Search results for: mobility features

Authors: Robert L. Burdett, Bayan Bevrani

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Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways, these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

Keywords: capacity analysis, capacity expansion, railways, track sub division, track duplication

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Authors: Jae-Neung Lee, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. Examples of yacht Simulator using Yacht Simulator include image processing for totaling the total number of vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT (scale invariant features transform) matching, and application of median filter and thresholding.

Keywords: yacht simulator, simulator, trends analysis, SIFT

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Authors: Teimuraz Manjapharashvili, Ketevani Manjaparashvili

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Fuzzy logic is a modeling method for complex or ill-defined systems and is a relatively new mathematical approach. Its basis is to consider overlapping cases of parameter values and define operations to manipulate these cases. Fuzzy logic can successfully create operative automatic management or appropriate advisory systems. Fuzzy logic techniques in various operational control technologies have grown rapidly in the last few years. Fuzzy logic is used in many areas of human technological activity. In recent years, fuzzy logic has proven its great potential, especially in the automation of industrial process control, where it allows to form of a control design based on the experience of experts and the results of experiments. The engineering of chemical technological processes uses fuzzy logic in optimal management, and it is also used in process control, including the operational control of continuous cycle chemical industrial, technological processes, where special features appear due to the continuous cycle and correct management acquires special importance. This paper discusses how intelligent systems can be developed, in particular, how fuzzy logic can be used to build knowledge-based expert systems in chemical process engineering. The implemented projects reveal that the use of fuzzy logic in technological process control has already given us better solutions than standard control techniques. Fuzzy logic makes it possible to develop an advisory system for decision-making based on the historical experience of the managing operator and experienced experts. The present paper deals with operational control and management systems of continuous cycle chemical technological processes, including advisory systems. Because of the continuous cycle, many features are introduced in them compared to the operational control of other chemical technological processes. Among them, there is a greater risk of transitioning to emergency mode; the return from emergency mode to normal mode must be done very quickly due to the impossibility of stopping the technological process due to the release of defective products during this period (i.e., receiving a loss), accordingly, due to the need for high qualification of the operator managing the process, etc. For these reasons, operational control systems of continuous cycle chemical technological processes have been specifically discussed, as they are different systems. Special features of such systems in control and management were brought out, which determine the characteristics of the construction of control and management systems. To verify the findings, the development of an advisory decision-making information system for operational control of a lime kiln using fuzzy logic, based on the creation of a relevant expert-targeted knowledge base, was discussed. The control system has been implemented in a real lime production plant with a lime burn kiln, which has shown that suitable and intelligent automation improves operational management, reduces the risks of releasing defective products, and, therefore, reduces costs. The special advisory system was successfully used in the said plant both for the improvement of operational management and, if necessary, for the training of new operators due to the lack of an appropriate training institution.

Keywords: chemical process control systems, continuous cycle industrial technological processes, fuzzy logic, lime kiln

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Shantanu Arya, Sachin Sakhuja, Gunjan Mehta, Sanjay Munjal

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Stuttering may be defined as a speech disorder affecting the fluency domain of speech and characterized by covert features like word substitution, omittance and circumlocution and overt features like prolongation of sound, syllables and blocks etc. Many etiologies have been postulated to explain stuttering based on various experiments and research. Moreover, Breathlessness has also been reported by many individuals with stuttering for which breathing exercises are generally advised. However, no studies reporting objective evaluation of the pulmonary capacity and further objective assessment of the efficacy of breathing exercises have been conducted. Pulmonary Function Test which evaluates parameters like Forced Vital Capacity, Peak Expiratory Flow Rate, Forced expiratory flow Rate can be used to study the pulmonary behavior of individuals with stuttering. The study aimed: a) To identify speech motor & physiologic behaviours associated with stuttering by administering PFT. b) To recognize possible reasons for an association between speech motor behaviour & stuttering severity. In this regard, PFT tests were administered on individuals who reported signs and symptoms of stuttering and showed abnormal scores on Stuttering Severity Index. Parameters like Forced Vital Capacity, Forced Expiratory Volume, Peak Expiratory Flow Rate (L/min), Forced Expiratory Flow Rate (L/min) were evaluated and correlated with scores of Stuttering Severity Index. Results showed significant decrease in the parameters (lower than normal scores) in individuals with established stuttering. Strong correlation was also found between degree of stuttering and the degree of decrease in the pulmonary volumes. Thus, it is evident that fluent speech requires strong support of lung pressure and requisite volumes. Further research in demonstrating the efficacy of abdominal breathing exercises in this regard is needed.

Keywords: forced expiratory flow rate, forced expiratory volume, forced vital capacity, peak expiratory flow rate, stuttering

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Authors: Vivek Krishna, Nikhil Jain, A. Mary Posonia A., Albert Mayan J

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Terrorism and insurgency are significant global issues that require constant attention and effort from governments and scientists worldwide. To combat these threats, nations invest billions of dollars in developing new defensive technologies to protect civilians. Breakthroughs in vehicle automation have led to the use of sophisticated machines for many dangerous and critical anti-terrorist activities. Our concept of an "Unmanned Ground Vehicle" can carry out tasks such as border security, surveillance, mine detection, and active combat independently or in tandem with human control. The robot's movement can be wirelessly controlled by a person in a distant location or can travel to a pre-programmed destination autonomously in situations where personal control is not feasible. Our defence system comprises two units: the control unit that regulates mobility and the motion tracking unit. The remote operator robot uses the camera's live visual feed to manually operate both units, and the rover can automatically detect movement. The rover is operated by manpower who controls it using a joystick or mouse, and a wireless modem enables a soldier in a combat zone to control the rover via an additional controller feature.

Keywords: robotics, computer vision, Machine learning, Artificial intelligence, future of AI

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Authors: G. V. Novikov, V. S. Sivozhelezov, S. S. Kolesnikov, K. V. Shaitan

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The study reports about the influence of binding of orthosteric ligands as well as point mutations on the conformational dynamics of β-2-adrenoreceptor. Using molecular dynamics simulation we found that there was a little fraction of active states of the receptor in its apo (ligand free) ensemble corresponded to its constitutive activity. Analysis of MD trajectories indicated that such spontaneous activation of the receptor is accompanied by the motion in intracellular part of its alpha-helices. Thus receptor’s constitutive activity directly results from its conformational dynamics. On the other hand the binding of a full agonist resulted in a significant shift of the initial equilibrium towards its active state. Finally, the binding of the inverse agonist stabilized the receptor in its inactive state. It is likely that the binding of inverse agonists might be a universal way of constitutive activity inhibition in vivo. Our results indicate that ligand binding redistribute pre-existing conformational degrees of freedom (in accordance to the Monod-Wyman-Changeux-Model) of the receptor rather than cause induced fit in it. Therefore, the ensemble of biologically relevant receptor conformations is encoded in its spatial structure, and individual conformations from that ensemble might be used by the cell in conformity with the physiological behaviour.

Keywords: seven-transmembrane receptors, constitutive activity, activation, x-ray crystallography, principal component analysis, molecular dynamics simulation

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Carlos Gonzalez

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This paper describes the use of the Internet as a feature to enhance the security of our software that is going to be distributed/sold to users potentially all over the world. By placing in a secure server some of the features of the secure software, we increase the security of such software. The communication between the protected software and the secure server is done by a double lock algorithm. This paper also includes an analysis of intruders and describes possible responses to detect threats.

Keywords: internet, secure software, threats, cryptography process

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Authors: Elham Bagheri, Yalda Mohsenzadeh

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Image memorability refers to the phenomenon where certain images are more likely to be remembered by humans than others. It is a quantifiable and intrinsic attribute of an image. Understanding how visual perception and memory interact is important in both cognitive science and artificial intelligence. It reveals the complex processes that support human cognition and helps to improve machine learning algorithms by mimicking the brain's efficient data processing and storage mechanisms. To explore the computational underpinnings of image memorability, this study examines the relationship between an image's reconstruction error, distinctiveness in latent space, and its memorability score. A trained autoencoder is used to replicate human-like memorability assessment inspired by the visual memory game employed in memorability estimations. This study leverages a VGG-based autoencoder that is pre-trained on the vast ImageNet dataset, enabling it to recognize patterns and features that are common to a wide and diverse range of images. An empirical analysis is conducted using the MemCat dataset, which includes 10,000 images from five broad categories: animals, sports, food, landscapes, and vehicles, along with their corresponding memorability scores. The memorability score assigned to each image represents the probability of that image being remembered by participants after a single exposure. The autoencoder is finetuned for one epoch with a batch size of one, attempting to create a scenario similar to human memorability experiments where memorability is quantified by the likelihood of an image being remembered after being seen only once. The reconstruction error, which is quantified as the difference between the original and reconstructed images, serves as a measure of how well the autoencoder has learned to represent the data. The reconstruction error of each image, the error reduction, and its distinctiveness in latent space are calculated and correlated with the memorability score. Distinctiveness is measured as the Euclidean distance between each image's latent representation and its nearest neighbor within the autoencoder's latent space. Different structural and perceptual loss functions are considered to quantify the reconstruction error. The results indicate that there is a strong correlation between the reconstruction error and the distinctiveness of images and their memorability scores. This suggests that images with more unique distinct features that challenge the autoencoder's compressive capacities are inherently more memorable. There is also a negative correlation between the reduction in reconstruction error compared to the autoencoder pre-trained on ImageNet, which suggests that highly memorable images are harder to reconstruct, probably due to having features that are more difficult to learn by the autoencoder. These insights suggest a new pathway for evaluating image memorability, which could potentially impact industries reliant on visual content and mark a step forward in merging the fields of artificial intelligence and cognitive science. The current research opens avenues for utilizing neural representations as instruments for understanding and predicting visual memory.

Keywords: autoencoder, computational vision, image memorability, image reconstruction, memory retention, reconstruction error, visual perception

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Anželika Teresė

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In order to solve issues in sign language linguistics, address matters pertaining to maintaining high quality of sign language (SL) translation, contribute to dispelling misconceptions about SL and deaf people, and raise awareness and understanding of the deaf community heritage, this presentation discusses literature in Lithuanian Sign Language (LSL) and inherent metaphors that are created by using the phonological parameter –handshape, location, movement, palm orientation and nonmanual features. The study covered in this presentation is twofold, involving both the micro-level analysis of metaphors in terms of phonological parameters as a sub-lexical feature and the macro-level analysis of the poetic context. Cognitive theories underlie research of metaphors in sign language literature in a range of SL. The study follows this practice. The presentation covers the qualitative analysis of 34 pieces of LSL literature. The analysis employs ELAN software widely used in SL research. The target is to examine how specific types of each phonological parameter are used for the creation of metaphors in LSL literature and what metaphors are created. The results of the study show that LSL literature employs a range of metaphors created by using classifier signs and by modifying the established signs. The study also reveals that LSL literature tends to create reference metaphors indicating status and power. As the study shows, LSL poets metaphorically encode status by encoding another meaning in the same sign, which results in creating double metaphors. The metaphor of identity has been determined. Notably, the poetic context has revealed that the latter metaphor can also be identified as a metaphor for life. The study goes on to note that deaf poets create metaphors related to the importance of various phenomena significance of the lyrical subject. Notably, the study has allowed detecting locations, nonmanual features and etc., never mentioned in previous SL research as used for the creation of metaphors.

Keywords: Lithuanian sign language, sign language literature, sign language metaphor, metaphor at the phonological level, cognitive linguistics

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Authors: Reynaldo Esquivel, Pedro Hernandez, Aaron Martinez-Higareda, Sergio Tena-Cano, Enrique Alvarez-Ramos, Armando Lucero-Acuna

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Stimuli-responsive nanomaterials play an essential role in loading, transporting and well-distribution of anti-cancer compounds in the cellular surroundings. The outstanding properties as the Lower Critical Solution Temperature (LCST), hydrolytic cleavage and protonation/deprotonation cycle, govern the release and delivery mechanisms of payloads. In this contribution, we experimentally determine the load efficiency and release of antineoplastic Vincristine Sulfate into PNIPAM-Interpenetrated-Chitosan (PIntC) nanoparticles. Structural analysis was performed by Fourier Transform Infrared Spectroscopy (FT-IR) and Proton Nuclear Magnetic Resonance (1HNMR). ζ-Potential (ζ) and Hydrodynamic diameter (DH) measurements were monitored by Electrophoretic Mobility (EM) and Dynamic Light scattering (DLS) respectively. Mathematical analysis of the release pharmacokinetics reveals a three-phase model above LCST, while a monophasic of Vincristine release model was observed at 32 °C. Cytotoxic essays reveal a noticeable enhancement of Vincristine effectiveness at low drug concentration on HeLa cervix cancer and MDA-MB-231 breast cancer.

Keywords: nanoparticles, vincristine, drug delivery, PNIPAM

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Authors: Ioannis Andrianakis, Panagiotis Panagiotopoulos, Kyriakos Chatzidimitriou, Dimitrios Tampakis, Manolis Falelakis

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Live music, whether performed in organized venues, restaurants, hotels or any other spots, creates value chains that support and develop local economies and tourism development. In this paper, we describe PerformAnts, a platform that increases the mobility of musicians and their accessibility to remotely located venues by rationalizing the cost of live acts. By analyzing the event history and taking into account their potential availability, the platform provides bespoke recommendations to both bands and venues while also facilitating the organization of tours and helping rationalize transportation expenses by realizing an innovative mechanism called “chain booking”. Moreover, the platform provides an environment where complicated tasks such as technical and financial negotiations, concert promotion or copyrights are easily manipulated by users using best practices. The proposed solution provides important benefits to the whole spectrum of small/medium size concert organizers, as the complexity and the cost of the production are rationalized. The environment is also very beneficial for local talent, musicians that are very mobile, venues located away from large urban areas or in touristic destinations, and managers who will be in a position to coordinate a larger number of musicians without extra effort.

Keywords: machine learning, music industry, creative industries, web applications

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Authors: Mariem Saied, Jens Gustedt, Gilles Muller

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We present Dido, a source-to-source auto-generation and optimization framework for multi-dimensional stencil computations. It enables a large programmer community to easily and safely implement stencil codes on distributed-memory parallel architectures with Ordered Read-Write Locks (ORWL) as an execution and communication back-end. ORWL provides inter-task synchronization for data-oriented parallel and distributed computations. It has been proven to guarantee equity, liveness, and efficiency for a wide range of applications, particularly for iterative computations. Dido consists mainly of an implicitly parallel domain-specific language (DSL) implemented as a source-level transformer. It captures domain semantics at a high level of abstraction and generates parallel stencil code that leverages all ORWL features. The generated code is well-structured and lends itself to different possible optimizations. In this paper, we enhance Dido to handle both Jacobi and Gauss-Seidel grid traversals. We integrate temporal blocking to the Dido code generator in order to reduce the communication overhead and minimize data transfers. To increase data locality and improve intra-node data reuse, we coupled the code generation technique with the polyhedral parallelizer Pluto. The accuracy and portability of the generated code are guaranteed thanks to a parametrized solution. The combination of ORWL features, the code generation pattern and the suggested optimizations, make of Dido a powerful code generation framework for stencil computations in general, and for distributed-memory architectures in particular. We present a wide range of experiments over a number of stencil benchmarks.

Keywords: stencil computations, ordered read-write locks, domain-specific language, polyhedral model, experiments

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Authors: Mrinal Kanti Bhowmik, Debanjana Debnath Jr., Debotosh Bhattacharjee

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A facial expression is undeniably the human manners. It is a significant channel for human communication and can be applied to extract emotional features accurately. People in pain often show variations in facial expressions that are readily observable to others. A core of actions is likely to occur or to increase in intensity when people are in pain. To illustrate the changes in the facial appearance, a system known as Facial Action Coding System (FACS) is pioneered by Ekman and Friesen for human observers. According to Prkachin and Solomon, a set of such actions carries the bulk of information about pain. Thus, the Prkachin and Solomon pain intensity (PSPI) metric is defined. So, it is very important to notice that facial expressions, being a behavioral source in communication media, provide an important opening into the issues of non-verbal communication in pain. People express their pain in many ways, and this pain behavior is the basis on which most inferences about pain are drawn in clinical and research settings. Hence, to understand the roles of different pain behaviors, it is essential to study the properties. For the past several years, the studies are concentrated on the properties of one specific form of pain behavior i.e. facial expression. This paper represents a comprehensive study on pain assessment that can model and estimate the intensity of pain that the patient is suffering. It also reviews the historical background of different pain assessment techniques in the context of painful expressions. Different approaches incorporate FACS from psychological views and a pain intensity score using the PSPI metric in pain estimation. This paper investigates in depth analysis of different approaches used in pain estimation and presents different observations found from each technique. It also offers a brief study on different distinguishing features of real and fake pain. Therefore, the necessity of the study lies in the emerging fields of painful face assessment in clinical settings.

Keywords: facial action coding system (FACS), pain, pain behavior, Prkachin and Solomon pain intensity (PSPI)

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Authors: Aiche Mohamed Amine, Mallem Leila, Yahia El Khansa, Boulakoud Mohamed Salah

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Until recently, toxicological studies focused on the effects of individual chemicals. However, humans and wildlife are exposed to a complex milieu of chemicals from different sources including food and water, personal care products and the environment. The aim of this study is to detect the toxicity of two fungicides and their mixtures in the fertility and oxidative damge induced in the rat. The male of rats (28) were used, they were divided in four groups (7 rats of each group) and one group was used as control. Rats were dosed orally with Propiconazole 60mg/Kg/day, Propinebe 100mg/Kg/day and their mixture 30mg Propiconazole/kg/day + 50mg Propineb/kg/day for 4 weeks. Animals were observed for clinical toxicity. At the end of treatment period, animals of all groups were scarified, blood was collected for hematological and biochemical’s analysis and desired organs were removed and weighted. The results indicated that the fungicide and their mixture were toxic in the treated animals. The semen study showed a decrease in the count and mobility of spermatozoa in all treated group, it was also a decrease in the weight of the testis and epidydimis in the treated group as compared with control. Reduced glutathione (GSH), Glutathione peroxidase (GPx) level was decreased in all treated groups.

Keywords: fungicides, mixtures, fertility, oxidative stress

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Authors: Carmela Perta

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In Italy the coexistence of standard language, its varieties and different minority languages - historical and migration languages - has been a way to study language contact in different directions; the focus of most of the studies is either the relations among the languages of the social repertoire, or the study of contact phenomena occurring in a particular structural level. However, studies on contact facts in relation to a given sociolinguistic situation of the speech community are still not present in literature. As regard the language level to investigate from the perspective of contact, it is commonly claimed that the lexicon is the most volatile part of language and most likely to undergo change due to superstrate influence, indeed first lexical features are borrowed, then, under long term cultural pressure, structural features may also be borrowed. The aim of this paper is to analyse language contact in two historical minority communities where Francoprovençal is spoken, in relation to their sociolinguistic situation. In this perspective, firstly lexical borrowings present in speakers’ speech production will be examined, trying to find a possible correlation between this part of the lexicon and informants’ sociolinguistic variables; secondly a possible correlation between a particular community sociolinguistic situation and lexical borrowing will be found. Methods used to collect data are based on the results obtained from 24 speakers in both the villages; the speaker group in the two communities consisted of 3 males and 3 females in each of four age groups, ranging in age from 9 to 85, and then divided into five groups according to their occupations. Speakers were asked to describe a sequence of pictures naming common objects and then describing scenes when they used these objects: they are common objects, frequently pronounced and belonging to semantic areas which are usually resistant and which are thought to survive. A subset of this task, involving 19 items with Italian source is examined here: in order to determine the significance of the independent variables (social factors) on the dependent variable (lexical variation) the statistical package SPSS, particularly the linear regression, was used.

Keywords: borrowing, Francoprovençal, language change, lexicon

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Authors: Ayesha Agha Shah

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The purpose of a mosque or a place of worship is to build a spiritual relation with God. If the sense of spirituality is not achieved, then sacred architecture appears to be lacking depth. Form and space play a significant role to enhance the architectural quality to impart a divine feel to a place. To achieve this divine feeling, form and space, and unity of opposites, either abstract or symbolic can be employed. It is challenging to imbue the emptiness of a space with qualitative experience. Mosque architecture mostly entails traditional forms and design typology. This approach for Muslim worship produces distinct landmarks in the urban neighborhoods of Muslim societies, while creating a great sense of spirituality. The universal symbolic characters in the mosque architecture had prototype geometrical forms for a long time in history. However, modern mosques have deviated from this approach to employ different built elements and symbolism, which are often hard to be identified as related to mosques or even as Islamic. This research aims to explore the sense of spirituality in modern mosques and questions whether the modification of geometrical features produce spirituality in the same manner. The research also seeks to investigate the role of ‘geometry’ in the modern mosque architecture. The research employs the analytical study of some modern mosque examples in the Kingdom of Bahrain, reflecting on the geometry and symbolism adopted in the new mosque architecture design. It buttresses the analysis by the engagement of people’s perceptions derived using a survey of opinions. The research expects to see the significance of geometrical architectural elements in the mosque designs. It will find answers to the questions such as; what is the role of the form of the mosque, interior spaces and the effect of the modified symbolic features in the modern mosque design? How can the symbolic geometry, forms and spaces of a mosque invite a believer to leave the worldly environment behind and move towards spirituality?

Keywords: geometry, mosque architecture, spirituality, symbolism

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Authors: Khatuna Buskivadze

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The aim of the present study is to investigate the sociolinguistic and classroom functions and frequency of Teacher’s Code Switching (CS) in the Content and Language Integrated (CLIL) Lesson. Nowadays, Georgian society struggles to become the part of the European world, the English language itself plays a role in forming new generations with European values. Based on our research conducted in 2019, out of all 114 private schools in Tbilisi, full- programs of CLIL are taught in 7 schools, while only some subjects using CLIL are conducted in 3 schools. The goal of the former research was to define the features of Content and Language Integrated learning (CLIL) methodology within the process of teaching English on the Example of Georgian private high schools. Taking the Georgian reality and cultural features into account, the modified version of the questionnaire, based on the classification of using CS in ESL Classroom proposed By Ferguson (2009) was used. The qualitative research revealed students’ and teacher’s attitudes towards teacher’s code-switching in CLIL lesson. Both qualitative and quantitative research were conducted: the observations of the teacher’s lessons (Recording of T’s online lessons), interview and the questionnaire among Math’s T’s 20 high school students. We came to the several conclusions, some of them are given here: Math’s teacher’s CS behavior mostly serves (1) the conversational function of interjection; (2) the classroom functions of introducing unfamiliar materials and topics, explaining difficult concepts, maintaining classroom discipline and the structure of the lesson; The teacher and 13 students have negative attitudes towards using only Georgian in teaching Math. The higher level of English is the more negative is attitude towards using Georgian in the classroom. Although all the students were Georgian, their competence in English is higher than in Georgian, therefore they consider English as an inseparable part of their identities. The overall results of the case study of teaching Math (Educational discourse) in one of the private schools in Tbilisi will be presented at the conference.

Keywords: attitudes, bilingualism, code-switching, CLIL, conversation analysis, interactional sociolinguistics.

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Authors: Chayonnat Thanamun, Kreangkrai Maneeintr

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For petroleum industry, polymer flooding is the one of the main methods in enhanced oil recovery (EOR) that is used water-soluble polymer such as partially hydrolyzed polyacrylamide (HPAM) to increase oil production. It is added to the flooding water to improve the mobility ratio in the flooding process. During the polymer flooding process, water is produced as a by-product along with oil and gas production. This produced water is a mixture of inorganic and organic compound. Moreover, produced water is more difficult to treat than that from water flooding. In this work, the effect of HPAM residue on the wastewater treatment from polymer flooding is studied. Polyaluminium chloride (PAC) is selected to use as a flocculant. Therefore, the objective of this study is to evaluate the effect of polymer residues in produced water on the wastewater treatment by using PAC. The operating parameters of this study are flocculant dosage ranging from 300,400 and 500 mg/L temperature from 30-50 Celsius degree and HPAM concentrations from 500, 1000 and 2000 mg/L. Furthermore, the turbidity, as well as total suspended solids (TSS), are also studied. The results indicated that with an increase in HPAM concentration, the TSS and turbidity increase gradually with the increasing of coagulant dosage under the same temperature. Also, the coagulation-flocculation performance is improved with the increasing temperature. This can be applied to use in the wastewater treatment from oil production before this water can be injected back to the reservoir.

Keywords: wastewater treatment, petroleum production, polyaluminium chloride, polyacrylamide

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Authors: Zakheleni P. Dube, Phatu W. Mashela

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The Curve-fitting Allelochemical Response Data (CARD) model had been adopted as a valuable tool in enhancing the understanding of the efficacy of cucurbitacin-containing phytonematicides on the suppression of nematodes. In most cases, for registration purposes, the active ingredients should be in purified form. Evidence in other phytonematicides suggested that purified active ingredients were less effective in suppression of nematodes. The objective of this study was to use CARD model to compare the overall sensitivities of Meloidogyne incognita J2 hatch, mobility and mortality to Nemarioc-AL phytonematicides, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B. Meloidogyne incognita eggs and J2 were exposed to 0.00, 0.50, 1.00, 1.50, 2.00, 2.50, 3.00, 3.50, 4.00, 4.50 and 5.00% of each phytonematicide, whereas in purified form the concentrations were 0.00, 0.25, 0.50, 0.75, 1.00, 1.25, 1.50, 1.75, 2.00, 2.25 and 2.50 μg.mL⁻¹. The exposure period to each concentration was 24-, 48- and 72-h. The overall sensitivities of J2 hatch to Nemarioc-AL phytonematicide, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B were 1, 30, 5 and 2 units, respectively, whereas J2 mobiltity were 3, 17, 3 and 6 units, respectively. For J2 mortality overall sensitivities to Nemarioc-AL phytonematicide, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B were 2, 4, 1 and 4 units, respectively. In conclusion, the two crude extracts, Nemarioc-AL and Nemafric-BL phytonematicides were generally more potent to M. incognita compared to their pure active ingredients. The crude plant extract preparation is easy, and they could be an ideal tactic for the management of nematodes in resource poor farming communities.

Keywords: Botanicals, cucumin, leptodermin, plant extracts, triterpenoids

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Authors: Dermot O'Brien, Vasileios Christaras, Georgios Fontaras, Igor Nai Fovino, Ioannis Kounelis

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With the rise of the Internet of Things (IoT), 5G, and blockchain (BC) technologies, vehicles are becoming ever increasingly connected and are already transmitting substantial amounts of data to the original equipment manufacturers (OEMs) servers. This data could be used to help detect mileage fraud and enable more accurate vehicle emissions monitoring. This would not only help regulators but could enable applications such as permitting efficient drivers to pay less tax, geofencing for air quality improvement, as well as pollution tolling and trading platforms for transport-related businesses and EU citizens. Other applications could include traffic management and shared mobility systems. BC enables the transmission of data with additional security and removes single points of failure while maintaining data provenance, identity ownership, and the possibility to retain varying levels of privacy depending on the requirements of the applied use case. This research performs simulations of vehicles interacting with European member state authorities and European Commission BC nodes that are running hyperleger fabric and explores whether the technology is currently feasible for transport applications such as the emission monitoring use-case.

Keywords: future transportation systems, technological innovations, policy approaches for transportation future, economic and regulatory trends, blockchain

Procedia PDF Downloads 176

Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

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In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

Procedia PDF Downloads 150

Authors: Bhavishya Ramchandani

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A little electronic device that is worn on the finger is called a smart ring. It incorporates mobile technology and has features that make it simple to use the device. These gadgets, which resemble conventional rings and are usually made to fit on the finger, are outfitted with features including access management, gesture control, mobile payment processing, and activity tracking. A poor sleep pattern, an irregular schedule, and bad eating habits are all part of the problems with health that a lot of people today are facing. Diets lacking fruits, vegetables, legumes, nuts, and whole grains are common. Individuals in India also experience metabolic issues. In the medical field, smart rings will help patients with problems relating to stomach illnesses and the incapacity to consume meals that are tailored to their bodies' needs. The smart ring tracks all bodily functions, including blood sugar and glucose levels, and presents the information instantly. Based on this data, the ring generates what the body will find to be perfect insights and a workable site layout. In addition, we conducted focus groups and individual interviews as part of our core approach and discussed the difficulties they're having maintaining the right diet, as well as whether or not the smart ring will be beneficial to them. However, everyone was very enthusiastic about and supportive of the concept of using smart rings in healthcare, and they believed that these rings may assist them in maintaining their health and having a well-balanced diet plan. This response came from the primary data, and also working on the Emerging Technology Canvas Analysis of smart rings in healthcare has led to a significant improvement in our understanding of the technology's application in the medical field. It is believed that there will be a growing demand for smart health care as people become more conscious of their health. The majority of individuals will finally utilize this ring after three to four years when demand for it will have increased. Their daily lives will be significantly impacted by it.

Keywords: smart ring, healthcare, electronic wearable, emerging technology

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Authors: J. Szoltysek, S. Twarog

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The happy city, as the desired effect of changes implemented by cities, involves the deliberate and purposeful evolution of material and spiritual space in which residents pursue happiness, as it is perceived collectively and individually. The quality of life (QoL) has, for many years, been researched as one of the dimensions of happiness. Both literature studies and the observation of how cities function lead to the conclusion that the happy city is the city of meetings. The importance of meeting spaces in cities for the quality of life has been confirmed also for Polish cities and, as a result, the conclusions may be drawn that public space should be planned in such a manner so as to tailor it – to the greatest possible degree – to the needs of the residents of Polish cities. The study embraced both Polish and foreign data concerning both the dimension of the quality of life in cities and the issues related to the existence of common spaces where meetings take place. Both quantitative and qualitative analytical techniques have been used to analyze and interpret the data collected. We sought the answers to the questions on the significance of the factors, identified by the respondents, which affect the QoL in a city. We identified 9 mega factors: being, work, education, recreation, health and safety, mobility, neighborhood, acceptance, agora. We established the preferences of the QoL in relation to the size of a city and the public spaces, that seem to be the cornerstone of the happy city.

Keywords: city, meetings, public spaces, social cohesion, quality of life

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Authors: Serkan Sayin, Songul F. Varol

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High attention on the organic light-emitting diodes has been paid since their efficient properties in the flat panel displays, and solid-state lighting was realized. Because of their high efficient electroluminescence, brightness and providing eminent in the emission range, organic light emitting diodes have been preferred a material compared with the other materials consisting of the liquid crystal. Calixarenes obtained from the reaction of p-tert-butyl phenol and formaldehyde in a suitable base have been potentially used in various research area such as catalysis, enzyme immobilization, and applications, ion carrier, sensors, nanoscience, etc. In addition, their tremendous frameworks, as well as their easily functionalization, make them an effective candidate in the applied chemistry. Herein, a calix[4]arene derivative has been synthesized, and its structure has been fully characterized using Fourier Transform Infrared Spectrophotometer (FTIR), proton nuclear magnetic resonance (¹H-NMR), carbon-13 nuclear magnetic resonance (¹³C-NMR), liquid chromatography-mass spectrometry (LC-MS), and elemental analysis techniques. The calixarene derivative has been employed as an emitting layer in the fabrication of the organic light-emitting diodes. The optical and electrochemical features of calixarane-contained organic light-emitting diodes (Clx-OLED) have been also performed. The results showed that Clx-OLED exhibited blue emission and high external quantum efficacy. As a conclusion obtained results attributed that the synthesized calixarane derivative is a promising chromophore with efficient fluorescent quantum yield that provides it an attractive candidate for fabricating effective materials for fluorescent probes and labeling studies. This study was financially supported by the Scientific and Technological Research Council of Turkey (TUBITAK Grant no. 117Z402).

Keywords: calixarene, OLED, supramolecular chemistry, synthesis

Procedia PDF Downloads 253

Authors: Ruichong Zhang, Fadi Sawaged, Lotfi Gargab

Abstract:

This paper introduces a wave-based approach for system identification of high-rise building structures with a pair of seismic recordings, which can be used to evaluate structural integrity and detect damage in post-earthquake structural condition assessment. The fundamental of the approach is based on wave features of generalized impulse and frequency response functions (GIRF and GFRF), i.e., wave responses at one structural location to an impulsive motion at another reference location in time and frequency domains respectively. With a pair of seismic recordings at the two locations, GFRF is obtainable as Fourier spectral ratio of the two recordings, and GIRF is then found with the inverse Fourier transformation of GFRF. With an appropriate continuous model for the structure, a closed-form solution of GFRF, and subsequent GIRF, can also be found in terms of wave transmission and reflection coefficients, which are related to structural physical properties above the impulse location. Matching the two sets of GFRF and/or GIRF from recordings and the model helps identify structural parameters such as wave velocity or shear modulus. For illustration, this study examines ten-story Millikan Library in Pasadena, California with recordings of Yorba Linda earthquake of September 3, 2002. The building is modelled as piecewise continuous layers, with which GFRF is derived as function of such building parameters as impedance, cross-sectional area, and damping. GIRF can then be found in closed form for some special cases and numerically in general. Not only does this study reveal the influential factors of building parameters in wave features of GIRF and GRFR, it also shows some system-identification results, which are consistent with other vibration- and wave-based results. Finally, this paper discusses the effectiveness of the proposed model in system identification.

Keywords: wave-based approach, seismic responses of buildings, wave propagation in structures, construction

Procedia PDF Downloads 233

Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

Abstract:

The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching, including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders, including Ghana Football Association (GFA), to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

Procedia PDF Downloads 69

Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

Abstract:

The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders including Ghana Football Association (GFA) to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

Procedia PDF Downloads 62