Search results for: improved sparrow search algorithm

Authors: Riyad Awad, Abdulmohsen Alghadeer, Meshari Otaibi

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Proper operation and maintenance (O&M) activities of high voltage equipment can lead to an increased asset lifecycle and maintain its integrity and reliability. Such a vital process is important to be proactively considered during equipment design and manufacturing phases by removing and eliminating any obstacles in the equipment which adversely affect the (O&M) activities. This paper presents a gap analysis pertaining to difficulties in performing operations and maintenance (O&M) high voltage electrical equipment, includes power transformers, switch gears, motor control center, disconnect switches and circuit breakers. The difficulties are gathered from field personnel, equipment design review comments, quality management system, and lessons learned database. The purpose of the gap analysis is to mitigate and prevent the (O&M) difficulties as early as possible in the design stage of the equipment lifecycle. The paper concludes with several recommendations and corrective actions for all identified gaps in order to reduce the cost (O&M) difficulties and improve the equipment lifecycle.

Keywords: operation and maintenance, high voltage equipment, equipment lifecycle, reduce the cost of maintenance

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

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Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

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Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

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Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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Authors: J. Al-Dmour, A. Sagahyroon, A. Al-Ali, S. Abusnana

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Radio Frequency Based Identification Systems have emerged as one of the possible valuable solutions that can be utilized in healthcare systems. Nowadays, RFID tags are available with built-in human vital signs sensors such as Body Temperature, Blood Pressure, Heart Rate, Blood Sugar level and Oxygen Saturation in Blood. This work proposes the design, implementation, and testing of an integrated mobile RFID-based health care system. The system consists of a wireless mobile vital signs data acquisition unit (RFID-DAQ) integrated with a fuzzy-logic–based software algorithm to monitor and assess patients conditions. The system is implemented and tested in ‘Rashid Center for Diabetes and Research’, Ajman, UAE. System testing results are compared with the Modified Early Warning System (MEWS) that is currently used in practice. We demonstrate that the proposed and implemented system exhibits an accuracy level that is comparable and sometimes better than the widely adopted MEWS system.

Keywords: healthcare, fuzzy logic, MEWS, RFID

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Authors: Vishwesh Kulkarni, Nikhil Bellarykar

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Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.

Keywords: synthetic gene network, network identification, optimization, nonlinear modeling

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Authors: Rahmat Purwoko, Bambang Riyanto Trilaksono

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This paper gives comparison of INS/GNSS architecture namely Loosely Coupled and Tightly Coupled using Hardware in the Loop Simulation in Guided Missile RKX-200 rocket model. INS/GNSS Tightly Coupled architecture requires pseudo-range, pseudo-range rate, and position and velocity of each satellite in constellation from GPS (Global Positioning System) measurement. The Loosely Coupled architecture use estimated position and velocity from GNSS receiver. INS/GNSS architecture also requires angular rate and specific force measurement from IMU (Inertial Measurement Unit). Loosely Coupled arhitecture designed using 15 states Kalman Filter and Tightly Coupled designed using 17 states Kalman Filter. Integration algorithm calculation using ECEF frame. Navigation System implemented Zedboard All Programmable SoC.

Keywords: kalman filter, loosely coupled, navigation system, tightly coupled

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

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Authors: R. Ziaie Moayed, A. Mahigir

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Stone column technique has been successfully employed to improve the load-settlement characteristics of foundations. A series of finite element numerical analyses of harmonic dynamic loading have been conducted on strengthened raft footing to study the effects of single and group stone columns on settlement of circular footings. The settlement of circular raft footing that improved by single and group of stone columns are studied under harmonic dynamic loading. This loading is caused by heavy machinery foundations. A detailed numerical investigation on behavior of single column and group of stone columns is carried out by varying parameters like weight of machinery, loading frequency and period. The result implies that presence of single and group of stone columns enhanced dynamic behavior of the footing so that the maximum and residual settlement of footing significantly decreased. 

Keywords: finite element analysis, harmonic loading, settlement, stone column

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Authors: A. Khodadadi, Hasani, Salehi

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The advantages of using modified asphalt binders are widely recognized—primarily, improved rutting resistance, reduced fatigue cracking and less cold-temperature cracking. Nanoclays are known to enhance the properties of many polymers. Nanoclays are used to improve modulus and tensile strength, flame resistance and thermal and structural properties of many materials. This paper intends to investigate the application and development of nano-technological concepts for bituminous materials and asphalt pavements. The application of nano clay on the fatigue life of asphalt pavement have not been yet thoroughly understood. In this research, two type of highway asphalt materials, dense Marshall specimens, with 2% nano clay and without nano clay, were employed for the fatigue behavior of the asphalt pavement.The effect of nano additive on the performance of flexible pavements has been investigated through the indirect tensile test for the samples prepared with 2% nano clay and without nano clay in four stress levels from 200–500 kPa. The primary results indicated samples with 2% nano clay have almost double or even more fatigue life in most of stress levels.

Keywords: Nano clay, Asphalt, fatigue life, pavement

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Authors: Gadisa Alemayehu, Muralidhar Avvari, Atkilt Mulu G.

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Since 1962 EC, the Faffa Food Share Company has been producing and supplying flour (famix) and value-added flour (baby food) in Ethiopia. It meets nearly all of the country's total flour demand, both for relief and commercial markets. However, it is incompetent in the international market due to a poor maintenance management system. The results of recorded documents and stopwatches revealed that frequent failure machines, as well as a poor maintenance management system, cause increased production downtimes, resulting in a 29.19 percent decrease in production from the planned production. As a result, the current study's goal is to recommend newly developed software for use in and as a Computerized Maintenance Management System (CMMS). As a result, the system increases machine reliability and decreases the frequency of equipment failure, reducing breakdown time and maintenance costs. The company's overall manufacturing performance improved by 4.45 percent, particularly after the implementation of the CMMS.

Keywords: CMMS, manufacturing performance, delivery, availability, flexibility, Faffa Food Share Company

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Authors: Zemour Kamel, Chouhim Kadda Mohamed Amine

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Salinity is one of the most environmental factors limiting crop productivity. It has a negative effect on both germination and plant growth processes (photosynthesis, respiration, and transpiration), nutrient balance, membrane properties and cellular homeostasis, enzymatic and metabolic activities. Among the strategic crops in the world and more mainly in Algeria, durum wheat is very affected by this abiotic stress. For that, this study focuses on an evaluation of salt stress effect on the germination process of durum wheat as well as its response after application of lavender hydrosol and aqueous pistachio extract. The results have shown that all the physicochemical parameters of germination have been affected by this stress. However, lavender hydrosol and aqueous pistachio extract, considered as organic compounds, significantly improved the germination of wheat seeds. Finally, this study has highlighted the importance of using organic products as an ideal alternative to reduce the effect of abiotic stress on durum wheat productivity.

Keywords: salinity, wheat durum, extract, lavender hydrosol, aqueous pistachio

Procedia PDF Downloads 83

Authors: Ramin Shadani

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This study introduces adaptive performance as a key organizational performance dimension and explores the relationship between the dimensions of a learning organization and adaptive performance. A survey was therefore conducted using the dimensions of the Learning Organization Questionnaire (DLOQ), followed by factor analysis and structural equation modeling in order to investigate the dynamics between learning organization practices and adaptive performance. Results confirm that adaptive performance is indeed one important dimension of organizational performance. The study also shows that perceived knowledge and adaptive performance mediate the positive relationship between the practices of a learning organization with perceived financial performance. We extend existing DLOQ research by demonstrating that adaptive performance, as a nonfinancial organizational learning outcome, has a significant impact on financial performance. Our study also provides additional validation of the measures of DLOQ's performance. Indeed, organizations need to take a glance at how the activities of learning and development can provide better overall improvement in performance, especially in enhancing adaptive capability. The study has provided requisite empirical support that activities of learning and development within organizations allow much-improved intangible performance outcomes, especially through adaptive performance.

Keywords: adaptive performance, continuous learning, financial performance, leadership style, organizational learning, organizational performance

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Authors: W. Handoko, F. Pahlevani, V. Sahajwalla

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Dual-phase high carbon steels (DHCS) are commonly known for their improved strength, hardness, and abrasive resistance properties due to co-presence of retained austenite and martensite at the same time. Retained austenite is a meta-stable phase at room temperature, and stability of this phase governs the response of DHCS at different conditions. This research paper studies the effect of RA stability on corrosion behaviour of high carbon steels after they have been immersed into 1.0 M NaCl solution for various times. For this purpose, two different steels with different RA stabilities have been investigated. The surface morphology of the samples before and after corrosion attack was observed by secondary electron microscopy (SEM) and atomic force microscopy (AFM), along with the weight loss and Vickers hardness analysis. Microstructural investigations proved the preferential attack to retained austenite phase during corrosion. Hence, increase in the stability of retained austenite in dual-phase steels led to decreasing the weight loss rate.

Keywords: high carbon steel, austenite stability, atomic force microscopy, corrosion

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Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

Procedia PDF Downloads 349

Authors: Shih-Wen Hsiao, Chu-Hsuan Lee, Rong-Qi Chen

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When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Keywords: 3D last design, customization, reverse engineering, weighted morphing, shape blending

Procedia PDF Downloads 340

Authors: Parul Bhandari

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An image of a modern and progressive India garners the rhetoric of ‘choice’ marriages, gender egalitarian relationships, and search for ‘love’ in conjugal unions. Such an image especially resonates with the lives of young professionals, who, largely belonging to the middle class, consider themselves to be the global face India. While this rhetoric of ‘progress’ and ‘love’ is abounding in both Indian and non-Indian public discourses, it is imperative to scientifically analyse the veracity of these claims. This paper thus queries and problematises the notions of being modern and progressive, through the lens of gender roles as expected and desired in a process of matchmaking. The fieldwork conducted is based on qualitative methodology, involving in-depth interviews with 100 highly qualified professionals, (60 men and 40 women), between the age of 24-31, belonging to the Hindu religion and of varied castes and communities, who are residing in New Delhi, and are in the process of spouse-selection or have recently completed it. Further, an analysis of the structure and content of matrimonial websites, which have fast emerged as the new method of matchmaking, was also undertaken. The main finding of this paper is that gender asymmetries continue to determine a suitable match, whether in ‘arranged’ or ‘love’ marriages. This is demonstrated by analysing the expectations of gender roles and gender practices of both men and women, to construct an ideal of a ‘good match’. On the basis of the interviews and the content of matrimonial websites, the paper discusses the characteristics of a ‘suitable boy’ and a ‘suitable girl’, and the ways in which these are received (practiced or criticised) by the young men and women themselves. It is then concluded that though an ideal of ‘compatibility’ and love determines conjugal desires, traditional gender roles, that, for example, consider men as the primary breadwinner and women as responsible for the domestic sphere, continue to dictate urban Indian marriages.

Keywords: gender, India, marriage, middle class

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Authors: Edeaghe Ehikhamenor, Jennifer Nnamdi

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Introduction: Gender-based violence (GBV) was a well-known global crisis before the COVID-19 pandemic. The pandemic burden only intensified the crisis. With prevailing lockdowns, increased poverty due to high unemployment, especially affecting females, and other mobility restrictions that have left many women trapped with their abusers, plus isolation from social contact and support networks, GBV cases spiraled out of control. Prevalence of economic with cultural disparity, which is greatly manifested in Nigeria, is a major contributory factor to GBV. This is made worst by religious adherents where the females are virtually relegated to the background. Our societal approaches to investigations and sanctions to culprits have not sufficiently applied forensic/DNA tools in combating these major vices. Violence against women or some rare cases against men can prevent them from carrying out their duties regardless of the position they hold. Objective: The main objective of this research is to highlight the origin of GBV, the victims, types, contributing factors, and the applications of forensics/DNA tools and remedies so as to minimize GBV in our society. Methods: Descriptive information was obtained through the search on our daily newspapers, electronic media, google scholar websites, other authors' observations and personal experiences, plus anecdotal reports. Results: Findings from our exploratory searches revealed a high incidence of GBV with very limited or no applications of Forensics/DNA tools as an intervening mechanism to reduce GBV in Nigeria. Conclusion: Nigeria needs to develop clear-cut policies on forensics/DNA tools in terms of institutional framework to develop a curriculum for the training of all stakeholders to fast-track justice for victims of GBV so as to serve as a deterrent to other culprits.

Keywords: gender-based violence, forensics, DNA, justice

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Authors: Tran Le Luu, Jeyong Yoon

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RuO2-TiO2 electrode now becomes popular in the chlor-alkali industry because of high electrocatalytic and stability with chlorine and oxygen evolutions. Using alternative green method for preparation RuO2-TiO2 electrode is necessary to reduce the cost, time. In addition, it is needed to increase the electrocatalyst performance, stability, and environmental compatibility. In this study, the Ti/RuO2-TiO2 electrodes were synthesized using sol-gel method under microwave irradiation and investigated for the anodic chlorine and oxygen evolutions. This method produced small size and uniform distribution of RuO2-TiO2 nanoparticles with mean diameter of 8-10 nm on the big crack size surface which contributes for the increasing of the outer active surface area. The chlorine, oxygen evolution efficiency and stability comparisons show considerably higher for microwave-assisted coated electrodes than for those obtained by the conventional heating method. The microwave-assisted sol-gel route has been identified as a novel and powerful method for quick synthesis of RuO2–TiO2 electrodes with excellent chlorine and oxygen evolution performances.

Keywords: RuO2, electro-catalyst, sol-gel, microwave, chlorine, oxygen evolution

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Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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Authors: Hasmadi Mamat, Noorfarahzilah Masri

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The search for lesser known and underutilized crops, many of which are potentially valuable as human and animal foods has been the focus of research in recent years. Tarap (Artocarpus odoratisimmus) is one of the most delicious tropical fruit and can be found extensively in Borneo, particularly in Sabah and Sarawak. This study was conducted in order to determine the proximate composition, mineral contents as well as to study the effect of the seed flour on the quality of bread produced. Tarap seed powder (TSP) was incorporated (up to 20%) with wheat flour and used to produce bread. The moisture content, ash, protein, fat, ash, carbohydrates, and dietary fiber were measured using AOAC methods while the mineral content was determined using AAS. The effect of substitution of wheat flour with Tarap seed flour on the quality of dough and bread was investigated using various techniques. Farinograph tests were applied to determine the effect of seaweed powder on the rheological properties of wheat flour dough, while texture profile analysis (TPA) was used to measure the textural properties of the final product. Besides that sensory evaluations were also conducted. On a dry weight basis, the TSP was composed of 12.50% moisture, 8.78% protein, 15.60% fat, 1.17% ash, 49.65% carbohydrate and 12.30% of crude fiber. The highest mineral found were Mg, followed by K, Ca, Fe and Na respectively. Farinograh results found that as TSP percentage increased, dough consistency, water absorption capacity and development time of dough decreased. Sensory analysis results showed that bread with 10% of TSP was the most accepted by panelists where the highest acceptability score were found for aroma, taste, colour, crumb texture as well as overall acceptance. The breads with more than 10% of TSP obtained lower acceptability score in most of attributes tested.

Keywords: tarap seed, proximate analysis, bread, sensory evaluation

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Authors: Mandeep Kaur, Jitendra K. Bera

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The search for atom-economical and green synthetic methods for the synthesis of functionalized molecules has attracted much attention. Metal ligand cooperation (MLC) plays a pivotal role in organometallic catalysis to activate C−H, H−H, O−H, N−H and B−H bonds through reversible bond breaking and bond making process. Towards this goal, a bifunctional N─heterocyclic carbene (NHC) based pyridyl-functionalized amide ligand precursor, and corresponding dearomatized iridium complex was synthesized. The NMR and UV/Vis acid titration study have been done to prove the proton response nature of the iridium complex. Further, the dearomatized iridium complex explored as a catalyst on the platform of MLC via dearomatzation/aromatization mode of action towards atom economical α and β─alkylation of ketones and secondary alcohols by using primary alcohols through hydrogen borrowing methodology. The key features of the catalysis are high turnover frequency (TOF) values, low catalyst loading, low base loading and no waste product. The greener syntheses of quinoline, lactone derivatives and selective alkylation of drug molecules like pregnenolone and testosterone were also achieved successfully. Another structurally similar iridium complex was also synthesized with modified ligand precursor where a pendant amide unit was absent. The inactivity of this analogue iridium complex towards catalysis authenticated the participation of proton responsive imido sidearm of the ligand to accelerate the catalytic reaction. The mechanistic investigation through control experiments, NMR and deuterated labeling study, authenticate the borrowing hydrogen strategy.

Keywords: C-C bond formation, hydrogen borrowing, metal ligand cooperation (MLC), n-heterocyclic carbene

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Authors: Antonio Boggia, Luisa Paolotti, Gianluca Massei, Lucia Rocchi, Elaine Pace, Maria Attard

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The aim of this paper is to present a methodology and a computer model for sustainability assessment based on the integration of Multi-criteria Decision Analysis (MCDA) with a Geographic Information System (GIS). It presents the result of a study for the implementation of a model for measuring sustainability to address the policy actions for the improvement of sustainability at territory level. The aim is to rank areas in order to understand the specific technical and/or financial support that is required to develop sustainable growth. Assessing sustainable development is a multidimensional problem: economic, social and environmental aspects have to be taken into account at the same time. The tool for a multidimensional representation is a proper set of indicators. The set of indicators must be integrated into a model, that is an assessment methodology, to be used for measuring sustainability. The model, developed by the Environmental Laboratory of the University of Perugia, is called GeoUmbriaSUIT. It is a calculation procedure developed as a plugin working in the open-source GIS software QuantumGIS. The multi-criteria method used within GeoUmbriaSUIT is the algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Design), which defines a ranking based on the distance from the worst point and the closeness to an ideal point, for each of the criteria used. For the sustainability assessment procedure, GeoUmbriaSUIT uses a geographic vector file where the graphic data represent the study area and the single evaluation units within it (the alternatives, e.g. the regions of a country, or the municipalities of a region), while the alphanumeric data (attribute table), describe the environmental, economic and social aspects related to the evaluation units by means of a set of indicators (criteria). The use of the algorithm available in the plugin allows to treat individually the indicators representing the three dimensions of sustainability, and to compute three different indices: environmental index, economic index and social index. The graphic output of the model allows for an integrated assessment of the three dimensions, avoiding aggregation. The presence of separate indices and graphic output make GeoUmbriaSUIT a readable and transparent tool, since it doesn’t produce an aggregate index of sustainability as final result of the calculations, which is often cryptic and difficult to interpret. In addition, it is possible to develop a “back analysis”, able to explain the positions obtained by the alternatives in the ranking, based on the criteria used. The case study presented is an assessment of the level of sustainability in the six regions of Malta, an island state in the middle of the Mediterranean Sea and the southernmost member of the European Union. The results show that the integration of MCDA-GIS is an adequate approach for sustainability assessment. In particular, the implemented model is able to provide easy to understand results. This is a very important condition for a sound decision support tool, since most of the time decision makers are not experts and need understandable output. In addition, the evaluation path is traceable and transparent.

Keywords: GIS, multi-criteria analysis, sustainability assessment, sustainable development

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Authors: Chui Ling Teng, R. Matsa

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We report a case with combined overdose of Lercanidipine (non-dihydropyridine calcium channel blocker), Quetiapine (Atypical antipsychotic), Ramipril and Duloxetine. A 66-year old male presented to the Emergency Department 12-hours after the ingestion of 1.2g Lercanidipine, 3g Quetiapine, 280mg of Ramipril and 420mg of Duloxetine. He describes lethargic, drowsiness and was unable to pass any urine since overdosed. He was found to be bradycardic, hypotensive and anuric. He had refractory hypotension and anuric despite fluid resuscitation, glucagon therapy and intravenous naloxone. His care was escalated to Intensive care, requiring noradrenaline, adrenaline, vasopressin, and hyperinsulinaemic euglycaemia therapy. He achieved haemodynamic stability and kidney function improved gradually with the support received. The total length of therapy lasted for 30 horus in which individual therapy was weaned down based on the requirement. He was then transferred to medical ward for further psychiatric assessment. This is a the first repored case of mixed overdose with lercanidipine, Quetiapine, Rampmipril and Duloxetine.

Keywords: calcium channel blocker, hyperinsulinaemic Euglycaemia therapy, lercanidipine, overdose

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Authors: Dan Kanmegne

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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

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Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

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The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

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Authors: Lyndsee Baumann-Birkbeck, Sohil A. Khan, Shailendra Anoopkumar-Dukie, Gary D. Grant

Abstract:

Technology-enhanced education tools are being rapidly integrated into health programs globally. These tools provide an interactive platform for students and can be used to deliver topics in various modes including games and simulations. Simulations are of particular interest to healthcare education, where they are employed to enhance clinical knowledge and help to bridge the gap between theory and practice. Simulations will often assess competencies for practical tasks, yet limited research examines the effects of simulation on student perceptions of their learning. The aim of this study was to determine the effects of an interactive virtual patient simulation for pharmacology education and clinical practice on student knowledge, skills and confidence. Ethics approval for the study was obtained from Griffith University Research Ethics Committee (PHM/11/14/HREC). The simulation was intended to replicate the pharmacy environment and patient interaction. The content was designed to enhance knowledge of proton-pump inhibitor pharmacology, role in therapeutics and safe supply to patients. The tool was deployed into a third-year clinical pharmacology and therapeutics course. A number of core practice areas were examined including the competency domains of questioning, counselling, referral and product provision. Baseline measures of student self-reported knowledge, skills and confidence were taken prior to the simulation using a specifically designed questionnaire. A more extensive questionnaire was deployed following the virtual patient simulation, which also included measures of student engagement with the activity. A quiz assessing student factual and conceptual knowledge of proton-pump inhibitor pharmacology and related counselling information was also included in both questionnaires. Sixty-one students (response rate >95%) from two cohorts (2014 and 2015) participated in the study. Chi-square analyses were performed and data analysed using Fishers exact test. Results demonstrate that student knowledge, skills and confidence within the competency domains of questioning, counselling, referral and product provision, show improvement following the implementation of the virtual patient simulation. Statistically significant (p<0.05) improvement occurred in ten of the possible twelve self-reported measurement areas. Greatest magnitude of improvement occurred in the area of counselling (student confidence p<0.0001). Student confidence in all domains (questioning, counselling, referral and product provision) showed a marked increase. Student performance in the quiz also improved, demonstrating a 10% improvement overall for pharmacology knowledge and clinical practice following the simulation. Overall, 85% of students reported the simulation to be engaging and 93% of students felt the virtual patient simulation enhanced learning. The data suggests that the interactive virtual patient simulation developed for clinical pharmacology and therapeutics education enhanced students knowledge, skill and confidence, with respect to the competency domains of questioning, counselling, referral and product provision. These self-reported measures appear to translate to learning outcomes, as demonstrated by the improved student performance in the quiz assessment item. Future research of education using virtual simulation should seek to incorporate modern quantitative measures of student learning and engagement, such as eye tracking.

Keywords: clinical simulation, education, pharmacology, simulation, virtual learning

Procedia PDF Downloads 338

Authors: S. Y. Lin, C. H. Kuan, C. H. She, W. T. Wang

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In this study, ultrasonic assisted machining (UAM) technique is applied in side-surface milling experiment for glass-ceramic workpiece material. The tungsten carbide cutting-tool with diamond coating is used in conjunction with two kinds of cooling/lubrication mediums such as water-soluble (WS) cutting fluid and minimum quantity lubricant (MQL). Full factorial process parameter combinations on the milling experiments are planned to investigate the effect of process parameters on cutting performance. From the experimental results, it tries to search for the better process parameter combination which the edge-indentation and the surface roughness are acceptable. In the machining experiments, ultrasonic oscillator was used to excite a cutting-tool along the radial direction producing a very small amplitude of vibration frequency of 20KHz to assist the machining process. After processing, toolmaker microscope was used to detect the side-surface morphology, edge-indentation and cutting tool wear under different combination of cutting parameters, and analysis and discussion were also conducted for experimental results. The results show that the main leading parameters to edge-indentation of glass ceramic are cutting depth and feed rate. In order to reduce edge-indentation, it needs to use lower cutting depth and feed rate. Water-soluble cutting fluid provides a better cooling effect in the primary cutting area; it may effectively reduce the edge-indentation and improve the surface morphology of the glass ceramic. The use of ultrasonic assisted technique can effectively enhance the surface finish cleanness and reduce cutting tool wear and edge-indentation.

Keywords: glass-ceramic, ultrasonic assisted machining, cutting performance, edge-indentation

Procedia PDF Downloads 285

Authors: Mohamed Farhat O. Hameed, Yasamin K. A. Alrayk, A. A Shaalan, S. S. A. Obayya

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The surface plasmon resonance (SPR) sensors are widely used due to its high sensitivity with molecular labels free. The commercial SPR sensors depend on the conventional prism-coupled configuration. However, this type of configuration suffers from miniaturization and integration. Therefore, the search for compact, portable and highly sensitive SPR sensors becomes mandatory.In this paper, sensitivity enhancement of a novel photonic crystal fiber biosensoris introduced and studied. The suggested design has microstructure of air holes in the core region surrounded by two large semicircular metallized channels filled with the analyte. The inner surfaces of the two channels are coated by a silver layer followed by a gold layer.The simulation results are obtained using full vectorial finite element methodwith perfect matched layer (PML) boundary conditions. The proposed design depends on bimetallic configuration to enhance the biosensor sensitivity. Additionally, the suggested biosensor can be used for multi-channel/multi-analyte sensing. In this study, the sensor geometrical parameters are studied to maximize the sensitivity for the two polarized modes. The numerical results show that high refractive index sensitivity of 4750 nm/RIU (refractive index unit) and 4300 nm/RIU can be achieved for the quasi (transverse magnetic) TM and quasi (transverse electric) TE modes of the proposed biosensor, respectively. The reportedbiosensor has advantages of integration of microfluidics setup, waveguide and metallic layers into a single structure. As a result, compact biosensor with better integration compared to conventional optical fiber SPR biosensors can be obtained.

Keywords: photonic crystal fibers, gold, silver, surface plasmon, biosensor

Procedia PDF Downloads 380

Authors: Odeyemi Ifeoluwayemi, Maha Joushua, Fulani Omoyeni

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In the search for sustainability, over time, architectural approaches to design have moved from just nature inspired design to the study of nature’s principles to produce effective designs that solve the issue of sustainability. Nature has established materials, shapes and processes that are effective right from a minor scale to an enormous scale. A branch of human knowledge that studies nature is called biology. Biology helps us to grasp and understand nature. Biomimicry is a new way of viewing and valuing nature, based not on what we can extract from the natural world but on what we can learn from it. Life has sustained on the earth for the last 3.85 billion years, and it is necessary for us to find out how life has been able to stay sustained for that long. The building must teach the society new ecological morals, thus, a better understanding of how nature works can usefully inspire architectural designs to resolve issues that have already been resolved by nature. This will not only help in creating a healthy environment but will also produce positive environmental impacts. Biomimetic Architecture connects and reproduces the ideologies found in nature in order to create built environment which benefit people and other living creatures as well as preserving it for the future. Understanding the bioprocess would lead to the establishment of ecological approaches that serve as a platform for creating a built environment that goes beyond sustaining current settings but also mimic nature’s regenerative ecosystem. This paper aims to explain these design methods under the name of biomimicry and biomimetic architecture by reviewing literature and research works done by examining these approaches classified as forms, processes and ecosystems. It is expected that this research will provide information that would, therefore, lead to the creation of buildings that are eco-friendly and provide greater comfort to the populaces.

Keywords: biomimetic architecture, biomimicry, ecological design, nature

Procedia PDF Downloads 256