Search results for: algorithm integration

Authors: Carolinda Douglass

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Institutional Effectiveness (IE) is the purposeful integration of functions that foster student success and support institutional performance. IE is growing rapidly within higher education as it is increasingly viewed by higher education administrators as a beneficial approach for promoting data-informed decision-making in campus-wide strategic planning and execution of strategic initiatives. Specific IE tools, including, but not limited to, project management; impactful collaboration and communication; commitment to continuous quality improvement; and accountability through rigorous evaluation; are gaining momentum under the auspices of IE. This research utilizes a case study approach to examine the use of these IE tools, highlight successes of this use, and identify areas for improvement in the implementation of IE tools within higher education. The research includes three case studies: (1) improving upon academic program review processes including the assessment of student learning outcomes as a core component of program quality; (2) revising an institutional vision, mission, and core values; and (3) successfully navigating an institution-wide re-accreditation process. Several methods of data collection are embedded within the case studies, including surveys, focus groups, interviews, and document analyses. Subjects of these methods include higher education administrators, faculty, and staff. Key findings from the research include areas of success and areas for improvement in the use of IE tools associated with specific case studies as well as aggregated results across case studies. For example, the use of case management proved useful in all of the case studies, while rigorous evaluation did not uniformly provide the value-added that was expected by higher education decision-makers. The use of multiple IE tools was shown to be consistently useful in decision-making when applied with appropriate awareness of and sensitivity to core institutional culture (for example, institutional mission, local environments and communities, disciplinary distinctions, and labor relations). As IE gains a stronger foothold in higher education, leaders in higher education can make judicious use of IE tools to promote better decision-making and secure improved outcomes of strategic planning and the execution of strategic initiatives.

Keywords: accreditation, data-informed decision-making, higher education management, institutional effectiveness tools, institutional mission, program review, strategic planning

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Authors: Merertu Wakuma Rundassa

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Global competition and rapidly changing customer requirements are forcing major changes in the production styles and configuration of manufacturing organizations. Increasingly, traditional centralized and sequential manufacturing planning, scheduling, and control mechanisms are being found insufficiently flexible to respond to changing production styles and highly dynamic variations in product requirements. The traditional approaches limit the expandability and reconfiguration capabilities of the manufacturing systems. Thus many business houses face increasing pressure to lower production cost, improve production quality and increase responsiveness to customers. In a textile and apparel manufacturing, globalization has led to increase in competition and quality awareness and these industries have changed tremendously in the last few years. So, to sustain competitive advantage, companies must re-examine and fine-tune their business processes to deliver high quality goods at very low costs and it has become very important for the textile and apparel industries to integrate themselves with information technology to survive. IT can create competitive advantages for companies to improve coordination and communication among trading partners, increase the availability of information for intermediaries and customers and provide added value at various stages along the entire chain. Ethiopia is in the process of realizing its potential as the future sourcing location for the global textile and garments industry. With a population of over 90 million people and the fastest growing non-oil economy in Africa, Ethiopia today represents limitless opportunities for international investors. For the textile and garments industry Ethiopia promises a low cost production location with natural resources such as cotton to enable the setup of vertically integrated textile and garment operation. However; due to lack of integration of their business activities textile and apparel industry of Ethiopia faced a problem in that it can‘t be competent in the global market. On the other hand the textile and apparel industries of other countries have changed tremendously in the last few years and globalization has led to increase in competition and quality awareness. So the aim of this paper is to study the trend of Ethiopian Textile and Apparel Industry on the application of different IT system to integrate them in the global market.

Keywords: information technology, business integrity, textile and apparel industries, Ethiopia

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Authors: Kyere Francis, Sun Dongying, Asante Dennis, Nkrumah Nana Kwame Edmund, Naana Yaa Gyamea Kumah

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With a focus on renewable energy to achieve low-carbon transition objectives, there is a greater demand for effective collaborative strategies for planning, strategic decision mechanisms, and long-term policy designs to steer the transitions. Government agencies, NGOs, the private sector, and individual citizens play an important role in sustainable energy production. In Ghana, however, such collaboration is fragile in the fight against climate change. This current study seeks to re-examine the position or potential of network governance in Ghana's renewable energy transition. The study adopted a qualitative approach and employed semi-structured interviews for data gathering. To explore network governance and low carbon transitions in Ghana, we examine key themes such as political environment and impact, actor cooperation and stakeholder interactions, financing and the transition, market design and renewable energy integration, existing regulation and policy gaps for renewable energy transition, clean cooking accessibility, and affordability. The findings reveal the following; Lack of comprehensive consultations with relevant stakeholders leads to lower acceptance of the policy model and sometimes lack of policy awareness. Again, the unavailability and affordability of renewable energy technologies and access to credit facilities is a significant hurdle to long-term renewable transition. Ghana's renewable energy transitions require strong networking and interaction among the public, private, and non-governmental organizations. The study participants believe that the involvement of relevant energy experts and stakeholders devoid of any political biases is instrumental in accelerating renewable energy transitions, as emphasized in the proposed framework. The study recommends that the national renewable energy transition plan be evident to all stakeholders and political administrators. Such policy may encourage renewable energy investment through stable and fixed lending rates by the financial institutions and build a network with international organizations and corporations. These findings could serve as valuable information for the transition-based energy process, primarily aiming to govern sustainability changes through network governance.

Keywords: actors, development, sustainable energy, network governance, renewable energy transition

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Authors: Zhen Cao, Yu Zhu, Junxue Fu

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Immunoassay, i.e., antigen-antibody reaction, is crucial for disease diagnostics. To achieve the adequate signal of the antigen protein detection, a large amount of sample and long incubation time is needed. However, the amount of protein is usually small at the early stage, which makes it difficult to detect. Unlike cells and DNAs, no valid chemical method exists for protein amplification. Thus, an alternative way to improve the signal is through particle manipulation techniques to concentrate proteins, among which dielectrophoresis (DEP) is an effective one. DEP is a technique that concentrates particles to the designated region through a force created by the gradient in a non-uniform electric field. Since DEP force is proportional to the cube of particle size and square of electric field gradient, it is relatively easy to capture larger particles such as cells. For smaller ones like proteins, a super high gradient is then required. In this work, three-dimensional Ag/SiO2 nanorods arrays, fabricated by an easy physical vapor deposition technique called as oblique angle deposition, have been integrated with a DEP device and created the field gradient as high as of 2.6×10²⁴ V²/m³. The nanorods based DEP device is able to enrich bovine serum albumin (BSA) protein by 1800-fold and the rate has reached 180-fold/s when only applying 5 V electric potential. Based on the above nanorods integrated DEP platform, an immunoassay of mouse immunoglobulin G (IgG) proteins has been performed. Briefly, specific antibodies are immobilized onto nanorods, then IgG proteins are concentrated and captured, and finally, the signal from fluorescence-labelled antibodies are detected. The limit of detection (LoD) is measured as 275.3 fg/mL (~1.8 fM), which is a 20,000-fold enhancement compared with identical assays performed on blank glass plates. Further, prostate-specific antigen (PSA), which is a cancer biomarker for diagnosis of prostate cancer after radical prostatectomy, is also quantified with a LoD as low as 2.6 pg/mL. The time to signal saturation has been significantly reduced to one minute. In summary, together with an easy nanorod fabrication and integration method, this nanorods based DEP platform has demonstrated highly sensitive immunoassay performance and thus poses great potentials in applications for early point-of-care diagnostics.

Keywords: dielectrophoresis, immunoassay, oblique angle deposition, protein concentration

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Authors: Leena Inamdar, David Allen, Sushma Acquilla, James Gore

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Health systems globally are facing increasingly complex challenges. Emerging health threats, changing population demographics and increasing health inequalities, globalisation, economic constraints on government spending are some of the most critical ones. These challenges demand not only innovative funding and cross-sectoral approaches, but also require a multidisciplinary public health workforce equipped with skills and expertise to meet the future challenges of the Sustainable Development Goals (SDGs). We aim to outline an approach to assessing the feasibility of establishing a competency-based public health training at a country level. Although the SDGs provide an enabling impetus for change and promote positive developments, public health training and education still lag behind. Large gaps are apparent in both the numbers of trained professionals and the options for high quality training. Public health training in most Low-Middle Income Countries is still largely characterized by a traditional and limited public health focus. There is a pressing need to review and develop core and emerging competences for a well-equipped workforce fit for the future. This includes the important role of national Health and Human Resource Ministries in determining these competences. Public health has long been recognised as a multidisciplinary field, with need for professionals from a wider range of disciplines such as management, health promotion, health economics, law. Leadership and communication skills are also critical to achieve the successes in meeting public health outcomes. Such skills and competences need to be translated into competency-based training and education, to prepare current public health professionals with the skills required in today’s competitive job market. Integration of academic and service based public-health training, flexible accredited programmes to support existing mid-career professionals, continuous professional development need to be explored. In the current global climate of austerity and increasing demands on health systems, the need for stepping up public health training and education is more important than ever. By using a case study, we demonstrate the process of assessing the in-county capacity to establish a competency based public health training programme that will help to develop a stronger, more versatile and much needed public health workforce to meet the SDGs.

Keywords: public health training, competency-based, assessment, SDGs

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Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

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Authors: Alireza Jalalvand, Maryam Saleh, Somayeh Behjat Khatouni, Zahra Bahri Najafi, Foroozan Fatahinia, Narges Ismailzadeh, Behrokh Farahmand

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Object: In the last two decades, the recent outbreak of Coronavirus (SARS-CoV-2) imposed a global pandemic in the world. Despite the increasing prevalence of the disease, there are no effective drugs to treat it. A suitable and rapid way to afford an effective drug and treat the global pandemic is a computational drug study. This study used molecular docking methods to examine the potential inhibition of over 50 antiviral drugs against three fundamental proteins of SARS-CoV-2. METHODS: Through a literature review, three important proteins (a key protease, RNA-dependent RNA polymerase (RdRp), and spike) were selected as drug targets. Three-dimensional (3D) structures of protease, spike, and RdRP proteins were obtained from the Protein Data Bank. Protein had minimal energy. Over 50 antiviral drugs were considered candidates for protein inhibition and their 3D structures were obtained from drug banks. The Autodock 4.2 software was used to define the molecular docking settings and run the algorithm. RESULTS: Five drugs, including indinavir, lopinavir, saquinavir, nelfinavir, and remdesivir, exhibited the highest inhibitory potency against all three proteins based on the binding energies and drug binding positions deduced from docking and hydrogen-bonding analysis. Conclusions: According to the results, among the drugs mentioned, saquinavir and lopinavir showed the highest inhibitory potency against all three proteins compared to other drugs. It may enter laboratory phase studies as a dual-drug treatment to inhibit SARS-CoV-2.

Keywords: covid-19, drug repositioning, molecular docking, lopinavir, saquinavir

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Authors: Jin Woo Hwang, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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As greenhouse effect has been recognized as serious environmental problem of the world, interests in carbon dioxide (CO₂) emission which comprises major part of greenhouse gas (GHG) emissions have been increased recently. Since construction industry takes a relatively large portion of total CO₂ emissions of the world, extensive studies about reducing CO₂ emissions in construction and operation of building have been carried out after the 2000s. Also, performance based design (PBD) methodology based on nonlinear analysis has been robustly developed after Northridge Earthquake in 1994 to assure and assess seismic performance of building more exactly because structural engineers recognized that prescriptive code based design approach cannot address inelastic earthquake responses directly and assure performance of building exactly. Although CO₂ emissions and PBD approach are recent rising issues on construction industry and structural engineering, there were few or no researches considering these two issues simultaneously. Thus, the objective of this study is to minimize the CO₂ emissions and cost of building designed by PBD approach in structural design stage considering structural materials. 4 story and 4 span reinforced concrete building optimally designed to minimize CO₂ emissions and cost of building and to satisfy specific seismic performance (collapse prevention in maximum considered earthquake) of building satisfying prescriptive code regulations using non-dominated sorting genetic algorithm-II (NSGA-II). Optimized design result showed that minimized CO₂ emissions and cost of building were acquired satisfying specific seismic performance. Therefore, the methodology proposed in this paper can be used to reduce both CO₂ emissions and cost of building designed by PBD approach.

Keywords: CO2 emissions, performance based design, optimization, sustainable design

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Authors: Carolina S. Correia, Thalita V. Thomé, Andersen Boniolo, Dhayana I. Veiga

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Evidence-based practices (EBP) in education is a set of principles and practices used to raise educational policy, it involves the integration of professional expertise in education with the best empirical evidence in making decisions about how to deliver instruction. The purpose of this presentation is to describe and characterize studies about EBP in education in elementary classroom setting. Data here presented is part of an ongoing systematic review research. Articles were searched and selected from four academic databases: ProQuest, Scielo, Science Direct and Capes. The search terms were evidence-based practices or program effectiveness, and education or teaching or teaching practices or teaching methods. Articles were included according to the following criteria: The studies were explicitly described as evidence-based or discussed the most effective practices in education, they discussed teaching practices in classroom context in elementary school level. Document excerpts were extracted and recorded in Excel, organized by reference, descriptors, abstract, purpose, setting, participants, type of teaching practice, study design and main results. The total amount of articles selected were 1.185, 569 articles from Proquest Research Library; 216 from CAPES; 251 from ScienceDirect and 149 from Scielo Library. The potentially relevant references were 178, from which duplicates were removed. The final number of articles analyzed was 140. From 140 articles, are 47 theoretical studies and 93 empirical articles. The following research design methods were identified: longitudinal intervention study, cluster-randomized trial, meta-analysis and pretest-posttest studies. From 140 articles, 103 studies were about regular school teaching and 37 were on special education teaching practices. In several studies, used as teaching method: active learning, content acquisition podcast (CAP), precision teaching (PT), mediated reading practice, speech therapist programs and peer-assisted learning strategies (PALS). The countries of origin of the studies were United States of America, United Kingdom, Panama, Sweden, Scotland, South Korea, Argentina, Chile, New Zealand and Brunei. The present study in is an ongoing project, so some representative findings will be discussed, providing further acknowledgment on the best teaching practices in elementary classroom setting.

Keywords: best practices, children, evidence-based education, elementary school, teaching methods

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Authors: Anne Marie Morrin

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This paper will focus on the design, delivery and assessment of a transdisciplinary STEAM (Science, Technology, Engineering, Arts, and Mathematics) education initiative in a college of education in Ireland. The project explores a transdisciplinary approach to supporting STEAM education where the concepts, methodologies and assessments employed derive from visual art sessions within initial teacher education. The research will demonstrate that the STEAM Education approach is effective when visual art concepts and methods are placed at the core of the teaching and learning experience. Within this study, emphasis is placed on authentic collaboration and transdisciplinary pedagogical approaches with the STEAM subjects. The partners included a combination of teaching expertise in STEM and Visual Arts education, artists, in-service and pre-service teachers and children. The inclusion of all stakeholders mentioned moves towards a more authentic approach where transdisciplinary practice is at the core of the teaching and learning. Qualitative data was collected using a combination of questionnaires (focused and open-ended questions) and focus groups. In addition, the data was collected through video diaries where students reflected on their visual journals and transdisciplinary practice, which gave rich insight into participants' experiences and opinions on their learning. It was found that an effective program of STEAM education integration was informed by co-teaching (continuous professional development), which involved a commitment to adaptable and flexible approaches to teaching, learning, and assessment, as well as the importance of continuous reflection-in-action by all participants. The delivery of a transdisciplinary model of STEAM education was devised to reconceptualizatise how individual subject areas can develop essential skills and tackle critical issues (such as self-care and climate change) through data visualisation and technology. The success of the project can be attributed to the collaboration, which was inclusive, flexible and a willingness between various stakeholders to be involved in the design and implementation of the project from conception to completion. The case study approach taken is particularistic (focusing on the STEAM-ED project), descriptive (providing in-depth descriptions from varied and multiple perspectives), and heuristic (interpreting the participants’ experiences and what meaning they attributed to their experiences).

Keywords: collaboration, transdisciplinary, STEAM, visual arts education

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Authors: Anne Lemnitzer, Eric Tavarez

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The academic rigor of the geotechnical engineering curriculum indicates strong institutional and geographical variations. Geotechnical engineering deals with the most challenging civil engineering material, as opposed to structural engineering, environmental studies, transportation engineering, and water resources. Yet, technical expectations posed by the practicing professional community do not necessarily consider the challenges inherent to the disparity in academic rigor and disciplinary differences. To recognize the skill shortages among current graduates as well as identify opportunities to better equip graduate students in specific fields of geotechnical engineering, a two-part survey was developed in collaboration with the Earth Retaining Structures (ERS) Committee of the American Society of Civil Engineers. Earth Retaining Structures are critical components of infrastructure systems and integral components to many major engineering projects. Within the geotechnical curriculum, Earth Retaining Structures is either taught as a separate course or major subject within a foundation design class. Part 1 of the survey investigated the breadth and depth of the curriculum with respect to ERS by requesting faculty across the United States to provide data on their curricular content, integration of practice-oriented course content, student preparation for professional licensing, and level of technical competency expected upon student graduation. Part 2 of the survey enables a comparison of training provided versus training needed. This second survey addressed practicing geotechnical engineers in all sectors of the profession (e.g., private engineering consulting, governmental agencies, contractors, suppliers/manufacturers) and collected data on the expectations with respect to technical and non-technical skills of engineering graduates entering the professional workforce. Results identified skill shortages in soft skills, critical thinking, analytical and language skills, familiarity with design codes and standards, and communication with various stakeholders. The data will be used to develop educational tools to advance the proficiency and expertise of geotechnical engineering students to meet and exceed the expectations of the profession and to stimulate a lifelong interest in advancing the field of geotechnical engineering.

Keywords: geotechnical engineering, academic training, industry requirements, earth retaining structures

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Authors: Christine Demaecker

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Many researchers have underlined the importance of metaphors in specialised language. Their use of specific domains helps us understand the conceptualisations used to communicate new ideas or difficult topics. Within the wide area of specialised discourse, wine tasting is a very specific example because it is almost exclusively metaphoric. Wine tasting metaphors express various conceptualisations. They are not linguistic but rather conceptual, as defined by Lakoff & Johnson. They correspond to the linguistic expression of a mental projection from a well-known or more concrete source domain onto the target domain, which is the taste of wine. But unlike most specialised terminologies, the vocabulary is never clearly defined. When metaphorical terms are listed in dictionaries, their definitions remain vague, unclear, and circular. They cannot be replaced by literal linguistic expressions. This makes it impossible to transfer them into another language with the traditional linguistic translation methods. Qualitative research investigates whether wine tasting metaphors could rather be translated with the cognitive translation process, as well described by Nili Mandelblit (1995). The research is based on a corpus compiled from two high-profile wine guides; the Parker’s Wine Buyer’s Guide and its translation into French and the Guide Hachette des Vins and its translation into English. In this small corpus with a total of 68,826 words, 170 metaphoric expressions have been identified in the original English text and 180 in the original French text. They have been selected with the MIPVU Metaphor Identification Procedure developed at the Vrije Universiteit Amsterdam. The selection demonstrates that both languages use the same set of conceptualisations, which are often combined in wine tasting notes, creating conceptual integrations or blends. The comparison of expressions in the source and target texts also demonstrates the use of the cognitive translation approach. In accordance with the principle of relevance, the translation always uses target language conceptualisations, but compared to the original, the highlighting of the projection is often different. Also, when original metaphors are complex with a combination of conceptualisations, at least one element of the original metaphor underlies the target expression. This approach perfectly integrates into Lederer’s interpretative model of translation (2006). In this triangular model, the transfer of conceptualisation could be included at the level of ‘deverbalisation/reverbalisation’, the crucial stage of the model, where the extraction of meaning combines with the encyclopedic background to generate the target text.

Keywords: cognitive translation, conceptual integration, conceptual metaphor, interpretative model of translation, wine tasting metaphor

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

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Authors: Mohanad Hammad

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Port institutions serve as a link connecting the land areas that receive the goods and the areas from where ships sail. These areas hold great significance for the conversion of goods into commodities of economic value, capable of meeting the needs of the society. Development of ports constitutes a fundamental component of the comprehensive economic development process. Recognizing this fact, developing countries have always resorted to this infrastructural element to resolve the numerous problems they face, taking into account its contribution to the reformation of their economic conditions. Iraqi ports have played a major role in boosting the commercial movement in Iraq, as they are the starting point of its oil exports and a key constituent in fulfilling the consumer and production needs of the various economic sectors of Iraq. With the Gulf wars and the economic blockade, Iraqi ports have continued to deteriorate and become unable to perform their functions as first-generation ports, prompting Iraq to use the ports of neighboring countries such as Jordan's Aqaba commercial port. Meanwhile, Iraqi ports face strong competition from the ports of neighboring countries, which have achieved progress and advancement as opposed to the declining performance and efficiency of Iraqi ports. The great developments in the economic conditions of Iraq lay a too great burden on the Iraqi maritime transport and ports, which require development in order to be able to meet the challenges arising from the fierce international and regional competition in the markets. Therefore, it is necessary to find appropriate solutions in support of the role that can be played by Iraqi ports in serving Iraq's foreign trade transported by sea and in keeping up with the development of foreign trade. Thus, this research aims at tackling the current situation of the Iraqi ports and their commercial activity and studying the problems and obstacles they face. The research also studies the future prospects of these ports, the potentials of maritime openness to Iraq under the fierce competition of neighboring ports, and the possibility of enhancing Iraqi ports’ competitiveness. Among the results produced by this research is the future scenario it proposes for Iraqi ports, mainly represented in the establishment of Al-Faw Port, which will contribute to a greater openness of maritime transport in Iraq, and the rehabilitation and expansion of existing ports. This research seeks to develop solutions to Iraq ports so that they can be repositioned as a vital means of promoting economic development.

Keywords: maritime transport, port, future prospects, regional integration

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Authors: W. Hamaidia, T. Zebbiche

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This paper presents the design of axisymmetric supersonic nozzles, in order to accelerate a supersonic flow to the desired Mach number and that having a small weight, in the same time gives a high thrust. The concerned nozzle gives a parallel and uniform flow at the exit section. The nozzle is divided into subsonic and supersonic regions. The supersonic portion is independent to the upstream conditions of the sonic line. The subsonic portion is used to give a sonic flow at the throat. In this case, nozzle gives a uniform and parallel flow at the exit section. It’s named by minimum length Nozzle. The study is done at high temperature, lower than the dissociation threshold of the molecules, in order to improve the aerodynamic performances. Our aim consists of improving the performances both by the increase of exit Mach number and the thrust coefficient and by reduction of the nozzle's mass. The variation of the specific heats with the temperature is considered. The design is made by the Method of Characteristics. The finite differences method with predictor-corrector algorithm is used to make the numerical resolution of the obtained nonlinear algebraic equations. The application is for air. All the obtained results depend on three parameters which are exit Mach number, the stagnation temperature, the chosen mesh in characteristics. A numerical simulation of nozzle through Computational Fluid Dynamics-FASTRAN was done to determine and to confirm the necessary design parameters.

Keywords: flux supersonic flow, axisymmetric minimum length nozzle, high temperature, method of characteristics, calorically imperfect gas, finite difference method, trust coefficient, mass of the nozzle, specific heat at constant pressure, air, error

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Authors: J. S. Saini, P. P. K. Sandhu

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The multi-hop nature of Wireless Mesh Networks and the hasty progression of throughput demands results in multi- channels and multi-radios structures in mesh networks, but the main problem of co-channels interference reduces the total throughput, specifically in multi-hop networks. Quality of Service mentions a vast collection of networking technologies and techniques that guarantee the ability of a network to make available desired services with predictable results. Quality of Service (QoS) can be directed at a network interface, towards a specific server or router's performance, or in specific applications. Due to interference among various transmissions, the QoS routing in multi-hop wireless networks is formidable task. In case of multi-channel wireless network, since two transmissions using the same channel may interfere with each other. This paper has considered the Destination Sequenced Distance Vector (DSDV) routing protocol to locate the secure and optimised path. The proposed technique also utilizes the Lempel–Ziv–Welch (LZW) based lossless data compression and intra cluster data aggregation to enhance the communication between the source and the destination. The use of clustering has the ability to aggregate the multiple packets and locates a single route using the clusters to improve the intra cluster data aggregation. The use of the LZW based lossless data compression has ability to reduce the data packet size and hence it will consume less energy, thus increasing the network QoS. The MATLAB tool has been used to evaluate the effectiveness of the projected technique. The comparative analysis has shown that the proposed technique outperforms over the existing techniques.

Keywords: WMNS, QOS, flooding, collision avoidance, LZW, congestion control

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Authors: Hoda Rahmani, Gary Weckman

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The body of research examining the integration of drones into various industries is expanding rapidly. Despite progress made in addressing the cybersecurity concerns for commercial drones, knowledge deficits remain in determining potential occupational hazards and risks of drone use to employees’ well-being and health in the workplace. This creates difficulty in identifying key approaches to risk mitigation strategies and thus reflects the need for raising awareness among employers, safety professionals, and policymakers about workplace drone-related accidents. The purpose of this study is to investigate the prevalence of and possible risk factors for drone-related mishaps by comparing the application of drones in construction with manufacturing industries. The chief reason for considering these specific sectors is to ascertain whether there exists any significant difference between indoor and outdoor flights since most construction sites use drones outside and vice versa. Therefore, the current research seeks to examine the causes and patterns of workplace drone-related mishaps and suggest possible ergonomic interventions through data collection. Potential ergonomic practices to mitigate hazards associated with flying drones could include providing operators with professional pieces of training, conducting a risk analysis, and promoting the use of personal protective equipment. For the purpose of data analysis, two data mining techniques, the random forest and association rule mining algorithms, will be performed to find meaningful associations and trends in data as well as influential features that have an impact on the occurrence of drone-related accidents in construction and manufacturing sectors. In addition, Spearman’s correlation and chi-square tests will be used to measure the possible correlation between different variables. Indeed, by recognizing risks and hazards, occupational safety stakeholders will be able to pursue data-driven and evidence-based policy change with the aim of reducing drone mishaps, increasing productivity, creating a safer work environment, and extending human performance in safe and fulfilling ways. This research study was supported by the National Institute for Occupational Safety and Health through the Pilot Research Project Training Program of the University of Cincinnati Education and Research Center Grant #T42OH008432.

Keywords: commercial drones, ergonomic interventions, occupational safety, pattern recognition

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Authors: Jonghoon Chun, Insung Kim, Jonghyun Lim, Gun Ro

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We believe that it is possible to provide a solution to reduce patient safety accidents by displaying correct medical records and prescription information through interactive patient identification. Our system is based on the use of smart bands worn by patients and these bands communicate with the hybrid gateways which understand both BLE and Wifi communication protocols. Through the convergence of low-power Bluetooth (BLE) and hybrid gateway technology, which is one of short-range wireless communication technologies, we implement ‘Intelligent Patient Identification and Location Tracking System’ to prevent medical malfunction frequently occurring in medical institutions. Based on big data and IOT technology using MongoDB, smart band (BLE, NFC function) and hybrid gateway, we develop a system to enable two-way communication between medical staff and hospitalized patients as well as to store locational information of the patients in minutes. Based on the precise information provided using big data systems, such as location tracking and movement of in-hospital patients wearing smart bands, our findings include the fact that a patient-specific location tracking algorithm can more efficiently operate HIS (Hospital Information System) and other related systems. Through the system, we can always correctly identify patients using identification tags. In addition, the system automatically determines whether the patient is a scheduled for medical service by the system in use at the medical institution, and displays the appropriateness of the medical treatment and the medical information (medical record and prescription information) on the screen and voice. This work was supported in part by the Korea Technology and Information Promotion Agency for SMEs (TIPA) grant funded by the Korean Small and Medium Business Administration (No. S2410390).

Keywords: BLE, hybrid gateway, patient identification, IoT, safety management, smart band

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Authors: Ayomide A Sijuade, Nafiza Anjum

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The rising demand to meet the need for clean and sustainable energy solutions has led the market to create effective energy storage technologies. In this study, we look at the possibility of using a heterostructure made of polyaniline (PANI), titanium carbide (Ti₃C₂), and vanadium carbide (V₂C) for energy storage devices. V₂C is a two-dimensional transition metal carbide with remarkable mechanical and electrical conductivity. Ti₃C2 has solid thermal conductivity and mechanical strength. PANI, on the other hand, is a conducting polymer with customizable electrical characteristics and environmental stability. Layer-by-layer assembly creates the heterostructure of V₂C, Ti₃C₂, and PANI, allowing for precise film thickness and interface quality control. Structural and morphological characterization is carried out using X-ray diffraction, scanning electron microscopy, and atomic force microscopy. For energy storage applications, the heterostructure’s electrochemical performance is assessed. Electrochemical experiments, such as cyclic voltammetry and galvanostatic charge-discharge tests, examine the heterostructure’s charge storage capacity, cycle stability, and rate performance. Comparing the heterostructure to the individual components reveals better energy storage capabilities. V₂C, Ti₃C₂, and PANI synergize to increase specific capacitance, boost charge storage, and prolong cycling stability. The heterostructure’s unique arrangement of 2D materials and conducting polymers promotes effective ion diffusion and charge transfer processes, improving the effectiveness of energy storage. The heterostructure also exhibits remarkable electrochemical stability, which minimizes capacity loss after repeated cycling. The longevity and long-term dependability of energy storage systems depend on this quality. By examining the potential of V₂C, Ti₃C₂, and PANI heterostructures, the results of this study expand energy storage technology. These materials’ specialized integration and design show potential for use in hybrid energy storage systems, lithium-ion batteries, and supercapacitors. Overall, the development of high-performance energy storage devices utilizing V₂C, Ti₃C₂, and PANI heterostructures is clarified by this research, opening the door to the realization of effective, long-lasting, and eco-friendly energy storage solutions to satisfy the demands of the modern world.

Keywords: MXenes, energy storage materials, conductive polymers, composites

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Authors: Martin Kittel, Alexander Roth

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The continuous integration of variable renewable energy sources (VRE) in the power sector is required for decarbonizing the European economy. Power sectors become increasingly exposed to weather variability, as the availability of VRE, i.e., mainly wind and solar photovoltaic, is not persistent. Extreme events, e.g., long-lasting periods of scarce VRE availability (‘VRE droughts’), challenge the reliability of supply. Properly accounting for the severity of VRE droughts is crucial for designing a resilient renewable European power sector. Energy system modeling is used to identify such a design. Our analysis reveals the sensitivity of the optimal design of the European power sector towards VRE droughts. We analyze how VRE droughts impact optimal power sector investments, especially in generation and flexibility capacity. We draw upon work that systematically identifies VRE drought patterns in Europe in terms of frequency, duration, and seasonality, as well as the cross-regional and cross-technological correlation of most extreme drought periods. Based on their analysis, the authors provide a selection of relevant historical weather years representing different grades of VRE drought severity. These weather years will serve as input for the capacity expansion model for the European power sector used in this analysis (DIETER). We additionally conduct robustness checks varying policy-relevant assumptions on capacity expansion limits, interconnections, and level of sector coupling. Preliminary results illustrate how an imprudent selection of weather years may cause underestimating the severity of VRE droughts, flawing modeling insights concerning the need for flexibility. Sub-optimal European power sector designs vulnerable to extreme weather can result. Using relevant weather years that appropriately represent extreme weather events, our analysis identifies a resilient design of the European power sector. Although the scope of this work is limited to the European power sector, we are confident that our insights apply to other regions of the world with similar weather patterns. Many energy system studies still rely on one or a limited number of sometimes arbitrarily chosen weather years. We argue that the deliberate selection of relevant weather years is imperative for robust modeling results.

Keywords: energy systems, numerical optimization, variable renewable energy sources, energy drought, flexibility

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Authors: Richard Draper

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A supercomputer can be constructed from identical building blocks which are small parallel processors connected by a network referred to as the local network. The routers have unused ports which are used to interconnect the building blocks. These connections are referred to as the global network. The address space has a global and a local component (g, l). The conventional way to connect the building blocks is to connect (g, l) to (g’,l). If there are K blocks, this requires K global ports in each router. If a block is of size M, the result is a machine with KM routers having diameter two. To increase the size of the machine to 2K blocks, each router connects to only half of the other blocks. The result is a larger machine but also one with greater diameter. This is a crude description of how the network of the CRAY XC® is designed. In this paper, a family of interconnection networks using routers with K global and M local ports is defined. Coordinates are (c,d, p) and the global connections are (c,d,p)↔(c’,p,d) which swaps p and d. The network is denoted D3(K,M) and is called a Swapped Dragonfly. D3(K,M) has KM2 routers and has diameter three, regardless of the size of K. To produce a network of size KM2 conventionally, diameter would be an increasing function of K. The family of Swapped Dragonflies has other desirable properties: 1) D3(K,M) scales linearly in K and quadratically in M. 2) If L < K, D3(K,M) contains many copies of D3(L,M). 3) If L < M, D3(K,M) contains many copies of D3(K,L). 4) D3(K,M) can perform an all-to-all exchange in KM2+KM time which is only slightly more than the time to do a one-to-all. This paper makes several contributions. It is the first time that a swap has been used to define a linearly scalable family of networks. Structural properties of this new family of networks are thoroughly examined. A synchronizing packet header is introduced. It specifies the path to be followed and it makes it possible to define highly parallel communication algorithm on the network. Among these is an all-to-all exchange in time KM2+KM. To demonstrate the effectiveness of the swap properties of the network of the CRAY XC® and D3(K,16) are compared.

Keywords: all-to-all exchange, CRAY XC®, Dragonfly, interconnection network, packet switching, swapped network, topology

Procedia PDF Downloads 109

Authors: Mark Anthony Burdeos, Kara Ella Catoto, Alraine Pauyon, Elesar Malicoban

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This study sought to develop, validate, and implement the WebQuest and Online Treasure Hunt as instructional materials in teaching Motion in One Dimension for Grade 7 students and to determine its effects on the students’ conceptual learning, performance and attitude towards Physics. In the development stage, several steps were taken, such as the actual planning and developing the WebQuest and Online Treasure Hunt and making the lesson plan and achievement test. The content and the ICT(Information Communications Technology) effect of the developed instructional materials were evaluated by the Content and ICT experts using adapted evaluation forms. During the implementation, pretest and posttest were administered to determine students’ performance, and pre-attitude and post-attitude tests to investigate students’ attitudes towards Physics before and after the WebQuest and Online Treasure Hunt activity. The developed WebQuest and Online Treasure Hunt passed the validation of Content experts and ICT experts. Students acquired more knowledge on Motion in One Dimension and gained a positive attitude towards Physics after the utilization of WebQuest and Online Treasure Hunt, evidenced significantly higher scores in posttest compared to pretest and higher ratings in post-attitude than pre-attitude. The developed WebQuest and Online Treasure Hunt were proven good in quality and effective materials in teaching Motion in One Dimension and developing a positive attitude towards Physics. However, students performed better in the pretest and posttest and rated higher in the pre-attitude and post-attitude tests in the WebQuest than in the Online Treasure Hunt. This study would provide significant learning experiences to the students that would be useful in building their knowledge, in understanding concepts in a most understandable way, in exercising to use their higher-order thinking skills, and in utilizing their capabilities and abilities to relate Physics topics to real-life situations thereby, students can have in-depth learning about Motion in One Dimension. This study would help teachers to enhance the teaching strategies as the two instructional materials provide interesting, engaging, and innovative teaching-learning experiences for the learners, which are helpful in increasing the level of their motivation and participation in learning Physics. In addition, it would provide information as a reference in using technology in the classroom and to determine which of the two instructional materials, WebQuest and Online Treasure Hunt, is suitable for the teaching-learning process in Motion in One Dimension.

Keywords: ICT integration, motion in one dimension, online treasure hunt, Webquest

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Authors: Juni C. Kim, Anna R. Robuck, Douglas I. Walker

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The human exposome, which includes chemical exposures over the lifetime and their effects, is now recognized as an important measure for understanding human health; however, the complexity of the data makes the identification of environmental chemicals challenging. The goal of our project was to establish a computational workflow for the improved identification of environmental pollutants containing chlorine or bromine. Using the “pattern. search” function available in the R package NonTarget, we wrote a multifunctional script that searches mass spectral clusters from untargeted gas-chromatography high-resolution mass spectrometry (GC-HRMS) for the presence of spectra consistent with chlorine and bromine-containing organic compounds. The “pattern. search” function was incorporated into a different function that allows the evaluation of clusters containing multiple analyte fragments, has multi-core support, and provides a simplified output identifying listing compounds containing chlorine and/or bromine. The new function was able to process 46,000 spectral clusters in under 8 seconds and identified over 150 potential halogenated spectra. We next applied our function to a deidentified dataset from patients diagnosed with primary biliary cholangitis (PBC), primary sclerosing cholangitis (PSC), and healthy controls. Twenty-two spectra corresponded to potential halogenated compounds in the PSC and PBC dataset, including six significantly different in PBC patients, while four differed in PSC patients. We have developed an improved algorithm for detecting halogenated compounds in GC-HRMS data, providing a strategy for prioritizing exposures in the study of human disease.

Keywords: exposome, metabolome, computational metabolomics, high-resolution mass spectrometry, exposure, pollutants

Procedia PDF Downloads 122

Authors: Jihane Bouabid

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The urgency to transition towards sustainable energy sources has revealed itself imperative. Today, in the 21st Century, the intellectual society have imposed technological advancements and improvements, and anticipates expeditious outcomes as an integral component of its relentless pursuit of an elevated standard of living. As a part of empowering human development, driving economic growth and meeting social needs, the access to energy services has become a necessity. As a part of these improvements, we are introducing the project "Mywindturbine" - an interactive web user interface for design and analysis in the field of wind energy, with a particular adherence to the IEC (International Electrotechnical Commission) standard 61400-2 "Wind turbines – Part 2: Design requirements for small wind turbines". Wind turbines play a pivotal role in Morocco's renewable energy strategy, leveraging the nation's abundant wind resources. The IEC 61400-2 standard ensures the safety and design integrity of small wind turbines deployed in Morocco, providing guidelines for performance and safety protocols. The conformity with this standard ensures turbine reliability, facilitates standards alignment, and accelerates the integration of wind energy into Morocco's energy landscape. The aim of the GUI (Graphical User Interface) for engineers and professionals from the field of wind energy systems who would like to design a small wind turbine system following the safety requirements of the international standards IEC 61400-2. The interface provides an easy way to analyze the structure of the turbine machine under normal and extreme load conditions based on the specific inputs provided by the user. The platform introduces an overview to sustainability and renewable energy, with a focus on wind turbines. It features a cross-examination of the input parameters provided from the user for the SLM (Simple Load Model) of small wind turbines, and results in an analysis according to the IEC 61400-2 standard. The analysis of the simple load model encompasses calculations for fatigue loads on blades and rotor shaft, yaw error load on blades, etc. for the small wind turbine performance. Through its structured framework and adherence to the IEC standard, "Mywindturbine" aims to empower professionals, engineers, and intellectuals with the knowledge and tools necessary to contribute towards a sustainable energy future.

Keywords: small wind turbine, IEC 61400-2 standard, user interface., simple load model

Procedia PDF Downloads 43

Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

Procedia PDF Downloads 43

Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

Procedia PDF Downloads 162

Authors: Erifyli Tsagkari, Stephanie Connelly, Zhaowei Liu, Andrew McBride, William Sloan

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Biofilms play an essential role in treating water in biofiltration systems. The biofilm morphology and function are inextricably linked to the hydrodynamics of flow through a filter, and yet engineers rarely explicitly engineer this interaction. We develop a system that links computer simulation and 3-D printing to optimize and rapidly prototype filter media to optimize biofilm function with the hypothesis that biofilm function is intimately linked to the flow passing through the filter. A computational model that numerically solves the incompressible time-dependent Navier Stokes equations coupled to a model for biofilm growth and function is developed. The model is imbedded in an optimization algorithm that allows the model domain to adapt until criteria on biofilm functioning are met. This is applied to optimize the shape of filter media in a simple flow channel to promote biofilm formation. The computer code links directly to a 3-D printer, and this allows us to prototype the design rapidly. Its validity is tested in flow visualization experiments and by microscopy. As proof of concept, the code was constrained to explore a small range of potential filter media, where the medium acts as an obstacle in the flow that sheds a von Karman vortex street that was found to enhance the deposition of bacteria on surfaces downstream. The flow visualization and microscopy in the 3-D printed realization of the flow channel validated the predictions of the model and hence its potential as a design tool. Overall, it is shown that the combination of our computational model and the 3-D printing can be effectively used as a design tool to prototype filter media to optimize biofilm formation.

Keywords: biofilm, biofilter, computational model, von karman vortices, 3-D printing.

Procedia PDF Downloads 131

Authors: Lamees Nasser, Yago Diez, Robert Martí, Joan Martí, Ibrahim Sadek

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Automated 3D breast ultrasound (ABUS) screening is a novel modality in medical imaging because of its common characteristics shared with other ultrasound modalities in addition to the three orthogonal planes (i.e., axial, sagittal, and coronal) that are useful in analysis of tumors. In the literature, few automatic approaches exist for typical tasks such as segmentation or registration. In this work, we deal with two problems concerning ABUS images: nipple and rib detection. Nipple and ribs are the most visible and salient features in ABUS images. Determining the nipple position plays a key role in some applications for example evaluation of registration results or lesion follow-up. We present a nipple detection algorithm based on color and shape of the nipple, besides an automatic approach to detect the ribs. In point of fact, rib detection is considered as one of the main stages in chest wall segmentation. This approach consists of four steps. First, images are normalized in order to minimize the intensity variability for a given set of regions within the same image or a set of images. Second, the normalized images are smoothed by using anisotropic diffusion filter. Next, the ribs are detected in each slice by analyzing the eigenvalues of the 3D Hessian matrix. Finally, a breast mask and a probability map of regions detected as ribs are used to remove false positives (FP). Qualitative and quantitative evaluation obtained from a total of 22 cases is performed. For all cases, the average and standard deviation of the root mean square error (RMSE) between manually annotated points placed on the rib surface and detected points on rib borders are 15.1188 mm and 14.7184 mm respectively.

Keywords: Automated 3D Breast Ultrasound, Eigenvalues of Hessian matrix, Nipple detection, Rib detection

Procedia PDF Downloads 321

Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: Mohamad Musa

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The history of mental health practices and services in the Middle East region has been deeply intertwined with its rich cultural, religious, and societal context. Tracing back to ancient times, mental health approaches were heavily influenced by the traditions of major monotheistic religions, with a strong emphasis on spiritual and traditional healing methods. As psychiatric institutions and Western medicine gradually gained a foothold in the region during the 20th century, a notable shift occurred. However, the integration of Western psychiatric practices faced significant challenges due to cultural barriers and deeply rooted beliefs. Families and communities often turned to traditional healers and religious practices as their initial recourse for mental health concerns, viewing Western interventions with skepticism and hesitation. Historically, mental health services in the Middle East have been overshadowed by a focus on physical health and the biomedical model. Mental illness carried substantial stigma, with individuals and families often reluctant to disclose mental health struggles due to fears of societal ostracization and discrimination. This stigma posed a significant barrier to accessing and accepting formal mental health support. Later in the 20th century, governments in the Middle East began recognizing the need for modernizing mental health services and integrating them into the broader healthcare system. However, this process was hindered by several factors, including limited resources, inadequate training for healthcare professionals, and ongoing conflicts and instability in certain regions, which disrupted the delivery of mental health services. As the 21st century progressed, several Middle Eastern nations, particularly those in the Arabian Gulf region, began implementing national mental health strategies and legislative reforms to address the growing need for comprehensive mental health care. These efforts aimed to destigmatize mental illness, protect the rights of individuals with mental health conditions, and promote public awareness and education. Despite these positive developments, the historical legacy of stigma, cultural barriers, and limited resources continues to pose challenges in the provision of accessible and culturally responsive mental health services across the diverse populations of the Middle East.

Keywords: mental health, history, middle east, literature review

Procedia PDF Downloads 21