Search results for: successful outsourcing

Authors: Diana Isabel Torres Silva

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Doris Salcedo is the most prominent sculptor from Colombia ever and currently, one of the most prestigious Latin-American artists in the world. Her artwork, intended as political art, has war as a background, in particular the Colombian civil conflict, and it addresses the way that its violence affects victims’ lives irreparably. While Salcedo is internationally recognized as a talented and a politically committed artist, some Colombian critics consider her artwork as the propagandist and influenced by the interest of multinational companies and the organizations that fund it. This paper, as part of a more extended research project, attempts to demonstrate that Doris Salcedo’s artwork makes visible the victims suffering and mourning and compels the viewers’ sympathy, although its approach is superficial. It does not achieve a complete or complex understanding of the social and historical causes underneath the war and maybe because of that has become a successful commodity for the international arts market. The paper considers, firstly, the influence that Colombian Nuevo Teatro, from the sixties, had on Salcedo’s early political perspective and, secondly, analyzes in detail the first series of her artwork (1992-1998) and how those works address grieving. The focus point of this analysis will be the domestic furniture sculptures, which are the main symbolic element of Salcedo’s oeuvre.

Keywords: Arts and politics, Doris Salcedo, Colombian art, Political Art

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Authors: Antoni Grau, Yolanda Bolea, Alberto Sanfeliu

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Embedding Sustainability in technological curricula has become a crucial factor for educating engineers with competences in sustainability. The Technical University of Catalonia UPC, in 2008, designed the Sustainable Technology Excellence Program STEP 2015 in order to assure a successful Sustainability Embedding. This Program takes advantage of the opportunity that the redesign of all Bachelor and Master Degrees in Spain by 2010 under the European Higher Education Area framework offered. The STEP program goals are: to design compulsory courses in each degree; to develop the conceptual base and identify reference models in sustainability for all specialties at UPC; to create an internal interdisciplinary network of faculty from all the schools; to initiate new transdisciplinary research activities in technology-sustainability-education; to spread the know/how attained; to achieve international scientific excellence in technology-sustainability-education and to graduate the first engineers/architects of the new EHEA bachelors with sustainability as a generic competence. Specifically, in this paper authors explain their experience in leading the STEP program, and two examples are presented: Industrial Robotics subject and the curriculum for the School of Architecture.

Keywords: sustainability, curricula improvement, robotics, STEP program

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Authors: Siddhartha Paul, Aman Harlalka, Ashim K. Dey

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Soft clayey soil possesses poor bearing capacity and high compressibility because of which foundations cannot be directly placed over soft clay. Normally pile foundations are constructed to carry the load through the soft soil up to the hard stratum below. Pile construction is costly and time consuming. In order to increase the properties of soft clay, many ground improvement techniques like stone column, preloading with and without sand drains/band drains, etc. are in vogue. Time is a constraint for successful application of these improvement techniques. Another way to improve the bearing capacity of soft clay and to reduce the settlement possibility is to apply geocells below the foundation. The geocells impart rigidity to the foundation soil, reduce the net load intensity on soil and thus reduce the compressibility. A well designed geocell reinforced soil may replace the pile foundation. The present paper deals with the applicability of geocells on improvement of the bearing capacity. It is observed that a properly designed geocell may increase the bearing capacity of soft clay up to two and a half times.

Keywords: bearing capacity, geo-cell, ground improvement, soft clay

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Authors: Simonida S. Djuric, Timea I. Hajnal Jafari, Dragana R. Stamenov

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The use of plant growth promoting fungi (PGPF) has significantly increased in the last decade mostly due to their multi-level properties, and their expected success as biofertilizers in agriculture. Beneficial fungi with broad-host range undergo long-term interactions with a large variety of plants thereby playing a significant role in managed ecosystems and in the adaptation of crops to global climate changes. Trichoderma spp. are promising fungi toward the development of sustainable agriculture. The aim of our experiment was to investigate the effect of seed inoculation of sunflower, maize, soybean, paprika, melon, and watermelon seeds with Trichoderma sp. on early seed germination energy and initial growth of the plant. The seed inoculation with Trichoderma sp. increased the seedling emergence from 7, 85% in melon to 156,70% in watermelon. The inoculation had the best effect on initial growth of maize shoot (+23,80%) and soybean root (+106,30%). The different response of seed and young plants on Trichoderma sp. inoculation implicate the need for future investigations of successful inoculation systems and modes of their integration in sustainable agriculture production systems.

Keywords: initial growth, inoculation, seedling, Trichoderma sp.

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Authors: S. Md. Shaarani, J. Md. Jahim, R. A. Rahman, R. Md. Illias

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Modern developments in biotechnology have paved the way for extensive use of biocatalysis in industries. Although it offers immense potential, industrial application is usually hampered by lack of operational stability, difficulty in recovery as well as limited re-use of the enzyme. These drawbacks, however, can be overcome by immobilization. Cross-linked enzyme aggregates (CLEAs), a versatile carrier-free immobilization technique is one that is currently capturing global interest. This approach involves precipitating soluble enzyme with an appropriate precipitant and subsequent crosslinking by a crosslinking reagent. Without ineffective carriers, CLEAs offer high enzymatic activity, stability and reduced production cost. This study demonstrated successful CLEA synthesis of recombinant xylanase from Trichoderma reesei using ethanol as aggregating agent and glutaraldehyde (2% (v/v); 100 mM) as crosslinker. Effects of additives including proteic feeder such as bovine serum albumin (BSA) and poly-L-Lysine were investigated to reveal its significance in enhancing the performance of enzyme. Addition of 0.1 mg BSA/U xylanase showed considerable increment in CLEA development with approximately 50% retained activity.

Keywords: cross-linked, immobilization, recombinant, xylanase

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Authors: Faezeh Shalchy

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Concrete is the most used materials in the world. It is also one of the most versatile while complex materials which human have used for construction. However, concrete is weak in tension, over the past thirty years many studies were accomplished to improve the tensile properties of concrete (cement-based materials) using a variety of methods. One of the most successful attempts is to use polymeric fibers in the structure of concrete to obtain a composite with high tensile strength and ductility. Understanding the mechanical behavior of fiber reinforced concrete requires the knowledge of the fiber/matrix interfaces at the small scale. In this study, a combination of numerical simulations and experimental techniques have been used to study the nano structure of fiber/matrix interfaces. A new model for calcium-silicate-hydrate (C-S-H)/fiber interfaces is proposed based on Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX) analysis. The adhesion energy between the C-S-H gel and 2 different polymeric fibers (polyvinyl alcohol and polypropylene) was numerically studied at the atomistic level since adhesion is one of the key factors in the design of fiber reinforced composites. The mechanisms of adhesion as a function of the nano structure of fiber/matrix interfaces are also studied and discussed.

Keywords: fiber-reinforced concrete, adhesion, molecular modeling

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Authors: Claudia Trillo

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Regional innovation eco-ecosystems are composed of a variety of interconnected urban innovation eco-systems, mutually reinforcing each other and making the whole territorial system successful. Combining principles drawn from the new economic growth theory and from the socio-constructivist approach to the economic growth, with the new geography of innovation emerging from the networked nature of innovation districts, this paper explores the spatial configuration of urban innovation districts, with the aim of unveiling replicable spatial patterns and transferable portfolios of urban policies. While some authors suggest that cities should be considered ideal natural clusters, supporting cross-fertilization and innovation thanks to the physical setting they provide to the construction of collective knowledge, still a considerable distance persists between regional development strategies and urban policies. Moreover, while public and private policies supporting entrepreneurship normally consider innovation as the cornerstone of any action aimed at uplifting the competitiveness and economic success of a certain area, a growing body of literature suggests that innovation is non-neutral, hence, it should be constantly assessed against equity and social inclusion. This paper draws from a robust qualitative empirical dataset gathered through 4-years research conducted in Boston to provide readers with an evidence-based set of recommendations drawn from the lessons learned through the investigation of the chosen innovation districts in the Boston area. The evaluative framework used for assessing the overall performance of the chosen case studies stems from the Habitat III Sustainable Development Goals rationale. The concept of inclusive growth has been considered essential to assess the social innovation domain in each of the chosen cases. The key success factors for the development of the Boston innovation ecosystem can be generalized as follows: 1) a quadruple helix model embedded in the physical structure of the two cities (Boston and Cambridge), in which anchor Higher Education (HE) institutions continuously nurture the Entrepreneurial Environment. 2) an entrepreneurial approach emerging from the local governments, eliciting risk-taking and bottom-up civic participation in tackling key issues in the city. 3) a networking structure of some intermediary actors supporting entrepreneurial collaboration, cross-fertilization and co-creation, which collaborate at multiple-scales thus enabling positive spillovers from the stronger to the weaker contexts. 4) awareness of the socio-economic value of the built environment as enabler of cognitive networks allowing activation of the collective intelligence. 5) creation of civic-led spaces enabling grassroot collaboration and cooperation. Evidence shows that there is not a single magic recipe for the successful implementation of place-based and social innovation-driven strategies. On the contrary, the variety of place-grounded combinations of micro and macro initiatives, embedded in the social and spatial fine grain of places and encompassing a diversity of actors, can create the conditions enabling places to thrive and local economic activities to grow in a sustainable way.

Keywords: innovation-driven sustainable Eco-systems , place-based sustainable urban development, sustainable innovation districts, social innovation, urban policie

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: D. I. Yani, S. Isaramalai, C. Kritpracha

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Adherence to health behaviors is essential to achieve successful TB treatment. This study aimed to examine the effect of a family-based DOTS support program on adherence to health behaviors in patients with pulmonary TB. Sixty TB patients and their families were selected using cluster randomization of community health centers. The subjects were assigned into a control group, who received the routine care, and an experimental group, who received both routine care and care from the family-based DOTS support program. Paired t-test and the independent t-test were applied. The total score of adherence to health behaviors in the experimental group was significantly higher after receiving care from the family-based DOTS support program than the pretest score (t = -10.34, p < .001). Suggestions were made to expand the application of this program in various contexts and to extend knowledge for nursing practices and research.

Keywords: self-care deficit nursing theory, family-based DOTS program, pulmonary tuberculosis, adherence, health behaviors

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Authors: Poom Thiparapkul, Tanat Jiravansirikul, Pakpoom Thongsari

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This study explores the design of electric vehicle (EV) dashboards with a focus on user interaction. Findings from a Thai sample reveal a preference for physical buttons over touch interfaces due to their immediate feedback. Touchscreens lack this assurance, leading to potential uncertainty. Users' smartphone experiences create a learning curve that doesn't translate well to in-car touch systems. Gender-wise, females exhibit slightly longer decision times. Designing EV dashboards should consider these factors, prioritizing user experience while avoiding overreliance on smartphone principles. A successful example is Subaru XV's design, which calculates screen angles and button positions for targeted users. In summary, EV dashboards should be intuitive, minimize touch dependency, and accommodate user habits. Balancing modernity with functionality can enhance driving experiences while ensuring safety. A user-centered approach, acknowledging gender differences, will yield efficient and safe driving environments.

Keywords: user experience design, user experience, electric vehicle, dashboard design, Thailand driver.

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Authors: Phumlani Msomi, Patrick Nonjola, Patrick Ndungu, James Ramontja

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A series of quaternized poly (2.6 dimethyl – 1.4 phenylene oxide)/ polysulfone (QPPO/PSF) blend anion exchange membrane (AEM) were successfully fabricated and characterized for methanol alkaline fuel cell application. Zinc Oxide (ZnO) nanoparticles were introduced in the polymer matrix to enhance the intrinsic properties of the AEM. To confirm successful fabrication, FT-IR spectroscopy and nuclear magnetic resonance (¹H NMR and HMBC ¹⁵N NMR) were used. The membrane properties were enhanced by the addition of ZnO nanoparticles. The addition of ZnO nanoparticles resulted to a higher ion exchange capacity (IEC) of 3.72 mmol.g⁻¹and a 30-fold ion conductivity (IC) increase of the nanocomposite due to no (zero (0)) methanol permeability at 30 °C and increased water uptake. The QPPO/PSF/2% ZnO composite retained over 80 % of its initial IC when evaluated for alkaline stability at room temperature. The maximum power output reached for the membrane electrode assembly (MEA) constructed with QPPO/PSF/2%ZnO is 69 mW.cm⁻², which is about three times more than the parent QPPO membrane. The above results indicate that QPPO/PSF-ZnO is a good candidate as an anion exchange membrane for fuel cell application.

Keywords: anion exchange membrane, fuel cell, zinc oxide, nanocomposite

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Authors: Oyugi Ngure Robert, Kallen Mulilo Nalyanya, Tabitha A. Amollo

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Nanomaterials have attracted significant attention in research because of their exemplary properties, making them suitable for diverse applications. This paper reports the successful synthesis as well as the structural properties of silver sulfide/reduced graphene oxide (Ag_2 S-rGO) nanocomposite. The nanocomposite was synthesized by the chemical reduction method. Scanning electron microscopy (SEM) showed that the reduced graphene oxide (rGO) sheets were intercalated within the Ag_2 S nanoparticles during the chemical reduction process. The SEM images also showed that Ag_2 S had the shape of nanowires. Further, SEM energy dispersive X-ray (SEM EDX) showed that Ag_2 S-rGO is mainly composed of C, Ag, O, and S. X-ray diffraction analysis manifested a high crystallinity for the nanowire-shaped Ag2S nanoparticles with a d-spacing ranging between 1.0 Å and 5.2 Å. Thermal gravimetric analysis (TGA) showed that rGO enhances the thermal stability of the nanocomposite. Ag_2 S-rGO nanocomposite exhibited strong optical absorption in the UV region. The formed nanocomposite is dispersible in polar and non-polar solvents, qualifying it for solution-based device processing.

Keywords: silver sulfide, reduced graphene oxide, nanocomposite, structural properties, optical properties

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Authors: A. Wahid Uddin

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Osmotic dilator for cervical ripening bypasses the initial hormonal exposure necessary for a routine method of induction. The study was a clinical intervention with an osmotic dilator followed by prospective observation. The aim was to calculate the percentage of women who had successful cervical ripening using modified BISHOP score as evidenced by artificial rupture of membrane. The study also estimated the delivery interval following a single administration of osmotic dilators. Randomly selected patients booked for induction of labour accepting the intervention were included in the study. The study population comprised singleton term pregnancy, cephalic presentation, intact membranes with a modified BISHOP score of less than 6. Initial sample recruited was 30, but 6 patients left the study and the study was concluded on 24 patients. The data were collected in a pre-designed questionnaire and analysis were expressed in percentages along with using mean value for continuous variables. In 70 % of cases, artificial rupture of the membrane was possible and the mean time from insertion of the osmotic dilator to the delivery interval was 30 hours. The study concluded that an osmotic dilator could be a suitable alternative for hormone-based induction of labour.

Keywords: dilator, induction, labour, osmotic

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Authors: Jesse D. Cano, Marlon J. Remedios

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Cuban tourism has developed so much in the last 30 years to the point of becoming one of the engines of the Cuban economy. With such a development, Cuban companies opting for e-tourism as a way to publicize their products and attract customers has also grown. Despite this fact, the majority of Cuban tourism-themed websites simply provide information on the different products and services they offer which results in many cases, in the user getting overwhelmed with the amount of information available which results in the user abandoning the search before he can find a product that fits his needs. Customization has been recognized as a critical factor for successful electronic tourism business and the use of recommender systems is the best approach to address the problem of personalization. This paper aims to outline a preliminary technique to obtain predictions about which products a particular user would give a better evaluation; these products would be those which the website would show in the first place. To achieve this, the theoretical elements of the Cuban tourism environment are discussed; recommendation systems and geographic information systems as tools for information representation are also discussed. Finally, for each structural component identified, we define a set of rules that allows obtaining an electronic tourism system that handles the personalization of the service provided effectively.

Keywords: geographic information system, technique, tourism products, recommendation

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Authors: Medan Isaeva, Anna Degtyareva

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Context: Biliary atresia is a common reason for liver transplants in children, and the Kasai procedure can potentially be successful in avoiding the need for transplantation. However, it is important to identify factors that influence surgical outcomes in order to optimize treatment and improve patient outcomes. Research aim: The aim of this study was to develop prognostic models to assess the outcomes of the Kasai procedure in children with biliary atresia. Methodology: This retrospective study analyzed data from 166 children with biliary atresia who underwent the Kasai procedure between 2002 and 2021. The effectiveness of the operation was assessed based on specific criteria, including post-operative stool color, jaundice reduction, and bilirubin levels. The study involved a comparative analysis of various parameters, such as gestational age, birth weight, age at operation, physical development, liver and spleen sizes, and laboratory values including bilirubin, ALT, AST, and others, measured pre- and post-operation. Ultrasonographic evaluations were also conducted pre-operation, assessing the hepatobiliary system and related quantitative parameters. The study was carried out by two experienced specialists in pediatric hepatology. Comparative analysis and multifactorial logistic regression were used as the primary statistical methods. Findings: The study identified several statistically significant predictors of a successful Kasai procedure, including the presence of the gallbladder and levels of cholesterol and direct bilirubin post-operation. A detectable gallbladder was associated with a higher probability of surgical success, while elevated post-operative cholesterol and direct bilirubin levels were indicative of a reduced chance of positive outcomes. Theoretical importance: The findings of this study contribute to the optimization of treatment strategies for children with biliary atresia undergoing the Kasai procedure. By identifying early predictive signs of success, clinicians can modify treatment plans and manage patient care more effectively and proactively. Data collection and analysis procedures: Data for this analysis were obtained from the health records of patients who received the Kasai procedure. Comparative analysis and multifactorial logistic regression were employed to analyze the data and identify significant predictors. Question addressed: The study addressed the question of identifying predictive factors for the success of the Kasai procedure in children with biliary atresia. Conclusion: The developed prognostic models serve as valuable tools for early detection of patients who are less likely to benefit from the Kasai procedure. This enables clinicians to modify treatment plans and manage patient care more effectively and proactively. Potential limitations of the study: The study has several limitations. Its retrospective nature may introduce biases and inconsistencies in data collection. Being single centered, the results might not be generalizable to wider populations due to variations in surgical and postoperative practices. Also, other potential influencing factors beyond the clinical, laboratory, and ultrasonographic parameters considered in this study were not explored, which could affect the outcomes of the Kasai operation. Future studies could benefit from including a broader range of factors.

Keywords: biliary atresia, kasai operation, prognostic model, native liver survival

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Authors: Ali Arabkheradmand, Enayat A. Shabani, Shabnam Ranjbar Nikkhoo

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Historical and ancestral bonds of the countries in the Middle East have led to similarities in culture and context of their societies. In addition, economic resources, such as the oil industry, have generally been an integrative point in the region. Higher education of a country is influenced by different national and international factors and regarding the mentioned bonds, it is inviting to study the development of the countries of the Middle East in higher education and draw some practical implications which can be used in the educational policy-making of the region. This review includes a data analysis on the population of international students in the countries of the Middle East. As its second objective, a review study on the successful countries, that is those which host the highest number of international students and the strategies they have developed to reach this state among the countries of the region has been conducted. Suggestions are made as to the strategies in higher education systems of these countries which could prove useful and practical in the development of internationalization of higher education in the region, specifically with regard to the recruitment of international students.

Keywords: internationalization of higher education, international student recruitment, Middle East countries, educational policy making

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Authors: Oualid Kherbach, Marian Liviu Mocan, Amine Ghoumrassi, Cristian Dumitrache

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The Globalization system and the development of economy, e-business, and introduction of new technologies formation create new challenges to all organizations particularly for small and medium enterprises (SMEs). Many studies on supply chain management (SCM) focus on large companies with universal operations employing high-stage information technology. These make a gap in the knowing of how SMEs use and practice supply chain management. In this screenplay, successful practices of supply chain management (SCM) can give SMEs an edge over their competitors. However, SMEs in Romania and Balkan countries face problems in SCM implementation and practices due to lack of resources and direction. The objectives of this research highlight the supply chain management practices of the small and medium enterprise strip in Romania and understand how SMEs manage and use SCM. This study Checks the potential existence of systematic differences between small businesses and medium-sized businesses with regard to supply chain management practices and the application of supply management has contributed to the improvement performance and increase the profitability of companies such as increasing the market share and improving the level of clients.

Keywords: globalization, small and medium enterprises, supply chain management, practices

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: G. Infante Dennis, S. Balinas Elvira, C. Valencia Yolanda, Cunanan

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This paper examined the feed-backs, concerns, and insights of the teachers, supervisors, and teacher-trainers on the nature and qualities of the K-12 grade 8 design, content, approaches, and materials. Specifically, it sought to achieve the following objectives: 1) to describe the critical nature and qualities of the design, content, teaching-learning-and-evaluation approaches, and the materials to be utilized in the implementation of the grade 8 curriculum; 2) to extract the possible challenges relevant to the implementation of the design, content, teaching-learning-and-evaluation approaches, and the materials of the grade 8 curriculum in terms of the linguistic and technical competence of the teachers, readiness to implement, willingness to implement, and capability to make relevant adaptations; 3) to present essential demands on the successful and meaningful implementation of the grade 8 curriculum in terms of teacher-related factors, school-related factors, and student-related concerns.

Keywords: curriculum reforms, K-12, teacher-training, language teaching, learning

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: Camila Penido Gomes

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Over the past decade, an emerging body of research has been pointing to artificial intelligence´s great potential to improve the use of open data, increase transparency and curb corruption in the public sector. Nonetheless, studies on this subject are scant and usually lack evidence to validate AI-based technologies´ effectiveness in addressing corruption, especially in developing countries. Aiming to fill this void in the literature, this paper sets out to examine how AI has been deployed by civil society to improve the use of open data and prevent congresspeople from misusing public resources in Brazil. Building on the current debates and carrying out a systematic literature review and extensive document analyses, this research reveals that AI should not be deployed as one silver bullet to fight corruption. Instead, this technology is more powerful when adopted by a multidisciplinary team as a civic tool in conjunction with other strategies. This study makes considerable contributions, bringing to the forefront discussion a more accurate understanding of the factors that play a decisive role in the successful implementation of AI-based technologies in anti-corruption efforts.

Keywords: artificial intelligence, civil society organization, corruption, open data, transparency

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Authors: Suzanne L. Stewart, Mikaela D. Gabriel

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Background: Indigenous People face multiple barriers to successful life transitions, including housing, employment, education, and health. Current statistical trends paint devastating life transitions for Indigenous Peoples, but colonization and its intergenerational impacts are typically lacking as the crucial context in which these trends occur. This presentation will illustrate the massive impact of colonization on Indigenous Peoples; its intergenerational transmission, and how it impacts Indigenous clients seeking mental health treatment today. Methods: A qualitative, narrative inquiry methodology was used to honour Indigenous storytelling and knowledge transmission. Indigenous Elders, outreach workers, and homeless clients were interviewed and narratively analyzed for in-depth trends and themes. Impact: This research provides a wealth of in-depth information as to the life transition needs of Indigenous clients, identify the systemic impacts of colonization to the health and wellbeing of Indigenous People, and strategies for mental health treatment.

Keywords: indigenous trauma, indigenous peoples of canada, intergenerational trauma, colonial trauma and treatment

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Authors: Natália C. C. Lobato, Ângela M. Ferreira, Marcelo B. Mansur

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In solvent extraction operations, large sedimentation areas in the mixer-settler are required when the disengagement of the aqueous and the organic phases is slow and/or difficult. The use of a magnetic organic liquid (also known as ferrofluid), consisting of magnetite nanoparticles coated by oleic acid dispersed in the organic diluent, has proven successful to speed up phase disengagement. The method, however, has never been used industrially; therefore, the aim of this study is to raise its main limitations. Tests were carried out using a ferrofluid containing 30 g/l of magnetite dissolved in commercial aliphatic kerosene Exxsol D80. The efficiency of cobalt extraction ([Co] = 1 g/l) with 10% v/v Cyanex 272 (bis-2,4,4-trimethylpentyl phosphinic acid) at changing pH of the aqueous phase (2 to 7) was found unaffected in the conditions studied. However, the chemical resistance of the ferrofluid in contact with deionized water at changing acidity (from 10-7 to 2 mol/l) revealed that the nanoparticles are not resistant when contacted to aqueous solutions with a pH ≤ 2. Such result represents a serious limitation to the applicability of the method mainly to hydrometallurgical systems because solvent extraction operations are normally done in acid conditions, therefore more effective strategies to coat the particles are required.

Keywords: magnetic solvent extraction, oleic acid, magnetite nanoparticles, cyanex 272

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Authors: Elysia Barker, Jian Guo Zhou, Ling Qian, Steve Decent

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A method of modelling topography used in the simulation of riverbeds is proposed in this paper, which removes the need for datapoints and measurements of physical terrain. While complex scans of the contours of a surface can be achieved with other methods, this requires specialised tools, which the proposed method overcomes by using fractional Brownian motion (FBM) as a basis to estimate the real surface within a 15% margin of error while attempting to optimise algorithmic efficiency. This removes the need for complex, expensive equipment and reduces resources spent modelling bed topography. This method also accounts for the change in topography over time due to erosion, sediment transport, and other external factors which could affect the topography of the ground by updating its parameters and generating a new bed. The lattice Boltzmann method (LBM) is used to simulate both stationary and steady flow cases in a side-by-side comparison over the generated bed topography using the proposed method and a test case taken from an external source. The method, if successful, will be incorporated into the current LBM program used in the testing phase, which will allow an automatic generation of topography for the given situation in future research, removing the need for bed data to be specified.

Keywords: bed topography, FBM, LBM, shallow water, simulations

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Isaac Kofi Mensah, Mi Jianing

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The lack of Information and Communication Technologies (ICT) infrastructure in African countries is hampering the successful adoption, development and implementation of e-government in Africa. Electronic government is the use of ICTs to modernize government public administration processes and to provide government services to citizens with a purpose to enhance efficiency, accountability, and transparency in government’s interaction with the citizenry. ICT application in public administration has the potential to modernize and create smarter government and improvement in public service delivery. China’s Internet Plus policy and One Belt One Road strategy present a golden opportunity for countries in Africa to attract the huge financial investment through Chinese IT companies to develop and close Africa’s ICT infrastructure gap. This study recommends the establishment of One Belt One Road ICT Infrastructure Fund for Africa (OBOR ICT Fund for Africa) to enable countries in Africa to source solely for the purpose of ICT infrastructure development in the public sector/government machinery which would in turn promote the adoption and development of e-government in the public sectors of respective countries in Africa.

Keywords: e-government, public service delivery, internet plus, one belt one road initiative, China, Africa

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Authors: S. Gordon

Abstract:

Dual language immersion is growing fast in language teaching today. This study provides an overview and evaluation of the different models of Dual language immersion programs in US K-12 schools. First, the paper provides a brief current literature review on the theory of Dual Language Immersion (DLI) in Second Language Acquisition (SLA) studies. Second, examples of several types of DLI language teaching models in US K-12 public schools are presented (including 50/50 models, 90/10 models, etc.). Third, we focus on the unique example of DLI education in the state of Utah, a successful, growing program in K-12 schools that includes: French, Chinese, Spanish, and Portuguese. The project investigates the theory and practice particularly of the case of public elementary and secondary school children that study half their school day in the L1 and the other half in the chosen L2, from kindergarten (age 5-6) through high school (age 17-18). Finally, the project takes the observations of Utah French DLI elementary through secondary programs as a case study. To conclude, we look at the principal challenges, pedagogical objectives and outcomes, and important implications for other US states and other countries (such as France currently) that are in the process of developing similar language learning programs.

Keywords: dual language immersion, second language acquisition, language teaching, pedagogy, teaching, French

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Authors: Albert Bou, Sebastian Dittert, Gianni de Fabritiis

Abstract:

Advancing reinforcement learning (RL) requires tools that are flexible enough to easily prototype new methods while avoiding impractically slow experimental turnaround times. To match the first requirement, the most popular RL libraries advocate for highly modular agent composability, which facilitates experimentation and development. To solve challenging environments within reasonable time frames, scaling RL to large sampling and computing resources has proved a successful strategy. However, this capability has been so far difficult to combine with modularity. In this work, we explore design choices to allow agent composability both at a local and distributed level of execution. We propose a versatile approach that allows the definition of RL agents at different scales through independent, reusable components. We demonstrate experimentally that our design choices allow us to reproduce classical benchmarks, explore multiple distributed architectures, and solve novel and complex environments while giving full control to the user in the agent definition and training scheme definition. We believe this work can provide useful insights to the next generation of RL libraries.

Keywords: deep reinforcement learning, Python, PyTorch, distributed training, modularity, library

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Authors: Muhammad Bilal, Adil Ahmed

Abstract:

This study proposes an approach for electrical induction motor predictive maintenance utilizing machine learning algorithms. On the basis of a study of temperature data obtained from sensors put on the motor, the goal is to predict motor failures. The proposed models are trained to identify whether a motor is defective or not by utilizing machine learning algorithms like Support Vector Machines (SVM) and K-Nearest Neighbors (KNN). According to a thorough study of the literature, earlier research has used motor current signature analysis (MCSA) and vibration data to forecast motor failures. The temperature signal methodology, which has clear advantages over the conventional MCSA and vibration analysis methods in terms of cost-effectiveness, is the main subject of this research. The acquired results emphasize the applicability and effectiveness of the temperature-based predictive maintenance strategy by demonstrating the successful categorization of defective motors using the suggested machine learning models.

Keywords: predictive maintenance, electrical induction motors, machine learning, temperature signal methodology, motor failures

Procedia PDF Downloads 119