Search results for: community detection

Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

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

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Authors: Muhammad Hassan Khalil, Xu Jiadong

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Early detection through screening is the best tool short of a perfect treatment against the malignant tumor inside the breast of a woman. By detecting cancer in its early stages, it can be recognized and treated before it has the opportunity to spread and change into potentially dangerous. Microwave tomography is a new imaging method based on contrast in dielectric properties of materials. The mathematical theory of microwave tomography involves solving an inverse problem for Maxwell’s equations. In this paper, we present designed antenna for breast cancer detection, which will use in microwave tomography configuration.

Keywords: microwave imaging, inverse scattering, breast cancer, malignant tumor detection

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Authors: Lenka Mynaříková, Hedvika Boukalová

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The study looks at the ability to detect nonverbal deception among police officers and management students in the Czech Republic. Respondents from police departments (n=197) and university students of human resources (n=161) completed a deception detection task and evaluated veracity of the statements of suspects in 21 video clips from real crime investigations. Their evaluations were based on nonverbal behavior. Voices in the video clips were modified so that words were not recognizable, yet paraverbal voice characteristics were preserved. Results suggest that respondents have a tendency to lie bias based on their profession. In the evaluation of video clips, stereotypes also played a significant role. The statements of suspects of a different ethnicity, younger age or specific visual features were considered deceitful more often. Research might be beneficial for training in professions that are in need of deception detection techniques.

Keywords: deception detection, police officers, human resources, forensic psychology, forensic studies, organizational psychology

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Authors: Majid Farsadrooh, Najmeh Sabbaghi, Seyed Mohammad Mostashari, Abolhasan Moradi

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Phenolic compounds are chief environmental contaminants on account of their hazardous and toxic nature on human health. The preparation of sensitive and potent chemosensors to monitor emerging pollution in water and effluent samples has received great consideration. A novel and versatile nanocomposite sensor based on poly pyrogallol is presented for the first time in this study, and its electrochemical behavior for simultaneous detection of hydroquinone (HQ), catechol (CT), and resorcinol (RS) in the presence of nitrite is evaluated. The physicochemical characteristics of the fabricated nanocomposite were investigated by emission-scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDS), and Brunauer-Emmett-Teller (BET). The electrochemical response of the proposed sensor to the detection of HQ, CT, RS, and nitrite is studied using cyclic voltammetry (CV), chronoamperometry (CA), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). The kinetic characterization of the prepared sensor showed that both adsorption and diffusion processes can control reactions at the electrode. In the optimized conditions, the new chemosensor provides a wide linear range of 0.5-236.3, 0.8-236.3, 0.9-236.3, and 1.2-236.3 μM with a low limit of detection of 21.1, 51.4, 98.9, and 110.8 nM (S/N = 3) for HQ, CT and RS, and nitrite, respectively. Remarkably, the electrochemical sensor has outstanding selectivity, repeatability, and stability and is successfully employed for the detection of RS, CT, HQ, and nitrite in real water samples with the recovery of 96.2%–102.4%, 97.8%-102.6%, 98.0%–102.4% and 98.4%–103.2% for RS, CT, HQ, and nitrite, respectively. These outcomes illustrate that poly pyrogallol is a promising candidate for effective electrochemical detection of dihydroxybenzene isomers in the presence of nitrite.

Keywords: electrochemical sensor, poly pyrogallol, phenolic compounds, simultaneous determination

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Authors: Kunihisa Kakumoto

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This technical paper is for the prototype of solar energy utilization for finding sustainable conditions. This model has been simulated under the climate conditions in Japan. At the beginning of the study, the solar model house was built up on site. And the concerned data was collected in this model house for several years. On the basis of these collected data, the concept on the solar community was built up. For the finding sustainable conditions, the amount of the solar energy generation and its reduction of carbon dioxide and the reduction of carbon dioxide by the green planting and the amount of carbon dioxide according to the normal daily life in the solar community and the amount of the necessary water for the daily life in the solar community and the amount of the water supply by the rainfall on-site were calculated. These all values were taken into consideration. The relations between each calculated result are shown in the expression of inequality. This solar community and its consideration for finding sustainable conditions can be one prototype to do the feasibility study for our life in the future

Keywords: carbon dioxide, green planting, smart city, solar community, sustainable condition, water activity

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Authors: John Gaber

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Planners regularly use citizen input as empirical data to help them better understand community issues they know very little about. This type of community data is based on the lived experiences of local residents and is known as "emic" data. What is becoming more common practice for planners is their use of data from local experts and stakeholders (known as "etic" data or the outsider perspective) to help them fill in the gaps in their analysis of applied planning research projects. Utilizing international Health Impact Assessment (HIA) data, I look at who planners invite to their citizen input investigations. Research presented in this paper shows that planners access a wide range of emic and etic community perspectives in their search for the “community’s view.” The paper concludes with how planners can chart out a new empirical path in their execution of emic/etic citizen participation strategies in their applied planning research projects.

Keywords: citizen participation, emic data, etic data, Health Impact Assessment (HIA)

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Authors: Shilpa Khobragade, Carlos Da Silva Granja, Niklas Sandström, Igor Efimov, Victor P. Ostanin, Wouter van der Wijngaart, David Klenerman, Sourav K. Ghosh

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Rapid, label-free and direct detection of pathogenic bacteria is critical for the prevention of disease outbreaks. This paper for the first time attempts to probe the nonlinear acoustic response of quartz crystal resonator (QCR) functionalized with specific DNA aptamers for direct detection and quantification of viable E. coli KCTC 2571 bacteria. DNA aptamers were immobilized through biotin and streptavidin conjugation, onto the gold surface of QCR to capture the target bacteria and the detection was accomplished by shift in amplitude of the peak 3f signal (3 times the drive frequency) upon binding, when driven near fundamental resonance frequency. The developed nonlinear acoustic aptasensor system demonstrated better reliability than conventional resonance frequency shift and energy dissipation monitoring that were recorded simultaneously. This sensing system could directly detect 10⁽⁵⁾ cells/mL target bacteria within 30 min or less and had high specificity towards E. coli KCTC 2571 bacteria as compared to the same concentration of S.typhi bacteria. Aptasensor response was observed for the bacterial suspensions ranging from 10⁽⁵⁾-10⁽⁸⁾ cells/mL. Conclusively, this nonlinear acoustic aptasensor is simple to use, gives real-time output, cost-effective and has the potential for rapid, specific, label-free direction detection of bacteria.

Keywords: acoustic, aptasensor, detection, nonlinear

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Authors: A.I. Adeyemo

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Ikogosi warm spring results from a complex mechanical and chemical forces that generates internal heat in the rocks forming a warm and cold water at the same geographical location at the same time. From time immemorial, the local community had thought, it to be the work of a deity, and they were worshipping the spring. This complex phenomenon has been a source of tourist attraction to both local and international tourists over the years. 450 copies of a structured questionnaire were given out, and a total of 500 respondents were interviewed. The result showed that ikogosi warm spring impacts the community positively by providing employment to the teeming youths, and it provides income to traders. The result shows that 66% of the respondents confirmed that it increased their income and that transportation business increased more than 73%.the level of enlightenment and socialization increased greatly in the community. However, it also impacted the community negatively as it increased crime rates such as stealing, kidnapping, prostitution, and unwanted pregnancy among the secondary school girls and the other teenagers. Generally, 50% of the respondents reported that tourism in the warm spring results in insecurity in the community. IT also increased environmental problems such as noise and waste pollutions; the continuous movement on the land results in soil compartment leading to erosion, and leaching, which also results in loss of soil fertility. It was concluded that if the potentials of the spring are fully tapped, it will be a good avenue for income generation to the country.

Keywords: community, Ikogosi, revenue, warm spring

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Authors: N. Gayathri Devi, K. Batri

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The advent of technology has increased the traffic hazards and the road accidents take place. Collision detection system in automobile aims at reducing or mitigating the severity of an accident. This project aims at avoiding Vehicle head on collision by means of collision detection algorithm. This collision detection algorithm predicts the collision and the avoidance or minimization have to be done within few seconds on confirmation. Under critical situation collision minimization is made possible by turning the vehicle to the desired turn radius so that collision impact can be reduced. In order to avoid the collision completely, the turning of the vehicle should be achieved at reduced speed in order to maintain the stability.

Keywords: collision avoidance system, time to collision, time to turn, turn radius

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Authors: Anisha Mandal, Swambabu Varanasi

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Lead is one of the most prevalent toxic heavy metal ions, and its pollution poses a significant threat to the environment and human health. On the other hand, Ethylenediaminetetraacetic acid is a widely used metal chelating agent that, due to its poor biodegradability, is an incessant pollutant to the environment. For the first time, a green, simple, and cost-effective approach is used to hydrothermally synthesise photoluminescent carbon dots using Moringa Oleifera Gum in a single step. Then, using Moringa Oleifera Gum-derived carbon dots, a photoluminescent "ON-OFF-ON" mechanism for dual mode detection of trace Pb2+ and EDTA was proposed. MOG-CDs detect Pb2+ selectively and sensitively using a photoluminescence quenching mechanism, with a detection limit (LOD) of 0.000472 ppm. (1.24 nM). The quenched photoluminescence can be restored by adding EDTA to the MOG-CD+Pb2+ system; this strategy is used to quantify EDTA at a level of detection of 0.0026 ppm. (8.9 nM). The quantification of Pb2+ and EDTA in actual samples encapsulated the applicability and dependability of the proposed photoluminescent probe.

Keywords: carbon dots, photoluminescence, sensor, moringa oleifera gum

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Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

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Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

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Authors: Gaokai Liu

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The distribution of material grain sizes reflects the strength, fracture, corrosion and other properties, and the grain size can be acquired via the grain boundary. In recent years, the automatic grain boundary detection is widely required instead of complex experimental operations. In this paper, an effective solution is applied to acquire the grain boundary of material images. First, the initial superpixel segmentation result is obtained via a superpixel approach. Then, a region merging method is employed to merge adjacent regions based on certain similarity criterions, the experimental results show that the merging strategy improves the superpixel segmentation result on material datasets.

Keywords: grain boundary detection, image segmentation, material images, region merging

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Evans Belly, Imdad Rizvi, M. M. Kadam

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Satellite imagery is one of the emerging technologies which are extensively utilized in various applications such as detection/extraction of man-made structures, monitoring of sensitive areas, creating graphic maps etc. The main approach here is the automated detection of buildings from very high resolution (VHR) optical satellite images. Initially, the shadow, the building and the non-building regions (roads, vegetation etc.) are investigated wherein building extraction is mainly focused. Once all the landscape is collected a trimming process is done so as to eliminate the landscapes that may occur due to non-building objects. Finally the label method is used to extract the building regions. The label method may be altered for efficient building extraction. The images used for the analysis are the ones which are extracted from the sensors having resolution less than 1 meter (VHR). This method provides an efficient way to produce good results. The additional overhead of mid processing is eliminated without compromising the quality of the output to ease the processing steps required and time consumed.

Keywords: building detection, shadow detection, landscape generation, label, partitioning, very high resolution (VHR) satellite imagery

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Authors: Dina Alnefaie

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This poster presents a study of a Discord private server with thirteen multilingual gamers, aiming to explore the elements that construct a multilingual online gaming community. The study focuses on the communication practices of four Saudi female and male gamers, using various data collection methods, including online observations through recorded videos and screenshots, interviews, and informal conversations for one year. The primary findings show that translanguaging was a prominent feature of their verbal and textual communication practices. Besides, these practices that mostly accompany cultural ones were used to facilitate communication and express their identities in an intercultural context.

Keywords: online community construction, perceptions, multilingualism, digital identity

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Authors: Phusit Phukamchanoad

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The research studies the behaviors based on sufficiency economy philosophy at individual and community levels as well as the satisfaction of the urban community leaders by collecting data with purposive sampling technique. For in-depth interviews with 26 urban community leaders, the result shows that the urban community leaders have good knowledge and understanding about sufficiency economy philosophy. Especially in terms of money spending, they must consider the need for living and be economical. The activities in the community or society should not take advantage of the others as well as colleagues. At present, most of the urban community leaders live in a sufficient way. They often spend time with public service, but many families are dealing with debt. Many communities have some political conflict and high family allowances because of living in the urban communities with rapid social and economic changes. However, there are many communities that leaders have applied their wisdom in development for their people by gathering and grouping the professionals to form activities such as making chili sauce, textile organization, making artificial flowers worshipping the sanctity. The most prominent group is the foot massage business in Wat Pracha Rabue Tham. This professional group is supported continuously by the government. One of the factors in terms of satisfaction used for evaluating community leaders is the customary administration in brotherly, interdependent way rather than using the absolute power or controlling power, but using the roles of leader to perform the activities with their people intently, determinedly and having a public mind for people.

Keywords: performance and activities, sufficiency economy, urban communities leader, Dusit district

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Authors: Yea-Mei Leou, Shiu-Hsung Huang, T. C. Shen, Chin-Ya Fang

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The purposes of this study were to explore how to establish a professional learning community for English teachers at a junior high school, and to explore how teachers and students think about the guided reading program. The participants were three experienced English teachers and their ESL seventh-grade students from three classes in a junior high school. Leveled picture books and worksheets were used in the program. Questionnaires and interviews were used for gathering information. The findings were as follows: First, most students enjoyed this guided reading program. Second, the teachers thought the guided reading program was helpful to students’ learning and the discussions in the professional learning community refreshed their ideas, but the preparation for the teaching was time-consuming. Suggestions based on the findings were provided.

Keywords: ESL students, guided reading, leveled books, professional learning community

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Authors: Mohammad Sarchami, Mohsen Zeinalkhani

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Always, financial reporting system faces some problems to win public ear. The increase in the number of fraud and representation, often combined with the bankruptcy of large companies, has raised concerns about the quality of financial statements. So, investors, legislators, managers, and auditors have focused on significant fraud detection or prevention in financial statements. This article aims to investigate the Sugeno fuzzy classification to consider fraud detection in financial reporting of accepted firms by Tehran stock exchange. The hypothesis is: Sugeno fuzzy classification may detect fraud in financial reporting by financial ratio. Hypothesis was tested using Matlab software. Accuracy average was 81/80 in Sugeno fuzzy classification; so the hypothesis was confirmed.

Keywords: fraud, financial reporting, Sugeno fuzzy classification, firm

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Authors: Xincheng Jiang, Yanyan An, Yaoyao Huang, Wei Ding, Manli Sun, Hong Li, Huaili Zheng

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The residual antibiotics in the environment will pose a threat to the environment and human health. Thus, efficient removal and rapid detection of norfloxacin (NOR) in wastewater is very important. The main sources of NOR pollution are the agricultural, pharmaceutical industry and hospital wastewater. The total consumption of NOR in China can reach 5440 tons per year. It is found that neither animals nor humans can totally absorb and metabolize NOR, resulting in the excretion of NOR into the environment. Therefore, residual NOR has been detected in water bodies. The hazards of NOR in wastewater lie in three aspects: (1) the removal capacity of the wastewater treatment plant for NOR is limited (it is reported that the average removal efficiency of NOR in the wastewater treatment plant is only 68%); (2) NOR entering the environment will lead to the emergence of drug-resistant strains; (3) NOR is toxic to many aquatic species. At present, the removal and detection technologies of NOR are applied separately, which leads to a cumbersome operation process. The development of simultaneous adsorption-flocculation removal and FTIR detection of pollutants has three advantages: (1) Adsorption-flocculation technology promotes the detection technology (the enrichment effect on the material surface improves the detection ability); (2) The integration of adsorption-flocculation technology and detection technology reduces the material cost and makes the operation easier; (3) FTIR detection technology endows the water treatment agent with the ability of molecular recognition and semi-quantitative detection for pollutants. Thus, it is of great significance to develop a smart water treatment material with high removal capacity and detection ability for pollutants. This study explored the feasibility of combining NOR removal method with the semi-quantitative detection method. A magnetic Cu-Ni-S/Ni foam was synthesized by in-situ loading Cu-Ni-S nanostructures on the surface of Ni foam. The novelty of this material is the combination of adsorption-flocculation technology and semi-quantitative detection technology. Batch experiments showed that Cu-Ni-S/Ni foam has a high removal rate of NOR (96.92%), wide pH adaptability (pH=4.0-10.0) and strong ion interference resistance (0.1-100 mmol/L). According to the Langmuir fitting model, the removal capacity can reach 417.4 mg/g at 25 °C, which is much higher than that of other water treatment agents reported in most studies. Characterization analysis indicated that the main removal mechanisms are surface complexation, cation bridging, electrostatic attraction, precipitation and flocculation. Transmission FTIR detection experiments showed that NOR on Cu-Ni-S/Ni foam has easily recognizable FTIR fingerprints; the intensity of characteristic peaks roughly reflects the concentration information to some extent. This semi-quantitative detection method has a wide linear range (5-100 mg/L) and a low limit of detection (4.6 mg/L). These results show that Cu-Ni-S/Ni foam has excellent removal performance and semi-quantitative detection ability of NOR molecules. This paper provides a new idea for designing and preparing multi-functional water treatment materials to achieve simultaneous removal and semi-quantitative detection of organic pollutants in water.

Keywords: adsorption-flocculation, antibiotics detection, Cu-Ni-S/Ni foam, norfloxacin

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Authors: Ergün Şakalar, Şeyma Özçirak Ergün

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Pistachio nuts, the fruits of the pistachio tree (Pistacia vera), are edible tree nuts highly valued for their organoleptic properties. Pistachio nuts used in snack foods, chocolates, baklava, meat products, ice-cream industries and other gourmet products as ingredients. Undeclared pistachios may be present in food products as a consequence of fraudulent substitution. Control of food samples is very important for safety and fraud. Mix of pistachio, peanut (Arachis hypogaea), pea (Pisum sativum L.) used instead of pistachio in food products, because pistachio is a considerably expensive nut. To solve this problem, a sensitive polymerase chain reaction PCR has been developed. A real-time PCR assay for the detection of pea, peanut and pistachio in baklava was designed by using EvaGreen fluorescence dye. Primers were selected from powerful regions for identification of pea, peanut and pistachio. DNA from reference samples and industrial products were successfully extracted with the GIDAGEN® Multi-Fast DNA Isolation Kit. Genomes were identified based on their specific melting peaks (Mp) which are 77°C, 85.5°C and 82.5°C for pea, peanut and pistachio, respectively. Homogenized mixtures of raw pistachio, pea and peanut were prepared with the ratio of 0.01%, 0.1%, 1%, 10%, 40% and 70% of pistachio. Quantitative detection limit of assay was 0.1% for pistachio. Also, real-time PCR technique used in this study allowed the qualitative detection of as little as 0.001% level of peanut DNA, 0,000001% level of pistachio DNA and 0.000001% level of pea DNA in the experimental admixtures. This assay represents a potentially valuable diagnostic method for detection of nut species adulterated with pistachio as well as for highly specific and relatively rapid detection of small amounts of pistachio in food samples.

Keywords: pea, peanut, pistachio, real-time PCR

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Authors: Cheryl Teelucksingh

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Toronto is in the midst of an urban development and infrastructure boom. Population growth and concerns about urban sprawl and carbon emissions have led to pressure on the municipal and the provincial governments to re-think urban development. Toronto’s approach to climate change mitigation and adaptation has positioning of the emerging green economy as part of the solution. However, the emerging green economy many not benefit all Torontonians in terms of jobs, improved infrastructure, and enhanced quality of life. Community benefits agreements (CBAs) are comprehensive, negotiated commitments, in which founders and builders of major infrastructure projects formally agree to work with community interest groups based in the community where the development is taking place, toward mutually beneficial environmental and labor market outcomes. When community groups are equitably represented in the process, they stand not only to benefit from the jobs created from the project itself, but also from the longer-term community benefits related to the quality of the completed work, including advocating for communities’ environmental needs. It is believed that green employment initiatives in Toronto should give greater consideration to best practices learned from community benefits agreements. Drawing on the findings of a funded qualitative study in Toronto (Canada), “The Green Gap: Toward Inclusivity in Toronto’s Green Economy” (2013-2016), this paper examines the emergent CBA in Toronto in relation to the development of a light rail transit project. Theoretical and empirical consideration will be given to the research gaps around CBAs, the role of various stakeholders, and discuss the potential for CBAs to gain traction in the Toronto’s urban development context. The narratives of various stakeholders across Toronto’s green economy will be interwoven with a discussion of the CBA model in Toronto and other jurisdictions.

Keywords: green economy in Toronto, equity, community benefits agreements, environmental justice, community sustainability

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Authors: Guilherme Reis Ranieri, Guilherme Leite Gaudereto, Michele Toledo, Luis Fernando Amato-Lourenco, Thais Mauad

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Given the importance to urban sustainability and the growing relevance of the term ‘community garden’, this paper aims to conduct a bibliometric analysis of the term. Using SCOPUS as database, we analyzed 105 articles that contained the keywords ‘community garden’, and conducted a cluster analysis with the associated keywords. As results, we found 205 articles and 404 different keywords. Among the keywords, 334 are not repeated anytime, 44 are repeated 2 times and 9 appear 3 times. The most frequent keywords are: community food systems (74), urban activism (14), Communities of practice (6), food production (6) and public rethoric (5). Within the areas, which contains more articles are: social sciences (74), environmental science (29) and agricultural and biological sciences (24).The three main countries that concentrated the papers are United States (54), Canada (15) and Australia (12). The main journal with these keywords is Local Environment (10). The first publication was in 1999, and by 2010 concentrated 30,5% of the publications. The other 69,5% occurred 2010 to 2015, indicating an increase in frequency. We can conclude that the papers, based on the distribution of the keywords, are still scattered in various research topics and presents high variability between subjects.

Keywords: bibliometrics, community garden, metrics, urban agriculture

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Authors: Oman Sukmana

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Geographically, Indonesia appears to be disaster-prone areas, whether for natural, nonnatural (man-made), or social disasters. This study aimed to construct the knowledge and social wisdom on the local community in the process of disaster management after the eruption of Mt. Kelud. This study, moreover, encompassed two major concerns: (1) the construction of knowledge and social wisdom on the local community in the process of disaster management after the eruption of Mt. Kelud; (2) the conceptual framework of disaster management on the basis of knowledge and social wisdom on the local community. The study was conducted by means of qualitative approach. The data were analyzed by using the qualitative-descriptive technique. The data collection techniques used in this study were in-depth interview, focus group discussion, observation, and documentation. It was conducted at Pandansari Village, Sub-district Ngantang, District Malang as the most at risk area of Mt. Kelud’s eruption. The purposive sampling was applied ad hoc to select the respondents including: the apparatus of Pandansari Village, the local figures of Pandansari Village, the Chief and Boards of the Forum of Disaster Risk Reduction (FPRB), the Head of Malang Regional Disaster Management Agency, and other agencies. The findings of this study showed that the local community has already possessed the adequate knowledge and social wisdom to overcome the disaster. Through the social wisdom, the local community could predict the potential eruption.

Keywords: knowledge, social and local wisdom, disaster management

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Authors: M. Y. Achouri, O. A. Alleg, M. C. L. Moulai, M. A. Selka

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This study aims to assess the perception and attitudes of community pharmacists in Sidi-Bel-Abbes (Algeria) towards generic drugs. This is a descriptive cross-sectional prospective survey and quantitative, conducted over a period of two months from April to May 2014. The target population consisted of 118 pharmacists practicing in pharmacies in Sidi-Bel-Abbes. Data collection was conducted through a questionnaire consisting of thirteen (13) items. Fifty six (67%) of community pharmacists in the town of Sidi-Bel-Abbes in the survey believe that generics have a lower quality compared to brand name medicines Only 42% of respondents viewed locally manufactured generic medicines as equal in quality compared to the imported generic medicines, and 63% believe that the generics substitution has led to change the relationship between a pharmacist and patient. In order to promote the practice of generic medicines in Algeria, an educational program should be implemented.

Keywords: generic drugs, perception, attitudes, community pharmacists

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Authors: Minh-Phuong Ngoc Bui, Abdennour Abbas

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Microbial spoilage of food/drug has been a constant nuisance and an unavoidable problem throughout history that affects food/drug quality and safety in a variety of ways. A simple and rapid test of fungi and bacteria in food/drugs and environmental clinical samples is essential for proper management of contamination. A number of different techniques have been developed for detection and enumeration of foodborne microorganism including plate counting, enzyme-linked immunosorbent assay (ELISA), polymer chain reaction (PCR), nucleic acid sensor, electrical and microscopy methods. However, the significant drawbacks of these techniques are highly demand of operation skills and the time and cost involved. In this report, we introduce a rapid method for detection of bacteria and fungi in food/drug products using a specific interaction between a reducing agent (tris(2-carboxylethyl)phosphine (TCEP)) and the microbial surface proteins. The chemical reaction was transferred to a transduction system using gold nanoplates-enhanced chemiluminescence. We have optimized our nanoplates synthetic conditions, characterized the chemiluminescence parameters and optimized conditions for the microbial assay. The new detection method was applied for rapid detection of bacteria (E.coli sp. and Lactobacillus sp.) and fungi (Mucor sp.), with limit of detection as low as single digit cells per mL within 10 min using a portable luminometer. We expect our simple and rapid detection method to be a powerful alternative to the conventional plate counting and immunoassay methods for rapid screening of microorganisms in food/drug products.

Keywords: microorganism testing, gold nanoplates, chemiluminescence, reducing agents, luminol

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Authors: Wei-Chieh Yeh, Yung-Tang Shen

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The concept of community building started in 1994 in Taiwan. After years of development, it fostered the notion of active local resident participation in community issues as co-operators, instead of minions. Participatory design gives participants more control in the decision-making process, helps to reduce the friction caused by arguments and assists in bringing different parties to consensus. This results in an increase in the efficiency of projects run in the community. Therefore, the participation of local residents is key to the success of community building. This study applied participatory design to develop plans for the reuse of deserted spaces in the community from the first stage of brainstorming for design ideas, making creative models to be employed later, through to the final stage of construction. After conducting a series of participatory designed activities, it aimed to integrate the different opinions of residents, develop a sense of belonging and reach a consensus. Besides this, it also aimed at building the residents’ awareness of their responsibilities for the environment and related issues of sustainable development. By reviewing relevant literature and understanding the history of related studies, the study formulated a theory. It took the “2012-2014 Changhua County Community Planner Counseling Program” as a case study to investigate the implementation process of participatory design. Research data are collected by document analysis, participants’ observation and in-depth interviews. After examining the three elements of “Design Participation”, “Construction Participation”, and” Follow–up Maintenance Participation” in the case, the study emerged with a promising conclusion: Maintenance works were carried out better compared to common public works. Besides this, maintenance costs were lower. Moreover, the works that residents were involved in were more creative. Most importantly, the community characteristics could be easy be recognized.

Keywords: participatory design, deserted space, community building, reuse

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Authors: Xiang Yu, Chuntao Feng, Lu Yang, Meiyang Song, Wenhao Zhou

Abstract:

The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.

Keywords: FMCW radar, fall detection, 3D CNN, time-varying range-doppler features

Procedia PDF Downloads 94

Authors: Weitao Lin

Abstract:

To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.

Keywords: natural language processing, Chinese event detection, rules matching, dependency parsing

Procedia PDF Downloads 111

Authors: Xiaoyan Dai, Hsieh Yisan

Abstract:

Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

Procedia PDF Downloads 134