Search results for: language class anxiety

Authors: Anna Sikharulidze, Gia Sirbiladze

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For the evaluation of unreliability levels of movement on the closed routes in the vehicle routing problem, the fuzzy operators family is constructed. The interactions between routing factors in extreme conditions on the roads are considered. A multi-criteria decision-making model (MCDM) is constructed. Constructed aggregations are based on the Choquet integral and the associated probability class of a fuzzy measure. Propositions on the correctness of the extension are proved. Connections between the operators and the compositions of dual triangular norms are described. The conjugate connections between the constructed operators are shown. Operators reflect interactions among all the combinations of the factors in the fuzzy MCDM process. Several variants of constructed operators are used in the decision-making problem regarding the assessment of unreliability and possibility levels of movement on closed routes.

Keywords: vehicle routing problem, associated probabilities of a fuzzy measure, choquet integral, fuzzy aggregation operator

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Authors: B. Sadek, N. Khan, D. Łażewska, K. Kieć-Kononowicz

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The effects of the non-imidazole histamine H3 receptor (H3R) antagonist DL77 in passive avoidance paradigm (PAP) and novel object recognition (NOR) task in MK801-induced cognitive deficits associated with schizophrenia (CDS) in adult male rats, and applying donepezil (DOZ) as a reference drug were investigated. The results show that acute systemic administration of DL77 (2.5, 5, and 10 mg/kg, i.p.) significantly improved MK801-induced (0.1 mg/kg, i.p.) memory deficits in PAP. The ameliorating activity of DL77 (5 mg/kg, i.p.) in MK801-induced deficits was partly reversed when rats were pretreated with the centrally-acting H2R antagonist zolantidine (ZOL, 10 mg/kg, i.p.) or with the antimuscarinic antagonist scopolamine (SCO, 0.1 mg/kg, i.p.), but not with the CNS penetrant H1R antagonist pyrilamine (PYR, 10 mg/kg, i.p.). Moreover, the memory enhancing effect of DL77 (5 mg/kg, i.p.) in MK801-induced memory deficits in PAP was strongly reversed when rats were pretreated with a combination of ZOL (10 mg/kg, i.p.) and SCO (1.0 mg/kg, i.p.). Furthermore, the significant ameliorative effect of DL77 (5 mg/kg, i.p.) on MK801-induced long-term memory (LTM) impairment in NOR test was comparable to the DOZ-provided memory-enhancing effect, and was abrogated when animals were pretreated with the histamine H3R agonist R-(α)-methylhistamine (RAMH, 10 mg/kg, i.p.). However, DL77(5 mg/kg, i.p.) failed to provide procognitive effect on MK801-induced short-term memory (STM) impairment in NOR test. In addition, DL77 (5 mg/kg) did not alter anxiety levels and locomotor activity of animals naive to elevated-plus maze (EPM), demonstrating that improved performances with DL77 (5 mg/kg) in PAP or NOR are unrelated to changes in emotional responding or spontaneous locomotor activity. These results provide evidence for the potential of H3Rs for the treatment of neurodegenerative disorders related to impaired memory function, e.g. CDS.

Keywords: histamine H3 receptor, antagonist, learning, memory impairment, passive avoidance paradigm, novel object recognition

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Authors: Doyin Afolabi, Phillip Adewole, Oladipupo Sennaike

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Most well-known classifiers, including the decision tree algorithm, can make predictions on balanced datasets efficiently. However, the decision tree algorithm tends to be biased towards imbalanced datasets because of the skewness of the distribution of such datasets. To overcome this problem, this study proposes a weighted decision tree algorithm that aims to remove the bias toward the majority class and prevents the reduction of majority observations in imbalance datasets classification. The proposed weighted decision tree algorithm was tested on three imbalanced datasets- cancer dataset, german credit dataset, and banknote dataset. The specificity, sensitivity, and accuracy metrics were used to evaluate the performance of the proposed decision tree algorithm on the datasets. The evaluation results show that for some of the weights of our proposed decision tree, the specificity, sensitivity, and accuracy metrics gave better results compared to that of the ID3 decision tree and decision tree induced with minority entropy for all three datasets.

Keywords: data mining, decision tree, classification, imbalance dataset

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Authors: Murada Alholy, Mengshi Lin, Omar Alhaj, Mahmoud Abugoush

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Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared spectroscopy (FT-IR) was used to identify and discriminate between four Alicyclobacillus strains and four Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm-1 reflected the most distinctive biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (e.g. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA)) were used to analyze the spectral data. Distinctive separation of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus and to distinguish between species belonging to these two genera.

Keywords: alicyclobacillus, bacillus, FT-IR, spectroscopy, PCA

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Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem

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The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.

Keywords: IoT, traffic security, deep learning, classification

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Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Muhammad Moaz

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In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance.

Keywords: differential drive robot, hybrid fuzzy controller, optimization, path tracking, unicycle robot

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Authors: Harendra Singh, Rajesh Pandey

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The paper presents a numerical method based on operational matrix of integration and Ryleigh method for the solution of a class of non-linear fractional variational problems (NLFVPs). Chebyshev first kind polynomials are used for the construction of operational matrix. Using operational matrix and Ryleigh method the NLFVP is converted into a system of non-linear algebraic equations, and solving these equations we obtained approximate solution for NLFVPs. Convergence analysis of the proposed method is provided. Numerical experiment is done to show the applicability of the proposed numerical method. The obtained numerical results are compared with exact solution and solution obtained from Chebyshev third kind. Further the results are shown graphically for different fractional order involved in the problems.

Keywords: non-linear fractional variational problems, Rayleigh-Ritz method, convergence analysis, error analysis

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Authors: B. Falah, N. E. Abakouy

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Due to its high computational cost, mutation testing has been neglected by researchers. Recently, many cost and mutants’ reduction techniques have been developed, improved, and experimented, but few of them has relied the possibility of reducing the cost of mutation testing on the program type of the application under test. This paper is a comparative study between four operators’ selection techniques (mutants sampling, class level operators, method level operators, and all operators’ selection) based on the program code type of each application under test. It aims at finding an alternative approach to reveal the effect of code type on mutation testing score. The result of our experiment shows that the program code type can affect the mutation score and that the programs using polymorphism are best suited to be tested with mutation testing.

Keywords: equivalent mutant, killed mutant, mutation score, mutation testing, program code type, software testing

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Authors: Tiberiu Boros, Angela Ionita, Maria Visan

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Wildfires are one of the frequent and uncontrollable phenomena that currently affect large areas of the world where the climate, geographic and social conditions make it impossible to prevent and control such events. In this paper we introduce the ground concepts that lie behind the SIAFIM (Satellite Image Analysis for Fire Monitoring) project in order to create a context and we introduce a set of newly created tools that are external to the project but inherently in interventions and complex decision making based on geospatial information and spatial data infrastructures.

Keywords: wildfire, forest fire, natural language processing, mobile applications, communication, GPS

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Authors: Wiseborn Manfe Danquah, D. Turgay Altilar

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Vehicular Ad-hoc Network (VANET) is an integral component of Intelligent Transport Systems (ITS) that has enjoyed a lot of attention from the research community and the automotive industry. This is mainly due to the opportunities and challenges it presents. Vehicular Ad-hoc Network being a class of Mobile Ad-hoc Networks (MANET) has all the security concerns existing in traditional MANET as well as new security and privacy concerns introduced by the unique vehicular communication environment. This paper provides a survey of the possible attacks in vehicular environment, as well as security and privacy concerns in VANET. It also provides an insight into the development of a comprehensive cloud framework to provide a more robust and secured communication among vehicular nodes and road side units. Our proposal, a Metropolitan Based Public Interconnected Vehicular Cloud (MIVC) infrastructure seeks to provide a more reliable and secured vehicular communication network.

Keywords: mobile Ad-hoc networks, vehicular ad hoc network, cloud, ITS, road side units (RSU), metropolitan interconnected vehicular cloud (MIVC)

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Authors: Pramod Keshav Kolase, Atul K. Desai

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This paper presents the experimental investigation results of Ultrasonic Pulse Velocity (UPV) tests conducted on roller compacted concrete pavement (RCCP) material containing Class F fly ash of as mineral admixture and triangular polyester fiber as a secondary reinforcement. The each mix design series fly ash content is varied from 0% to 45 % and triangular polyester fiber 0% to 0.75% by volume fraction. In each series and for different ages of curing (i.e. 7, 28 and 90 days) forty-eight cube specimens are cast and tested for compressive strength and UPV. The UPV of fly ash was found to be lower for all mixtures at 7 days in comparison with control mix concrete. But at 28, 56 days and 90 days the UPV were significantly improved for all the mixes. Relationships between compressive strength of RCCP and UPV and Dynamic Elastic Modulus are proposed for all series mixes.

Keywords: compressive strength, dynamic elastic modulus, fly ash, fiber, roller compacted concrete, ultrasonic pulse velocity

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Authors: Vangmayee. V. Subban, Somashekara H. S, Shwetha Prabhu, Jayashree S. Bhat

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Introduction and Need: Phonological processing is critical in learning to read alphabetical and non-alphabetical languages. However, its role in learning to read Kannada an alphasyllabary is equivocal. The literature has focused on the developmental role of phonological awareness on reading. To the best of authors knowledge, the role of phonological memory and phonological naming has not been addressed in alphasyllabary Kannada language. Therefore, there is a need to evaluate the comprehensive role of the phonological processing skills in Kannada on word decoding skills during the early years of schooling. Aim and Objectives: The present study aimed to explore the phonological processing abilities and their role in learning to decode pseudowords in children learning to read the Kannada language during initial years of formal schooling between 5.6 to 8.6 years. Method: In this cross sectional study, 60 typically developing Kannada speaking children, 20 each from Grade I, Grade II, and Grade III between the age range of 5.6 to 6.6 years, 6.7 to 7.6 years and 7.7 to 8.6 years respectively were selected from Kannada medium schools. Phonological processing abilities were assessed using an assessment tool specifically developed to address the objectives of the present research. The assessment tool was content validated by subject experts and had good inter and intra-subject reliability. Phonological awareness was assessed at syllable level using syllable segmentation, blending, and syllable stripping at initial, medial and final position. Phonological memory was assessed using pseudoword repetition task and phonological naming was assessed using rapid automatized naming of objects. Both phonological awareneness and phonological memory measures were scored for the accuracy of the response, whereas Rapid Automatized Naming (RAN) was scored for total naming speed. Results: The mean scores comparison using one-way ANOVA revealed a significant difference (p ≤ 0.05) between the groups on all the measures of phonological awareness, pseudoword repetition, rapid automatized naming, and pseudoword reading. Subsequent post-hoc grade wise comparison using Bonferroni test revealed significant differences (p ≤ 0.05) between each of the grades for all the tasks except (p ≥ 0.05) for syllable blending, syllable stripping, and pseudoword repetition between Grade II and Grade III. The Pearson correlations revealed a highly significant positive correlation (p=0.000) between all the variables except phonological naming which had significant negative correlations. However, the correlation co-efficient was higher for phonological awareness measures compared to others. Hence, phonological awareness was chosen a first independent variable to enter in the hierarchical regression equation followed by rapid automatized naming and finally, pseudoword repetition. The regression analysis revealed syllable awareness as a single most significant predictor of pseudoword reading by explaining the unique variance of 74% and there was no significant change in R² when RAN and pseudoword repetition were added subsequently to the regression equation. Conclusion: Present study concluded that syllable awareness matures completely by Grade II, whereas the phonological memory and phonological naming continue to develop beyond Grade III. Amongst phonological processing skills, phonological awareness, especially syllable awareness is crucial for word decoding than phonological memory and naming during initial years of schooling.

Keywords: phonological awareness, phonological memory, phonological naming, phonological processing, pseudo-word decoding

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Authors: Ruben Peralta, Sam Thomas, Nazia Hirani, Ayman El-Menyar, Hassan Al-Thani, Mohammed Al-Thani, Mohammed Al-Hajjaj, Rafael Consunji

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Moderate to severe work-related injuries [WRI's] are a leading cause of trauma admission in Qatar but information on risk factors for their incidence are lacking. This study aims to document and analyze the predictive characteristics for WRI to inform the creation of targeted interventions to improve worker safety in Qatar. This study was conducted as part of the NPRP grant # 7 - 1120 - 3 - 288, titled "A Unified Registry for Occupational Injury Prevention in Qatar”. 266 workers were interviewed using a standard questionnaire, during ‘World Day for Safety and Health at Work’, a Ministry of Public Health event, none refused interview. Nurses and doctors from the Hamad Trauma Center conducted the interviews. Questions were translated into the worker’s native language when it was deemed necessary. Standard information on epidemiologic characteristics and incidence of work-related injury were collected and compared between nationalities and those injured versus those not injured. 262 males and 4 females were interviewed. 17 [6.4%] reported a WRI in the last 24 months. More than half of the injured worked in construction [59%] followed by water supply [11.8%]. Factors significantly associated with recent injury were: Working for a company with > 500 employees and speaking Hindi. Protective characteristics included: Being from the Philippines or Sri Lanka, speaking Arabic, working in healthcare, an office or trading and company size between 100-500 employees. Years of schooling and working in Qatar were not predictive factor for WRI. The findings from this survey should guide future research that will better define worker populations at an increased risk for WRI and inform recruiters and sending countries. A focus on worker language skills, interventions in the construction industry and occupational safety in large companies is needed.

Keywords: occupational injury, prevention, safety, trauma, work related injury

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Authors: F. Abdelhamid

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Algeria is a multilingual speech community where individuals constantly mix between codes in spoken discourse. Code is used as a cover term to refer to the existing languages and language varieties which include, among others, the mother tongue of the majority Algerian Arabic, the official language Modern Standard Arabic and the foreign languages French and English. The present study explores whether Algerians mix between these codes in online communication as well. Facebook is the selected platform from which data is collected because it is the preferred social media site for most Algerians and it is the most used one. Adopting the notion of translanguaging, this study attempts explaining how users of Facebook use multilingual messages to communicate meaning. Accordingly, multilingual interactions are not approached from a pejorative perspective but rather as a creative linguistic behavior that multilingual utilize to achieve intended meanings. The study is intended as a contribution to the research on multilingualism online because although an extensive literature has investigated multilingualism in spoken discourse, limited research investigated it in the online one. Its aim is two-fold. First, it aims at ensuring that the selected platform for analysis, namely Facebook, could be a source for multilingual data to enable the qualitative analysis. This is done by measuring frequency rates of multilingual instances. Second, when enough multilingual instances are encountered, it aims at describing and interpreting some selected ones. 120 posts and 16335 comments were collected from two Facebook pages. Analysis revealed that third of the collected data are multilingual messages. Users of Facebook mixed between the four mentioned codes in writing their messages. The most frequent cases are mixing between Algerian Arabic and French and between Algerian Arabic and Modern Standard Arabic. A focused qualitative analysis followed where some examples are interpreted and explained. It seems that Algerians mix between codes when communicating online despite the fact that it is a conscious type of communication. This suggests that such behavior is not a random and corrupted way of communicating but rather an intentional and natural one.

Keywords: Algerian speech community, computer mediated communication, languages in contact, multilingualism, translanguaging

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Authors: Rozafa Shala

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Development of preschool education in Kosovo has passed through several periods. The period after the 1999 war was very intensive period when preschool education started to change. Step-by-step program was one of the programs which were very well extended during the period after the 1999 war until now. The aim of this study is to present the impact of the step-by-step program in the preschool education. This research is based on the hypothesis that: Step-by-step program continues to be present with its elements, in all other programs that the teachers can use. For data collection a questionnaire is constructed which was distributed to 25 teachers of preschool education who work in public preschool institutions. All the teachers have finished the training for step by step program. To support the data from the questionnaire a focus group is also organized with whom the critical issues of the program were discussed. From the results obtained we can conclude that the step-by-step program has a very strong impact in the preschool level. Many specific elements such as: circle time, weather calendar, environment inside the class, portfolios and many other elements are present in most of the preschool classes. The teacher's approach also has many elements of the step-by-step program.

Keywords: preschool education, step-by-step program, impact, teachers

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Authors: R. Sulakshana, R. Lakshmi

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Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR associate (CRISPR/Cas) is an adaptive immunity system found in bacteria and archaea. It has been modified to serve as a potent gene editing tool. Moreover, it has found widespread use in the field of genome research because of its accessibility and low cost. Several bioinformatics methods have been created to aid in the construction of specific single guide RNA (sgRNA), which is highly active and crucial to CRISPR/Cas performance. Various Cas proteins, including Cas1, Cas2, Cas9, and Cas12, have been used to create genome engineering tools because of their programmable sequence specificity. Class 1 and 2 CRISPR/Cas systems, as well as the processes of all known Cas proteins (including Cas9 and Cas12), are discussed in this review paper. In addition, the various CRISPR methodologies and their tools so far discovered are discussed. Finally, the challenges and issues in the CRISPR system along with future works, are presented.

Keywords: gene editing tool, Cas proteins, CRISPR, guideRNA, programmable sequence

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Authors: Magdalena Jabłońska-Czapla

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The work allowed gaining knowledge about redox and speciation changes of As, Cr, and Sb ionic forms in Klodnica River water. This kind of studies never has been conducted in this region of Poland. In study optimized and validated previously HPLC-ICP-MS methods for determination of As, Sb and Cr was used. Separation step was done using high-performance liquid chromatograph equipped with ion-exchange column followed by ICP-MS spectrometer detector. Preliminary studies included determination of the total concentration of As, Sb and Cr, pH, Eh, temperature and conductivity of the water samples. The study was conducted monthly from March to August 2014, at six points on the Klodnica River. The results indicate that exceeded at acceptable concentration of total Cr and Sb was observed in Klodnica River and we should qualify Klodnica River waters below the second purity class. In Klodnica River waters dominates oxidized antimony and arsenic forms, as well as the two forms of chromium Cr(VI) and Cr(III). Studies have also shown the methyl derivative of arsenic's presence.

Keywords: antimony, arsenic, chromium, HPLC-ICP-MS, river water, speciation

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Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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Authors: Sarah P. Wuebbolt, Ashlee N. Sawyer-Mays

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Non-medical prescription and other drug (NMPOD) use has been a significant public health issue for the last few decades, with problematic use increasing among university students more recently. The current study focused on associations between NMPOD use and mental health, well-being, and world beliefs among young adults. Young adults (N=513) completed online questionnaires assessing stress, demographic characteristics, self-esteem, NMPOD use, coping mechanisms, and anxiety. A substantial portion of participants reported using cannabis (48.5%, n=249), while smaller portions of participants reported using stimulants (26.7%, n = 137), sedatives (17.2%, n=88), opioids (10.8%, n=55), and hallucinogens (14.4%, n=74). Five hierarchical logistic regressions were performed to determine the independent relationships between mental health, well-being, and world belief factors and NMPOD use for the five classes of substances. After controlling for demographic factors (age, gender, race/ethnicity, sexual orientation, and religious affiliation), depression was associated with increased non-medical stimulant, opioid, and cannabis use; coping self-efficacy was associated with increased hallucinogen use, and attendance of worship services was associated with decreased non-medical cannabis and hallucinogen use. Results suggest that depression was strongly associated with non-medical stimulant, opioid, and cannabis use, and attendance of worship services was protective against cannabis and hallucinogen use. To the best of our knowledge, this is one of the first studies to investigate the relationships between mental health, well-being, world beliefs, and NMPOD use among young adults. The present study illuminates future targets for intervention, such as increased access to mental health diagnosis and treatment and the exploration of the roles of religion and shared community in the prevention of drug use among young adults.

Keywords: cannabis, mental health, non-medical prescription and other drug use, world beliefs

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Authors: Almutazballlah Qablan, Jihan M. Muhaidat, Bana Abu Rajab

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Background: Acne vulgaris is the most common skin condition that general practitioners and dermatologists encounter. It represents a chronic inflammatory disease affecting the pilosebaceous unit. Although acne vulgaris is not a life-threatening condition, it has a considerable psychological impact on the affected person. Acne patients have poor body image, low self-esteem, social isolation, and restricted activities. As part of the emotional impact, increased levels of anxiety, anger, depression, and frustration have also been observed in acne patients. (1) In this study, we want to assess the association between two modifiable risk factors; BMI and smoking, regarding acne vulgaris. Methods: A case-control study was conducted at King Abdullah University Hospital in Irbid, north Jordan in 2019/2020. A total number of 163 Acne cases were collected and interviewed by the author; on the other hand, there were 162 control cases. Anthropometric measures for Acne patients and control individuals were taken, and BMI was calculated. Both groups were asked about smoking habits. Data on subjects between 14 and 33 years of age were extracted. The characteristics of people who reported acne were compared with those with no acne using univariate and multivariate analysis. The Statistical Package for Social Sciences (SPSS) was relied on to analyze the collected data. The crosstabs methods (chi-square) and odd ratios were relied on to test the study hypothesis. Results: Cigarette smoking was highly associated with no-acne, with an odds ratio of 0.4 (95% CI: 0.2–0.9), P-value = 0.018. BMI and waterpipe smoking were not significantly associated with acne in the multivariate analysis. Conclusion: Cigarette smoking was found to be protective from Acne. No significant relation between BMI nor waterpipe smoking and the development of Acne Vulgaris.

Keywords: acne, BMI, smoking, case-control

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Authors: Jafar Ahmadi, Nafiseh Noormohammadi, Sedegeh Fabriki Ourang

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GRF, Growth regulating factor, genes encode a novel class of plant-specific transcription factors. The GRF proteins play a role in the regulation of cell numbers in young and growing tissues and may act as transcription activations in growth and development of plants. Identification of GRF genes and their expression are important in plants to performance of the growth and development of various organs. In this study, to better understanding the structural and functional differences of GRFs family, 45 GRF proteins sequences in A. thaliana, Z. mays, O. sativa, B. napus, B. rapa, H. vulgare, and S. bicolor, have been collected and analyzed through bioinformatics data mining. As a result, in secondary structure of GRFs, the number of alpha helices was more than beta sheets and in all of them QLQ domains were completely in the biggest alpha helix. In all GRFs, QLQ, and WRC domains were completely protected except in AtGRF9. These proteins have no trans-membrane domain and due to have nuclear localization signals act in nuclear and they are component of unstable proteins in the test tube.

Keywords: domain, gene family, GRF, motif

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Authors: M. Regina Carreira-Lopez

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Lightweight ontologies seek to concrete union relationships between a parent node, and a secondary node, also called "child node". This logic relation (L) can be formally defined as a triple ontological relation (LO) equivalent to LO in ⟨LN, LE, LC⟩, and where LN represents a finite set of nodes (N); LE is a set of entities (E), each of which represents a relationship between nodes to form a rooted tree of ⟨LN, LE⟩; and LC is a finite set of concepts (C), encoded in a formal language (FL). Mondoc enables more refined searches on semantic and classified facets for retrieving specialized knowledge about Atlantic migrations, from the Declaration of Independence of the United States of America (1776) and to the end of the Spanish Civil War (1939). The model looks forward to increasing documentary relevance by applying an inverse frequency of co-ocurrent hypernymy phenomena for a concrete dataset of textual corpora, with RMySQL package. Mondoc profiles archival utilities implementing SQL programming code, and allows data export to XML schemas, for achieving semantic and faceted analysis of speech by analyzing keywords in context (KWIC). The methodology applies random and unrestricted sampling techniques with RMySQL to verify the resonance phenomena of inverse documentary relevance between the number of co-occurrences of the same term (t) in more than two documents of a set of texts (D). Secondly, the research also evidences co-associations between (t) and their corresponding synonyms and antonyms (synsets) are also inverse. The results from grouping facets or polysemic words with synsets in more than two textual corpora within their syntagmatic context (nouns, verbs, adjectives, etc.) state how to proceed with semantic indexing of hypernymy phenomena for subject-heading lists and for authority lists for documentary and archival purposes. Mondoc contributes to the development of web directories and seems to achieve a proper and more selective search of e-documents (classification ontology). It can also foster on-line catalogs production for semantic authorities, or concepts, through XML schemas, because its applications could be used for implementing data models, by a prior adaptation of the based-ontology to structured meta-languages, such as OWL, RDF (descriptive ontology). Mondoc serves to the classification of concepts and applies a semantic indexing approach of facets. It enables information retrieval, as well as quantitative and qualitative data interpretation. The model reproduces a triple tuple ⟨LN, LE, LT, LCF L, BKF⟩ where LN is a set of entities that connect with other nodes to concrete a rooted tree in ⟨LN, LE⟩. LT specifies a set of terms, and LCF acts as a finite set of concepts, encoded in a formal language, L. Mondoc only resolves partial problems of linguistic ambiguity (in case of synonymy and antonymy), but neither the pragmatic dimension of natural language nor the cognitive perspective is addressed. To achieve this goal, forthcoming programming developments should target at oriented meta-languages with structured documents in XML.

Keywords: hypernymy, information retrieval, lightweight ontology, resonance

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Authors: Ya-Yi Yen

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The operating room is a medical environment full of high-risk, high-complexity and high-cost. In addition to assuring patient safety, the operating room should effort on the efficient and safe medical quality for the surgical patients of high risk, elders, and children. If the nursing staffs of operation room carry on the pre-operative visiting prior to surgery, the patient's anxiety and complications are expected to be alleviated, and the hospitalization days may also be shortened. Purpose: Applying the information system to enhance pre-operative visiting, case tracking, and effectiveness recording Method: (I) Application the information system to screen cases by integrating the operation scheduling, and linking the severe surgery codes, for to shorten the time to track cases of operative visiting. Through the improvement, the time required decreased to 1.5 minutes per day from 20 minutes per day, and nursing staffs’ satisfaction with satisfaction for tracking and visiting procedure of case increased to 86% from 54%. (II)The electronic establishment of the operative visiting record enhanced the integrity of the operative visiting record. The integrity rate was rise to 92% from 66%, while nursing staffs’ satisfaction with the visiting record increased to 82% from 61.3%. Since information technology continues evolving, the application of information technology is helpful to the integration of nursing information, simplification of processes, and saving of man-hours. This article introduces the application of information systems to simplify the processes and improve the effectiveness of operation visiting and tracking, including the saving of time, improving the integrity rate of record, and improving the satisfaction of nursing staffs.

Keywords: effectiveness, information system, perioperative nursing, pre-operative visiting

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Authors: Sumiti Saharan, Pallav Patankar, Lily W. Lee

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Understanding the health-seeking behaviors and attitudes of women towards maternal health in the context of gender roles and family dynamics is tremendously crucial for designing effective and impactful interventions aimed at improving maternal and child health outcomes. Further, as the digital world becomes more accessible and affordable, it is imperative to scope the potential of digital technology in enabling access to maternal health information in different socio-economic groups (SEGs). In the summer of 2017, we conducted a study with 500 women across different SEGs in urban India who were pregnant or had had a delivery in the last year. The study was undertaken to assess their maternal health information seeking behavior with a particular focus on probing their use of digital technology for health-related information. The study also measured women's decision-making autonomy in the context of maternal health, awareness of their rights to quality and respectful maternal healthcare, and agency to voice their rights. We probed the impact of key variables including education, age, and socioeconomic status on all outcome variables. In terms of health-seeking behaviors, we found that women heavily relied on medical professionals and/or their mothers and mothers-in-law for all maternal health advice. Digital adoption was found to be high across all SEGs, with around 70% of women from all populations using the internet several times a week. On the other hand, use of the internet for both accessing maternal health information and choosing maternity hospitals were both significantly dependent on SEG. The key reasons reported for not using the internet for health purposes were lack of awareness and lack of trust on content accuracy. Decisions around health practices and type of delivery were found to be jointly made by women and other family members. Almost all women reported their husbands to play a key role in all maternal health decisions and for decisions with a clear financial implication like choice of hospital for delivery, husbands were reported to be the sole decision maker by a majority of women. The agency of women was also found to be low in interactions with maternal healthcare providers with a third of respondents not comfortable with voicing their opinions and preferences to their doctors. Interestingly, we find that this relatively low agency was prominent in both lower middle class and middle-class SEGs. Recognition of the sociocultural determinants of behavior is the first step in developing actionable strategies for improving maternal health outcomes. Our study quantifies the agency and autonomy of women in urban India and the variables that impact them. Our findings emphasize the value of gender normative approaches that factor in the key role husbands play in guiding maternal health decisions. They also highlight the power of digital approaches for catalyzing access to maternal health information. These insights into the attitude and behaviors of mothers in context of their sociocultural environments—and their relationship with digital technology—can help pave the way towards designing effective, scalable maternal and child health programs in developing nations like India.

Keywords: access to healthcare information, behavior, digital health, maternal health

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Barnali Saha

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Dalit writing is the interventionalist voice of the dispossessed subaltern in the cultural economy of the society. As such, Dalit writing, including Dalit poetry, considers the contradictions that permeate the socio-cultural structure historically allocated and religiously sanctioned in the Indian subcontinent. As an epicenter of all Dalit experiences of trauma and violence, the poetics the Dalit body is deeply rooted in the peripheral space socially assigned to it by anachronistic caste-based litigation. An appraisal of Dalit creative-critical work by writers like Sharan Kumar Limbale, Arjun Dangle, Namdeo Dhasal, Om Prakash Valmiki, Muktibodh and others underscore the conjunction of the physical, psychical and the psychological in their interpretation of Dalit consciousness. They put forward the idea that Dalit poetry is begotten by the trauma of societal oppression and therefore, Dalit language and its revitalization are two elements obdurately linked to Dalit poetics. The present research paper seeks to read the problematization of the Dalit agency through the conduit of the Dalit voice wherein the anatomical category of the mouth is closely related to the question of Dalit identity. Theoretically aligned to Heidegger’s notion of language as the house of being and Bachelard’s assertion of a house as an ideal metaphor of poetic imagination and Dylan Trigg’s view of the coeval existence of space and body, the paper examines a series of selected poems by Dalit poetic voices to examine how their distinct Dalit point of view underscores Dalit speech and directs our attention to the historical abstraction of it. The paper further examines how speech as a category in Dalit writing places the Dalit somatic entity as a site of contestation with the ‘Mouth’ as a loaded symbolic category inspiring rebellion and resistance. And as the quintessential purpose of Dalit literature is the unleashing of Dalit voice from the anti-verbal domain of social decrepitude, Dalit poetry needs to be critically read based on the experience of the mouth and the patois.

Keywords: Dalit, poetry, speech, mouth, subaltern, minority, exploitation, space

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Authors: Ukpaka Paschal

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Margret Boden argues that a creative product is one that is new, surprising, and valuable as a result of the combination, exploration, or transformation involved in producing it. Boden uses examples of artificial intelligence systems that fit all of these criteria and argues that real creativity involves autonomy, intentionality, valuation, emotion, and consciousness. This paper provides an analysis of all these elements in order to try to understand whether they are sufficient to account for creativity, especially human creativity. This paper focuses on Generative Adversarial Networks (GANs), which is a class of artificial intelligence algorithms that are said to have disproved the common perception that creativity is something that only humans possess. This paper will then argue that Boden’s listed properties of creativity, which capture the creativity exhibited by GANs, are not sufficient to account for human creativity, and this paper will further identify “first-person phenomenological experience” as an essential property of human creativity. The rationale behind the proposed essential property is that if creativity involves comprehending our experience of the world around us into a form of self-expression, then our experience of the world really matters with regard to creativity.

Keywords: artificial intelligence, creativity, GANs, first-person experience

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Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

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Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

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Authors: Lilla Szabó Hangya, Szilvia Jambori

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The comfort zone is less studied area in the field of psychology. One of the most important definitions is that comfort zone is a psychological state in which things feel familiar to a person with low level of anxiety and stress. But the validity of comfort zone does not confirm till now. The aim of our pilot research is to test which psychological factors could determine how young adults behave during their decision process to stay in one’s comfort zone or to leave it. Every person has a number of comfort zones, so we are not able to measure it directly, only those personality traits which predict if someone leaves his comfort zone easier or harder. In our study at first we wanted to clarify the meaning of comfort zone. 110 young adults (male: 37, female: 73; ages from 18 to 70, average age: 26,6) took part in the study. Beside their demographic datas we asked them what does the comfort zone mean for them. The results showed that the meaning of the comfort zone can be grouped in five dimensions: comfort (49,6 %), leaving it-change (8,1%), ambivalent feelings (10,6%), related to other people (10,6%), pursuit of self-realization (16,8%). Our results demonstrated age related characteristics. For young people at the age of 19 the comfort zone is related to other people, because during adolescents peer relationships become more important. Subjects at the age 20-30 answered that the comfort zone means comfort and stability for them. Their life becomes stable for a while, they are studying or working. But at the age of 25, when they finish university, most of them answered comfort zone means a changing process for them. On the other hand for subjects at the age of 27 the means of the comfort zone is pursuit of self-realization. After that period at the age of 31 when they have families and stable job the stability will also dominant. We saw that the comfort zone has much more meaning besides a pleasant psychological trait. Further we would like to determine which psychological factors relate to comfort zone, and what kind of personality traits could predict leaving or staying in one’s comfort zone. We want to observe the relationship between comfort zone and subjective well-being, life satisfaction self-efficacy or self-esteem.

Keywords: comfort zone, development, personality trait, young adults

Procedia PDF Downloads 326