Search results for: word to vector

Authors: Aiza Dalman

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Words are powerful when these are used wisely and strategically. In this study, twelve (12) campaign speeches of President Donald J. Trump were analyzed as to frequently used words and ethos, pathos and logos being employed. The speeches were read thoroughly, analyzed and interpreted. With the use of Word Counter Tool and Text Analyzer software accessible online, it was found out that the word ‘will’ has the highest frequency of 121, followed by Hillary (58), American (38), going (35), plan and Clinton (32), illegal (30), government (28), corruption (26) and criminal (24). When the speeches were analyzed as to ethos, pathos and logos, on the other hand, it revealed that these were all employed in his speeches. The statements under these pointed out against Hillary or in his favor. The unique strategy of President Donald J. Trump as to frequently used words and ethos, pathos and logos in persuading people perhaps lead the way to his victory.

Keywords: campaign speeches, corpus analysis, ethos, logos and pathos, power of words

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Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

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Authors: Fekri Shawtari

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The banking sector plays a very crucial role in the economic development of the country. As a financial intermediary, it has assigned a great role in the economic growth and stability. This paper aims to examine the empirically the relationship between banking industry and economic growth in state of Qatar. We adopt the VAR vector error correction model (VECM) along with Granger causality to address the issue over the long-run and short-run between the banking sector and economic growth. It is expected that the results will give policy directions to the policymakers to make strategies that are conducive toward boosting development to achieve the targeted economic growth in current situation.

Keywords: economic growth, banking sector, Qatar, vector error correction model, VECM

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Authors: Duong Thuy Nguyen, Giulia Bencini

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The present study examined structural and prosodic factors on the computation of antecedent-reflexive relationships and sentence comprehension in native English (L1) and Vietnamese-English bilinguals (L2). Participants read sentences presented on the computer screen in one of three presentation formats aimed at manipulating prosodic parsing: word-by-word (RSVP), phrase-segment (self-paced), or whole-sentence (self-paced), then completed a grammaticality rating and a comprehension task (following Pratt & Fernandez, 2016). The design crossed three factors: syntactic structure (simple; complex), grammaticality (target-match; target-mismatch) and presentation format. An example item is provided in (1): (1) The actress that (Mary/John) interviewed at the awards ceremony (about two years ago/organized outside the theater) described (herself/himself) as an extreme workaholic). Results showed that overall, both L1 and L2 speakers made use of a good-enough processing strategy at the expense of more detailed syntactic analyses. L1 and L2 speakers’ comprehension and grammaticality judgements were negatively affected by the most prosodically disrupting condition (word-by-word). However, the two groups demonstrated differences in their performance in the other two reading conditions. For L1 speakers, the whole-sentence and the phrase-segment formats were both facilitative in the grammaticality rating and comprehension tasks; for L2, compared with the whole-sentence condition, the phrase-segment paradigm did not significantly improve accuracy or comprehension. These findings are consistent with the findings of Pratt & Fernandez (2016), who found a similar pattern of results in the processing of subject-verb agreement relations using the same experimental paradigm and prosodic manipulation with English L1 and L2 English-Spanish speakers. The results provide further support for a Good-Enough cue model of sentence processing that integrates cue-based retrieval and implicit prosodic parsing (Pratt & Fernandez, 2016) and highlights similarities and differences between L1 and L2 sentence processing and comprehension.

Keywords: anaphora resolution, bilingualism, implicit prosody, sentence processing

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lorenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in a smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore relying on fixed operational models would be inappropriate. This paper presents a study on developing an Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose an Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

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Authors: T. Alghamdi, G. Alaghband

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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

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Authors: K. Frahtia, I. Mihoubi, S. Picot

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Leishmaniasis is a group of parasitic disease with a varied clinical expression caused by flagellate protozoa of the Leishmania genus. These diseases are transmitted to humans and animals by the sting of a vector insect, the female sandfly. Among the groups of dipteral disease vectors, Phlebotominae occupy a prime position and play a significant role in human pathology, such as leishmaniasis that affects nearly 350 million people worldwide. The vector control operation launched by health services throughout the country proves to be effective since despite the prevalence of the disease remains high especially in rural areas, leishmaniasis appears to be declining in Algeria. In this context, this study mainly concerns molecular detection of Leishmania from the vector. Furthermore, a molecular diagnosis has also been made on skin samples taken from patients in the region of Constantine, located in the North-East of Algeria. Concerning the vector, 5858 sandflies were captured, including 4360 males and 1498 females. Male specimens were identified based on their morphological. The morphological identification highlighted the presence of the Phlebotomus genus with a prevalence of 93% against 7% represented by the Sergentomyia genus. About the identified species, P. perniciosus is the most abundant with 59.4% of the male identified population followed by P. longicuspis with 24.7% of the workforce. P. perfiliewi is poorly represented by 6.7% of specimens followed by P. papatasi with 2.2% and 1.5% S. dreyfussi. Concerning skin samples, 45/79 (56.96%) collected samples were found positive by real-time PCR. This rate appears to be in sharp decline compared to previous years (alert peak of 30,227 cases in 2005). Concerning the detection of Leishmania from sandflies by RT-PCR, the results show that 3/60 PCR performed genus are positive with melting temperatures corresponding to that of the reference strain (84.1 +/- 0.4 ° C for L. infantum). This proves that the vectors were parasitized. On the other side, identification by RT-PCR species did not give any results. This could be explained by the presence of an insufficient amount of leishmanian DNA in the vector, and therefore support the hypothesis of the regression of leishmaniasis in Constantine.

Keywords: Algeria, molecular diagnostic, phlebotomus, real time PCR

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

Abstract:

The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

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Authors: Riddhi Jangid, Gajendra Pratap Singh

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Petri nets, a mathematical tool, is used for modeling in different areas of computer sciences, biological networks, chemical systems and many other disciplines. A Petri net model of a given system is created by the graphical representation that describes the properties and behavior of the system. While looking for the behavior of any system, 1-safe Petri nets are of particular interest to many in the application part. Boolean Petri nets correspond to those class in 1- safe Petri nets that generate all the binary n-vectors in their reachability analysis. We study the class by changing different parameters like the token counts in the places and how the structure of the tree changes in the reachability analysis. We discuss here an extended class of Boolean Petri nets that generates n-ary trees in their reachability-based analysis.

Keywords: marking vector, n-vector, petri nets, reachability

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Authors: Jennifer De Paola

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Objectives: The literature is saturated with figures and hard data on happiness and its rates, causes and effects at a large scale, whereas very little is known about the way specific groups of people within societies understand and talk about happiness in their everyday life. The present study contributes to fill this gap in the happiness research by analyzing social representations of happiness among young women through the theoretical frame provided by Moscovici’s Social Representation Theory. Methods: Participants were (N= 351) female students (16-18 year olds) from Finnish, Swedish and English speaking high schools in the Helsinki region, Finland. Main source of data collection were word associations using the stimulus word ‘happiness’ and word associations using as stimulus the term that in the participants’ opinion represents the opposite of happiness. The allowed number of associations was five per stimulus word (10 associations per participant). In total, the 351 participants produced 6973 associations with the two stimulus words given: 3500 (50,19%) associations with ‘happiness’ and 3473 (49,81%) associations with ‘opposite of happiness’. The associations produced were analyzed qualitatively to identify associations with similar meaning and then coded combining similar associations in larger categories. Results: In total, 33 categories were identified respectively for the stimulus word ‘happiness’ and for the stimulus word ‘opposite of happiness’. In general terms, the 33 categories identified for ‘happiness’ included associations regarding relationships with key people considered important, such as ‘family’, abstract concepts such as meaningful life, success and moral values as well as more mundane and hedonic elements like food, pleasure and fun. Similarly, the 33 categories emerged for ‘opposite of happiness’ included relationship problems and arguments, negative feelings such as sadness, depression, stress as well as more concrete issues such as financial problems. Participants were also asked to rate their own level of happiness on a scale from 1 to 10. Results indicated the mean of the self-rated level of happiness was 7,93 (the range varied from 1 to 10; SD = 1, 50). Participants’ responses were further divided into three different groups according to the self-rated level of happiness: group 1 (level 10-9), group 2 (level 8-6), and group 3 (level 5 and lower) in order to investigate the way the categories mentioned above were distributed among the different groups. Preliminary results show that the category ‘family’ is associated with higher level of happiness, whereas its presence gradually decreases among the participants with a lower level of happiness. Moreover, the category ‘depression’ seems to be mainly present among participants in group 3, whereas the category ‘sadness’ is mainly present among participants with higher level of happiness. Conclusion: In conclusion, this study indicates the prevalent ways of thinking about happiness and its opposite among young female students, suggesting that representations varied to some extent depending on the happiness level of the participants. This study contributes to bringing new knowledge as it considers happiness as a holistic state, thus going beyond the literature that so far has too often viewed happiness as a mere unidimensional spectrum.

Keywords: female, happiness, social representations, unhappiness

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Authors: Oluwaponmile D. Alao

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In this paper, two models have been developed to ascertain the best network needed for diagnosis of breast cancer. Breast cancer has been a disease that required the attention of the medical practitioner. Experience has shown that misdiagnose of the disease has been a major challenge in the medical field. Therefore, designing a system with adequate performance for will help in making diagnosis of the disease faster and accurate. In this paper, two models: backpropagation neural network and support vector machine has been developed. The performance obtained is also compared with other previously obtained algorithms to ascertain the best algorithms.

Keywords: breast cancer, data mining, neural network, support vector machine

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Authors: Jamileh Ahmed, Helena Hernandez, Gabriel De Erausquin

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H1N1 virus susceptibility of iPSC-derived DA neurons from schizophrenia patients and controls will compared. C57/BL-6 fibroblasts were reprogrammed into iPSCs using a lenti-viral vector containing SOKM genes. Pluripotency verification with the AP assay and immunocytochemistry ensured iPSC presence. The experimental outcome of ISPCs from DA neuron differentiation will be discussed in the Results section. Fibroblasts from patients and controls will be reprogrammed into iPSCs using a sendai-virus vector containing SOKM. IPSCs will be characterized using the AP assay, immunocytochemistry and RT-PCR. IPSCs will then be differentiated into DA neurons. Gene methylation will be compared for both groups with custom-designed microarrays.

Keywords: schizophrenia, iPSCs, stem cells, neuroscience

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Authors: Azita Ramezani, Atousa Ramezani

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In the ever-escalating landscape of windows malware the necessity for pioneering defense strategies turns into undeniable this study introduces an avant-garde approach fusing the capabilities of clustering random forests and support vector machines SVM to combat the intricate web of cyber threats our fusion model triumphs with a staggering accuracy of 98.67 and an equally formidable f1 score of 98.68 a testament to its effectiveness in the realm of windows malware defense by deciphering the intricate patterns within malicious code our model not only raises the bar for detection precision but also redefines the paradigm of cybersecurity preparedness this breakthrough underscores the potential embedded in the fusion of diverse analytical methodologies and signals a paradigm shift in fortifying against the relentless evolution of windows malicious threats as we traverse through the dynamic cybersecurity terrain this research serves as a beacon illuminating the path toward a resilient future where innovative fusion models stand at the forefront of cyber threat defense.

Keywords: fusion models, cyber threat defense, windows malware, clustering, random forests, support vector machines (SVM), accuracy, f1-score, cybersecurity, malicious code detection

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Authors: Claude Tadonki

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We address the issues related to the computation of the covariance matrix. This matrix is likely to be ill conditioned following its canonical expression, thus consequently raises serious numerical issues. The underlying linear system, which therefore should be solved by means of iterative approaches, becomes computationally challenging. A huge number of iterations is expected in order to reach an acceptable level of convergence, necessary to meet the required accuracy of the computation. In addition, this linear system needs to be solved at each iteration following the general form of the covariance matrix. Putting all together, its comes that we need to compute as fast as possible the associated matrix-vector product. This is our purpose in the work, where we consider and discuss skillful formulations of the problem, then propose a parallel implementation of the matrix-vector product involved. Numerical and performance oriented discussions are provided based on experimental evaluations.

Keywords: covariance-matrix, multicore, numerical computing, parallel computing

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Authors: Bachir Belmadani, Rachid Taleb, Zinelaabidine Boudjema, Adil Yahdou

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Carrier-based methods have been used widely for switching of multilevel inverters due to their simplicity, flexibility and reduced computational requirements compared to space vector modulation (SVM). This paper focuses on Multicarrier Sinusoidal Pulse Width Modulation (MCSPWM) strategy for the three phase Five-Level Flying Capacitor Inverter (5LFCI). The inverter is simulated for Induction Motor (IM) load and Total Harmonic Distortion (THD) for output waveforms is observed for different controlling schemes.

Keywords: flying capacitor inverter, multicarrier sinusoidal pulse width modulation, space vector modulation, total harmonic distortion, induction motor

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: Farhan Beg

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A space vector based pulse width modulation control technique for the three-phase PWM converter is proposed in this paper. The proposed control scheme is based on a synchronous reference frame model. High performance and efficiency is obtained with regards to the DC bus voltage and the power factor considerations of the PWM rectifier thus leading to low losses. MATLAB/SIMULINK are used as a platform for the simulations and a SIMULINK model is presented in the paper. The results show that the proposed model demonstrates better performance and properties compared to the traditional SPWM method and the method improves the dynamic performance of the closed loop drastically. For the space vector based pulse width modulation, sine signal is the reference waveform and triangle waveform is the carrier waveform. When the value of sine signal is larger than triangle signal, the pulse will start producing to high; and then when the triangular signals higher than sine signal, the pulse will come to low. SPWM output will change by changing the value of the modulation index and frequency used in this system to produce more pulse width. When more pulse width is produced, the output voltage will have lower harmonics contents and the resolution will increase.

Keywords: power factor, SVPWM, PWM rectifier, SPWM

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Authors: Fadhl Qutaish

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This paper examines the pharyngealization spread in one of the Yemeni Arabic dialects, namely, Ibbi Arabic (IA). It investigates how pharyngealized sounds spread their acoustic features onto the neighboring vowels and change their default features. This feature has been investigated quietly well in MSA but still has to be deeply studied in the different dialect of Arabic which will bring about a clearer picture of the similarities and the differences among these dialects and help in mapping them based on the way this feature is utilized. Though the studies are numerous, no one of them has illustrated how far in the multi-syllabic word the spread can be and whether it takes a steady or gradient manner. This study tries to fill this gap and give a satisfactory explanation of the pharyngealization spread in Ibbi Dialect. This study is the first step towards a larger investigation of the different dialects of Yemeni Arabic in the future. The data recorded are represented in minimal pairs in which the trigger (pharyngealized or the non-pharyngealized sound) is in the initial or final position of monosyllabic and multisyllabic words. A group of 24 words were divided into four groups and repeated three times by three subjects which will yield 216 tokens that are tested and analyzed. The subjects are three male speakers aged between 28 and 31 with no history of neurological, speaking or hearing problems. All of them are bilingual speakers of Arabic and English and native speakers of Ibbi-Dialect. Recordings were done in a sound-proof room and praat software was used for the analysis and coding of the trajectories of F1 and F2 for the low vowel /a/ to see the effect of pharyngealization on the formant trajectory within the same syllable and in other syllables of the same word by comparing the F1 and F2 formants to the non-pharyngealized environment. The results show that pharyngealization spread is gradient (progressively and regressively). The spread is reflected in the gradual raising of F1 as we move closer towards the trigger and the gradual lowering of F2 as well. The results of the F1 mean values in tri-syllabic words when the trigger is word initially show that there is a raise of 37.9 HZ in the first syllable, 26.8HZ in the second syllable and 14.2HZ in the third syllable. F2 mean values undergo a lowering of 239 HZ in the first syllable, 211.7 HZ in the second syllable and 176.5 in the third syllable. This gradual decrease in the difference of F2 values in the non-pharyngealized and pharyngealized context illustrates that the spread is gradient. A similar result was found when the trigger is word-final which proves that the spread is gradient (progressively and regressively.

Keywords: pharyngealization, Yemeni Arabic, Ibbi dialect, pharyngealization spread

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: H. Yazdani, K. Ghorbanian

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This paper deals with modeling and simulation of the plasma actuator with OpenFOAM. Plasma actuator is one of the newest devices in flow control techniques which can delay separation by inducing external momentum to the boundary layer of the flow. The effects of the plasma actuators on the external flow are incorporated into Navier-Stokes computations as a body force vector which is obtained as a product of the net charge density and the electric field. In order to compute this body force vector, the model solves two equations: One for the electric field due to the applied AC voltage at the electrodes and the other for the charge density representing the ionized air. The simulation result is compared to the experimental and typical values which confirms the validity of the modeling.

Keywords: active flow control, flow-field, OpenFOAM, plasma actuator

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Authors: Dhruba Das

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In this paper, a method has been developed to construct the membership surfaces of row and column vectors and arithmetic operations of imprecise matrix. A matrix with imprecise elements would be called an imprecise matrix. The membership surface of imprecise vector has been already shown based on Randomness-Impreciseness Consistency Principle. The Randomness- Impreciseness Consistency Principle leads to defining a normal law of impreciseness using two different laws of randomness. In this paper, the author has shown row and column membership surfaces and arithmetic operations of imprecise matrix and demonstrated with the help of numerical example.

Keywords: imprecise number, imprecise vector, membership surface, imprecise matrix

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Authors: Abraham Kuruvilla

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Since the inception of Christianity, one of the most important precepts has been that of the ‘word becoming flesh.’ Incarnation, as we understand it, is that the ‘word became flesh.’ As we know, it is a commonly held understanding that the concept of Logos was borrowed from the Greek religion. Such understanding has dominated our thought process. This is problematic as it does not draw out the deep roots of Logos. The understanding of Logos also existed in religion such as Hinduism. For the Hindu faith, the understanding of Shabd is pivotal. It could be arguably equated with the understanding of the Logos. The paper looks into the connection of the primal Christian doctrine of the Logos with that of the Hindu understanding of Shabd. The methodology of the paper would be a comparative theological analysis with the New Testament understanding of the Logos with that of the understanding of Shabd as perceived in the different Vedas of the Hindu faith. The paper would come to the conclusion that there is a conceptual connectivity between Logos and the Shabd. As such the understanding of Logos cannot just be attributed to the Greek understanding of Logos, but rather it predates the Greek understanding of Logos by being connected to the Hindu understanding of Shabd. Accordingly, such comparison brings out the implication for a constructive dialogue between Christianity and the Hindu faith.

Keywords: Christianity, Hinudism, Logos, Shabd

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Authors: Aleksandra Zysk, Pawel Badura

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Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: classification, singing, spectral analysis, vocal emission, vocal register

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Authors: Mamyrbek A. Beisenbi, Nurgul M. Kissikova, Saltanat E. Beisembina, Salamat T. Suleimenova, Samal A. Kaliyeva

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The paper proposes a method for constructing a self-organizing control system for unstable and deterministic chaotic processes in the class of catastrophe “hyperbolic umbilic” for objects with m-inputs and n-outputs. The self-organizing control system is investigated by the universal gradient-velocity method of Lyapunov vector functions. The conditions for self-organization of the control system in the class of catastrophes “hyperbolic umbilic” are shown in the form of a system of algebraic inequalities that characterize the aperiodic robust stability in the stationary states of the system.

Keywords: gradient-velocity method of Lyapunov vector-functions, hyperbolic umbilic, self-organizing control system, stability

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Authors: S. Kherchaoui, A. Houacine

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This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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Authors: Mohammed Arif, Abdessalam Kifouche

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Speech is a very convenient way of communication between people and machines. It conveys information about the identity of the talker. Since speaker recognition technology is increasingly securing our everyday lives, the objective of this paper is to develop two automatic text-independent speaker verification systems (TI SV) using low-level spectral features and machine learning methods. (i) The first system is based on a support vector machine (SVM), which was widely used in voice signal processing with the aim of speaker recognition involving verifying the identity of the speaker based on its voice characteristics, and (ii) the second is based on Gaussian Mixture Model (GMM) and Universal Background Model (UBM) to combine different functions from different resources to implement the SVM based.

Keywords: speaker verification, text-independent, support vector machine, Gaussian mixture model, cepstral analysis

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Authors: Bahareh Yousefian, Laurel Smith Stvan

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Linguistic structures have two facades: form and meaning. These structures could have either literal meaning or figurative meaning (although it could also depend on the context in which that structure appears). The literal meaning is understandable more easily, but for the figurative meaning, a word or concept is understood from a different word or concept. In linguistic structures with a figurative meaning, it’s more difficult to relate their forms to the meanings than structures with literal meaning. In these cases, the relationship between form and figurative meaning could be studied from different perspectives. Various linguists have been curious about what happens in someone’s mind to understand figurative meaning through the forms; they have used different perspectives and theories to explain this process. It has been studied through cognitive linguistics as well, in which mind and mental activities are really important. In this viewpoint, meaning (in other words, conceptualization) is considered a mental process. In this descriptive-analytic study, 20 Persian compound nouns with figurative meanings have been collected from the Persian-language Moeen Encyclopedic Dictionary and other sources. Examples include [“Sofreh Xaneh”] (traditional restaurant) and [“Dast Yar”] (Assistant). These were studied in a cognitive semantics framework using “Conceptual Blending Theory” which hasn’t been tested on Persian compound nouns before. It was noted that “Conceptual Blending Theory” could lead to the process of understanding the figurative meanings of Persian compound nouns. Many cognitive linguists believe that “Conceptual Blending” is not only a linguistic theory but it’s also a basic human cognitive ability that plays important roles in thought, imagination, and even everyday life as well (though unconsciously). The ability to use mental spaces and conceptual blending (which is exclusive to humankind) is such a basic but unconscious ability that we are unaware of its existence and importance. What differentiates Conceptual Blending Theory from other ways of understanding figurative meaning, are arising new semantic aspects (emergent structure) that lead to a more comprehensive and precise meaning. In this study, it was found that Conceptual Blending Theory could explain reaching the figurative meanings of Persian compound nouns from their forms, such as [talkative for compound word of “Bolbol + Zabani” (nightingale + tongue)] and [wage for compound word of “Dast + Ranj” (hand + suffering)].

Keywords: cognitive linguistics, conceptual blending, figurative meaning, Persian compound nouns

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Authors: Alejandro Paz Parra, Jose Luis Oslinger Gutierrez, Javier Olaya Ochoa

Abstract:

In the present paper, five electric current based methods to analyze electric faults on the stator of induction motors (IM) are used and compared. The analysis tries to extend the application of the multiple reference frames diagnosis technique. An eccentricity indicator is presented to improve the application of the Park’s Vector Approach technique. Most of the fault indicators are validated and some others revised, agree with the technical literatures and published results. A tri-phase 3hp squirrel cage IM, especially modified to establish different fault levels, is used for validation purposes.

Keywords: motor fault diagnosis, induction motor, MCSA, ESA, Extended Park´s vector approach, multiparameter analysis

Procedia PDF Downloads 337

Authors: Arun Goel

Abstract:

The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free over-fall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, support vector machine (Polynomial and rbf) models, and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free over-fall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: air entrainment rate, dissolved oxygen, weir, SVM, regression

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Authors: Wanqing He

Abstract:

The current study explores aspects of exploratory behaviors and social capacities in urban Chinese infants to examine whether these factors mediate the link between infant walking and receptive and productive vocabularies. The linkage between the onset of walking and language attainment proves solid, but little is known about the factors that drive such link. This study examined whether joint attention, gesture use, and object activities mediate the association between locomotion and language development. Results showed that both the frequency (p = .05) and duration (p = .03) of carrying an object are strong mediators that afford opportunities for word comprehension. Also, accessing distal objects may be beneficial to infants’ language expression. Further studies on why object carrying may account for word comprehension and why infants with autism could not benefit from walking onset in terms of language development may yield valuable clinical implications.

Keywords: exploratory behaviors, infancy, language acquisition, motor development, social communicative skills

Procedia PDF Downloads 106