique, supply chain networks can be built efficiently based on an information system. However, with reference to the reported research, which involves distributed modelling of a supply chain, a higher level coordination mechanism is not specified. This paper aims to propose a framework that utilizes a multiagent system with a corresponding coordination mechanism dedicated to manufacturing supply chain networks.
Acoustic emission intensity analysis of corrosion in prestressed concrete piles

Corrosion of steel strands in prestressed concrete (PC) bridges may lead to substantial damage or collapse well before the end of the design life. Acoustic Emission (AE) is a suitable nondestructive technique to detect and locate corrosion in reinforced and prestressed concrete, which is key to prioritize inspection and maintenance. An effective tool to analyze damage-related AE data is intensity analysis (IA), which is based on two data trends, namely Severity (average signal strength of high amplitude hits) and Historic Index (ratio of the average signal strength of the most recent hits to the average of all hits). IA criteria for corrosion assessment in PC were recently proposed based on empirical evidence from accelerated corrosion tests. In this paper, AE data from prestressed and non-prestressed concrete pile specimens exposed to salt water wet-dry cycling for over 600 days are used to analyze the relation between Severity and Historic Index and actual corrosion. Evidence of corrosion is gained from the inspection of decommissioned specimens. The selection of suitable J and K parameters for IA is discussed, and an IA chart with updated corrosion criteria for PC piles is presented.Corrosion of steel strands in prestressed concrete (PC) bridges may lead to substantial damage or collapse well before the end of the design life. Acoustic Emission (AE) is a suitable nondestructive technique to detect and locate corrosion in reinforced and prestressed concrete, which is key to prioritize inspection and maintenance. An effective tool to analyze damage-related AE data is intensity analysis (IA), which is based on two data trends, namely Severity (average signal strength of high amplitude hits) and Historic Index (ratio of the average signal strength of the most recent hits to the average of all hits). IA criteria for corrosion assessment in PC were recently proposed based on empirical evidence from accelerated corrosion tests. In this paper, AE data from prestressed and non-prestressed concrete pile specimens exposed to salt water wet-dry cycling for over 600 days are used to analyze the relation between Severity and Historic Index and actual corrosion. Evidence of corrosion is gained from.
A collaborative decision support framework for managing the evolution of virtual enterprises

During the operation phase of a virtual enterprise (VE) different kinds of unexpected problems usually take place and they should be properly handled in order to keep the VE goals. However, the nature of a VE imposes new requirements as decisions should be taken in a distributed and decentralised manner due to members’ autonomy and independence. Besides quality, agility in the decision-making is a must to guarantee success. For that, this paper presents a framework that provides a supporting methodology for guiding VE members along the diverse steps in the problem resolution, including assistance in their discussion. The framework relies on Business Process Management (BPM) and Service Oriented Architecture (SOA) approaches, and the methodology on project management reference models (focused on changes management). A discussion about the problem is driven by a semi-automated protocol conducted by a Distributed Collaborative Decision Support System for the Management of VE Evolution (DSS-VE). The protocol delineates a sequence of steps to be taken but is flexible to cope with partners’ heterogeneity and VE uniqueness. The impact of decisions can be evaluated via a distributed toolbox, containing a set of techniques for performance measurement and evaluation analysis.
6.1.1 A Framework for Harmonizing Systems Engineering and Off‐The‐Shelf Procurement Processes

Systems engineering, as a discipline, has been utilized since the middle of the twentieth century to successfully execute numerous complex system developments. Many of the practices and standards utilized are perceived as being biased towards new development systems. With the changing imperative to deliver “to market” quicker and cheaper, many programs are placing a higher reliance on the use of Off‐The‐Shelf (OTS) components in the final system solution. Integrating this strategy into traditional systems engineering practices has led to challenges in the past.
The research skill factor as a cause for high postgraduate attrition rate

Purpose – This paper aims in the first part to document experiences encountered in dealing with challenges facing students embarking on their postgraduate research journey. It gives a brief background on the consequences for not being able to handle properly the research processes. It also identifies factors that contribute to postgraduate attrition and long completion periods focusing on the perceived major contributor to problem – the lack of skills in research on the part of students especially in the early part of the research process. Second, the paper aims to describe and discuss the proposed framework for approaching the research project definition and design process in a systematic and logical manner after formulating a research framework.Design/methodology/approach – Experience recording method is used by reflecting on the authors' supervision experience at honours, masters and doctoral level. A reflection on these experiences is compared with good practices in research approaches to identify gap.
Soft sensor development and optimization of the commercial petrochemical plant integrating support vector regression and genetic algorithm

Soft sensors have been widely used in the industrial process control to improve the quality of the product and assure safety in the production. The core of a soft sensor is to construct a soft sensing model. This paper introduces support vector regression (SVR), a new powerful machine learning method based on a statistical learning theory (SLT) into soft sensor modeling and proposes a new soft sensing modeling method based on SVR. This paper presents an artificial intelligence based hybrid soft sensormodeling and optimization strategies, namely support vector regression - genetic algorithm (SVR-GA) for modeling and optimization of mono ethylene glycol (MEG) quality variable in a commercial glycol plant. In the SVR-GA approach, a support vector regression model is constructed for correlating the process data comprising values of operating and performance variables. Next, model inputs describing the process operating variables are optimized using genetic algorithm with a view to maximize the process performance. The SVR-GA is a new strategy for soft sensor modeling and optimization. The major advantage of the strategies is that modeling and optimization can be conducted exclusively from the historic process data wherein the detailed knowledge of process phenomenology (reaction mechanism, kinetics etc.) is not required. Using SVR-GA strategy, a number of sets of optimized operating conditions were found. The optimized solutions, when verified in an actual plant, resulted in a significant improvement in the quality.
Effect of input excitation on the quality of empirical dynamic models for type 1 diabetes

Accurate prediction of future blood glucose trends has the potential to significantly improve glycemic regulation in type 1 diabetes patients. A model-based controller for an artificial β-cell, for example, would determine the most efficacious insulin dose for the current sampling interval given available input–output data and model predictions of the resultant glucose trajectory. The two inputs most influential to the glucose concentration are bolused insulin and meal carbohydrates, which in practice are often taken simultaneously and in a specified ratio. This linear dependence has adverse effects on the quality of linear dynamic models identified from such data. On the other hand, inputs with greater degrees of excitation may force the subject into extreme hypoglycemia or hyperglycemia, and thus may be clinically unacceptable. Inputs with good excitation that do not endanger the subject are shown to result in models that can predict glucose trends reasonably accurately, 1–2 h ahead. © 2009 American Institute of Chemical Engineers AIChE J, 2009
Simulation Study on Effects of Hematocrit on Blood Flow Properties Using Particle Method

The effects of hematocrit (Hct) on blood flow in microcirculation were investigated by computer simulation using a particle method. Deformable red blood cells (RBCs) and blood plasma were modeled by assembly of discrete particles. It was assumed that an RBC consisted of an elastic membrane and inner viscous fluid, and that plasma was viscous fluid. The particles for the RBC membrane were connected with their neighboring membrane particles by stretch/compression and bending springs. The motion of all the particles that was subjected to incompressible viscous flow was solved by the moving particle semi-implicit (MPS) method based on Navier-Stokes (NS) equations. The forces induced by the springs to express the elastic RBC membrane were substituted into the NS equations as the external force, which enabled coupled analysis of elastic RBC motion and plasma fluid flow. Two-dimensional simulations of blood flow between parallel plates were carried out for various Hct values. As a result, it was shown that at higher Hct, RBCs were less deformed into a parachute shape during their downstream motion, indicating that mechanical interaction between RBCs restricted the RBC deformation. Mechanical interaction between RBCs had a significant influence on RBC deformation and the velocity profile of plasma flow when the Hct value was more than 0.20∼0.30. Apparent blood flow resistance increased with Hct, corresponding to previously reported in vitro experimental results compiled to an empirical formula.
Fitting conduction transfer function method to low Fourier numbers: application to ground-coupled floors

This paper proposes a practical solution to the problems arising when the conduction transfer function (CTF) method is applied to solve the 1D transient component of heat transfer in the internal zone of ground-coupled floors. The lower boundary condition for these problems must be imposed at a depth of several metres. The proposed method is based on the division of the ground domain into a number of layers that allows calculation of transfer function coefficients while keeping the first cross coefficient negligible. A mathematical expression is proposed for the proper layer thickness that assures the applicability of the CTF method to thick ground domains. A numerical validation for a slab-on-grade configuration has been carried out showing maximum errors of 0.09°C (0.42%) and 0.73 W/m2 (2.24%) for temperature and heat flow rates on the floor surface, respectively.
Cost-Benefit Analysis of Mood Uplifting Paintings in Hospitals

The Net Present Value of Benefits (NPVB) of installing mood uplifting paintings on hospital stay lengths were projected using a Cost- Benefits analysis. Net benefits were estimated from the "effect size” of mood uplift from Abstract Romanticism paintings and the average cost of hospital stay at $2,000/day. We used a nominal Social Discount Rate of 4% and a period of ten years. The analysis was conducted for a sample of hospitals and states. The results showed that installation of Abstract Romanticism paintings would have net benefits and this enhancement to the patient environment would likely result in substantial healthcare savings. ran a Repeated Measures Multivariate Analysis of Variance on the raw from Amirmostofian The dependent measure was the participants' mood after viewing paintings. Participants viewed painting at three different including the Khavarani’s Abstract Romanticism gallery. Thus, was the within-subjects independent variable. The results showed a significant gallery effect ( F = p The effect size (partial eta squared) was 0.867. Essentially, 87% of the variance could be to an increase in mood after viewing the Abstract Romanticism paintings. to large effect size.
A Novel Prefix Cache with Two-Level Bloom Filters in IP Address Lookup

Prefix caching is one of the notable techniques in enhancing the IP address lookup performance which is crucial in packet forwarding. A cached prefix can match a range of IP addresses, so prefix caching leads to a higher cache hit ratio than IP address caching. However, prefix caching has an issue to be resolved. When a prefix is matched in a cache, the prefix cannot be the result without assuring that there is no longer descendant prefix of the matching prefix which is not cached yet. This is due to the aspect of the IP address lookup seeking to find the longest matching prefix. Some prefix expansion techniques avoid the problem, but the expanded prefixes occupy more entries as well as cover a smaller range of IP addresses. This paper proposes a novel prefix caching scheme in which the original prefix can be cached without expansion. In this scheme, for each prefix, a Bloom filter is constructed to be used for testing if there is any matchable descendant. The false positive ratio of a Bloom filter generally grows as the number of elements contained in the filter increases. We devise an elaborate two-level Bloom filter scheme which adjusts the filter size at each level, to reduce the false positive ratio, according to the number of contained elements. The experimental result shows that the proposed scheme achieves a very low cache miss ratio without increasing the number of prefixes. In addition, most of the filter assertions are negative, which means the proposed prefix cache effectively hits the matching prefix using the filter.
Supply Chain Risks and Roles of the Strategy of Green Supply Chain Management Practices

Supply chain risk is one of the factors disrupting the performance of an organisation. Furthermore, supply chain risk does not only affect economic performance but will also disrupt environmental performance. The focus of this paper is to explore the relationship between supply chain risks, the role of green supply chain management practices, and organisational performance. In particular, the originality of this paper is it is reviewing the role of green supply chain management practices as a strategy for organisations in order to mitigate supply chain risk and improve organisational performance. Efforts have been made in order to study the connection between supply chain risks, green supply chain management practices, and organisational performance since there is still a lack of studies focus on the roles of the strategy of green supply chain management practices.