Search results for: bird song processing

Authors: Lin Meng, Xi Lu, Haibo Wang, Yong Song, Lili Cao, Wenfang Song, Yong Hu

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China has abundant heavy oil resources, and thermal recovery is the main recovery method for heavy oil reservoirs. However, high energy consumption, high carbon emission and high production costs make heavy oil thermal recovery unsustainable. It is urgent to explore a replacement for developing technology. A low Carbon and cost technology of heavy oil recovery, chemical viscosity-reduction in layer (CVRL), is developed by the petroleum exploration and development research institute of Sinopec via investigated mechanisms, synthesized products, and improved oil production technologies, as follows: (1) Proposed a cascade viscous mechanism of heavy oil. Asphaltene and resin grow from free molecules to associative structures further to bulk aggregations by π - π stacking and hydrogen bonding, which causes the high viscosity of heavy oil. (2) Aimed at breaking the π - π stacking and hydrogen bond of heavy oil, the copolymer of N-(3,4-dihydroxyphenethyl) acryl amide and 2-Acrylamido-2-methylpropane sulfonic acid was synthesized as a viscosity reducer. It achieves a viscosity reduction rate of>80% without shearing for heavy oil (viscosity < 50000 mPa‧s), of which fluidity is evidently improved in the layer. (3) Synthesized hydroxymethyl acrylamide-maleic acid-decanol ternary copolymer self-assembly plugging agent. The particle size is 0.1 μm-2 mm adjustable, and the volume is 10-500 times controllable, which can achieve the efficient transportation of viscosity reducer to enriched oil areas. CVRL has applied 400 wells until now, increasing oil production by 470000 tons, saving 81000 tons of standard coal, reducing CO2 emissions by 174000 tons, and reducing production costs by 60%. It promotes the transformation of heavy oil towards low energy consumption, low carbon emissions, and low-cost development.

Keywords: heavy oil, chemical viscosity-reduction, low carbon, viscosity reducer, plugging agent

Procedia PDF Downloads 79

Authors: Sergei Aleinik, Yuri Matveev

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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

Procedia PDF Downloads 396

Authors: Sanskar, Abhinav Pal, Aryush Gupta, Sushil Kumar Mishra

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One of the critical and tedious assignments in agricultural practices is the detection of diseases on vegetation. Agricultural production is very important in today’s economy because plant diseases are common, and early detection of plant diseases is important in agriculture. Automatic detection of such early diseases is useful because it reduces control efforts in large productive farms. Using digital image processing and machine learning algorithms, this paper presents a method for plant disease detection. Detection of the disease occurs on different leaves of the plant. The proposed system for plant disease detection is simple and computationally efficient, requiring less time than learning-based approaches. The accuracy of various plant and foliar diseases is calculated and presented in this paper.

Keywords: plant diseases, machine learning, image processing, deep learning

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Authors: W. Ait Ahmed, M. Aggour, M. Naciri

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Extracting energy from biomass is an important alternative to produce different types of energy (heat, electricity, or both) assuring low pollution and better efficiency. It is a new yet reliable approach to reduce green gas emission by extracting methane from industry effluents and use it to power machinery. We focused in our project on using paper and mill effluents, treated in a UASB reactor. The methane produced is used in the factory’s power supply. The aim of this work is to develop an electronic system using Arduino platform connected to a gas sensor, to measure and display the curve of daily methane production on processing. The sensor will send the gas values in ppm to the Arduino board so that the later sends the RS232 hardware protocol. The code developed with processing will transform the values into a curve and display it on the computer screen.

Keywords: biogas, Arduino, processing, code, methane, gas sensor, program

Procedia PDF Downloads 328

Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

Procedia PDF Downloads 329

Authors: Hee-Choul Kwon, Heeyong Kwon

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Image rotation is one of main pre-processing steps for image processing or image pattern recognition. It is implemented with a rotation matrix multiplication. It requires a lot of floating point arithmetic operations and trigonometric calculations, so it takes a long time to execute. Therefore, there has been a need for a high speed image rotation algorithm without two major time-consuming operations. However, the rotated image has a drawback, i.e. distortions. We solved the problem using an augmented two-step shear transform. We compare the presented algorithm with the conventional rotation with images of various sizes. Experimental results show that the presented algorithm is superior to the conventional rotation one.

Keywords: high-speed rotation operation, image rotation, transform matrix, image processing, pattern recognition

Procedia PDF Downloads 280

Authors: Dunwen Zuo, Yongfang Deng, Bo Song

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An attempt is made here to measure the forces of three directions, under conditions of different feed speeds, different tilt angles of tool and without or with the pin on the tool, by using octagonal ring dynamometer in the AA2024 aluminum FSJ (Friction Stir Joining) process, and investigate how four main factors influence forces in the FSJ process. It is found that, high feed speed lead to small feed force and small lateral force, but high feed speed leads to large feed force in the stable joining stage of process. As the rotational speed increasing, the time of axial force drop from the maximum to the minimum required increased in the push-up process. In the stable joining stage, the rotational speed has little effect on the feed force; large rotational speed leads to small lateral force and axial force. The maximum axial force increases as the tilt angle of tool increases at the downward movement stage. At the moment of start feeding, as tilt angle of tool increases, the amplitudes of the axial force increasing become large. In the stable joining stage, with the increase of tilt angle of tool, the axial force is increased, the lateral force is decreased, and the feed force almost unchanged. The tool with pin will decrease axial force in the downward movement stage. The feed force and lateral force will increase, but the axial force will reduced in the stable joining stage by using the tool with pin compare to by using the tool without pin.

Keywords: FSJ, force factor, AA2024 aluminum, friction stir joining

Procedia PDF Downloads 495

Authors: Mohammed Bnebaghdad, Feriel Betouche, Malika Semmani

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Image processing become more sophisticated over time due to technological advances, especially artificial intelligence (AI) technology. Currently, AI image processing is used in many areas, including surveillance, industry, science, and medicine. AI in medical image processing can help doctors diagnose diseases faster, with minimal mistakes, and with less effort. Among these diseases is malaria, which remains a major public health challenge in many parts of the world. It affects millions of people every year, particularly in tropical and subtropical regions. Early detection of malaria is essential to prevent serious complications and reduce the burden of the disease. In this paper, we propose and implement a scheme based on AI image processing to enhance malaria disease diagnosis through automated analysis of blood smear images. The scheme is based on the convolutional neural network (CNN) method. So, we have developed a model that classifies infected and uninfected single red cells using images available on Kaggle, as well as real blood smear images obtained from the Central Laboratory of Medical Biology EHS Laadi Flici (formerly El Kettar) in Algeria. The real images were segmented into individual cells using the watershed algorithm in order to match the images from the Kaagle dataset. The model was trained and tested, achieving an accuracy of 99% and 97% accuracy for new real images. This validates that the model performs well with new real images, although with slightly lower accuracy. Additionally, the model has been embedded in a Raspberry Pi4, and a graphical user interface (GUI) was developed to visualize the malaria diagnostic results and facilitate user interaction.

Keywords: medical image processing, malaria parasite, classification, CNN, artificial intelligence

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Authors: Azyz Sharafy

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3D Text Toys is an innovative and creative approach that utilizes 3D text objects to enhance creativity, literacy, and basic learning in an enjoyable and gamified manner. By using 3D Text Toys, children can develop their creativity, visually learn words and texts, and apply their artistic talents within their creative abilities. This process incorporates haptic engagement with 2D and 3D texts, word building, and mechanical construction of everyday objects, thereby facilitating better word and text retention. The concept involves constructing visual objects made entirely out of 3D text/words, where each component of the object represents a word or text element. For instance, a bird can be recreated using words or text shaped like its wings, beak, legs, head, and body, resulting in a 3D representation of the bird purely composed of text. This can serve as an art piece or a learning tool in the form of a 3D text toy. These 3D text objects or toys can be crafted using natural materials such as leaves, twigs, strings, or ropes, or they can be made from various physical materials using traditional crafting tools. Digital versions of these objects can be created using 2D or 3D software on devices like phones, laptops, iPads, or computers. To transform digital designs into physical objects, computerized machines such as CNC routers, laser cutters, and 3D printers can be utilized. Once the parts are printed or cut out, students can assemble the 3D texts by gluing them together, resulting in natural or everyday 3D text objects. These objects can be painted to create artistic pieces or text toys, and the addition of wheels can transform them into moving toys. One of the significant advantages of this visual and creative object-based learning process is that students not only learn words but also derive enjoyment from the process of creating, painting, and playing with these objects. The ownership and creation process further enhances comprehension and word retention. Moreover, for individuals with learning disabilities such as dyslexia, ADD (Attention Deficit Disorder), or other learning difficulties, the visual and haptic approach of 3D Text Toys can serve as an additional creative and personalized learning aid. The application of 3D Text Toys extends to both the English language and any other global written language. The adaptation and creative application may vary depending on the country, space, and native written language. Furthermore, the implementation of this visual and haptic learning tool can be tailored to teach foreign languages based on age level and comprehension requirements. In summary, this creative, haptic, and visual approach has the potential to serve as a global literacy tool.

Keywords: 3D text toys, creative, artistic, visual learning for world literacy

Procedia PDF Downloads 67

Authors: Aasheesh Raturi, Vimal Kothiyal, P. D. Semalty

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We studied mechanical properties of Eucalyptus tereticornis using FT-NIR spectroscopy. Firstly, spectra were pre-processed to eliminate useless information. Then, prediction model was constructed by partial least squares regression. To study the influence of pre-processing on prediction of mechanical properties for NIR analysis of wood samples, we applied various pretreatment methods like straight line subtraction, constant offset elimination, vector-normalization, min-max normalization, multiple scattering. Correction, first derivative, second derivatives and their combination with other treatment such as First derivative + straight line subtraction, First derivative+ vector normalization and First derivative+ multiplicative scattering correction. The data processing methods in combination of preprocessing with different NIR regions, RMSECV, RMSEP and optimum factors/rank were obtained by optimization process of model development. More than 350 combinations were obtained during optimization process. More than one pre-processing method gave good calibration/cross-validation and prediction/test models, but only the best calibration/cross-validation and prediction/test models are reported here. The results show that one can safely use NIR region between 4000 to 7500 cm-1 with straight line subtraction, constant offset elimination, first derivative and second derivative preprocessing method which were found to be most appropriate for models development.

Keywords: FT-NIR, mechanical properties, pre-processing, PLS

Procedia PDF Downloads 364

Authors: Schnell Zsuzsanna

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Background: The interpretation of written texts, language processing in the visual domain, in other words, atypical reading abilities, also known as dyslexia, is an ever-growing phenomenon in today’s societies and educational communities. The much-researched problem affects cognitive abilities and, coupled with normal intelligence normally manifests difficulties in the differentiation of sounds and orthography and in the holistic processing of written words. The factors of susceptibility are varied: social, cognitive psychological, and linguistic factors interact with each other. Methods: The research will explain the psycholinguistics of dyslexia on the basis of several empirical experiments and demonstrate how domain-general abilities of inhibition, retrieval from the mental lexicon, priming, phonological processing, and visual modality transfer affect successful language processing and interpretation. Interpretation of visual stimuli is hindered, and the problem seems to be embedded in a sociocultural, psycholinguistic, and cognitive background. This makes the picture even more complex, suggesting that the understanding and resolving of the issues of dyslexia has to be interdisciplinary, aided by several disciplines in the field of humanities and social sciences, and should be researched from an empirical approach, where the practical, educational corollaries can be analyzed on an applied basis. Aim and applicability: The lecture sheds light on the applied, cognitive aspects of interpretation, social cognitive traits of language processing, the mental underpinnings of cognitive interpretation strategies in different languages (namely, Hungarian and English), offering solutions with a few applied techniques for success in foreign language learning that can be useful advice for the developers of testing methodologies and measures across ESL teaching and testing platforms.

Keywords: dyslexia, social cognition, transparency, modalities

Procedia PDF Downloads 87

Authors: Su-Hyun Jung, Chang-Bin Ha, Hyoung-Kyu Song

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Recently, increasing the quality of experience (QoE) is an important issue. Since performance degradation at cell edge extremely reduces the QoE, several techniques are defined at LTE/LTE-A standard to remove inter-cell interference (ICI). However, the conventional techniques have disadvantage because there is a trade-off between resource allocation and reliable communication. The proposed scheme reduces the ICI more efficiently by using channel state information (CSI) smartly. It is shown that the proposed scheme can reduce the ICI with less resources.

Keywords: adaptive beamforming, CoMP, LTE-A, ICI reduction

Procedia PDF Downloads 472

Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

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This study employs a method based on image analyses and structure information to detect accumulated ice on known structures. The icing of marine vessels and offshore structures causes significant reductions in their efficiency and creates unsafe working conditions. Image processing methods are used to measure ice loads automatically. Most image processing methods are developed based on captured image analyses. In this method, ice loads on structures are calculated by defining structure coordinates and processing captured images. A pyramidal structure is designed with nine cylindrical bars as the known structure of experimental setup. Unsymmetrical ice accumulated on the structure in a cold room represents the actual case of experiments. Camera intrinsic and extrinsic parameters are used to define structure coordinates in the image coordinate system according to the camera location and angle. The thresholding method is applied to capture images and detect iced structures in a binary image. The ice thickness of each element is calculated by combining the information from the binary image and the structure coordinate. Averaging ice diameters from different camera views obtains ice thicknesses of structure elements. Comparison between ice load measurements using this method and the actual ice loads shows positive correlations with an acceptable range of error. The method can be applied to complex structures defining structure and camera coordinates.

Keywords: camera calibration, ice detection, ice load measurements, image processing

Procedia PDF Downloads 369

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 208

Authors: Chin-Chih Chiou, Tai-Yuan Su, Ti-Yu Chen, Wen-Yu Chiu, Chungyu Chen

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The purpose of this study was to investigate the effect of reaction time (RT) or balance performance as the number of stimulus-response choices increases, the amount of information processing of 0-bit and 1-bit conditions based on Hick’s law, using the dual-task design. Eighteen children (age: 9.38 ± 0.27 years old) were recruited as the participants for this study, and asked to assess RT and balance performance separately and simultaneously as following five conditions: simple RT (0-bit decision), choice RT (1-bit decision), single balance control, balance control with simple RT, and balance control with choice RT. Biodex 950-300 balance system and You-Shang response timer were used to record and analyze the postural stability and information processing speed (RT) respectively for the participants. Repeated measures one-way ANOVA with HSD post-hoc test and 2 (balance) × 2 (amount of information processing) repeated measures two-way ANOVA were used to test the parameters of balance performance and RT (α = .05). The results showed the overall stability index in the 1-bit decision was lower than in 0-bit decision, and the mean deflection in the 1-bit decision was lower than in single balance performance. Simple RTs were faster than choice RTs both in single task condition and dual task condition. It indicated that the chronometric approach of RT could use to infer the attention requirement of the secondary task. However, this study did not find that the balance performance is interfered for children by the increasing of the amount of information processing.

Keywords: capacity theory, reaction time, Hick’s law, balance

Procedia PDF Downloads 454

Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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In this paper, altera de1-SoC FPGA board technology is utilized as a distinguished tool for nondestructive characterization of an aluminum circular cylindrical shell of radius ratio b/a (a: outer radius; b: inner radius). The acoustic backscattered signal processing system has been developed using OpenMP architecture. The design is built in three blocks; it is implemented per functional block, in a heterogeneous Intel-Altera system running under Linux. The useful data to determine the performances of SoC FPGA is computed by the analytical method. The exploitation of SoC FPGA has lead to obtain the backscattering form function and resonance spectra. A0 and S0 modes of propagation in the tube are shown. The findings are then compared to those achieved from the Matlab simulation of analytical method. A good agreement has, therefore, been noted. Moreover, the detailed SoC FPGA-based system has shown that acoustic spectra are performed at up to 5 times faster than the Matlab implementation using almost the same data. This FPGA-based system implementation of processing algorithms is realized with a coefficient of correlation R and absolute error respectively about 0.962 and 5 10⁻⁵.

Keywords: OpenMP, signal processing system, acoustic backscattering, nondestructive characterization, thin tubes

Procedia PDF Downloads 94

Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

Procedia PDF Downloads 325

Authors: George Hanna Abdelmelek Henien

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Quality and safety issues are common in Ethiopia's food processing industry, which can negatively impact consumers' health and livelihoods. The country is known for its various agricultural products that are important to the economy. However, food quality and safety policies and management practices in the food processing industry have led to many health problems, foodborne illnesses and economic losses. This article aims to show the causes and consequences of food safety and quality problems in the food processing industry in Ethiopia and discuss possible solutions to solve them. One of the main reasons for food quality and safety in Ethiopia's food processing industry is the lack of adequate regulation and enforcement mechanisms. Inadequate food safety and quality policies have led to inefficiencies in food production. Additionally, the failure to monitor and enforce existing regulations has created a good opportunity for unscrupulous companies to engage in harmful practices that endanger the lives of citizens. The impact on food quality and safety is significant due to loss of life, high medical costs, and loss of consumer confidence in the food processing industry. Foodborne diseases such as diarrhoea, typhoid and cholera are common in Ethiopia, and food quality and safety play an important role in . Additionally, food recalls due to contamination or contamination often cause significant economic losses in the food processing industry. To solve these problems, the Ethiopian government began taking measures to improve food quality and safety in the food processing industry. One of the most prominent initiatives is the Ethiopian Food and Drug Administration (EFDA), which was established in 2010 to monitor and control the quality and safety of food and beverage products in the country. EFDA has implemented many measures to improve food safety, such as carrying out routine inspections, monitoring the import of food products and implementing labeling requirements. Another solution that can improve food quality and safety in the food processing industry in Ethiopia is the implementation of food safety management system (FSMS). FSMS is a set of procedures and policies designed to identify, assess and control food safety risks during food processing. Implementing a FSMS can help companies in the food processing industry identify and address potential risks before they harm consumers. Additionally, implementing an FSMS can help companies comply with current safety and security regulations. Consequently, improving food safety policy and management system in Ethiopia's food processing industry is important to protect people's health and improve the country's economy. . Addressing the root causes of food quality and safety and implementing practical solutions that can help improve the overall food safety and quality in the country, such as establishing regulatory bodies and implementing food management systems.

Keywords: food quality, food safety, policy, management system, food processing industry food traceability, industry 4.0, internet of things, block chain, best worst method, marcos

Procedia PDF Downloads 69

Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

Procedia PDF Downloads 47

Authors: Rahele Mesbah, Nic Van Der Wee, Manja Koenders, Erik Giltay, Albert Van Hemert, Max De Leeuw

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Introduction: Patients with bipolar disorder (BD), characterized by depressive and manic episodes, often suffer from cognitive dysfunction. An up-to-date meta-analysis of functional Magnetic Resonance Imaging (fMRI) studies examining cognitive function in BD is lacking. Objective: The aim of the current fMRI meta-analysis is to investigate brain functioning of bipolar patients compared with healthy subjects within three domains of emotion processing, reward processing, and working memory. Method: Differences in brain regions activation were tested within whole-brain analysis using the activation likelihood estimation (ALE) method. Separate analyses were performed for each cognitive domain. Results: A total of 50 fMRI studies were included: 20 studies used an emotion processing (316 BD and 369 HC) task, 9 studies a reward processing task (215 BD and 213 HC), and 21 studies used a working memory task (503 BD and 445 HC). During emotion processing, BD patients hyperactivated parts of the left amygdala and hippocampus as compared to HC’s, but showed hypoactivation in the inferior frontal gyrus (IFG). Regarding reward processing, BD patients showed hyperactivation in part of the orbitofrontal cortex (OFC). During working memory, BD patients showed increased activity in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC). Conclusions: This meta-analysis revealed evidence for activity disturbances in several brain areas involved in the cognitive functioning of BD patients. Furthermore, most of the found regions are part of the so-called fronto-limbic network which is hypothesized to be affected as a result of BD candidate genes' expression.

Keywords: cognitive functioning, fMRI analysis, bipolar disorder, fronto-limbic network

Procedia PDF Downloads 466

Authors: Jun-Yong Lee, Hyoung-Gook Kim

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In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

Procedia PDF Downloads 429

Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

Procedia PDF Downloads 114

Authors: Cecile Laval, Harriet Lowe

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Processing Instruction is a psycholinguistic pedagogical approach drawing insights from the Input Processing Model which establishes the initial innate strategies used by second language learners to connect form and meaning of linguistic features. With the ever-growing use of technology in Second Language Acquisition research, the present study uses eye-tracking to measure the effectiveness of Processing Instruction in the acquisition of French and its effects on learner’s cognitive strategies. The experiment was designed using a TOBII Pro-TX300 eye-tracker to measure participants’ default strategies when processing French linguistic input and any cognitive changes after receiving Processing Instruction treatment. Participants were drawn from lower intermediate adult learners of French at the University of Greenwich and randomly assigned to two groups. The study used a pre-test/post-test methodology. The pre-tests (one per linguistic item) were administered via the eye-tracker to both groups one week prior to instructional treatment. One group received full Processing Instruction treatment (explicit information on the grammatical item and on the processing strategies, and structured input activities) on the primary target linguistic feature (French past tense imperfective aspect). The second group received Processing Instruction treatment except the explicit information on the processing strategies. Three immediate post-tests on the three grammatical structures under investigation (French past tense imperfective aspect, French Subjunctive used for the expression of doubt, and the French causative construction with Faire) were administered with the eye-tracker. The eye-tracking data showed the positive change in learners’ processing of the French target features after instruction with improvement in the interpretation of the three linguistic features under investigation. 100% of participants in both groups made a statistically significant improvement (p=0.001) in the interpretation of the primary target feature (French past tense imperfective aspect) after treatment. 62.5% of participants made an improvement in the secondary target item (French Subjunctive used for the expression of doubt) and 37.5% of participants made an improvement in the cumulative target feature (French causative construction with Faire). Statistically there was no significant difference between the pre-test and post-test scores in the cumulative target feature; however, the variance approximately tripled between the pre-test and the post-test (3.9 pre-test and 9.6 post-test). This suggests that the treatment does not affect participants homogenously and implies a role for individual differences in the transfer-of-training effect of Processing Instruction. The use of eye-tracking provides an opportunity for the study of unconscious processing decisions made during moment-by-moment comprehension. The visual data from the eye-tracking demonstrates changes in participants’ processing strategies. Gaze plots from pre- and post-tests display participants fixation points changing from focusing on content words to focusing on the verb ending. This change in processing strategies can be clearly seen in the interpretation of sentences in both primary and secondary target features. This paper will present the research methodology, design and results of the experimental study using eye-tracking to investigate the primary effects and transfer-of-training effects of Processing Instruction. It will then provide evidence of the cognitive benefits of Processing Instruction in Second Language Acquisition and offer suggestion in second language teaching of grammar.

Keywords: eye-tracking, language teaching, processing instruction, second language acquisition

Procedia PDF Downloads 281

Authors: Shepherd Manhokwe, Sheron Shoko, Cuthbert Zvidzai

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In the present study, the interactive effects of temperature and cultured bacteria on the performance of a biological treatment system of yeast processing wastewater were investigated. The main objective of this study was to investigate and optimize the operating parameters that reduce organic load and colour. Experiments were conducted based on a Central Composite Design (CCD) and analysed using Response Surface Methodology (RSM). Three dependent parameters were either directly measured or calculated as response. These parameters were total Chemical Oxygen Demand (COD) removal, colour reduction and total solids. COD removal efficiency of 26 % and decolourization efficiency of 44 % were recorded for the wastewater treatment. The optimized conditions for the biological treatment were found to be at 20 g/l cultured bacteria and 25 °C for COD reduction. For colour reduction optimum conditions were temperature of 30.35°C and bacterial formulation of 20g/l. Biological treatment of baker’s yeast processing effluent is a suitable process for the removal of organic load and colour from wastewater, especially when the operating parameters are optimized.

Keywords: COD reduction, optimisation, response surface methodology, yeast processing wastewater

Procedia PDF Downloads 346

Authors: Sun H. Hwang, Young E. Lee, Yunhan Ga, Gilwon Yoon

Abstract:

EEG is a very complex signal with noises and other bio-potential interferences. EOG is the most distinct interfering signal when EEG signals are measured and analyzed. It is very important how to process raw EEG signals in order to obtain useful information. In this study, the EEG signal processing techniques such as EOG filtering and outlier removal were examined to minimize unwanted EOG signals and other noises. The two different mental states of resting and focusing were examined through EEG analysis. A focused state was induced by letting subjects to watch a red dot on the white screen. EEG data for 32 healthy subjects were measured. EEG data after 60-Hz notch filtering were processed by a commercially available EOG filtering and our presented algorithm based on the removal of outliers. The ratio of beta wave to theta wave was used as a parameter for determining the degree of focusing. The results show that our algorithm was more appropriate than the existing EOG filtering.

Keywords: EEG, focus, mental state, outlier, signal processing

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Authors: Dan Wang, Qing Ma, Xiaodan Wang, Tianjiao Qi

Abstract:

The sound of peddling in Beijing, also called “yo-heave-ho” or “cry of one's ware”, is a unique folk culture and usually found in Beijing hutong. For the civilians in Beijing, sound of peddling is part of their childhood. And for those who love the traditional culture of Beijing, it is an old song singing the local conditions and customs of the ancient city. For example, because of his great appreciation, the British poet Osbert Stewart once put sound of peddling which he had heard in Beijing as a street orchestra performance in the article named "Beijing's sound and color".This research aims to collect and integrate the voice/photo resources and historical materials of sound concerning peddling in Beijing by digital technology in order to protect the intangible cultural heritage and pass on the city memory. With the goal in mind, the next stage is to collect and record all the materials and resources based on the historical documents study and interviews with civilians or performers. Then set up a metadata scheme (which refers to the domestic and international standards such as "Audio Data Processing Standards in the National Library", DC, VRA, and CDWA, etc.) to describe, process and organize the sound of peddling into a database. In order to fully show the traditional culture of sound of peddling in Beijing, web design and GIS technology are utilized to establish a website and plan holding offline exhibitions and events for people to simulate and learn the sound of peddling by using VR/AR technology. All resources are opened to the public and civilians can share the digital memory through not only the offline experiential activities, but also the online interaction. With all the attempts, a multi-media narrative platform has been established to multi-dimensionally record the sound of peddling in old Beijing with text, images, audio, video and so on.

Keywords: sound of peddling, GIS, metadata scheme, VR/AR technology

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Authors: Mohammad Aldubyan, Fateh Belaid, Anwar Gasim

Abstract:

This paper aims at linking to link residential energy efficiency to the rebound effect concept, a well-known behavioral phenomenon in which service consumption increases when consumers notice a reduction in monetary spending on energy due to improvements in energy efficiency. It provides insights on into how and why the rebound effect happens when energy efficiency improves and whether this phenomenon is positive or negative. It also shows one technique to estimate the rebound effect on the national residential level. The paper starts with a bird’s eye view of the rebound effect and then dives in in-depth into measuring the rebound effect and evaluating its impact. Finally, the paper estimates the rebound effect in the Saudi residential sector through by linking pre-estimated price elasticities of demand to the Saudi residential building stock.

Keywords: energy efficiency, rebound effect, energy consumption, residential electricity demand

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Authors: Yong-Jun Kim, Jae-Hyun Ro, Chang-Bin Ha, Hyoung-Kyu Song

Abstract:

This paper proposes the cooperative transmission scheme with pre-coding because the cellular communication requires high reliability. The cooperative transmission scheme uses pre-coding method with limited feedback information among small cells. Particularly, the proposed scheme has adaptive mode according to the position of mobile station. Thus, demand of recent wireless communication is resolved by this scheme. From the simulation results, the proposed scheme has better performance compared to the conventional scheme in the cellular network.

Keywords: CDD, cellular network, pre-coding, SPC

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Authors: Miroslav Dumbrovsky, Lucie Larisova

Abstract:

The infiltration characteristic of the soil surface is one of the major factors that determines the potential soil degradation risk. The physical, chemical and biological characteristic of soil is changed by the processing of soil. The infiltration soil ability has an important role in soil and water conservation. The subject of the contribution is the evaluation of the influence of the conventional tillage and reduced tillage technology on soil surface crusting processing and infiltration properties of the soil in the North Bohemia region. Field experimental work at the area was carried out in the years 2013-2016 on Cambisol district medium-heavy clayey soil. The research was conducted on sloping erosion-endangered blocks of compacted arable land. The areas were chosen each year in the way that one of the experimental areas was handled by conventional tillage technologies and the other by reduced tillage technologies. Intact soil samples were taken into Kopecký´s cylinders in the three landscape positions, at a depth of 10 cm (representing topsoil) and 30 cm (representing subsoil). The cumulative infiltration was measured using a mini-disc infiltrometer near the consumption points. The Zhang method (1997), which provides an estimate of the unsaturated hydraulic conductivity K(h), was used for the evaluation of the infiltration tests of the mini-disc infiltrometer. The soil profile processed by conventional tillage showed a higher degree of compaction and soil crusting processing. The bulk density was between 1.10–1.67 g.cm⁻³, compared to the land processed by the reduced tillage technology, where the values were between 0.80–1.29 g.cm⁻³. Unsaturated hydraulic conductivity values were about one-third higher within the reduced tillage technology soil processing.

Keywords: soil crusting processing, unsaturated hydraulic conductivity, cumulative infiltration, bulk density, porosity

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Authors: Cemil Kutlutürk

Abstract:

Hindu culture and religious doctrines such as caste, reincarnation, yoga, nirvana have always proved a popular theme for the film industry. The analyzing of these motifs in the movies with a scientific approach enables to individuals either to comprehend the messages and deep meanings of films or to understand others’ religious beliefs systems and daily lives in a properly way. The primary aim of this study is to handle the subtle influence of Hindu doctrines on cinema industry by focusing on James Cameron’s film, Avatar and its relationship with Hindu concept of avatara by referring to original Hindu sacred texts where this doctrine is basically clarified. The Sanskrit word avatara means to come down or to descend. Although an avatara is commonly considered as an appearance of any deity on earth, the term refers the Vishnu’s descending on earth. When the movie avatar and avatara doctrine are compared, various similarities have noteworthy revealed. Firstly in the movie, Jake is chosen by Eywa to protect Pandora from evils. Similarly in the movie, avatar is born when there is a rise of jealousy and unrighteousness. The same concept is found in avatara doctrine. According to this belief whenever righteousness (dharma) wanes and unrighteousness (adharma) increases God incarnates himself as an avatara. In Hindu tradition, the ten avataras of Vishnu are the most popular. This standard list of ten avataras includes the Fish, the Tortoise, the Boar, the Man-Lion (Narasimha), the Dwarf, Parasurama, Rama, Krishna, the Buddha and Kalki. In the movie the avatar has tail, eyes, nose, ear which is similar to Narasimha (half man-half lion) avatara. On the other hand use of bow and arrow by Navis in the film, evokes us Rama avatara whose basic gun is same. Navis fly on a dragon like bird called Ikra and ride a horse-like quadruped animal. The vehicle for transformation of the avatar in the movie is also resemblance with the idea of Garuda, the great mythical bird, which is used by Vishnu in Hindu mythology. In addition, the last avatara, Kalki, will be seen on a white horse according to Puranas. The basic difference is that for Hinduism avatara means descent of a God, yet in the movie, a human being named Jake Sully, is manifested as humanoid of another planet, this is called as avatar. While in the movie the avatar manifests himself in another planet, Pandora, in Hinduism avataras descent on this world. On the other hand, in Hindu scriptures, there are many avataras and they are categorized according to their functions and attributes. These sides of avatara doctrine cannot be also seen clearly in the film. Even though there are some differences between each other, the main hypothesis of this study is that the general character of the movie is similar to avatara doctrine. In the movie instead of emphasizing on a specific avatara, qualities of different Vishnu avataras have been properly used.

Keywords: film industry, Hinduism, incarnation, James Cameron, movie avatar

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