Search results for: palm kernel expeller

Authors: Jigg Pelayo, Ricardo Villar

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The Philippines is long considered as a valuable producer of high value crops globally. The country’s employment and economy have been dependent on agriculture, thus increasing its demand for the efficient agricultural mechanism. Remote sensing and geographic information technology have proven to effectively provide applications for precision agriculture through image-processing technique considering the development of the aerial scanning technology in the country. Accurate information concerning the spatial correlation within the field is very important for precision farming of high value crops, especially. The availability of height information and high spatial resolution images obtained from aerial scanning together with the development of new image analysis methods are offering relevant influence to precision agriculture techniques and applications. In this study, an algorithm was developed and implemented to detect and count high value crops simultaneously through adaptive scaling of support vector machine (SVM) algorithm subjected to object-oriented approach combining watershed transformation and local maxima filter in enhancing tree counting and detection. The methodology is compared to cutting-edge template matching algorithm procedures to demonstrate its effectiveness on a demanding tree is counting recognition and delineation problem. Since common data and image processing techniques are utilized, thus can be easily implemented in production processes to cover large agricultural areas. The algorithm is tested on high value crops like Palm, Mango and Coconut located in Misamis Oriental, Philippines - showing a good performance in particular for young adult and adult trees, significantly 90% above. The s inventories or database updating, allowing for the reduction of field work and manual interpretation tasks.

Keywords: high value crop, LiDAR, OBIA, precision agriculture

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Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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Authors: Hiripurage Mallika Sandamali Dissanayaka

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Butterflies are found everywhere on Earth, helping flowering plants reproduce through pollination. Wetlands perform many valuable functions such as providing wildlife habitat. Diyasaru Wetland Park was chosen as the study site. It is located in a highly urbanized area of Sri Jayawardenepura Kotte, Sri Lanka. A distribution map was prepared to increase butterfly habitat in the urbanized area, and research was conducted to determine the most suitable sections for using it. As this wetland has footpaths for walking, line transect surveys were used to mark species within the sampling area, and directly observed species were recorded. All data collection was done from 0900 to 1200 hours and 1300 to 1600 hours and fieldwork was done from 11 February 2020 to 20 January 2021. ED binoculars (10.5x45), DSLR cameras (Canon EOS/EFS5 mm 3.5-5.6), and Garmin GPS (Etrex 10) were used to observe butterfly species, identify locations, and take photographs as evidence. Analyzing their habitats using GIS (ArcGIS Pro) to identify their distribution within the park premises, the distribution density of the known size of the population was calculated for each point by kernel density, and local similarity values were calculated for each pair of corresponding features through hotspot analysis, and cell values were determined by inverse distance weighting (IDW) using a linearly weighted combination of a set of sample points. According to the maps prepared to predict the distribution of butterflies in this park, the high level of distribution or favorable areas were near flower gardens and meadows, but some individual species prefer habitats that are more suitable for their life activities, so they live in other areas. Sixty-six (66) species belonging to six (6) families have been recorded in the premises. Sixty (60) species of least concern (LC), two (2) near threatened (NT), and four (4) vulnerable (VU) species have been recorded, and several new species, such as Plum Judy (Abisara echerius), were reported. The outcome of the study will form the basis for decision-making by the Sri Lanka Land Development (SLLD) Corporation for the future development and maintenance of the park.

Keywords: wetland, Lepidoptera, habitat, urban, west

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: F. Murilo T. Luna, Vanessa F. Oliveira, Alysson Rocha, Expedito J. S. Parente, Andre V. Bueno, Matheus C. M. Farias, Celio L. Cavalcante Jr.

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Aviation jetfuel used in aircraft gas-turbine engines is customarily obtained from the kerosene distillation fraction of petroleum (150-275°C). Mineral jetfuel consists of a hydrocarbon mixture containing paraffins, naphthenes and aromatics, with low olefins content. In order to ensure their safety, several stringent requirements must be met by jetfuels, such as: high energy density, low risk of explosion, physicochemical stability and low pour point. In this context, aviation fuels eventually obtained from biofeedstocks (which have been coined as ‘biojetfuel’), must be used as ‘drop in’, since adaptations in aircraft engines are not desirable, to avoid problems with their operation reliability. Thus, potential aviation biofuels must present the same composition and physicochemical properties of conventional jetfuel. Among the potential feedtstocks for aviation biofuel, the babaçu oil, extracted from a palm tree extensively found in some regions of Brazil, contains expressive quantities of short chain saturated fatty acids and may be an interesting choice for biojetfuel production. In this study, biojetfuel was synthesized through homogeneous transesterification of babaçu oil using methanol and its properties were compared with petroleum-based jetfuel through measurements of oxidative stability, physicochemical properties and low temperature properties. The transesterification reactions were carried out using methanol and after decantation/wash procedures, the methyl esters were purified by molecular distillation under high vacuum at different temperatures. The results indicate significant improvement in oxidative stability and pour point of the products when compared to the fresh oil. After optimization of operational conditions, potential biojetfuel samples were obtained, consisting mainly of C8 esters, showing low pour point and high oxidative stability. Jet engine tests are being conducted in an automated test bed equipped with pollutant emissions analysers to study the operational performance of the biojetfuel that was obtained and compare with a mineral commercial jetfuel.

Keywords: biojetfuel, babaçu oil, oxidative stability, engine tests

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Authors: Omer Al-Kaabi, Ahmed Nasr, Abdullah Al-Ghafri, Mohammed Abdelfattah

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The Falaj system, derived from natural water sources, is a man-made canal system designed to supply communities of farmers with water for domestic and agricultural purposes. For thousands of years, Falaj has served communities by harnessing the force of gravity; it persists as a vital water management system in numerous regions across the Sultanate of Oman. Remarkably, predates the establishment of many fundamental hydraulic principles used today. Al-Khatmain Falaj, with its accessibility and historical significance spanning over 2000 years, was chosen as the focal point of this study. The research aimed to investigate the efficiency of Al-Khatmain Falaj in meeting specific water demands. The HEC-RAS model was utilized to visualize water flow dynamics within the Falaj channels, accompanied by graphical representations of pertinent variables. The application of HEC-RAS helped to measure different water flow scenarios within the channel, enabling a clear comparison with the demand area catchment. The cultivated land of Al-Khatmain is 723,124 m² and consists of 16,873 palm trees representing 91% of the total area and the remaining 9% is mixed types of trees counted 3,920 trees. The study revealed a total demand of 8,244 m³ is required to irrigate the cultivated land. Through rigorous analysis, the study has proven that the Falaj system in Al-Khatmain operates with high efficiency, as the average annual water supply is 9676.8 m3/day. Additionally, the channel designed at 0.6m width x 0.3m height efficiently holds the optimal water supply, with an average flow depth of 0.21m. Also, the system includes an overflow drainage channel to mitigate floods and prevent crop damage based on seasonal requirements. This research holds promise for examining diverse hydrological conditions and devising effective strategies to manage scenarios of both high and low flow rates.

Keywords: Al-Khatmain, sustainability, Falaj, HEC-RAS, water management system

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Authors: Enrique González Pendás, Vidal Pérez Hernández, Jorge Ferro Díaz, Nelson Careaga Pendás

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The investigation is carried out on the Protected Area of San Ubaldo, toward the interior of an open pinegrove with palm trees in a dry plainness of quar zitic sands, belonging to the Floristic Managed Reservation San Ubaldo-Sabanalamar, Guane, Pinar del Río, Cuba. This area is characterized by drastic seasonal variations, high temperatures and water evaporation, strong solar radiation, with sandy soils of almost pure quartz, which are very acid and poor in nutrients. The objective of the present work is to determine evidence of facilitation and its relationship with the structure and composition of plant communities in these peculiar ecosystems. For this study six lineal parallel transepts of 100 m are traced, in those, a general recording of the flora is carried out. To establish which plants act as nurses, is taken into account a height over 1 meter, canopy over 1.5 meter and the occurrence of several species under it. Covering was recorded using the line intercept method; the medium values of species richness for the taxa under nurses is compared with those that are located in open spaces among them. Then, it is determined which plants are better recruiter of other species (better nurses). An experiment is made to measure and compare some parameters in pine seedlings under the canopy of the Byrsonima crassifolia (L.) Kunth. and in open spaces, also the number of individuals is counted by species to calculate the frequency and total abundance in the study area. As a result, it is offered an up-to-date floristic list, a phylogenetic tree of the plant community showing a high phylodiversity, it is proven that the medium values of species richness and abundance of species under the nurses, is significantly superior to those occurring in open spaces. Furthermore, by means of phylogenetic trees it is shown that the species which cohabit under the nurses are not phylogenetically related. The former results are cited evidences of facilitation among plants, as well as it is one more time shown the importance of the nurse effect in preserving plant diversity on extreme environments.

Keywords: facilitation, nurse plants, positive interactions, quarzitic sands

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Authors: Muhammad Shoaib, Hassan M Al-Swaidan

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Saudi Arabia is the major date producer in the world. In order to maximize the production from date tree, pruning of the date trees is required annually. Large amount of this agriculture waste material (palm tree fronds) is available in Saudi Arabia and considered as an ideal source as a precursor for production of activated carbon (AC). The single step procedure for the preparation of micro porous activated carbon (AC) from Saudi date tree fronds using mixture of gases (N2 and CO2) is carried out at carbonization/activation temperature at 850°C and at different ramp rates of 10, 20 and 30 degree per minute. Alloy 330 horizontal reactor is used for tube furnace. Flow rate of nitrogen and carbon dioxide gases are kept at 150 ml/min and 50 ml/min respectively during the preparation. Characterization results reveal that the BET surface area, pore volume, and average pore diameter of the resulting activated carbon generally decreases with the increase in ramp rate. The activated carbon prepared at a ramp rate of 10 degrees/minute attains larger surface area and can offer higher potential to produce activated carbon of greater adsorption capacity from agriculture wastes such as date fronds. The BET surface areas of the activated carbons prepared at a ramp rate of 10, 20 and 30 degree/minute after 30 minutes activation time are 1094, 1020 and 515 m2/g, respectively. Scanning electron microscopy (SEM) for surface morphology, and FTIR for functional groups was carried out that also verified the same trend. Moreover, by increasing the ramp rate from 10 and 20 degrees/min the yield remains same, i.e. 18%, whereas at a ramp rate of 30 degrees/min the yield increases from 18 to 20%. Thus, it is feasible to produce high-quality micro porous activated carbon from date frond agro waste using N2 carbonization followed by physical activation with CO2 and N2 mixture. This micro porous activated carbon can be used as adsorbent of heavy metals from wastewater, NOx SOx emission adsorption from ambient air and electricity generation plants, purification of gases, sewage treatment and many other applications.

Keywords: activated carbon, date tree fronds, agricultural waste, applied chemistry

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Authors: Juan Facetti, Rocky McBride, Karina Loup

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The Chaco Region of Paraguay is a key biodiverse area for the conservation of jaguars (Panthera onca), the largest feline of the Americas. It comprises five eco-regions, which holds important but decreasing populations of this species. The last decades, the expansion of soybean over the Atlantic Forest, forced the translocation of cattle-ranches towards the Chaco. Few studies of Jaguar's population densities in the American hemisphere were done until now. In the region, the specie is listed as vulnerable or threatened and more information is needed to implement any conservation policy. Among the factors that threaten the populations are land-use change, habitat fragmentation, prey depletion and illegal hunting. Two largest eco-regions were studied: the Wet Chaco and the Dry Chaco. From 2002 more than 20 jaguars were captured and fitted with GPS-collar. Data collected from 11 GPS-collars were processed, transformed numerically and finally converted into maps for analyzing. 8.092 locations were determined for four adult females (AF) and one adult male (AM) in the Wet Chaco, and one AF, one juvenile male (JM) and four AM in the Dry Chaco, during 1,867 days. GIS and kernel methodology were used to calculate daily distance of movement, home range-HR (95% isopleth), and core area (considered as 50% isopleth). In the Wet Chaco HR were 56 Km2 and 238 km2 for females and males respectively; while in the Dry Chaco HR were 685 Km2 and 844.5 km2 for females and males respectively, and 172 Km2 for a juvenile. Core areas of individual activity for each jaguar, were on average 11.5 Km2 and 33.55 km2 for AF and AM respectively in the Wet Chaco, while in the Dry Chaco were larger: 115 km2 for five AM and 225 Km2 for an AF and 32.4 Km2 for a JM. In both ecoregions, only one relevant overlap of HR of adults was reported. During the reproduction season, the HR (95% K) of one AM overlapped 49.83% with that of one AF. At the Wet Chaco, the maximum daily distance moved by an AF was 14.5 Km and 11.6 Km for the AM, while the Maximum Mean Daily Moved (MMDM) distance was 5.6 km for an AF and 3.1 km for an AM. At the Dry Chaco, the maximum daily distance for an AF was 61.7Km., 50.9Km for the AM and 6.6 Km for the JM, while the MMDM distance was 13.2 km for an AM and 8.4 km for an AF. This study confirmed that, as the invasion to jaguar habitat increased, it resulted in fragmented landscapes that influence spacing patterns of jaguars. Males used largest HR that of the smaller females and males covers largest distances that of the females. There appeared to be important spatial segregation between not only females but also males. It is likely that the larger areas used by males are partly caused by the sexual dimorphism in body size that entails differences in prey requirements. These could explain the larger distances travelled daily by males.

Keywords: Chaco ecoregions, Jaguar, home range, Panthera onca, Paraguay

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Authors: Jitendra Pratap, Jonathan Sivyer

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Introduction: Dual energy/Spectral CT scanning permits simultaneous acquisition of two x-ray spectra datasets and can complement radiological diagnosis by allowing tissue characterisation (e.g., uric acid vs. non-uric acid renal stones), enhancing structures (e.g. boost iodine signal to improve contrast resolution), and quantifying substances (e.g. iodine density). However, the latter showed inconsistent results between the 2 main modes of dual energy scanning (i.e. dual source vs. dual layer). Therefore, the present study aimed to determine which technology is more accurate in quantifying iodine density. Methods: Twenty vials with known concentrations of iodine solutions were made using Optiray 350 contrast media diluted in sterile water. The concentration of iodine utilised ranged from 0.1 mg/ml to 1.0mg/ml in 0.1mg/ml increments, 1.5 mg/ml to 4.5 mg/ml in 0.5mg/ml increments followed by further concentrations at 5.0 mg/ml, 7mg/ml, 10 mg/ml and 15mg/ml. The vials were scanned using Dual Energy scan mode on a Siemens Somatom Force at 80kV/Sn150kV and 100kV/Sn150kV kilovoltage pairing. The same vials were scanned using Spectral scan mode on a Philips iQon at 120kVp and 140kVp. The images were reconstructed at 5mm thickness and 5mm increment using Br40 kernel on the Siemens Force and B Filter on Philips iQon. Post-processing of the Dual Energy data was performed on vendor-specific Siemens Syngo VIA (VB40) and Philips Intellispace Portal (Ver. 12) for the Spectral data. For each vial and scan mode, the iodine concentration was measured by placing an ROI in the coronal plane. Intraclass correlation analysis was performed on both datasets. Results: The iodine concentrations were reproduced with a high degree of accuracy for Dual Layer CT scanner. Although the Dual Source images showed a greater degree of deviation in measured iodine density for all vials, the dataset acquired at 80kV/Sn150kV had a higher accuracy. Conclusion: Spectral CT scanning by the dual layer technique has higher accuracy for quantitative measurements of iodine density compared to the dual source technique.

Keywords: CT, iodine density, spectral, dual-energy

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Authors: Nizar Chaira

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Dates, main products of the oases, due to their therapeutic interests, are considered highly nutritious fruit. Several studies on the valuation biotechnology and technology of dates are made, and several products are already prepared. Isolation of the yeast Saccharomyces cerevisiae, naturally presents in a scrap of date, optimization of growth in the medium based on date syrup and production biomass can potentially expand the range of secondary products of dates. To this end, this paper tries to study the suitability for processing dates technology and biotechnology to use the date pulp as a carbon source for biological transformation. Two strains of Saccharomyces cerevisiae isolated from date syrup (S1, S2) and a commercial strain have used for this study. After optimization of culture conditions, production in a fermenter on two different media (date syrup and beet molasses) was performed. This is followed by studying the kinetics of growth, protein production and consumption of sugars in crops strain 1, 2 and the commercial strain and on both media. The results obtained showed that a concentration of 2% sugar, 2.5 g/l yeast extract, pH 4.5 and a temperature between 25 and 35°C are the optimal conditions for cultivation in a bioreactor. The exponential phase of the specific growth rate of a strain on both media showed that it is about 0.3625 h-1 for the production of a medium based on date syrup and 0.3521 h-1 on beet molasses with a generation time equal to 1.912 h and on the medium based on date syrup, yeast consumes preferentially the reducing sugars. For the production of protein, we showed that this latter presents an exponential phase when the medium starts to run out of reducing sugars. For strain 2, the specific growth rate is about 0.261h-1 for the production on a medium based on date syrup and 0207 h-1 on beet molasses and the base medium syrup date of the yeast consumes preferentially reducing sugars. For the invertase and other metabolits, these increases rapidly after exhaustion of reducing sugars. The comparison of productivity between the three strains on the medium based on date syrup showed that the maximum value is obtained with the second strain: p = 1072 g/l/h as it is about of 0923 g/l/h for strain 1 and 0644 g/l/h for the commercial strain. Thus, isolates of date syrup are more competitive than the commercial strain and can give the same performance in a shorter time with energy gain.

Keywords: date palm, fermentation, molasses, Saccharomyces, syrup

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Authors: Qiankun Zhong

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In a global cultural context, film festival awards become authorities to define the aesthetic value of films. To study which genres and producing countries are valued by different film festivals and how those evaluations interact with each other, this research explored the interactions between the film festivals through their selection of movies and the factors that lead to the tendency of film festivals to nominate the same movies. To do this, the author employed a two-mode network on the movies that won the highest awards at five international film festivals with the highest attendance in the past ten years (the Venice Film Festival, the Cannes Film Festival, the Toronto International Film Festival, Sundance Film Festival, and the Berlin International Film Festival) and the film festivals that nominated those movies. The title, genre, producing country and language of 50 movies, and the range (regional, national or international) and organizing country or area of 129 film festivals were collected. These created networks connected by nominating the same films and awarding the same movies. The author then assessed the density and centrality of these networks to answer the question: What are the film festivals that tend to have more shared values with other festivals? Based on the Eigenvector centrality of the two-mode network, Palm Springs, Robert Festival, Toronto, Chicago, and San Sebastian are the festivals that tend to nominate commonly appreciated movies. In contrast, Black Movie Film Festival has the unique value of generally not sharing nominations with other film festivals. A homophily test was applied to access the clustering effects of film and film festivals. The result showed that movie genres (E-I index=0.55) and geographic location (E-I index=0.35) are possible indicators of film festival clustering. A blockmodel was also created to examine the structural roles of the film festivals and their meaning in real-world context. By analyzing the same blocks with film festival attributes, it was identified that film festivals either organized in the same area, with the same history, or with the same attitude on independent films would occupy the same structural roles in the network. Through the interpretation of the blocks, language was identified as an indicator that contributes to the role position of a film festival. Comparing the result of blockmodeling in the different periods, it is seen that international film festivals contrast with the Hollywood industry’s dominant value. The structural role dynamics provide evidence for a multi-value film festival network.

Keywords: film festivals, film studies, media industry studies, network analysis

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Authors: Hamitri-Guerfi Fatiha, Madani Khodir, Hadjal Samir, Kati Djamel, Youyou Ahcene

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Date palm (Phoenix dactylifera) is a principal fruit that is grown in many regions of the world, resulting in a surplus production of dates. Algeria is considered to be one of the date producing countries. Date seeds (pits) have been a problem to the date industry as a waste stream. However, finding a way to make a profit on the pits would benefit date farmers substantially. This work concentrated on the valorization of date seed oils. A preliminary study was carried out on three varieties (soft, half soft, and dry) and we selected the dry variety. This work concerns the valorization of the date seed oil of the dry variety: ‘Mech Degla’ by its incorporation in a food formulation: margarine of table. Lipid extraction was carried out by hot extraction with the soxhlet; the extracts obtained are rich in fat contents, the results gave outputs of 13.21±0.21 %. The antioxidant activity of extracted oils was studied by the test of DPPH, the content polyphenols as well as the anti-radicalaire activity. The analysis of fatty acids was made by CPG. Thus, it comes out from our results that the recovered fat contents are interesting and considerable. A formulation of the margarine ‘BIO’ was elaborated on the scale industrialist by the addition of the extracts of date seeds ‘Mech-Degla’ oil in order to substitute a synthetic additive. The physicochemical characteristics of the elaborate margarines prove to be in conformity with the standards set by the Algerian companies. The texture of the elaborate margarine has an acceptable color, an aspect brilliant and homogeneous, it is plastic and easy to paste having an index of required SFC and the margarine melts easily in the mouth. Moreover, the evaluation of oxidative stability is carried out by the test of Rancimat. The result obtained reported that the margarine enriched with date seed oil, proved more resistant to oxidation, than the margarine without extract, which is improved much during incorporation of the extracts simultaneously. By conclusion, considering the content of polyphénols noted in the two extracts (aqueous and oily), we can exhort the scientific community to become aware of the treasures of our country especially the wonders of the south which are the dates and theirs under products (pits).

Keywords: antioxydant activity, date seed oil, quality characteristics, margarine

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Authors: Khalid Mahmoud Gaafar

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In human diets , ω-6 and ω-3 are important essential fatty acids for immunity and health. However, considerable alteration in dietary patterns and contents has resulted in change of the consumption of such fatty acids ,with subsequent increase in the consumption of ω-6 fatty acids and a marked decrease in the consumption of ω-3 fatty acids. This dietary alteration has led to an imbalance in the ratio for ω-6/ω-3, which at 20:1 now differs considerably from the original ratio (1:1). Therefore, dietary supplements such as eggs and meat enriched with omega 3 are necessary to increase the consumption of ω-3 to meet the recommended need for ω-3. Foods that supply ω-6 fatty acids include soybean, palm , sunflower, and rapeseed oils, whereas foods that supply ω-3 fatty acids such as linseed and fish oils. Lin seed oils contain Alpha – linolenic acid (ALA), which can be converted to DHA and EPA in the birds body, with linseed oil containing more than 50% ALA. On the other hand, high doses of omega 6 sources in the diet may have deleterious effects on humans. Maintaining an optimum ratio of ω-3 and ω-6fatty acids not only improves performance but also prevents these health risks. The ratio of n-6:ω-3 fatty acids also plays an important role in the immune response, production performance of broilers and designing meat enriched with ω-3 polyunsaturated fatty acids (PUFAs). Birds of three experimental groups fed on basal starter (0-2nd weeks), grower (3rd -4th weeks) and finisher (5th week) rations. The first is control group fed during the grower-finisher periods on basic diet with two replicate (one fed on basic diet contain vegetable oil and the other don’t) without any additives. The three experimental groups (T1 – T2 –T3) fed during the grower- finisher periods on diets free from vegetable oils and contain of 5% of extruded mixture of soybean and linseed (60%:40%). The second (T2) and third (T3) experimental groups supplemented with vitamin B12 and enzyme mixture. The first experimental groups don’t receive vitamins or enzymes. The obtained results showed a significant increased growth performance, immune response, highest antioxidant activity and serum HDL with lowest serum LDL and triglycerides levels in all experimental groups compared with control group, which was highly significant in group fed on vitamin B6.

Keywords: omega fatty acids, broiler, feeding, human health, growth performance, immunity

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Authors: Younghoon Kim, Seoung Bum Kim

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One-class classification plays an important role in detecting outlier and abnormality from normal observations. In the previous research, several attempts were made to extend the scope of application of the one-class classification techniques to statistical process control problems. For most previous approaches, such as support vector data description (SVDD) control chart, the design of the control limits is commonly based on the assumption that the proportion of abnormal observations is approximately equal to an expected Type I error rate in Phase I process. Because of the limitation of the one-class classification techniques based on convex optimization, we cannot make the proportion of abnormal observations exactly equal to expected Type I error rate: controlling Type I error rate requires to optimize constraints with integer decision variables, but convex optimization cannot satisfy the requirement. This limitation would be undesirable in theoretical and practical perspective to construct effective control charts. In this work, to address the limitation of previous approaches, we propose the one-class classification algorithm based on the mixed integer programming technique, which can solve problems formulated with continuous and integer decision variables. The proposed method minimizes the radius of a spherically shaped boundary subject to the number of normal data to be equal to a constant value specified by users. By modifying this constant value, users can exactly control the proportion of normal data described by the spherically shaped boundary. Thus, the proportion of abnormal observations can be made theoretically equal to an expected Type I error rate in Phase I process. Moreover, analogous to SVDD, the boundary can be made to describe complex structures by using some kernel functions. New multivariate control chart applying the effectiveness of the algorithm is proposed. This chart uses a monitoring statistic to characterize the degree of being an abnormal point as obtained through the proposed one-class classification. The control limit of the proposed chart is established by the radius of the boundary. The usefulness of the proposed method was demonstrated through experiments with simulated and real process data from a thin film transistor-liquid crystal display.

Keywords: control chart, mixed integer programming, one-class classification, support vector data description

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Authors: Mahdi Nasiri Tabrizi, A. Dadkhah, M. Khirkhah

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In order to study the effect of planting on yield, yield components and quality traits in bread and durum wheat varieties, a field split-plot experiment based on complete randomized design with three replications was conducted in Agricultural and Natural Resources Research Center of Razavi Khorasan located in city of Mashhad during 2013-2014. Main factor were consisted of five sowing dates (first October, fifteenth December, first March, tenth March, twentieth March) and as sub-factors consisted of different bread wheat (Bahar, Pishgam, Pishtaz, Mihan, Falat and Karim) and two durum wheat (Dena and Dehdasht). According to results of analysis variance the effect of planting date was significant on all examined traits (grain yield, biological yield, harvest index, number of grain per spike, thousands kernel weight, number of spike per square meter, plant height, the number of days to heading, the number of days to maturity, during the grain filling period, percentage of wet gluten, percentage of dry gluten, gluten index, percentage of protein). By delay in planting, majority of traits significantly decreased, except quality traits (percentage of wet gluten, percentage of dry gluten and percentage of protein). Results of means comparison showed, among planting date the highest grain yield and biological yield were related to first planting date (Octobr) with mean of production of 5/6 and 1/17 tons per hectare respectively and the highest bread quality (gluten index) with mean of 85 and percentage of protein with mean of 13% to fifth planting date also the effect of genotype was significant on all traits. The highest grain yield among of studied wheat genotypes was related to Dehdasht cultivar with an average production of 4.4 tons per hectare. The highest protein percentage and bread quality (gluten index) were related to Dehdasht cultivar with 13.4% and Falat cultivar with number of 90 respectively. The interaction between cultivar and planting date was significant on all traits and different varieties had different trend for these traits. The highest grain yield was related to first planting date (October) and Falat cultivar with an average of production of 6/7 tons per hectare while in grain yield did not show a significant different with Pishtas and Mihan cultivars also the most of gluten index (bread quality index) and protein percentage was belonged to the third planting date and Karim cultivar with 7.98 and Dena cultivar with 7.14% respectively.

Keywords: yield component, yield, planting date, cultivar, quality traits, wheat

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Authors: Ayodeji Oluleye

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This study used Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) and reanalysis dataset of thirty years (1983-2012) to investigate the influence of the atmospheric circulation on dust transport during the Harmattan period over WestAfrica using TOMS data. The Harmattan dust mobilization and atmospheric circulation pattern were evaluated using a kernel density estimate which shows the areas where most points are concentrated between the variables. The evolution of the Inter-Tropical Discontinuity (ITD), Sea surface Temperature (SST) over the Gulf of Guinea, and the North Atlantic Oscillation (NAO) index during the Harmattan period (November-March) was also analyzed and graphs of the average ITD positions, SST and the NAO were observed on daily basis. The Pearson moment correlation analysis was also employed to assess the effect of atmospheric circulation on Harmattan dust transport. The results show that the departure (increased) of TOMS AI values from the long-term mean (1.64) occurred from around 21st of December, which signifies the rich dust days during winter period. Strong TOMS AI signal were observed from January to March with the maximum occurring in the latter months (February and March). The inter-annual variability of TOMSAI revealed that the rich dust years were found between 1984-1985, 1987-1988, 1997-1998, 1999-2000, and 2002-2004. Significantly, poor dust year was found between 2005 and 2006 in all the periods. The study has found strong north-easterly (NE) trade winds were over most of the Sahelianregion of West Africa during the winter months with the maximum wind speed reaching 8.61m/s inJanuary.The strength of NE winds determines the extent of dust transport to the coast of Gulf of Guinea during winter. This study has confirmed that the presence of the Harmattan is strongly dependent on theSST over Atlantic Ocean and ITD position. The locus of the average SST and ITD positions over West Africa could be described by polynomial functions. The study concludes that the evolution of near surface wind field at 925 hpa, and the variations of SST and ITD positions are the major large scale atmospheric circulation systems driving the emission, distribution, and transport of Harmattan dust aerosols over West Africa. However, the influence of NAO was shown to have fewer significance effects on the Harmattan dust transport over the region.

Keywords: atmospheric circulation, dust aerosols, Harmattan, West Africa

Procedia PDF Downloads 292

Authors: Temitayo Abayomi Ewemoje, Oluwamayowa Oluwafemi Oluwaniyi

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Agriculture and food processing, industry are among the largest industrial sectors that uses large amount of energy. Thus, a larger amount of gases from their fuel combustion technologies is being released into the environment. The choice of input energy supply not only directly having affects the environment, but also poses a threat to human health. The study was therefore designed to assess each unit production processes in order to identify hotspots using life cycle assessments (LCA) approach in South-western Nigeria. Data such as machine power rating, operation duration, inputs and outputs of shea butter materials for unit processes obtained at site were used to modelled Life Cycle Impact Analysis on GaBi6 (Holistic Balancing) software. Four scenarios were drawn for the impact assessments. Material sourcing from Kaiama, Scenarios 1, 3 and Minna Scenarios 2, 4 but different heat supply sources (Liquefied Petroleum Gas ‘LPG’ Scenarios 1, 2 and 10.8 kW Diesel Heater, scenarios 3, 4). Modelling of shea butter production on GaBi6 was for 1kg functional unit of shea butter produced and the Tool for the Reduction and Assessment of Chemical and other Environmental Impacts (TRACI) midpoint assessment was tool used to was analyse the life cycle inventories of the four scenarios. Eight categories in all four Scenarios were observed out of which three impact categories; Global Warming Potential (GWP) (0.613, 0.751, 0.661, 0.799) kg CO2¬-Equiv., Acidification Potential (AP) (0.112, 0.132, 0.129, 0.149) kg H+ moles-Equiv., and Smog (0.044, 0.059, 0.049, 0.063) kg O3-Equiv., categories had the greater impacts on the environment in Scenarios 1-4 respectively. Impacts from transportation activities was also seen to contribute more to these environmental impact categories due to large volume of petrol combusted leading to releases of gases such as CO2, CH4, N2O, SO2, and NOx into the environment during the transportation of raw shea kernel purchased. The ratio of transportation distance from Minna and Kaiama to production site was approximately 3.5. Shea butter unit processes with greater impacts in all categories was the packaging, milling and with the churning processes in ascending order of magnitude was identified as hotspots that may require attention. From the 1kg shea butter functional unit, it was inferred that locating production site at the shortest travelling distance to raw material sourcing and combustion of LPG for heating would reduce all the impact categories assessed on the environment.

Keywords: GaBi6, Life cycle assessment, shea butter production, TRACI

Procedia PDF Downloads 289

Authors: Inyoung Park, Youngjoo Woo, Euiseong Seo

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With the advent of WebGL, Web apps are now able to provide high quality graphics by utilizing the underlying graphic processing units (GPUs). Despite that the Web apps are becoming common and popular, the current power management schemes, which were devised for the conventional native applications, are suboptimal for Web apps because of the additional layer, the Web browser, between OS and application. The Web browser running on a CPU issues GL commands, which are for rendering images to be displayed by the Web app currently running, to the GPU and the GPU processes them. The size and number of issued GL commands determine the processing load of the GPU. While the GPU is processing the GL commands, CPU simultaneously executes the other compute intensive threads. The actual user experience will be determined by either CPU processing or GPU processing depending on which of the two is the more demanded resource. For example, when the GPU work queue is saturated by the outstanding commands, lowering the performance level of the CPU does not affect the user experience because it is already deteriorated by the retarded execution of GPU commands. Consequently, it would be desirable to lower CPU or GPU performance level to save energy when the other resource is saturated and becomes a bottleneck in the execution flow. Based on this observation, we propose a power management scheme that is specialized for the Web app runtime environment. This approach incurs two technical challenges; identification of the bottleneck resource and determination of the appropriate performance level for unsaturated resource. The proposed power management scheme uses the CPU utilization level of the Window Manager to tell which one is the bottleneck if exists. The Window Manager draws the final screen using the processed results delivered from the GPU. Thus, the Window Manager is on the critical path that determines the quality of user experience and purely executed by the CPU. The proposed scheme uses the weighted average of the Window Manager utilization to prevent excessive sensitivity and fluctuation. We classified Web apps into three categories using the analysis results that measure frame-per-second (FPS) changes under diverse CPU/GPU clock combinations. The results showed that the capability of the CPU decides user experience when the Window Manager utilization is above 90% and consequently, the proposed scheme decreases the performance level of CPU by one step. On the contrary, when its utilization is less than 60%, the bottleneck usually lies in the GPU and it is desirable to decrease the performance of GPU. Even the processing unit that is not on critical path, excessive performance drop can occur and that may adversely affect the user experience. Therefore, our scheme lowers the frequency gradually, until it finds an appropriate level by periodically checking the CPU utilization. The proposed scheme reduced the energy consumption by 10.34% on average in comparison to the conventional Linux kernel, and it worsened their FPS by 1.07% only on average.

Keywords: interactive applications, power management, QoS, Web apps, WebGL

Procedia PDF Downloads 168

Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu

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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.

Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature

Procedia PDF Downloads 182

Authors: Omar Shafqat, Jaime Arias, Cristian Bogdan, Björn Palm

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Heating constitutes a major part of the overall energy consumption in Sweden. In 2013 heating and hot water accounted for about 55% of the total energy use in the housing sector. Historically, the end users have not been able to make a significant impact on their consumption on account of traditional control systems that do not facilitate interaction and control of the heating systems. However, in recent years internet connected home energy management systems have become increasingly available which allow users to visualize the indoor temperatures as well as control the heating system. However, the adoption of these systems is still in its nascent stages. This paper presents the outcome of a study carried out in a community of single-family houses in Stockholm. Heating in the area is provided through district heating, and the neighbourhood is connected through a local micro thermal grid, which is owned and operated by the local community. Heating in the houses is accomplished through a hydronic system equipped with radiators. The system installed offers the households to control the indoor temperature through a mobile application as well as through a physical thermostat. It was also possible to program the system to, for instance, lower the temperatures during night time and when the users were away. The users could also monitor the indoor temperatures through the application. It was additionally possible to create different zones in the house with their own individual programming. The historical heating data (in the form of billing data) was available for several previous years and has been used to perform quantitative analysis for the study after necessary normalization for weather variations. The experiment involved 30 households out of a community of 178 houses. The area was selected due to uniform construction profile in the area. It was observed that despite similar design and construction period there was a large variation in the heating energy consumption in the area which can for a large part be attributed to user behaviour. The paper also presents qualitative analysis done through survey questions as well as a focus group carried out with the participants. Overall, considerable energy savings were accomplished during the trial, however, there was a considerable variation between the participating households. The paper additionally presents recommendations to improve the impact of home energy management systems for heating in terms of improving user engagement and hence the energy impact.

Keywords: energy efficiency in buildings, energy behavior, heating control system, home energy management system

Procedia PDF Downloads 147

Authors: Hamza Benzerrouk, Alexander Nebylov

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In classical GNSS/INS integration designs, the loosely coupled approach uses the GNSS derived position and the velocity as the measurements vector. This design is suboptimal from the standpoint of preventing GNSSoutliers/outages. The tightly coupled GPS/INS navigation filter mixes the GNSS pseudo range and inertial measurements and obtains the vehicle navigation state as the final navigation solution. The ultra‐tightly coupled GNSS/INS design combines the I (inphase) and Q(quadrature) accumulator outputs in the GNSS receiver signal tracking loops and the INS navigation filter function intoa single Kalman filter variant (EKF, UKF, SPKF, CKF and HCKF). As mentioned, EKF and UKF are the most used nonlinear filters in the literature and are well adapted to inertial navigation state estimation when integrated with GNSS signal outputs. In this paper, it is proposed to move a step forward with more accurate filters and modern approaches called Cubature and High Degree cubature Kalman Filtering methods, on the basis of previous results solving the state estimation based on INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (HCKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQKF). Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. In ultra tightly or a deeply coupled GNSS/INS system is dynamics EKF is used with transition matrix factorization together with GNSS block processing which is well described in the paper and assumes available the intermediary frequency IF by using a correlator samples with a rate of 500 Hz in the presented approach. GNSS (GPS+GLONASS) measurements are assumed available and modern SPKF with Cubature Kalman Filter (CKF) are compared with new versions of CKF called high order CKF based on Spherical-radial cubature rules developed at the fifth order in this work. Estimation accuracy of the high degree CKF is supposed to be comparative to GHKF, results of state estimation are then observed and discussed for different initialization parameters. Results show more accurate navigation state estimation and more robust GNSS receiver when Ultra Tightly Coupled approach applied based on High Degree Cubature Kalman Filter.

Keywords: GNSS, INS, Kalman filtering, ultra tight integration

Procedia PDF Downloads 261

Authors: Nathalie Stephenne, Mathieu Veschkens, Stéphane Palm, Christophe Charlemagne, Jacques Defoux

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According to Europe’s first River basin Management Plans (RBMPs), 56% of European rivers failed to achieve the good status targets of the Water Framework Directive WFD. In Central European countries such as Belgium, even more than 80% of rivers failed to achieve the WFD quality targets. Although the RBMP’s should reduce the stressors and improve water body status, their potential to address multiple stress situations is limited due to insufficient knowledge on combined effects, multi-stress, prioritization of measures, impact on ecology and implementation effects. This paper describes a webGis prototype developed for the Walloon administration to improve the communication and the management of sediment dredging actions carried out in rivers and lakes in the frame of RBMPs. A large number of stakeholders are involved in the management of rivers and lakes in Wallonia. They are in charge of technical aspects (client and dredging operators, organizations involved in the treatment of waste…), management (managers involved in WFD implementation at communal, provincial or regional level) or policy making (people responsible for policy compliance or legislation revision). These different kinds of stakeholders need different information and data to cover their duties but have to interact closely at different levels. Moreover, information has to be shared between them to improve the management quality of dredging operations within the ecological system. In the Walloon legislation, leveling dredged sediments on banks requires an official authorization from the administration. This request refers to spatial information such as the official land use map, the cadastral map, the distance to potential pollution sources. The production of a collective geodatabase can facilitate the management of these authorizations from both sides. The proposed internet system integrates documents, data input, integration of data from disparate sources, map representation, database queries, analysis of monitoring data, presentation of results and cartographic visualization. A prototype of web application using the API geoviewer chosen by the Geomatic department of the SPW has been developed and discussed with some potential users to facilitate the communication, the management and the quality of the data. The structure of the paper states the why, what, who and how of this communication tool.

Keywords: sediments, web application, GIS, rivers management

Procedia PDF Downloads 387

Authors: Michal Pravenec, Miroslava Simakova, Jan Silhavy

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Brown adipose tissue (BAT) plays an important role in lipid and glucose metabolism in rodents and possibly also in humans. Recently, using systems genetics approach in the BAT from BXH/HXB recombinant inbred strains, derived from the SHR (spontaneously hypertensive rat) and BN (Brown Norway) progenitors, we identified Cd36 (fatty acid translocase) as the hub gene of co-expression module associated with BAT relative weight and function. An important aspect of BAT biology is to better understand the mechanisms regulating the uptake and utilization of fatty acids and glucose. Accordingly, BAT function in the SHR that harbors mutant nonfunctional Cd36 variant (hereafter referred to as SHR-Cd36⁻/⁻) was compared with SHR transgenic line expressing wild type Cd36 under control of a universal promoter (hereafter referred to as SHR-Cd36⁺/⁺). BAT was incubated in media containing insulin and 14C-U-glucose alone or 14C-U-glucose together with palmitate. Incorporation of glucose into BAT lipids was significantly higher in SHR-Cd36⁺/⁺ versus SHR-Cd36⁻/⁻ rats when incubation media contained glucose alone (SHR-Cd36⁻/⁻ 591 ± 75 vs. SHR-Cd36⁺/⁺ 1036 ± 135 nmol/gl./2h; P < 0.005). Adding palmitate into incubation media had no effect in SHR-Cd36⁻/⁻ rats but significantly reduced glucose incorporation into BAT lipids in SHR-Cd36⁺/⁺ (SHR-Cd36⁻/⁻ 543 ± 55 vs. SHR-Cd36⁺/⁺ 766 ± 75 nmol/gl./2h; P < 0.05 denotes significant Cd36 x palmitate interaction determined by two-way ANOVA). This Cd36-dependent reduced glucose uptake in SHR-Cd36⁺/⁺ BAT was likely secondary to increased palmitate incorporation and utilization due to the presence of wild type Cd36 fatty acid translocase in transgenic rats. This possibility is supported by increased incorporation of 14C-U-palmitate into BAT lipids in the presence of both palmitate and glucose in incubation media (palmitate alone: SHR-Cd36⁻/⁻ 870 ± 21 vs. SHR-Cd36⁺/⁺ 899 ± 42; glucose+palmitate: SHR-Cd36⁻/⁻ 899 ± 47 vs. SHR-Cd36⁺/⁺ 1460 ± 111 nmol/palm./2h; P < 0.05 denotes significant Cd36 x glucose interaction determined by two-way ANOVA). It is possible that addition of glucose into the incubation media increased palmitate incorporation into BAT lipids in SHR-Cd36⁺/⁺ rats because of glucose availability for glycerol phosphate production and increased triglyceride synthesis. These changes in glucose and palmitate incorporation into BAT lipids were associated with significant differential expression of Irs1, Irs2, Slc2a4 and Foxo1 genes involved in insulin signaling and glucose metabolism only in SHR-Cd36⁺/⁺ rats which suggests Cd36-dependent effects on insulin action. In conclusion, these results provide compelling evidence that Cd36 plays an important role in BAT insulin signaling and energy substrate utilization.

Keywords: brown adipose tissue, Cd36, energy substrate utilization, insulin signaling, spontaneously hypertensive rat

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Authors: Leslie Nobler

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African fabrics based specifically on the Dutch Wax Print, or Ankara, popularized during Africa's colonial era, have had an enormous impact on western fashion (especially in the US and UK), in the last half-decade. The trend has had an effect on the world of visual arts as well, which circuitously, also heavily impacts fashion design. In fashion, and notably in celebrity apparel choices, this is in part due to ‘identity’ and taking pride in one's African roots; in the visual arts, artists such as Yinka Shonibare and Njideka Akunyili Crosby are making statements about identity politics, colonialism up through post-colonialism, and racism. The ‘global village’ brought on by the internet has driven this proliferation, as have improvements in the printing technology with which the Ankara print is made, combining wax-resist with roller printing. The newest patterns can now be designed authentically in western African and easily sent electronically to Europe for printing. Examples of Ankara's new reach across the Atlantic abound. They have taken several paths, which the paper will detail. Briefly, the first is its greater utilization in the fashion world, from authentic textile shops in African American neighborhoods to copied (knocked-off) low-end reproductions in discount chains. Secondly, we are seeing far more uses of these textiles/patterns in important works of fine arts from major museums, in Philadelphia to Palm Beach to the Mass MOCA (in the US), all the way to the Israel Museum in Jerusalem, and everywhere in between. And lastly, but quite significantly, we see this trend throughout social media thanks to Instagram, Pinterest and celebrity photos –even at the recent royal wedding. What shall sustain this major new design direction is that Ankara changes with and adapts to the times. Some of it is now printed in West Africa, often in the Nigeria area. And some may be designed in Europe or even at knock-off apparel studios in NY or Asia. But it stays utterly relevant because the motifs are based on objects and scenes in everyday life. In my design studio and university design classes, this idea is first and foremost, from our big spiritual eye motifs to drawings of our art supplies to the ‘politically-loaded’ chain patterns. This first-hand creativity experience becomes part of the research of this paper, along with historic and contemporary sources of inquiry, both through a literature/image search and anecdotal experience into what is behind this exciting and surprising trend.

Keywords: African wax print, Ankara, identity (politics), textile design, surface design

Procedia PDF Downloads 111

Authors: Aprajeeta Jha, Punyadarshini P. Tripathy

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Drying technologies for various food processing operations shares an inevitable linkage with energy, cost and environmental sustainability. Hence, solar drying of food grains has become imperative choice to combat duo challenges of meeting high energy demand for drying and to address climate change scenario. But performance and reliability of solar dryers depend hugely on sunshine period, climatic conditions, therefore, offer a limited control over drying conditions and have lower efficiencies. Solar drying technology, supported by Photovoltaic (PV) power plant and hybrid type solar air collector can potentially overpower the disadvantages of solar dryers. For development of such robust hybrid dryers; to ensure quality and shelf-life of paddy grains the optimization of process parameter becomes extremely critical. Investigation of the moisture distribution profile within the grains becomes necessary in order to avoid over drying or under drying of food grains in hybrid solar dryer. Computational simulations based on finite element modeling can serve as potential tool in providing a better insight of moisture migration during drying process. Hence, present work aims at optimizing the process parameters and to develop a 3-dimensional (3D) finite element model (FEM) for predicting moisture profile in paddy during solar drying. COMSOL Multiphysics was employed to develop a 3D finite element model for predicting moisture profile. Furthermore, optimization of process parameters (power level, air velocity and moisture content) was done using response surface methodology in design expert software. 3D finite element model (FEM) for predicting moisture migration in single kernel for every time step has been developed and validated with experimental data. The mean absolute error (MAE), mean relative error (MRE) and standard error (SE) were found to be 0.003, 0.0531 and 0.0007, respectively, indicating close agreement of model with experimental results. Furthermore, optimized process parameters for drying paddy were found to be 700 W, 2.75 m/s at 13% (wb) with optimum temperature, milling yield and drying time of 42˚C, 62%, 86 min respectively, having desirability of 0.905. Above optimized conditions can be successfully used to dry paddy in PV integrated solar dryer in order to attain maximum uniformity, quality and yield of product. PV-integrated hybrid solar dryers can be employed as potential and cutting edge drying technology alternative for sustainable energy and food security.

Keywords: finite element modeling, moisture migration, paddy grain, process optimization, PV integrated hybrid solar dryer

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Bharti Singh, Shri K. Singh

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Child malnutrition is a multifaceted issue that transcends geographical boundaries. Malnutrition not only stunts physical growth but also leads to a spectrum of morbidities and child mortality. It is one of the leading causes of death (~50 %) among children under age five. Despite economic progress and advancements in healthcare, child malnutrition remains a formidable challenge for India. The objective is to investigate the impact of women's empowerment on child nutrition outcomes in India from 2006 to 2021. A composite index of women's empowerment was constructed using Confirmatory Factor Analysis (CFA), a rigorous technique that validates the measurement model by assessing how well-observed variables represent latent constructs. This approach ensures the reliability and validity of the empowerment index. Secondly, kernel density plots were utilised to visualise the distribution of key nutritional indicators, such as stunting, wasting, and overweight. These plots offer insights into the shape and spread of data distributions, aiding in understanding the prevalence and severity of malnutrition. Thirdly, linear polynomial graphs were employed to analyse how nutritional parameters evolved with the child's age. This technique enables the visualisation of trends and patterns over time, allowing for a deeper understanding of nutritional dynamics during different stages of childhood. Lastly, multilevel analysis was conducted to identify vulnerable levels, including State-level, PSU-level, and household-level factors impacting undernutrition. This approach accounts for hierarchical data structures and allows for the examination of factors at multiple levels, providing a comprehensive understanding of the determinants of child malnutrition. Overall, the utilisation of these statistical methodologies enhances the transparency and replicability of the study by providing clear and robust analytical frameworks for data analysis and interpretation. Our study reveals that NFHS-4 and NFHS-5 exhibit an equal density of severely stunted cases. NFHS-5 indicates a limited decline in wasting among children aged five, while the density of severely wasted children remains consistent across NFHS-3, 4, and 5. In 2019-21, women with higher empowerment had a lower risk of their children being undernourished (Regression coefficient= -0.10***; Confidence Interval [-0.18, -0.04]). Gender dynamics also play a significant role, with male children exhibiting a higher susceptibility to undernourishment. Multilevel analysis suggests household-level vulnerability (intra-class correlation=0.21), highlighting the need to address child undernutrition at the household level.

Keywords: child nutrition, India, NFHS, women’s empowerment

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Authors: Yik Sin Chan, Bee Ling Chuah, Wei Quan Chan, Ri Jin Cheng, Yan Hang Oon, Kong Soo Khoo, Nam Weng Sit

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Traditionally, medicinal plants have been used to treat different kinds of ailments including infectious diseases. They serve as a good source of lead compounds for the development of new and safer anti-infective agents. This study aimed to investigate the antimicrobial potential of the leaves of three medicinal plants, namely Catunaregam spinosa (Rubiaceae; Mountain pomegranate), Houttuynia cordata (Saururaceae; "fishy-smell herb") and Rhapis excelsa (Arecaceae; “broadleaf lady palm”). The leaves extracts were obtained by sequential extraction using hexane, chloroform, ethyl acetate, ethanol, methanol and water. The antibacterial and antifungal activities were assessed using a colorimetric broth microdilution method against a panel of human pathogenic bacteria (Gram-positive: Bacillus cereus and Staphylococcus aureus; Gram-negative: Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa) and fungi (yeasts: Candida albicans, Candida parapsilosis and Cryptococcus neoformans; Moulds: Aspergillus fumigatus and Trichophyton mentagrophytes) respectively; while antiviral activity was evaluated against the Chikungunya virus on monkey kidney epithelial (Vero) cells by neutral red uptake assay. All the plant extracts showed bacteriostatic activity, however, only 72% of the extracts (13/18) were found to have bactericidal activity. The lowest minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were given by the hexane extract of C. spinosa against S. aureus with the values of 0.16 and 0.31 mg/mL respectively. All the extracts also possessed fungistatic activity. Only the hexane, chloroform and ethyl acetate extracts of H. cordata exerted inhibitory activity against A. fumigatus, giving the lowest fungal susceptibility index of 16.7%. In contrast, only 61% of the extracts (11/18) showed fungicidal activity. The ethanol extract of R. excelsa exhibited the strongest fungicidal activity against C. albicans, C. parapsilosis and T. mentagrophytes with minimum fungicidal concentration (MFC) values of 0.04–0.08 mg/mL, in addition to its methanol extract against T. mentagrophytes (MFC=0.02 mg/mL). For anti-Chikungunya virus activity, only chloroform and ethyl acetate extracts of R. excelsa showed significant antiviral activity with 50% effective concentrations (EC50) of 29.9 and 78.1 g/mL respectively. Extracts of R. excelsa warrant further investigations into their active principles responsible for antifungal and antiviral properties.

Keywords: bactericidal, Chikungunya virus, extraction, fungicidal

Procedia PDF Downloads 381

Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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