Search results for: conventional computing

Authors: Shahin A. Abdel-Naby, James P. Colgan, Michael S. Pindzola

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A time-dependent close-coupling method is developed to calculate a total, double and triple autoionization rates for hollow atomic ions of four-electron systems. This work was motivated by recent observations of the four-electron Auger process in near K-edge photoionization of C+ ions. The time-dependent close-coupled equations are solved using lattice techniques to obtain a discrete representation of radial wave functions and all operators on a four-dimensional grid with uniform spacing. Initial excited states are obtained by relaxation of the Schrodinger equation in imaginary time using a Schmidt orthogonalization method involving interior subshells. The radial wave function grids are partitioned over the cores on a massively parallel computer, which is essential due to the large memory requirements needed to store the coupled-wave functions and the long run times needed to reach the convergence of the ionization process. Total, double, and triple autoionization rates are obtained by the propagation of the time-dependent close-coupled equations in real-time using integration over bound and continuum single-particle states. These states are generated by matrix diagonalization of one-electron Hamiltonians. The total autoionization rates for each L excited state is found to be slightly above the single autoionization rate for the excited configuration using configuration-average distorted-wave theory. As expected, we find the double and triple autoionization rates to be much smaller than the total autoionization rates. Future work can be extended to study electron-impact triple ionization of atoms or ions. The work was supported in part by grants from the American University of Sharjah and the US Department of Energy. Computational work was carried out at the National Energy Research Scientific Computing Center (NERSC) in Berkeley, California, USA.

Keywords: hollow atoms, autoionization, auger rates, time-dependent close-coupling method

Procedia PDF Downloads 153

Authors: Muhammad Umair, Yuri Nikolaev, Denis Artemov, Ighor Uzhinsky

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A flexible manufacturing system is an integral part of a smart factory of industry 4.0 in which every machine is interconnected and works autonomously. Robots are in the process of replacing humans in every industrial sector. As the cyber-physical-system (CPS) and artificial intelligence (AI) are advancing, the manufacturing industry is getting more dependent on computers than human brains. This modernization has boosted the production with high quality and accuracy and shifted from classic production to smart manufacturing systems. However, material handling for such automated productions is a challenge and needs to be addressed with the best possible solution. Conventional clamping systems are designed for manual work and not suitable for highly automated production systems. Researchers and engineers are trying to find the most economical solution for loading/unloading and transportation workpieces from a warehouse to a machine shop for machining operations and back to the warehouse without human involvement. This work aims to propose an advanced multi-shape tooling solution for highly automated manufacturing systems. The currently obtained result shows that it could function well with automated guided vehicles (AGVs) and modern conveyor belts. The proposed solution is following requirements to be automation-friendly, universal for different part geometry and production operations. We used a bottom-up approach in this work, starting with studying different case scenarios and their limitations and finishing with the general solution.

Keywords: artificial intelligence, cyber physics system, Industry 4.0, material handling, smart factory, flexible manufacturing system

Procedia PDF Downloads 132

Authors: Ayman Othman, Tallat Ali

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The successive increase of generated waste materials like glass has led to many environmental problems. Using crushed waste glass in hot mix asphalt paving has been though as an alternative to landfill disposal and recycling. This paper discusses the possibility of utilizing crushed waste glass, as a part of fine aggregate in hot mix asphalt in Egypt. This is done through evaluation of the mechanical properties of asphalt concrete mixtures mixed with waste glass and determining the appropriate glass content that can be adapted in asphalt pavement. Four asphalt concrete mixtures with various glass contents, namely; 0%, 4%, 8% and 12% by weight of total mixture were studied. Evaluation of the mechanical properties includes performing Marshall stability, indirect tensile strength, fracture energy and unconfined compressive strength tests. Laboratory testing had revealed the enhancement in both compressive strength and Marshall stability test parameters when the crushed glass was added to asphalt concrete mixtures. This enhancement was accompanied with a very slight reduction in both indirect tensile strength and fracture energy when glass content up to 8% was used. Adding more than 8% of glass causes a sharp reduction in both indirect tensile strength and fracture energy. Testing results had also shown a reduction in the optimum asphalt content when the waste glass was used. Measurements of the heat loss rate of asphalt concrete mixtures mixed with glass revealed their ability to hold heat longer than conventional mixtures. This can have useful application in asphalt paving during cold whether or when a long period of post-mix transportation is needed.

Keywords: waste glass, hot mix asphalt, mechanical performance, indirect tensile strength, fracture energy, compressive strength

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Authors: Riya Thomas, Denis Music, Tautgirdas Ruzgas

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The detection of tyrosinase holds considerable interest in the domains of food nutrition and human health due to its significant role in causing a detrimental effect on the colour, flavour, and nutritional value of food as well as in the synthesis of melanin causing skin melanoma. Compared to other conventional analytical techniques, electrochemical (EC) sensors are highly promising owing to their quick response, great sensitivity, ease of use, and low cost. Particularly, titania nanoparticle-based electrochemical sensors have drawn special attention in identifying several biomolecules including enzymes, antibodies, and receptors, owing to their enhanced electrocatalytic activity and electron-accepting properties. In this study, Ti-O film-modified electrode is fabricated using reactive magnetron sputtering, and its affinity towards tyrosinase is examined via electrochemical methods. To comprehend the physiochemical and surface properties-governed electrocatalytic activity of modified electrodes, Ti-O films are grown under various compositional ranges and deposition temperature, and their corresponding electrochemical activity towards tyrosinase is studied. Further, to understand the underlying atomistic mechanisms and electronic-scale electrochemical characteristics, density functional theory (DFT) is employed. The main goal of the current work is to determine the correlation between macroscopic measurements and the underlying atomic properties to improve the tyrosinase activity on Ti-O surfaces. Moreover, this work offers an intriguing new perspective on the use of Ti-O-modified electrodes to detect tyrosinase in the areas of clinical diagnosis, skincare, and food science.

Keywords: density functional theory, electrochemical sensor, Ti-O film, tyrosinase

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

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Authors: Dairi Sabri, Mrad Dounia, Djebbar Yassine, Abida Habib

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Food security, which may be ensured by important agricultural production, needs huge amounts of water for irrigation. Recognizing this, the Algerian government made enormous efforts to mobilize water resources. Every drop of water collected, regardless of its origin, is needed to strengthen agricultural production. The present irrigated area in Algeria is about 1 million hectares while the potential agricultural area all over the country exceeds 9 million ha. This clearly shows the need for non-conventional water resources in Algeria, especially treated wastewater reuse. The use of treated wastewater in agricultural irrigation is still at the experimental stage in Algeria. While 20 million hectares worldwide are irrigated with treated wastewater, only 2300 hectares in Algeria are irrigated on an experimental basis in the regions of Setif, Constantine, Mila Telemcen, Tougourt and Boumerdès. The volume of wastewater discharged nationwide is estimated to be around 750 million cubic meters and is expected to exceed 1.5 billion m3 in 2020. An ambitious program of providing treatment facilities has been initiated in this direction to increase the treatment capacity to 2.5 million m3 per day in 2030. In order to optimize the use of this resource, specific research actions interested in defining treated wastewater reuse opportunities and standards are undertaken. The objective of this study is basically to examine the different components of treated wastewater reuse, including standards, treatment processes, agricultural opportunities and potentials as well as technical and economic aspects governing the feasibility of this technology in Algeria based on Geographic Information System (GIS).

Keywords: wastewater reuse, integrated management, irrigation, GIS

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Authors: Madalina Postaru, Alexandra Tucaliuc, Dan Cascaval, Anca Irina Galaction

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Ergosterol (ergosta-5,7,22-trien-3β-ol) is the precursor of vitamin D2 (ergocalciferol), known as provitamin D2 as it is converted under UV radiation to this vitamin. The natural sources of ergosterol are mainly the yeasts (Saccharomyces sp., Candida sp.), but it can be also found in fungus (Claviceps sp.) or plants (orchids). As ergosterol is mainly accumulated in yeast cell membranes, especially in free form in the plasma-membrane, and the chemical synthesis of ergosterol does not represent an efficient method for its production, this study aimed to analyze the influence of aeration efficiency on ergosterol production by S. cerevisiae in batch and fed-batch fermentations, by considering different levels of mixing intensity, aeration rate, and n-dodecane concentration. Our previous studies on ergosterol production by S. cerevisiae in batch and fed-batch fermentation systems indicated that the addition of n-dodecane led to the increase of almost 50% of this sterol concentration, the highest productivity being reached for the fed-batch process. The experiments were carried out in a laboratory stirred bioreactor, provided with computer-controlled and recorded parameters. In batch fermentation system, the study indicated that the oxygen mass transfer coefficient, kLa, is amplified for about 3 times by increasing the volumetric concentration of n-dodecane from 0 to 15%. Moreover, the increase of dissolved oxygen concentration by adding n-dodecane leads to the diminution for 3.5 times of the produced alcohol amount. In fed-batch fermentation process, the positive influence of hydrocarbon on oxygen transfer rate is amplified mainly at its higher concentration level, as the result of the increased yeasts cells amount. Thus, by varying n-dodecane concentration from 0 to 15% vol., the kLa value increase becomes more important than for the batch fermentation, being of 4 times

Keywords: ergosterol, yeast fermentation, n-dodecane, oxygen-vector

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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.

Procedia PDF Downloads 47

Authors: J. M. Counsell, Y. Khalid, M. J. Stewart

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Achieving nearly zero carbon heating continues to be identified by UK government analysis as an important feature of any lowest cost pathway to reducing greenhouse gas emissions. Heat currently accounts for 48% of UK energy consumption and approximately one third of UK’s greenhouse gas emissions. Heat Networks are being promoted by UK investment policies as one means of supporting hybrid heat pump based solutions. To this effect the RISE (Renewable Integrated and Sustainable Electric) heating system project is investigating how an all-electric heating sourceshybrid configuration could play a key role in long-term decarbonisation of heat.  For the purposes of this study, hybrid systems are defined as systems combining the technologies of an electric driven air source heat pump, electric powered thermal storage, a thermal vessel and micro-heat network as an integrated system.  This hybrid strategy allows for the system to store up energy during periods of low electricity demand from the national grid, turning it into a dynamic supply of low cost heat which is utilized only when required. Currently a prototype of such a system is being tested in a modern house integrated with advanced controls and sensors. This paper presents the virtual performance analysis of the system and its design for a micro heat network with multiple dwelling units. The results show that the RISE system is controllable and can reduce carbon emissions whilst being competitive in running costs with a conventional gas boiler heating system.

Keywords: gas boilers, heat pumps, hybrid heating and thermal storage, renewable integrated and sustainable electric

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Authors: Rami Faraj, Cezary Graczykowski, Błażej Popławski, Grzegorz Mikułowski, Rafał Wiszowaty

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Progress in the field of sensors, electronics and computing results in more and more often applications of adaptive techniques for dynamic response mitigation. When it comes to systems excited with mechanical impacts, the control system has to take into account the significant limitations of actuators responsible for system adaptation. The paper provides a comprehensive discussion of the problem of appropriate design and implementation of adaptation techniques and mechanisms. Two case studies are presented in order to compare completely different adaptation schemes. The first example concerns a double-chamber pneumatic shock absorber with a fast piezo-electric valve and parameters corresponding to the suspension of a small unmanned aerial vehicle, whereas the second considered system is a safety air cushion applied for evacuation of people from heights during a fire. For both systems, it is possible to ensure adaptive performance, but a realization of the system’s adaptation is completely different. The reason for this is technical limitations corresponding to specific types of shock-absorbing devices and their parameters. Impact mitigation using a pneumatic shock absorber corresponds to much higher pressures and small mass flow rates, which can be achieved with minimal change of valve opening. In turn, mass flow rates in safety air cushions relate to gas release areas counted in thousands of sq. cm. Because of these facts, both shock-absorbing systems are controlled based on completely different approaches. Pneumatic shock-absorber takes advantage of real-time control with valve opening recalculated at least every millisecond. In contrast, safety air cushion is controlled using the semi-passive technique, where adaptation is provided using prediction of the entire impact mitigation process. Similarities of both approaches, including applied models, algorithms and equipment, are discussed. The entire study is supported by numerical simulations and experimental tests, which prove the effectiveness of both adaptive impact mitigation techniques.

Keywords: adaptive control, adaptive system, impact mitigation, pneumatic system, shock-absorber

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Authors: Zil e Huma

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This study explores the role of Pakistani conventional print media in edging peace talks between the Taliban and the Government of Pakistan from 1st January 2015 till 1st July 2015. The study examines the role of Pakistan's print media during the efforts for peace talks in the context of a Low-Intensity Conflict (LIC). This quantitative research study utilizes content analysis to examine how Pakistan's print media framed the peace negotiations between the government and the TTP. Editorials and columns from two English newspapers, Dawn and The News, were analyzed. The findings reveal that during the peace talks, the print media in Pakistan did not actively contribute to fostering constructive dialogue to support the peace process. Instead, the media failed to provide the necessary communicative space for the political negotiations to move forward, with narratives of fear and despair being dominant. This study offers insight into the psychology of newspapers, showing how they frame news, columns, and articles on complex issues such as the Taliban peace talks. Additionally, it highlights the importance of understanding the role of newspapers in shaping identities and relationships. By examining how Pakistan's print media framed peace initiatives, this research contributes to the existing literature on conflict resolution between the Taliban and the government of Pakistan. Furthermore, it explores the connection between media framing of the peace talks and the actual trajectory of the negotiations, questioning whether the Pakistani print media acted as a facilitator or portrayed the peace process as an inevitable risk of further violence.

Keywords: changing identities, low-intensity, peace journalism, terrorism, the conflict, taliban peace talks, pakistani press

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Authors: K. Bala Subramanian, A. Siva, S. Swaminathan, Arul. M. G. Ajin

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Concrete is an essential building material which is widely used in construction industry all over the world due to its compressible strength. Curing of concrete plays a vital role in durability and other performance necessities. Improper curing can affect the concrete performance and durability easily. When areas like scarcity of water, structures is not accessible by humans external curing cannot be performed, so we opt for internal curing. Internal curing (or) self-curing plays a major role in developing the concrete pore structure and microstructure. The concept of internal curing is to enhance the hydration process to maintain the temperature uniformly. The evaporation of water in the concrete is reduced by self-curing agent (Super Absorbing Polymer – SAP) thereby increasing the water retention capacity of the concrete. The research work was carried out to reduce water, which is prime material used for concrete in the construction industry. Concrete curing plays a major role in developing hydration process. Concept of self-curing will reduce the evaporation of water from concrete. Self-curing will increase water retention capacity as compared to the conventional concrete. Proper self-curing (or) internal curing increases the strength, durability and performance of concrete. Super absorbing Polymer (SAP) used as internal curing agent. In this study 0.2% to 0.4% of SAP was varied in different grade of high strength concrete. In the experiment replacement of cement by silica fumes with 5%, 10% and 15% are studied. It is found that replacement of silica fumes by 10 % gives more strength and durability when compared to others

Keywords: compressive strength, high strength concrete rapid chloride permeability, super absorbing polymer

Procedia PDF Downloads 378

Authors: Samkeliso S. Ndzimandze, Welldone Moyo, Oranso T. Mahlangu, Adolph A. Muleja, Alex T. Kuvarega, Thabo T. I. Nkambule

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The high cost of precursor materials has hindered the commercialization of ceramic membrane technology in water treatment. In this work, a ceramic membrane disc (approximately 50 mm in diameter and 4 mm thick) was prepared from low-cost starting materials, kaolin, and fly ash by pressing at 200 bar and calcining at 900 °C. The fabricated membrane was characterized for various physicochemical properties, natural organic matter (NOM) removal as well as fouling propensity using several techniques. Further, the ceramic membrane was tested on samples collected from four drinking water treatment plants in KwaZulu-Natal, South Africa (named plants 1-4). The membrane achieved 48.6%, 54.6%, 57.4%, and 76.4% bulk UV254 reduction for raw water at plants 1, 2, 3, and 4, respectively. These removal rates were comparable to UV254 reduction achieved by coagulation/flocculation steps at the respective plants. Further, the membrane outperformed sand filtration steps in plants 1-4 in removing disinfection by-product precursors (8%-32%) through size exclusion. Fluorescence excitation-emission matrices (FEEM) studies showed the removal of fluorescent NOM fractions present in the water samples by the membrane. The membrane was fabricated using an up-scalable facile method, and it has the potential for application as a polishing step to complement conventional processes in water treatment for drinking purposes.

Keywords: crossflow filtration, drinking water treatment plants, fluorescence excitation-emission matrices, ultraviolet 254 (UV₂₅₄)

Procedia PDF Downloads 43

Authors: Michael Nthabiseng Moeti, Makhulu Relebogile Langa, Joey Jansen van Vuuren

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This paper examines the utilization of personal electronic devices like laptops, tablets, and smartphones for professional duties within a financial organization. This phenomenon is known as bring your own device (BYOD). BYOD accords employees the freedom to use their personal devices to access corporate resources from anywhere in the world with Internet access. BYOD arrangements introduce significant security risks for both organizations and users. These setups change the threat landscape for enterprises and demand unique security strategies, as conventional tools tailored for safeguarding managed devices fall short in adequately protecting enterprise assets without active user cooperation. This paper applies protection motivation theory (PMT) to highlight behavioral risks from BYOD users that may impact the security of financial institutions. Thematic analysis was applied to gain a comprehensive understanding of how users perceive this phenomenon. These findings demonstrates that the existence of a security policy does not ensure that all employees will take measures to protect their personal devices. Active promotion of BYOD security policies is crucial for financial institution employees and management. This paper developed a BYOD security model which is useful for understanding compliant behaviors. Given that BYOD security is becoming a major concern across financial sector, it is important. The paper recommends that future research could expand the number of universities from which data is collected.

Keywords: BYOD, information security, protection motivation theory, security risks, thematic analysis

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Authors: Hansraj Riteesh Bookun, Emily Maree Stevens, Jarryd Leigh Solomon, Anthony Chan

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Objective: This was a retrospective cross-sectional study evaluating the safety and efficacy of femoral endarterectomy using the eversion technique with transection as opposed to the conventional endarterectomy technique with either vein or synthetic patch arterioplasty. Methods: Between 2010 to mid 2017, 19 patients with mean age of 75.4 years, underwent eversion femoral endarterectomy with transection by a single surgeon. There were 13 males (68.4%), and the comorbid burden was as follows: ischaemic heart disease (53.3%), diabetes (43.8%), stage 4 kidney impairment (13.3%) and current or ex-smoking (73.3%). The indications were claudication (45.5%), rest pain (18.2%) and tissue loss (36.3%). Results: The technical success rate was 100%. One patient required a blood transfusion following bleeding from intraoperative losses. Two patients required blood transfusions from low post operative haemogloblin concentrations – one of them in the context of myelodysplastic syndrome. There were no unexpected returns to theatre. The mean length of stay was 11.5 days with two patients having inpatient stays of 36 and 50 days respectively due to the need for rehabilitation. There was one death unrelated to the operation. Conclusion: The eversion technique with transection is safe and effective with low complication rates and a normally expected length of stay. It poses the advantage of not requiring a synthetic patch. This technique features minimal extraneous dissection as there is no need to harvest vein for a patch. Additionally, future endovascular interventions can be performed by puncturing the native vessel. There is no change to the femoral bifurcation anatomy after this technique. We posit that this is a useful adjunct to the surgeon’s panoply of vascular surgical techniques.

Keywords: endarterectomy, eversion, femoral, vascular

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Authors: R. Bhattu Babajee, Marie Sandrine Estelle Benoit

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The past decades have witnessed a considerable institutional shift towards Central Bank Independence across economies of the world. The motivation behind such a change is the acceptance that increased central bank autonomy has the power of alleviating inflation bias. Hence, studying whether Central Bank Independence acts as a significant factor behind the price stability in the African economies or whether this macroeconomic aim in these countries result from other economic, political or social factors is a pertinent issue. The main research objective of this paper is to assess the relationship between central bank autonomy and inflation in African economies where inflation has proved to be a serious problem. In this optic, we shall measure the degree of CBI in Africa by computing the turnover rates of central banks governors thereby studying whether decisions made by African central banks are affected by external forces. The purpose of this study is to investigate empirically the association between Central Bank Independence (CBI) and inflation for 10 African economies over a period of 17 years, from 1995 to 2012. The sample includes Botswana, Egypt, Ghana, Kenya, Madagascar, Mauritius, Mozambique, Nigeria, South Africa, and Uganda. In contrast to empirical research, we have not been using the usual static panel model for it is associated with potential mis specification arising from the absence of dynamics. To this issue a dynamic panel data model which integrates several control variables has been used. Firstly, the analysis includes dynamic terms to explain the tenacity of inflation. Given the confirmation of inflation inertia, that is very likely in African countries there exists the need for including lagged inflation in the empirical model. Secondly, due to known reverse causality between Central Bank Independence and inflation, the system generalized method of moments (GMM) is employed. With GMM estimators, the presence of unknown forms of heteroskedasticity is admissible as well as auto correlation in the error term. Thirdly, control variables have been used to enhance the efficiency of the model. The main finding of this paper is that central bank independence is negatively associated with inflation even after including control variables.

Keywords: central bank independence, inflation, macroeconomic variables, price stability

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Authors: Heng Ma

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Third-party warehousing logistics has an important role in the development of external logistics. At present, the third-party logistics in our country is still a new industry, the accounting system has not yet been established, the current financial accounting system of third-party warehousing logistics is mainly in the traditional way of thinking, and only able to provide the total cost information of the entire enterprise during the accounting period, unable to reflect operating indirect cost information. In order to solve the problem of third-party logistics industry cost information distortion, improve the level of logistics cost management, the paper combines theoretical research and case analysis method to reflect cost allocation by building third-party logistics costing model using Time-Driven Activity-Based Costing(TDABC), and takes S company as an example to account and control the warehousing logistics cost. Based on the idea of “Products consume activities and activities consume resources”, TDABC put time into the main cost driver and use time-consuming equation resources assigned to cost objects. In S company, the objects focuses on three warehouse, engaged with warehousing and transportation (the second warehouse, transport point) service. These three warehouse respectively including five departments, Business Unit, Production Unit, Settlement Center, Security Department and Equipment Division, the activities in these departments are classified by in-out of storage forecast, in-out of storage or transit and safekeeping work. By computing capacity cost rate, building the time-consuming equation, the paper calculates the final operation cost so as to reveal the real cost. The numerical analysis results show that the TDABC can accurately reflect the cost allocation of service customers and reveal the spare capacity cost of resource center, verifies the feasibility and validity of TDABC in third-party logistics industry cost accounting. It inspires enterprises focus on customer relationship management and reduces idle cost to strengthen the cost management of third-party logistics enterprises.

Keywords: third-party logistics enterprises, TDABC, cost management, S company

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

Procedia PDF Downloads 72

Authors: Samiya Siddique, Taslima Akter Elma, Shahrina Mahzabin, Tamanna Jerin, Mohammed Russedul Islam

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In the maneuver and designing of highway engineering, pavement performance is a principal concern. Quality of construction and materials, traffic volume, climate, etc. are the factors that affect the performance of asphalt concrete. Modified asphalt requires to attain greater strength and stability even at inimical circumstances. In this point of view, pyrolytic carbon black (PCB), which is a by-product of waste tire pyrolysis, holds incomparable properties that individualizes it from other conventional fillers by making it an imminent modifier of bitumen. Optimum asphalt content of 60/70 penetration grade asphalt is determined 5% through the Marshall Stability and Flow test for the wearing course of flexible pavement. 5, 10, and 15 percentages of PCB are then used with neat asphalt for modification. Deviations of physical and rheological properties are investigated on both PCB modified and neat asphalt by going through several laboratory tests such as penetration, softening point, and ductility tests. The obtained results reveal that the performance of paving asphalt can be upgraded by modifying it with PCB. With the increasing percentage of PCB, ductility is gradually decreased, and also penetration grade is gradually reduced from 60/70 to 30/40. Furthermore, asphalt mixtures modified with PCB demonstrate higher stability and lower flow values. The research discloses that the apposite percentage of PCB used in asphalt concrete plays a significant role in the advancement of pavement performances and reutilizing of waste tires.

Keywords: asphalt modification, pavement performances, pyrolytic carbon black, marshall stability, wearing course

Procedia PDF Downloads 149

Authors: Stanislaw Kosmynka

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Although the genesis of the activity of fighting salafist radicalism in Spain dates back to the 80’s, the development of extremism of this kind manifested itself only in the next decade. Its first permanently functioning structures in this country in the second half of 90’s of 20th century came from Algieria and Syria. At the same time it should be emphasized that this distinction is in many dimensions conventional, the more so because they consisted also of immigrants from other coutries of Islam, particularly from Morocco. The paper seeks to understand the radical salafist challenge for Spain in the context of some terrorist networks consisted of immigrants from Morocco. On the eve of the new millennium Moroccan jihadists played an increasingly important role. Although the activity of these groups had for many years mainly logistical and propaganda character, the bomb attack carried out on 11 March 2004 in Madrid constituted an expression of open forms of terrorism, directed against the authorities and society of Spain and reflected the narration of representatives of the trend of the global jihad. The people involved in carrying out that act of violence were to a large extent Moroccan immigrants; also in the following years among the cells of radicals in Spain Moroccans stood out many times. That is why the forms and directions of activity of these extremists in Spain, also after 11th March 2004 and in the actual context of the impact of Islamic State, are worth presenting. The paper is focused on threats to the security of Spain and the region and remains connected with the issues of mutual relations of the society of a host country with immigrant communities which to a large degree come from this part of Maghreb.

Keywords: jihadi terrorism, Morocco, radical salafism, security, Spain, terrorist cells, threat

Procedia PDF Downloads 525

Authors: Quoc Van Nguyen, Behzad Fatahi, Aslan S. Hokmabadi

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Performance based seismic design is a modern approach to earthquake-resistant design shifting emphasis from “strength” to “performance”. Soil-Structure Interaction (SSI) can influence the performance level of structures significantly. In this paper, a fifteen storey moment resisting frame sitting on a shallow foundation (footing) with different sizes is simulated numerically using ABAQUS software. The developed three dimensional numerical simulation accounts for nonlinear behaviour of the soil medium by considering the variation of soil stiffness and damping as a function of developed shear strain in the soil elements during earthquake. Elastic-perfectly plastic model is adopted to simulate piles and structural elements. Quiet boundary conditions are assigned to the numerical model and appropriate interface elements, capable of modelling sliding and separation between the foundation and soil elements, are considered. Numerical results in terms of base shear, lateral deformations, and inter-storey drifts of the structure are compared for the cases of soil-structure interaction system with different foundation sizes as well as fixed base condition (excluding SSI). It can be concluded that conventional design procedures excluding SSI may result in aggressive design. Moreover, the size of the foundation can influence the dynamic characteristics and seismic response of the building due to SSI and should therefore be given careful consideration in order to ensure a safe and cost effective seismic design.

Keywords: soil-structure-interaction, seismic response, shallow foundation, abaqus, rayleigh damping

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Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

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Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

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Authors: Emma Serwaa Obobisaa, Haibo Chen

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International trade and outward foreign direct investment are important factors which are generally recognized in the economic growth and development. Though several scholars have struggled to reveal the influence of trade and outward foreign direct investment (FDI) on economic growth, most studies utilized common econometric models such as vector autoregression and aggregated the variables, which for the most part prompts, however, contradictory and mixed results. Thus, there is an exigent need for the precise study of the trade and FDI effect of economic growth while applying strong econometric models and disaggregating the variables into its separate individual variables to explicate their respective effects on economic growth. This will guarantee the provision of policies and strategies that are geared towards individual variables to ensure sustainable development and growth. This study, therefore, seeks to examine the causal effect of China-Africa trade and Outward Foreign Direct Investment on the economic growth of Africa using a robust and recent econometric approach such as system dynamics model. Our study impanels and tests an ensemble of a group of vital variables predominant in recent studies on trade-FDI-economic growth causality: Foreign direct ınvestment, international trade and economic growth. Our results showed that the system dynamics method provides accurate statistical inference regarding the direction of the causality among the variables than the conventional method such as OLS and Granger Causality predominantly used in the literature as it is more robust and provides accurate, critical values.

Keywords: economic growth, outward foreign direct investment, system dynamics model, international trade

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Authors: G. St-Pierre-Lemieux, E. Askari Mahvelati, D. Groleau, P. Proulx

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Mathematical modeling has become an important tool for the study of foam behavior. Computational Fluid Dynamic (CFD) can be used to investigate the behavior of foam around foam breakers to better understand the mechanisms leading to the ‘destruction’ of foam. The focus of this investigation was the simple cone foam breaker, whose performance has been identified in numerous studies. While the optimal pumping angle is known from the literature, the contribution of pressure drop, shearing, and centrifugal forces to the foam syneresis are subject to speculation. This work provides a screening of those factors against changes in the cone angle and foam rheology. The CFD simulation was made with the open source OpenFOAM toolkits on a full three-dimensional model discretized using hexahedral cells. The geometry was generated using a python script then meshed with blockMesh. The OpenFOAM Volume Of Fluid (VOF) method was used (interFOAM) to obtain a detailed description of the interfacial forces, and the model k-omega SST was used to calculate the turbulence fields. The cone configuration allows the use of a rotating wall boundary condition. In each case, a pair of immiscible fluids, foam/air or water/air was used. The foam was modeled as a shear thinning (Herschel-Buckley) fluid. The results were compared to our measurements and to results found in the literature, first by computing the pumping rate of the cone, and second by the liquid break-up at the exit of the cone. A 3D printed version of the cones submerged in foam (shaving cream or soap solution) and water, at speeds varying between 400 RPM and 1500 RPM, was also used to validate the modeling results by calculating the torque exerted on the shaft. While most of the literature is focusing on cone behavior using Newtonian fluids, this works explore its behavior in shear thinning fluid which better reflects foam apparent rheology. Those simulations bring new light on the cone behavior within the foam and allow the computation of shearing, pressure, and velocity of the fluid, enabling to better evaluate the efficiency of the cones as foam breakers. This study contributes to clarify the mechanisms behind foam breaker performances, at least in part, using modern CFD techniques.

Keywords: bioreactor, CFD, foam breaker, foam mitigation, OpenFOAM

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Authors: Habtamu Tkubet Ebuy

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Purpose Conventional dynamic energy simulation tools go beyond the static dimension of simplified methods by providing better and more accurate prediction of building performance. However, their ability to forecast actual performance is undermined by a low representation of human interactions. The purpose of this study is to examine the potential benefits of incorporating information on occupant diversity into occupant behavior models used to simulate building performance. The co-simulation of the stochastic behavior of the occupants substantially increases the accuracy of the simulation. Design/methodology/approach In this article, probabilistic models of the "opening and closing" behavior of the window of inhabitants have been developed in a separate multi-agent platform, SimOcc, and implemented in the building simulation, TRNSYS, in such a way that the behavior of the window with the interconnectivity can be reflected in the simulation analysis of the building. Findings The results of the study prove that the application of complex behaviors is important to research in predicting actual building performance. The results aid in the identification of the gap between reality and existing simulation methods. We hope this study and its results will serve as a guide for researchers interested in investigating occupant behavior in the future. Research limitations/implications Further case studies involving multi-user behavior for complex commercial buildings need to more understand the impact of the occupant behavior on building performance. Originality/value This study is considered as a good opportunity to achieve the national strategy by showing a suitable tool to help stakeholders in the design phase of new or retrofitted buildings to improve the performance of office buildings.

Keywords: occupant behavior, co-simulation, energy consumption, thermal comfort

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Authors: Filippo Ranalli, Forest Flager, Martin Fischer

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This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: cost-based structural optimization, cost-based topology and sizing, optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures

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Authors: A. Bouhmouche, I. Rhrissi, A. Jabar, R. Moubah

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Quantum spin liquids (QSLs), known for their competing interactions that prevent conventional ordering, exhibit emergent phenomena and exotic properties resulting from quantum correlations. Despite these recent advancements in QSLs, a significant portion of the optical and thermodynamic properties in the Kagome lattice remains unknown. In addition, the thermodynamic phenomenology of NaRuO₂ bears a resemblance to that of highly frustrated magnets. Here, we employed ab-initio calculations to explore the electronic, optical and thermodynamic properties of NaRuO₂, a new QSL candidate. NaRuO₂ was identified as a semiconductor with a small bandgap energy of 0.69 eV. Our results reveal huge anisotropic optical properties, in which a distinct refractive index within the ab-plane indicating an impressive birefringent character of the NaRuO₂ system and a significant enhancement of the optical absorption coefficient and optical conductivity in the in-plane with respect to the c-axis. The investigation also examines the electronic anisotropy of the gap energy; by applying strain, the gap energy displays significant variations in the ab-plane compared to the out-of-plane direction. Conversely, calculations of the thermodynamic properties reveal a low thermal conductivity (2.5-0.5 W.m-¹. K-¹) and specific heat, which suggests the existence of strong interactions among the NaRuO₂ quantum spins. The linear specific heat behavior observed in NaRuO₂ suggests the fractionalization of electrons and the presence of a spinons Fermi surface. These findings hold promising potential for future quantum applications.

Keywords: quantum spin liquids, anisotropy, hybrid-DFT, applied strain, optoelectronic and thermodynamic properties

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Authors: Zahreddine Hafsi, Manoranjan Mishra , Sami Elaoud

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Ensuring the maximum recovery rate of oil from reservoir rocks is a challenging task that requires preliminary numerical analysis of different techniques used to enhance the recovery process. After conventional oil recovery processes and in order to retrieve oil left behind after the primary recovery phase, water flooding in one of several techniques used for enhanced oil recovery (EOR). In this research work, EOR via water flooding is numerically modeled, and hydrodynamic instabilities resulted from immiscible oil-water flow in reservoir rocks are investigated. An oil reservoir is a porous medium consisted of many fractures of tiny dimensions. For modeling purposes, the oil reservoir is considered as a collection of capillary tubes which provides useful insights into how fluids behave in the reservoir pore spaces. Equations governing oil-water flow in oil reservoir rocks are developed and numerically solved following a finite element scheme. Numerical results are obtained using Comsol Multiphysics software. The two phase Darcy module of COMSOL Multiphysics allows modelling the imbibition process by the injection of water (as wetting phase) into an oil reservoir. Van Genuchten, Brooks Corey and Levrett models were considered as retention models and obtained flow configurations are compared, and the governing parameters are discussed. For the considered retention models it was found that onset of instabilities viz. fingering phenomenon is highly dependent on the capillary pressure as well as the boundary conditions, i.e., the inlet pressure and the injection velocity.

Keywords: capillary pressure, EOR process, immiscible flow, numerical modelling

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Authors: Michelle Micah Augustine

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Soap opera narrative creates a sense of community. Uzalo is a South African local soap opera television series. It is unique because Uzalo tells the story of black people and their everyday struggle centered in KwaMashu township community, which is an excellent example of how moving image culture has contributed in portraying township community that was once marginalized by the apartheid regime in contemporary South Africa. While soap opera importance and promotion of social change and behaviours have been extensively studied throughout history, little research has examined the importance of space and place in its narrative. This study explored the conventional community space and place, the core elements that drive soap opera narrative. By means of qualitative content analysis, the study investigated the construction of public meeting places in Uzalo, using a purposive sampling technique to collect data by choosing episodes. The result indicates that characters convergence in public meeting places in soap opera creates disequilibrium which drives the narrative; reveals that construction of a public meeting place is an important way of creating a minimum of homogeneousness among disparate characters, gives a sense of unified experience drawing on the notion of the particular characteristics or attitude generated from such place. The result shows that the use of camera angles, movements, editing, music and usual tricks (mise-en-scene) applied in the narrative setting function as a guide for viewers comprehension of emotional responses of the story and to connect with the space in which the narrative is set.

Keywords: community, narrative, place, space, soap opera

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

Procedia PDF Downloads 157