Search results for: automated document processing

Authors: Jürgen Fleischer, Woramon Pangboonyanon, Dominic Lesage

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Non-metallic lightweight materials such as fiber reinforced plastics (FRP) become very significant at present. Prepregs e.g. SMC and unidirectional tape (UD-tape) are one of raw materials used to produce FRP. This study concerns with the manufacturing steps of handling and preforming of this UD-SMC and focuses on the investigation of gripper characteristics regarding gripping forces in normal and lateral direction, in order to identify suitable operating pressures for a secure gripping operation. A reliable handling and preforming operation results in a higher adding value of the overall process chain. As a result, the suitable operating pressures depending on travelling direction for each material type could be shown. Moreover, system boundary conditions regarding allowable pulling force in normal and lateral directions during preforming could be measured.

Keywords: continuous-discontinuous fiber reinforced plastics, UD-SMC-prepreg, handling, preforming, prepregs, sheet moulding compounds, surface suction gripper

Procedia PDF Downloads 210

Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

Procedia PDF Downloads 162

Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

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In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

Procedia PDF Downloads 375

Authors: Tanvi P. Patel, Warish D. Patel

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Association rule mining forms the core of data mining and it is termed as one of the well-known methodologies of data mining. Objectives of mining is to find interesting correlations, frequent patterns, associations or casual structures among sets of items in the transaction databases or other data repositories. Hence, association rule mining is imperative to mine patterns and then generate rules from these obtained patterns. For efficient targeted query processing, finding frequent patterns and itemset mining, there is an efficient way to generate an itemset tree structure named Memory Efficient Itemset Tree. Memory efficient IT is efficient for storing itemsets, but takes more time as compare to traditional IT. The proposed strategy generates maximal frequent itemsets from memory efficient itemset tree by using levelwise pruning. For that firstly pre-pruning of items based on minimum support count is carried out followed by itemset tree reconstruction. By having maximal frequent itemsets, less number of patterns are generated as well as tree size is also reduced as compared to MEIT. Therefore, an enhanced approach of memory efficient IT proposed here, helps to optimize main memory overhead as well as reduce processing time.

Keywords: association rule mining, itemset mining, itemset tree, meit, maximal frequent pattern

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Authors: Honorio Salmeron Valdivieso, Andy Keane, David Toal

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In the area of mechanical reverse engineering, processes often encounter difficulties capturing small, highly localized surface information. This could be the case if a physical turbine was 3D scanned for lifecycle management or robust design purposes, with interest on eroded areas or scratched coating. The limitation partly is due to insufficient automated frameworks for handling -localized - surface information during the reverse engineering pipeline. We have developed a tool for blending surface patches with arbitrary irregularities into a base body (e.g. a CAD solid). The approach aims to transfer small surface features while preserving their shape and relative placement by using a multi-resolution scheme and rigid deformations. Automating this process enables the inclusion of outsourced surface information in CAD models, including samples prepared in mesh handling software, or raw scan information discarded in the early stages of reverse engineering reconstruction.

Keywords: application lifecycle management, multiresolution deformation, reverse engineering, robust design, surface blending

Procedia PDF Downloads 130

Authors: Juzhong Tan, William Kerr

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Roasting is one critical procedure in chocolate processing, where special favors are developed, moisture content is decreased, and better processing properties are developed. Therefore, determination of roasting degree of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products, and it also decides the commercial value of cocoa beans collected from cocoa farmers. The roasting degree of cocoa beans currently relies on human specialists, who sometimes are biased, and chemical analysis, which take long time and are inaccessible to many manufacturers and farmers. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was used to detecting the gas generated by cocoa beans with a different roasting degree (0min, 20min, 30min, and 40min) and the signals collected by gas sensors were used to train a three-layers ANN. Chemical analysis of the graded beans was operated by traditional GC-MS system and the contents of volatile chemical compounds were used to train another ANN as a reference to electronic nosed signals trained ANN. Both trained ANN were used to predict cocoa beans with a different roasting degree for validation. The best accuracy of grading achieved by electronic nose signals trained ANN (using signals from TGS 813 826 820 880 830 2620 2602 2610) turned out to be 96.7%, however, the GC trained ANN got the accuracy of 83.8%.

Keywords: artificial neutron network, cocoa bean, electronic nose, roasting

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Authors: Bharat P. Modi, Jayesh M. Patel

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Mobile Internet is acting as a major source of data. As the number of web pages continues to grow the Mobile web provides the data miners with just the right ingredients for extracting information. In order to cater to this growing need, a special term called Mobile Web mining was coined. Mobile Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web Usage mining deals with understanding the behavior of users by making use of Mobile Web Access Logs that are generated on the server while the user is accessing the website. A Web access log comprises of various entries like the name of the user, his IP address, a number of bytes transferred time-stamp etc. A variety of Log Analyzer tools exists which help in analyzing various things like users navigational pattern, the part of the website the users are mostly interested in etc. The present paper makes use of such log analyzer tool called Mobile Web Log Expert for ascertaining the behavior of users who access an astrology website. It also provides a comparative study between a few log analyzer tools available.

Keywords: mobile web access logs, web usage mining, web server, log analyzer

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Authors: Maria Tagarelli De Monte

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Since its formal recognition in 2021, Italian Sign Language (LIS) and interpreters’ education has become a topic for higher education in Italian universities. In April 2022, Italian universities have been invited to present their proposals to create sign language courses for interpreters’ training for both LIS and tactile LIS. As a result, a few universities have presented a three-year course leading candidate students from the introductory level to interpreters. In such a context, there is an open debate not only on the fact that three years may not be enough to prepare skillful interpreters but also on the need to refer to international standards in the definition of the training path to follow. Among these, are the Common European Framework of Reference (CEFR) for languages and Dublin’s descriptors. This contribution will discuss the potentials and the challenges given by LIS training in academic settings, by comparing traditional studies to the requests coming from universities. Particular attention will be given to the use of CEFR as a reference document for the Italian Sign Language Curriculum. Its use has given me the chance to reflect on how LIS can be taught in higher education, and the adaptations that need to be addressed to respect the visual-gestural nature of sign language and the formal requirements of academic settings.

Keywords: Italian sign language, higher education, sign language curriculum, interpreters education, CEFR

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Authors: Maria Joseph Israel, Ahmed Amer

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Our work aims to broaden the application of provenance technology beyond its traditional domains of scientific workflow management and database systems by offering a general provenance framework to capture richer and extensible metadata in unstructured textual data sources such as literary texts, commentaries, translations, and digital humanities. Specifically, we demonstrate the feasibility of capturing and representing expressive provenance metadata, including more of the context for citing scholarly works (e.g., the authors’ explicit or inferred intentions at the time of developing his/her research content for publication), while also supporting subsequent augmentation with similar additional metadata (by third parties, be they human or automated). To better capture the nature and types of possible citations, in our proposed provenance scheme metaScribe, we extend standard provenance conceptual models to form our proposed provCite ontology. This provides a conceptual framework which can accurately capture and describe more of the functional and rhetorical properties of a citation than can be achieved with any current models.

Keywords: knowledge representation, provenance architecture, ontology, metadata, bibliographic citation, semantic web annotation

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Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: Hoyeon Park, Yunhwan Keon, Kyoung-Jae Kim

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Location Based Social Network services (LBSNs) is a new term that combines location based service and social network service (SNS). Unlike traditional SNS, LBSNs emphasizes empirical elements in the user's actual physical location. Point-of-Interest (POI) is the most important factor to implement LBSNs recommendation system. POI information is the most popular spot in the area. In this study, we would like to recommend POI to users in a specific area through recommendation system using collaborative filtering. The process is as follows: first, we will use different data sets based on Seoul and New York to find interesting results on human behavior. Secondly, based on the location-based activity information obtained from the personalized LBSNs, we have devised a new rating that defines the user's preference for the area. Finally, we have developed an automated rating algorithm from massive raw data using distributed systems to reduce advertising costs of LBSNs.

Keywords: location-based social network services, point-of-interest, recommender systems, business analytics

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Authors: Gulmira Zhakupova, Tamara Tultabayeva, Aknur Muldasheva, Assem Sagandyk

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The development of technology and production of products with increased biological value based on the use of natural food raw materials are important tasks in the policy of the food market of the Republic of Kazakhstan. For Kazakhstan, livestock farming, in particular sheep farming, is the most ancient and developed industry and way of life. The history of the Kazakh people is largely connected with this type of agricultural production, with established traditions using dairy products from sheep's milk. Therefore, the development of new technologies from sheep’s milk remains relevant. In addition, one of the most promising areas for the development of food technology for therapeutic and prophylactic purposes is sheep milk products as a source of protein, immunoglobulins, minerals, vitamins, and other biologically active compounds. This article presents the results of research on the study of milk processing technology. The objective of the study is to study the possibilities of processing sheep milk and its role in human nutrition, as well as the results of research to improve the technology of sheep milk products. The studies were carried out on the basis of sanitary and hygienic requirements for dairy products in accordance with the following test methods. To perform microbiological analysis, we used the method for identifying Salmonella bacteria (Horizontal method for identifying, counting, and serotyping Salmonella) in a certain mass or volume of product. Nutritional value is a complex of properties of food products that meet human physiological needs for energy and basic nutrients. The protein mass fraction was determined by the Kjeldahl method. This method is based on the mineralization of a milk sample with concentrated sulfuric acid in the presence of an oxidizing agent, an inert salt - potassium sulfate, and a catalyst - copper sulfate. In this case, the amino groups of the protein are converted into ammonium sulfate dissolved in sulfuric acid. The vitamin composition was determined by HPLC. To determine the content of mineral substances in the studied samples, the method of atomic absorption spectrophotometry was used. The study identified the technological parameters of sheep milk products and determined the prospects for researching sheep milk products. Microbiological studies were used to determine the safety of the study product. According to the results of the microbiological analysis, no deviations from the norm were identified. This means high safety of the products under study. In terms of nutritional value, the resulting products are high in protein. Data on the positive content of amino acids were also obtained. The results obtained will be used in the food industry and will serve as recommendations for manufacturers.

Keywords: dairy, milk processing, nutrition, colostrum

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Authors: Fuad M. Alkoot

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Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

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Authors: Emmanuel Havugimana

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If there is a natural phenomenon that could endanger the lives of countless people in Central Africa, it is the possible eruption of the Nyiragongo Volcano. This one is 3,470 m above sea level and has a summit formed by a crater 1.2 km in diameter. Its composite is made up of many layers of lava and tephras from the Great Rift Valley located in the Democratic Republic of Congo. It is also located in the region of the volcanic mountains near the city of Goma in Congo and near the city of Gisenyi in Rwanda. Nyiragongo represents an imminent danger considering that its magma has a very low silica content and is thus quite fluid. Its slopes are also high and slippery, and the lava takes advantage of this to flow up to 100 km. Lately, its eruptions took place in May 2002, resumed in May 2021, and they were faster than before. The volcano remains active even today. All these factors make it among the most dangerous volcanoes in the world. On top of that, no one knows when the next eruption will take place, especially since it can also occur without any warning signs. Unfortunately, volcanological monitoring services in Congo are non-existent, and that is why this document concludes that Nyiragongo could if nothing is done in this regard, ravage the two neighboring towns: Goma in Congo and Gisenyi in Rwanda. It also proposes solutions that may contribute to preventing the expected dangers in this context.

Keywords: Nyiragongo, volcanic eruption, precursor signs, active volcano

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Authors: D. Shakirah Shukor, A. Aminudin, Hashim U. A., Waziralilah N. Fathiah, T. Vikneshvaran

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The interior noise control is essential to be explored due to the interior acoustic analysis is significant in the systems such as automobiles, aircraft, air-handling system and diesel engine exhausts system. In this research, experimental work was undertaken for canceling an active noise in the rectangular enclosure. The rectangular enclosure was fabricated with multiple speakers and microphones inside the enclosure. A software program using digital signal processing is implemented to evaluate the proposed method. Experimental work was conducted to obtain the acoustic behavior and characteristics of the rectangular enclosure and noise cancellation based on active noise control in low-frequency range. Noise is generated by using multispeaker inside the enclosure and microphones are used for noise measurements. The technique for noise cancellation relies on the principle of destructive interference between two sound fields in the rectangular enclosure. One field is generated by the original or primary sound source, the other by a secondary sound source set up to interfere with, and cancel, that unwanted primary sound. At the end of this research, the result of output noise before and after cancellation are presented and discussed. On the basis of the findings presented in this research, an active noise cancellation in the rectangular enclosure is worth exploring in order to improve the noise control technologies.

Keywords: active noise control, digital signal processing, noise cancellation, rectangular enclosure

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Authors: Dimpi A. Patel, Pankaj Raina, Ramesh Chinnasamy, Sunetro Ghosal

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The herpetological fauna of Ladakh has been surveyed few times till 1999. In 2019, a rapid survey to document current herpetofaunal composition was undertaken in which a total of 6 species belonging to 2 orders and five families along with their altitudinal ranges were recorded. We present a revised checklist of reptiles found in Ladakh trans Himalayas based on historical records and recent field surveys. Records for erroneously reported species in literature are discussed and recommended for removal from the list from this region. For several species, new elevation range records have been recorded. This paper contributes to the present status of the richness of reptiles and amphibians in the region by documenting the composition and ecological distribution of the herpetofauna of unstudied sites. Species-specific temperature and humidity regimes were also recorded during the survey periods. Our study creates baseline information for future ecological and behavioral studies on the herpetofauna of the region by providing habitat preferences and distribution in detail.

Keywords: amphibians, distribution, diversity, reptiles, trans-Himalaya

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Authors: Anirudh Lahiri

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Neuromorphic computing, inspired by the intricate operations of biological neural networks, offers a revolutionary approach to overcoming the limitations of traditional computing architectures. This research proposes the integration of spintronics with neuromorphic systems, aiming to enhance computational performance, scalability, and energy efficiency. Traditional computing systems, based on the Von Neumann architecture, struggle with scalability and efficiency due to the segregation of memory and processing functions. In contrast, the human brain exemplifies high efficiency and adaptability, processing vast amounts of information with minimal energy consumption. This project explores the use of spintronics, which utilizes the electron's spin rather than its charge, to create more energy-efficient computing systems. Spintronic devices, such as magnetic tunnel junctions (MTJs) manipulated through spin-transfer torque (STT) and spin-orbit torque (SOT), offer a promising pathway to reducing power consumption and enhancing the speed of data processing. The integration of these devices within a neuromorphic framework aims to replicate the efficiency and adaptability of biological systems. The research is structured into three phases: an exhaustive literature review to build a theoretical foundation, laboratory experiments to test and optimize the theoretical models, and iterative refinements based on experimental results to finalize the system. The initial phase focuses on understanding the current state of neuromorphic and spintronic technologies. The second phase involves practical experimentation with spintronic devices and the development of neuromorphic systems that mimic synaptic plasticity and other biological processes. The final phase focuses on refining the systems based on feedback from the testing phase and preparing the findings for publication. The expected contributions of this research are twofold. Firstly, it aims to significantly reduce the energy consumption of computational systems while maintaining or increasing processing speed, addressing a critical need in the field of computing. Secondly, it seeks to enhance the learning capabilities of neuromorphic systems, allowing them to adapt more dynamically to changing environmental inputs, thus better mimicking the human brain's functionality. The integration of spintronics with neuromorphic computing could revolutionize how computational systems are designed, making them more efficient, faster, and more adaptable. This research aligns with the ongoing pursuit of energy-efficient and scalable computing solutions, marking a significant step forward in the field of computational technology.

Keywords: material science, biological engineering, mechanical engineering, neuromorphic computing, spintronics, energy efficiency, computational scalability, synaptic plasticity.

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Authors: Hyun-Woo Cho

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Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

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Authors: Saeed Rabea Baatwah, Zalailah Salleh, Norsiah Ahmad

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This study examines whether audit committee chair with financial expertise enhances the audit committee role in financial reporting quality in emerging market. We investigate this influence by employing the direct effect and moderating effect of audit committee chair with financial expertise on financial reporting timeliness. By using Omani data and the panel data method for two proxies for financial reporting timeliness, we find that audit committee chair with financial expertise enhances the timeliness of financial reporting through making the disclosure of annual reports timely. Further, we report evidence showing that both accounting and non-accounting financial expertise on the audit committee have a positive and significant influence on the timeliness of financial reporting. We also document that the association between financial expertise and the timeliness of financial reporting is more pronounced when the chair of the audit committee has financial expertise. This study is among the first to comprehensively prove that audit committee chair with financial expertise contributes to the quality of financial reporting in emerging market.

Keywords: audit committee, chair with financial expertise, timeliness of financial reporting, Oman

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Authors: K. Shaji Mon, P. R. John Sreenidhi

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In deep-submicrometer CMOS processes, time-domain resolution of a digital signal is becoming higher than voltage resolution of analog signals. This claim is nowadays pushing toward a new circuit design paradigm in which the traditional analog signal processing is expected to be progressively substituted by the processing of times in the digital domain. Within this novel paradigm, digitally controlled delay lines (DCDL) should play the role of digital-to-analog converters in traditional, analog-intensive, circuits. Digital delay locked loops are highly prevalent in integrated systems.The proposed paper addresses the glitches present in delay circuits along with area,power dissipation and signal integrity.The digitally controlled delay lines(DCDL) under study have been designed in a 90 nm CMOS technology 6 layer metal Copper Strained SiGe Low K Dielectric. Simulation and synthesis results show that the novel circuits exhibit no glitches for dual output coarse DCDL with less power dissipation and consumes less area compared to the glitch free NAND based DCDL.

Keywords: glitch free, NAND-based DCDL, CMOS, deep-submicrometer

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Authors: Vitaliy Petrov, Natalia Shusharina, Vitaliy Kasymov, Maksim Patrushev, Evgeny Bogdanov

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The leading worldwide death reasons are ischemic heart disease and other cardiovascular illnesses. Generally, the common symptom is high blood pressure. Long-time blood pressure control is very important for the prophylaxis, correct diagnosis and timely therapy. Non-invasive methods which are based on Korotkoff sounds are impossible to apply often and for a long time. Implantable devices can combine longtime monitoring with high accuracy of measurements. The main purpose of this work is to create a real-time monitoring system for decreasing the death rate from cardiovascular diseases. These days implantable electronic devices began to play an important role in medicine. Usually implantable devices consist of a transmitter, powering which could be wireless with a special made battery and measurement circuit. Common problems in making implantable devices are short lifetime of the battery, big size and biocompatibility. In these work, blood pressure measure will be the focus because it’s one of the main symptoms of cardiovascular diseases. Our device will consist of three parts: the implantable pressure sensor, external transmitter and automated workstation in a hospital. The Implantable part of pressure sensors could be based on piezoresistive or capacitive technologies. Both sensors have some advantages and some limitations. The Developed circuit is based on a small capacitive sensor which is made of the technology of microelectromechanical systems (MEMS). The Capacitive sensor can provide high sensitivity, low power consumption and minimum hysteresis compared to the piezoresistive sensor. For this device, it was selected the oscillator-based circuit where frequency depends from the capacitance of sensor hence from capacitance one can calculate pressure. The external device (transmitter) used for wireless charging and signal transmission. Some implant devices for these applications are passive, the external device sends radio wave signal on internal LC circuit device. The external device gets reflected the signal from the implant and from a change of frequency is possible to calculate changing of capacitance and then blood pressure. However, this method has some disadvantages, such as the patient position dependence and static using. Developed implantable device doesn’t have these disadvantages and sends blood pressure data to the external part in real-time. The external device continuously sends information about blood pressure to hospital cloud service for analysis by a physician. Doctor’s automated workstation at the hospital also acts as a dashboard, which displays actual medical data of patients (which require attention) and stores it in cloud service. Usually, critical heart conditions occur few hours before heart attack but the device is able to send an alarm signal to the hospital for an early action of medical service. The system was tested with wireless charging and data transmission. These results can be used for ASIC design for MEMS pressure sensor.

Keywords: MEMS sensor, RF power, wireless data, oscillator-based circuit

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Authors: Cristiane Hengler Corrêa Bernardo

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The communication is an essential part of the process that characterizes scientific research. It should be present in every stage of research in a systemic way. However, this process is not always efficient and effective. Reports of researchers focused on agribusiness point to difficulties in communicating with farmers that negatively impact on research results and may cause distortions and even quite significant inconsistencies. This research aims at identifying the main noise and barriers in communication between agribusiness researchers and farmers. It discusses the possibility of creating a specific strategy to correct or minimize such failures. The main research question: what features of the communication process will be decisive for the communication between agribusiness researcher and farmer occur with greater efficiency? It is expected that the research will result in processes that may correct or minimize such problems, promoting dialogues more efficient knowledge. The research will adopt a qualitative approach, using action research as a form of investigative action for social and educational nature, aiming at promoting understanding and interaction between researchers and members of the investigated situations. To collect and analyze data to document analysis will be used; questionnaires and interviews and content analysis.

Keywords: agribusiness farmers, researchers, science communication, analysis

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Authors: Guillermo Cardoso-Landa, Ana Julita Cuenca-Castro

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The present paper focuses to research the possible causes of curtain failure of dam "El Batan" in Querétaro, Mexico, including the design of the fineness of the employee filter during the construction of the curtain was verified since this depends greatly on the proper functioning of this filter. To carry out the required analysis, it was necessary to document elements provided understanding about the composition and behavior of the land curtain, and the main types of failure in these curtains. The general characteristics of the curtain dam "El Batan", the composition of the filter, as well as possible causes resulted in the failure were also analyzed. Once obtained data starting, the actual analysis was carried out by reviewing the following possible causes of failure: fails due to a poor constructive process of the curtain, failure due to hydraulic suppression, fails due to a structural design wrong, fails due to a geotechnical design wrong, fails due to a hydraulic design wrong, fails due to an inadequate design of the curtain filter. It is concluded that the type of the filter employed in the land dam curtain of "El Batan", located in the municipality of Querétaro, México, do not have adequate characteristics, outside of the ranges of design, using the curves: Terzaghi criteria, Sherard and Dunnigan criteria, UCSCS criteria, and Foster and Fell criteria.

Keywords: failure, dam, filter, curtain

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Authors: Abdelrahman Abdelazim

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Most industries are looking for technologies that are easy to use, efficient and fast to accomplish. To implement these, factories tend to use advanced systems that could alter complicity to simplicity and rudimentary to advancement. Cloud Manufacturing is a new movement that aims to mirror and integrate cloud computing into manufacturing. Amongst cloud manufacturing various advantages are decreasing the human involvements and increasing the dependency on automated machines, which in turns decreases human errors and increases efficiency. A reliable and extraordinary performance processes with minimum errors are highly desired factors of today’s manufacturers. At the glance it seems to be the best alternative, however, the implementation of a cloud system can be very challenging. This work investigates cloud manufacturing in details, it outlines its advantages and disadvantages by converting a local factory in Kuwait to a cloud-ready system. Initially the flow of the factory’s manufacturing process has been analyzed identifying the bottlenecks and illustrating how cloud manufacturing can eliminate them. Following this an automation process has been analyzed and implemented. A comparison between the process before and after the adaptation has been carried out showing the effects on the cost, the output and the efficiency of the process.

Keywords: cloud manufacturing, automation, Kuwait industrial sector, advanced digital manufacturing

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Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

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Authors: Havish Nalapareddy, Mark V. Albert, Ranak Bansal, Avi Udash, Lin Lin

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Students engage in many course projects during their degree programs. However, impactful projects often need a time frame longer than a single semester. Ideally, projects are documented and structured to be readily accessible to future students who may choose to continue the project, with features that emphasize the local community, university, or course structure. The Research and Project Portal (RAPP) is a place where students can post both their completed and ongoing projects with all the resources and tools used. This portal allows students to see what other students have done in the past, in the same university environment, related to their domain of interest. Computer science instructors or students selecting projects can use this portal to assign or choose an incomplete project. Additionally, this portal allows non-computer science faculty and industry collaborators to document their project ideas for students in courses to prototype directly, rather than directly soliciting the help of instructors in engaging students. RAPP serves as a platform linking students across classes and faculty both in and out of computer science courses on joint projects to encourage long-term project efforts across semesters or years.

Keywords: education, technology, research, academic portal

Procedia PDF Downloads 124

Authors: Pasan Dunuwila, V. H. L. Rodrigo, Naohiro Goto

Abstract:

Sri Lanka is one the largest natural rubber (NR) producers of the world, where the NR industry is a major foreign exchange earner. Among the locally manufactured NR products, concentrated latex (CL) and ribbed smoked sheets (RSS) hold a significant position. Furthermore, these products become the foundation for many products utilized by the people all over the world (e.g. gloves, condoms, tires, etc.). Processing of CL and RSS costs a significant amount of material, energy, and workforce. With this background, both manufacturing lines have immensely challenged by waste, low productivity, lack of cost efficiency, rising cost of production, and many environmental issues. To face the above challenges, the adaptation of sustainable manufacturing measures that use less energy, water, materials, and produce less waste is imperative. However, these sectors lack comprehensive studies that shed light on such measures and thoroughly discuss their improvement potentials from both environmental and economic points of view. Therefore, based on a study of three CL and three RSS mills in Sri Lanka, this study deploys sustainable manufacturing techniques and tools to uncover the underlying potentials to improve performances in CL and RSS processing sectors. This study is comprised of three steps: 1. quantification of average material waste, economic losses, and greenhouse gas (GHG) emissions via material flow analysis (MFA), material flow cost accounting (MFCA), and life cycle assessment (LCA) in each manufacturing process, 2. identification of improvement options with the help of Pareto and What-if analyses, field interviews, and the existing literature; and 3. validation of the identified improvement options via the re-execution of MFA, MFCA, and LCA. With the help of this methodology, the economic and environmental hotspots, and the degrees of improvement in both systems could be identified. Results highlighted that each process could be improved to have less waste, monetary losses, manufacturing costs, and GHG emissions. Conclusively, study`s methodology and findings are believed to be beneficial for assuring the sustainable growth not only in Sri Lankan NR processing sector itself but also in NR or any other industry rooted in other developing countries.

Keywords: concentrated latex, natural rubber, ribbed smoked sheets, Sri Lanka

Procedia PDF Downloads 249

Authors: Zainuddin Zakaria, Sun Woh Lye

Abstract:

Despite the continuous advancements in automated conflict resolution tools, there is still a low rate of adoption of automation from Air Traffic Control Officers (ATCOs). Trust or acceptance in these tools and conformance to the individual ATCO preferences in strategy execution for conflict resolution are two key factors that impact their use. This paper proposes a methodology to unearth and classify ATCO conflict resolution strategies from simulator data of trained and qualified ATCOs. The methodology involves the extraction of ATCO executive control actions and the establishment of a system of strategy resolution classification based on ATCO radar commands and prevailing flight parameters in deconflicting a pair of aircraft. Six main strategies used to handle various categories of conflict were identified and discussed. It was found that ATCOs were about twice more likely to choose only vertical maneuvers in conflict resolution compared to horizontal maneuvers or a combination of both vertical and horizontal maneuvers.

Keywords: air traffic control strategies, conflict resolution, simulator data, strategy classification system

Procedia PDF Downloads 132

Authors: Tamene Keneni, Tibebu Yohannes

Abstract:

The prevalence of autism spectrum disorder (ASD) in general and autism in particular is on the rise globally, and the need for evidence-based intervention and care for children with autism has grown, too. However, evidence on autism is scanty in developing countries, including Ethiopia. With the aim to help fill the gap and paucity in research into the issue, the main purpose of this study is to explore, better understand, and document the experiences and perceptions of parents of children with autism. To this end, we used a qualitative survey to collect data from a convenient sample of parents raising a child with autism. The data collected were subjected to qualitative analysis that yielded several themes and subthemes, including late diagnosis, parents’ reactions to diagnosis, sources of information during and after diagnosis, differing reactions to having a child with autism from siblings, extended family members, and the larger community, attribution of autism to several causes by the community, lack of recognition and open discussion of autism and lack of appropriated public educational and health care services for children with autism and their parents. The themes and subthemes identified were discussed in light of existing literature, and implications for practice were drawn.

Keywords: ASD, autism, children with autism, raising children with autism

Procedia PDF Downloads 142

Authors: Francis E. Idachaba, Sarah Uyimeh Tommy

Abstract:

This paper describes the design of an RFID laptop monitoring and management system. Laptops embedded with RFID chips are monitored and tracked to provide a monitoring system for the purpose of tracking as well as monitoring movement of the laptops in and out of a building. The proposed system is implemented with both hardware and software components. The hardware architecture consists of RFID passive tag, RFID module (reader), and a server hosting the application and database. The RFID readers are distributed at major exits of a building or premises. The tags are programmed with owner laptop details are concealed in the laptops. The software architecture consists of application software that has the APIs (Applications Programming Interface) necessary to interface the RFID system with the PC, to achieve automated laptop monitoring system. A friendly graphic user interface (GUI) and a database that saves all readings and owners details. The system is capable of reducing laptop theft especially in students’ hostels as laptops can be monitored as they are taken either in or out of the building.

Keywords: asset tracking, GUI, laptop monitoring, radio frequency identification, passive tags

Procedia PDF Downloads 372