Search results for: emotion detection in the text

Authors: Jihad S. Daba, J. P. Dubois

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Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

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Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: Bing Li, Tong Lu, Lei Qiang

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Stoneley waves are interface waves that propagate at the interface between two solid media. In this study, the dispersion characteristics and wave structures of Stoneley waves in elastic multilayered plates are displayed and investigated. With a perspective of bulk wave, a reasonable assumption of the potential function forms of the expansion wave and shear wave in nth layer medium is adopted, and the characteristic equation of Stoneley waves in a three-layered plate is given in a determinant form. The dispersion curves and wave structures are solved and presented in both numerical and simulation results. It is observed that two Stoneley wave modes exist in a three-layered plate, that conspicuous dispersion occurs on low frequency band, that the velocity of each Stoneley wave mode approaches the corresponding Stoneley wave velocity at interface between two half infinite spaces. The wave structures reveal that the in-plane displacement of Stoneley waves are relatively high at interfaces, which shows great potential for interface defects detection.

Keywords: characteristic equation, interface waves, potential function, Stoneley waves, wave structure

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Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Sharul T. Tajuddin, Hartiny Md Azmi

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Taking into consideration the real time situation specifically the higher academic institutions, small, medium to large companies, public to private sectors and the remaining sectors, do experience the inventory or asset shrinkages due to theft, loss or even inventory tracking errors. This happening is due to a zero or poor security systems and measures being taken and implemented in their organizations. Henceforth, implementing the Radio Frequency Identification (RFID) technology into any manual or existing web-based system or web application can simply deter and will eventually solve certain major issues to serve better data retrieval and data access. Having said, this manual or existing system can be enhanced into a mobile-based system or application. In addition to that, the availability of internet connections can aid better services of the system. Such involvement of various technologies resulting various privileges to individuals or organizations in terms of accessibility, availability, mobility, efficiency, effectiveness, real-time information and also security. This paper will look deeper into the integration of mobile devices with RFID technologies with the purpose of asset tracking and control. Next, it is to be followed by the development and utilization of MongoDB as the main database to store data and its association with RFID technology. Finally, the development of a web based system which can be viewed in a mobile based formation with the aid of Hypertext Preprocessor (PHP), MongoDB, Hyper-Text Markup Language 5 (HTML5), Android, JavaScript and AJAX programming language.

Keywords: RFID, asset tracking system, MongoDB, NoSQL

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Sang Hun Park, Chul Gyu Song

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Artery and vein occlusion changes observed in patients and experimental animals are unexplainable symptoms. As the fat accumulated in cardiovascular ruptures, it causes vascular blocking. Likewise, early detection of cardiovascular disease can be useful for treatment. In this study, we used the mouse femoral occlusion model to observe the arterial and venous occlusion changes without darkroom. We observed the femoral arterial flow pattern changes by proposed fluorescent imaging system using an animal model of thrombosis. We adjusted the near-infrared light source current in order to control the intensity of the fluorescent substance light. We got the clear fluorescent images and femoral artery flow pattern were measured by a 5-minute interval. The result showed that the fluorescent substance flowing in the femoral arteries were accumulated in thrombus as time passed, and the fluorescence of other vessels gradually decreased.

Keywords: thrombus, fluorescence, femoral, arteries

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Authors: Martina Katalin Szabó, István Üveges

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In this paper, the usage of negative emotive words is examined on the basis of a large Hungarian twitter-database via NLP methods. The data is analysed from a gender point of view, as well as changes in language usage over time. The term negative emotive word refers to those words that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g. rohadt jó ’damn good’) or a sentiment expression with positive polarity despite their negative prior polarity (e.g. brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’. Based on the findings of several authors, the same phenomenon can be found in other languages, so it is probably a language-independent feature. For the recent analysis, 67783 tweets were collected: 37818 tweets (19580 tweets written by females and 18238 tweets written by males) in 2016 and 48344 (18379 tweets written by females and 29965 tweets written by males) in 2021. The goal of the research was to make up two datasets comparable from the viewpoint of semantic changes, as well as from gender specificities. An exhaustive lexicon of Hungarian negative emotive intensifiers was also compiled (containing 214 words). After basic preprocessing steps, tweets were processed by ‘magyarlanc’, a toolkit is written in JAVA for the linguistic processing of Hungarian texts. Then, the frequency and collocation features of all these words in our corpus were automatically analyzed (via the analysis of parts-of-speech and sentiment values of the co-occurring words). Finally, the results of all four subcorpora were compared. Here some of the main outcomes of our analyses are provided: There are almost four times fewer cases in the male corpus compared to the female corpus when the negative emotive intensifier modified a negative polarity word in the tweet (e.g., damn bad). At the same time, male authors used these intensifiers more frequently, modifying a positive polarity or a neutral word (e.g., damn good and damn big). Results also pointed out that, in contrast to female authors, male authors used these words much more frequently as a positive polarity word as well (e.g., brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’). We also observed that male authors use significantly fewer types of emotive intensifiers than female authors, and the frequency proportion of the words is more balanced in the female corpus. As for changes in language usage over time, some notable differences in the frequency and collocation features of the words examined were identified: some of the words collocate with more positive words in the 2nd subcorpora than in the 1st, which points to the semantic change of these words over time.

Keywords: gender differences, negative emotive words, semantic changes over time, twitter

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Authors: Ivana Loncarevic, Biljana Pajin, Ivana Vasiljevic, Milana Lazovic, Danica Mrkajic, Aleksandar Fises, Strahinja Kovacevic

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Biscuits belong to a group of flour-confectionery products that are considerably consumed worldwide. The basic raw material for their production is wheat flour or integral flour as a nutritionally highly valuable component. However, this raw material is also a potential source of contamination since it may contain the residues of biochemical compounds originating from plant and soil protection agents. Therefore, it is necessary to examine the health safety of both raw materials and final products. The aim of this research was to examine the content of undesirable residues of pesticides (mostly organochlorine pesticides, organophosphorus pesticides, carbamate pesticides, triazine pesticides, and pyrethroid pesticides) in 30 different biscuit samples of domestic origin present on the Vojvodina market using Gas Chromatograph Thermo ISQ/Trace 1300. The results showed that all tested samples had the limit of detection of pesticide content below 0.01 mg/kg, indicating that this type of confectionary products is not contaminated with pesticides.

Keywords: biscuits, pesticides, contamination, quality

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Authors: Yuhui Liu, Lydia Speyer, Jasmin Wertz, Ingrid Obsuth

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Childhood adversities refer to situations where a child's basic needs for safety and support are compromised, leading to substantial disruptions in their emotional, cognitive, social, or neurobiological development. Given the prevalence of adversities (8%-39%), their impact on developmental outcomes is challenging to completely avoid. Delinquency is an important consequence of childhood adversities, given its potential causing violence and other forms of victimisation, influencing victims, delinquents, their families, and the whole of society. Studying mediators helps explain the link between childhood adversity and delinquency, which aids in designing effective intervention programs that target explanatory variables to disrupt the path and mitigate the effects of childhood adversities on delinquency. The Dimensional Model of Adversity and Psychopathology suggests that threat-based adversities influence outcomes through emotion processing, while deprivation-based adversities do so through cognitive mechanisms. Thus, considering a wide range of threat-based and deprivation-based adversities and their co-occurrence and their associations with delinquency through cognitive and emotional mechanisms is essential. This study employs the Millennium Cohort Study, tracking the development of approximately 19,000 individuals born across England, Scotland, Wales and Northern Ireland, representing a nationally representative sample. Parallel mediation models compare the mediating roles of self-esteem (cognitive) and depression (affective) in the associations between childhood adversities and delinquency. Eleven types of childhood adversities were assessed both individually and through latent class analysis, considering adversity experiences from birth to early adolescence. This approach aimed to capture how threat-based, deprived-based, or combined threat and deprived-based adversities are associated with delinquency. Eight latent classes were identified: three classes (low adversity, especially direct and indirect violence; low childhood and moderate adolescent adversities; and persistent poverty with declining bullying victimisation) were negatively associated with delinquency. In contrast, three classes (high parental alcohol misuse, overall high adversities, especially regarding household instability, and high adversity) were positively associated with delinquency. When mediators were included, all classes showed a significant association with delinquency through depression, but not through self-esteem. Among the eleven single adversities, seven were positively associated with delinquency, with five linked through depression and none through self-esteem. The results imply the importance of affective variables, not just for threat-based but also deprivation-based adversities. Academically, this suggests exploring other mechanisms linking adversities and delinquency since some adversities are linked through neither depression nor self-esteem. Clinically, intervention programs should focus on affective variables like depression to mitigate the effects of childhood adversities on delinquency.

Keywords: childhood adversity, delinquency, depression, self-esteem

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Xiaohui Wang, Zhichuan Guan, Roman Shor, Chuanbin Xu

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Early monitoring and real-time quantitative description of gas intrusion under the premise of ensuring the integrity of the drilling fluid circulation system will greatly improve the accuracy and effectiveness of deepwater gas-kick monitoring. Therefore, in order to study the propagation characteristics of ultrasonic waves in the gas-liquid two-phase flow within the marine riser, in this paper, a numerical simulation method of ultrasonic propagation in the annulus of the riser was established, and the credibility of the numerical analysis was verified by the experimental results of the established gas intrusion monitoring simulation experimental device. The numerical simulation can solve the sound field in the gas-liquid two-phase flow according to different physical models, and it is easier to realize the single factor control. The influence of each parameter on the received signal can be quantitatively investigated, and the law with practical guiding significance can be obtained.

Keywords: gas-kick detection, ultrasonic, void fraction, coda wave velocity

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Authors: Hailyie Tekleselase

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Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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Authors: José Eugenio Ortiz, Pierre Plaza, Josefa Herrero, Iván Cabria, José Luis Blanco, Javier Gavilanes, José Ignacio Escavy, Ignacio López-Cilla, Virginia Yagüe, César Pérez, Silvia Rodríguez, Jorge Rico, Cecilia Serrano, Jesús Bernat

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The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: aggregates, artificial intelligence, automatization, mining operations

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Authors: Ripon Sarkar, Kabita Chaterjee, Ananya Barui

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Smoking is one of the leading causes of oral cancer. Cigarette smoke affects various cellular parameters and alters molecular metabolism of cells. Epithelial cells losses their cytoskeleton structure, membrane integrity, cellular polarity that subsequently initiates the process of epithelial cells to mesenchymal transition due to long exposure of cigarette smoking. It changes the normal cellular metabolic activity which induces oxidative stress and enhances the reactive oxygen spices (ROS) formation. Excessive ROS and associated oxidative stress are considered to be a driving force in alteration in cellular phenotypes, polarity distribution and mitochondrial metabolism. Noninvasive assessment of such parameters plays essential role in development of routine screening system for early diagnosis of oral cancer. Electrical cell-substrate impedance sensing (ECIS) is one of such method applied for detection of cellular membrane impedance which can be correlated to cell membrane integrity. Present study intends to explore the alteration in cellular impedance along with the expression of cellular polarity molecules and cytoskeleton distributions in oral epithelial cells of habitual smokers and to correlate the outcome to that of clinically diagnosed oral leukoplakia and oral squamous cell carcinoma patients. Total 80 subjects were categorized into four study groups: nonsmoker (NS), cigarette smoker (CS), oral leukoplakia (OLPK) and oral squamous cell carcinoma (OSCC). Cytoskeleton distribution was analyzed by staining of actin filament and generation of ROS was measured using assay kit using standard protocol. Cell impedance was measured through ECIS method at different frequencies. Expression of E-cadherin and protease-activated receptor (PAR) proteins were observed through immune-fluorescence method. Distribution of actin filament is well organized in NS group however; distribution pattern was grossly varied in CS, OLPK and OSCC. Generation of ROS was low in NS which subsequently increased towards OSCC. Expressions of E-cadherin and change in cellular electrical impedance in different study groups indicated the hallmark of cancer progression from NS to OSCC. Expressions of E-cadherin, PAR protein, and cell impedance were decreased from NS to CS and farther OSCC. Generally, the oral epithelial cells exhibit apico-basal polarity however with cancer progression these cells lose their characteristic polarity distribution. In this study expression of polarity molecule and ECIS observation indicates such altered pattern of polarity among smoker group. Overall the present study monitored the alterations in intracellular ROS generation and cell metabolic function, membrane integrity in oral epithelial cells in cigarette smokers. Present study thus has clinical significance, and it may help in developing a noninvasive technique for early diagnosis of oral cancer amongst susceptible individuals.

Keywords: cigarette smoking, early oral cancer detection, electric cell-substrate impedance sensing, noninvasive screening

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Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: R. Gadea, J. M. Monzó, F. J. Puertas, M. Castro, A. Tebar, P. J. Fito, R. J. Colom

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There exists a wide array of ailments impacting the structural soundness of the esophageal walls, predominantly linked to digestive issues. Presently, the techniques employed for identifying esophageal tract complications are excessively invasive and discomforting, subjecting patients to prolonged discomfort in order to achieve an accurate diagnosis. This study proposes the creation of a sensor with profound measuring capabilities designed to detect fluids coursing through the esophageal tract. The multi-sensor detection system relies on radiofrequency photospectrometry. During experimentation, individuals representing diverse demographics in terms of gender and age were utilized, positioning the sensors amidst the trachea and diaphragm and assessing measurements in vacuum conditions, water, orange juice, and saline solutions. The findings garnered enabled the identification of various liquid mediums within the esophagus, segregating them based on their ionic composition.

Keywords: radiofrequency spectrophotometry, medical device, gastroesophageal disease, photonics

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Authors: Ghadeer M Alkusayer, Adelicia Yu, Pamela Orr

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Study objective: To report a case of postpartum pulmonary cryptococcal infection (CCI) in an otherwise healthy 35-year-old woman. Additionally, the cases of pulmonary cryptococcal infections either in the antepartum or the postpartum period with pregnancy outcomes, were systematically reviwed. Methods: A systematic search of Cochrane Library, MEDLINE, and EMBASE was conducted for peer-reviewed studies without date restrictions, published in English and relating to CCI during pregnancy or postpartum period. Conference press, editorials, opinion pieces and letters were excluded. Two authors independently screened citations and full-text articles, extracted data and assessed study quality. Given the heterogeneity of study designs, a narrative synthesis was conducted. Results: The search identified 128 references, of which 22 case reports and series met the inclusion criteria. This is a total of 29 women (including the current case) . The mean age of the women was 28.3 ± 12.3 years. Nine (31.03%) presented and were diagnosed in the postpartum period. Two (6.90%) of the patients were reported as immunocompromised with HIV. Four maternal deaths (13.79%) were found in this case series with one (4.3%) patient with severe neurological deficits. Four (17.4%) infant deaths were reported. Women primary presentation varied with chest pain 13 (44.82%), headache 10 (35.70%), dyspnea 19 (65.51%), or fever 12 (41.38%). Three studies reported placental pathology positive for C. neoformans. Conclusion: This case of pulmonary cryptococcal infection in the postpartum period is an important addition to the literature of this rare infection in pregnancy. The patient is not immunocompromised. The patient was successfully treated with 4 months of Fluconazole 400 mg and continued to breastfeed the healthy baby.

Keywords: pulmonary cryptococcus, pregnancy, cryptococci , postpartum

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Authors: Hannah Kuhar

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This paper delves into the attitudes of professional and semi-professional rugby union athletes in regard to socio-emotional vulnerability, or the willingness to express the full spectrum of human emotion in a social context. Like all humans, athletes of all sports regularly experience feelings of shame, powerlessness, and loneliness, and often feel unable to express such feelings due to factors including lack of situational support, absence of adequate expressive language and lack of resource. To this author’s knowledge, however, no previous research has considered the particular demographic of professional rugby union athletes, despite the sport’s immense popularity and economic contribution to global communities. Hence, this paper aims to extend previous research by exploring the experiences of professional rugby union athletes and their unwillingness and inability to express socio-emotional vulnerability. By having a better understanding of vulnerability in rugby and sports, this paper is able to contribute to the growing field of mental health and wellbeing research, particularly towards the emerging themes of resilience and belonging. Based on qualitative fieldwork conducted over a period of seven months across France and Australia, via the mechanisms of semi-structured interview and observation, this work uses the field theory framework of Pierre Bourdieu to construct an analysis of multidisciplinary thought. Approaching issues of gender, sexuality, physicality, education, and family, this paper shows that socio-emotional vulnerability is experienced by all players regardless of their background, in a variety of ways. Common themes and responses are drawn to show the universality of rugby’s pitfalls, which have previously been limited to specific demographics in isolation of their broader contexts. With the author themselves a semi-professional athlete, the provision of unique ‘insider’ access facilitates a deeper and more comprehensive understanding of first-hand athlete experiences, often unexplored within the context of the academic arena. The primary contention of this paper is to argue that by celebrating socio-emotional vulnerability, there becomes an opportunity to improve on-field team outcomes. Ultimately, players play better when they feel supported by their teammates, and this logic extends to the outcome of the team when socio-emotional team initiatives are widely embraced. The creation of such a culture requires deliberate and purposeful efforts, where player ownership and buy-in are high. Further study in this field may assist teams to better understand the elements which contribute to strong team culture and to strong results on the pitch.

Keywords: rugby, vulnerability, athletes, France, Bourdieu

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Authors: Balachandra Kumaraswamy, P. G. Poonacha

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Automatic Music Information Retrieval has been one of the challenging topics of research for a few decades now with several interesting approaches reported in the literature. In this paper we have developed a pitch extraction method based on a finite Fourier series approximation to the given window of samples. We then estimate pitch as the fundamental period of the finite Fourier series approximation to the given window of samples. This method uses analysis of the strength of harmonics present in the signal to reduce octave as well as harmonic errors. The performance of our method is compared with three best known methods for pitch extraction, namely, Yin, Windowed Special Normalization of the Auto-Correlation Function and Harmonic Product Spectrum methods of pitch extraction. Our study with artificially created signals as well as music files show that Fourier Approximation method gives much better estimate of pitch with less octave and harmonic errors.

Keywords: pitch, fourier series, yin, normalization of the auto- correlation function, harmonic product, mean square error

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Ifeanyichukwu Valerie Oguafor

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Women generally have been categorized and placed under the chain of business industry, sometimes highly regarded and other times merely. The social construction of womanhood does not in all sense support a woman going into business, let alone succeed in it because it is believed that it a man’s world. In a typical patriarchal setting, a woman is expected to know nothing more domestic roles. For some women, this is not the case as they have been able to break these barriers to excel in business amidst these social setting and stereotypes. This study examines media representation of Nigerians business women, using content analysis of TV interviews as media text, framing analysis as an approach in qualitative methodology, The study further aims to analyse media frames of two Nigerian business women: FolorunshoAlakija, a business woman in the petroleum industry with current net worth 1.1 billion U.S dollars, emerging as the richest black women in the world 2014. MosunmolaAbudu, a media magnate in Nigeria who launched the first Africa’s global black entertainment and lifestyle network in 2013. This study used six predefined frames: the business woman, the myth of business women, the non-traditional woman, women in leading roles, the family woman, the religious woman, and the philanthropist woman to analyse the representation of Nigerian business women in the media. The analysis of the aforementioned frames on TV interviews with these women reveals that the media perpetually reproduces existing gender stereotype and do not challenge patriarchy. Women face challenges in trying to succeed in business while trying to keep their homes stable. This study concludes that the media represent and reproduce gender stereotypes in spite of the expectation of empowering women. The media reduces these women’s success insignificant rather than a role model for women in society.

Keywords: representation of business women in the media, business women in Nigeria, framing in the media, patriarchy, women's subordination

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Authors: Y. Laib Dit Leksir, S. Bouhouche

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Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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Authors: Agata Chudzicka-Czupała, Nadiya Hapon, Liudmyla Karamushka, Marta żywiołek-Szeja

Abstract:

Objectives: The study is about the determinants of coping with stress connected with volunteer activity for Russo-Ukrainian war 2022 refugees. We examined the mental health reactions, chosen psychological traits, and motivational functions of volunteers working in Poland and Ukraine in relation to their coping with stress styles. The study was financed with funds from the Foundation for Polish Science in the framework of the FOR UKRAINE Programme. Material and Method: The study was conducted in 2022. The study was a quantitative, questionnaire-based survey. Data was collected through an online survey. The volunteers were asked to assess their propensity to use different styles of coping with stress connected with their activity for Russo-Ukrainian war refugees using The Brief Coping Orientation to Problems Experienced Inventory (Brief-COPE) questionnaire. Depression, anxiety, and stress were measured using the Depression, Anxiety, and Stress (DASS)-21 item scale. Chosen psychological traits, psychological capital and hardiness, were assessed by The Psychological Capital Questionnaire and The Norwegian Revised Scale of Hardiness (DRS-15R). Then The Volunteer Function Inventory (VFI) was used. The significance of differences between the variable means of the samples was tested by the Student's t-test. We used multivariate linear regression to identify factors associated with coping with stress styles separately for each national sample. Results: The sample consisted of 720 volunteers helping war refugees (in Poland, 435 people, and 285 in Ukraine). The results of the regression analysis indicate variables that are significant predictors of the propensity to use particular styles of coping with stress (problem-focused style, emotion-focused style and avoidant coping). These include levels of depression and stress, individual psychological characteristics and motivational functions, different for Polish and Ukrainians. Ukrainian volunteers are significantly more likely to use all three coping with stress styles than Polish ones. The results also prove significant differences in the severity of anxiety, stress and depression, the selected psychological traits and motivational functions studied, which led volunteers to participate in activities for war refugees. Conclusions: The results show that depression and stress severity, as well as psychological capital and hardiness, and motivational factors are connected with coping with stress behavior. The results indicate the need for increased attention to the well-being of volunteers acting under stressful conditions. They also prove the necessity of guiding the selection of people for specific types of volu

Keywords: anxiety, coping with stress styles, depression, hardiness, mental health, motivational functions, psychological capital, resilience, stress, war, volunteer, civil society

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Authors: Tzu-Hao Li, Yen-Ying Kung, Chang-Youh Tsai

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Oral dryness is a common chief complaint among patients with Sjőgren syndrome (SS), which is a disorder currently known as autoantibodies production; however, to author’s best knowledge, there has been no satisfying pharmacy to relieve the associated symptoms. Hence the effectiveness of other non-pharmacological interventions such as acupuncture should be accessed. We conducted a meta-analysis of randomized clinical trials (RCTs) which evaluated the effectiveness of xerostomia in SS. PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Chongqing Weipu Database (CQVIP), China Academic Journals Full-text Database, AiritiLibrary, Chinese Electronic Periodicals Service (CEPS), China National Knowledge Infrastructure (CNKI) Database were searches through May 12, 2018 to select studies. Data for evaluation of subjective and objective xerostomia was extracted and was assessed with random-effects meta-analysis. After searching, a total of 541 references were yielded and five RCTs were included, covering 340 patients dry mouth resulted from SS, among whom 169 patients received acupuncture and 171 patients were control group. Acupuncture group was associated with higher subjective response rate (odds ratio 3.036, 95% confidence interval [CI] 1.828 – 5.042, P < 0.001) and increased salivary flow rate (weighted mean difference [WMD] 3.066, 95% CI 2.969 – 3.164, P < 0.001), as an objective marker. In addition, two studies examined IgG levels, which were lower in the acupuncture group (WMD -166.857, 95% CI -233.138 - -100.576, P < 0.001). Therefore, in the present meta-analysis, acupuncture improves both subjective and objective markers of dry mouth with autoantibodies reduction in patients with SS and is considered as an option of non-pharmacological treatment for SS.

Keywords: acupuncture, meta-analysis, Sjogren syndrome, xerostomia

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Authors: Tian-Fang Kang, Chao-Nan Ge, Rui Li

Abstract:

An electrochemical biosensor for the determination of organophosphorus pesticides was developed based on electrochemical co-deposition of Au and Pd nanoparticles on glassy carbon electrode (GCE). Energy disperse spectroscopy (EDS) analysis was used for characterization of the surface structure. Scanning electron micrograph (SEM) demonstrates that the films are uniform and the nanoclusters are homogeneously distributed on the GCE surface. Acetylcholinesterase (AChE) was immobilized on the Au and Pd nanoparticle modified electrode (Au-Pd/GCE) by cross-linking with glutaraldehyde. The electrochemical behavior of thiocholine at the biosensor (AChE/Au-Pd/GCE) was studied. The biosensors exhibited substantial electrocatalytic effect on the oxidation of thiocholine. The peak current of linear scan voltammetry (LSV) of thiocholine at the biosensor is proportional to the concentration of acetylthiocholine chloride (ATCl) over the range of 2.5 × 10-6 to 2.5 × 10-4 M in 0.1 M phosphate buffer solution (pH 7.0). The percent inhibition of acetylcholinesterase was proportional to the logarithm of parathion concentration in the range of 4.0 × 10-9 to 1.0 × 10-6 M. The detection limit of parathion was 2.6 × 10-9 M. The proposed method exhibited high sensitivity and good reproducibility.

Keywords: acetylcholinesterase, Au-Pd nanoparticles, electrochemical biosensors, parathion

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Authors: Judith Enriquez-Gibson

Abstract:

This paper meddles with the notion of phatic communion introduced 90 years ago by Malinowski, who was a Polish-born British anthropologist. It explores the phatic in Twitter within the contents of tweets related to moocs (massive online open courses) as a topic or trend. It is not about moocs though. It is about practices that could easily be hidden or neglected if we let big or massive topics take the lead or if we simply follow the computational or secret codes behind Twitter itself and third party software analytics. It draws from media and cultural studies. Though at first it appears data-driven as I submitted data collection and analytics into the hands of a third party software, Twitonomy, the aim is to follow how phatic communion might be practised in a social media site, such as Twitter. Lurking becomes its research method to analyse mooc-related tweets. A total of 3,000 tweets were collected on 11 October 2013 (UK timezone). The emphasis of lurking is to engage with Twitter as a system of connectivity. One interesting finding is that a click is in fact a phatic practice. A click breaks the silence. A click in one of the mooc website is actually a tweet. A tweet was posted on behalf of a user who simply chose to click without formulating the text and perhaps without knowing that it contains #mooc. Surely, this mechanism is not about reciprocity. To break the silence, users did not use words. They just clicked the ‘tweet button’ on a mooc website. A click performs and maintains connectivity – and Twitter as the medium in attendance in our everyday, available when needed to be of service. In conclusion, the phatic culture of breaking silence in Twitter does not have to submit to the power of code and analytics. It is a matter of human code.

Keywords: click, Twitter, phatic communion, social media data, mooc

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Authors: Nuraisyah H. Zulkifley, Suriani Ismail, Rosliza Abdul Manaf, Poh Y. Lim

Abstract:

Taking care of a person with dementia (PWD) is one of the most problematic and challenging caregiving situations. Without proper support, caregiver would need to deal with the impact of caregiving that would lead to caregiver burden. One of the most common tools used to measure caregiver burden among caregivers of PWD is Zarit Burden Interview (ZBI). A systematic review has been conducted through searching Medline, Science Direct, Cochrane Library, Embase, PsycINFO, ProQuest, and Scopus databases to identify relevant articles that elaborate on intervention and outcomes on ZBI among informal caregiver of PWD. The articles were searched in October 2019 with no restriction on language or publication status. Inclusion criteria are randomized control trial (RCT) studies, participants were informal caregivers of PWD, ZBI measured as outcomes, and intervention group was compared with no intervention control or usual care control. Two authors reviewed and extracted the data from the full-text articles. From a total of 344 records, nine studies were selected and included in this narrative review, and eight studies were included in the meta-analysis. The types of interventions that were implemented to ease caregiver burden are psychoeducation, physical activity, psychosocial, and computer-based intervention. The meta-analysis showed that there is a significant difference in the mean score of ZBI (p = 0.006) in the intervention group compared to the control group after implementation of intervention. In conclusion, interventions such as psychoeducation, psychosocial, and physical activity can help to reduce the burden experiencing by the caregivers of PWD.

Keywords: dementia, informal caregiver, randomized control trial, Zarit burden interview

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