Search results for: dual task paradigm

Authors: M. Meddi, A. Boufekane

Abstract:

The Mitidja coastal groundwater which extends over an area of 1450 km2 is a strategic resource in the Algiers region. The high dependence of the regional economy on the use of this groundwater forces us to have recourse to its artificial recharge from the Wadi El Harrach in its upstream part. This system of artificial recharge has shown its effectiveness in the development of water resource mentioned in the succeeding works in several regions of the world. The objective of this study is to: Increase the reserves of water inputs by infiltration, raise the water level and its good quality in wells and boreholes, reduce losses to the sea, and address seawater intrusion by maintaining balance in the freshwater-saltwater interface in the downstream part of the groundwater basin. After analyzing the situation, it was noticed that a qualitative monitoring of the Wadi water for the groundwater recharge has to be done. For this purpose, we proceeded during three successive years (2010, 2011, and 2012) to the monthly sampling of water in the upstream part of the Wadi El Harrach for chemical analysis. The variation of the sediment transport concentration will be also measured. This monitoring aims to characterize the water quality and avoid clogging in the proposed recharge area. The results of these analyses showed the good chemical quality according to the analyses we performed in the laboratory during the three years, but they are too loaded with suspended matters. We noticed that these fine particles come from the grinding of limestone of sandpit located upstream of the area of the proposed recharge system. This problem can be solved by a water supply upstream of sandpit. For the recharge, we propose the method of using two wells for dual use, which means that it can be used for water supply and extraction. This solution is inexpensive in our case and could easily be used as wells are already drilled in the upstream part. This solution increases over time the piezometric level and also reduce groundwater contamination by saltwater in the downstream part.

Keywords: water quality, artificial groundwater recharge, Mitidja, North Algeria

Procedia PDF Downloads 268

Authors: Rafat Alwazna

Abstract:

Technical lexicon is witnessing a large upsurge in the use of new terminologies whose emergence is an inevitable result of the spread of high-quality technology, the existence of scientific paradigms and the fast growth of research in different disciplines. One important subfield of terminology is legal terminology, which forms a crucial part of legal studies, and whose translation from one legal system into another is deemed a formidable and arduous task that needs to be properly performed by legal translators. Indeed, the issue of untranslatability of legal terms, particularly between originally unrelated languages, like legal Arabic and legal English, has long been a real challenge in legal translation. It stems from the conceptual incongruency between legal terms of different legal languages, which are derived from different legal cultures and legal systems. Such conceptual asymmetry is owing to the fact that law has no universal reference and that legal language is what determines the degree of difference in conceptual correspondence. The present paper argues that although conceptual asymmetry, which is the main reason for the issue of untranslatability of legal terms, cannot be denied in legal translation, there exist certain translation techniques which, if properly adopted, would resolve the issue of untranslatability of legal terms and therefore achieve acceptable legal translation. Hence, the question of untranslatability of legal terms should no longer exist within the context of legal translation.

Keywords: conceptual incongruency, Legal terms, translation techniques, untranslatability

Procedia PDF Downloads 169

Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

Abstract:

The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

Procedia PDF Downloads 121

Authors: Walid Hassairi, Moncef Bousselmi, Mohamed Abid

Abstract:

Functional verification is a major part of today’s system design task. Several approaches are available for verification on a high abstraction level, where designs are often modeled using MATLAB/Simulink. However, different approaches are a barrier to a unified verification flow. In this paper, we propose a co-simulation interface between SystemC and MATLAB and Simulink to enable functional verification of multi-abstraction levels designs. The resulting verification flow is tested on JPEG compression algorithm. The required synchronization of both simulation environments, as well as data type conversion is solved using the proposed co-simulation flow. We divided into two encoder jpeg parts. First implemented in SystemC which is the DCT is representing the HW part. Second, consisted of quantization and entropy encoding which is implemented in Matlab is the SW part. For communication and synchronization between these two parts we use S-Function and engine in Simulink matlab. With this research premise, this study introduces a new implementation of a Hardware SystemC of DCT. We compare the result of our simulation compared to SW / SW. We observe a reduction in simulation time you have 88.15% in JPEG and the design efficiency of the supply design is 90% in SDR.

Keywords: hardware/software, co-design, co-simulation, systemc, matlab, s-function, communication, synchronization

Procedia PDF Downloads 382

Authors: Anuja Singh, Avik K. Pati, Ashok K. Mishra

Abstract:

Organic fluorophores with π-conjugated scaffolds are important because of their interesting optoelectronic properties. In recent years, our lab has been engaged in understanding the photophysics of small diacetylene bridged fluorophores and found the diynes as a promising class of π-conjugated fluorophores. Building on this understanding, recently we have focused on the photophysics of a less explored class of cross-conjugated Y-shaped enediynes (one double and two triple bonds). Here we present the photophysical properties of such enediynes which show interesting photophysical properties that include dual emissions from locally excited (LE) and intramolecular charge transfer (ICT) states and ring size dependent aggregate fluorescence in non-aqueous media. The dyes also show prominent aggregate fluorescence in mixed-aqueous solvents and solid powder form. We further show that the solid state fluorescence can be reversibly switched multiple of cycles by external stimuli, highlighting their potential applications in solid states. The enediynes with push-pull electronic substituents/moieties exhibit high contrast fluorescence color switching upon continuous photon illumination. The intriguing photophysical outcomes of the enediynyl fluorophores are judiciously exploited to generate single-component white light emission in binary solvent mixtures and sense polar aprotic vapor in polymer film matrices. The photophysical behavior of the dyes is further successfully utilized to monitor the microenvironment changes of biologically relevant anisotropic media such as bile salts. In summary, the newly introduced cross-conjugated enediynes enrich the toolbox of organic fluorophores and vouch to display versatile applications.

Keywords: aggregation in solution and solid state, enediynes, physical photochemistry and photophysics, vapor sensing and white light emission

Procedia PDF Downloads 464

Authors: Shady S. Hassan, Brijesh K. Tiwari, Gwilym A. Williams, Amit K. Jaiswal

Abstract:

Waste materials from a wide range of agro-industrial processes may be used as substrates for microbial growth, and subsequently the production of a range of high value products and bioenergy. In addition, utilization of these agro-residues in bioprocesses has the dual advantage of providing alternative substrates, as well as solving their disposal problems. Spent coffee grounds (SCG) are a by-product (45%) of coffee processing. SCG is a lignocellulosic material, which is composed mainly of cellulose, hemicelluloses, and lignin. Thus, a pretreatment process is required to facilitate an efficient enzymatic hydrolysis of such carbohydrates. In this context, microwave pretreatment of lignocellulosic biomass without the addition of harsh chemicals represents a green technology. Moreover, microwave treatment has a high heating efficiency and is easy to implement. Thus, microwave pretreatment of SCG without adding of harsh chemicals investigated as a green technology to enhance enzyme hydrolysis. In the present work, microwave pretreatment experiments were conducted on SCG at varying power levels (100, 250, 440, 600, and 1000 W) for 60 s. By increasing microwave power to a certain level (which vary by varying biomass), reducing sugar increases, then reducing sugar from biomass start to decrease with microwave power increase beyond this level. Microwave pretreatment of SCG at 60s followed by enzymatic hydrolysis resulted in total reducing sugars of 91.6 ± 7.0 mg/g of biomass (at microwave power of 100 w). Fourier transform Infrared Spectroscopy (FTIR) was employed to investigate changes in functional groups of biomass after pretreatment, while high-performance liquid chromatography (HPLC) was employed for determination of glucose. Pretreatment of lignocellulose using microwave was found to be an effective and energy efficient technology to improve saccharification and glucose yield. Energy performance will be evaluated for the microwave pretreatment, and the enzyme hydrolysate will be used as media component substitute for the production of ethanol and other high value products.

Keywords: lignocellulose, microwave, pretreatment, spent coffee grounds

Procedia PDF Downloads 399

Authors: A. Majeed, M.K. Abbasi, S. Hameed, A. Imran, T. Naqqash, M. K. Hanif

Abstract:

Plant growth-promoting rhizobacteria (PGPR) are free-living soil bacteria that aggressively colonize the rhizosphere/plant roots, and enhance the growth and yield of plants when applied to seed or crops. Root associated (endophytic and rhizospheric) PGPR were isolated from Sunflower (Helianthus anus) grown in soils collected from 16 different sites of sub division Dhirkot, Poonch, Azad Jammu & Kashmir, Pakistan. A total of 150 bacterial isolates were isolated, purified, screened in vitro for their plant growth promoting (PGP) characteristics. 11 most effective isolates were selected on the basis of biochemical assays (nitrogen fixation, phosphate solubilization, growth hormone production, biocontrol assay, and carbon substrates utilization assay through gas chromatography (GCMS), spectrophotometry, high performance liquid chromatography HPLC, fungal and bacterial dual plate assay and BIOLOG GN2/GP2 microplate assay respectively) and were tested on the crop under controlled and field conditions. From the inoculation assay, the most promising 4 strains (on the basis of increased root/shoot weight, root/shoot length, seed oil content, and seed yield) were than selected for colonization studies through confocal laser scanning and transmission electron microscope. 16Sr RNA gene analysis showed that these bacterial isolates belong to Pseudononas, Enterobacter, Azospirrilum, and Citobacter genera. This study is the clear evident that such isolates have the potential for application as inoculants adapted to poor soils and local crops to minimize the chemical fertilizers harmful for soil and environment

Keywords: PGPR, nitrogen fixation, phosphate solubilization, colonization

Procedia PDF Downloads 321

Authors: S. Cafiso, B. Capace, A. Di Graziano, C. D’Agostino

Abstract:

Systematic monitoring of the trackbed is necessary to assure safety and quality of service in the railway system. Moreover, to produce effective management of the maintenance treatments, the assessment of bearing capacity of the railway trackbed must include ballast, sub-ballast and subgrade layers at different depths. Consequently, there is an increasing interest in obtaining a consistent measure of ballast bearing capacity with no destructive tests (NDTs) able to work in the physical and time restrictions of railway tracks in operation. Moreover, in the case of the local railway with reduced gauge, the use of the traditional high-speed track monitoring systems is not feasible. In that framework, this paper presents results from in site investigation carried out on ballast and sleepers with Ground Penetrating Radar (GPR) and Light Falling Weight Deflectometer (LWD). These equipment are currently used in road pavement maintenance where they have shown their reliability and effectiveness. Application of such Non-Destructive Tests in railway maintenance is promising but in the early stage of the investigation. More specifically, LWD was used to estimate the stiffness of ballast and sleeper support, as well. LWD, despite the limited load (6 kN in the trial test) applied directly on the sleeper, was able to detect defects in the bearing capacity at the Sleeper/Ballast interface. A dual frequency GPR was applied to detect the presence of layers’ discontinuities at different depths due to fouling phenomena that are the main causes of changing in the layer dielectric proprieties within the ballast thickness. The frequency of 2000Mhz provided high-resolution data to approximately 0.4m depth, while frequency of 600Mhz showed greater depth penetration up to 1.5 m. In the paper literature review and trial in site experience are used to identify Strengths, Weaknesses, Opportunities, and Threats (SWOT analysis) of the application of GPR and LWD for the assessment of bearing capacity of railway track-bed.

Keywords: bearing capacity, GPR, LWD, no destructive test, railway track

Procedia PDF Downloads 118

Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

Abstract:

Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

Procedia PDF Downloads 459

Authors: Sultanbayeva Gulmira Serikbayevna, Golovchun Aleftina Anatolyevna

Abstract:

The development of any nation is directly related to the development of human capital in it. A human development is an increase its intellectual potential, its compliance with the requirements of time, present and future society. Demands of globalization cannot limit the processes of national traditions. The education system must be formed on the basis of international practice of cultural development. In Kazakhstan, where modernization changes are rapidly developing, the education system should be formed in two ways: first, on a national basis, and secondly, based on global best practices. There is the need to recognize and promote the importance of education as a value. The world community considers the problem of spiritual values. Along with individual values, spiritual values are also universal values. Formation of values such as the presence in young people a sense of respect for their homeland, social responsibility, respect the culture and traditions of its people is the most important task than the possession of material goods. When forming the intellectual nation, values in the field of education and science become investments for the development of the society, as well as education and science today transformed into the most important capital.

Keywords: human capital, humanitarian technology, intangible assets, intelligent nation, society of knowledge

Procedia PDF Downloads 301

Authors: Svetlana V. Topolyanskaya, Tatyana A. Eliseeva, Olga N. Vakulenko, Leonid I. Dvoretski

Abstract:

Introduction: Limited data are available on osteoporosis in centenarians. Therefore, we evaluated bone mineral density in long-living patients with coronary artery disease (CAD). Methods: 202 patients hospitalized with CAD were enrolled in this cross-sectional study. The patients' age ranged from 90 to 101 years. The majority of study participants (64.4%) were women. The main exclusion criteria were any disease or medication that can lead to secondary osteoporosis. Bone mineral density (BMD) was measured by dual-energy X-ray absorptiometry. Results: Normal lumbar spine BMD was observed in 40.9%, osteoporosis – in 26.9%, osteopenia – in 32.2% of patients. Normal proximal femur BMD values were observed in 21.3%, osteoporosis – in 39.9%, and osteopenia – in 38.8% of patients. Normal femoral neck BMD was registered only in 10.4% of patients, osteoporosis was observed in 60.4%, osteopenia in 29.2%. Significant positive correlation was found between all BMD values and body mass index of patients (p < 0.001). Positive correlation was registered between BMD values and serum uric acid (p=0.0005). The likelihood of normal BMD values with hyperuricemia increased 3.8 times, compared to patients with normal uric acid, who often have osteoporosis (Odds Ratio=3.84; p = 0.009). Positive correlation was registered between all BMD values and body mass index (p < 0.001). Positive correlation between triglycerides levels and T-score (p=0.02), but negative correlation between BMD and HDL-cholesterol (p=0.02) were revealed. Negative correlation between frailty severity and BMD values (p=0.01) was found. Positive correlation between BMD values and functional abilities of patients assessed using Barthel index (r=0,44; p=0,000002) and IADL scale (r=0,36; p=0,00008) was registered. Fractures in history were observed in 27.6% of patients. Conclusions: The study results indicate some features of BMD in long-livers. In the study group, significant relationships were found between bone mineral density on the one hand, and patients' functional abilities on the other. It is advisable to further study the state of bone tissue in long-livers involving a large sample of patients.

Keywords: osteoporosis, bone mineral density, centenarians, coronary artery disease

Procedia PDF Downloads 126

Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

Abstract:

Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

Procedia PDF Downloads 216

Authors: Rusne Kregzdaite

Abstract:

The value of the cultural sector stems from the symbolic exploration that differentiates cultural organisations from other product or service organisations. As a result, the cultural sector has a dual impact on the socio-economic system: the economic value (expressed in terms of market relations) created influences the dynamics of the country's financial indicators, while the cultural (non-market) value indirectly contributes to the welfare of the state through changes in societal values, creativity transformations and cultural needs of the country. Measurement of indirect (cultural value) impacts is difficult, but in the case of the cultural sector (especially when it comes to economically inefficient state-funded culture), it helps to reveal the essential characteristics of the sector. The study aims to analyze the value of cultural organisations that are invisible in market processes and to base it on quantified calculations. This was be done by analyzing the usefulness of the consumer, incorporating not only the price paid but also the social and cultural decision-making factors that determine the spectator's choice (time dedicated for a visit, additional costs, content, previous experiences, corporate image). This may reflect the consumer's real choice to consume (all the costs he incurs may be considered the financial equivalent of his experience with the cultural establishment). The research methodology was tested by analyzing the performing arts sector and applying methods to the Lithuanian national drama theatre case. The empirical research consisted of a survey (more than 800 participants) of Lithuanian national drama theatre visitors to different performances. The willingness to pay and travel costs methods were used. Analysis of different performances lets identifies the factor that increases willingness to pay for the performance and affects theatre attendance. The research stresses the importance of cultural value and social perspective of the cultural sector and relates it to the discussions of public funding of culture.

Keywords: cultural economics, performing arts, willingness to pay, travel cost analysis, performing arts management

Procedia PDF Downloads 72

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

Abstract:

Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

Procedia PDF Downloads 114

Authors: Diana Codat

Abstract:

Tweets' analysis is part of text mining. Each document is a written text. It's possible to apply the usual text search techniques, in particular by switching to the bag-of-words representation. But the tweets induce peculiarities. Some may enrich the analysis. Thus, their length is calibrated (at least as far as public messages are concerned), special characters make it possible to identify authors (@) and themes (#), the tweet and retweet mechanisms make it possible to follow the diffusion of the information. Conversely, other characteristics may disrupt the analyzes. Because space is limited, authors often use abbreviations, emoticons to express feelings, and they do not pay much attention to spelling. All this creates noise that can complicate the task. The tweets carry a lot of potentially interesting information. Their exploitation is one of the main axes of the analysis of the social networks. We show how to access Twitter-related messages. We will initiate a study of the properties of the tweets, and we will follow up on the exploitation of the content of the messages. We will work under R with the package 'twitteR'. The study of tweets is a strong focus of analysis of social networks because Twitter has become an important vector of communication. This example shows that it is easy to initiate an analysis from data extracted directly online. The data preparation phase is of great importance.

Keywords: data mining, language R, social networks, Twitter

Procedia PDF Downloads 162

Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, José J. Hernández-Flores, Edith Olaco Garcia

Abstract:

The Project Scheduling Problem (PSP) is a generic name given to a whole class of problems in which the best form, time, resources and costs for project scheduling are necessary. The PSP is an application area related to the project management. This paper aims at being a guide to understand PSP by presenting a survey of the general parameters of PSP: the Resources (those elements that realize the activities of a project), and the Activities (set of operations or own tasks of a person or organization); the mathematical models of the main variants of PSP and the algorithms used to solve the variants of the PSP. The project scheduling is an important task in project management. This paper contains mathematical models, resources, activities, and algorithms of project scheduling problems. The project scheduling problem has attracted researchers of the automotive industry, steel manufacturer, medical research, pharmaceutical research, telecommunication, industry, aviation industry, development of the software, manufacturing management, innovation and technology management, construction industry, government project management, financial services, machine scheduling, transportation management, and others. The project managers need to finish a project with the minimum cost and the maximum quality.

Keywords: PSP, Combinatorial Optimization Problems, Project Management; Manufacturing Management, Technology Management.

Procedia PDF Downloads 402

Authors: Ritu Vashistha, Jitender Kumar

Abstract:

Clustering using the K-means algorithm is a very common way to understand and analyze the obtained output data. When a similar object is grouped, this is called the basis of Clustering. There is K number of objects and C number of cluster in to single cluster in which k is always supposed to be less than C having each cluster to be its own centroid but the major problem is how is identify the cluster is correct based on the data. Formulation of the cluster is not a regular task for every tuple of row record or entity but it is done by an iterative process. Each and every record, tuple, entity is checked and examined and similarity dissimilarity is examined. So this iterative process seems to be very lengthy and unable to give optimal output for the cluster and time taken to find the cluster. To overcome the drawback challenge, we are proposing a formula to find the clusters at the run time, so this approach can give us optimal results. The proposed approach uses the Euclidian distance formula as well melanosis to find the minimum distance between slots as technically we called clusters and the same approach we have also applied to Ant Colony Optimization(ACO) algorithm, which results in the production of two and multi-dimensional matrix.

Keywords: ant colony optimization, data clustering, centroids, data mining, k-means

Procedia PDF Downloads 115

Authors: Onyekachi Ohagwu

Abstract:

Human trafficking remains a pressing issue globally, with Nigeria serving as a source, transit, and destination country. In response to this crisis, the Edo State Task Force Against Human Trafficking (ETAHT), in collaboration with local partners and international organizations such as the International Organization for Migration, has implemented various initiatives, including technical and vocational education and training (TVET) programmes. This research article examines the effectiveness of the ETAHT TVET programme in providing a second chance for female returnee migrants in Nigeria. Through qualitative analysis, including in-depth interviews and case studies, the study evaluates the impact of the programme on participants' lives, socio-economic reintegration, and empowerment. Findings suggest that the ETAHT TVET programme plays a significant role in empowering female returnees, fostering self-reliance, and reducing the risk of re-trafficking. The article concludes with recommendations for enhancing the programme's effectiveness and scalability.

Keywords: Edo State, human trafficking, TVET programme, female returnee migrants, empowerment, socio-economic reintegration

Procedia PDF Downloads 42

Authors: Fawaz S. Al-Anzi, Dia AbuZeina

Abstract:

Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

Procedia PDF Downloads 242

Authors: Yasaswi Palagummi, Sareh Rowlands

Abstract:

Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work of ours, to solve the GZSL problem, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GSZL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets -AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: generalised, zero-shot learning, inductive learning, shifted-window attention, Swin transformer, vision transformer

Procedia PDF Downloads 58

Authors: Jungho Moon, Lae Jeong Park

Abstract:

This paper introduces the development of a firmware downloader for students attending microcontroller-related courses taught by the authors In the courses, AVR microcontroller experiment kits are used for programming exercise and the AVR microcontroller is programmed through a serial communication interface using a bootloader preinstalled on it. To use the bootloader, a matching firmware downloader that runs on a host computer and communicates with the bootloader is also required. When firmware downloading is completed, the serial port used for it needs to be closed. If the downloaded firmware uses serial communication, the serial port needs to be reopened in a serial terminal. As a result, the programmer of the AVR board switches from the downloader program and the serial terminal and vice versa. It is a simple task but quite a hassle to do each time new firmware needs downloading. To provide a more convenient programming environment for the courses, the authors developed a downloader program that includes a serial terminal in it. The program operates in downloader or terminal mode and the mode switching is performed automatically; therefore manual mode switching is not necessary. The feature provides a more convenient development environment by eliminating the need for manual mode switching each time firmware downloading is required.

Keywords: bootloader, firmware downloader, microcontroller, serial communication

Procedia PDF Downloads 176

Authors: Meng Wu

Abstract:

Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.

Keywords: motion planning, gravity gradient inversion algorithm, ant colony optimization

Procedia PDF Downloads 126

Authors: Donatien Callon, Ian Lalonde, Mathieu Nadeau, Alexandre Girard

Abstract:

Patient transfer is a challenging, critical task because it exposes caregivers to injury risks. Available transfer devices, like floor lifts, lead to improvements but are far from perfect. They do not eliminate the caregivers’ risk of musculoskeletal disorders, and they can be burdensome to use due to their poor maneuverability. This paper presents a new motorized floor lift with a single central motorized wheel connected to an instrumented handle. Admittance controllers are designed to 1) improve the device maneuverability, 2) reduce the required caregiver effort, and 3) ensure the security and comfort of patients. Two controller designs, one with a linear admittance law and a non-linear admittance law with variable damping, were developed and implemented on a prototype. Tests were performed on seven participants to evaluate the performance of the assistance system and the controllers. The experimental results show that 1) the motorized assistance with the variable damping controller improves maneuverability by 28%, 2) reduces the amount of effort required to push the lift by 66%, and 3) provides the same level of patient comfort compared to a standard unassisted floor lift.

Keywords: floor lift, human robot interaction, admittance controller, variable admittance

Procedia PDF Downloads 78

Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

Abstract:

In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

Procedia PDF Downloads 131

Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

Abstract:

We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

Procedia PDF Downloads 122

Authors: Jalil Boudjadar

Abstract:

Dynamic Voltage and Frequency Scaling (DVFS) multicore platforms are promising execution platforms that enable high computational performance, less energy consumption and flexibility in scheduling the system processes. However, the resulting interleaving and memory interference together with per-core frequency tuning make real-time guarantees hard to be delivered. Besides, energy consumption represents a strong constraint for the deployment of such systems on energy-limited settings. Identifying the system configurations that would achieve a high performance and consume less energy while guaranteeing the system schedulability is a complex task in the design of modern embedded systems. This work studies the trade-off between energy consumption, cores utilization and memory bottleneck and their impact on the schedulability of DVFS multicore time-critical systems with a hierarchy of shared memories. We build a model-based framework using Parametrized Timed Automata of UPPAAL to analyze the mutual impact of performance, energy consumption and schedulability of DVFS multicore systems, and demonstrate the trade-off on an actual case study.

Keywords: time-critical systems, multicore systems, schedulability analysis, energy consumption, performance analysis

Procedia PDF Downloads 91

Authors: Mohamed Boubekri, Jaewook Lee

Abstract:

The assessment of the daylighting performance of a design solution is a complex task due to the changing nature of daylight. A few quantitative metrics are available to designers to assess such a performance, among them are the mean hourly illuminance (MHI), the daylight factor (DF), the daylight autonomy (DA) and the useful daylight illuminance (UDI). Each of these metrics has criteria and limitations that affect the outcome of the evaluation. When to use one metric instead of another depends largely on the design goals to be achieved. Using Design Iterate Validate Adapt (DIVA) daylighting simulation program we set out to examine the performance behavior of these four metrics with the changing dimensions of three shading devices: a horizontal overhang, a horizontal louver system, and a vertical louver system, and compare their performance behavior as the orientation of the window changes. The context is a classroom of a prototypical elementary school in South Korea. Our results indicate that not all four metrics behave similarly as we vary the size of each shading device and as orientations changes. The UDI is the metric that leads to outcome most different than the other three metrics. Our conclusion is that not all daylighting metrics lead to the same conclusions and that it is important to use the metric that corresponds to the specific goals and objectives of the daylighting solution.

Keywords: daylight factor, hourly daylight illuminance, daylight autonomy, useful daylight illuminance

Procedia PDF Downloads 268

Authors: Shreya Pare, Parvin Akhter

Abstract:

Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

Procedia PDF Downloads 155

Authors: Tingyu Zhang

Abstract:

The horizontal ecological compensation (HEC) mechanism is the key to stimulating the active participation of the whole basin in ecological protection. In this paper, we construct an evolutionary model for HEC in the Yangtze River Economic Belt (YREB) basin with the introduction of the central government constraint and incentive mechanism (CGCIM) and explore the conditions for the realization of a (Protection and compensation) strategy that meets the social expectations. Further, the water quality-water quantity model is utilized to measure the HEC amount with the characteristic factual data of the YREB in 2020-2022. The results show that the stability of the evolutionary game model of upstream and downstream governments in the YREB is closely related to the CGCIM. If (Protection Compensation) is to be realized as the only evolutionary stable strategy of the evolutionary game system composed of upstream and downstream governments, it is necessary for the CGCIM to satisfy that the sum of the incentives for the protection side and its unilateral or bilateral constraints is greater than twice the input cost of the active strategy, and the sum of the incentives for the compensation side and its unilateral or bilateral constraints is greater than the amount of ecological compensation that needs to be paid by it when it adopts the active strategy. At this point, the total amount of HEC that the downstream government should give to the upstream government of the YREB is 2856.7 million yuan in 2020, 5782.1 million yuan in 2021, and 23166.7 million yuan in 2022. The results of the study can provide a reference for promoting the improvement and refinement of the HEC mechanism in the YREB.

Keywords: horizontal ecological compensation, Yangtze river economic belt, evolutionary game analysis, water quality and quantity model research on territorial ecological restoration in Mianzhu city, Sichuan, under the dual evaluation framework

Procedia PDF Downloads 22

Authors: Elizabeth Mahenge

Abstract:

Unemployment is a problem that face many graduates all over the world. Every year universities in many parts of the world produce graduates who are looking for an employment. Swahili, a Bantu language originated in East African coast, can be used as an avenue for youth’s employment in South Africa. This paper helps youth to know about job opportunities available through teaching Swahili language. The objective of this paper is capacity building to youths to be teachers of Swahili and be ready to compete in the marketplace. The methodology was through two weeks online training on how to teach Swahili as a foreign language. The communicative approach and task-based approach were used.  Participants to this training were collected through a WhatsApp group advertisement about “short training for Swahili teachers for foreigners”. A total number of 30 participants registered but only 11 attended the training. Training was online via zoom. The contribution of this paper is that by being fluent in Swahili one would benefit with teaching job opportunities anywhere in the world. Hence the problem of unemployment among the youths would be reduced as they can employ themselves or being employed in academic institutions anywhere in the world. The paper calls for youths in South Africa to opt for Swahili language courses to be trained and become experts in the teaching Swahili as a foreign language.

Keywords: foreign language, linguistic market, Swahili, employment

Procedia PDF Downloads 59