Search results for: autoregressive integrate moving average model selection

Authors: Mikaela Kutrolli, Noah S. Pereira, Vanessa Scanlon, Mohamadmahdi Samandari, Ali Tamayol

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Bone tissue engineering has drawn significant attention and various biomaterials have been tested. Polymers such as polycaprolactone (PCL) offer excellent biocompatibility, reasonable mechanical properties, and biodegradability. However, PCL scaffolds suffer a critical drawback: a lack of micro/mesoporosity, affecting cell attachment, tissue integration, and mineralization. It also results in a slow degradation rate. While 3D-printing has addressed the issue of macroporosity through CAD-guided fabrication, PCL scaffolds still exhibit poor smaller-scale porosity. To overcome this, we generated composites of PCL, hydroxyapatite (HA), and powdered sucrose (PS). The latter serves as a sacrificial material to generate porous particles after sucrose dissolution. Additionally, we have incorporated dexamethasone (DEX) to boost the PCL osteogenic properties. The resulting scaffolds maintain controlled macroporosity from the lattice print structure but also develop micro/mesoporosity within PCL fibers when exposed to aqueous environments. The study involved mixing PS into solvent-dissolved PCL in different weight ratios of PS to PCL (70:30, 50:50, and 30:70 wt%). The resulting composite was used for 3D printing of scaffolds at room temperature. Printability was optimized by adjusting pressure, speed, and layer height through filament collapse and fusion test. Enzymatic degradation, porogen leaching, and DEX release profiles were characterized. Physical properties were assessed using wettability, SEM, and micro-CT to quantify the porosity (percentage, pore size, and interconnectivity). Raman spectroscopy was used to verify the absence of sugar after leaching. Mechanical characteristics were evaluated via compression testing before and after porogen leaching. Bone marrow stromal cells (BMSCs) behavior in the printed scaffolds was studied by assessing viability, metabolic activity, osteo-differentiation, and mineralization. The scaffolds with a 70% sugar concentration exhibited superior printability and reached the highest porosity of 80%, but performed poorly during mechanical testing. A 50% PS concentration demonstrated a 70% porosity, with an average pore size of 25 µm, favoring cell attachment. No trace of sucrose was found in Raman after leaching the sugar for 8 hours. Water contact angle results show improved hydrophilicity as the sugar concentration increased, making the scaffolds more conductive to cell adhesion. The behavior of bone marrow stromal cells (BMSCs) showed positive viability and proliferation results with an increasing trend of mineralization and osteo-differentiation as the sucrose concentration increased. The addition of HA and DEX also promoted mineralization and osteo-differentiation in the cultures. The integration of PS as porogen at a concentration of 50%wt within PCL scaffolds presents a promising approach to address the poor cell attachment and tissue integration issues of PCL in bone tissue engineering. The method allows for the fabrication of scaffolds with tunable porosity and mechanical properties, suitable for various applications. The addition of HA and DEX further enhanced the scaffolds. Future studies will apply the scaffolds in an in-vivo model to thoroughly investigate their performance.

Keywords: bone, PCL, 3D printing, tissue engineering

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Authors: Layla Alzarah

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The purpose of this research was to study the effects of co-teaching upon study achievement by teaching unite of teaching strategy course to a sample of students at education college at King Faisal University. The sample of this study, which consisted of 100 students, was divided into two equal groups. 50 students were selected to be the Control group which had been taught by the traditional way with one teacher, whereas the remaining 50 students represented the experimental group who had been taught by co-teaching. The study had lasted for 4 weeks. Related achievement test had been prepared, consisted of 23 questions, from multi choice question type, which had been divided on the chosen unite syllabus. The validity and reliability had been tested. The study conducted at the second semester of 1433-1434 HT tests had been used to analysis the data. The research findings showed that the average exam scores of students receiving team teaching were higher than those of students receiving traditional teaching as there were significant differences in means at (<0.05) between the two groups in favor of the experimental group. Based on the study findings the researcher recommended applying co-teaching in teaching the course of teaching strategies and other courses also to conduct similar studies.

Keywords: co-teaching, cooperative teaching, teaching strategies, study achievement

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Authors: Tatiana V. Melnikova, Lyudmila P. Polyakova, Alla A. Oudalova

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As a result of environmental pollution, the production of agriculture and foodstuffs inevitably contain residual amounts of Persistent Organic Pollutants (POP). The special attention must be given to organic pollutants, including various organochlorinated pesticides (OCP). Among priorities, OCP is DDT (and its metabolite DDE), alfa-HCH, gamma-HCH (lindane). The control of these substances spends proceeding from requirements of sanitary norms and rules. During too time often is lost sight of that the primary product can pass technological processing (in particular irradiation treatment) as a result of which transformation of physicochemical forms of initial polluting substances is possible. The goal of the present work was to study the OCP radiation degradation at a various gamma-radiation dosimetric characteristics. The problems posed for goal achievement: to evaluate the content of the priority of OCPs in food; study the character the degradation of OCP in model solutions (with micro concentrations commensurate with the real content of their agricultural and food products) depending upon dosimetric characteristics of gamma-radiation. Qualitative and quantitative analysis of OCP in food and model solutions by gas chromatograph Varian 3400 (Varian, Inc. (USA)); chromatography-mass spectrometer Varian Saturn 4D (Varian, Inc. (USA)) was carried out. The solutions of DDT, DDE, alpha- and gamma- isomer HCH (0.01, 0.1, 1 ppm) were irradiated on "Issledovatel" (60Co) and "Luch - 1" (60Co) installations at a dose 10 kGy with a variation of dose rate from 0.0083 up to 2.33 kGy/sec. It was established experimentally that OCP residual concentration in individual samples of food products (fish, milk, cereal crops, meat, butter) are evaluated as 10-1-10-4 mg/kg, the value of which depends on the factor-sensations territory and natural migration processes. The results were used in the preparation of model solutions OCP. The dependence of a degradation extent of OCP from a dose rate gamma-irradiation has complex nature. According to our data at a dose 10 kGy, the degradation extent of OCP at first increase passes through a maximum (over the range 0.23 – 0.43 Gy/sec), and then decrease with the magnification of a dose rate. The character of the dependence of a degradation extent of OCP from a dose rate is kept for various OCP, in polar and nonpolar solvents and does not vary at the change of concentration of the initial substance. Also in work conditions of the maximal radiochemical yield of OCP which were observed at having been certain: influence of gamma radiation with a dose 10 kGy, in a range of doses rate 0.23 – 0.43 Gy/sec; concentration initial OCP 1 ppm; use of solvent - 2-propanol after preliminary removal of oxygen. Based on, that at studying model solutions of OCP has been established that the degradation extent of pesticides and qualitative structure of OCP radiolysis products depend on a dose rate, has been decided to continue researches radiochemical transformations OCP into foodstuffs at various of doses rate.

Keywords: degradation extent, dosimetric characteristics, gamma-radiation, organochlorinated pesticides, persistent organic pollutants

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Authors: Cristina Azocar, Ivana Markova

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A survey of 565 male undergraduates examined the effects of exposure to social networking sites and entertainment media on young men’s body image. Exposure to social and to entertainment media was found to have negative effects on men’s body satisfaction, social comparison, and thin ideal internalization. Findings indicated significant differences in those men who were more exposed to social and to entertainment media than those who were not as exposed. Consistent with past studies, gay men were found to be more dissatisfied with their bodies than straight men. Gay men compared themselves to other better-looking individuals and internalized ideal body types seen in media significantly more than their straight counterparts. Surprisingly, straight men seem to care as much about their physical attractiveness/appearance as gay men do, but only in public settings such as at the beach, at athletic events (including gyms) and social events. Although on average ethnic groups were more similar than different, small but significant differences occurred with Asian men indicating significantly higher body dissatisfaction than White/European men and Middle Eastern/Arab men their counterparts. The study increases our knowledge about SNS and entertainment use and its associated body image, and body satisfaction affects among low-income ethnic minority men.

Keywords: body dissatisfaction, body image, entertainment media, gay men, race and ethnicity, social economic status, social comparison, social media

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Authors: Behnam Zahednejad, Saeed Kosari

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Widespread deployment of Internet of Things (IoT) has raised security and privacy issues in this environment. Designing a secure two-factor authentication scheme between the user and server is still a challenging task. In this paper, we focus on Cancelable Biometric (CB) as an authentication factor in IoT. We show that previous CB-based scheme fail to provide real two-factor security, Perfect Forward Secrecy (PFS) and suffer database attacks and traceability of the user. Then we propose our improved scheme based on CB and Physically Unclonable Functions (PUF), which can provide real two-factor security, PFS, user’s unlinkability, and resistance to database attack. In addition, Key Compromise Impersonation (KCI) resilience is achieved in our scheme. We also prove the security of our proposed scheme formally using both Real-Or-Random (RoR) model and the ProVerif analysis tool. For the usability of our scheme, we conducted a performance analysis and showed that our scheme has the least communication cost compared to the previous CB-based scheme. The computational cost of our scheme is also acceptable for the IoT environment.

Keywords: IoT, two-factor security, cancelable biometric, key compromise impersonation resilience, perfect forward secrecy, database attack, real-or-random model, ProVerif

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Authors: Tsai Yu-hsin, Chung Yi-Hsin

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The employment of an HSR system, resulting in elevation in the inter-city/-region accessibility, is likely to promote spatial interaction between places in the HSR and extended territory. The inter-city/-region travel via HSR could be, among others, affected by the land use, transportation, and location of the HSR station at both trip origin and destination ends. However, relatively few insights have been shed on these impacts and spatial patterns of the HSR travel. The research purposes, as phase one of a series of HSR related research, of this study are threefold: to analyze the general spatial patterns of HSR trips, such as the spatial distribution of trip origins and destinations; to analyze if specific land use, transportation characteristics, and trip characteristics affect HSR trips in terms of the use of HSR, the distribution of trip origins and destinations, and; to analyze the socio-economic characteristics of HSR travelers. With the Taiwan HSR starting operation in 2007, this study emphasizes on the intermediate-term impact of HSR, which is made possible with the population and housing census and industry and commercial census data and a station area intercept survey conducted in the summer 2014. The analysis will be conducted at the city, inter-city, and inter-region spatial levels, as necessary and required. The analysis tools include descriptive statistics and multivariate analysis with the assistance of SPSS, HLM and ArcGIS. The findings, on the one hand, can provide policy implications for associated land use, transportation plan and the site selection of HSR station. On the other hand, on the travel the findings are expected to provide insights that can help explain how land use and real estate values could be affected by HSR in following phases of this series of research.

Keywords: high speed rail, land use, travel, spatial pattern

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Authors: Chi C. Lin, Chih. H. Hsieh, Chi H. Lin

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The present study attempted to develop and test a self-determination theory dual-process model among teachers’ need supportive teaching, need thwarting teaching, and students’ need satisfaction, need frustration, and motivation regulation on vocational high school learners. This study adopted a survey questionnaire method. Participants were 736 (472 males, 264 females) vocational high school students in Taiwan. The instrument included five sets: the Teachers’ Need Supportive Teaching Scale, the Teachers’ Need Thwart Teaching Scale, the Need Satisfaction Scale, the Need Frustration Scale, and the Motivational Regulation Scale. A Structural equation modeling was used for the data analyses, results indicated that (1) teachers’ need supportive teaching had direct effects on students’ need satisfaction; (2) teachers’ thwarting teaching also had a direct effect on students’ need frustration; (3) teachers’ need supportive teaching had a negative direct effect on students’ need frustration; (4) students’ need satisfaction had direct effects on their autonomous motivation and control motivation, respectively; (5) students’ need frustration also had direct effects on their control motivation and motivation, respectively; (6) the model proposed in this study fit mostly with the empirical data.

Keywords: motivational regulation, need satisfaction, need frustration, supportive teaching, thwart teaching, vocational high school students

Procedia PDF Downloads 117

Authors: M. Irannezhad, E. H. N. Gashti, S. Mohammadighavam, M. Zarrini, B. Kløve

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Climate warming would increase rainfall by shifting precipitation falling form from snow to rain, and would accelerate snow cover disappearing by increasing snowpack. Using temperature and precipitation data in the temperature-index snowmelt model, we evaluated variability of snowfall and continuous snow cover duration(CSCD) during 1944-2010 over Pelso, central Finland. MannKendall non-parametric test determined that annual precipitation increased by 2.69 (mm/year, p<0.05) during the study period, but no clear trend in annual temperature. Both annual rainfall and snowfall increased by 1.67 and 0.78 (mm/year, p<0.05), respectively. CSCD was generally about 205 days from 14 October to 6 May. No clear trend was found in CSCD over Pelso. Spearman’s rank correlation showed most significant relationships of annual snowfall with the East Atlantic (EA) pattern, and CSCD with the East Atlantic/West Russia (EA/WR) pattern. Increased precipitation with no warming temperature caused the rainfall and snowfall to increase, while no effects on CSCD.

Keywords: variations, snowfall, snow cover duration, temperature-index snowmelt model, teleconnection patterns

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Authors: Arpit Kumar Shrivastava, Subrat Kumar, Rajani Kanta Mohapatra, Priyadarshi Soumyaranjan Sahu

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Computational approaches to predict structure, function and other biological characteristics of proteins are becoming more common in comparison to the traditional methods in drug discovery. Cryptosporidiosis is a major zoonotic diarrheal disease particularly in children, which is caused primarily by Cryptosporidium hominis and Cryptosporidium parvum. Currently, there are no vaccines for cryptosporidiosis and recommended drugs are not effective. With the availability of complete genome sequence of C. hominis, new targets have been recognized for the development of effective and better drugs and/or vaccines. We identified a unique hypothetical epitopic protein in C. hominis genome through BLASTP analysis. A 3D model of the hypothetical protein was generated using I-Tasser server through threading methodology. The quality of the model was validated through Ramachandran plot by PROCHECK server. The functional annotation of the hypothetical protein through DALI server revealed structural similarity with human Transportin 3. Phylogenetic analysis for this hypothetical protein also showed C. hominis hypothetical protein (CUV04613) was the closely related to human transportin 3 protein. The 3D protein model is further subjected to virtual screening study with inhibitors from the Zinc Database by using Dock Blaster software. Docking study reported N-(3-chlorobenzyl) ethane-1,2-diamine as the best inhibitor in terms of docking score. Docking analysis elucidated that Leu 525, Ile 526, Glu 528, Glu 529 are critical residues for ligand–receptor interactions. The molecular dynamic simulation was done to access the reliability of the binding pose of inhibitor and protein complex using GROMACS software at 10ns time point. Trajectories were analyzed at each 2.5 ns time interval, among which, H-bond with LEU-525 and GLY- 530 are significantly present in MD trajectories. Furthermore, antigenic determinants of the protein were determined with the help of DNA Star software. Our study findings showed a great potential in order to provide insights in the development of new drug(s) or vaccine(s) for control as well as prevention of cryptosporidiosis among humans and animals.

Keywords: cryptosporidium hominis, hypothetical protein, molecular docking, molecular dynamics simulation

Procedia PDF Downloads 352

Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

Procedia PDF Downloads 163

Authors: Amar Ghelani

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People with auditory verbal hallucinations (AVH) who seek support from mental health services commonly report feeling unheard and invalidated in their interactions with social workers and psychiatric professionals. Current mental health training and clinical approaches have proven to be inadequate in addressing the complex nature of voice hearing. Childhood trauma is a key factor in the development of AVH and can render people more vulnerable to hearing both supportive and/or disturbing voices. Lived experiences of racism, poverty, and immigration are also associated with development of what is broadly classified as psychosis. Despite evidence affirming the influence of environmental factors on voice hearing, the Western biomedical system typically conceptualizes this experience as a symptom of genetically-based mental illnesses which requires diagnosis and treatment. Overemphasis on psychiatric medications, referrals, and directive approaches to people’s problems has shifted clinical interventions away from assessing and addressing problems directly related to AVH. The Maastricht approach offers voice hearers and mental health workers an alternative and respectful starting point for understanding and coping with voices. The approach was developed by voice hearers in partnership with mental health professionals and entails an innovative method to assess and create meaning from voice hearing and related life stressors. The objectives of the approach are to help people who hear voices: (1) understand the problems and/or people the voices may represent in their history, and (2) cope with distress and find solutions to related problems. The Maastricht approach has also been found to help voice hearers integrate emotional conflicts, reduce avoidance or fear associated with AVH, improve therapeutic relationships, and increase a sense of control over internal experiences. The proposed oral presentation will be guided by a recovery-oriented theoretical framework which suggests healing from psychological wounds occurs through social connections and community support systems. The presentation will start with a brainstorming exercise to identify participants pre-existing knowledge of the subject matter. This will lead into a literature review on the relations between trauma, intersectionality, and AVH. An overview of the Maastricht approach and review of research related to its therapeutic risks and benefits will follow. Participants will learn trauma-informed coping skills and questions which can help voice hearers make meaning from their experiences. The presentation will conclude with a review of resources and learning opportunities where participants can expand their knowledge of the Hearing Voices Movement and Maastricht approach.

Keywords: Maastricht interview, recovery, therapeutic assessment, voice hearing

Procedia PDF Downloads 96

Authors: Runlin Liu, Shilong Li

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China is a mountainous country, with two-thirds of its territory covered by plateaus, hills, and mountains, and nearly half of the cities and towns are distributed in mountainous areas. Compared with the environmental constraints in the development path of cities and towns in the plains, there are heterogeneities in aspects such as spatial characteristics, growth mode, and ecological protection and so on for mountain village and townlets, and the development path of mountain village and townlets has a bidirectional relationship between mountain space and economic growth. Based on classical growth theory, this article explores the two-dimensional coupling relation between space and economy in mountain village and townlets under background of rural rejuvenation. GIS technology is adopted in the study to analyze spatial trends and patterns, economical spatial differentiation characteristics of village and townlets. This powerful tool can also help differentiate and analyze limiting factors and assessment systems in the economic growth of village and townlets under spatial dimension of mountainous space. To make the research more specific, this article selects mountain village and townlets in Southwest China as the object of study; this provides good cases for analyzing parallel coupling mechanism of the duality structure system between economic growth and spatial expansion and discussing the path selection of spatial economic growth of mountain village and towns with multiple constraints. The research results can provide quantitative references for the spatial and economic development paths of mountain villages and towns, which is helpful in realizing efficient and high-quality development mode with equal emphasis on spatial and economic benefits for these type of towns.

Keywords: coupling mechanism, geographic information technology, mountainous town, synergetic development, spatial economy

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Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

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Authors: Mathias B. Michael, Esther T. Akinlabi, Tien-Chien Jen

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Thermal energy consumption in palm oil production plant comprises mainly of steam, hot water and hot air. In most efficient plants, hot water and air are generated from the steam supply system. Research has shown that thermal energy utilize in palm oil production plants is about 70 percent of the total energy consumption of the plant. In order to manage the plants’ energy efficiently, the energy systems are modelled and optimized. This paper aimed to present the model of steam supply systems of a typical palm oil production plant in Ghana. The models include exergy and energy models of steam boiler, steam turbine and the palm oil mill. The paper further simulates the virtual plant model to obtain the thermal energy performance of the plant under study. The simulation results show that, under normal operating condition, the boiler energy performance is considerably below the expected level as a result of several factors including intermittent biomass fuel supply, significant moisture content of the biomass fuel and significant heat losses. The total thermal energy performance of the virtual plant is set as a baseline. The study finally recommends number of energy efficiency measures to improve the plant’s energy performance.

Keywords: palm biomass, steam supply, exergy and energy models, energy performance benchmark

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Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: S. Behnia, S. Fathizadeh, A. Akhshani

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In the recent decades, DNA has increasingly interested in the potential technological applications that not directly related to the coding for functional proteins that is the expressed in form of genetic information. One of the most interesting applications of DNA is related to the construction of nanostructures of high complexity, design of functional nanostructures in nanoelectronical devices, nanosensors and nanocercuits. In this field, DNA is of fundamental interest to the development of DNA-based molecular technologies, as it possesses ideal structural and molecular recognition properties for use in self-assembling nanodevices with a definite molecular architecture. Also, the robust, one-dimensional flexible structure of DNA can be used to design electronic devices, serving as a wire, transistor switch, or rectifier depending on its electronic properties. In order to understand the mechanism of the charge transport along DNA sequences, numerous studies have been carried out. In this regard, conductivity properties of DNA molecule could be investigated in a simple, but chemically specific approach that is intimately related to the Su-Schrieffer-Heeger (SSH) model. In SSH model, the non-diagonal matrix element dependence on intersite displacements is considered. In this approach, the coupling between the charge and lattice deformation is along the helix. This model is a tight-binding linear nanoscale chain established to describe conductivity phenomena in doped polyethylene. It is based on the assumption of a classical harmonic interaction between sites, which is linearly coupled to a tight-binding Hamiltonian. In this work, the Hamiltonian and corresponding motion equations are nonlinear and have high sensitivity to initial conditions. Then, we have tried to move toward the nonlinear dynamics and phase space analysis. Nonlinear dynamics and chaos theory, regardless of any approximation, could open new horizons to understand the conductivity mechanism in DNA. For a detailed study, we have tried to study the current flowing in DNA and investigated the characteristic I-V diagram. As a result, It is shown that there are the (quasi-) ohmic areas in I-V diagram. On the other hand, the regions with a negative differential resistance (NDR) are detectable in diagram.

Keywords: DNA conductivity, Landauer resistance, negative dierential resistance, Chaos theory, mean Lyapunov exponent

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Authors: Nabat Gojaeva, Mikayil Naghiyev, Sultan Jafarov, Gular Mikayilova

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Chovdar ore area is located in the contact of Dashkesan caldera and Shamkir horst-graben uplift, which comprises the central part of Lok-Karabakh Island arcs of South Caucasus metallogenic province in terms of regional tectonics. One of the main structural features of formation of the Mereh and Aghyokhush group of low sulfidation epithermal gold deposits, locating in the north peripheric part of the ore area, is involving the crossing areas of ore-hosting and ore-forming Pan-Caucasian-direction structurally-compound faults with the meridional, rhombically shaped faults. In addition, another significant feature is the temporally two- or three-stage ore formation. In the first stage -an early phase of Upper Bathonian age, sulfides are the dominant minerals, in the second stage- late ‘productive’ phase of Upper Bathonian age, mainly gold mineralization is formed. Also, in the Upper Jurassic – Lower Cretaceous ages, rarely-encountered Cu-polymetallic ore formations are documented. Finally, in the last stage, the re-dislocation of ore-formation is foreseen in the previously-formed mineralization areas. The faults in the strike and dip directions formed shearing, brecciation, sulfide mineralization aureoles, and hydrothermal alteration zones in the wall rocks along with the local depression blocks. The geological-structural analysis of the area shows that multiple and various morphogenetic volcano-tectonically fault systems have developed in the area. These fault systems have played a trap role for ore-formation in the intersected parts of faults mentioned above. Thus, in the referred parts, mostly predominance of felsic volcanism and metasomatic alteration (silicification, argillitic, etc.) of wall rocks, as well as the products of this volcanism, account for the inclusion of hydrothermal ore-forming fluids along these faults. It is possible to determine temporally and lithological-structural connection between the ore-formation along with local depression blocks and faults as borders for products of felsic volcanism of Upper Cretaceous-Lesser Jurassic ages, in the results of the replacement of hydrothermal alteration zones with relatively low-temperature metasomatic alterations while moving from the felsic parts to the margins, and due to being non-ore bearing intermediate and intermediate-felsic magmatic facies.

Keywords: Aghyokhush, fault, gold deposit, Mereh

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer

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Crowdsourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowdsourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is the first to develop safety performance functions using crowdsourced data by adopting a negative binomial structure model and Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.

Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening

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Authors: Mehdi Tajdari, Farzad Mokhtarnejad, Fatemeh Moradi, Mehdi Najafizadeh

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Nowadays, energy absorbing devices have been widely used in all vehicles and moving parts such as railway couches, aircraft, ships and lifts. The aim is to protect these structures from serious damages while subjected to impact loads, or to minimize human injuries while collision is occurred in transportation systems. These energy-absorbing devices can dissipate kinetic energy in a wide variety of ways like friction, facture, plastic bending, crushing, cyclic plastic deformation and metal cutting. On the other hand, various structures may be used as collapsible energy absorbers. Metallic cylindrical tubes have attracted much more attention due to their high stiffness and strength combined with the low weight and ease of manufacturing process. As a matter of fact, favorable crash worthiness characteristics for energy dissipation purposes can be achieved from axial collapse of tubes while they crush progressively in symmetric modes. However, experimental and theoretical results have shown that depending on various parameters such as tube geometry, material properties of tube, boundary and loading conditions, circular tubes buckle in different modes of deformation, namely, diamond and Euler collapsing modes. It is shown that when the tube length is greater than the critical length, the tube deforms in overall Euler buckling mode, which is an inefficient mode of energy absorption and needs to be avoided in crash worthiness applications. This study develops a new method with the aim of improving energy absorption characteristics of long steel circular tubes. Inserting a helical spring into the tubes is proved experimentally to be an efficient solution. In fact when a long tube is subjected to axial compression load, the spring prevents of undesirable Euler or diamond collapsing modes. This is because the spring reinforces the internal wall of tubes and it causes symmetric deformation in tubes. In this research three specimens were prepared and three tests were performed. The dimensions of tubes were selected so that in axial compression load buckling is occurred. In the second and third tests a spring was inserted into tubes and they were subjected to axial compression load in quasi-static and impact loading, respectively. The results showed that in the second and third tests buckling were not happened and the tubes deformed in symmetric modes which are desirable in energy absorption.

Keywords: energy absorption, circular tubes, collapsing deformation, crashworthiness

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Authors: Atitallah Sofien, Bouyahia Olfa, Hadj Salah Ibrahim, Ben Saleh Foued, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

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Introduction: Carbon monoxide (CO) poisoning is a common pathology responsible for high morbidity and mortality worldwide. Aim: The purpose of this study was to determine the epidemiological profile of CO poisoning as well as its clinical, paraclinical, therapeutic, and evolutionary aspects. Methods: Our study included observations of CO poisoning in children hospitalized in the pediatric department C of the Children's Hospital in Tunis over a period of 3 years. Results: We have collected 199 cases of CO poisoning in children. The average age was 5.43 years, with a sex ratio of 0.98. The source of CO was inside the home in 73.2% of cases, and it was the gas bath heater in 68.8% of cases. The intoxication was collective in 93.5% of the cases, and it occurred during the month of January in 35.8% of the cases. The clinical manifestations were headaches in 69.5% of cases. The rate of carboxyhemoglobin was pathological in 73.9% of cases. All patients received normobaric oxygen therapy, and only 3.6% of patients had a hyperbaric oxygen therapy session. We did not deplore any case of death in our study. Conclusion: CO poisoning remains a public health problem in Tunisia with high morbidity. The risk of secondary complications, particularly neuropsychiatric, requires clinical and possibly neuroradiological monitoring of these victims.

Keywords: poisoning, carbon monoxide, children, hyperbaric oxygenation

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Authors: Hannah Rosenqvist, Fanny Guay

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Critical infrastructure protection has been an important topic for several years. Programmes such as the European Programme for Critical Infrastructure Protection (EPCIP), Critical Infrastructure Warning Information Network (CIWIN) and the European Reference Network for Critical Infrastructure Protection (ENR-CIP) have been the pillars to the work done since 2006. However, measuring critical infrastructure resilience has not been an easy task. This has to do with the fact that the concept of resilience has several definitions and is applied in different domains such as engineering and social sciences. Since June 2015, the EU project IMPROVER has been focusing on developing a methodology for implementing a combination of societal, organizational and technological resilience concepts, in the hope to increase critical infrastructure resilience. For this paper, we performed research on how to include societal resilience as a form of measurement of the context of critical infrastructure resilience. Because one of the main purposes of critical infrastructure (CI) is to deliver services to the society, we believe that societal resilience is an important factor that should be considered when assessing the overall CI resilience. We found that existing methods for CI resilience assessment focus mainly on technical aspects and therefore that is was necessary to develop a resilience model that take social factors into account. The model developed within the project IMPROVER aims to include the community’s expectations of infrastructure operators as well as information sharing with the public and planning processes. By considering such aspects, the IMPROVER framework not only helps operators to increase the resilience of their infrastructures on the technical or organizational side, but aims to strengthen community resilience as a whole. This will further be achieved by taking interdependencies between critical infrastructures into consideration. The knowledge gained during this project will enrich current European policies and practices for improved disaster risk management. The framework for societal resilience analysis is based on three dimensions for societal resilience; coping capacity, adaptive capacity and transformative capacity which are capacities that have been recognized throughout a widespread literature review in the field. A set of indicators have been defined that describe a community’s maturity within these resilience dimensions. Further, the indicators are categorized into six community assets that need to be accessible and utilized in such a way that they allow responding to changes and unforeseen circumstances. We conclude that the societal resilience model developed within the project IMPROVER can give a good indication of the level of societal resilience to critical infrastructure operators.

Keywords: community resilience, critical infrastructure protection, critical infrastructure resilience, societal resilience

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

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Authors: Ghita Benayad

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Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

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Authors: Ebrahim Solgi, Zahra Hamedani, Behrouz Mohammad Kari, Ruwan Fernando, Henry Skates

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The use of thermal energy storage (TES) as part of a passive design strategy can reduce a building’s energy demand. TES materials do this by increasing the lag between energy consumption and energy supply by absorbing, storing and releasing energy in a controlled manner. The increase of lightweight construction in the building industry has made it harder to utilize thermal mass. Consequently, Phase Change Materials (PCMs) are a promising alternative as they can be manufactured in thin layers and used with lightweight construction to store latent heat. This research investigates utilizing PCMs, with the first step being measuring their performance under experimental conditions. To do this requires three components. The first is a calorimeter for measuring indoor thermal conditions, the second is a pyranometer for recording the solar conditions: global, diffuse and direct radiation and the third is a data-logger for recording temperature and humidity for the studied period. This paper reports on the design and implementation of an experimental setup used to measure the thermal characteristics of PCMs as part of a wall construction. The experimental model has been simulated with the software EnergyPlus to create a reliable simulation model that warrants further investigation.

Keywords: phase change materials, EnergyPlus, experimental evaluation, night ventilation

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Authors: H. Merzouka, D. T. Talantikitea, S. Fettouchib, L. Nessarkb

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Recently New nanosized materials studies are in huge expansion worldwide. They play a fundamental role in various industrial applications thanks their unique and functional properties. Moreover, in recent years, a great effort has been made in design and control fabrication of nano-structured semiconductors such as zinc sulphide. In recent years, much attention has been accorded in doped and co-doped ZnS to improve the ZnS films quality. We present in this work preparation and characterization of ZnS and Cu doped ZnS thin films. Nanoparticles ZnS and Cu doped ZnS films are prepared by chemical bath deposition method (CBD), for various dopant concentrations. Thin films are deposed onto commercial microscope glass slides substrates. Thiourea is used as sulfide ion source, zinc acetate as zinc ion source and copper acetate as Cu ion source in alkaline bath at 90 °C. X-ray diffraction (XRD) analyses are carried out at room temperature on films and powders with a powder diffractometer, using CuK radiation. The average grain size obtained from the Debye–Scherrer’s formula is around 10 nm. Films morphology is examined by scanning electron microscopy. IR spectra of representative sample are recorded with the FTIR between 400 and 4000 cm-1. The transmittance is more than 70 % is performed with the UV–VIS spectrometer in the wavelength range 200–800 nm. This value is enhanced by Cu doping.

Keywords: Cu doped ZnS, nanostructured, thin films, CBD, XRD, FTIR

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Authors: S. Apprich, F. Wulle, A. Lechler, A. Pott, A. Verl

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Large-scale machine tools for the manufacturing of large work pieces, e.g. blades, casings or gears for wind turbines, feature pose-dependent dynamic behavior. Small structural damping coefficients lead to long decay times for structural vibrations that have negative impacts on the production process. Typically, these vibrations are handled by increasing the stiffness of the structure by adding mass. That is counterproductive to the needs of sustainable manufacturing as it leads to higher resource consumption both in material and in energy. Recent research activities have led to higher resource efficiency by radical mass reduction that rely on control-integrated active vibration avoidance and damping methods. These control methods depend on information describing the dynamic behavior of the controlled machine tools in order to tune the avoidance or reduction method parameters according to the current state of the machine. The paper presents the appearance, consequences and challenges of the pose-dependent dynamic behavior of lightweight large-scale machine tool structures in production. The paper starts with the theoretical introduction of the challenges of lightweight machine tool structures resulting from reduced stiffness. The statement of the pose-dependent dynamic behavior is corroborated by the results of the experimental modal analysis of a lightweight test structure. Afterwards, the consequences of the pose-dependent dynamic behavior of lightweight machine tool structures for the use of active control and vibration reduction methods are explained. Based on the state of the art on pose-dependent dynamic machine tool models and the modal investigation of an FE-model of the lightweight test structure, the criteria for a pose-dependent model for use in vibration reduction are derived. The description of the approach for a general pose-dependent model of the dynamic behavior of large lightweight machine tools that provides the necessary input to the aforementioned vibration avoidance and reduction methods to properly tackle machine vibrations is the outlook of the paper.

Keywords: dynamic behavior, lightweight, machine tool, pose-dependency

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Authors: Kayla Marie Sarte

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This study sought to describe mother tongue-based classes in the light of classroom interactional discourse using the Sinclair and Coulthard model. It specifically identified the exchanges, grouped into Teaching and Boundary types; moves, coded as Opening, Answering and Feedback; and the occurrence of the 13 acts (Bid, Cue, Nominate, Reply, React, Acknowledge, Clue, Accept, Evaluate, Loop, Comment, Starter, Conclusion, Aside and Silent Stress) in the classroom, and determined what these reveal about the teaching and learning processes in the MTB classroom. Being a qualitative study, using the Single Collective Case Within-Site (embedded) design, varied data collection procedures such as non-participant observations, audio-recordings and transcription of MTB classes, and semi-structured interviews were utilized. The results revealed the presence of all the codes in the model (except for the silent stress) which also implied that the Hiligaynon mother tongue-based class was eclectic, cultural and communicative, and had a healthy, analytical and focused environment which aligned with the aims of MTB-MLE, and affirmed the purported benefits of mother tongue teaching. Through the study, gaps in the mother tongue teaching and learning were also identified which involved the difficulty of children in memorizing Hiligaynon terms expressed in English in their homes and in the communities.

Keywords: discourse analysis, language teaching and learning, mother tongue-based education, multilingualism

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Authors: Daniel Asiamah Ameyaw

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This research attempts to investigate how lecturer evaluation makes a difference in enhancing higher education teaching and learning processes. The research questions to guide this research work states first as, “What are the perspectives on the difference made by evaluating academic teachers in order to enhance higher education teaching and learning processes?” and second, “What are the implications of the findings for Policy and Practice?” Data for this research was collected mainly through interviewing and partly documents review. Data analysis was conducted under the framework of grounded theory. The findings showed that for individual lecturer level, lecturer evaluation provides a continuous improvement of teaching strategies, and serves as source of data for research on teaching. At the individual student level, it enhances students learning process; serving as source of information for course selection by students; and by making students feel recognised in the educational process. At the institutional level, it noted that lecturer evaluation is useful in personnel and management decision making; it assures stakeholders of quality teaching and learning by setting up standards for lecturers; and it enables institutions to identify skill requirement and needs as a basis for organising workshops. Lecturer evaluation is useful at national level in terms of guaranteeing the competencies of graduates who then provide the needed manpower requirement of the nation. Besides, it mentioned that resource allocation to higher educational institution is based largely on quality of the programmes being run by the institution. The researcher concluded, that the findings have implications for policy and practice, therefore, higher education managers are expected to ensure that policy is implemented as planned by policy-makers so that the objectives can successfully be achieved.

Keywords: academic quality, higher education, lecturer evaluation, teaching and learning processes

Procedia PDF Downloads 130

Authors: Michael Ricardo Lang, AdriéLle Costa, Ivana Iesbik, Karine Haag, Leonardo Trindade Buffara, Oscar Reimann Junior, Chelin Auswaldt Steclan

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Stroke affects not only the individual, but has significant impacts on the social and family context. Therefore, it is necessary to know the peculiarities of each region, in order to contribute to regional public health policies effectively. Thus, the present study discusses biomarkers in a post-stroke population, admitted to a stroke unit (U-stroke) of reference in the southern region of Brazil. Biomarkers were analyzed, such as age, length of stay, mortality rate, survival time, risk factors and family history of stroke in patients after ischemic stroke. In this studied population, comparing men and women, it was identified that men were more affected than women, and the average age of women affected was higher, as they also had the highest mortality rate and the shortest hospital stay. The risk factors identified here were according to the global scenario; with SAH being the most frequent and those associated with sedentary lifestyle in women the most frequent (dyspilipidemia, heart disease and obesity). In view of this, the importance of studies that characterize populations regionally is evident, strengthening the strategic planning of policies in favor of health care.

Keywords: biomarkers, sex, stroke, stroke unit, population

Procedia PDF Downloads 245