Search results for: computational methods

Authors: Ebrahim Behrouzian Nejad, Rezvan Alipoor Sabzevari

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Cloud computing systems are large-scale distributed systems, so that they focus more on large scale resource sharing, cooperation of several organizations and their use in new applications. One of the main challenges in this realm is resource allocation. There are many different ways to resource allocation in cloud computing. One of the common methods to resource allocation are economic methods. Among these methods, the auction-based method has greater prominence compared with Fixed-Price method. The double combinatorial auction is one of the proper ways of resource allocation in cloud computing. This method includes two phases: winner determination and resource allocation. In this paper a new method has been presented to determine winner in double combinatorial auction-based resource allocation using Imperialist Competitive Algorithm (ICA). The experimental results show that in our new proposed the number of winner users is higher than genetic algorithm. On other hand, in proposed algorithm, the number of winner providers is higher in genetic algorithm.

Keywords: cloud computing, resource allocation, double auction, winner determination

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Authors: A. Peyvan, D. Li, J. Komperda, F. Mashayek

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Turbulence can be observed in a variety fluid motions in nature and industrial applications. Recent investment in high-speed aircraft and propulsion systems has revitalized fundamental research on turbulent flows. In these systems, capturing chaotic fluid structures with different length and time scales is accomplished through the Direct Numerical Simulation (DNS) approach since it accurately simulates flows down to smallest dissipative scales, i.e., Kolmogorov’s scales. The discontinuous spectral element method (DSEM) is a high-order technique that uses spectral functions for approximating the solution. The DSEM code has been developed by our research group over the course of more than two decades. Recently, the code has been improved to run large cases in the order of billions of solution points. Running big simulations requires a considerable amount of RAM. Therefore, the DSEM code must be highly parallelized and able to start on multiple computational nodes on an HPC cluster with distributed memory. However, some pre-processing procedures, such as determining global element information, creating a global face list, and assigning global partitioning and element connection information of the domain for communication, must be done sequentially with a single processing core. A separate code has been written to perform the pre-processing procedures on a local machine. It stores the minimum amount of information that is required for the DSEM code to start in parallel, extracted from the mesh file, into text files (pre-files). It packs integer type information with a Stream Binary format in pre-files that are portable between machines. The files are generated to ensure fast read performance on different file-systems, such as Lustre and General Parallel File System (GPFS). A new subroutine has been added to the DSEM code to read the startup files using parallel MPI I/O, for Lustre, in a way that each MPI rank acquires its information from the file in parallel. In case of GPFS, in each computational node, a single MPI rank reads data from the file, which is specifically generated for the computational node, and send them to other ranks on the node using point to point non-blocking MPI communication. This way, communication takes place locally on each node and signals do not cross the switches of the cluster. The read subroutine has been tested on Argonne National Laboratory’s Mira (GPFS), National Center for Supercomputing Application’s Blue Waters (Lustre), San Diego Supercomputer Center’s Comet (Lustre), and UIC’s Extreme (Lustre). The tests showed that one file per node is suited for GPFS and parallel MPI I/O is the best choice for Lustre file system. The DSEM code relies on heavily optimized linear algebra operation such as matrix-matrix and matrix-vector products for calculation of the solution in every time-step. For this, the code can either make use of its matrix math library, BLAS, Intel MKL, or ATLAS. This fact and the discontinuous nature of the method makes the DSEM code run efficiently in parallel. The results of weak scaling tests performed on Blue Waters showed a scalable and efficient performance of the code in parallel computing.

Keywords: computational fluid dynamics, direct numerical simulation, spectral element, turbulent flow

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Authors: Emre Ipekci Cetin, Ebru Tarcan Icigen

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Personnel selection process is considered as one of the most important and most difficult issues in human resources management. At the stage of personnel selection, the applicants are handled according to certain criteria, the candidates are dealt with, and efforts are made to select the most appropriate candidate. However, this process can be more complicated in terms of the managers who will carry out the staff selection process. Candidates should be evaluated according to different criteria such as work experience, education, foreign language level etc. It is crucial that a rational selection process is carried out by considering all the criteria in an integrated structure. In this study, the problem of choosing the front office manager of a 5 star accommodation enterprise operating in Antalya is addressed by using multi-criteria decision-making methods. In this context, SWARA (Step-wise weight assessment ratio analysis) and MOORA (Multi-Objective Optimization on the basis of ratio analysis) methods, which have relatively few applications when compared with other methods, have been used together. Firstly SWARA method was used to calculate the weights of the criteria and subcriteria that were determined by the business. After the weights of the criteria were obtained, the MOORA method was used to rank the candidates using the ratio system and the reference point approach. Recruitment processes differ from sector to sector, from operation to operation. There are a number of criteria that must be taken into consideration by businesses in accordance with the structure of each sector. It is of utmost importance that all candidates are evaluated objectively in the framework of these criteria, after these criteria have been carefully selected in the selection of suitable candidates for employment. In the study, staff selection process was handled by using SWARA and MOORA methods together.

Keywords: accommodation establishments, human resource management, multi-objective optimization on the basis of ratio analysis, multi-criteria decision making, step-wise weight assessment ratio analysis

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Authors: Dorra Kallel, Ines Kanoun, Diala Dhouib

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This paper elaborates a Systematic Literature Review SLR) to select the most outstanding studies that address the Menu Planning Problem (MPP) and to classify them according to the to the three following criteria: the used methods, types of patients and the required constraints. At first, a set of 4165 studies was selected. After applying the SLR’s guidelines, this collection was filtered to 13 studies using specific inclusion and exclusion criteria as well as an accurate analysis of each study. Second, the selected papers were invested to answer the proposed research questions. Finally, data synthesis and new perspectives for future works are incorporated in the closing section.

Keywords: Menu Planning Problem (MPP), Systematic Literature Review (SLR), classification, exact and approaches methods

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Authors: Prateek Sharma, Venkata Ramachandrarao Maddali, Kapil Kukreja, B. N. Mohapatra

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Waste management is one of the pressing issues of India. Several initiatives by the Indian Government, including the recent one “Swachhata hi Seva” campaign launched by Prime Minister on 15th August 2018, can be one of the game changers to waste disposal. Under this initiative, the government, cement industry and other stakeholders are working hand in hand to dispose of single-use plastics in cement plants in rotary kilns. This is an exemplary effort and a move that establishes the Indian Cement industry as one of the key players in a circular economy. One of the cement plants in Southern India has been mandated by the state government to co-process shredded plastic and refuse-derived fuel (RDF) available in nearby regions as an alternative fuel in their cement plant. The plant has set a target of 25 % thermal substitution rate (TSR) by RDF in the next five years. Most of the cement plants in India and abroad have achieved high TSR through pre calciner firing. But the cement plant doesn’t have the precalciner and has to achieve this daunting task of 25 % TSR by firing through the main kiln burner. Since RDF is a heterogeneous waste with the change in fuel quality, it is difficult to achieve this task; hence plant has to resort to firing some portion of RDF/plastics at kiln inlet. But kiln inlet has reducing conditions as observed during measurements) under baseline condition. The combustion behavior of RDF of different sizes at different firing locations in riser was studied with the help of a computational fluid dynamics tool. It has been concluded that RDF above 50 mm size results in incomplete combustion leading to CO formation. Moreover, best firing location appears to be in the bottom portion of the kiln riser.

Keywords: kiln inlet, plastics, refuse derived fuel, thermal substitution rate

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: S. Zenhari, M. R. Hematiyan, A. Khosravifard, M. R. Feizi

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The boundary element method (BEM) and the method of fundamental solutions (MFS) are well-known fundamental solution-based methods for solving a variety of problems. Both methods are boundary-type techniques and can provide accurate results. In comparison to the finite element method (FEM), which is a domain-type method, the BEM and the MFS need less manual effort to solve a problem. The aim of this study is to compare the accuracy and reliability of the BEM and the MFS. This comparison is made for 2D potential and elasticity problems with different boundary and loading conditions. In the comparisons, both convex and concave domains are considered. Both linear and quadratic elements are employed for boundary element analysis of the examples. The discretization of the problem domain in the BEM, i.e., converting the boundary of the problem into boundary elements, is relatively simple; however, in the MFS, obtaining appropriate locations of collocation and source points needs more attention to obtain reliable solutions. The results obtained from the presented examples show that both methods lead to accurate solutions for convex domains, whereas the BEM is more suitable than the MFS for concave domains.

Keywords: boundary element method, method of fundamental solutions, elasticity, potential problem, convex domain, concave domain

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Authors: Carri Welsby, Jessie Gunson, Pen Roe

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Currently, there is limited research examining health care professionals (HCPs) views on long-acting reversible contraception (LARC) advice and prescription, particularly outside of the general practice (GP) setting. The aim of this study is to systematically review existing evidence around the barriers and enablers of oral contraception (OC) in comparison to LARC, as perceived by HCPs in non-GP settings. Five electronic databases were searched in April 2018 using terms related to LARC, OC, HCPs, and views, but not terms related to GPs. Studies were excluded if they concerned emergency oral contraception, male contraceptives, contraceptive use in conjunction with a health condition(s), developing countries, GPs and GP settings, were non-English or was not published before 2013. A total of six studies were included for systematic reviewing. Five key areas emerged, under which themes were categorised, including (1) understanding HCP attitudes and counselling practices towards contraceptive methods; (2) assessment of HCP attitudes and beliefs about contraceptive methods; (3) misconceptions and concerns towards contraceptive methods; and (4) influences on views, attitudes, and beliefs of contraceptive methods. Limited education and training of HCPs exists around LARC provision, particularly compared to OC. The most common misconception inhibiting HCPs contraceptive information delivery to women was the belief that LARC was inappropriate for nulliparous women. In turn, by not providing the correct information on a variety of contraceptive methods, HCP counselling practices were disempowering for women and restricted them from accessing reproductive justice. Educating HCPs to be able to provide accurate and factual information to women on all contraception is vital to encourage a woman-centered approach during contraceptive counselling and promote informed choices by women.

Keywords: advice, contraceptives, health care professionals, long acting reversible contraception, oral contraception, reproductive justice

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Authors: Samuel Atongaba Danji, Veseke Moleke

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The increase of globalization is a very important part of today’s changing environment and due to this, manufacturing industries have to always come up with methods of continuous improvement of their manufacturing methods in order to be competitive, without which may lead them to be left out of the market due to constant changing customers requirement. Due to this, the need is an advance supply chain system which prevents a number of issues that can prevent a company from being competitive. In this work, we developed a feedback control supply chain system which streamline the entire process in order to improve competitiveness and the result shows that when applied in a different geographical area, the output varies.

Keywords: globalization, supply chain, improvement, manufacturing

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Authors: Habiba Ben Abdessalem

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The emergence of giant set of textual data was the push that has encouraged researchers to invest in this field. The purpose of textual data analysis methods is to facilitate access to such type of data by providing various graphic visualizations. Applying these methods requires a corpus pretreatment step, whose standards are set according to the objective of the problem studied. This step determines the forms list contained in contingency table by keeping only those information carriers. This step may, however, lead to noisy contingency tables, so the use of wavelet denoising function. The validity of the proposed approach is tested on a text database that offers economic and political events in Tunisia for a well definite period.

Keywords: textual data, wavelet, denoising, contingency table

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Authors: Samira Ghizellaoui, Manel Boumagoura

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The municipality of Constantine in eastern Algeria draws water from the Hamma groundwater source. The high fouling capacity is due to the high content of bicarbonate (442 mg/L) and calcium (136 mg/L). This work focuses on the use of three new green inhibitors for reducing calcium carbonate scale formation: gallic acid, quercetin and alginate, and on the comparison between them. These inhibitors have proven to be green antiscalants because they have no impact on the environment. Electrochemical methods (chronoamperometry and impedancemetry) were used to evaluate their performance. According to the study, these inhibitors are excellent green chemical inhibitors of scaling, and the best inhibitor is quercetin because it gave a good result with a lower concentration (2mg/L) compared to others inhibitors.

Keywords: scaling, green inhibitor, chronoamperometry, impedancemetry

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Authors: Simona Maria Ignat

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Bullying online has been an increasing studied topic during the last years. Different approaches, psychological, linguistic, or computational, have been applied. To our best knowledge, a definition and a set of characteristics of phenomenon agreed internationally as a common framework are still waiting for answers. Thus, the objectives of this paper are the identification of bullying utterances on Twitter and their algorithms. This research paper is focused on the identification of words or groups of words, categorized as “utterances”, with bullying effect, from Twitter platform, extracted on a set of legislative criteria. This set is the result of analysis followed by synthesis of law documents on bullying(online) from United States of America, European Union, and Ireland. The outcome is a linguistic corpus with approximatively 10,000 entries. The methods applied to the first objective have been the following. The discourse analysis has been applied in identification of keywords with bullying effect in texts from Google search engine, Images link. Transcription and anonymization have been applied on texts grouped in CL1 (Corpus linguistics 1). The keywords search method and the legislative criteria have been used for identifying bullying utterances from Twitter. The texts with at least 30 representations on Twitter have been grouped. They form the second corpus linguistics, Bullying utterances from Twitter (CL2). The entries have been identified by using the legislative criteria on the the BoW method principle. The BoW is a method of extracting words or group of words with same meaning in any context. The methods applied for reaching the second objective is the conversion of parts of speech to alphabetical and numerical symbols and writing the bullying utterances as algorithms. The converted form of parts of speech has been chosen on the criterion of relevance within bullying message. The inductive reasoning approach has been applied in sampling and identifying the algorithms. The results are groups with interchangeable elements. The outcomes convey two aspects of bullying: the form and the content or meaning. The form conveys the intentional intimidation against somebody, expressed at the level of texts by grammatical and lexical marks. This outcome has applicability in the forensic linguistics for establishing the intentionality of an action. Another outcome of form is a complex of graphemic variations essential in detecting harmful texts online. This research enriches the lexicon already known on the topic. The second aspect, the content, revealed the topics like threat, harassment, assault, or suicide. They are subcategories of a broader harmful content which is a constant concern for task forces and legislators at national and international levels. These topic – outcomes of the dataset are a valuable source of detection. The analysis of content revealed algorithms and lexicons which could be applied to other harmful contents. A third outcome of content are the conveyances of Stylistics, which is a rich source of discourse analysis of social media platforms. In conclusion, this corpus linguistics is structured on legislative criteria and could be used in various fields.

Keywords: corpus linguistics, cyberbullying, legislation, natural language processing, twitter

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Authors: Jennifer M. Penton

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Record high lake levels in 2017 and 2019 (2017 max lake level = 75.81 m; 2018 max lake level = 75.26 m; 2019 max lake level = 75.92 m) combined with a number of severe storms in the Great Lakes region, have resulted in significant wave generation across Lake Ontario. The resulting large wave heights have led to erosion of the natural shoreline, overtopping of existing revetments, backshore erosion, and partial and complete failure of several coastal structures, which in turn have led to further erosion of the shoreline and damaged existing infrastructure. Such impacts can be seen all along the coast of Lake Ontario. Three specific locations have been chosen as case studies for this paper, each addressing erosion and/or flood mitigation methods, such as revetments and sheet piling with increased land levels. Varying site conditions and the resulting shoreline damage are compared herein. The results are reflected in the case-specific design components of the mitigation and adaptation methods and are presented in this paper.

Keywords: erosion mitigation, flood mitigation, great lakes, high water levels

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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: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

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Authors: Thomas Jin-Chee Liu

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In this paper, the thermo-electro-structural coupled-field in a cracked metal plate is studied using the finite element analysis. From the computational results, the compressive stresses reveal near the crack tip. This conclusion agrees with the past reference. Furthermore, the compressive condition can retard and stop the crack growth during the Joule heating process.

Keywords: compressive stress, crack tip, Joule heating, finite element

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Authors: Thierno Diop, Michel Fortin, Jean Deteix

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Since the precise formulation of the elastic part is irrelevant for the description of the algorithm, we shall consider a generic case. In practice, however, we will have to deal with a non linear material (for instance a Mooney-Rivlin model). We are interested in solving a finite element approximation of the problem, leading to large-scale non linear discrete problems and, after linearization, to large linear systems and ultimately to calculations needing iterative methods. This also implies that penalty method, and therefore augmented Lagrangian method, are to be banned because of their negative effect on the condition number of the underlying discrete systems and thus on the convergence of iterative methods. This is in rupture to the mainstream of methods for contact in which augmented Lagrangian is the principal tool. We shall first present the problem and its discretization; this will lead us to describe a general solution algorithm relying on a preconditioner for saddle-point problems which we shall describe in some detail as it is not entirely standard. We will propose an iterative approach for solving three-dimensional frictional contact problems between elastic bodies, including contact with a rigid body, contact between two or more bodies and also self-contact.

Keywords: frictional contact, three-dimensional, large-scale, iterative method

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Authors: Mohamed Zaidour

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In this summary, we are going to look in brief at the bridges and their building and construction on most roads and we have followed a simple method to explain each field clearly because the geographical and climatic diversity of an area leads to different methods and types of roads and installation engineering in other areas In mountain areas we need to build retaining walls in areas of rain. It needs to construct ferries to discharge water from roads in areas of temporary or permanent rivers. There is a need to build bridges and construct road installations in the process of collecting the necessary information, such as soil type. This information needs it, engineer, when designing the constructor and in this section, we will identify the types and methods of calculation bridge columns rules phrases the walls are chock.

Keywords: bridges, buildings, concrete, constructions, roads

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Authors: Megha Jain, K. K. Pathak

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In sub-tropical humid climates, it is estimated most of the urban peak load of energy consumption is used to satisfy air-conditioning or air-coolers cooling demand in summer time. As the urbanization rate in developing nation – like the case in India is rising rapidly, the pressure placed on energy resources to satisfy inhabitants’ indoor comfort requirements is consequently increasing too. This paper introduces passive cooling through roof as a means of reducing energy cooling loads for satisfying human comfort requirements in a sub-tropical climate. Experiments were performed by applying different insulators which are locally available solar reflective materials to insulate the roofs of five rooms of 4 case buildings; three rooms having RCC (Reinforced Cement Concrete) roof and two having Asbestos sheet roof of existing buildings. The results are verified by computer simulation using Computational Fluid Dynamics tools with FLUENT software. The result of using solar reflective paint with high albedo coating shows a fall of 4.8⁰C in peak hours and saves 303 kWh considering energy load with air conditioner during the summer season in comparison to non insulated flat roof energy load of residential buildings in Bhopal. An optimum solution of insulator for both types of roofs is presented. It is recommended that the selected cool roof solution be combined with insulation on other elements of envelope, to increase the indoor thermal comfort. The application is intended for low cost residential buildings in composite and warm climate like Bhopal.

Keywords: cool roof, computational fluid dynamics, energy loads, insulators, passive cooling, subtropical climate, thermal performance

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Authors: Kamyar Maleki Bagherabadi, Torstein Aarseth Bø, Truls Flatberg, Olve Mo

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Hydrogen fuel cells and batteries are one of the promising solutions aligned with carbon emission reduction goals for the marine sector. However, the higher installation and operation costs of hydrogen-based systems compared to conventional diesel gensets raise questions about the appropriate hydrogen tank size, energy, and fuel consumption estimations. Ship designers need methodologies and tools to calculate energy and fuel consumption for different component sizes to facilitate decision-making regarding feasibility and performance for retrofits and design cases. The aim of this work is to compare three alternative modeling approaches for the estimation of energy and fuel consumption with various hydrogen tank sizes, battery capacities, and load-sharing strategies. A fishery vessel is selected as an example, using logged load demand data over a year of operations. The modeled power system consists of a PEM fuel cell, a diesel genset, and a battery. The methodologies used are: first, an energy-based model; second, considering load variations during the time domain with a rule-based Power Management System (PMS); and third, a load variations model and dynamic PMS strategy based on optimization with perfect foresight. The errors and potentials of the methods are discussed, and design sensitivity studies for this case are conducted. The results show that the energy-based method can estimate fuel and energy consumption with acceptable accuracy. However, models that consider time variation of the load provide more realistic estimations of energy and fuel consumption regarding hydrogen tank and battery size, still within low computational time.

Keywords: fuel cell, battery, hydrogen, hybrid power system, power management system

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Authors: Ilya Simanovskii

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Nonlinear convective flows developed under the joint action of buoyant and thermo-capillary effects in a two-layer system with periodic boundary conditions on the lateral walls have been investigated. The influence of an interfacial heat release on oscillatory regimes has been studied. The computational regions with different lengths have been considered. It is shown that the development of oscillatory instability can lead to the appearance of different no steady flows.

Keywords: interface, instabilities, two-layer systems, bioinformatics, biomedicine

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Authors: Rafael Alvarenga, Hubert Herbaux, Laurent Linguet

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The uncertainty concerning the power production of intermittent renewable energy is one of the main barriers to the integration of such assets into the power grid. Efforts have thus been made to develop methods to quantify this uncertainty, allowing producers to ensure more reliable and profitable engagements related to their future power delivery. Even though a diversity of probabilistic approaches was proposed in the literature giving promising results, the added value of adopting such methods for scheduling intermittent power plants is still unclear. In this study, the profits obtained by a decision-making model used to optimally schedule an existing PV power plant connected to batteries are compared when the model is fed with deterministic and probabilistic forecasts generated with two of the most recent methods proposed in the literature. Moreover, deterministic forecasts with different accuracy levels were used in the experiments, testing the utility and the capability of probabilistic methods of modeling the progressively increasing uncertainty. Even though probabilistic approaches are unquestionably developed in the recent literature, the results obtained through a study case show that deterministic forecasts still provide the best performance if accurate, ensuring a gain of 14% on final profits compared to the average performance of probabilistic models conditioned to the same forecasts. When the accuracy of deterministic forecasts progressively decreases, probabilistic approaches start to become competitive options until they completely outperform deterministic forecasts when these are very inaccurate, generating 73% more profits in the case considered compared to the deterministic approach.

Keywords: PV power forecasting, uncertainty quantification, optimal scheduling, power systems

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Authors: Benedictus Asriparusa

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In the area of the oil industry, there is accompanied by associated natural gas. The thing shows that a large amount of energy is being wasted mostly in the developing countries by contributing to the global warming process. This research represents an overview of methods in Minas area employed by these researchers in PT. Chevron Pacific Indonesia to determine ways of measuring and reducing gas flaring and its emission drastically. It provides an approximation includes analytical studies, numerical studies, modeling, computer simulations, etc. Flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process will release emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the air and environment around the industrial area. Therefore, we need a simulation to create the pattern of the dissemination of pollutant. This research paper has being made to see trends in gas flaring model and current developments to predict dominant variable which gives impact to dissemination of pollutant. Fluent models used to simulate the distribution of pollutant gas coming out of the stack. While WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. This study condition focused on transition season in 2012 at Minas area. The goal of the simulation is looking for the exact time which is most influence towards dissemination of pollutants. The most influence factor divided into two main subjects. It is the quickest wind and the slowest wind. According to the simulation results, it can be seen that quickest wind moves to horizontal way and slowest wind moves to vertical way.

Keywords: flaring system, fluent model, dissemination of pollutant, transition season

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Authors: Sammani Danwawu Abdullahi

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Vertex Enumeration Algorithms explore the methods and procedures of generating the vertices of general polyhedra formed by system of equations or inequalities. These problems of enumerating the extreme points (vertices) of general polyhedra are shown to be NP-Hard. This lead to exploring how to count the vertices of general polyhedra without listing them. This is also shown to be #P-Complete. Some fully polynomial randomized approximation schemes (fpras) of counting the vertices of some special classes of polyhedra associated with Down-Sets, Independent Sets, 2-Knapsack problems and 2 x n transportation problems are presented together with some discovered open problems.

Keywords: counting with uncertainties, mathematical programming, optimization, vertex enumeration

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Authors: Manel Boulakoud, Abdelkader Chouaih, Fodil Hamzaoui

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In the present work we are interested in the determination of the Molecular electrostatic potential (MEP) in Z-3N(2-Ethoxyphenyl), 2-N’(2-Ethoxyphenyl) imino thiazolidin-4-one molecule by ab initio and Density Functional Theory (DFT) in the ground state. The MEP is related to the electronic density and is a very useful descriptor in understanding sites for electrophilic attack and nucleophilic reactions as well as hydrogen bonding interactions. First, geometry optimization was carried out using Hartree–Fock (HF) and DFT methods with 6-311G(d,p) basis set. In order to get more information on the molecule, its stability has been analyzed by natural bond orbital (NBO) analysis. Mulliken population analyses have been calculated. Finally, the molecular electrostatic potential (MEP) and HOMO-LUMO energy levels have been performed. The calculated HOMO and LUMO energies show also the charge transfer within the molecule. The energy gap obtained is about 4 eV which explain the stability of the studied compound. The obtained molecular electrostatic potential from the two methods confirms the nature of the electron charge transfer at the molecular shell and locate the electropositive part and the electronegative part in molecular scale of the title compound.

Keywords: DFT, ab initio, HOMO-LUMO, organic compounds

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Authors: E. V. Krishnan

Abstract:

In this paper, we employ mapping methods to construct exact travelling wave solutions for a modified Korteweg-de Vries equation. We have derived periodic wave solutions in terms of Jacobi elliptic functions, kink solutions and singular wave solutions in terms of hyperbolic functions.

Keywords: travelling wave solutions, Jacobi elliptic functions, solitary wave solutions, Korteweg-de Vries equation

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Authors: Ö. Şenyiğit, A. Çolak

Abstract:

It is of great importance for an architectural student to know the parameters through which he/she can conduct his/her design and makes his/her design effective in architectural education. Therefore; an empirical application study was carried out through the designing activity using the emulation model to support the design and design approaches of architectural students. During the investigation period, studies were done on the basic design elements and principles of the fall semester, and the emulation model, one of the designing methods that constitute the subject of the study, was fictionalized as three phased “recognition-interpretation-application”. As a result of the study, it was observed that when students were given a key method during the design process, their awareness increased and their aspects improved as well.

Keywords: basic design, design education, design methods, emulation

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Authors: Sumera, Sanila Amber, Fatima Javed Mirza, Amjad Ali, Saadia Zahid

Abstract:

Glioblastoma multiforme (GBM) is a widely spread and fatal primary brain tumor with an increased risk of relapse in spite of aggressive treatment. The current procedures for GBM diagnosis include invasive procedures i.e. resection or biopsy, to acquire tumor mass. Implementation of negligibly invasive tests as a potential diagnostic technique and biofluid-based monitoring of GBM stresses on discovering biomarkers in CSF and blood. Therefore, we performed a comprehensive in silico analysis to identify potential circulating biomarkers for GBM. Initially, six gene and protein databases were utilized to mine brain-specific proteins. The resulting proteins were filtered using a channel of five tools to predict the secretory proteins. Subsequently, the expression profile of the secreted proteins was verified in the brain and blood using two databases. Additional verification of the resulting proteins was done using Plasma Proteome Database (PPD) to confirm their presence in blood. The final set of proteins was searched in literature for their relationship with GBM, keeping a special emphasis on secretome proteome. 2145 proteins were firstly mined as brain-specific, out of which 69 proteins were identified as secretory in nature. Verification of expression profile in brain and blood eliminated 58 proteins from the 69 proteins, providing a final list of 11 proteins. Further verification of these 11 proteins further eliminated 2 proteins, giving a final set of nine secretory proteins i.e. OPCML, NPTX1, LGI1, CNTN2, LY6H, SLIT1, CREG2, GDF1 and SERPINI1. Out of these 9 proteins, 7 were found to be linked to GBM, whereas 2 proteins are not investigated in GBM so far. We propose that these secretory proteins can serve as potential circulating biomarker signatures of GBM and will facilitate the development of minimally invasive diagnostic methods and novel therapeutic interventions for GBM.

Keywords: glioblastoma multiforme, secretory proteins, brain secretome, biomarkers

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Authors: Rowanda Daoud Ahmed, Mansoor Abdulhak, Muhammad Azeem Afzal, Sezer Filiz, Usama Ahmad Mughal

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This paper discusses important aspects of AI in the healthcare domain. The increase of data in healthcare both in size and complexity, opens more room for artificial intelligence applications. Our focus is to review the main AI methods within the scope of the health care domain. The results of the review show that recommendations for diagnosis and recommendations for treatment, patent engagement, and administrative tasks are the key applications of AI in healthcare. Understanding the potential of AI methods in the domain of healthcare would benefit healthcare practitioners and will improve patient outcomes.

Keywords: AI in healthcare, technologies of AI, neural network, future of AI in healthcare

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Authors: João F. A. Martos, Felipe J. Costa, Sergio N. P. Laiton, Bruno C. Lima, Israel S. Rêgo, Paulo P. G. Toro

Abstract:

Nowadays, the scramjet is a topic that has attracted the attention of several scientific communities (USA, Australia, Germany, France, Japan, India, China, Russia), that are investing in this in this type of propulsion system due its interest to facilitate access to space and reach hypersonic speed, who have invested in this type of propulsion due to the interest in facilitating access to space. The Brazilian hypersonic scramjet aerospace vehicle 14-X B is a technological demonstrator of a hypersonic airbreathing propulsion system based on the supersonic combustion (scramjet) intended to be tested in flight into the Earth's atmosphere at 30 km altitude and Mach number 7. The 14-X B has been designed at the Prof. Henry T. Nagamatsu Laboratory of Aerothermodynamics and Hypersonics of the Institute for Advanced Studies (IEAv) in Brazil. The IEAv Hypersonic Shock Tunnel, named T3, is a ground-test facility able to reproduce the flight conditions as the Mach number as well as pressure and temperature in the test section close to those encountered during the test flight of the vehicle 14-X B into design conditions. A 1-m long stainless steel 14-X B model was experimentally investigated at T3 Hypersonic Shock Tunnel, for freestream Mach number 7. Static pressure measurements along the lower surface of the 14-X B model, along with high-speed schlieren photographs taken from the 5.5° leading edge and the 14.5° deflection compression ramp, provided experimental data that were compared to the analytical-theoretical solutions and the computational fluid dynamics (CFD) simulations. The results show a good qualitative agreement, and in consequence demonstrating the importance of these methods in the project of the 14-X B hypersonic aerospace vehicle.

Keywords: 14-X, CFD, hypersonic, hypersonic shock tunnel, scramjet

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