Search results for: network screening

Authors: Zachary Muthii Rukenya, James Mbaria, Peter Mbaabu, Kiama Stephen Gitahi, Ronald Onzago

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Aloe turkanensis is one of the widely used medicinal shrub and in Kenya the plant is mainly found in Baringo, Isiolo, Laikipia, Turkana and West Pokot Counties where it is used in ethno-medicine and ethno-veterinary medicine. The Turkana community uses the plant products to manage malaria, wounds, stomach ache, constipation, pain, skin infection, poultry diseases and retained afterbirth in cows. This evaluated the efficacy and safety of the plant obtained from Turkana County, Kenya. Preliminary data on the use of the plant in the county was collected through observation, photographing and interviews. A sample of the whole plant was harvested in Natira sublocation, in ex-Turkana west district in February 2012 after identification by Aloe-working group herbalists who voluntarily provided information on its medicinal uses. Botanical identification was done at Kenya Forest Research Centre in Karura where voucher specimen was deposited. Cold maceration using 70% methanol and distilled water was used for extraction. Bioassays were to determine the effects of the plant extracts on brine shrimp and selected bacterial and fungal cultures. The extracts were tested in-vitro activity against standard cultures of B. cereus (ATCC 11778), S. aureus (ATCC25923), P. aeroginosa (ATCC 27853), E. coli (ATCC 25922) and a human infections clinical isolate of C. albicans. The extracts of Aloe turkanensis inhibited the growth B. cereus (100-200 mg/ml), S. aureus (50-100 mg/ml), P. aeroginosa (200mg/ml), E. coli (400mg/ml) while C. albicans was not affected. The extracts also inhibited the growth of S. aureus and B. cereus with mean diameters of inhibition zones being 19.75±1 mm and 18.5±05 mm reapectively. Phytochemical screening showed the presence of alkaloids, tarpenoids, steroids, quinones, saponins and tannins in the plant extracts. The extract was found to be non-toxic at a concentration of 1000µg/ml with a 100% survival of Brine Shrimp larva. It was concluded that Aloe turkanensis growing the study area has metabolites that inhibit the growth of microorganisms and is however, there is need for further studies to validate the in-vivo bioactivity of the plant and more generate adequate toxicological data.to support conservation, value chain addition of its products and widespread use as a herbal remedy.

Keywords: Aloe turkanensis, bioactivity, cultivated, human infections

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Authors: S. M. Gupta, Vanita Aggarwal, Som Nath Sachdeva

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The work reported through this paper is an experimental work conducted on High Performance Concrete (HPC) with super plasticizer with the aim to develop some models suitable for prediction of compressive strength of HPC mixes. In this study, the effect of varying proportions of fly ash (0% to 50% at 10% increment) on compressive strength of high performance concrete has been evaluated. The mix designs studied were M30, M40 and M50 to compare the effect of fly ash addition on the properties of these concrete mixes. In all eighteen concrete mixes have been designed, three as conventional concretes for three grades under discussion and fifteen as HPC with fly ash with varying percentages of fly ash. The concrete mix designing has been done in accordance with Indian standard recommended guidelines i.e. IS: 10262. All the concrete mixes have been studied in terms of compressive strength at 7 days, 28 days, 90 days and 365 days. All the materials used have been kept same throughout the study to get a perfect comparison of values of results. The models for compressive strength prediction have been developed using Linear Regression method (LR), Artificial Neural Network (ANN) and Leave One Out Validation (LOOV) methods.

Keywords: high performance concrete, fly ash, concrete mixes, compressive strength, strength prediction models, linear regression, ANN

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Authors: Nattawipa Pakasri

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58S (60SiO2-36CaO-4P2O5), three-dimensionally ordered macroporous bioactive glasses (3DOM-BGs) were synthesized by the sol-gel method using dual templating methods. non-ionic surfactant Brij56 used as templates component produced mesoporous and the spherical PMMA colloidal crystals as one template component yielded either three-dimensionally ordered microporous products or shaped bioactive glass nanoparticles. The bioactive glass with aging step for 12 h at room temperature, no structure transformation occurred and the 3DOM structure was produced (Figure a) due to no shrinkage process between the aging step. After 48 h time of o 3DOM structure remained and, nanocube with ∼120 nm edge lengths and nanosphere particle with ∼50 nm was obtained (Figure c, d). PMMA packing templates have octahedral and tetrahedral holes to make 2 final shapes of 3DOM-BGs which is rounded and cubic, respectively. The ageing time change from 12h, 24h and 48h affected to the thickness of interconnecting macropores network. The wall thickness was gradually decrease after increase aging time.

Keywords: three-dimensionally ordered macroporous bioactive glasses, sol-gel method, PMMA, bioactive glass

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Authors: Smithinun Thairoongrojana

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This research is a qualitative research with three main purposes: (1) to develop the local tax map software system to be linked to the main Local Tax Map System (LTAX3000) system; (2) to design and develop a program for tax data fieldwork on wireless devices and link it to LTAX3000 database of Surat Thani Municipality; (3) to develop the human resource responsible for the fieldwork to be able to use the program and maintain the system and also to be able to work with the dynamic of technologies. In-depth interviews with the two groups of samples, the board of Surat Thani Municipality and operation staff responsible for observing and taxing fieldworks were conducted. The result of this study demonstrates the new developed fieldworks system that can be used both stand-alone usage and networking usage. The fieldworks system to collect and store the variety of taxing information within Surat Thani Municipality will be explained. Then the fieldwork operation process development and the replacement of transferring and storing the information via the network communication.

Keywords: Local tax map, software system development, wireless devices, human resource

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Authors: Şule Turhan, Özlem Turan

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Permanence in the international markets for many global companies is about being known as having effective logistics which targets customer satisfaction management and lower costs. Under competitive conditions, the necessity of providing the products to customers quickly and on time for the companies which constantly aim to improve their profitability increased the strategic importance of the logistics concept. Food logistic is one of the most difficult areas in logistics. In the process from manufacturer to final consumer, quality and hygiene standards must be provided constantly. In food logistics, reliable and extensive service network has great importance and on time delivery is the target. Developing logistics industry provide the supply of foods in the country and the development of export markets more quickly and has an important role in providing added value to the country's economy. Turkey that creates a bridge between the east and the west is an attractive market for logistics companies. In this study, by examining both the place and the importance of logistics in Turkish food sector, recommendations will be made for the food industry.

Keywords: logistics, Turkish food industry, competition, food industry

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Authors: Mouhoubi Nedjima, Sassi Boudemagh Souad

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In the framework of the modernization of the city of Constantine, and in order to restore its status as a regional metropolis and introduce it into the network of cities international metropolises, a major urban project was launched: project of modernization and of metropolitanization of the city of Constantine (PMMC). Our research project focuses on the management of the project for the modernization of the city of Constantine (PMMC) focusing on the management of some aspects of the urban project whose participation, with the objective assessment of the managerial approach business. Among the cases revealing taken into account in our research work on the question of participation of actors and their organizations, the operation relating to "the urban improvement in the city of the Brothers FERRAD in the district of Zouaghi". This operation with the objective of improving the living conditions of citizens has faced several challenges and obstacles that have been in major part the factors of its failure. Through this study, we examine the management process and the mode of organization of the actors of the project as well as the level of participation of the citizen to finally propose managerial solutions to conflict situations observed.

Keywords: the urban project, the urban improvement, participation, Constantine

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Authors: S. Cheng, C. Catallo

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Introduction: Canada's healthcare and social services systems are failing high risk, vulnerable older adults. Care for vulnerable older Canadians (65 and older) is not optimal in Canada. It does not address the care needs of vulnerable, high risk adults using a holistic approach. Given the growing aging population, and the care needs for seniors with complex conditions is one of the highest in Canada's health care system, there is a sense of urgency to optimize care. Integration of health and social services is an emerging trend in Canada when compared to European countries. There is no common and universal understanding of healthcare and social services integration within the country. Consequently, a clear understanding and definition of integrated health and social services are absent in Canada. Objectives: A study was undertaken to develop a case definition for integrated health and social care initiatives that serve older adults, which was then tested against three Canadian integrated initiatives. Methodology: A limited literature review was undertaken to identify common characteristics of integrated health and social care initiatives that serve older adults, and comprised both scientific and grey literature, in order to develop a case definition. Three Canadian integrated initiatives that are located in the province of Ontario, were identified using an online search and a screening process. They were surveyed to determine if the literature-based integration definition applied to them. Results: The literature showed that there were 24 common healthcare and social services integration characteristics that could be categorized into ten themes: 1) patient-care approach; 2) program goals; 3) measurement; 4) service and care quality; 5) accountability and responsibility; 6) information sharing; 7) Decision-making and problem-solving; 8) culture; 9) leadership; and 10) staff and professional interaction. The three initiatives showed agreement on all the integration characteristics except for those characteristics associated with healthcare and social care professional interaction, collaborative leadership and shared culture. This disagreement may be due to several reasons, including the existing governance divide between the healthcare and social services sectors within the province of Ontario that has created a ripple effect in how professions in the two different sectors interact. In addition, the three initiatives may be at maturing levels of integration, which may explain disagreement on the characteristics associated with leadership and culture. Conclusions: The development of a case definition for healthcare and social services integration that incorporates common integration characteristics can act as a useful instrument in identifying integrated healthcare and social services, particularly given the emerging and evolutionary state of this phenomenon within Canada.

Keywords: Canada, case definition, healthcare and social services integration, integration, seniors health, services delivery

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Authors: Siriporn Poolsuwan, Kanyarat Bussaban

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This research aims to investigate and analyze user’s behaviour towards the utilization of the online news clipping database at Suan Sunandha Rajabhat University, Thailand. Data is gathered from 214 lecturers and 380 undergraduate students by using questionnaires. Findings show that most users knew the online news clipping service from their friends, library’s website and their teachers. The users learned how to use it by themselves and others learned by training of SSRU library. Most users used the online news clipping database one time per month at home and always used the service for general knowledge, up-to-date academic knowledge and assignment reference. Moreover, the results of using the online news clipping service problems include the users themselves, service management, service device- computer and tools – and the network, service provider, and publicity. This research would be benefit for librarians and teachers for planning and designing library services in their works and organization.

Keywords: online database, user behavior, news clipping, library services

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Authors: Chutikarn Sriwiboon, Suwaree Yordchim

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Benjarong handicraft product is one of the most important handicraft products from Thailand. It involves the management of traditional wisdom of arts and Thai culture. This paper drew upon data collection from local communities by using an in-depth interview technique which was conducted in Thailand during summer of 2014. The survey was structured primarily to obtain local wisdom and concerns toward their career development. This research paper was a qualitative research conducted by focus groups with a total of 51 cooperative women and occupational groups around Thailand which produced the Benjarong products. The data were significantly collected from many sources and many communities, which totaled 24,430 handicraft products, in which the 668 different patterns of Benjarong products were produced by 51 local community network groups in Thailand. The findings revealed that after applying the Philosophy of Sufficiency Economy, there was a significantly positive change in their career development and the process of knowledge management enables local community to enhance their personal development and career.

Keywords: Benjarong, career development, community, handicraft

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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Authors: Mohsen Maadani, Seyed Ahmad Motamedi

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The use of wireless technology in industrial networks has gained vast attraction in recent years. In this paper, we have thoroughly analyzed the effect of contention window (CW) size on the performance of IEEE 802.11-based industrial wireless networks (IWN), from delay and reliability perspective. Results show that the default values of CWmin, CWmax, and retry limit (RL) are far from the optimum performance due to the industrial application characteristics, including short packet and noisy environment. An adaptive CW algorithm (payload-dependent) has been proposed to minimize the average delay. Finally a simple, but effective CW and RL setting has been proposed for industrial applications which outperforms the minimum-average-delay solution from maximum delay and jitter perspective, at the cost of a little higher average delay. Simulation results show an improvement of up to 20%, 25%, and 30% in average delay, maximum delay and jitter respectively.

Keywords: average delay, contention window, distributed coordination function (DCF), jitter, industrial wireless network (IWN), maximum delay, reliability, retry limit

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Authors: Provides Ng

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Platform economy is a peer-to-peer model of distributing resources facilitated by community-based digital platforms. In recent years, digital platforms are rapidly reconfiguring the public realm using hyper-personalisation techniques. This paper aims at investigating how urban planning can leapfrog into the digital age to help relieve the rising tension of the global issue of labour flow; it discusses the means to transfer techniques of hyper-personalisation into urban planning for plasticity using platform technologies. This research first denotes the limitations of the current system of urban residency, where the system maintains itself on the circulation of documents, which are data on paper. Then, this paper tabulates how some of the institutions around the world, both public and private, digitise data, and streamline communications between a network of systems and citizens using platform technologies. Subsequently, this paper proposes ways in which hyper-personalisation can be utilised to form a digital planning platform. Finally, this paper concludes by reviewing how the proposed strategy may help to open up new ways of thinking about how we affiliate ourselves with cities.

Keywords: platform urbanism, hyper-personalisation, digital inventory, urban accessibility

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Authors: Tomas Menard

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The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters.

Keywords: dynamical system, control law design, sampled output, observer design

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Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

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Authors: Z. Gharaee

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Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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Authors: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

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In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

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Authors: Brian Ceh, Alison Jackson-Holland

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Food deserts are a reality in some cities. These deserts can be described as a shortage of healthy food options within close proximity of consumers. The shortage in this case is typically facilitated by a lack of stores in an urban area that provide adequate fruit and vegetable choices. This study explores new avenues to better understand food deserts by examining modes of transportation that are available to shoppers or consumers, e.g. walking, automobile, or public transit. Further, this study is unique in that it not only explores the location of large grocery stores, but small grocery and convenience stores too. In this study, the relationship between some socio-economic indicators, such as personal income, are also explored to determine any possible association with food deserts. In addition, to help facilitate our understanding of food deserts, complex network spatial models that are built on adequate algorithms are used to investigate the possibility of food deserts in the city of Hamilton, Canada. It is found that Hamilton, Canada is adequate serviced by retailers who provide healthy food choices and that the food desert phenomena is almost absent.

Keywords: Canada, desert, food, Hamilton, store

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Authors: Andrea N. Ofori-Boadu

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The purpose is to develop a conceptual model of subcontractor development practices and processes that strengthen the integration of subcontractors into construction supply chain systems for improved subcontractor performance on Leadership in Energy and Environmental Design (LEED) certified building projects. The construction management of a LEED project has an important objective of meeting sustainability certification requirements. This is in addition to the typical project management objectives of cost, time, quality, and safety for traditional projects; and, therefore increases the complexity of LEED projects. Considering that construction management organizations rely heavily on subcontractors, poor performance on complex projects such as LEED projects has been largely attributed to the unsatisfactory preparation of subcontractors. Furthermore, the extensive use of unique and non-repetitive short term contracts limits the full integration of subcontractors into construction supply chains and hinders long-term cooperation and benefits that could enhance performance on construction projects. Improved subcontractor development practices are needed to better prepare and manage subcontractors, so that complex objectives can be met or exceeded. While supplier development and supply chain theories and practices for the manufacturing sector have been extensively investigated to address similar challenges, investigations in the construction sector are not that obvious. Consequently, the objective of this research is to investigate effective subcontractor development practices and processes to guide construction management organizations in their development of a strong network of high performing subcontractors. Drawing from foundational supply chain and supplier development theories in the manufacturing sector, a mixed interpretivist and empirical methodology is utilized to assess the body of knowledge within literature for conceptual model development. A self-reporting survey with five-point Likert scale items and open-ended questions is administered to 30 construction professionals to estimate their perceptions of the effectiveness of 37 practices, classified into five subcontractor development categories. Data analysis includes descriptive statistics, weighted means, and t-tests that guide the effectiveness ranking of practices and categories. The results inform the proposed three-phased LEED subcontractor development program model which focuses on preparation, development and implementation, and monitoring. Highly ranked LEED subcontractor pre-qualification, commitment, incentives, evaluation, and feedback practices are perceived as more effective, when compared to practices requiring more direct involvement and linkages between subcontractors and construction management organizations. This is attributed to unfamiliarity, conflicting interests, lack of trust, and resource sharing challenges. With strategic modifications, the recommended practices can be extended to other non-LEED complex projects. Additional research is needed to guide the development of subcontractor development programs that strengthen direct involvement between construction management organizations and their network of high performing subcontractors. Insights from this present research strengthen theoretical foundations to support future research towards more integrated construction supply chains. In the long-term, this would lead to increased performance, profits and client satisfaction.

Keywords: construction management, general contractor, supply chain, sustainable construction

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Authors: Muhammad Bilal, Amelia Jane Llyod, Habsah Mohamad, Jia Hui Wong, Abdul Aziz Mohamed Yusoff, Jafri Malin Abdullah, Jingli Zhang

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Epilepsy is one of the major brain afflictions occurs with uncontrolled excitation of cortex; disturbed 50 million of world’s population. About 25 percent of patients subjected to adverse effects from antiepileptic drugs (AEDs) such as depression, nausea, tremors, gastrointestinal symptoms, osteoporosis, dizziness, weight change, drowsiness, fatigue are commonly observed indications; therefore, new drugs are required to cure epilepsy. GABA is principle inhibitory neurotransmitter, control excitation of the brain. Mutation or dysfunction of GABA receptor is one of the primary causes of epilepsy, which is confirmed from many acquired models of epilepsy like traumatic brain injury, kindling, and status epilepticus models of epilepsy. GABA receptor has 3 distinct types such as GABA (A), GABA (B), GABA(C).GABA (A) receptor has 20 different subunits, α1β2γ2 subunits composition of GABA (A) receptor is the most used combination of subunits for screening of compounds against epilepsy. We expressed α1β2γ2s subunits of GABA (A) Receptor in Xenopus leavis oocytes and examined the enhancement potential of 4-Hydroxybenzoic acid compound on GABA (A) receptor via two-electrode voltage clamp current recording technique. Bamboo shoots are the young, tender offspring of bamboo, which are usually harvested after a cultivating period of 2 weeks. Proteins, acids, fat, starch, carbohydrate, fatty acid, vitamin, dietary fiber, and minerals are the major constituent found systematically in bamboo shoots. These shoots reported to have anticancer, antiviral, antibacterial activity, also possess antioxidant properties due to the presence of phenolic compounds. Student t-test analysis suggested that 4- hydroxybenzoic acid positively allosteric GABA (A) receptor, increased normalized current amplitude to 1.0304±0.0464(p value 0.032) compared with vehicle. 4-Hydrobenzoic acid, a compound from Dendrocalamus Asper bamboo shoot gives new insights for future studies on bamboo shoots with motivation for extraction of more compounds to investigate their effects on human and rodents against epilepsy, insomnia, and anxiety.

Keywords: α1β2γ2S, antiepileptic, bamboo shoots, epilepsy GABA (A) receptor, two-microelectrode voltage clamp, xenopus laevis oocytes

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Authors: Mariam Dianat Sabet Gilani, Lars M. Blank, Birgitta E. Ebert

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Plant-derived lupane-type, pentacyclic triterpenoids are biologically active compounds that are highly interesting for applications in medical, pharmaceutical, and cosmetic industries. Due to the low abundance of these valuable compounds in their natural sources, and the environmentally harmful downstream process, alternative production methods, such as microbial cell factories, are investigated. Engineered Saccharomyces cerevisiae strains, harboring the heterologous genes for betulinic acid synthesis, can produce up to 2 g L-1 triterpenoids, showing high potential for large-scale production of triterpenoids. One limitation of the microbial synthesis is the intracellular product accumulation. It not only makes cell disruption a necessary step in the downstream processing but also limits productivity and product yield per cell. To overcome these restrictions, the aim of this study is to develop an in-situ extraction method, which extracts triterpenoids into a second organic phase. Such a continuous or sequential product removal from the biomass keeps the cells in an active state and enables extended production time or biomass recycling. After screening of twelve different solvents, selected based on product solubility, biocompatibility, as well as environmental and health impact, isopropyl myristate (IPM) was chosen as a suitable solvent for in-situ product removal from S. cerevisiae. Impedance-based single-cell analysis and off-gas measurement of carbon dioxide emission showed that cell viability and physiology were not affected by the presence of IPM. Initial experiments demonstrated that after the addition of 20 vol % IPM to cultures in the stationary phase, 40 % of the total produced triterpenoids were extracted from the cells into the organic phase. In future experiments, the application of IPM in a repeated batch process will be tested, where IPM is added at the end of each batch run to remove triterpenoids from the cells, allowing the same biocatalysts to be used in several sequential batch steps. Due to its high biocompatibility, the amount of IPM added to the culture can also be increased to more than 20 vol % to extract more than 40 % triterpenoids in the organic phase, allowing the cells to produce more triterpenoids. This highlights the potential for the development of a continuous large-scale process, which allows biocatalysts to produce intracellular products continuously without the necessity of cell disruption and without limitation of the cell capacity.

Keywords: betulinic acid, biocompatible solvent, in-situ extraction, isopropyl myristate, process development, secondary metabolites, triterpenoids, yeast

Procedia PDF Downloads 131

Authors: A. Mulry, C. Kealey, D. B. Brady

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Planktonic bacteria can form biofilms which are microbial aggregates embedded within a matrix of extracellular polymeric substances (EPS). They can be found attached to abiotic or biotic surfaces. Biofilms are responsible for oral diseases such as dental caries, gingivitis and the progression of periodontal disease. Biofilms can resist 500 to 1000 times the concentration of biocides and antibiotics used to kill planktonic bacteria. Biofilm development on oral surfaces involves four stages, initial attachment, early development, maturation and dispersal of planktonic cells. The Minimum Inhibitory Concentration (MIC) was determined using a range of saturated and unsaturated fatty acids using the resazurin assay, followed by serial dilution and spot plating on BHI agar plates to establish the Minimum Bactericidal Concentration (MBC). Log reduction of bacteria was also evaluated for each fatty acid. The Minimum Biofilm Inhibition Concentration (MBIC) was determined using crystal violet assay in 96 well plates on forming and pre-formed S. mutans biofilms using BHI supplemented with 1% sucrose. Saturated medium-chain fatty acids Octanoic (C8.0), Decanoic (C10.0) and Undecanoic acid (C11.0) do not display strong antibiofilm properties; however, Lauric (C12.0) and Myristic (C14.0) display moderate antibiofilm properties with 97.83% and 97.5% biofilm inhibition with 1000 µM respectively. Monounsaturated, Oleic acid (C18.1) and polyunsaturated large chain fatty acids, Linoleic acid (C18.2) display potent antibiofilm properties with biofilm inhibition of 99.73% at 125 µM and 100% at 65.5 µM, respectively. Long-chain polyunsaturated Omega-3 fatty acids α-Linoleic (C18.3), Eicosapentaenoic Acid (EPA) (C20.5), Docosahexaenoic Acid (DHA) (C22.6) have displayed strong antibiofilm efficacy from concentrations ranging from 31.25-250µg/ml. DHA is the most promising antibiofilm agent with an MBIC of 99.73% with 15.625µg/ml. This may be due to the presence of six double bonds and the structural orientation of the fatty acid. To conclude, fatty acids displaying the most antimicrobial activity appear to be medium or long-chain unsaturated fatty acids containing one or more double bonds. Most promising agents include Omega-3-fatty acids Linoleic, α-Linoleic, EPA and DHA, as well as Omega-9 fatty acid Oleic acid. These results indicate that fatty acids have the potential to be used as antimicrobials and antibiofilm agents against S. mutans. Future work involves further screening of the most potent fatty acids against a range of bacteria, including Gram-positive and Gram-negative oral pathogens. Future work will involve incorporating the most effective fatty acids onto dental implant devices to prevent biofilm formation.

Keywords: antibiofilm, biofilm, fatty acids, S. mutans

Procedia PDF Downloads 139

Authors: M. Gowri, E. K. Girija, V. Ganesh

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Background and Significance: Among the dental infections, inflammation and infection of the root canal are common among all age groups. Currently, the management of root canal infections involves cleaning the canal with powerful irrigants followed by intracanal medicament application. Though these treatments have been in vogue for a long time, root canal failures do occur. Treatment for root canal infections is limited due to the anatomical complexity in terms of small micrometer volumes and poor penetration of drugs. Thus, infections of the root canal seem to be a challenge that demands development of new agents that can eradicate C. albicans. Methodology: In the present study, we synthesized and screened silver-curcumin nanoparticle against Candida albicans. Detailed molecular studies were carried out with silver-curcumin nanoparticle on C. albicans pathogenicity. Morphological cell damage and antibiofilm activity of silver-curcumin nanoparticle on C. albicans was studied using scanning electron microscopy (SEM). Biochemical evidence for membrane damage was studied using flow cytometry. Further, the antifungal activity of silver-curcumin nanoparticle was evaluated in an ex vivo dentinal tubule infection model. Results: Screening data showed that silver-curcumin nanoparticle was active against C. albicans. Silver-curcumin nanoparticle exerted time kill effect and post antifungal effect. When used in combination with fluconazole or nystatin, silver-curcumin nanoparticle revealed a minimum inhibitory concentration (MIC) decrease for both drugs used. In-depth molecular studies with silver-curcumin nanoparticle on C. albicans showed that silver-curcumin nanoparticle inhibited yeast to hyphae (Y-H) conversion. Further, SEM images of C. albicans showed that silver-curcumin nanoparticle caused membrane damage and inhibited biofilm formation. Biochemical evidence for membrane damage was confirmed by increased propidium iodide (PI) uptake in flow cytometry. Further, the antifungal activity of silver-curcumin nanoparticle was evaluated in an ex vivo dentinal tubule infection model, which mimics human tooth root canal infection. Confocal laser scanning microscopy studies showed eradication of C. albicans and reduction in colony forming unit (CFU) after 24 h treatment in the infected tooth samples in this model. Conclusion: The results of this study can pave the way for developing new antifungal agents with well deciphered mechanisms of action and can be a promising antifungal agent or medicament against root canal infection.

Keywords: C. albicans, ex vivo dentine model, inhibition of biofilm formation, root canal infection, yeast to hyphae conversion inhibition

Procedia PDF Downloads 194

Authors: Adamu Mudi, Ibrahim Wahab Fawole, Abubakar Abba Kolo

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In this research paper, we present a microcontroller-based liquid level controller that identifies the various levels of a liquid, carries out certain actions, and is capable of communicating with the human being and other devices through the GSM network. This project is useful in ensuring that a liquid is not wasted. It also contributes to the internet of things paradigm, which is the future of the internet. The method used in this work includes designing the circuit and simulating it. The circuit is then implemented on a solderless breadboard, after which it is implemented on a strip board. A C++ computer program is developed and uploaded into the microcontroller. This program instructs the microcontroller on how to carry out its actions. In other to determine levels of the liquid, an ultrasonic wave is sent to the surface of the liquid similar to radar or the method for detecting the level of sea bed. Message is sent to the phone of the user similar to the way computers send messages to phones of GSM users. It is concluded that the routine of observing the levels of a liquid in a tank, refilling the tank when the liquid level is too low can be entirely handled by a programmable device without wastage of the liquid or bothering a human being with such tasks.

Keywords: Arduino Uno, HC-SR04 ultrasonic sensor, internet of things, IoT, SIM900 GSM module

Procedia PDF Downloads 116

Authors: Badryah Alshehri, Kevin Gormley, Gillian Prue, Karen McCutcheon

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In a disaster event, sharing patient information between the pre-hospital Emergency Medical Services (EMS) and Emergency Department (ED) hospitals is a complex process during which important information may be altered or lost due to poor communication. The aim of this study was to critically discuss the current evidence base in relation to communication between pre- EMS hospital and ED hospital professionals by the use of Information and Communication Systems (ICT). This study followed the systematic approach; six electronic databases were searched: CINAHL, Medline, Embase, PubMed, Web of Science, and IEEE Xplore Digital Library were comprehensively searched in January 2018 and a second search was completed in April 2020 to capture more recent publications. The study selection process was undertaken independently by the study authors. Both qualitative and quantitative studies were chosen that focused on factors that are positively or negatively associated with coordinated communication between pre-hospital EMS and ED teams in a disaster event. These studies were assessed for quality, and the data were analyzed according to the key screening themes which emerged from the literature search. Twenty-two studies were included. Eleven studies employed quantitative methods, seven studies used qualitative methods, and four studies used mixed methods. Four themes emerged on communication between EMTs (pre-hospital EMS and ED staff) in a disaster event using the ICT. (1) Disaster preparedness plans and coordination. This theme reported that disaster plans are in place in hospitals, and in some cases, there are interagency agreements with pre-hospital and relevant stakeholders. However, the findings showed that the disaster plans highlighted in these studies lacked information regarding coordinated communications within and between the pre-hospital and hospital. (2) Communication systems used in the disaster. This theme highlighted that although various communication systems are used between and within hospitals and pre-hospitals, technical issues have influenced communication between teams during disasters. (3) Integrated information management systems. This theme suggested the need for an integrated health information system that can help pre-hospital and hospital staff to record patient data and ensure the data is shared. (4) Disaster training and drills. While some studies analyzed disaster drills and training, the majority of these studies were focused on hospital departments other than EMTs. These studies suggest the need for simulation disaster training and drills, including EMTs. This review demonstrates that considerable gaps remain in the understanding of the communication between the EMS and ED hospital staff in relation to response in disasters. The review shows that although different types of ICTs are used, various issues remain which affect coordinated communication among the relevant professionals.

Keywords: emergency medical teams, communication, information and communication technologies, disaster

Procedia PDF Downloads 115

Authors: Sonal H. Singh, Bhaskar Bhowmick

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The research hypothesis formulated in this paper examines the importance of microfinance provision for entrepreneurship development by engendering a high level of entrepreneurial orientation among the grassroots entrepreneurs. A theoretically well supported empirical framework is proposed to identify the influence of financial services and non-financial services provided by microfinance institutes in strengthening the impact of grassroots innovation on entrepreneurial orientation under resource constraints. In this paper, Grassroots innovation is perceived in three dimensions: new learning practice, localized solution, and network development. The study analyzes the moderating effect of microfinance provision on the relationship between grassroots innovation and entrepreneurial orientation. The paper employed structural equation modelling on 400 data entries from the grassroots entrepreneurs in India. The research intends to help policymakers, entrepreneurs and microfinance providers to promote the innovative design of microfinance services for the well-being of grassroots entrepreneurs and to foster sustainable entrepreneurship development.

Keywords: entrepreneurship development, grassroots innovation, India, structural equation model

Procedia PDF Downloads 248

Authors: Somayyeh Naeemi, Ezhar Tamam

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In most of the countries, Facebook allocated high rank of usage among other social network sites. Several studies have examined the effect of Facebook intensity on individuals’ psychological well-being. However, few studies have investigated its effect on eudaimonic well-being. The current study explored how emotional dependency to Facebook relates to psychological well-being in terms of eudaimonic well-being. The number of 402 adolescents 13-16 years old who studied in upper secondary school in Malaysia participated in this study. It was expected to find out a negative association between emotional dependency to Facebook and time spent on Facebook and psychological well-being. It also was examined the moderation effects of self-efficacy on psychological well-being. The results by Structural Equation Modeling revealed that emotional dependency to Facebook has a negative effect on adolescents’ psychological well-being. Surprisingly self-efficacy did not have moderation effect on the relationship between emotional dependency to Facebook and psychological well-being. Lastly, the emotional dependency to Facebook and not the time spent on Facebook lessen adolescents’ psychological well-being, suggesting the value of investigating Facebook usage among college students in future studies.

Keywords: emotional dependency to facebook, psychological well-being, eudaimonic well-being, self-efficacy, adolescent

Procedia PDF Downloads 501