Search results for: multiple input multiple output
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8069

Search results for: multiple input multiple output

5939 Input and Interaction as Training for Cognitive Learning: Variation Sets Influence the Sudden Acquisition of Periphrastic estar 'to be' + verb + -ndo*

Authors: Mary Rosa Espinosa-Ochoa

Abstract:

Some constructions appear suddenly in children’s speech and are productive from the beginning. These constructions are supported by others, previously acquired, with which they share semantic and pragmatic features. Thus, for example, the acquisition of the passive voice in German is supported by other constructions with which it shares the lexical verb sein (“to be”). This also occurs in Spanish, in the acquisition of the progressive aspectual periphrasis estar (“to be”) + verb root + -ndo (present participle), supported by locative constructions acquired earlier with the same verb. The periphrasis shares with the locative constructions not only the lexical verb estar, but also pragmatic relations. Both constructions can be used to answer the question ¿Dónde está? (“Where is he/she/it?”), whose answer could be either Está aquí (“He/she/it is here”) or Se está bañando (“He/she/it is taking a bath”).This study is a corpus-based analysis of two children (1;08-2;08) and the input directed to them: it proposes that the pragmatic and semantic support from previously-acquired constructions comes from the input, during interaction with others. This hypothesis is based on analysis of constructions with estar, whose use to express temporal change (which differentiates it from its counterpart ser [“to be”]), is given in variation sets, similar to those described by Küntay and Slobin (2002), that allow the child to perceive the change of place experienced by nouns that function as its grammatical subject. For example, at different points during a bath, the mother says: El jabón está aquí “The soap is here” (beginning of bath); five minutes later, the soap has moved, and the mother says el jabón está ahí “the soap is there”; the soap moves again later on and she says: el jabón está abajo de ti “the soap is under you”. “The soap” is the grammatical subject of all of these utterances. The Spanish verb + -ndo is a progressive phase aspect encoder of a dynamic state that generates a token. The verb + -ndo is also combined with verb estar to encode. It is proposed here that the phases experienced in interaction with the adult, in events related to the verb estar, allow a child to generate this dynamicity and token reading of the verb + -ndo. In this way, children begin to produce the periphrasis suddenly and productively, even though neither the periphrasis nor the verb + -ndo itself are frequent in adult speech.

Keywords: child language acquisition, input, variation sets, Spanish language

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5938 Medical Advances in Diagnosing Neurological and Genetic Disorders

Authors: Simon B. N. Thompson

Abstract:

Retinoblastoma is a rare type of childhood genetic cancer that affects children worldwide. The diagnosis is often missed due to lack of education and difficulty in presentation of the tumor. Frequently, the tumor on the retina is noticed by photography when the red-eye flash, commonly seen in normal eyes, is not produced. Instead, a yellow or white colored patch is seen or the child has a noticeable strabismus. Early detection can be life-saving though often results in removal of the affected eye. Remaining functioning in the healthy eye when the child is young has resulted in super-vision and high or above-average intelligence. Technological advancement of cameras has helped in early detection. Brain imaging has also made possible early detection of neurological diseases and, together with the monitoring of cortisol levels and yawning frequency, promises to be the next new early diagnostic tool for the detection of neurological diseases where cortisol insufficiency is particularly salient, such as multiple sclerosis and Cushing’s disease.

Keywords: cortisol, neurological disease, retinoblastoma, Thompson cortisol hypothesis, yawning

Procedia PDF Downloads 386
5937 RGB-D SLAM Algorithm Based on pixel level Dense Depth Map

Authors: Hao Zhang, Hongyang Yu

Abstract:

Scale uncertainty is a well-known challenging problem in visual SLAM. Because RGB-D sensor provides depth information, RGB-D SLAM improves this scale uncertainty problem. However, due to the limitation of physical hardware, the depth map output by RGB-D sensor usually contains a large area of missing depth values. These missing depth information affect the accuracy and robustness of RGB-D SLAM. In order to reduce these effects, this paper completes the missing area of the depth map output by RGB-D sensor and then fuses the completed dense depth map into ORB SLAM2. By adding the process of obtaining pixel-level dense depth maps, a better RGB-D visual SLAM algorithm is finally obtained. In the process of obtaining dense depth maps, a deep learning model of indoor scenes is adopted. Experiments are conducted on public datasets and real-world environments of indoor scenes. Experimental results show that the proposed SLAM algorithm has better robustness than ORB SLAM2.

Keywords: RGB-D, SLAM, dense depth, depth map

Procedia PDF Downloads 140
5936 Research on Supply Chain Coordination Based on Lateral Transshipment in the Background of New Retail

Authors: Yue Meng, Lingyun Wei

Abstract:

In this paper, the coordination problem of a supply chain system composed of multiple retailers and manufacturers is studied under the background of the new retail supply chain. Taking a system composed of two retailers and one manufacturer as an example, this paper introduces an online store owned by the manufacturer to reflect the characteristics of the combination of online and offline new retail. Then, this paper gives the conditions that need to be satisfied to realize the coordination between retailers and manufacturers, such as the revenue sharing coefficient. The supply chain coordination model is compared with the newsboy model through a specific example. Finally, the conclusion is drawn that the profits of the coordinated supply chain and its members are better than the corresponding profits under the newsboy model; that is, the coordination of the supply chain is realized by using the revenue sharing contract and the transshipment fund mechanism.

Keywords: transshipment, coordination, multi-retailer, revenue-sharing contract

Procedia PDF Downloads 143
5935 Systematic Examination of Methods Supporting the Social Innovation Process

Authors: Mariann Veresne Somosi, Zoltan Nagy, Krisztina Varga

Abstract:

Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.

Keywords: factors of social innovation, methodological combination, social innovation process, supporting decision-making

Procedia PDF Downloads 155
5934 Secure Transmission Scheme in Device-to-Device Multicast Communications

Authors: Bangwon Seo

Abstract:

In this paper, we consider multicast device-to-device (D2D) direct communication systems in cellular networks. In multicast D2D communications, nearby mobile devices exchanges, their data directly without going through a base station and a D2D transmitter send its data to multiple D2D receivers that compose of D2D multicast group. We consider wiretap channel where there is an eavesdropper that attempts to overhear the transmitted data of the D2D transmitter. In this paper, we propose a secure transmission scheme in D2D multicast communications in cellular networks. In order to prevent the eavesdropper from overhearing the transmitted data of the D2D transmitter, a precoding vector is employed at the D2D transmitter in the proposed scheme. We perform computer simulations to evaluate the performance of the proposed scheme. Through the simulation, we show that the secrecy rate performance can be improved by selecting an appropriate precoding vector.

Keywords: device-to-device communications, wiretap channel, secure transmission, precoding

Procedia PDF Downloads 291
5933 Image Instance Segmentation Using Modified Mask R-CNN

Authors: Avatharam Ganivada, Krishna Shah

Abstract:

The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

Procedia PDF Downloads 73
5932 Measuring Strategic Management Maturity: An Empirical Study in Turkish Public and Private Sector Organizations

Authors: F. Demir

Abstract:

Strategic Management is highly critical for all types of organizations. This paper examines maturity level of strategic management practices of public and private sector organizations in Turkey, and presents a conceptual model for assessing the maturity of strategic management in any organization. This research focuses on R&D intensive organizations (RDO) because it is claimed that such organizations are more innovative and innovation is a critical part of the model. The Strategic management maturity model (S-3M) is basically composed of six maturity levels with five different dimensions. Based on 63 organizations, the findings reveal that the average maturity of all organizations in the sample group is three out of five. It corresponds to the stage of ‘performed’. Results simply show that the majority of organizations from various industries and sectors implement strategic management activities; however, they experience multiple challenges to optimize strategic management processes and integrate organizational components with business strategies. Briefly, they struggle to become an innovative organization.

Keywords: strategic management maturity, innovation, developing countries, research and development

Procedia PDF Downloads 287
5931 Active Vibration Reduction for a Flexible Structure Bonded with Sensor/Actuator Pairs on Efficient Locations Using a Developed Methodology

Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

Abstract:

With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

Procedia PDF Downloads 232
5930 Voices of the Students From a Fully Inclusive Classroom

Authors: Ashwini Tiwari

Abstract:

Introduction: Inclusive education for all is a multifaceted approach that requires system thinking and the promotion of a "Culture of Inclusion." Such can only be achieved through the collaboration of multiple stakeholders at the community, regional, state, national, and international levels. Researchers have found effective practices used in inclusive general classrooms are beneficial to all students, including students with disabilities, those who experience challenges academically and socially, and students without disabilities as well. However, to date, no statistically significant effects on the academic performance of students without disabilities in the presence of students with disabilities have been revealed. Therefore, proponents against inclusive education practices, based solely on their beliefs regarding the detrimental effects of students without disabilities, appears to have unfounded perceptions. This qualitative case study examines students' perspectives and beliefs about inclusive education in a middle school in South Texas. More specifically, this study examined students understanding of how inclusive education practices intersect with the classroom community. The data was collected from the students attending fully inclusive classrooms through interviews and focus groups. The findings suggest that peer integration and friendships built during classes are an essential part of schooling for both disabled and non-disabled students. Research Methodology: This qualitative case study used observations and focus group interviews with 12 middle school students attending an inclusive classroom at a public school located in South Texas. The participant of this study includes eight females and five males. All the study participants attend a fully inclusive middle school with special needs peers. Five of the students had disabilities. The focus groups and interviews were conducted during for entire academic year, with an average of one focus group and observation each month. The data were analyzed using the constant comparative method. The data from the focus group and observation were continuously compared for emerging codes during the data collection process. Codes were further refined and merged. Themes emerged as a result of the interpretation at the end of the data analysis process. Findings and discussion: This study was conducted to examine disabled and non-disabled students' perspectives on the inclusion of disabled students. The study revealed that non-disabled students generally have positive attitudes toward their disabled peers. The students in the study did not perceive inclusion as a special provision; rather, they perceived inclusion as a way of instructional practice. Most of the participants in the study spoke about the multiple benefits of inclusion. They emphasized that peer integration and friendships built during classes are an essential part of their schooling. Students believed that it was part of their responsibility to assist their peers in the ways possible. This finding is in line with the literature that the personality of children with disabilities is not determined by their disability but rather by their social environment and its interaction with the child. Interactions with peers are one of the most important socio-cultural conditions for the development of children with disabilities.

Keywords: inclusion, special education, k-12 education, student voices

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5929 Correlation between Indoor and Outdoor Air

Authors: Jamal A. Radaideh, Ziad N. Shatnawi

Abstract:

Both indoor and outdoor air quality is investigated throughout residential areas of Al Hofuf city/ Eastern province of Saudi Arabia through a multi‐week multiple sites measurement and sampling survey. Concentration levels of five criteria air pollutants, including carbon dioxide (CO2), carbon monoxide (CO), nitrous dioxide (NO2), sulfur dioxide (SO2) and total volatile organic compounds (TVOC) were measured and analyzed during the study period from January to May 2014. For this survey paper, three different sites, roadside RS, urban UR, and rural RU were selected. Within each site type, six locations were assigned to carryout air quality measurements and to study varying indoor/outdoor air quality for each pollutant. Results indicate that a strong correlation between indoor and outdoor air exists. The I/O ratios for the considered criteria pollutants show that the strongest relationship between indoor and outdoor air is found by analyzing of carbon dioxide, CO2 (0.88), while the lowest is found by both NO2 and SO2 (0.7).

Keywords: criteria air pollutants, indoor/outdoor air pollution, indoor/outdoor ratio, Saudi Arabia

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5928 Application of Artificial Neural Network in Initiating Cleaning Of Photovoltaic Solar Panels

Authors: Mohamed Mokhtar, Mostafa F. Shaaban

Abstract:

Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

Procedia PDF Downloads 144
5927 An Analysis of Sequential Pattern Mining on Databases Using Approximate Sequential Patterns

Authors: J. Suneetha, Vijayalaxmi

Abstract:

Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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5926 Effect of Resveratrol and Ascorbic Acid on the Stability of Alfa-Tocopherol in Whey Protein Isolate Stabilized O/W Emulsions

Authors: Lei Wang, Yingzhou Ni, Amr M. Bakry, Hao Cheng, Li Liang

Abstract:

Food proteins have been widely used as carrier materials because of their multiple functional properties. In this study, alfa-tocopherol was encapsulated in the oil phase of an oil-in-water emulsion stabilized with whey protein isolate (WPI). The influence of WPI concentration and resveratrol or ascorbic acid on the decomposition of alfa-tocopherol in the emulsion during storage is discussed. Decomposition decreased as WPI concentrations increased. Decomposition was delayed at ascorbic acid/WPI molar ratios lower than 5 but was promoted at higher ratios. Resveratrol partitioned into the oil-water interface by binding to WPI and its cis-isomer is believed to have contributed most of the protective effect of this polyphenol. These results suggest the possibility of using the emulsifying and ligand-binging properties of WPI to produce carriers for simultaneous encapsulation of alfa-tocopherol and resveratrol in a single emulsion system.

Keywords: stability, alfa-tocopherol, resveratrol, whey protein isolate

Procedia PDF Downloads 528
5925 Temperature Control Improvement of Membrane Reactor

Authors: Pornsiri Kaewpradit, Chalisa Pourneaw

Abstract:

Temperature control improvement of a membrane reactor with exothermic and reversible esterification reaction is studied in this work. It is well known that a batch membrane reactor requires different control strategies from a continuous one due to the fact that it is operated dynamically. Due to the effect of the operating temperature, the suitable control scheme has to be designed based reliable predictive model to achieve a desired objective. In the study, the optimization framework has been preliminary formulated in order to determine an optimal temperature trajectory for maximizing a desired product. In model predictive control scheme, a set of predictive models have been initially developed corresponding to the possible operating points of the system. The multiple predictive control moves have been further calculated on-line using the developed models corresponding to current operating point. It is obviously seen in the simulation results that the temperature control has been improved compared to the performance obtained by the conventional predictive controller. Further robustness tests have also been investigated in this study.

Keywords: model predictive control, batch reactor, temperature control, membrane reactor

Procedia PDF Downloads 468
5924 Usability and Biometric Authentication of Electronic Voting System

Authors: Nighat Ayub, Masood Ahmad

Abstract:

In this paper, a new voting system is developed and its usability is evaluated. The main feature of this system is the biometric verification of the voter and then a few easy steps to cast a vote. As compared to existing systems available, e.g dual vote, the new system requires no training in advance. The security is achieved via multiple key concept (another part of this project). More than 100 student voters were participated in the election from University of Malakanad, Chakdara, PK. To achieve the reliability, the voters cast their votes in two ways, i.e. paper based and electronic based voting using our new system. The results of paper based and electronic voting system are compared and it is concluded that the voters cast their votes for the intended candidates on the electronic voting system. The voters were requested to fill a questionnaire and the results of the questionnaire are carefully analyzed. The results show that the new system proposed in this paper is more secure and usable than other systems.

Keywords: e-voting, security, usability, authentication

Procedia PDF Downloads 392
5923 Early Stage Suicide Ideation Detection Using Supervised Machine Learning and Neural Network Classifier

Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

Abstract:

In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

Procedia PDF Downloads 90
5922 A t-SNE and UMAP Based Neural Network Image Classification Algorithm

Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

Abstract:

Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

Procedia PDF Downloads 198
5921 Public Libraries as Social Spaces for Vulnerable Populations

Authors: Natalie Malone

Abstract:

This study explores the role of a public library in the creation of social spaces for vulnerable populations. The data stems from a longitudinal ethnographic study of the Anderson Library community, which included field notes, artifacts, and interview data. Thematic analysis revealed multiple meanings and thematic relationships within and among the data sources -interviews, field notes, and artifacts. Initial analysis suggests the Anderson Library serves as a space for vulnerable populations, with the sub-themes of fostering interpersonal communication to create a social space for children and fostering interpersonal communication to create a social space for parents and adults. These findings are important as they illustrate the potential of public libraries to serve as community empowering institutions.

Keywords: capital, immigrant families, public libraries, space, vulnerable

Procedia PDF Downloads 151
5920 College Students’ Multitasking and Its Causes

Authors: Huey-Wen Chou, Shuo-Heng Liang

Abstract:

This study focuses on studying college students’ multitasking with cellphones/laptops during lectures. In-class multitasking behavior is defined as the activities students engaged that are irrelevant to learning. This study aims to understand if students' learning engagement affects students' multitasking as well as to investigate the causes or motivations that contribute to the occurrence of multitasking behavior. Survey data were collected and analyzed by PLS method and multiple regression to test the research model and hypothesis. Major results include: 1. Students' multitasking motivation positively predicts students’ in-class multitasking. 2. Factors affecting multitasking in class, including efficiency, entertainment and social needs, significantly impact on multitasking. 3. Polychronic personality traits will positively predict students’ multitasking. 4. Students' classroom learning engagement negatively predicts multitasking. 5. Course attributes negatively predict student learning engagement and positively predict student multitasking.

Keywords: engagement, monochronic personality, multitasking, learning, personality traits

Procedia PDF Downloads 133
5919 Reactive Dyed Superhydrophobic Cotton Fabric Production by Sol-Gel Method

Authors: Kuddis Büyükakıllı

Abstract:

The pretreated and bleached mercerized cotton fabric was dyed with reactive Everzol Brilliant Yellow 4GR (C.I. Yellow 160) dyestuff. Superhydrophobicity is provided to white and reactive dyed fabrics by using a nanotechnological sol-gel method with tetraethoxysilane and fluorcarbon water repellent agents by the two-step method. The effect of coating on color yield, fastness and functional properties of fabric was investigated. It was observed that water drop contact angles were higher in colorless coated fabrics compared to colored coated fabrics, there was no significant color change in colored superhydrophobic fabric and high color fastness values. Although there are no significant color losses in the fabrics after multiple washing and dry cleaning processes, water drop contact angles are greatly reduced.

Keywords: fluorcarbon water repellent agent, colored cotton fabric, sol-gel, superhydrophobic

Procedia PDF Downloads 118
5918 Finite Element Analysis of High Performance Synchronous Reluctance Machines

Authors: T. Mohanarajah, J. Rizk, M. Nagrial, A. Hellany

Abstract:

This paper analyses numerous features of the synchronous Reluctance Motor (Syn-RM) and propose a rotor for high electrical torque, power factor & efficiency using Finite Element Method (FEM). A comprehensive analysis completed on solid rotor structure while the total thickness of the flux guide kept constant. A number of tests carried out for nine different studies to find out optimum location of the flux guide, the optimum location of multiple flux guides & optimum wall thickness between flux guides for high-performance reluctance machines. The results are concluded with the aid of FEM simulation results, the saliency ratio and machine characteristics (location, a number of barriers & wall width) analysed.

Keywords: electrical machines, finite element method, synchronous reluctance machines, variable reluctance machines

Procedia PDF Downloads 486
5917 Treatment Outcome Of Corneal Ulcers Using Levofloxacin Hydrate 1.5% Ophthalmic Solution And Adjuvant Oral Ciprofloxacin, A Treatment Strategy Applicable To Primary Healthcare

Authors: Celine Shi Ying Lee, Jong Jian Lee

Abstract:

Background: Infectious keratitis is one of the leading causes of blindness worldwide. Prompt treatment with effective medication will control the infection early, preventing corneal scarring and visual loss. fluoroquinolones ophthalmic medication is used because of its broad-spectrum properties, potency, good intraocular penetration, and low toxicity. The study aims to evaluate the treatment outcome of corneal ulcers using Levofloxacin 1.5% ophthalmic solution (LVFX) with adjuvant oral ciprofloxacin when indicated and apply this treatment strategy in primary health care as first-line treatment. Methods: Patients with infective corneal ulcer treated in an eye center were recruited. Inclusion criteria includes Corneal infection consistent with bacterial keratitis, single or multiple small corneal ulcers. Treatment regime: LVFX hourly for the first 2 days, 2 hourly from the 3rd day, and 3 hourly on the 5th day of review. Adjuvant oral ciprofloxacin 500mg BD was administered for 5 days if there were multiple corneal ulcers or when the location of the cornea ulcer was central or paracentral. Results: 47 subjects were recruited. There were 16 (34%) males and 31 (66%) females. 40 subjects (85%) were contact lens (CL) related to corneal ulcer, and 7 subjects (15%) were non-contact lens related. 42 subjects (89%) presented with one ulcer, of which 20 of them (48%) needed adjuvant therapy. 5 subjects presented with 2 or 3 ulcers, of which 3 needed adjuvant therapy. A total of 23 subjects (49%) was given adjuvant therapy (oral ciprofloxacin 500mg BD for 5 days).21 of them (91%) were CL related. All subjects recovered fully, and the average duration of treatment was 3.7 days, with 49% of the subjects resolved on the 3rd day, 38% on the 5thday of and 13% on the 7thday. All subjects showed symptoms of relief of pain, light-sensitivity, and redness on the 3rd day with full visual recovery post-treatment. No adverse drug reactions were recorded. Conclusion: Our treatment regime demonstrated good clinical outcome as first-line treatment for corneal ulcers. A corneal ulcer is a common eye condition in Singapore, mainly due to CL wear. Pseudomonas aeruginosa is the most frequent and potentially sight-threatening pathogen involved in CL related corneal ulcer. Coagulase-negative Staphylococci, Staphylococcus aureus, and Streptococcus Pneumoniae were seen in non-CL users. All these bacteria exhibit good sensitivity rates to ciprofloxacin and levofloxacin. It is therefore logical in our study to use LVFX Eyedrops and adjuvant ciprofloxacin oral antibiotics when indicated as first line treatment for most corneal ulcers. Our study of patients, both CL related and non-CL related, have shown good clinical response and full recovery using the above treatment strategy. There was also a full restoration of visual acuity in all the patients. Eye-trained primary Healthcare practitioners can consider adopting this treatment strategy as first line treatment in patients with corneal ulcers. This is relevant during the COVID pandemic, where hospitals are overwhelmed with patients and in regions with limited access to specialist eye care. This strategy would enable early treatment with better clinical outcome.

Keywords: corneal ulcer, levofloxacin hydrate, treatment strategy, ciprofloxacin

Procedia PDF Downloads 175
5916 Analysis of Long-Term Response of Seawater to Change in CO₂, Heavy Metals and Nutrients Concentrations

Authors: Igor Povar, Catherine Goyet

Abstract:

The seawater is subject to multiple external stressors (ES) including rising atmospheric CO2 and ocean acidification, global warming, atmospheric deposition of pollutants and eutrophication, which deeply alter its chemistry, often on a global scale and, in some cases, at the degree significantly exceeding that in the historical and recent geological verification. In ocean systems the micro- and macronutrients, heavy metals, phosphor- and nitrogen-containing components exist in different forms depending on the concentrations of various other species, organic matter, the types of minerals, the pH etc. The major limitation to assessing more strictly the ES to oceans, such as pollutants (atmospheric greenhouse gas, heavy metals, nutrients as nitrates and phosphates) is the lack of theoretical approach which could predict the ocean resistance to multiple external stressors. In order to assess the abovementioned ES, the research has applied and developed the buffer theory approach and theoretical expressions of the formal chemical thermodynamics to ocean systems, as heterogeneous aqueous systems. The thermodynamic expressions of complex chemical equilibria, involving acid-base, complex formation and mineral ones have been deduced. This thermodynamic approach utilizes thermodynamic relationships coupled with original mass balance constraints, where the solid phases are explicitly expressed. The ocean sensitivity to different external stressors and changes in driving factors are considered in terms of derived buffering capacities or buffer factors for heterogeneous systems. Our investigations have proved that the heterogeneous aqueous systems, as ocean and seas are, manifest their buffer properties towards all their components, not only to pH, as it has been known so far, for example in respect to carbon dioxide, carbonates, phosphates, Ca2+, Mg2+, heavy metal ions etc. The derived expressions make possible to attribute changes in chemical ocean composition to different pollutants. These expressions are also useful for improving the current atmosphere-ocean-marine biogeochemistry models. The major research questions, to which the research responds, are: (i.) What kind of contamination is the most harmful for Future Ocean? (ii.) What are chemical heterogeneous processes of the heavy metal release from sediments and minerals and its impact to the ocean buffer action? (iii.) What will be the long-term response of the coastal ocean to the oceanic uptake of anthropogenic pollutants? (iv.) How will change the ocean resistance in terms of future chemical complex processes and buffer capacities and its response to external (anthropogenic) perturbations? The ocean buffer capacities towards its main components are recommended as parameters that should be included in determining the most important ocean factors which define the response of ocean environment at the technogenic loads increasing. The deduced thermodynamic expressions are valid for any combination of chemical composition, or any of the species contributing to the total concentration, as independent state variable.

Keywords: atmospheric greenhouse gas, chemical thermodynamics, external stressors, pollutants, seawater

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5915 Seasonal Effect of Antibiotic Resistant Bacteria into the Environment from Treated Sewage Effluents

Authors: S. N. Al-Bahry, S. K. Al-Musharafi, I. Y. Mahmoud

Abstract:

Recycled treated sewage effluents (TSE) is used for agriculture, Public park irrigation and industrial purposes. TSE was found to play a major role in the distribution of antibiotic resistant bacteria into the environment. Fecal coliform and enterococci counts were significantly higher during summer compared to winter seasons. Oman has low annual rainfall with annual average temperature varied between 15-45oC. The main source of potable water is from seawater desalination. Resistance of the isolates to 10 antibiotics (Amikacin, Ampicillin, chloramphenicol, gentamycine, minocylin, nalidixicacid, neomycin, streptomycin, Tetracycline, Tobramycin, and Trimethoprim) was tested. Both fecal coliforms and enterococci were multiple resistant to 2-10 antibiotics. However, temperature variation during summer and winter did not affect resistance of the isolates to antibiotics. The significance of this investigation may be indicator to the environmental TSE pollution.

Keywords: antibiotic resistance, bacteria, environment, sewage treated effluent

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5914 Agriculture Yield Prediction Using Predictive Analytic Techniques

Authors: Nagini Sabbineni, Rajini T. V. Kanth, B. V. Kiranmayee

Abstract:

India’s economy primarily depends on agriculture yield growth and their allied agro industry products. The agriculture yield prediction is the toughest task for agricultural departments across the globe. The agriculture yield depends on various factors. Particularly countries like India, majority of agriculture growth depends on rain water, which is highly unpredictable. Agriculture growth depends on different parameters, namely Water, Nitrogen, Weather, Soil characteristics, Crop rotation, Soil moisture, Surface temperature and Rain water etc. In our paper, lot of Explorative Data Analysis is done and various predictive models were designed. Further various regression models like Linear, Multiple Linear, Non-linear models are tested for the effective prediction or the forecast of the agriculture yield for various crops in Andhra Pradesh and Telangana states.

Keywords: agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models

Procedia PDF Downloads 314
5913 Modelling of Multi-Agent Systems for the Scheduling of Multi-EV Charging from Power Limited Sources

Authors: Manan’Iarivo Rasolonjanahary, Chris Bingham, Nigel Schofield, Masoud Bazargan

Abstract:

This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.

Keywords: model predictive control, non-scheduled, power limited sources, scheduled and stop-start battery charging

Procedia PDF Downloads 158
5912 How Technology Import Improve the Enterprise's Innovation Capacity: The Mediating Role of Absorptive Capacity

Authors: Zhan Zheng-Qun, Li Min, Xie Yan

Abstract:

Technology plays a key role in determining productivity and economy development in a country. The process of enterprises’ innovation can be seen as a process of knowledge management including the process of knowledge attainment; acquisition and converting and integrating into new knowledge. This research analyzes the influence factors and mechanism of the independent innovation of high-tech enterprises in the year 1995-2013. The result shows that the technology import has a significant positive effect on the innovation capacity of enterprises. And the absorptive capacity, represented by the research outlay input and research staff input, has a significant positive effect on the innovation capacity of enterprises. Furthermore, the effect of technology import on the independent research capacity of high-tech enterprises is significantly positively affected by their absorptive capacity.

Keywords: technology import, innovation capacity, absorptive capacity, high-tech industry

Procedia PDF Downloads 283
5911 Concrete Mix Design Using Neural Network

Authors: Rama Shanker, Anil Kumar Sachan

Abstract:

Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Keywords: aggregate proportions, artificial neural network, concrete grade, concrete mix design

Procedia PDF Downloads 389
5910 Estimation of the Acute Toxicity of Halogenated Phenols Using Quantum Chemistry Descriptors

Authors: Khadidja Bellifa, Sidi Mohamed Mekelleche

Abstract:

Phenols and especially halogenated phenols represent a substantial part of the chemicals produced worldwide and are known as aquatic pollutants. Quantitative structure–toxicity relationship (QSTR) models are useful for understanding how chemical structure relates to the toxicity of chemicals. In the present study, the acute toxicities of 45 halogenated phenols to Tetrahymena Pyriformis are estimated using no cost semi-empirical quantum chemistry methods. QSTR models were established using the multiple linear regression technique and the predictive ability of the models was evaluated by the internal cross-validation, the Y-randomization and the external validation. Their structural chemical domain has been defined by the leverage approach. The results show that the best model is obtained with the AM1 method (R²= 0.91, R²CV= 0.90, SD= 0.20 for the training set and R²= 0.96, SD= 0.11 for the test set). Moreover, all the Tropsha’ criteria for a predictive QSTR model are verified.

Keywords: halogenated phenols, toxicity mechanism, hydrophobicity, electrophilicity index, quantitative stucture-toxicity relationships

Procedia PDF Downloads 301