Search results for: microbial detection

Authors: Emhimed Saffor

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In this paper, the problem of edge detection in digital images is considered. Three methods of edge detection based on mathematical morphology algorithm were applied on two sets (Brain and Chest) CT images. 3x3 filter for first method, 5x5 filter for second method and 7x7 filter for third method under MATLAB programming environment. The results of the above-mentioned methods are subjectively evaluated. The results show these methods are more efficient and satiable for medical images, and they can be used for different other applications.

Keywords: CT images, Matlab, medical images, edge detection

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Authors: Mustafa Salman, Nurcan Cetinkaya, Zehra Selcuk, Bugra Genc

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The objectives of the present study were to estimate the microbial-N flow to the small intestine and to predict the digestible organic matter intake (DOMI) in grazing Karayaka sheep based on urinary excretion of purine derivatives (xanthine, hypoxanthine, uric acid, and allantoin) by the use of spot urine sampling under field conditions. In the trial, 10 Karayaka sheep from 2 to 3 years of age were used. The animals were grazed in a pasture for ten months and fed with concentrate and vetch plus oat hay for the other two months (January and February) indoors. Highly significant linear and cubic relationships (P<0.001) were found among months for purine derivatives index, purine derivatives excretion, purine derivatives absorption, microbial-N and DOMI. Through urine sampling and the determination of levels of excreted urinary PD and Purine Derivatives / Creatinine ratio (PDC index), microbial-N values were estimated and they indicated that the protein nutrition of the sheep was insufficient. In conclusion, the prediction of protein nutrition of sheep under the field conditions may be possible with the use of spot urine sampling, urinary excreted PD and PDC index. The mean purine derivative levels in spot urine samples from sheep were highest in June, July and October. Protein nutrition of pastured sheep may be affected by weather changes, including rainfall. Spot urine sampling may useful in modeling the feed consumption of pasturing sheep. However, further studies are required under different field conditions with different breeds of sheep to develop spot urine sampling as a model.

Keywords: Karayaka sheep, spot sampling, urinary purine derivatives, PDC index, microbial-N, feed intake

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Authors: Siddig H. Hamad, Salah M. Al-Eid, Fahad M. Al-Jassas

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Composite samples of minced chicken were vacuum-packaged and pressure treated at 300, 400, 450 and 500 MPa in a Stansted 'FOOD-LAB' model S-FL-850-9-W high hydrostatic pressure research apparatus (Stansted Fluid Power Ltd., Stansted, UK). Treated and untreated samples were then stored at 3°C, and microbial content as well as some chemical and physical properties monitored. The microbial load of the untreated samples reached the spoilage level of 107 cfu/g in about one week, resulting in bad smell and dark brown color. The pressure treatments reduced total bacterial counts by about 1.8 to 3.2 log10 cycles and reduced counts of Enterobacteriaceae and Salmonella to non-detectable levels. The color of meat was slightly affected, but pH, moisture content and the oxidation products of lipids were not substantially changed. The treatment killed mainly gram negative bacteria but also caused sub-lethal injury to part of the population resulting in prolonged lag phase. The population not killed by the 350 to 450 MPa treatments grew relatively slowly during storage, and its loads reached spoilage level in 4 to 6 weeks, while the load of the population treated at 500 MPa did not reach this level till the end of a storage period of 9 weeks.

Keywords: chicken, cold storage, microbial spoilage, high hydrostatic pressure

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Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

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The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

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Authors: Salah Mohammed Al-Eid, Siddig Hussein Hamad, Fahad Mohammed Aljassas

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The effects of high hydrostatic pressure (HHP) treatments on microbial contamination, chemical and physical properties of fresh dates (Rutab stage) were studied. Khalas, Barhi and Hilali cultivars were treated at 200, 250, 300 and 350 MPa using HHP research apparatus. The objective of such treatments was to preserve fresh dates without adversely affecting its properties. Treating fresh dates at 300 MPa for 5 minutes at 40°C reduced microbial contamination in about 2.5 log cycles. Applying 250 MPa was enough to control Rutab contamination with molds, yeasts, and coliforms. Both treatments were enough to reduce Rutab microbial contamination to acceptable levels. HHP caused no significant effect on Rutab chemical properties (moisture, sugars, protein, pectin and acidity). However, a slight decrease in moisture contents due to HHP was observed. Rutab lightness (L*) significantly decreased due to the application of HHP. Only Rutab treated at 300 MPs gave lower redness (a*) values compared with an untreated sample. The effect of 300 MPa on increasing yellowness (b*) was observed for Barhi and Hilali but decreasing for Khalas. The hardness of all Rutab cultivars significantly decreased as a result of HHP application. In fact, the pressure applied at 300 MPa had an adverse effect on texture, which may limit its suitability for use in Rutab preservation.

Keywords: high hydrostatic pressure, fresh dates (Rutab), microbial contamination, color, texture

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Authors: Tahra El-Obeid, Reham Mousa, Amal Alzahiri

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During the past few years the traditional market of Qatar has become an attraction to many customers who eat from the numerous women street vendors selling Qatari traditional dishes. To gain an understanding on the safety of these street vended foods, we designed the study to test microbiological quality of 14 different Qatari foods sold in Souk Wagif, the main traditional market in Qatar. This study was conducted to mainly identify presence or absence of microbial pathogens. A total of 56 samples were purchased from 10 different street vendors and the samples were collected randomly on different days. The samples were tested for microbial contaminants at Central Food Laboratories, Doha, Qatar. The qualitative study was conducted using Real Time-PCR to screen for; Salmonella spp., Listeria monocytogenes, Escherichia coli and E. coli 0157:H7. Out of the 56 samples, only two samples “Biryani” and “Khabess” contained E. coli. However, both samples tested negative for E. coli O157:H7. The microbial contamination of the Qatari traditional street vended foods was 3%. This result may be attributed to the food safety training requirement set by the regulatory authorities before issuing any license to food handlers in Qatar as well as the food inspection conducted by the food health inspectors on a regular basis.

Keywords: microbiological quality, street vended food, traditional dishes, Qatar

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Authors: A. Natsir, M. Nadir, S. Syahrir, A. Mujnisa, N. Purnomo, A. R. Egan, B. J. Leury

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Rumen degradation characteristic of feedstuff is one of the prominent factors affecting microbial population in rumen of animal. High rumen degradation rate of faba bean protein may lead to inconstant rumen conditions that could have a prominent impact on rumen microbial diversity. Amplified Ribosomal DNA Restriction Analysis (ARDRA) is utilized to monitor diversity of rumen microbes on sheep fed low quality forage supplemented by faba beans. Four mature merino sheep with existing rumen cannula were used in this study according to 4 x 4 Latin square design. The results of study indicated that there were 37 different ARDRA types identified out of 136 clones examined. Among those clones, five main clone types existed across the treatments with different percentages. In conclusion, the ARDRA method is potential to be used as a routine tool to assess the temporary changes in the rumen community as a result of different feeding strategies.

Keywords: ARDRA method, cattle, genomic diversity, rumen microbes

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Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh

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In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically.

Keywords: spectral index, shadow detection, remote sensing images, World-View 2

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Authors: Hadjer Didouh, Mohammed Hadj Meliani, Izzaddine Sameut Bouhaik

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This study employs a multidisciplinary approach to investigate the intricate processes governing biofilm-surface interactions. Results indicate that surface properties significantly influence initial microbial attachment, with materials characterized by increased roughness and hydrophobicity promoting enhanced biofilm adhesion. Moreover, the chemical composition of materials plays a crucial role in impacting the development of biofilms. Environmental factors, such as temperature fluctuations and nutrient availability, were identified as key determinants affecting biofilm formation dynamics. Advanced imaging techniques revealed complex three-dimensional biofilm structures, emphasizing microbial communication and cooperation within these networks. These findings offer practical implications for industries operating in crude oil environments, guiding the selection and design of materials to mitigate biofilm-related challenges and enhance operational efficiency in such settings.

Keywords: biofilm adhesion, surface properties, crude oil environments, microbial interactions, multidisciplinary investigation

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Authors: Abimbola M. Enitan, John O. Odiyo, Feroz M. Swalaha

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The study of microbial ecology and their function in anaerobic digestion processes are essential to control the biological processes. This is to know the symbiotic relationship between the microorganisms that are involved in the conversion of complex organic matter in the industrial wastewater to simple molecules. In this study, diversity and quantity of bacterial community in the granular sludge taken from the different compartments of a full-scale upflow anaerobic sludge blanket (UASB) reactor treating brewery wastewater was investigated using polymerase chain reaction (PCR) and real-time quantitative PCR (qPCR). The phylogenetic analysis showed three major eubacteria phyla that belong to Proteobacteria, Firmicutes and Chloroflexi in the full-scale UASB reactor, with different groups populating different compartment. The result of qPCR assay showed high amount of eubacteria with increase in concentration along the reactor’s compartment. This study extends our understanding on the diverse, topological distribution and shifts in concentration of microbial communities in the different compartments of a full-scale UASB reactor treating brewery wastewater. The colonization and the trophic interactions among these microbial populations in reducing and transforming complex organic matter within the UASB reactors were established.

Keywords: bacteria, brewery wastewater, real-time quantitative PCR, UASB reactor

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Authors: Qingqing Zhao, Junhong Bai

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To investigate the effects of salinity on dynamics of soil carbon and nitrogen contents and stocks, soil samples were collected at a depth of 30 cm at four sampling sites (Sites B, T, S and P) along a salinity gradient in a drained coastal wetland, the Yellow River Delta, China. The salinity of these four sites ranked in the order: B (8.68±4.25 ms/cm) > T (5.89±3.17 ms/cm) > S (3.19±1.01 ms/cm) > P (2.26±0.39 ms/cm). Soil total carbon (TC), soil organic carbon (SOC), soil microbial biomass carbon (MBC), soil total nitrogen (TC) and soil microbial biomass carbon (MBC) were measured. Based on these data, soil organic carbon density (SOCD), soil microbial biomass carbon density (MBCD), soil nitrogen density (TCD) and soil microbial biomass nitrogen density (MBND) were calculated at four sites. The results showed that the mean concentrations of TC, SOC, MBC, TN and MBN showed a general deceasing tendency with increasing salinities in the top 30 cm of soils. The values of SOCD, MBCD, TND and MBND exhibited similar tendency along the salinity gradient. As for profile distribution pattern, The C/N ratios ranged from 8.28 to 56. 51. Higher C/N ratios were found in samples with high salinity. Correlation analysis showed that the concentrations of TC, SOC and MBC at four sampling sites were significantly negatively correlated with salinity (P < 0.01 or P < 0.05), indicating that salinity could inhibit soil carbon accumulation. However, no significant relationship was observed between TN, MBN and salinity (P > 0.05).

Keywords: carbon content and stock, nitrogen content and stock, salinity, coastal wetland

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Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

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Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

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In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: Parminder Kaur, Chandrajit B. Majumder

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The unrestrained usage of pesticides to meet the burgeoning demand of enhanced crop productivity has led to the serious contamination of both terrestrial and aquatic ecosystem. The remediation of mixture of pesticides is a challenging affair regarding inadvertent mixture of pesticides from agricultural lands treated with various compounds. Global concerns about the excessive use of pesticides have driven the need to develop more effective and safer alternatives for their remediation. We focused our work on the microbial degradation of a mixture of three Type II-pyrethroids, namely Cypermethrin, Cyhalothrin and Deltamethrin commonly applied for both agricultural and domestic purposes. The fungal strains (Fusarium strain 8-11P and Fusarium sp. zzz1124) had previously been isolated from agricultural soils and their ability to biotransform this amalgam was studied. In brief, the experiment was conducted in two growth systems (added carbon and carbon-free) enriched with variable concentrations of pyrethroids between 100 to 300 mgL⁻¹. Parameter optimization (pH, temperature, concentration and time) was done using a central composite design matrix of Response Surface Methodology (RSM). At concentrations below 200 mgL⁻¹, complete removal was observed; however, degradation of 95.6%/97.4 and 92.27%/95.65% (in carbon-free/added carbon) was observed for 250 and 300 mgL⁻¹ respectively. The consortium has been shown to degrade the pyrethroid mixture (300 mg L⁻¹) within 120 h. After 5 day incubation, the residual pyrethroids concentration in unsterilized soil were much lower than in sterilized soil, indicating that microbial degradation predominates in pyrethroids elimination with the half-life (t₁/₂) of 1.6 d and R² ranging from 0.992-0.999. Overall, these results showed that microbial consortia might be more efficient than single degrader strains. The findings will complement our current understanding of the bioremediation of mixture of Type II pyrethroids with microbial consortia and potentially heighten the importance for considering bioremediation as an effective alternative for the remediation of such pollutants.

Keywords: bioremediation, fungi, pyrethroids, soil

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Authors: Diafat Abdelouahab, Ekhalfi A Hammoudia, Meribai Abdelmalek A, Bahloul Ahmedb

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The present study aimed to characterize 30 honey samples from the Bordj Bou Arreridj region (Algeria) regarding their floral origins, physicochemical parameters, mineral composition and microbial safety. Mean values obtained for physicochemical parameters were: pH 4.11, 17.17% moisture, 0.0061% ash, 370.57μS cm−1 electrical conductivity, 21.98 meq/kg free acidity, and 9.703 mg/kg HMF. The mineral content was determined by atomic absorption spectrometry. The mean values obtained were (mg/kg): Fe, 7.5714; Mg, 37.68; Na, 186,63; Zn, 3,86; Pb, 0,4869 × 10-3 ; Cd, 267 × 10-3. Aerobic mesophiles, fecal coliforms and sulphite-reducing clostridia were the microbial contaminants of interest studied. Microbiologically, the honey quality was considered good and all samples showed to be negative in respect to safety parameters. The results obtained for physicochemical characteristics of Bordj Bou Arreridj honey indicate a good quality level, adequate processing, good maturity and freshness.

Keywords: pollen analysis, physicochemical analysis, mineral content, microbial contaminants

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Authors: Sana Mohammad Jafar

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Salmonella is one of the major causes of foodborne diseases throughout the world. Shrimp are an important commodity in world fishery trade. The microbiological quality of shrimp must be evaluated for assurance of shrimp. The aim of this study was to evaluate the microbiological quality and to determine the prevalence of Salmonella in shrimp sold in Khuzestan province. In this study, a total of 245 samples of shrimp sold in Khuzestan province were tested for Salmonella prevalence and total microbial population. The mean aerobic bacterial count in 50.2% of samples was 2200, in 29.8% of samples was 13,600, in 20% of samples was 36,700, and the mean aerobic bacterial count in the total samples was 20,000. (20,000 cfu/cc). Of the total samples, 33 samples were positive for Salmonella and the prevalence of Salmonella was determined 13.4%. These results indicate the possibility that shrimp contribute to foodborne infections. The improvement of shrimp quality is an important issue, and shrimp before consuming should be washed with water containing chlorine, with the aim of increasing safety. In addition, it should be avoided to eat shrimp as raw or not cooked properly.

Keywords: determination, total microbial, Salmonella, shrimp

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Authors: Sadia Ilyas, Hyunjung Kim, Rajiv R. Srivastava

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Current work has attempted to establish the linkages between circular bio-economy and recycling of copper and gold from urban mine by applying microbial activities instead of the smelter and chemical technologies. Thereafter, based on the potential of microbial approaches and research hypothesis, the structural model has been tested for a significance level of 99%, which is supported by the corresponding standardization co-efficient values. A prediction model applied to determine the recycling impact on circular bio-economy indicates to re-circulate 51,833 tons of copper and 58 tons of gold by 2030 for the production of virgin metals/raw-materials, while recycling rate of the accumulated e-waste remains to be 20%. This restoration volume of copper and gold through the microbial activities corresponds to mitigate 174 million kg CO₂ emissions and 24 million m³ water consumption if compared with the primary production activities. The study potentially opens a new window for environmentally-friendly biotechnological recycling of e-waste urban mine under the umbrella concept of circular bio-economy.

Keywords: urban mining, biobleaching, circular bio-economy, environmental impact

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Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: Kun Xu, Yuan Xu, Jia Qiao

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The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Jiandong Lv, Xingang Wang, Cuiling Shao

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The rapid development of social media platforms has made it one of the important news sources. While it provides people with convenient real-time communication channels, fake news and rumors are also spread rapidly through social media platforms, misleading the public and even causing bad social impact in view of the slow speed and poor consistency of artificial rumor detection. We propose an end-to-end rumor detection model-TIMF, which captures the dependencies between multimodal data based on the interactive attention mechanism, uses a transformer for cross-modal feature sequence mapping and combines hybrid fusion strategies to obtain decision results. This paper verifies two multi-modal rumor detection datasets and proves the superior performance and early detection performance of the proposed model.

Keywords: hybrid fusion, multimodal fusion, rumor detection, social media, transformer

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Authors: Tiisetso Mpai, Sanjay K. Jaiswal, Felix D. Dakora

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The South African Cape fynbos biome is a global biodiversity hotspot. This biome contains a diversity of endemic shrub legumes, including Polhillia, Wiborgia, and Wiborgiella species, which are important for ecotourism as well as for improving soil fertility status. This is due to their proven N₂-fixing abilities when in association with compatible soil bacteria. In fact, Polhillia, Wiborgia, and Wiborgiella species have been reported to derive over 61% of their needed nitrogen through biological nitrogen fixation and to exhibit acid and alkaline phosphatase activity in their rhizospheres. Thus, their interactions with soil microbes may explain their survival mechanisms under the continued summer droughts and acidic, nutrient-poor soils in this region. However, information regarding their rhizosphere microbiome is still unavailable, yet it is important for Fynbos biodiversity management. Therefore, the aim of this study was to assess the microbial community structures associated with rhizosphere soils of Polhillia pallens, Polhillia brevicalyx, Wiborgia obcordata, Wiborgia sericea, and Wiborgiella sessilifolia growing at different locations of the South African Cape fynbos, during the wet and dry seasons. The hypothesis is that the microbial communities in these legume rhizospheres are the same type and are not affected by the growing season due to the restricted habitat of these wild fynbos legumes. To obtain the results, DNA was extracted from 0.5 g of each rhizosphere soil using PowerSoil™ DNA Isolation Kit, and sequences were obtained using the 16S rDNA Miseq Illumina technology. The results showed that in both seasons, bacteria were the most abundant microbial taxa in the rhizosphere soils of all five legume species, with Actinobacteria showing the highest number of sequences (about 30%). However, over 19.91% of the inhabitants in all five legume rhizospheres were unclassified. In terms of genera, Mycobacterium and Conexibacter were common in rhizosphere soils of all legumes in both seasons except for W. obcordata soils sampled during the dry season, which had Dehalogenimonas as the major inhabitant (6.08%). In conclusion, plant species and season were found to be the main drivers of microbial community structure in Cape fynbos, with the wet season being more dominant in shaping microbial diversity relative to the dry season. Wiborgia obcordata had a greater influence on microbial community structure than the other four legume species.

Keywords: 16S rDNA, Cape fynbos, endemic legumes, microbiome, rhizosphere

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Authors: Mehak Munjal, Raj Kishore Sharma, Gurmeet Singh

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Microbial Fuel Cells (MFCs) are an alternative sustainable approach that utilize bacteria present in waste water as a bio-catalyst for the production of energy. It is a promising growing technology with minimal requirement for chemical supplements. Here electrode material plays a vital role in its performance. The present study represents CoFe2O4 spinel as a novel anode material in the MFC. It not only improve the bacterial metabolics but also enhance the power output. Generally, biocompatible conductive carbon paper/cloth, graphite and stainless steel are utilised as anode in MFCs. However, these materials lack electrochemical activity for anodic microbial reaction. Therefore, we developed CoFe2O4 on graphite sheet which enhanced the anodic charge transfer process. Redox pair in CoFe2O4 helped in improvement of extracellular electron transfer, thereby enhancing the performance. The physical characterizations (FT-IR, XRD, Raman) and electrochemical measurements demonstrate the strong interaction with E.coli bacteria and thus providing an excellent power density i.e. 1850 mW/m2 .The maximum anode half -cell potential is measured to be 0.65V. Therefore, use of noble metal free anodic material further decrease the cost and the long term cell stability makes it an effective material for practical applications.

Keywords: microbial fuel cell, cobalt ferrite, E. coli, bioelectricity

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Zerrin Erginkaya, Gözde Konuray

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In this study, antimicrobial effect of Greek clover was determined with usage of MIC (minimum inhibition concentration) and agar diffusion method. Moreover, pH, water activity and microbial change were determined during storage of fenugreek paste. At first part of our study, microbial load of spices was evaluated. Two different fenugreek pastes were produced with mixing of Greek clover, spices, garlic and water. Fenugreek pastes were stored at 4 °C. At the second part, antimicrobial effect of Greek clover was determined on Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Debaryomyces hansenii, Aspergillus parasiticus, Candida rugosa, Mucor spp., when the concentrations of Greek clover were 8%, 12% and 16%. According to the results obtained, mould growth was determined at 15^th and 30^th days of storage in first and second fenugreek samples, respectively. Greek clover showed only antifungal effect on Aspergillus parasiticus at previously mentioned concentrations.

Keywords: antimicrobial, fenugreek, Greek clover, minimum inhibition concentration

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Authors: Pujari Muruga, T. K. Radhakrishnan, N. Samsudeen

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Hydrogen is considered as the most important energy carrier and fuel of the future because of its high energy density and zero emission properties. Microbial Electrolysis Cell (MEC) is a new and promising approach for hydrogen production from organic matter, including wastewater and other renewable resources. By utilizing anode microorganism activity, MEC can produce hydrogen gas with smaller voltages (as low as 0.2 V) than those required for electrolytic hydrogen production ( ≥ 1.23 V). The hydrogen production processes of the MEC reactor are very nonlinear and highly complex because of the presence of microbial interactions and highly complex phenomena in the system. Increasing the hydrogen production rate and lowering the energy input are two important challenges of MEC technology. The mathematical model of the MEC is based on material balance with the integration of bioelectrochemical reactions. The main objective of the research is to produce biohydrogen by selecting the optimum current and controlling applied voltage to the MEC. Precise control is required for the MEC reactor, so that the amount of current required to produce hydrogen gas can be controlled according to the composition of the substrate in the reactor. Various simulation tests involving multiple set-point changes disturbance and noise rejection were performed to evaluate the performance using PID controller tuned with Ziegler Nichols settings. Simulation results shows that other good controller can provide better control effect on the MEC system, so that higher hydrogen production can be obtained.

Keywords: microbial electrolysis cell, hydrogen production, applied voltage, PID controller

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Authors: Lise Alonso, Audrey Dubost, Patricia Luis, Thomas Pommier, Yvan Moënne-Loccoz

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The Lascaux Cave in South-Est France is an archeological landmark renowned for its Paleolithic paintings dating back c.18.000 years. Extensive touristic frequenting and repeated chemical treatments have resulted in the development of microbial stains on cave walls, which is a major issue in terms of art conservation. Therefore, it is of prime importance to better understand the microbiology specific to the Lascaux Cave, in comparison to regional situations. To this end, we compared the microbial community (i.e. both prokaryotic and eukaryotic microbial populations) of Lascaux Cave with three other anthropized Périgord caves as well as three pristine caves from the same area. We used state-of-the-art metagenomic analyses of cave wall samples to obtain a global view of the composition of the microbial community colonizing cave walls. We measured the relative abundance and diversity of four DNA markers targeting different fractions of the ribosomal genes of bacteria (i.e. eubacteria), archaea (i.e. archeobacteria), fungi and other micro-eukaryotes. All groups were highly abundant and diverse in all Périgord caves, as several hundred genera of microorganisms were identified in each. However, Lascaux Cave displayed a specify microbial community, which differed from those of both pristine and anthropized caves. Comparison of stains versus non-stained samples from the Passage area of the Lascaux Cave indicated that a few taxa (e.g. the Sordiaromycetes amongst fungi) were more prevalent within than outside stains, yet the main difference was in the relative proportion of the different microbial taxonomic groups and genera, which supposedly supports the biological origin of the stains. Overall, metagenomic sequencing of cave wall samples was effective to evidence the large colonization of caves by a diversified range of microorganisms. It also showed that Lascaux Cave represented a very particular situation in comparison with neighboring caves, probably in relation to the extent of disturbance it had undergone. Our results provide key baseline information to guide conservation efforts in anthropized caves such as Lascaux and pave the way to modern monitoring of ornamented caves.

Keywords: cave conservation, Lascaux cave, microbes, paleolithic paintings

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Authors: Maher un Nisa, Ahsan Khawaja

Abstract:

Retinal imaging with Ultra-WideField (UWF) view technology has opened up new avenues in the field of retinal pathology detection. Recent developments in retinal imaging such as Optos California Imaging Device helps in acquiring high resolution images of the retina to help the Ophthalmologists in diagnosing and analyzing eye related pathologies more accurately. This paper investigates the acquired retinal details by comparing vessel detection in standard 450 color fundus images with the state of the art 2000 UWF retinal images.

Keywords: color fundus, retinal images, ultra-widefield, vessel detection

Procedia PDF Downloads 420

Authors: Bahareh Asefi, Fereidoun Farzaneh, Ghazaleh Asefi, Chang-Ping Yu

Abstract:

Increased production of food waste (FW) is a global issue that is receiving more attention due to its environmental and economic impacts. The generation of electricity from food waste, known as energy recovery, is one of the effective solutions in food waste management. Food waste has high energy content which seems ideal to achieve dual benefits in terms of energy recovery and waste stabilization. Microbial fuel cell (MFC) is a promising technology for treating food waste and generate electricity. In this work, we will review energy utilization from different kind of food waste using MFC and factors which affected the process. We have studied the key technology of energy generated from food waste using MFC to enhance the food waste management. The power density and electricity production by each kind of food waste and challenges were identified. This work explored the conversion of FW into energy from different type of food waste, which aim to provide a theoretical analysis for energy utilization of food waste.

Keywords: energy generation, food waste, microbial fuel cell, power density

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Authors: Sergei Aleinik, Yuri Matveev

Abstract:

In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

Procedia PDF Downloads 358

Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

Abstract:

Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

Procedia PDF Downloads 302