Search results for: finte element method

Authors: Aleksandar Jovanovic, Katarina Kukic, Ana Uzelac, Dusan Teodorovic

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Wisdom of the Crowd (WoC) is a decentralized method that uses the collective intelligence of humans. Individual guesses may be far from the target, but when considered as a group, they converge on optimal solutions for a given problem. We will utilize WoC to address the challenge of controlling traffic lights within intersections from the streets of Kragujevac, Serbia. The problem at hand falls within the category of NP-hard problems. We will employ an algorithm that leverages the swarm intelligence of bees: Bee Colony Optimization (BCO). Data regarding traffic signal timing at a single intersection will be gathered from citizens through a survey. Results obtained in that manner will be compared to the BCO results for different traffic scenarios. We will use Vissim traffic simulation software as a tool to compare the performance of bees’ and humans’ collective intelligence.

Keywords: wisdom of the crowd, traffic signal control, combinatorial optimization, bee colony optimization

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Authors: John Gaber

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Objectives: Complementary and alternative medicine (CAM) is a medicine or health practice that is used alongside conventional practice. Nowadays, CAM is commonly used in North America and other countries, and there is a need for more scientific study to understand its efficacy in different clinical cases. This retrospective study explores the effectiveness and recovery time of CAMs such as cupping, acupuncture, and sotai to treat cases of non-specific low back pain (ANLBP). Methods: We assessed the effectiveness of acupuncture, cupping, and sotai methods on pain and for the treatment of ANLBP. We have compared the magnitude of pain relief using a pain scale assessment method to compare the efficacy of each treatment. The Face Pain Scale assessment was conducted before and 24 hours post-treatment. This retrospective study analyzed 40 patients and categorized them according to the treatment they received. The study included the control group, and the three intervention groups, each with ten patients. Each of the three intervention groups received one of the intervention methods. The first group received the cupping treatment, where cups were placed on the lower back of both sides on points: BL23, BL25, BL26, BL54, BL37, BL40, and BL57. After vacuuming, the cups will stay for 10-15 minutes under infrared light (IR) heating. IR heating is applied by an infrared heat lamp. The second group received the acupuncture treatment, placing needles on points: BL23, BL25, BL26, BL52BL54, GB30, BL37, BL40, BL57, BL59, BL60, and KI3. The needles will be simulated with IR light. The final group received the sotai treatment, a Japanese form of structural realignment that relieves pain, balance, and mobility -moving the body naturally and spontaneously towards a comfortable direction by focusing on the inner feeling and synchronizing with the patient’s breathing. The SPSS statistical software was used to analyze the data using repeated-measures ANOVA. The data collected demonstrates the change in the FPS assessment method value over the course of treatment. p<0.05 was considered statistically significant. Results: In the cupping, acupuncture, and sotai therapy groups, the mean of the FPS value reduced from 8.7±1.2, 8.8±1.2, 9.0±0.8 before the intervention to 3.5±1.4, 4.3±1.4, 3.3±1.3, 24 hours after the intervention, respectively. The data collected shows that the CAM methods included in this study all show improvements in pain relief 24 hours after treatment. Conclusion: Complementary and alternative medicine were developed to treat injuries and illnesses with the whole body in mind, designed to be used in addition to standard treatments. The data above shows that the use of these treatments can have a pain-relieving effect, but more research should be done on the matter, as finding CAM methods that are efficacious is crucial in the landscape of health sciences.

Keywords: acupuncture, cupping, alternative medicine, rehabilitation, acute injury

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

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In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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Authors: Nicki Mohammadi, Emma Reford, Natalia Romano Spica, Laura Tabacof, Jenna Tosto-Mancuso, David Putrino, Christopher P. Kellner

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Introductory Statement: The onset of the COVID-19 pandemic demanded an unprecedented need for the rapid development, dispersal, and application of infection testing. However, despite the impressive mobilization of resources, individuals were incredibly limited in their access to tests, particularly during the initial months of the pandemic (March-April 2020) in New York City (NYC). Access to COVID-19 testing is crucial in understanding patients’ illness experiences and integral to the development of COVID-19 standard-of-care protocols, especially in the context of overall access to healthcare resources. Succinct Description of basic methodologies: 18 Patients in a COVID-19 Remote Patient Monitoring Program (Precision Recovery within the Mount Sinai Health System) were interviewed regarding their experience with COVID-19 during the first wave (March-May 2020) of the COVID-19 pandemic in New York City. Patients were asked about their experiences navigating COVID-19 diagnoses, the health care system, and their recovery process. Transcribed interviews were analyzed for thematic codes, using grounded theory to guide the identification of emergent themes and codebook development through an iterative process. Data coding was performed using NVivo12. References for the domain “testing” were then extracted and analyzed for themes and statistical patterns. Clear Indication of Major Findings of the study: 100% of participants (18/18) referenced COVID-19 testing in their interviews, with a total of 79 references across the 18 transcripts (average: 4.4 references/interview; 2.7% interview coverage). 89% of participants (16/18) discussed the difficulty of access to testing, including denial of testing without high severity of symptoms, geographical distance to the testing site, and lack of testing resources at healthcare centers. Participants shared varying perspectives on how the lack of certainty regarding their COVID-19 status affected their course of recovery. One participant shared that because she never tested positive she was shielded from her anxiety and fear, given the death toll in NYC. Another group of participants shared that not having a concrete status to share with family, friends and professionals affected how seriously onlookers took their symptoms. Furthermore, the absence of a positive test barred some individuals from access to treatment programs and employment support. Concluding Statement: Lack of access to COVID-19 testing in the first wave of the pandemic in NYC was a prominent element of patients’ illness experience, particularly during their recovery phase. While for some the lack of concrete results was protective, most emphasized the invalidating effect this had on the perception of illness for both self and others. COVID-19 testing is now widely accessible; however, those who are unable to demonstrate a positive test result but who are still presumed to have had COVID-19 in the first wave must continue to adapt to and live with the effects of this gap in knowledge and care on their recovery. Future efforts are required to ensure that patients do not face barriers to care due to the lack of testing and are reassured regarding their access to healthcare. Affiliations- 1Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY 2Abilities Research Center, Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY

Keywords: accessibility, COVID-19, recovery, testing

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Authors: Moein Izadi, Ali Mohammadzadeh

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Detection of damaged parts of roads after earthquake is essential for coordinating rescuers. In this study, an approach is presented for the semi-automatic detection of damaged roads in a city using pre-event vector maps and both pre- and post-earthquake QuickBird satellite images. Damage is defined in this study as the debris of damaged buildings adjacent to the roads. Some spectral and texture features are considered for SVM classification step to detect damages. Finally, the proposed method is tested on QuickBird pan-sharpened images from the Bam City earthquake and the results show that an overall accuracy of 81% and a kappa coefficient of 0.71 are achieved for the damage detection. The obtained results indicate the efficiency and accuracy of the proposed approach.

Keywords: SVM classifier, disaster management, road damage detection, quickBird images

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Authors: Fahad Alamoudi, Yaser Miaji

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The growing popularity of swimming pools and other activities in the water for sport, fitness, therapy or just enjoyable relaxation have led to the increased use of swimming pools and the establishment of a variety of specific-use pools such as spa pools, water slides, and more recently, hydrotherapy and wave pools. In this research, a few simple equipment is used for test, detect and alert for detection of water cleanness and pollution. YSI Photometer Systems, TDSTestr High model, Rio 12HF and Electrode A1. The researchers used electrolysis as a method of separating bonded elements and compounds by passing an electric current through them. The results which use 41 experiments show the higher the salt concentration, the more efficient the electrode and the smaller the gap between the plates, the lower the electrode voltage. Furthermore, it is proved that the larger the surface area, the lower the cell voltage and the higher current used the more chlorine produced.

Keywords: photometer, electrode, electrolysis, swimming pool chlorination

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Authors: Lovepreet Kaur Dhugga, Dwijendra P. Singh

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Calcium copper titanate (CCTO) was synthesized via the sol-gel auto-combustion method. The precursor was calcined at 800°C and 1000°C for 6 hours providing brown-coloured powders, which were pelletized and sintered at 1000°C for 12 hrs to determine their dielectric behaviour in the frequency range (100Hz-10MHz) at room temperature. The dielectric constant(εr) and loss tangent (tanδ) has been found to be ~ 6153 and 0.5 for 800°C and ~ 5504 and 0.2 for 1000°C respectively, at frequency 1kHz. Microstructure study revealed maximum grain growth occurs in sample calcined at 800°C, responsible for its high dielectric constant. Phase identification of CaCu₃Ti₄O₁₂ has been carried out through X-ray diffraction. It can be used in various electronic applications as it shows large εᵣ and low tanδ values over a wide frequency spectrum, including energy storage devices, microwave shielding, and sensors.

Keywords: calcium copper titanate, dielectric behaviour, microstructure, X-ray diffraction

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Authors: Janjira Triped, Wipada Sanongraj, Wipawee Khamwichit

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The research work covered in this study includes the morphological structure and optical properties of TiO2-coated silk fibroin (SF) filters at 2.5% wt. TiO2/vol. PVA solution. SEM micrographs revealed the fibrous morphology of the TiO2-coated SF filters. An average diameter of the SF fiber was estimated to be approximately 10µm. Also, it was confirmed that TiO2 can be adhered more on SF filter surface at higher TiO2 dosages. The activity of semiconductor materials was studied by UV-VIS spectrophotometer method. The spectral data recorded shows the strong cut off at 390 nm. The calculated band-gap energy was about 3.19 eV. The photocatalytic activity of the filter was tested for gaseous formaldehyde removal in a modeling room with the total volume of 2.66 m3. The highest removal efficiency (54.72 ± 1.75%) was obtained at the initial formaldehyde concentration of about 5.00 ± 0.50ppm.

Keywords: photocatalytic oxidation process, formaldehyde (HCHO), silk fibroin (SF), titanium dioxide (TiO2)

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Authors: Oğuzhan Urhan

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In this paper, an improved motion estimation (ME) approach based on weighted constrained one-bit transform is proposed for block-based ME employed in video encoders. Binary ME approaches utilize low bit-depth representation of the original image frames with a Boolean exclusive-OR based hardware efficient matching criterion to decrease computational burden of the ME stage. Weighted constrained one-bit transform (WC‑1BT) based approach improves the performance of conventional C-1BT based ME employing 2-bit depth constraint mask instead of a 1-bit depth mask. In this work, the range of constraint mask is further extended to increase ME performance of WC-1BT approach. Experiments reveal that the proposed method provides better ME accuracy compared existing similar ME methods in the literature.

Keywords: fast motion estimation; low-complexity motion estimation, video coding

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Authors: Mohammadreza Kashizadeh, Mohammadamin Hashemi

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Solymorph, a kinetic building facade designed for optimal energy capture and architectural expression, is explored in this paper. The system integrates photovoltaic panels with soft robotic actuators for precise solar tracking, resulting in enhanced electricity generation compared to static facades. Driven by the growing interest in dynamic building envelopes, the exploration of novel facade systems is necessitated. Increased energy generation and regulation of energy flow within buildings are potential benefits offered by integrating photovoltaic (PV) panels as kinetic elements. However, incorporating these technologies into mainstream architecture presents challenges due to the complexity of coordinating multiple systems. To address this, Solymorph leverages soft robotic actuators, known for their compliance, resilience, and ease of integration. Additionally, the project investigates the potential for employing Large Language Models (LLMs) to streamline the design process. The research methodology involved design development, material selection, component fabrication, and system assembly. Grasshopper (GH) was employed within the digital design environment for parametric modeling and scripting logic, and an LLM was experimented with to generate Python code for the creation of a random surface with user-defined parameters. Various techniques, including casting, 3D printing, and laser cutting, were utilized to fabricate the physical components. Finally, a modular assembly approach was adopted to facilitate installation and maintenance. A case study focusing on the application of Solymorph to an existing library building at Politecnico di Milano is presented. The facade system is divided into sub-frames to optimize solar exposure while maintaining a visually appealing aesthetic. Preliminary structural analyses were conducted using Karamba3D to assess deflection behavior and axial loads within the cable net structure. Additionally, Finite Element (FE) simulations were performed in Abaqus to evaluate the mechanical response of the soft robotic actuators under pneumatic pressure. To validate the design, a physical prototype was created using a mold adapted for a 3D printer's limitations. Casting Silicone Rubber Sil 15 was used for its flexibility and durability. The 3D-printed mold components were assembled, filled with the silicone mixture, and cured. After demolding, nodes and cables were 3D-printed and connected to form the structure, demonstrating the feasibility of the design. Solymorph demonstrates the potential of soft robotics and Artificial Intelligence (AI) for advancements in sustainable building design and construction. The project successfully integrates these technologies to create a dynamic facade system that optimizes energy generation and architectural expression. While limitations exist, Solymorph paves the way for future advancements in energy-efficient facade design. Continued research efforts will focus on cost reduction, improved system performance, and broader applicability.

Keywords: artificial intelligence, energy efficiency, kinetic photovoltaics, pneumatic control, soft robotics, sustainable building

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Authors: Deepti Kumari, Upamanyu Hore

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Cities are an example of a human-modified environment with few fragments of urban green spaces, which are widely considered for urban biodiversity. The study aims to address the avifaunal diversity in urban parks based on the park size and their urbanization intensity. Also, understanding the key factors affecting species composition and structure as birds are a good indicator of a healthy ecosystem, and they are sensitive to changes in the environment. A 50 m-long line-transect method is used to survey birds in 39 urban parks in Delhi, India. Habitat variables, including vegetation (percentage of non-native trees, percentage of native trees, top canopy cover, sub-canopy cover, diameter at breast height, ground vegetation cover, shrub height) were measured using the quadrat method along the transect, and disturbance variables (distance from water, distance from road, distance from settlement, park area, visitor rate, and urbanization intensity) were measured using ArcGIS and google earth. We analyzed species data for diversity and richness. We explored the relation of species diversity and richness to habitat variables using the multi-model inference approach. Diversity and richness are found significant in different park sizes and their urbanization intensity. Medium size park supports more diversity, whereas large size park has more richness. However, diversity and richness both declined with increasing urbanization intensity. The result of CCA revealed that species composition in urban parks was positively associated with tree diameter at breast height and distance from the settlement. On the model selection approach, disturbance variables, especially distance from road, urbanization intensity, and visitors are the best predictors for the species richness of birds in urban parks. In comparison, multiple regression analysis between habitat variables and bird diversity suggested that native tree species in the park may explain the diversity pattern of birds in urban parks. Feeding guilds such as insectivores, omnivores, carnivores, granivores, and frugivores showed a significant relation with vegetation variables, while carnivores and scavenger bird species mainly responded with disturbance variables. The study highlights the importance of park size in urban areas and their urbanization intensity. It also indicates that distance from the settlement, distance from the road, urbanization intensity, visitors, diameter at breast height, and native tree species can be important determining factors for bird richness and diversity in urban parks. The study also concludes that the response of feeding guilds to vegetation and disturbance in urban parks varies. Therefore, we recommend that park size and surrounding urban matrix should be considered in order to increase bird diversity and richness in urban areas for designing and planning.

Keywords: diversity, feeding guild, urban park, urbanization intensity

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: Alessandra Pardu, Elena Curti, Marco Caredda, Alessio Dedola, Margherita Addis, Massimo Pes, Antonio Pirisi, Tonina Roggio, Sergio Uzzau, Roberto Anedda

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Some of the artisanal cheeses products of European Countries certificated as PDO (Protected Designation of Origin) are made from raw milk. To recognise potential frauds (e.g. pasteurisation or thermisation of milk aimed at raw milk cheese production), the alkaline phosphatase (ALP) assay is currently applied only for pasteurisation, although it is known to have notable limitations for the validation of ALP enzymatic state in nonbovine milk. It is known that frauds considerably impact on customers and certificating institutions, sometimes resulting in a damage of the product image and potential economic losses for cheesemaking producers. Robust, validated, and univocal analytical methods are therefore needed to allow Food Control and Security Organisms, to recognise a potential fraud. In an attempt to develop a new reliable method to overcome this issue, Time-Domain Nuclear Magnetic Resonance (TD-NMR) spectroscopy has been applied in the described work. Daily fresh milk was analysed raw (680.00 µL in each 10-mm NMR glass tube) at least in triplicate. Thermally treated samples were also produced, by putting each NMR tube of fresh raw milk in water pre-heated at temperatures from 68°C up to 72°C and for up to 3 min, with continuous agitation, and quench-cooled to 25°C in a water and ice solution. Raw and thermally treated samples were analysed in terms of 1H T2 transverse relaxation times with a CPMG sequence (Recycle Delay: 6 s, interpulse spacing: 0.05 ms, 8000 data points) and quasi-continuous distributions of T2 relaxation times were obtained by CONTIN analysis. In line with previous data collected by high field NMR techniques, a decrease in the spin-spin relaxation constant T2 of the predominant 1H population was detected in heat-treated milk as compared to raw milk. The decrease of T2 parameter is consistent with changes in chemical exchange and diffusive phenomena, likely associated to changes in milk protein (i.e. whey proteins and casein) arrangement promoted by heat treatment. Furthermore, experimental data suggest that molecular alterations are strictly dependent on the specific heat treatment conditions (temperature/time). Such molecular variations in milk, which are likely transferred to cheese during cheesemaking, highlight the possibility to extend the TD-NMR technique directly on cheese to develop a method for assessing a fraud related to the use of a milk thermal treatment in PDO raw milk cheese. Results suggest that TDNMR assays might pave a new way to the detailed characterisation of heat treatments of milk.

Keywords: cheese fraud, milk, pasteurisation, TD-NMR

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Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

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Authors: Ishiyaku Abdulkadir, Satish Kumar J

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Land Productivity is a measure of the greenness of above-ground biomass in health and potential gain and is not related to agricultural productivity. Monitoring land productivity dynamics is essential to identify, especially when and where the trend is characterized degraded for mitigation measures. This research aims to monitor the land productivity trend of Gombe State between 2001 and 2015. QGIS was used to compute NDVI from AVHRR/MODIS datasets in a cloud-based method. The result appears that land area with improving productivity account for 773sq.km with 4.31%, stable productivity traced to 4,195.6 sq.km with 23.40%, stable but stressed productivity represent 18.7sq.km account for 0.10%, early sign of decline productivity occupied 5203.1sq.km with 29%, declining productivity account for 7019.7sq.km, represent 39.2%, water bodies occupied 718.7sq.km traced to 4% of the state’s area.

Keywords: above-ground biomass, dynamics, land productivity, man-environment relationship

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Authors: P. Hashim, M. S. Mohd Ridzwan, J. Bakar

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Collagen was isolated from chicken feet by using papain and pepsin enzymes in acetic acid solution at 4°C for 24h with a yield of 18.16% and 22.94% by dry weight, respectively. Chemical composition and characteristics of chicken feet collagen such as amino acid composition, SDS-PAGE patterns, FTIR spectra and thermal properties were evaluated. The chicken feet collagen is rich in the amino acids glycine, glutamic acid, proline and hydroxyproline. Electrophoresis pattern demonstrated two distinct α-chains (α1 and α2) and β chain, indicating that type I collagen is a major component of chicken feet collagen. The thermal stability of collagen isolated by papain and pepsin revealed stable denaturation temperatures of 48.40 and 53.35°C, respectively. The FTIR spectra of both collagens were similar with amide regions in A, B, I, II, and III. The study demonstrated that chicken feet collagen using papain isolation method is possible as commercial alternative ingredient.

Keywords: chicken feet, collagen, papain, pepsin

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Authors: Kholil Kholil, Aniwidayati

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MDS (Multi-Dimensional Scaling) is one method that has been widely used to evaluate the use of natural resources. By using Raffish software tool, we will able to analyze sustainability level of the natural resources use. This paper will discuss the level of sustainability of the reservoir using MDS (Multi-Dimensional Scaling) based on five dimensions: (1) Ecology & Layout, (2) Economics, (3) Social & Culture, (4) Regulations & Institutional, and (5) Infrastructure and Technology. MDS analysis results show that the dimension of ecological and layout, institutional and the regulation are lack of sustainability due to the low index score of 45.76 and 42.24. While for the economic, social and culture, and infrastructure and technology dimension reach each score of 63.12, 64.42, and 68.64 (only the sufficient sustainability category). It means that the sustainability performance of Cirata Reservoir seriously threatened.

Keywords: MDS, cirata reservoir, carrying capacity, water quality, sustainable development, sedimentation, sustainability index

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Authors: Ozlem Uguz, Ali Demirci, Hanzade Haykiri-Acma, Serdar Yaman

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Lignitic coal holds its position as Turkey’s most important indigenous energy source to generate energy in thermal power plants. Hence, efficient and environmental-friendly use of lignite in electricity generation is of great importance. Thus, clean coal technologies have been planned to mitigate emissions and provide more efficient burning in power plants. In this context, oxygen enriched combustion (oxy-combustion) is regarded as one of the clean coal technologies, which based on burning with oxygen concentrations higher than that in air. As it is known that the most of the Turkish coals are low rank with high mineral matter content, unburnt carbon trapped in ash is, unfortunately, high, and it leads significant losses in the overall efficiencies of the thermal plants. Besides, the necessity of burning huge amounts of these low calorific value lignites to get the desired amount of energy also results in the formation of large amounts of ash that is rich in unburnt carbon. Oxygen enriched combustion technology enables to increase the burning efficiency through the complete burning of almost all of the carbon content of the fuel. This also contributes to the protection of air quality and emission levels drop reasonably. The aim of this study is to investigate the unburnt carbon content and the burning reactivities of several different lignite samples under oxygen enriched conditions. For this reason, the combined effects of temperature and oxygen/nitrogen ratios in the burning atmosphere were investigated and interpreted. To do this, Turkish lignite samples from Adıyaman-Gölbaşı and Kütahya-Tunçbilek regions were characterized first by proximate and ultimate analyses and the burning profiles were derived using DTA (Differential Thermal Analysis) curves. Then, these lignites were subjected to slow burning process in a horizontal tube furnace at different temperatures (200ºC, 400ºC, 600ºC for Adıyaman-Gölbaşı lignite and 200ºC, 450ºC, 800ºC for Kütahya-Tunçbilek lignite) under atmospheres having O₂+N₂ proportions of 21%O₂+79%N₂, 30%O₂+70%N₂, 40%O₂+60%N₂, and 50%O₂+50%N₂. These burning temperatures were specified based on the burning profiles derived from the DTA curves. The residues obtained from these burning tests were also analyzed by proximate and ultimate analyses to detect the unburnt carbon content along with the unused energy potential. Reactivity of these lignites was calculated using several methodologies. Burning yield under air condition (21%O₂+79%N₂) was used a benchmark value to compare the effectiveness of oxygen enriched conditions. It was concluded that oxygen enriched combustion method enhanced the combustion efficiency and lowered the unburnt carbon content of ash. Combustion of low-rank coals under oxygen enriched conditions was found to be a promising way to improve the efficiency of the lignite-firing energy systems. However, cost-benefit analysis should be considered for a better justification of this method since the use of more oxygen brings an unignorable additional cost.

Keywords: coal, energy, oxygen enriched combustion, reactivity

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Authors: Jun Byung Joon, Seo Seok Hyun, Lee Seo Young

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As carbon dioxide emissions increase due to rapid industrialization and reckless development, abnormal climates such as floods and droughts are occurring. In order to respond to such climate change, the use of existing fossil fuels is reduced, and the proportion of eco-friendly renewable energy is gradually increasing. Korea is an energy resource-poor country that depends on imports for 93% of its total energy. As the global energy supply chain instability experienced due to the Russia-Ukraine crisis increases, countries around the world are resetting energy policies to minimize energy dependence and strengthen security. Seawater thermal energy is a renewable energy that replaces the existing air heat energy. It uses the characteristic of having a higher specific heat than air to cool and heat main spaces of buildings to increase heat transfer efficiency and minimize power consumption to generate electricity using fossil fuels, and Carbon dioxide emissions can be minimized. In addition, the effect on the marine environment is very small by using only the temperature characteristics of seawater in a limited way. K-water carried out a demonstration project of supplying cooling and heating energy to spaces such as the central control room and presentation room in the management building by acquiring the heat source of seawater circulated through the power plant's waterway by using the characteristics of the tidal power plant. Compared to the East Sea and the South Sea, the main system was designed in consideration of the large tidal difference, small temperature difference, and low-temperature characteristics, and its performance was verified through operation during the demonstration period. In addition, facility improvements were made for major deficiencies to strengthen monitoring functions, provide user convenience, and improve facility soundness. To spread these achievements, the basic concept was to expand the seawater heating and cooling system with a scale of 200 USRT at the Tidal Culture Center. With the operational experience of the demonstration system, it will be possible to establish an optimal seawater heat cooling and heating system suitable for the characteristics of the west coast ocean. Through this, it is possible to reduce operating costs by KRW 33,31 million per year compared to air heat, and through industry-university-research joint research, it is possible to localize major equipment and materials and develop key element technologies to revitalize the seawater heat business and to advance into overseas markets. The government's efforts are needed to expand the seawater heating and cooling system. Seawater thermal energy utilizes only the thermal energy of infinite seawater. Seawater thermal energy has less impact on the environment than river water thermal energy, except for environmental pollution factors such as bottom dredging, excavation, and sand or stone extraction. Therefore, it is necessary to increase the sense of speed in project promotion by innovatively simplifying unnecessary licensing/permission procedures. In addition, support should be provided to secure business feasibility by dramatically exempting the usage fee of public waters to actively encourage development in the private sector.

Keywords: seawater thermal energy, marine energy, tidal power plant, energy consumption

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Authors: Amornchai Challcharoenwattana, Chanathip Pharino

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Rising amount of MSW every day, maximizing material diversions from landfills via recycling is a prefer method to land dumping. Characteristic of Thai MSW is classified as 40 -60 per cent compostable wastes while potentially recyclable materials in waste streams are composed of plastics, papers, glasses, and metals. However, rate of material recovery from MSW, excluding composting or biogas generation, in Thailand is still low. Thailand’s recycling rate in 2010 was only 20.5 per cent. Central government as well as local governments in Thailand have tried to curb this problem by charging some of MSW management fees at the users. However, the fee is often too low to promote MSW minimization. The objective of this paper is to identify levels of willingness-to-pay (WTP) for MSW recycling in different social structures with expected outcome of sustainable MSW managements for different town settlements to maximize MSW recycling pertaining to each town’s potential. The method of eliciting WTP is a payment card. The questionnaire was deployed using online survey during December 2012. Responses were categorized into respondents living in Bangkok, living in other municipality areas, or outside municipality area. The responses were analysed using descriptive statistics, and multiple linear regression analysis to identify relationships and factors that could influence high or low WTP. During the survey period, there were 168 filled questionnaires from total 689 visits. However, only 96 questionnaires could be usable. Among respondents in the usable questionnaires, 36 respondents lived in within the boundary of Bangkok Metropolitan Administration while 45 respondents lived in the chartered areas that were classified as other municipality but not in BMA. Most of respondents were well-off as 75 respondents reported positive monthly cash flow (77.32%), 15 respondents reported neutral monthly cash flow (15.46%) while 7 respondent reported negative monthly cash flow (7.22%). For WTP data including WTP of 0 baht with valid responses, ranking from the highest means of WTP to the lowest WTP of respondents by geographical locations for good MSW management were Bangkok (196 baht/month), municipalities (154 baht/month), and non-urbanized towns (111 baht/month). In-depth analysis was conducted to analyse whether there are additional room for further increase of MSW management fees from the current payment that each correspondent is currently paying. The result from multiple-regression analysis suggested that the following factors could impacts the increase or decrease of WTP: incomes, age, and gender. Overall, the outcome of this study suggests that survey respondents are likely to support improvement of MSW treatments that are not solely relying on landfilling technique. Recommendations for further studies are to obtain larger sample sizes in order to improve statistical powers and to provide better accuracy of WTP study.

Keywords: MSW, willingness to pay, payment card, waste seperation

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Authors: S. Zidani, A. Benakmoum, A. Mansouri, A. Ammouche

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In this research paper, we studied the oxidative stability of table margarine and soya/sunflower oils rich in lycopene with tomato peel powder (TPP). For this 1%, 2%, and 3% (w/w) of TPP was added to oil used in margarine manufacture. Chromatic characteristics of margarine and soya/sunflower oil have been studied using 'Tristimulus Colorimetry' method. The main point of the research was to determine the antioxidant activity and the oxidative resistance of soya/sunflower and margarine with TPP (peroxide index, TBA index, and rancimat test). The sensory and textural properties, overall acceptability of margarine and oil were good, indicating that TPP could be added to oil to produce a margarine enriched in lycopene with excellent stability oxidative.

Keywords: tomato peel powder, lycopene, table margarine, soya/sunflower oils, antioxidant activity, stability oxidative

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Authors: Shokrya Saleh A. Alshqaq, Abdullah Ali H. Ahmadini

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The Schwarz information criterion (SIC) is a popular tool for selecting the best variables in regression datasets. However, SIC is defined using an unbounded estimator, namely, the least-squares (LS), which is highly sensitive to outlying observations, especially bad leverage points. A method for robust variable selection based on SIC for linear regression models is thus needed. This study investigates the robustness properties of SIC by deriving its influence function and proposes a robust SIC based on the MM-estimation scale. The aim of this study is to produce a criterion that can effectively select accurate models in the presence of vertical outliers and high leverage points. The advantages of the proposed robust SIC is demonstrated through a simulation study and an analysis of a real dataset.

Keywords: influence function, robust variable selection, robust regression, Schwarz information criterion

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Authors: H. Yousefnia, SJ. Ahmadi, S. Sajadi, S. Zolghadri, A. Bahrami-Samani, M. Bagherzadeh

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Nowadays, superparamagnetic iron oxide nanoparticles (SPIONs) as the multitask agents have showed advantageous characteristics. The aim of this study was the preparation and quality control of 153Sm-DTPA-DA-SPION complex. Samarium-153 was produced by neutron irradiation of the enriched 152Sm2O3 in a research reactor for 5 d. For radiolabeling purposes, 8 mg of the ligand was added to the vial containing 153SmCl3 and the mixture was sonicated 30 min, while pH was adjusted to 7-8. The radiochemical purity of the complex was checked by the ITLC method using NH4OH:MeOH:H2O (0.2:2:4) as the mobile phase. This new radiolabeled complex was prepared with a radiochemical purity of higher than 98% in 30 min at the optimized condition. The complex was kept at room temperature and in human serum at 37 °C for 48 h, showed no loss of 153Sm from the complex. Considering all of these features, this new radiolabeled complex can be considered as a good therapeutic agent; however, further studies on its biological behavior are still needed.

Keywords: iron nanoparticles, preparation, quality control, 153Sm

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Authors: Kanit Manatura

Abstract:

The combustion and pyrolysis behavior of Palm Kernel Shell (PKS) were investigated in a thermogravimetric analyzer. A 10 mg sample of each biomass was heated from 30 °C to 800 °C at four heating rates (within 5, 10, 15 and 30 °C/min) in nitrogen and dry air flow of 20 ml/min instead of pyrolysis and combustion process respectively. During pyrolysis, thermal decomposition occurred on three different stages include dehydration, hemicellulose-cellulose and lignin decomposition on each temperature range. The TG/DTG curves showed the degradation behavior and the pyrolysis/combustion characteristics of the PKS samples which led to apply in thermogravimetric analysis. The kinetic factors including activation energy and pre-exponential factor were determined by the Coats-Redfern method. The obtained kinetic factors are used to simulate the thermal decomposition and compare with experimental data. Rising heating rate leads to shift the mass loss towards higher temperature.

Keywords: combustion, palm kernel shell, pyrolysis, thermogravimetric analyzer

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Authors: Hesham A. Elkaranshawy, Amr M. Abdelrazek, Hosam M. Ezzat

Abstract:

The system of ordinary nonlinear differential equations describing sliding velocity during impact with friction for a three-dimensional rigid-multibody system is developed. No analytical solutions have been obtained before for this highly nonlinear system. Hence, a power series solution is proposed. Since the validity of this solution is limited to its convergence zone, a suitable time step is chosen and at the end of it a new series solution is constructed. For a case study, the trajectory of the sliding velocity using the proposed method is built using 6 time steps, which coincides with a Runge-Kutta solution using 38 time steps.

Keywords: impact with friction, nonlinear ordinary differential equations, power series solutions, rough collision

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Authors: Pengchao Wei, Xiangzhong Fang

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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: Chuhan Zhang

Abstract:

As a typical mountainous city in the world, with the rise of shared transportation, cycling behavior in Chongqing is undergoing a role change from a traditional leisure activity to an important transportation mode. However, with the rapid increase in people's cycling demand, the built environment with mountainous features in Chongqing has become a key constraint hindering the further development of bicycle traffic. Based on the above background, the research summarizes the current development contradictions of bicycle traffic in Chongqing, analyses the global experience in the construction of bicycle-friendly cities with mountain characteristics, and combines the characteristics of bicycle traffic in Chongqing to further propose the planning method of the bicycle in mountain cities, to improve the bikability of Chongqing from the perspective of urban planning.

Keywords: bicycle traffic, mountainous city, bicycle-friendly, bikability, Chongqing

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Authors: Ahad Salimi, Hassan Masoumi

Abstract:

Prostate cancer is one of the most common recognized cancers in men, and, is one of the most important mortality factors of cancer in this group. Determining of prostate’s boundary in TRUS (Transrectal Ultra Sound) images is very necessary for prostate cancer treatments. The weakness edges and speckle noise make the ultrasound images inherently to segment. In this paper a new automatic algorithm for prostate segmentation in TRUS images proposed that include three main stages. At first morphological smoothing and sticks filtering are used for noise removing. In second step, for finding a point in prostate region, SOFM algorithm is enlisted and in the last step, the boundary of prostate extracting accompanying active contour is employed. For validation of proposed method, a number of experiments are conducted. The results obtained by our algorithm show the promise of the proposed algorithm.

Keywords: SOFM, preprocessing, GVF contour, segmentation

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Authors: Paramet Damchoo

Abstract:

The purpose of this study is to study the factors that influence the decision making of foreign volunteer tourists in Thailand. A sample size was 400 drawn from 10 provinces of Thailand using cluster sampling method. The factor analysis was used to analysis the data. The findings indicate that volunteer tourism which was based in Thailand contained a total of 45 activities which could be divided into 4 categories. The most of these tourists were from Europe including UK and Scandinavia which was 54.50 percent. Moreover, the tourists were male rather than female and 63.50 Percent of them ware younger than 20 years old. It is also found that there are 67.00 percent of the tourists used website to find where the volunteer tourism was based. Finally, the factors that influence the decision making of foreign volunteer tourists in Thailand consist of a wide variety of activities together with a flexibility in their activities and also low prices.

Keywords: decision making, volunteer tourism, special interest tourism, GAP year

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Authors: Firdaus Khairi Abdul Kadir, Nazihah Rusli, Noor Aisyah Abdul Aziz

Abstract:

Islam is a comprehensive religion encompassing all aspects of society’s life such as social, economic, political, cultural and environmental. The environment is part of the manifestation of God’s greatness which has pearls of wisdom, bestowed upon human beings to make them realize that everything is in the hands of God (Allah SWT). However, the equilibrium of nature could be disturbed from the excessive exploitation by humans’ hands. As a caliph on this earth, it is the responsibility of human beings to look after the environment proactively. Besides, Islam calls for the execution of accountable development and respecting the principles of sustainability. Therefore, this study focuses on the role of human beings as caliphs on this earth who are responsible for nature and their acts in conserving and preserving the environment based on the approach of religious education. This study also used the research method of the survey library.

Keywords: environment, human beings, caliph, tauhid, Allah SWT

Procedia PDF Downloads 113