Search results for: machine learning applications

Authors: C. M. Sapkota, B. P. Sapkota

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Background: Continuous developments in science and technology are increasing the availability of thousands of medical devices – all of which should be of good quality and used appropriately to address global health challenges. It is obvious that bio medical devices are becoming ever more indispensable in health service delivery and among the key workforce responsible for their design, development, regulation, evaluation and training in their use: biomedical technician (BMET) is the crucial. As a pivotal member of health workforce, biomedical technicians are an essential component of the quality health service delivery mechanism supporting the attainment of the Sustainable Development Goals. Methods: The study was based on cross sectional descriptive design. Indicators measuring the quality of health services were assessed in Mechi Zonal Hospital (MZH) and Sagarmatha Zonal Hospital (SZH). Indicators were calculated based on the data about hospital utilization and performance of 2018 available in Medical record section of both hospitals. MZH had employed the BMET during 2018 but SZH had no BMET in 2018.Focus Group Discussion with health workers in both hospitals was conducted to validate the hospital records. Client exit interview was conducted to assess the level of client satisfaction in both the hospitals. Results: In MZH there was round the clock availability and utilization of Radio diagnostics equipment, Laboratory equipment. Operation Theater was functional throughout the year. Bed Occupancy rate in MZH was 97% but in SZH it was only 63%.In SZH, OT was functional only 54% of the days in 2018. CT scan machine was just installed but not functional. Computerized X-Ray in SZH was functional only in 72% of the days. Level of client satisfaction was 87% in MZH but was just 43% in SZH. MZH performed all (256) the Caesarean Sections but SZH performed only 36% of 210 Caesarean Sections in 2018. In annual performance ranking of Government Hospitals, MZH was placed in 1st rank while as SZH was placed in 19th rank out of 32 referral hospitals nationwide in 2018. Conclusion: Biomedical technicians are the crucial member of the human resource for health team with the pivotal role. Trained and qualified BMET professionals are required within health-care systems in order to design, evaluate, regulate, acquire, maintain, manage and train on safe medical technologies. Applying knowledge of engineering and technology to health-care systems to ensure availability, affordability, accessibility, acceptability and utilization of the safer, higher quality, effective, appropriate and socially acceptable bio medical technology to populations for preventive, promotive, curative, rehabilitative and palliative care across all levels of the health service delivery.

Keywords: biomedical equipment technicians, BMET, human resources for health, HRH, quality health service, rural hospitals

Procedia PDF Downloads 122

Authors: A.Boularouk, F. Chouikh, M. Lamri, H. Moualkia, Y. Bouznit

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The principal aim of this study is to considerably reduce the resistivity of the SnO2 thin layers. In this order, we have doped tin oxide with aluminum and antimony incorporation with different atomic percentages (0 and 4%). All the pure and doped SnO2 films were grown by simple, flexible and cost-effective Automatic Spray Pyrolysis Method (ASPM) on glass substrates at a temperature of 350 °C. The microstructural, optical, morphological and electrical properties of the films have been studied. The XRD results demonstrate that all films have polycrystalline nature with a tetragonal rutile structure and exhibit the (200) preferential orientation. It has been observed that all the dopants are soluble in the SnO2 matrix without forming secondary phases. However, dopant introduction does not modify the film growth orientation. The crystallite size of the pure SnO2 film is about 36 nm. The films are highly transparent in the visible region with an average transmittance reaching up to 80% and it slightly reduces with increasing doping concentration (Al and Sb). The optical band gap value was evaluated between 3.60 eV and 3.75 eV as a function of doping. The SEM image reveals that all films are nanostructured, densely continuous, with good adhesion to the substrate. We note again that the surface morphology change with the type and concentration dopant. The minimum resistivity is 0.689*10-4, which is observed for SnO2 film doped 4% Al. This film shows better properties and is considered the best among all films. Finally, we concluded that the physical properties of the pure and doped SnO2 films grown on a glass substrate by ASPM strongly depend on the type and concentration dopant (Al and Sb) and have highly desirable optical and electrical properties and are promising materials for several applications.

Keywords: tin oxide, automatic spray, Al and Sb doped, transmittance, MEB, XRD and UV-VIS

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Authors: Abiodun Ezekiel Adesina, Alice M. Olagunju

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This study determined the effects of Computer Assisted Instructions (CAI) and Academic Self-Concepts (ASC) on pre-service teachers’ achievement in AE concepts in CoE in Southwest, Nigeria. The study adopted pretest-posttest, control group, quasi-experimental design. Six CoE with e-library facilities were purposively selected. Two hundred and thirty-two intact 200 level Agricultural education students offering introduction to AE course across the six CoE were participants. The participants were assigned to three groups (D&PM, 77, TM, 73 and control, 82). Treatment lasted eight weeks. The AE achievement test (r=0.76), pre-service teachers’ ASC Scale (r=0.81); instructional guides for tutorial (r=0.76), drill and practice (r=0.81) and conventional lecture modes (r=0.83), and teacher performance assessment sheet were used for data collection. Data were analysed using analysis of covariance and Scheffe post-hoc at 0.05 level of significance. The participants were 55.6% female with mean age of 20.8 years. Treatment had significant main effects on pre-service teachers’ achievement (F(2,207)=60.52; η²=0.21; p < 0.05). Participants in D&PM (x̄ =27.83) had the best achievement compared to those in TM (x̄ =25.41) and control (x̄ =18.64) groups. ASC had significant main effect on pre-service teachers’ achievement (F(1,207)=22.011; η²=0.166; p < 0.05). Participants with high ASC (x̄ =27.52) had better achievement compared to those with low ASC (x̄ =22.37). The drill and practice and tutorial instructional modes enhanced students’ achievement in Agricultural Economics concepts. Therefore, the two instructional modes should be adopted for improved learning outcomes in agricultural economics concepts among pre-service teachers.

Keywords: achievement in agricultural economics concepts, colleges of education in southwestern Nigeria, computer-assisted instruction, drill and practice instructional mode, tutorial instructional mode

Procedia PDF Downloads 199

Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: Aisultan Shoiynbek, Darkhan Kuanyshbay, Paulo Menezes, Akbayan Bekarystankyzy, Assylbek Mukhametzhanov, Temirlan Shoiynbek

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Speech emotion recognition (SER) has received increasing research interest in recent years. It is a common practice to utilize emotional speech collected under controlled conditions recorded by actors imitating and artificially producing emotions in front of a microphone. There are four issues related to that approach: emotions are not natural, meaning that machines are learning to recognize fake emotions; emotions are very limited in quantity and poor in variety of speaking; there is some language dependency in SER; consequently, each time researchers want to start work with SER, they need to find a good emotional database in their language. This paper proposes an approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describes the sequence of actions involved in the proposed approach. One of the first objectives in the sequence of actions is the speech detection issue. The paper provides a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To investigate the working capacity of the developed model, an analysis of speech detection and extraction from real tasks has been performed.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Carmen E. Pérez-Donado, Fernando Pérez-Muñoz, Rosa N. Chávez-Jáuregui

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Plantain contains starch as the majority component and represents a relevant source of this carbohydrate. Starches from different cultivars of plantain and bananas have been studied for industrialization purposes due to their morphological and thermal characteristics and their influence on food products. This study aimed to characterize the physical, chemical, and thermal properties of starch from three different plantains cultivated in Puerto Rico: Maricongo, Maiden, and FHIA 20. Amylose and amylopectin content, color, granular size, morphology, and thermal properties were determined. According to the content of amylose in starches, FHIA 20 starch presented minor content of the three cultivars studied. In terms of color, Maiden and FHIA 20 starch exhibited a significantly higher whiteness index comparing their values with Maricongo starch. The starches of the three cultivars had an elongated-ovoid morphology, with a smooth surface and a non-porous appearance. Regardless of similarities in their morphology, FHIA 20 showed a lower aspect ratio, which meant that their granules tended to be more elongated granules. Comparing the thermal properties of starches, it was found that the initial gelatinization temperature of the starch of the cultivars was similar. However, the final gelatinization temperatures of the starches belonging to the cultivars Maricongo (79.69°C) and Maiden (77.40°C) were similar, whereas FHIA 20 starch presented a noticeably higher final gelatinization temperature (87.95°C) and transition enthalpy. Despite source similarities, starches from plantain cultivars showed differences in their composition and thermal behavior. Therefore, this represents an opportunity to diversify their use in food-related applications.

Keywords: aspect ratio, morphology, Musa spp., starch, thermal properties

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Authors: Popoola Sulaimon Akorede, Muinat A. Agbabiaka-Mustapha

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The Quranic / piazza school where the rudiments of Islam are being imparted from the teaching of Arabic/ Quranic alphabets which later metamorphosized to higher fundamental principles of Islam is the major determinant of the existence of Islam in any part of south western Nigeria. In other words, one can successfully say that where there is a few or non-existence of such schools in that part of the country, the practice of the religion of Islam would be either very low or not existing at all. However, it has been discovered in the modern worlds that several challenges are militating against the development of these schools and among these challenges are poor admission policy, inadequate facilities such as learning environment and instructional materials, curriculum inadequacy and the management and the administration of the schools which failed to change in order to meet the modern contemporary Educational challenges. The focus of this paper therefore is to improve the conditions of these basic Islamic schools through the introduction of quality assurance and integrating accreditation Exercise to improve their status in order to enhance economic empowerment and to further their educational career in the future so that they will be able to compete favourably among the graduates of conventional universities. The scope of this study is limited to only seven (7) states of yorubaland and with only three (3) proprietors/ schools from each state which are Lagos, Oyo, Ogun, Osun, Ekiti, Ondo and parts of Kwara State. The study revealed that quality assurance as well as accreditation exercise are lacking in all the local Arabic/Quranic schools. Suggestions are proffered towards correcting the anomalies in these schools so that they can meet the modern Educational standard.

Keywords: accreditation, quality assurance, Quranic schools, South-western Nigeria

Procedia PDF Downloads 374

Authors: Daniel Ihemtuge Akim, Micheal O. Ikeanumba

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This research focused on team teaching; students perception, challenges, and remedies for effective implementation, a case study of the department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria. It seeks to address the misconception by students on the use of team teaching as a methodology for learning. Five purposes and five research questions guided this study. Descriptive survey design was used in the study. The students of biology department enrolled in both Bachelor degree and National Certificate in Education in Alvan Ikoku Federal College of Education, Owerri, formed the population size. Simple random sampling technique was used to select the sampled students and 20% of whole lecturers were selected out of the whole given sample size of three hundred and forty (340). The instrument used for data collection was structured 4 point Likert scale questionnaire and analysis was made using mean method. The result revealed that poor time management by lectures, lack of lecture venues, manpower are some of the challenges hindering the effective implementation of team teaching. It was also observed that students perform better in academic when team teaching approach is used than single teaching approach. Finally, recommendations made suggested that teachers involved in team teaching should work together with their teaching strategies and within the time frame to achieve the stated objectives.

Keywords: challenges, implementation, perception, team teaching

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Authors: Taher M. Abou-deif, Esmail M. El-Bialy, Essam E. Khalil

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The paper is devoted to numerically investigating the influence of the air supply outlets geometry on human comfort inside living looms. A computational fluid dynamics model is developed to examine the air flow characteristics of a room with different supply air diffusers. The work focuses on air flow patterns, thermal behavior in the room with few number of occupants. As an input to the full-scale 3-D room model, a 2-D air supply diffuser model that supplies direction and magnitude of air flow into the room is developed. Air distribution effect on thermal comfort parameters was investigated depending on changing the air supply diffusers type, angles and velocity. Air supply diffusers locations and numbers were also investigated. The pre-processor Gambit is used to create the geometric model with parametric features. Commercially available simulation software “Fluent 6.3” is incorporated to solve the differential equations governing the conservation of mass, three momentum and energy in the processing of air flow distribution. Turbulence effects of the flow are represented by the well-developed two equation turbulence model. In this work, the so-called standard k-ε turbulence model, one of the most widespread turbulence models for industrial applications, was utilized. Basic parameters included in this work are air dry bulb temperature, air velocity, relative humidity and turbulence parameters are used for numerical predictions of indoor air distribution and thermal comfort. The thermal comfort predictions through this work were based on ADPI (Air Diffusion Performance Index),the PMV (Predicted Mean Vote) model and the PPD (Percentage People Dissatisfied) model, the PMV and PPD were estimated using Fanger’s model.

Keywords: thermal comfort, Fanger's model, ADPI, energy effeciency

Procedia PDF Downloads 405

Authors: Raviteja Chintala

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Water shortage in many areas of the world have predominantly increased the demand for efficient methods involved in the production of drinking water, So purification of water invoking cost effective and efficient methods is a challenging field of research. In this regard, Reverse osmosis membrane desalination of both seawater and inland brackish water is currently being deployed in various locations around the world. In the present work an attempt is made to integrate these existing technologies with novel method, Wherein carbon nanotubes at the lab scale are prepared which further replace activated carbon tubes being used traditionally. This has proven to enhance the efficiency of the water filter, Effectively neutralising most of the organic impurities. Furthermore, This ensures the reduction in TDS. Carbon nanotubes have wide range in scope of applications such as composite reinforcements, Field emitters, Sensors, Energy storage and energy conversion devices and catalysts support phases, Because of their unusual mechanical, Electrical, Thermal and structural properties. In particular, The large specific surface area, as well as the high chemical and thermal stability, Makes carbon nanotube an attractive adsorbent in waste water treatment. Carbon nanotubes are effective in eliminating these harmful media from water as an adsorbent. In this work, Candle soot method has been incorporated for the preparation of carbon nanotubes and mixed with activated charcoal in different compositions. The effect of composition change is monitored by using TDS measuring meter. As the composition of Nano carbon increases, The TDS of the water gradually decreases. In order to enhance the life time for carbon filter, Nano tubes are provided with larger surface area.

Keywords: TDS (Total Dissolved Solids), carbon nanotubes, water, candle soot

Procedia PDF Downloads 333

Authors: Ritwik Dutta, Marylin Wolf

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This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver

Procedia PDF Downloads 383

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

Procedia PDF Downloads 272

Authors: Gabriella Dravecz, László Péter, Zsolt Kis

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Abstract— The growth of optical LiNbO3 single crystal and its physical and chemical properties are well known on the macroscopic scale. Nowadays the rare-earth doped single crystals became important for coherent quantum optical experiments: electromagnetically induced transparency, slow down of light pulses, coherent quantum memory. The expansion of applications is increasingly requiring the production of nano scaled LiNbO3 particles. For example, rare-earth doped nanoscaled particles of lithium niobate can be act like single photon source which can be the bases of a coding system of the quantum computer providing complete inaccessibility to strangers. The polyol method is a chemical synthesis where oxide formation occurs instead of hydroxide because of the high temperature. Moreover the polyol medium limits the growth and agglomeration of the grains producing particles with the diameter of 30-200 nm. In this work nano scaled LiNbO3 was prepared by the polyol method. The starting materials (niobium oxalate and LiOH) were diluted in H2O2. Then it was suspended in ethylene glycol and heated up to about the boiling point of the mixture with intensive stirring. After the thermal equilibrium was reached, the mixture was kept in this temperature for 4 hours. The suspension was cooled overnight. The mixture was centrifuged and the particles were filtered. Dynamic Light Scattering (DLS) measurement was carried out and the size of the particles were found to be 80-100 nms. This was confirmed by Scanning Electron Microscope (SEM) investigations. The element analysis of SEM showed large amount of Nb in the sample. The production of LiNbO3 nano particles were succesful by the polyol method. The agglomeration of the particles were avoided and the size of 80-100nm could be reached.

Keywords: lithium-niobate, nanoparticles, polyol, SEM

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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

Procedia PDF Downloads 334

Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: Adrien Cornille, Sylvain Caillol, Bernard Boutevon

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The development of polyurethanes began in 1937 at I. G. Farbenindustrie where Bayer with coworkers discovered the addition polymerization reaction between diisocyanates and diols. Since their discovery, the demand in PU has continued to increase and it will attain in 2016 a production of 18 million tons. However, isocyanates compounds are harmful to human and environment. Methylene diphenyl 4,4’-diisocyanate (MDI) and toluene diisocyanate (TDI), the most widely used isocyanates in PU industry, are classified as CMR (Carcinogen, Mutagen, and Reprotoxic). In order to design isocyanate-free materials, an interesting alternative is the use of Polyhydroxyurethanes (PHUs) by reaction between cyclic carbonate and polyfunctional amines. The main problem concerning PHUs synthesis relates to the low reactivity of carbonate/amine reaction. To solve this issue, many studies in the literature have been conducted to design PHU from more reactive cyclic-carbonates, bearing electro-withdrawing substituent or by using six-membered, seven-membered or thio-cyclic carbonate. The main drawback of all these systems remains the low molar masses obtained for the synthesized PHUs, which hinders their use for material applications. Therefore, we developed another strategy to afford new hybrid PHU with high conversion. This very innovative two-step approach consists in the first step in the synthesis of aminotelechelic PHU oligomers with different chain length from bis-cyclic carbonate with different excess of primary amine functions. In the second step, these aminotelechelic PHU oligomers were used in formulation with biobased epoxy monomers (from cashew nut shell liquid and tannins) to synthesize hybrid polyepoxyurethane polymers. These materials were then characterized by thermal and mechanical analyses.

Keywords: polyurethane, polyhydroxyurethane, aminotelechelic NIPU oligomers, carbonates, epoxy, amine, epoxyurethane polymers, hybrid polymers

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Authors: Jareeluk Ratanaphan

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The purposed of this research were; 1. To survey the teacher’s needs on knowledge about special education management for special needs student 2. Development of distance training packages for teacher on special education management for special needs student 3. to study the effects of using the packages on trainee’s achievement 4. to study the effects of using the packages on trainee’s opinion on the distance training packages. The design of the experiment was research and development. The research sample for survey were 86 teachers, and 22 teachers for study the effects of using the packages on achievement and opinion. The research instrument comprised: 1) training packages on special education management for special needs student 2) achievement test 3) questionnaire. Mean, percentage, standard deviation, t-test and content analysis were used for data analysis. The findings of the research were as follows: 1. The teacher’s needs on knowledge about teaching for a learner with learning disability, mental retardation, autism, physical and health impairment and research in special education. 2. The package composed of special education management for special needs student document and manual of distance training packages. The document consisted by the name of packages, the explanation for the educator, content’s structure, concept, objectives, content and activities. Manual of distance training packages consisted by the explanation about a document, objectives, explanation about using the package, training schedule, and evaluation. The efficiency of packages was established at 79.50/81.35. 3. The results of using the packages were the posttest average scores of trainee’s achievement were higher than the pretest. 4. The trainee’s opinion on the package was at the highest level.

Keywords: distance training package, teacher, learner with special needs

Procedia PDF Downloads 481

Authors: Nasim Rasuli, Akram Ahmadi, Hossein Riahi, Zeinab Shariatmadari, Majid Ghorbani Nohooji, Pooyan Mehraban Joubani

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Cyanobacteria are one of the most promising sources of new biostimulants and have received much attention due to their diverse applications in biotechnology. These microorganisms enhance the growth and productivity of plants by producing plant growth stimulants and fixing atmospheric nitrogen. Thymus vulgaris L., a valuable medicinal plant from the Lamiaceae family, is widely distributed across the globe. essential oil of T. vulgaris is best characterized by the prominence of phenols, making them the key compounds in its composition. Lignin biosynthesis as a natural plant polyphenol plays a crucial role in promoting plant growth, strengthening cell walls, and increasing resistance to pathogens. In this study, the bioelicitor activity of five cyanobacterial suspensions including Anabaena torulosa ISB213, Nostoc calcicola ISB215, Nostoc ellipsosporum ISB217, Trichormus doliolum ISB214, and Oscillatoria sp. ISB2116 on the lignin content of the T. vulgaris L. was investigated. Pot experiments were performed by inoculation of a %2 algal extract to the soil of treated plants one week before planting and then every 20 days. After four months, the lignin content in the leaves of both treated and control plants was evaluated. The results demonstrated that the application of cyanobacteria significantly increased the lignin content in the leaves of treated plants compared to the control. The treatment with Oscillatoria sp. ISB216 and N. ellipsosporum ISB217 resulted in the highest lignin content, with an increase of 93.33% and 86.67%, respectively. These findings highlight the potential of cyanobacteria as bioelicitors, offering a viable alternative for enhancing the production of secondary metabolites in T. vulgaris. Consequently, this could contribute to the economic value of this medicinal plant.

Keywords: cyanobacteria, bioelicitor, thymus vulgaris, lignin

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Authors: E. P. Bhowmik, R. Singh

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Certain materials casually thrown away as by-product household waste, such as used tea leaves, used coffee remnants, eggshells, peanut husks, coconut coir, unwanted paper, and pencil shavings- have scope in the hidden properties that they offer as recyclable raw ingredients. This paper aims to explore and experiment with the sustainable potential of such disposed wastes, obtained from domestic and commercial backgrounds, that could otherwise contribute to the field of interior design if mass-collected and repurposed. Research has been conducted on available recorded methods of mass-collection, storage, and processing of such materials by certain brands, designers, and researchers, as well as the various application and angles possible with regards to re-usage. A questionnaire survey was carried out to understand the willingness of the demographics for efforts of the mass collection and their openness to such unconventional materials for interiors. An experiment was also conducted where the selected waste ingredients were used to create small samples that could be used as decorative panels. Comparisons were made for properties like color, smell, texture, relative durability, and weight- and accordingly, applications were suggested. The experiment, therefore, helped to propose to recycle of the common household as a potential surface finish for floors, walls, and ceilings, and even founding material for furniture and decor accessories such as pottery and lamp shades; for non-structural application in both residential and commercial interiors. Common by-product wastes often see their ends at landfills- laymen unaware of their sustainable possibilities dispose of them. However, processing these waste materials and repurposing them by incorporating them into interiors would serve as a sustainable alternative to ethical dilemmas in the construction of interior design/architecture elements.

Keywords: interior materials, mass-collection, sustainable, waste recycle

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Authors: Shivankar Agrawal, Sunil Kumar Deshmukh, Colin Barrow, Alok Adholeya

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A variety of genetic and environmental factors cause various cosmetics and dermatological problems. There are already claimed drugs available in market for treating these problems. However, the challenge remains in finding more potent, environmental friendly, causing minimal side effects and economical cosmeceuticals. This leads to an increased demand for natural cosmeceutical products in the last few decades. Plant derived ingredients are limited because plants either contain toxic metabolites, grow too slow or seasonal harvesting is a problem. The research work carried out in this project aims at isolation, characterization of marine fungal secondary metabolite and evaluating their potential use in future cosmetic skin care products. We have isolated and purified 35 morphologically different fungal isolates from various marine habitats of the India. These isolates have been functionally characterized for anti-tyrosinase, antioxidant and anti-acne activities. For molecular characterization, the Internal Transcribed spacer (ITS) region of 15 functionally active marine fungal isolates was amplified using universal primers, ITS1 and ITS4 and sequenced. Out of 15 marine fungal isolates crude extract of strains D4 (Aspergillus terreus) and P2 (Talaromyces stipitatus) showed 70% and 57% tyrosinase inhibition at 1mg/mL respectively. Strain D5 (Simplicillium lamellicola) has showed significant inhibition against Propionibacterium acnes and Staphylococcus epidermidis. In addition, all these strains also displayed DPPH- radical scavenging activity and may be utilized as skin cosmeceutical applications. Purification and characterization of crude extracts for identification of active lead molecule is under process.

Keywords: anti-acne, anti-tyrosinase, cosmeceutical, marine fungi

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Authors: Swati Sundararajan, Asit B. Samui, Prashant S. Kulkarni

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Polymeric ionic liquids combine the properties of ionic liquids and polymers into a single material which has gained massive interest in the recent years. These ionic liquids offer several advantages such as high phase change enthalpy, wide temperature range, chemical and thermal stability, non-volatility and the ability to make them task-specific. Separation of CO2 is an area of critical importance due to the concerns over greenhouse gasses leading to global warming. Thermal energy storage materials, also known as phase change materials absorb latent heat during fusion process and release the absorbed energy to the surrounding environment during crystallization. These materials retain this property over a number of cycles and therefore, are useful for bridging the gap between energy requirement and use. In an effort to develop materials, which will help in minimizing the growing energy demand and environmental concerns, a series of dicationic poly(ethylene glycol) based polymeric ionic liquids were synthesized. One part of an acrylate of poly(ethylene glycol) was reacted with imidazolium quarternizing agent and the second part was reacted with triazolium quarternizing agent. These two different monomers were then copolymerized to prepare dicationic polymeric ionic liquid. These materials were characterized for solid-liquid phase transition and the enthalpy by using differential scanning calorimetry. The CO2 capture studies were performed on a fabricated setup with varying pressure range from 1-20 atm. The findings regarding the prepared materials, having potential dual applications in the fields of thermal energy storage and CO2 capture, will be discussed in the presentation.

Keywords: CO2 capture, phase change materials, polyethylene glycol, polymeric ionic liquids, thermal energy storage

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Authors: Nedal N. Marei, Nashaat Nassar

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Many treatment techniques have been used to remove the soluble pollutants from wastewater as; dyes and metal ions which could be found in rich amount in the used water of the textile and tanneries industry. The effluents from these industries are complex, containing a wide variety of dyes and other contaminants, such as dispersants, acids, bases, salts, detergents, humectants, oxidants, and others. These techniques can be divided into physical, chemical, and biological methods. Adsorption has been developed as an efficient method for the removal of heavy metals from contaminated water and soil. It is now recognized as an effective method for the removal of both organic and inorganic pollutants from wastewaters. Nanosize materials are new functional materials, which offer high surface area and have come up as effective adsorbents. Nano alumina is one of the most important ceramic materials widely used as an electrical insulator, presenting exceptionally high resistance to chemical agents, as well as giving excellent performance as a catalyst for many chemical reactions, in microelectronic, membrane applications, and water and wastewater treatment. In this study, methylene blue (MB) dye has been used as model dye of textile wastewater in order to synthesize a synthetic MB wastewater. NiO nanoparticles were added in small percentage in the sand packed bed adsorption columns to remove the MB from the synthetic textile wastewater. Moreover, different parameters have been evaluated; flow of the synthetic wastewater, pH, height of the bed, percentage of the NiO to the sand in the packed material. Different mathematical models where employed to find the proper model which describe the experimental data and help to analyze the mechanism of the MB adsorption. This study will provide good understanding of the dyes adsorption using metal oxide nanoparticles in the classical sand bed.

Keywords: adsorption, column, nanoparticles, methylene

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Authors: Amit Keshav, Alok Sharma, Bidyut Mazumdar

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Colocasia esculenta leaves and roots are widely used in Asian countries, such as, India, Srilanka and Pakistan, as food and feed material. The root is high in carbohydrates and rich in zinc. The leaves and stalks are often traditionally preserved to be eaten in dry season. Leaf juice is stimulant, expectorant, astringent, appetizer, and otalgia. Looking at the medicinal uses of the plant leaves; phytochemicals were extracted from the plant leaves and were characterized using Fourier-transform infrared spectroscopy (FTIR) to find the functional groups. Phytochemical analysis of Colocasia esculenta (L.) leaf was studied using three solvents (methanol, chloroform, and ethanol) with soxhlet apparatus. Powder of the leaves was employed to obtain the extracts, which was qualitatively and quantitatively analyzed for phytochemical content using standard methods. Phytochemical constituents were abundant in the leave extract. Leaf was found to have various phytochemicals such as alkaloids, glycosides, flavonoids, terpenoids, saponins, oxalates and phenols etc., which could have lot of medicinal benefits such as reducing headache, treatment of congestive heart failure, prevent oxidative cell damage etc. These phytochemicals were identified using UV spectrophotometer and results were presented. In order to find the antioxidant activity of the extract, DPPH (2,2-diphenyl-1-picrylhydrazyl) method was employed using ascorbic acid as standard. DPPH scavenging activity of ascorbic acid was found to be 84%, whereas for ethanol it was observed to be 78.92%, for methanol: 76.46% and for chloroform: 72.46%. Looking at the high antioxidant activity, Colocasia esculenta may be recommended for medicinal applications. The characterizations of functional groups were analyzed using FTIR spectroscopy.

Keywords: antioxidant activity, Colocasia esculenta, leaves, characterization, FTIR

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Authors: Sahar Heidary, Ramin Ghasemi Shayan

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The recent coronavirus disease 2019 (COVID-19) occurrence has carried considerabletrials to the world health system, comprising the training of dental and maxillofacial radiology (DMFR). DMFR will keep avital role in healthcare throughout this disaster. Severe acute breathing disease coronavirus 2 (SARS-CoV-2), the virus producing the current coronavirus disease 2019 (COVID-19) pandemic, is not only extremely contagious but can make solemn consequences in susceptible persons comprising dental patients and dental health care personnel (DHCPs). Reactions to COVID-19 have been available by the Cores for Infection Switch and Inhibition and the American Dental Association, but a more detailed answer is necessary for the harmless preparation of oral and maxillofacial radiology. Our goal is to evaluation the existing information just how the illness threatens patients and DHCPs and how to define which patients are possible to be SARS-CoV-2 infected; study how the usage of private shielding utensils and contamination control measures based on recent top observes, and knowledge can decrease the danger of virus spread in radiologic trials; and scrutinize how intraoral radiography, with its actually superior danger of scattering the infection, might be changed by extraoralradiographic methods for definite diagnostic jobs. In the pandemic, teleradiology has been extensively recycled for diagnostic determinations of COVID-19 patients, for discussions with radiologists in crisis cases, or managing of distance among radiology clinics. Dentists can have the digital radiographic images of their emergency patients through online service area also by electronic message or messaging applications to view in their smart phones, laptops, or other electronic devices.

Keywords: radiology, dental, oral, COVID-19, infection

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Authors: Mohammed Ahmed Ahmed Odah

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DNA barcoding is a crucial method for assessing and monitoring species diversity amidst escalating threats to global biodiversity. The author explores DNA barcoding's potential as a robust and reliable tool for biodiversity assessment. It begins with a comprehensive review of existing literature, delving into the theoretical foundations, methodologies and applications of DNA barcoding. The suitability of various DNA regions, like the COI gene, as universal barcodes is extensively investigated. Additionally, the advantages and limitations of different DNA sequencing technologies and bioinformatics tools are evaluated within the context of DNA barcoding. To evaluate the efficacy of DNA barcoding, diverse ecosystems, including terrestrial, freshwater and marine habitats, are sampled. Extracted DNA from collected specimens undergoes amplification and sequencing of the target barcode region. Comparison of the obtained DNA sequences with reference databases allows for the identification and classification of the sampled organisms. Findings demonstrate that DNA barcoding accurately identifies species, even in cases where morphological identification proves challenging. Moreover, it sheds light on cryptic and endangered species, aiding conservation efforts. The author also investigates patterns of genetic diversity and evolutionary relationships among different taxa through the analysis of genetic data. This research contributes to the growing knowledge of DNA barcoding and its applicability for biodiversity assessment. The advantages of this approach, such as speed, accuracy and cost-effectiveness, are highlighted, along with areas for improvement. By unlocking the genetic code, DNA barcoding enhances our understanding of biodiversity, supports conservation initiatives and informs evidence-based decision-making for the sustainable management of ecosystems.

Keywords: DNA barcoding, biodiversity assessment, genetic code, species identification, taxonomic resolution, next-generation sequencing

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Authors: Alireza Arab, Morteza Elsa, Amirhossein Moghanian

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In this study, experiments were carried out to achieve a promising multifunctional and modified silicate based bioactive glass (BG). The main aim of the study was investigating the effect of lithium (Li) and magnesium (Mg) substitution, on in vitro bioactivity of substituted-58S BG. Moreover, it is noteworthy to state that modified BGs were synthesized in 60SiO₂–(36-x)CaO–4P₂O₅–(x)Li₂O and 60SiO₂–(36-x)CaO–4P₂O₅–(x)MgO (where x = 0, 5, 10 mol.%) quaternary systems, by sol-gel method. Their performance was investigated through different aspects such as biocompatibility, antibacterial activity as well as their effect on alkaline phosphatase (ALP) activity, and proliferation of MC3T3 cells. The antibacterial efficiency was evaluated against methicillin-resistant Staphylococcus aureus bacteria. To do so, CaO was substituted with Li₂O and MgO up to 10 mol % in 58S-BGs and then samples were immersed in simulated body fluid up to 14 days and then, characterized by X-ray diffraction, Fourier transform infrared spectroscopy, inductively coupled plasma atomic emission spectrometry, and scanning electron microscopy. Results indicated that this modification led to a retarding effect on in vitro hydroxyapatite (HA) formation due to the lower supersaturation degree for nucleation of HA compared with 58s-BG. Meanwhile, magnesium revealed further pronounced effect. The 3-(4,5 dimethylthiazol-2-yl)-2,5 diphenyltetrazolium bromide (MTT) and ALP analysis illustrated that substitutions of both Li₂O and MgO, up to 5 mol %, had increasing effect on biocompatibility and stimulating proliferation of the pre-osteoblast MC3T3 cells in comparison to the control specimen. Regarding to bactericidal efficiency, the substitution of either Li or Mg for Ca in the 58s BG composition led to statistically significant difference in antibacterial behaviors of substituted-BGs. Meanwhile, the sample containing 5 mol % CaO/Li₂O substitution (BG-5L) was selected as a multifunctional biomaterial in bone repair/regeneration due to the improved biocompatibility, enhanced ALP activity and antibacterial efficiency among all of the synthesized L-BGs and M-BGs.

Keywords: alkaline, alkaline earth, bioactivity, biomedical applications, sol-gel processes

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Authors: Iwan Cony Setiadi, Aulia M. T. Nasution

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The multispectral imaging (MSI) technique has been used for skin analysis, especially for distant mapping of in-vivo skin chromophores by analyzing spectral data at each reflected image pixel. For ergonomic purpose, our multispectral imaging system is decomposed in two parts: a light source compartment based on LED with 11 different wavelenghts and a monochromatic 8-Bit CCD camera with C-Mount Objective Lens. The software based on GUI MATLAB to control the system was also developed. Our system provides 11 monoband images and is coupled with a software reconstructing hyperspectral cubes from these multispectral images. In this paper, we proposed a new method to build a hyperspectral reflectance cube based on artificial neural network algorithm. After preliminary corrections, a neural network is trained using the 32 natural color from X-Rite Color Checker Passport. The learning procedure involves acquisition, by a spectrophotometer. This neural network is then used to retrieve a megapixel multispectral cube between 380 and 880 nm with a 5 nm resolution from a low-spectral-resolution multispectral acquisition. As hyperspectral cubes contain spectra for each pixel; comparison should be done between the theoretical values from the spectrophotometer and the reconstructed spectrum. To evaluate the performance of reconstruction, we used the Goodness of Fit Coefficient (GFC) and Root Mean Squared Error (RMSE). To validate reconstruction, the set of 8 colour patches reconstructed by our MSI system and the one recorded by the spectrophotometer were compared. The average GFC was 0.9990 (standard deviation = 0.0010) and the average RMSE is 0.2167 (standard deviation = 0.064).

Keywords: multispectral imaging, reflectance cube, spectral reconstruction, artificial neural network

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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 55