Search results for: optimization problem

Authors: Ana Belon Hercilla

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The study is developed in “Reactivos Jeans” company, in the city of Arequipa, whose main business is the laundry of garments at an industrial level. In 2012 the company initiated actions to provide a dry cleaning service of alpaca fiber garments, recognizing that this item is in a growth phase in Peru. Additionally this company took the initiative to use a new greenwashing technology which has not yet been developed in the country. To accomplish this, a redesign of both the process and the plant layout was required. For redesigning the plant, the methodology used was the Systemic Layout Planning, allowing this study divided into four stages. First stage is the information gathering and evaluation of the initial situation of the company, for which a description of the areas, facilities and initial equipment, distribution of the plant, the production process and flows of major operations was made. Second stage is the development of engineering techniques that allow the logging and analysis procedures, such as: Flow Diagram, Route Diagram, DOP (process flowchart), DAP (analysis diagram). Then the planning of the general distribution is carried out. At this stage, proximity factors of the areas are established, the Diagram Paths (TRA) is developed, and the Relational Diagram Activities (DRA). In order to obtain the General Grouping Diagram (DGC), further information is complemented by a time study and Guerchet method is used to calculate the space requirements for each area. Finally, the plant layout redesigning is presented and the implementation of the improvement is made, making it possible to obtain a model much more efficient than the initial design. The results indicate that the implementation of the new machinery, the adequacy of the plant facilities and equipment relocation resulted in a reduction of the production cycle time by 75.67%, routes were reduced by 68.88%, the number of activities during the process were reduced by 40%, waits and storage were removed 100%.

Keywords: redesign, time optimization, industrial laundry, greenwashing

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Authors: Ashish Khanal, Suja Giri

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The scrap collection work is associated with multiple health hazards. Cut and scratches during collection and transportation of scraps are common. IWBs purchase the scraps mainly papers, cartoons, glass bottles and metals from the households. This study was conducted in Kathmandu, the capital city of Nepal. The location was chosen because Kathmandu is the biggest city of Nepal with highest number of IWBs. The research used a case study strategy to examine the occupational health hazards of IWBs. The only mode of collecting and transporting of scraps in Kathmandu is the bicycle. They have to do this regular work even during the scorching sun and chilled winter. The musculoskeletal and gastrointestinal disorders are the common health problem shared by IWBs in Kathmandu, Nepal. Despite of these problems, IWBs don’t take it seriously and rarely goes for the health check-up. There is need of personal protective equipment and guidance for safety of IWBs. IWBs need to wear closed shoes and use gloves to avoid cuts during the collection and transportation of the recyclables.

Keywords: itinerant waste buyers, Kathmandu, occupational health, scrap

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Authors: A.M. Kaja, Q. Yu, H.J.H Brouwers

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An increased functionality of concrete towards higher eco-efficiency is nowadays of great importance due to the decreasing air quality in urban areas. Surface modifications of concrete walls and roads, as a coating or an intermixing of the surface layer with TiO₂, provide an opportunity to improve the air quality by reducing NOx via photocatalytic phenomena. Nevertheless, there are still concerns regarding the cost-efficiency as well as the toxicity of intermediate products which can be produced during the photocatalysis, limiting a widespread adoption of these materials. This study addresses the problem of the selectivity of cement mortars towards nitrate in terms of microstructural characteristics and hydration products. The ability of cement mortars matrix intermixed with commercial TiO₂ and TiO₂-SiO₂ composite to abate NO₂ is investigated. The influence of hydration products formed under the carbonation facilitating conditions is discussed and solutions how to optimize the mix design are proposed. The incorporation of the TiO₂-SiO₂ composite into cement mortar is found to increase the nitrate selectivity index.

Keywords: cement matrix, NO₂ abatement, photocatalysis, TiO₂-SiO₂ composite

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Authors: Abosede Priscilla Ipadeola

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The quest for egalitarian justice requires a suitable theoretical foundation that can address the problem of marginalization and subjugation arising from various forms of oppression, such as sexism, racism, classism, and others. Many thinkers and societies have appealed to contractarianism, a theory that has been widely regarded as a doctrine of egalitarianism by some political theorists for about five centuries. Despite its numerous criticisms, the social contract still enjoys a prominent status as a key theory for egalitarian justice. However, Pateman and Mills have contended that the contractarian approach legitimizes gender and racial inequalities by excluding and marginalizing women and people of color from the original agreement. Therefore, the social contract is incapable of generating or fostering equality. This study proposes postcontractarianism, which is a viable alternative to the social contract. Postcontractarianism argues that the basis for egalitarianism cannot be grounded on agreement but rather on understanding. Postcontractarianism draws on Jorge Nef’s idea of mutual vulnerability and Obiri (an African theory of cosmology) to argue for the imperative of social equality.

Keywords: postcontractarianism, obiri, mutual vulnerability, egalitarianism, the social contract

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Authors: Mohamed Moussaoui

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A series of thirty-one potential inhibitors targeting the epidermal growth factor receptor kinase (EGFR), derived from quinazoline, underwent 3D-QSAR analysis using CoMFA and CoMSIA methodologies. The training and test sets of quinazoline derivatives were utilized to construct and validate the QSAR models, respectively, with dataset alignment performed using the lowest energy conformer of the most active compound. The best-performing CoMFA and CoMSIA models demonstrated impressive determination coefficients, with R² values of 0.981 and 0.978, respectively, and Leave One Out cross-validation determination coefficients, Q², of 0.645 and 0.729, respectively. Furthermore, external validation using a test set of five compounds yielded predicted determination coefficients, R² test, of 0.929 and 0.909 for CoMFA and CoMSIA, respectively. Building upon these promising results, eighteen new compounds were designed and assessed for drug likeness and ADMET properties through in silico methods. Additionally, molecular docking studies were conducted to elucidate the binding interactions between the selected compounds and the enzyme. Detailed molecular dynamics simulations were performed to analyze the stability, conformational changes, and binding interactions of the quinazoline derivatives with the EGFR kinase. These simulations provided deeper insights into the dynamic behavior of the compounds within the active site. This comprehensive analysis enhances the understanding of quinazoline derivatives as potential anti-cancer agents and provides valuable insights for lead optimization in the early stages of drug discovery, particularly for developing highly potent anticancer therapeutics

Keywords: 3D-QSAR, CoMFA, CoMSIA, ADMET, molecular docking, quinazoline, molecular dynamic, egfr inhibitors, lung cancer, anticancer

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Authors: Yang Cui, Yong Qiang Chen

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An appropriate project delivery system (PDS) is crucial to the success of a construction project. Case-based reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the relational case-based reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then, feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: relational cased-based reasoning, case-based reasoning, project delivery system, PDS selection

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Authors: Rosemary R. Carlton, Roxane Caron

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Almost three decades ago, bell hooks (1994) identified the classroom as “the most radical space of possibility in the academy”. A feminist scholar, educator, and activist, hooks urged educators to transgress the boundaries of what might be customary or considered acceptable in teaching, thus encouraging the pursuit of new ways of knowing and different strategies for sharing knowledge. This paper reflects upon a particular response to hooks’ still relevant call for transgression in teaching. Specifically, this paper reports on the design, implementation, and preliminary analysis of a social work course integrating active pedagogy and transnational exchange to encourage students’ critical thinking and autonomous learning in their development as social workers in a global context. The bachelor’s level course, Pratiques spécifiques: Projet international, was developed collaboratively across three francophone institutions of higher learning in Belgium, Canada, and France: the Haute École de Namur-Liège-Luxembourg (Hénallux); the Université de Montréal; and, the Institut d’enseignement supérieur et professionnel, l’IRTS Paris Île-de-France. The driving aims of the course are to promote autonomous learning and critical thinking through a lens of transnational understandings of social problems -competencies indispensable to students’ development as social workers. The course is offered to two paired cohorts, one addressing the subject of “migrations” (Canada/France) and the other the subject of “sexual exploitation” (Canada/Belgium). Through the adaptation of a critical pedagogy of problem-based learning, students are called upon to actively engage in acquiring and applying knowledge to respond to “real life” social issues relating to migration or sexual exploitation. At the conclusion of the course, each cohort of students is brought together for a week-long intensive period of transnational exchange either at the Université de Montréal in Canada or at Hénallux in Belgium. Extending the bounds of the classroom across international borders allows students novel opportunities to deepen and expand their understandings of issues relating to predefined social issues and to critically examine associated social work practices. The paper opens with a presentation of the social work course. Specifically, the authors will outline their adaptation of a pedagogy of problem-based learning integrating transnational exchange in the design and implementation of the course. Returning to hooks’ notion of transgression in teaching, the paper offers a preliminary analysis of how and with what effect the course provides opportunities to transgress hierarchical student-teacher relationships; transgress conventional modes of learning to explore diverse sources of knowledge and transgress the walls of the university to engage with and learn from local and global partners. The paper concludes with a consideration of the potential influence of such transgressions in teaching for students’ development of critical thinking in their practice of social work in global context.

Keywords: active learning, critical pedagogy, social work intervention, transnational learning

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Authors: M. Belachia, R. Djebien

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In the development that our country has in all areas and especially in the field of Building and Construction, the development of new building materials is a current problem where researchers are trying to find the right materials for each region and returning cheapest countries. Enhancement of crushed sand and sand dunes and reuse of waste as additions in concrete can help to overcome the deficit in aggregates. This work focuses on the development of concrete made from sand, knowing that our country has huge potential in sand dune. This study is complemented by a review of the possibility of using certain recycled wastes in concrete sand, including the effect of fines (marble powders) on the rheological and mechanical properties of concrete and sand to the outcome optimal formulation. After the characterization phase of basic materials, we proceeded to carry out the experimental program was to search the optimum characteristics by adding different percentages of fines. The aim is to show that the possibility of using local materials (sand dune) for the manufacture of concrete and reuse of waste (marble powders) in the implementation of concrete.

Keywords: sand dune, mechanical properties, rheological properties, fine marble

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Authors: Myrto Dagkouli-Kyriakoglou

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Southern European countries tend to have a lot of connections in their culture, customs, ideals and attitude towards everyday aspects. On the contrary, all of them demonstrate a lot of differences in their history, political life and economic situation. Nevertheless, the state welfare and its insufficiency to deal with citizens’ needs, is common for the whole region. As the global financial crisis initiated, all of them gradually were affected and established austerity measures. Consequently, there were crucial budget cuts in state welfare and accordingly limited support to the citizens at a time that is most needed as the economic difficulties of the households are rising rapidly. Crisis in connection with austerity measures brought up a housing problem which was hidden for decades with the assistance of the institution of the Southern European family. New or old copying practices concerning housing are already developed and more will rise in order to survive this new era. Expressly, youth is one of the most vulnerable groups in this situation and therefore there is a special focus on the policies that affect their housing as well as their copying practices in connection with the family/kinship strategies.

Keywords: housing, coping practices, Greece, familism

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Authors: Isa Ahmadi, Ramin Khamedi

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In this paper, the elasto-plastic and cyclic torsion of a shaft is studied using a finite element method. The Prager kinematic hardening theory of plasticity with the Ramberg and Osgood stress-strain equation is used to evaluate the cyclic loading behavior of the shaft under the torsional loading. The material of shaft is assumed to follow the non-linear strain hardening property based on the Prager model. The finite element method with C1 continuity is developed and used for solution of the governing equations of the problem. The successive substitution iterative method is used to calculate the distribution of stresses and plastic strains in the shaft due to cyclic loads. The shear stress, effective stress, residual stress and elastic and plastic shear strain distribution are presented in the numerical results.

Keywords: cyclic loading, finite element analysis, Prager kinematic hardening model, torsion of shaft

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Authors: Pinisetti Swami Sairam, Meera C. S.

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Marker pens are widely used all over the world, mainly in educational institutions due to their neat, accurate and easily erasable nature. But refilling the ink in these pens is a tedious and time consuming job. Besides, it requires careful handling of the pens and ink bottle. A fully automated marker filling system is a solution developed to overcome this problem. The system comprises of pneumatics and electronics modules as well as PLC control. The system design is done in such a way that the empty markers are dumped in a marker container which then sent through different modules of the system in order to refill it automatically. The filled markers are then collected in a marker container. Refilling of ink takes place in different stages inside the system. An ink detecting system detects the colour of the marker which is to be filled and then refilling is done. The processes like capping and uncapping of the cap as well as screwing and unscrewing of the tip are done with the help of robotic arm and gripper. We make use of pneumatics in this system in order to get the precision while performing the capping, screwing, and refilling operations. Thus with the help of this system we can achieve cleanliness, accuracy, effective and time saving in the process of filling a marker.

Keywords: automated system, market filling, information technology, control and automation

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Authors: Mimi Mohaffyza Mohamad, Yee Mei Heong, Nurfirdawati Muhammad Hanafi, Tee Tze Kiong

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This study is conducted to investigate the disparity of between learning styles and cognitive abilities specifically in Vocational Education. Felder and Silverman Learning Styles Model (FSLSM) was applied to measure the students’ learning styles while the content in Building Construction Subject consists; knowledge, skills and problem solving were taken into account in constructing the elements of cognitive abilities. There are four dimension of learning styles proposed by Felder and Silverman intended to capture student learning preferences with regards to processing either active or reflective, perception based on sensing or intuitive, input of information used visual or verbal and understanding information represent with sequential or global learner. The study discovered that students are tending to be visual learners and each type of learner having significant difference whereas cognitive abilities. The finding may help teachers to facilitate students more effectively and to boost the student’s cognitive abilities.

Keywords: learning styles, cognitive abilities, dimension of learning styles, learning preferences

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Authors: Syed Talib Abbas Raza, Tahseen Ahmed Jilani, Saleem Abdullah

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This paper presents interval-valued intuitionistic fuzzy soft sets based TOPSIS method for group decision making. The interval-valued intuitionistic fuzzy soft set is a mutation of an interval-valued intuitionistic fuzzy set and soft set. In group decision making problems IVIFSS makes the process much more algebraically elegant. We have used weighted arithmetic averaging operator for aggregating the information and define a new Hybrid Score Function as metric tool for comparison between interval-valued intuitionistic fuzzy values. In an illustrative example we have applied the developed method to a criminological problem. We have developed a group decision making model for integrating the imprecise and hesitant evaluations of multiple law enforcement agencies working on target killing cases in the country.

Keywords: group decision making, interval-valued intuitionistic fuzzy soft set, TOPSIS, score function, criminology

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Authors: Domingos Vita, Patrick Brady

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Background: There is a tuberculosis (TB) epidemic in Angola that has been getting worse for more than a decade despite the active implementation of the DOTS strategy. The aim of this study was to directly interrogate healthcare workers involved in TB control on what they consider to be the drivers of the TB epidemic in Angola. Methods: Twenty four in-depth qualitative interviews were conducted with medical staff working in this field in the provinces of Luanda and Benguela. Results: The healthcare professionals see the migrant working poor as a particular problem for the control of TB. These migrants are constructed as ‘Rural People’ and are seen as non-compliant and late-presenting. This is a stigmatized and marginal group contending with the additional stigma associated with TB infection. The healthcare professionals interviewed also see the interruption of treatment and self medication generally as a better explanation for the TB epidemic than urbanization or lack of medication. Conclusions: The local narrative is in contrast to previous explanations used elsewhere in the developing world. To be effective policy must recognize the local issues of the migrant workforce, interruption of treatment and the stigma associated with TB in Angola.

Keywords: Africa, Angola, migrants, qualitative, research, tuberculosis

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Authors: K. Y. Shih, H. M. Lin, S. Y. Lee, T. L. Hong

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Recently a number of food safety scandals have been on the news. In view of the fact that in Taiwan the majority of undergraduate college students reside in the dorms and dine out, the problem of restaurant sanitation is of utmost importance in their lives. The purpose of this study is to analyze students' dining habit and their perception of food safety. Four universities in the city of Tainan were randomly selected, and from each selected university a class was then chosen to receive 50 questionnaires. The total of 200 questionnaires yielded 144 usable returns. Students were asked to respond to questions, and each question was graded on a scale from 1 to 5 according to the importance. There were 32 questions ranging over various aspects: cleanliness of surroundings, washroom, food sanitation, serving temperature, kitchen sanitation, and service personnel cleanliness. It is found that the food sanitation received the highest score, while the service personnel ranked the lowest. An incidental finding is that the students tend to dine out in groups and as such their choice of restaurants are mostly dictated by consensus.

Keywords: food safety, restaurant, risk perception, sanitation

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Authors: Mahdi Shamsi, Tohid Yousefi Rezaii, Siavash Eftekharifar

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Compressed sensing (CS) is a new powerful mathematical theory concentrating on sparse signals which is widely used in signal processing. The main idea is to sense sparse signals by far fewer measurements than the Nyquist sampling rate, but the reconstruction process becomes nonlinear and more complicated. Common dilemma in sparse signal recovery in CS is the lack of knowledge about sparsity order of the signal, which can be viewed as model order selection procedure. In this paper, we address the problem of sparsity order estimation in sparse signal recovery. This is of main interest in situations where the signal sparsity is unknown or the signal to be recovered is approximately sparse. It is shown that the proposed method also leads to some kind of signal denoising, where the observations are contaminated with noise. Finally, the performance of the proposed approach is evaluated in different scenarios and compared to an existing method, which shows the effectiveness of the proposed method in terms of order selection as well as denoising.

Keywords: compressed sensing, data denoising, model order selection, sparse representation

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Authors: Gebremeskel Hagos Gebremedhin, Feng Chong, Heyan Huang

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Software system is the combination of architecture and organized components to accomplish a specific function or set of functions. A good software architecture facilitates application system development, promotes achievement of functional requirements, and supports system reconfiguration. We describe three studies demonstrating the utility of our architecture in the subdomain of mobile office robots and identify software engineering principles embodied in the architecture. The main aim of this paper is to analyze prove architecture design and automatic re-architecting using machine learning. Intelligence software architecture and automatic re-architecting process is reorganizing in to more suitable one of the software organizational structure system using the user access dataset for creating relationship among the components of the system. The 3-step approach of data mining was used to analyze effective recovery, transformation and implantation with the use of clustering algorithm. Therefore, automatic re-architecting without changing the source code is possible to solve the software complexity problem and system software reuse.

Keywords: intelligence, software architecture, re-architecting, software reuse, High level design

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Authors: Roman Kalvin, Anam Nadeem, Saba Arif, Juntakan Taweekun

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In the current scenario demand of power is increasing day by day with increasing population. It is needed to sort out this problem with a technique which will not only overcome this energy crisis but also should be environment friendly. This project emphasizes on idea which shows that power could be generated by specially designed speed breaker. This project shows clearly how power can be generated by using Cam Mechanism where basically linear motion is converted into rotatory motion that can be used to generate electricity. When vehicle passes over the speed breaker, presses the cam with the help of connecting rod which rotate main shaft attached with large pulley. A flywheel is coupled with the shaft whose purpose is to normalize the oscillation in the energy and to make the energy unvarying. So, the shafts will spin with firm rpm. These shafts are coupled from end to end with a belt drive. The results show that power generated from this mechanism is 12 watts. The generated electricity does not required any fuel consumption it only generates power which can be used for the street light as well as for the traffic signals.

Keywords: revolution per minute, RPM, cam, speed breaker, rotatory motion

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Authors: Neha Singh, Shristi Singh

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Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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Authors: Efri Mardawati, Ronny Purwadi, Made Tri Ari Penia Kresnowati, Tjandra Setiadi

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EFB are mainly composed of cellulose (≈ 43%), hemicellulose (≈ 23%) and lignin (≈20%). The palm oil empty fruit bunches (EFB) is the lignosellulosic waste from crude palm oil industries mainly compose of (≈ 43%), hemicellulose (≈ 23%) and lignin (≈20%). Xylan, a polymer made of pentose sugar xylose and the most abundant component of hemicellulose in plant cell wall. Further xylose can be used as a raw material for production of a wide variety of chemicals such as xylitol, which is extensively used in food, pharmaceutical and thin coating applications. Currently, xylose is mostly produced from xylan via chemical hydrolysis processes. However, these processes are normally conducted at a high temperature and pressure, which is costly, and the required downstream processes are relatively complex. As an alternative method, enzymatic hydrolysis of xylan to xylose offers an environmentally friendly biotechnological process, which is performed at ambient temperature and pressure with high specificity and at low cost. This process is catalysed by xylanolytic enzymes that can be produced by some fungal species such as Aspergillus niger, Penicillium crysogenum, Tricoderma reseei, etc. Fungal that will be used to produce crude xylanase enzyme in this study is T. Viride ITB CC L.67. It is the purposes of this research to study the influence of pretreatment of EFB for the enzymatic hydrolysis process, optimation of temperature and pH of the hydrolysis process, the influence of substrate and enzyme concentration to the enzymatic hydrolysis process, the dynamics of hydrolysis process and followingly to study the kinetics of this process. Xylose as the product of enzymatic hydrolysis process analyzed by HPLC. The results show that the thermal pretreatment of EFB enhance the enzymatic hydrolysis process. The enzymatic hydrolysis can be well approached by the Michaelis Menten kinetic model, and kinetic parameters are obtained from experimental data.

Keywords: oil palm empty fruit bunches (EFB), xylose, enzymatic hydrolysis, kinetic modelling

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Zihan Geng, L. Quentin Dixon

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It has been proposed that early bilingual experience confers a number of advantages in the development of executive control mechanisms. Although the literature provides empirical evidence for bilingual benefits, some studies also reported null or mixed results. To make sense of these contradictory findings, the current review synthesize recent empirical studies investigating bilingual effects on children’s executive function and attention control. The publication time of the studies included in the review ranges from 2010 to 2017. The key searching terms are bilingual, bilingualism, children, executive control, executive function, and attention. The key terms were combined within each of the following databases: ERIC (EBSCO), Education Source, PsycINFO, and Social Science Citation Index. Studies involving both children and adults were also included but the analysis was based on the data generated only by the children group. The initial search yielded 137 distinct articles. Twenty-eight studies from 27 articles with a total of 3367 participants were finally included based on the selection criteria. The selective studies were then coded in terms of (a) the setting (i.e., the country where the data was collected), (b) the participants (i.e., age and languages), (c) sample size (i.e., the number of children in each group), (d) cognitive outcomes measured, (e) data collection instruments (i.e., cognitive tasks and tests), and (f) statistic analysis models (e.g., t-test, ANOVA). The results show that the majority of the studies were undertaken in western countries, mainly in the U.S., Canada, and the UK. A variety of languages such as Arabic, French, Dutch, Welsh, German, Spanish, Korean, and Cantonese were involved. In relation to cognitive outcomes, the studies examined children’s overall planning and problem-solving abilities, inhibition, cognitive complexity, working memory (WM), and sustained and selective attention. The results indicate that though bilingualism is associated with several cognitive benefits, the advantages seem to be weak, at least, for children. Additionally, the nature of the cognitive measures was found to greatly moderate the results. No significant differences are observed between bilinguals and monolinguals in overall planning and problem-solving ability, indicating that there is no bilingual benefit in the cooperation of executive function components at an early age. In terms of inhibition, the mixed results suggest that bilingual children, especially young children, may have better conceptual inhibition measured in conflict tasks, but not better response inhibition measured by delay tasks. Further, bilingual children showed better inhibitory control to bivalent displays, which resembles the process of maintaining two language systems. The null results were obtained for both cognitive complexity and WM, suggesting no bilingual advantage in these two cognitive components. Finally, findings on children’s attention system associate bilingualism with heightened attention control. Together, these findings support the hypothesis of cognitive benefits for bilingual children. Nevertheless, whether these advantages are observable appears to highly depend on the cognitive assessments. Therefore, future research should be more specific about the cognitive outcomes (e.g., the type of inhibition) and should report the validity of the cognitive measures consistently.

Keywords: attention, bilingual advantage, children, executive function

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Authors: Dilek Turan Eroğlu

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Educators have been searching the more effective and appalling methods of teaching for ages. It has always been an issue among the teachers and scientists to improve the quality of education and to ensure that all students have equal opportunities to learn. However, when it comes to the effective ways of learning,the learners are exposed to the ways which are chosen and approved to be effective by their teachers not by the learners themselves. This is the main problem of this study as the learners are not always happy to be in their classes being treated with their teachers’ favourite styles. This paper is telling the results of a study which has been conducted with the university students in Turkey. The students have been interviewed and asked to respond some questions related to best practices to find out their favourite styles, medium, techniques and strategies. The study has been conducted using qualitative research methods i.e one to one interviews and group discussions. The results show that the learners have significantly different views than the educators when it comes to modern teaching styles. Their definition of the term “modern teaching styles” is different than the general understanding. The university students expect their teachers to be “early adopter”. of ICT tools and or the other electronic devices, but a modern teacher must have many other characteristics for them.

Keywords: effective, innovation, teaching, modern teaching styles

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Authors: I. Benhsine, M. Hellou, F. Lominé, Y. Roques

Abstract:

During the manufacture of fertilizer, it is necessary to add water for granulation purposes. The water content is then removed or reduced using rotary dryers. They are commonly used to dry wet granular materials and they are usually fitted with lifting flights. The transport of granular materials occurs when particles cascade from the lifting flights and fall into the air stream. Each cascade consists of a lifting and a falling cycle. Lifting flights are thus of great importance for the transport of granular materials along the dryer. They also enhance the contact between solid particles and the air stream. Optimization of the drying process needs an understanding of the behavior of granular materials inside a rotary dryer. Different approaches exist to study the movement of granular materials inside the dryer. Most common of them are based on empirical formulations or on study the movement of the bulk material. In the present work, we are interested in the behavior of each particle in the cross section of the dryer using Discrete Element Method (DEM) to understand. In this paper, we focus on studying the hold-up, the cascade patterns, the falling time and the falling length of the particles leaving the flights. We will be using two segment flights. Three different profiles are used: a straight flight (180° between both segments), an angled flight (with an angle of 150°), and a right-angled flight (90°). The profile of the flight affects significantly the movement of the particles in the dryer. Changing the flight angle changes the flight capacity which leads to different discharging profile of the flight, thus affecting the hold-up in the flight. When the angle of the flight is reduced, the range of the discharge angle increases leading to a more uniformed cascade pattern in time. The falling length and the falling time of the particles also increase up to a maximum value then they start decreasing. Moreover, the results show an increase in the falling length and the falling time up to 70% and 50%, respectively, when using a right-angled flight instead of a straight one.

Keywords: discrete element method, granular materials, lifting flight, rotary dryer

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Authors: V. Mantey, N. Findlay, I. Maddox

Abstract:

The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Soroush Maddah, Houra Asgarian, Mahdi Navidbakhsh

Abstract:

In the present paper, the problem of pulsatile micropolar blood flow through an elastic artery has been studied. An arbitrary Lagrangian-Eulerian (ALE) formulation for the governing equations has been produced to model the fully-coupled fluid-structure interaction (FSI) and has been solved numerically using finite difference scheme by exploiting a mesh generation technique which leads to a uniformly spaced grid in the computational plane. Effect of the variations of cardiac output and wall artery module of elasticity on blood pressure with blood-pressure regulating drugs like Atenolol has been determined. Also, a numerical model has been produced to define precisely the effects of various dosages of a drug on blood flow in arteries without the numerous experiments that have many mistakes and expenses.

Keywords: arbitrary Lagrangian-Eulerian, Atenolol, fluid structure interaction, micropolar fluid, pulsatile blood flow

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Authors: Mohamed Mokhtar, Mostafa F. Shaaban

Abstract:

Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

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Authors: Jair Servín-Aguilar, Yu Tang

Abstract:

We address the problem of robust attitude tracking for agile satellites under unknown bounded torque disturbances using a double-gimbal variable-speed control-moment gyro (DGVSCMG) driven by a cluster of three permanent magnet synchronous motors (PMSMs). Uniform practical asymptotic stability is achieved at the torque control level first. The desired speed of gimbals and the acceleration of the spin wheel to produce the required torque are then calculated by a velocity-based steering law and tracked at the PMSM speed-control level by designing a speed-tracking controller with compensation for the vibration caused by eccentricity and imbalance due to mechanical imperfection in the DGVSCMG. Uniform practical asymptotic stability of the overall system is ensured by loan relying on the analysis of the resulting cascaded system. Numerical simulations are included to show the performance improvement of the proposed controller.

Keywords: agile satellites, vibration compensation, internal model, stability

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Authors: Hao Min Chuah, Tatsuya Yamazaki, Ryosui Iwasawa, Tatsumi Suto

Abstract:

In recent years, with the advancement of digital technology, the movement to introduce so-called ICT (Information and Communication Technology), such as computer technology and network technology, to civil engineering construction sites and construction sites is accelerating. As part of this movement, attempts are being made in various situations to reproduce actual sites inside computers and use them for designing and construction planning, as well as for training inexperienced engineers. The installation of wave-dissipating blocks on coasts, etc., is a type of work that has been carried out by skilled workers based on their years of experience and is one of the tasks that is difficult for inexperienced workers to carry out on site. Wave-dissipating blocks are structures that are designed to protect coasts, beaches, and so on from erosion by reducing the energy of ocean waves. Wave-dissipating blocks usually weigh more than 1 t and are installed by being suspended by a crane, so it would be time-consuming and costly for inexperienced workers to train on-site. In this paper, therefore, a block installation simulator is developed based on Unity 3D, a game development engine. The simulator computes porosity. Porosity is defined as the ratio of the total volume of the wave breaker blocks inside the structure to the final shape of the ideal structure. Using the evaluation of porosity, the simulator can determine how well the user is able to install the blocks. The voxelization technique is used to calculate the porosity of the structure, simplifying the calculations. Other techniques, such as raycasting and box overlapping, are employed for accurate simulation. In the near future, the simulator will install an automatic block installation algorithm based on combinatorial optimization solutions and compare the user-demonstrated block installation and the appropriate installation solved by the algorithm.

Keywords: 3D simulator, porosity, user interface, voxelization, wave-dissipating blocks

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Authors: Ozlem Durna Aydin, Gultekin Yildiz

Abstract:

Antibiotics are microbial metabolites with low molecular weight produced by fungi and algae, inhibiting the development of other microorganisms even in low growth. Antibiotics have been used as growth factors in animal feeds for many years. They prohibited; because of increased residue problem and increased resistance to antibiotics in bacteria due to prolonged use. Aromatic plants and extracts have attracted the attention of scientists nowadays due to positive reasons such as confidence of the community to the products those are coming from nature, desire to consume, and no residue problems. Plant extracts are obtained from aromatic plants, and they come forward with antifungal, antibacterial, antiviral, antioxidant and antilipidemic properties. It has been stated that intestinal histomorphology and microbiosis are positively affected by the use of plant extract in feeds. In the present day, aromatic plants and extracts are a remarkable research field with intriguing unknowns in the field of animal nutrition, and they continue to exist in the journal in vitro and in vivo studies.

Keywords: aromatic plant, broilers, extract mechanism of action, intestinal health

Procedia PDF Downloads 161