Search results for: fish processing

Authors: Hamid Fallah

Abstract:

Asphalt is generally a mixture of stone materials with continuous granulation and a binder, which is usually bitumen. Asphalt is made in different shapes according to its use. The most familiar type of asphalt is hot asphalt or hot asphalt concrete. Stone materials usually make up more than 90% of the asphalt mixture. Therefore, stone materials have a significant impact on the quality of the resulting asphalt. According to the method of application and mixing, asphalt is divided into three categories: hot asphalt, protective asphalt, and cold asphalt. Cold mix asphalt is a mixture of stone materials and mixed bitumen or bitumen emulsion whose raw materials are mixed at ambient temperature. In some types of cold asphalt, the bitumen may be heated as necessary, but other materials are mixed with the bitumen without heating. Protective asphalts are used to make the roadbed impermeable, increase its abrasion and sliding resistance, and also temporarily improve the existing asphalt and concrete surfaces. This type of paving is very economical compared to hot asphalt due to the speed and ease of implementation and the limited need for asphalt machines and equipment. The present article, which is prepared in descriptive library form, introduces asphalt, its types, characteristics, and its application.

Keywords: asphalt, type of asphalt, asphalt concrete, sulfur concrete, bitumen in asphalt, sulfur, stone materials

Procedia PDF Downloads 69

Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

Procedia PDF Downloads 170

Authors: Bernabeo R. Alberto

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With the tremendous improvements in the processing power of computers, the possibilities of artificial intelligence will increasingly be used in aviation and make autonomous flights, preventive maintenance, ATM (Air Traffic Management) optimization, pilots, cabin crew, ground staff, and airport staff training possible in a cost-saving, less time-consuming and less polluting way. Through the use of artificial intelligence, we foresee an interviewing scenario where the interviewee will interact with the artificial intelligence tool to contextualize the character and the necessary information in a way that aligns reasonably with the character and the scenario. We are creating simulated scenarios connected with either an aviation incident or accident to enhance also the training of future accident/incident investigators integrating artificial intelligence and augmented reality tools. The project's goal is to improve the learning and teaching scenario through academic and professional expertise in aviation and in the artificial intelligence field. Thus, we intend to contribute to the needed high innovation capacity, skills, and training development and management of artificial intelligence, supported by appropriate regulations and attention to ethical problems.

Keywords: artificial intelligence, aviation accident, aviation incident, risk, safety

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Authors: Manisha Ohlan, Manju Dahiya

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The present study was conducted in Karnal, Rohtak, and Jhajjar districts of Haryana state, covering 360 respondents. Results showed that 42.78 percent of the respondents had above average knowledge at the preparation stage followed by 48.33 percent of the respondents who had high knowledge at the production stage, and 37.22 percent of the respondents had average knowledge at the processing stage regarding the usage of digital technologies. Nearly half of the respondents (47.50%) agreed with the usage of digital technologies, followed by strongly agreed (19.45%) and strongly disagreed (14.45%). A significant and positive relationship was found between independent variables and knowledge and of digital technologies at 5 percent level of significance. Therefore, the null hypothesis cannot be rejected. All the dependent variables, including knowledge and attitude, had a significant and positive relationship with z value at 5 percent level of significance, which showed that it is between -1.96 to +1.96; therefore, the data falls between the acceptance region, that’s why the null hypothesis is accepted.

Keywords: knowledge, attitude, digital technologies, significant, positive relationship

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Authors: F. Stephen Joe, V. Sathya Narayanan, V. R. Sanal Kumar

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A comprehensive review of the literature on photovoltaic cells has been carried out for exploring the better options for cost efficient technologies for future solar cell applications. Literature review reveals that the Bulk Heterojunction (BHJ) Polymer Solar cells offer special opportunities as renewable energy resources. It is evident from the previous studies that the device fabricated with TiOx layer shows better power conversion efficiency than that of the device without TiOx layer. In this paper, authors designed a controlled BHJ solar cell using a modified organic vapor spray deposition technique facilitated with a vertical-moving gun named as 'Stephen Joe Technique' for getting a desirable surface pattern over the substrate to improving its efficiency over the years for industrial applications. We comprehended that the efficient processing and the interface engineering of these solar cells could increase the efficiency up to 5-10 %.

Keywords: BHJ polymer solar cell, photovoltaic cell, solar cell, Stephen Joe technique

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Authors: Amara Rafik, Mostefa Belhadj Aissa

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Radar data is one of the many data sources used by ATM Air Traffic Management systems. These data come from air navigation radar antennas. These radars intercept signals emitted by the various aircraft crossing the controlled airspace and calculate the position of these aircraft and retransmit their positions to the Air Traffic Management System. For greater reliability, these radars are positioned in such a way as to allow their coverage areas to overlap. An aircraft will therefore be detected by at least one of these radars. However, the position coordinates of the same aircraft and sent by these different radars are not necessarily identical. Therefore, the ATM system must calculate a single position (radar track) which will ultimately be sent to the control position and displayed on the air traffic controller's monitor. There are several techniques for calculating the radar track. Furthermore, the geographical nature of the problem requires the use of a Geographic Information System (GIS), i.e. a geographical database on the one hand and geographical processing. The objective of this work is to propose a GIS for traffic simulation which reconstructs the evolution over time of aircraft positions from a multi-source radar data set and by applying these different techniques.

Keywords: ATM, GIS, radar data, simulation

Procedia PDF Downloads 118

Authors: Zzibu Mark Brian

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As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

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Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

Procedia PDF Downloads 259

Authors: M. Hilani, B. Nassih

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Phishing is one of the oldest and best known scams on the Internet. It can be defined as any type of telecommunications fraud that uses social engineering tricks to obtain confidential data from its victims. It’s a cybercrime aimed at stealing your sensitive information. Phishing is generally done via private email, so scammers impersonate large companies or other trusted entities to encourage victims to voluntarily provide information such as login credentials or, worse yet, credit card numbers. The COVID-19 theme is used by cybercriminals in multiple malicious campaigns like phishing. In this environment, messaging filtering solutions have become essential to protect devices that will now be used outside of the secure perimeter. Despite constantly updating methods to avoid these cyberattacks, the end result is currently insufficient. Many researchers are looking for optimal solutions to filter phishing emails, but we still need good results. In this work, we concentrated on solving the problem of detecting phishing emails using the different steps of NLP preprocessing, and we proposed and trained a model using one-dimensional CNN. Our study results show that our model obtained an accuracy of 99.99%, which demonstrates how well our model is working.

Keywords: phishing, e-mail, NLP preprocessing, CNN, e-mail filtering

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Authors: Liana Lortkipanidze, Nino Amirezashvili, Nino Javashvili

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The purpose of the grammatical dictionary is to provide information on the morphological and syntactic characteristics of the basic word in the dictionary entry. The electronic grammatical dictionaries are used as a tool of automated morphological analysis for texts processing. The Georgian Grammatical Dictionary should contain grammatical information for each word: part of speech, type of declension/conjugation, grammatical forms of the word (paradigm), alternative variants of basic word/lemma. In this paper, we present the system for compiling the Georgian Grammatical Dictionary automatically. We propose dictionary-based methods for extending grammatical lexicons. The input lexicon contains only a few number of words with identical grammatical features. The extension is based on similarity measures between features of words; more precisely, we add words to the extended lexicons, which are similar to those, which are already in the grammatical dictionary. Our dictionaries are corpora-based, and for the compiling, we introduce the method for lemmatization of unknown words, i.e., words of which neither full form nor lemma is in the grammatical dictionary.

Keywords: acquisition of lexicon, Georgian grammatical dictionary, lemmatization rules, morphological processor

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Authors: Ahmad Saadiq, Neeraj Sahu

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Sediment, which comprises of solid particles of mineral and organic material are transported by water. In river systems, the amount of sediment transported is controlled by both the transport capacity of the flow and the supply of sediment. The transport of sediment in rivers is important with respect to pollution, channel navigability, reservoir ageing, hydroelectric equipment longevity, fish habitat, river aesthetics and scientific interests. The sediment load transported in a river is a very complex hydrological phenomenon. Hence, sediment transport has attracted the attention of engineers from various aspects, and different methods have been used for its estimation. So, several experimental equations have been submitted by experts. Though the results of these methods have considerable differences with each other and with experimental observations, because the sediment measures have some limits, these equations can be used in estimating sediment load. In this present study, two black box models namely, an SRC (Sediment Rating Curve) and ANN (Artificial Neural Network) are used in the simulation of the suspended sediment load. The study is carried out for Seonath subbasin. Seonath is the biggest tributary of Mahanadi river, and it carries a vast amount of sediment. The data is collected for Jondhra hydrological observation station from India-WRIS (Water Resources Information System) and IMD (Indian Meteorological Department). These data include the discharge, sediment concentration and rainfall for 10 years. In this study, sediment load is estimated from the input parameters (discharge, rainfall, and past sediment) in various combination of simulations. A sediment rating curve used the water discharge to estimate the sediment concentration. This estimated sediment concentration is converted to sediment load. Likewise, for the application of these data in ANN, they are normalised first and then fed in various combinations to yield the sediment load. RMSE (root mean square error) and R² (coefficient of determination) between the observed load and the estimated load are used as evaluating criteria. For an ideal model, RMSE is zero and R² is 1. However, as the models used in this study are black box models, they don’t carry the exact representation of the factors which causes sedimentation. Hence, a model which gives the lowest RMSE and highest R² is the best model in this study. The lowest values of RMSE (based on normalised data) for sediment rating curve, feed forward back propagation, cascade forward back propagation and neural network fitting are 0.043425, 0.00679781, 0.0050089 and 0.0043727 respectively. The corresponding values of R² are 0.8258, 0.9941, 0.9968 and 0.9976. This implies that a neural network fitting model is superior to the other models used in this study. However, a drawback of neural network fitting is that it produces few negative estimates, which is not at all tolerable in the field of estimation of sediment load, and hence this model can’t be crowned as the best model among others, based on this study. A cascade forward back propagation produces results much closer to a neural network model and hence this model is the best model based on the present study.

Keywords: artificial neural network, Root mean squared error, sediment, sediment rating curve

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Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: R. B. B. Samantha Ramachandra, L. D. J. Upul Senarath, S. H. Padmal De Silva

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Dietary pattern largely differs over countries and even within a country, it shows cultural differences. The dietary pattern changes the energy consumption and micronutrient intake, directly affects the pregnancy outcome. The dietary diversity was used as an indirect measure to assess micronutrient adequacy for pregnant mothers in this study. The study was conducted as a baseline survey with the objective of designing an intervention to improve the dietary diversity of pregnant mothers in Sri Lanka. The survey was conducted in Kalutara district of Sri Lanka in 2015 among 769 pregnant mothers at different gestational ages. Dietary diversity questionnaire developed by Food and Agricultural Organization’s (FAO) Food and Nutrition technical Assistance (FANTA) II project, recommended for cross-country use with adaptations was used for data collection. Trained data collectors met pregnant mothers at field ante-natal clinic and questioned on last 24hr dietary recall with portion size and coded food items to identify the diversity. Pregnant mothers were identified from randomly selected 21 clusters of public health midwife areas. 81.5% mothers (n=627) in the sample had been registered at Public Health Midwife (PHM) before 8 weeks of gestation. 24.4% of mothers were with low starting BMI and 22.7% mothers were with high starting BMI. 47.6% (n=388) mothers had abstained from at least one food item during the pregnancy. The food group with the highest consumption was rice (98.4%) followed by sugar (89.9%). 76.1% mothers had consumed milk, 73% consumed fish and sea foods. Consumption of green leaves was 52% and Vit A rich foods consumed only by 49% mothers. Animal organs, flesh meat and egg all showed low prevalence as 4.7%, 21.6% and 20% respectively. Consumption of locally grown roots, nut, legumes all showed very low prevalence. Consumption of 6 or more food groups was considered as good dietary diversity (DD), 4 to 5 food groups as moderate diversity and 3 or less food groups as poor diversity by FAO FANTA II project. 42.1% mothers demonstrated good DD while another 42.1% recorded moderate diversity. Working mothers showed better DD (51.6%, n=82/159) compared to housewives in the sample (chi = 10.656a,. df=2, p=0.005). The good DD showed gradual improvement from 43.1% to 55.5% along the poorest to richest wealth index (Chi=48.045, df=8 and p=0.000). DD showed significant association with the ethnicity and Moors showed the lowest DD. DD showed no association with the home gardening even though where better diversity expected among those who have home gardening (p=0.548). Sri Lanka is a country where many food items can be grown in the garden and semi-urban setting have adequate space for gardening. Many Sri Lankan mothers do not add homegrown items in their meal. At the same time, their consumption of animal food shows low prevalence. The DD of most of the mothers being either moderate or low (58%) may result from inadequate micro nutrient intake during pregnancy. It is recommended that adding green leaves, locally grown vegetables, roots, nuts and legumes can help increasing the DD of Sri Lankan mothers at low cost.

Keywords: dietary diversity, pregnant mothers, micro-nutrient, food groups

Procedia PDF Downloads 164

Authors: S. Mohamed Rabeek, Mi Kyoung Park, M. Annamalai Arasu

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This paper presents a design of a wireless read out system for tracking the frequency shift of the polymer coated piezoelectric micro electromechanical resonator due to gas absorption. The measure of this frequency shift indicates the percentage of a particular gas the sensor is exposed to. It is measured using an oscillator and an FPGA based frequency counter by employing the resonator as a frequency determining element in the oscillator. This system consists of a Gas Sensing Wireless Readout (GSWR) and an USB Wireless Transceiver (UWT). GSWR consists of an oscillator based on a trans-impedance sustaining amplifier, an FPGA based frequency readout, a sub 1GHz wireless transceiver and a micro controller. UWT can be plugged into the computer via USB port and function as a wireless module to transfer gas sensor data from GSWR to the computer through its USB port. GUI program running on the computer periodically polls for sensor data through UWT - GSWR wireless link, the response from GSWR is logged in a file for post processing as well as displayed on screen.

Keywords: gas sensor, GSWR, micromechanical system, UWT, volatile emissions

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Authors: Tahira Pirzada, Zahra Ashrafi, Saad Khan

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We present a facile and sustainable solid templating approach to fabricate highly porous, flexible and superhydrophobic aerogels of composite nanofibers of cellulose diacetate and silica which are produced through sol gel electrospinning. Scanning electron microscopy, contact angle measurement, and attenuated total reflection-Fourier transform infrared spectrometry are used to understand the structural features of the resultant aerogels while thermogravimetric analysis and differential scanning calorimetry demonstrate their thermal stability. These aerogels exhibit a self-supportive three-dimensional network abundant in large secondary pores surrounded by primary pores resulting in a highly porous structure. Thermal crosslinking of the aerogels has further stabilized their structure and flexibility without compromising on the porosity. Ease of processing, thermal stability, high porosity and oleophilic nature of these aerogels make them promising candidate for a wide variety of applications including acoustic and thermal insulation and oil and water separation.

Keywords: hybrid aerogels, sol-gel electrospinning, oil-water separation, nanofibers

Procedia PDF Downloads 158

Authors: Yogendra Sisodia

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Researchers are becoming more interested in extracting useful information from legal documents thanks to the development of large-scale language models in natural language processing (NLP), and deep learning has accelerated the creation of powerful text mining models. Legal fields like contracts benefit greatly from semantic text search since it makes it quick and easy to find related clauses. After collecting sentence embeddings, it is relatively simple to locate sentences with a comparable meaning throughout the entire legal corpus. The author of this research investigated two pre-trained language models for this task: MiniLM and Roberta, and further fine-tuned them on Legal Contracts. The author used Multiple Negative Ranking Loss for the creation of sentence transformers. The fine-tuned language models and sentence transformers showed promising results.

Keywords: legal contracts, multiple negative ranking loss, natural language inference, sentence transformers, semantic textual similarity

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Authors: Malek Bendjaballah, Hacina Saidi, Sarra Hamidoud

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The aim of this study is to model and optimize the performance of a new electrocoagulation (E.C) process for the treatment of wastewater as well as the energy consumption in order to extrapolate it to the industrial scale. Through judicious application of an experimental design (DOE), it has been possible to evaluate the individual effects and interactions that have a significant influence on both objective functions (maximizing efficiency and minimizing energy consumption) by using aluminum electrodes as sacrificial anode. Preliminary experiments have shown that the pH of the medium, the applied potential and the treatment time with E.C are the main parameters. A factorial design 33 has been adopted to model performance and energy consumption. Under optimal conditions, the pollution reduction efficiency is 93%, combined with a minimum energy consumption of 2.60.10-3 kWh / mg-COD. The potential or current applied and the processing time and their interaction were the most influential parameters in the mathematical models obtained. The results of the modeling were also correlated with the experimental ones. The results offer promising opportunities to develop a clean process and inexpensive technology to eliminate or reduce wastewater,

Keywords: electrocoagulation, green process, experimental design, optimization

Procedia PDF Downloads 97

Authors: Retno Supriyanti, Best Leader Nababan, Yogi Ramadhani, Wahyu Siswandari

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Blood cell morphology is an important parameter in a hematology test. Currently, in developing countries, a lot of hematology is done manually, either by physicians or laboratory staff. According to the limitation of the human eye, examination based on manual method will result in a lower precision and accuracy. In addition, the hematology test by manual will further complicate the diagnosis in some areas that do not have competent medical personnel. This research aims to develop a simple tool in the detection of blood cell morphology-based computer. In this paper, we focus on the detection of the outer contour of leukocytes. The results show that the system that we developed is promising for detecting blood cell morphology automatically. It is expected, by implementing this method, the problem of accuracy, precision and limitations of the medical staff can be solved.

Keywords: morphology operation, developing countries, hematology test, limitation of medical personnel

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Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

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Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

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Authors: M. Fadlallah, G. Ghibaudo, C. G. Theodorou

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The dynamic variation in memory devices such as the Static Random Access Memory can give errors in read or write operations. In this paper, the effect of low-frequency and random telegraph noise on the dynamic variation of one SRAM cell is detailed. The effect on circuit noise, speed, and length of time of processing is examined, using the Supply Read Retention Voltage and the Read Static Noise Margin. New test run methods are also developed. The obtained results simulation shows the importance of noise caused by dynamic variation, and the impact of Random Telegraph noise on SRAM variability is examined by evaluating the statistical distributions of Random Telegraph noise amplitude in the pull-up, pull-down. The threshold voltage mismatch between neighboring cell transistors due to intrinsic fluctuations typically contributes to larger reductions in static noise margin. Also the contribution of each of the SRAM transistor to total dynamic variation has been identified.

Keywords: low-frequency noise, random telegraph noise, dynamic variation, SRRV

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Authors: Assefa Mitike Janko, Gosa Alemu

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The review of supply and marketing of floriculture in Ethiopia was conducted to analyses the production potential and to know the marketing share of the country. The data was collected from secondary and primary. Ethiopia has been operating in the floriculture industry for over 20 years. As is the case in many developing countries, the major export items of Ethiopia are dominated by few agricultural products that earn very small amounts in the international market. Moreover, most of the exports are destined to only few countries. Given the highly capital intensive nature of production and processing, rose farming is not a smallholder activity. It is also important to note the extremely tightly controlled time dimension of the logistics process, given the product attributes desired and the fragility and perishability of the roses. Another characteristic of the Ethiopian floriculture sector is the lack of domestically produced inputs that flower producers can access. The export volume and value of cut-flowers accounts for a small proportion of the total exports of Ethiopia. In recent years the sector is showing improvements in terms of the quality and quantity of exports to the international market.

Keywords: roses, production, value chain, floriculture, supply

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Authors: Sotiris Papantonopoulos, Marianna Bortziou

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This study aimed at developing a new package of saffron using emotional design and specifically the Kansei Engineering method. Kansei Engineering is a proactive product development methodology, which aims to improve the product development process and to translate consumers' feelings and image of a product into design elements. A survey was conducted with two major purposes: (1) to determine the target group of saffron use and to collect information about the adequacy of the product’s promotion and the importance of its packaging, (2) to collect the most important properties of a package according to consumers and to evaluate the existing saffron packages according to these properties (benchmarking). The interaction with the general public conducted by the distribution of online questionnaires and personal interviews as well as the statistical analysis of the results were performed using the SPSS software. The results of the survey were used in all stages of Kansei Engineering. Based on the results, a new saffron package was designed by using various designing and image processing software. This improved package is expected to achieve a better promotion and increased sales of the product.

Keywords: design, emotional design, Kansei Engineering, packaging, saffron

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Authors: Ratna Siti Khodijah, Mirzam Abdurrachman

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Gold is recovered from gold ores. Within the ores, there are not only gold but also several types of precious metals. Copper, silver, and platinum group elements (ruthenium, rhodium, palladium, rhenium, osmium, and iridium) are metals commonly found in the ores. These metals combine to form an ore because they have the same properties. It is due to their position in periodic-system-of-elements are near to gold. However, the presence of mercury in every gold ore has not been mentioned, even though it is located right next to gold in the periodic-system-of-elements and they are located in the same block, d-block. Thus, it is possible that mercury is contained in the ores. Moreover, the elements of the same group with mercury—zinc and cadmium—sometimes can be found in the ores. It is suspected that mercury can not be detected because the processing of gold ores usually using fire assay method. Before the ores melting, mercury would evaporate because it has the lowest boiling point of all precious metal in the ores. Therefore, it suggested doing research on the presence of mercury in gold ores by CVAAS method. The results of this study would obtain the amount of mercury in gold ores that should be purified. So it can be produced economically if possible.

Keywords: boiling point, d-block, fire assay, precious metal

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Authors: Muhammad Talal Asghar

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The lift-off technique of the photoresist for metal patterning in integrated circuit (IC) packaging has been widely utilized in the field of microelectromechanical systems and semiconductor component manufacturing. The main advantage lies in cost-saving, reduction in complexity, and maturity of the process. The selection of photoresist depends upon many factors such as cost, the thickness of the resist, comfortable and valuable parameters extraction. In the present study, an extremely cheap dry film photoresist E8015 of thickness 38-micrometer is processed for the first time for edge profiling, according to the author's best knowledge. Successful extraction of the helpful parameter range for resist processing is performed. An undercut angle of 66 to 73 degrees is realized by parameter variation like exposure energy and development time. Finally, 10-micrometer thick metallic multilayer aluminum nickel is lifted off on the plain silicon wafer. Possible applications lie in controlled self-propagating reactions within structured metallic multilayer that may be utilized for IC packaging in the future.

Keywords: lift-off, IC packaging, photoresist, multilayer

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Authors: Selcuk Aslan, Dervis Karaboga, Celal Ozturk

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Artificial Bee Colony (ABC) algorithm is one of the most successful swarm intelligence based metaheuristics. It has been applied to a number of constrained or unconstrained numerical and combinatorial optimization problems. In this paper, we presented a parallelized version of ABC algorithm by adapting employed and onlooker bee phases to the Compute Unified Device Architecture (CUDA) platform which is a graphical processing unit (GPU) programming environment by NVIDIA. The execution speed and obtained results of the proposed approach and sequential version of ABC algorithm are compared on functions that are typically used as benchmarks for optimization algorithms. Tests on standard benchmark functions with different colony size and number of parameters showed that proposed parallelization approach for ABC algorithm decreases the execution time consumed by the employed and onlooker bee phases in total and achieved similar or better quality of the results compared to the standard sequential implementation of the ABC algorithm.

Keywords: Artificial Bee Colony algorithm, GPU computing, swarm intelligence, parallelization

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Authors: Helga Heylen

Abstract:

With dogs saving wildlife in New Zealand since 1890 and governments in Africa, Australia and Canada trusting them to give the best results, Conservation Dogs Ireland want to introduce more detection dogs to protect Europe's native wildlife. Conservation detection dogs are fast, portable and endlessly trainable. They are a cost-effective, highly sensitive and non-invasive way to detect protected and invasive species and wildlife disease. Conservation dogs find targets up to 40 times faster than any other method. They give results instantly, with near-perfect accuracy. They can search for multiple targets simultaneously, with no reduction in efficacy The European Red List indicates the decline in biodiversity has been most rapid in the past 50 years, and the risk of extinction never higher. Just two examples of major threats dogs are trained to tackle are: (I)Japanese Knotweed (Fallopia Japonica), not only a serious threat to ecosystems, crops, structures like bridges and roads - it can wipe out the entire value of a house. The property industry and homeowners are only just waking up to the full extent of the nightmare. When those working in construction on the roads move topsoil with a trace of Japanese Knotweed, it suffices to start a new colony. Japanese Knotweed grows up to 7cm a day. It can stay dormant and resprout after 20 years. In the UK, the cost of removing Japanese Knotweed from the London Olympic site in 2012 was around £70m (€83m). UK banks already no longer lend on a house that has Japanese Knotweed on-site. Legally, landowners are now obliged to excavate Japanese Knotweed and have it removed to a landfill. More and more, we see Japanese Knotweed grow where a new house has been constructed, and topsoil has been brought in. Conservation dogs are trained to detect small fragments of any part of the plant on sites and in topsoil. (II)Zebra mussels (Dreissena Polymorpha) are a threat to many waterways in the world. They colonize rivers, canals, docks, lakes, reservoirs, water pipes and cooling systems. They live up to 3 years and will release up to one million eggs each year. Zebra mussels attach to surfaces like rocks, anchors, boat hulls, intake pipes and boat engines. They cause changes in nutrient cycles, reduction of plankton and increased plant growth around lake edges, leading to the decline of Europe's native mussel and fish populations. There is no solution, only costly measures to keep it at bay. With many interconnected networks of waterways, they have spread uncontrollably. Conservation detection dogs detect the Zebra mussel from its early larvae stage, which is still invisible to the human eye. Detection dogs are more thorough and cost-effective than any other conservation method, and will greatly complement and speed up the work of biologists, surveyors, developers, ecologists and researchers.

Keywords: native biodiversity, conservation detection dogs, invasive species, Japanese Knotweed, zebra mussel

Procedia PDF Downloads 196

Authors: A. Vani, M. N. Mamatha

Abstract:

Visual signal processing in human beings occurs in the occipital lobe of the brain. The signals that are generated in the brain are universal for all the human beings and they are called Visual Evoked Potential (VEP). Generally, the visually impaired people lose sight because of severe damage to only the eyes natural photo sensors, but the occipital lobe will still be functioning. In this paper, a technique of artificially generating VEP is proposed to enhance the visual ability of the subject. The system uses the electrical photoreceptors to capture image, process the image, to detect and recognize the subject or object. This voltage is further processed and can transmit wirelessly to a BIOMEMS implanted into occipital lobe of the patient’s brain. The proposed BIOMEMS consists of array of electrodes that generate the neuron potential which is similar to VEP of normal people. Thus, the neurons get the visual data from the BioMEMS which helps in generating partial vision or sight for the visually challenged patient. 

Keywords: BioMEMS, neuro-prosthetic, openvibe, visual evoked potential

Procedia PDF Downloads 315

Authors: Jiwon Lee, Chanho Jung, Si-Hwan Jang, Kyung-Ill Kim, Sanghyun Joo, Wook-Ho Son

Abstract:

Since the advances in digital imaging technologies have led to development of high quality digital devices, there are a lot of illegal copies of copyrighted video content on the internet. Thus, we propose a high-quality (HQ) video watermarking scheme that can prevent these illegal copies from spreading out. The proposed scheme is applied spatial and temporal gradient methods to improve the fidelity and detection performance. Also, the scheme duplicates the watermark signal temporally to alleviate the signal reduction caused by geometric and signal-processing distortions. Experimental results show that the proposed scheme achieves better performance than previously proposed schemes and it has high fidelity. The proposed scheme can be used in broadcast monitoring or traitor tracking applications which need fast detection process to prevent illegally recorded video content from spreading out.

Keywords: editing prevention technique, gradient method, luminance change, video watermarking

Procedia PDF Downloads 456

Authors: Sara Sahraoui

Abstract:

This research studied the effect of Alzheimer's disease (AD) on language information processing in subjects with Alzheimer’s disease (AD) who were bilingual (French and dialectical Arabic). The results show a disorder of certain semantic aspects of their mother tongue (L1). On the other hand, grammatical levels appeared to be relatively unaffected in oral speech in L1 but were disturbed in the second language (L2). In consequence, we constructed a cognitive-language stimulation protocol for bilingual patients (PSCLAB) to respond to this disorder. The efficacy of this protocol in terms of rehabilitation was assessed in 30 such patients through discourse analysis carried out before and after initiating the protocol. The results show that cognitive/language training using the PSCLAB appears to improve the language behaviour of bilingual patients with AD. However, this survey study aims to verify the satisfaction of patients’ relatives with the results of cognitive language training by PSCLAB. We developed a brief instrument to measure the satisfaction of family members. The results report that the patient's relatives are satisfied with the results of cognitive training by PSCLAB.

Keywords: satisfaction, Alzheimer's disease, rehabilitation, levels language

Procedia PDF Downloads 79

Authors: A. Tuna, Y. Okumuş, A. T. Seyhan, H. Çelebi

Abstract:

In this study, microfluidization was considered a promising approach to breaking up of carbonized chicken feather fibers (CCFFs) flocs to synthesizing epoxy suspensions containing (1 wt. %) CCFFs. For comparison, CCFF was also treated using sonication. The energy consumed to break up CCFFs in the ethanol was the same for both processes. CCFFs were found to be dispersed in ethanol in a significantly shorter time with the high shear processor. The CCFFs treated by both sonication and microfluidization were dispersed in epoxy by sonication. SEM examination revealed that CCFFs were broken up into smaller pieces using the high shear processor while being not agglomerated. Further, DSC, TMA, and DMA were systematically used to measure thermal properties of the resulting composites. A significant improvement was observed in the composites including CCFFs treated with microfluidization.

Keywords: carbonized chicken feather fiber (CCFF), modulated differential scanning calorimetry (MDSC), modulated thermomechanical analysis (MTMA), thermal properties

Procedia PDF Downloads 316