Search results for: multi-layer perception neural networks

Authors: Julia Kapr, Andrea Rossi, Haribaskar Ramachandran, Marius Pollet, Ilka Egger, Selina Dangeleit, Katharina Koch, Jean Krutmann, Ellen Fritsche

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It is widely acknowledged that animal models do not always represent human disease. Especially human brain development is difficult to model in animals due to a variety of structural and functional species-specificities. This causes significant discrepancies between predicted and apparent drug efficacies in clinical trials and their subsequent failure. Emerging alternatives based on 3D in vitro approaches, such as human brain spheres or organoids, may in the future reduce and ultimately replace animal models. Here, we present a human induced pluripotent stem cell (hiPSC)-based 3D neural in a vitro disease model for the Cockayne Syndrome B (CSB). CSB is a rare hereditary disease and is accompanied by severe neurologic defects, such as microcephaly, ataxia and intellectual disability, with currently no treatment options. Therefore, the aim of this study is to investigate the molecular and cellular defects found in neural hiPSC-derived CSB models. Understanding the underlying pathology of CSB enables the development of treatment options. The two CSB models used in this study comprise a patient-derived hiPSC line and its isogenic control as well as a CSB-deficient cell line based on a healthy hiPSC line (IMR90-4) background thereby excluding genetic background-related effects. Neurally induced and differentiated brain sphere cultures were characterized via RNA Sequencing, western blot (WB), immunocytochemistry (ICC) and multielectrode arrays (MEAs). CSB-deficiency leads to an altered gene expression of markers for autophagy, focal adhesion and neural network formation. Cell migration was significantly reduced and electrical activity was significantly increased in the disease cell lines. These data hint that the cellular pathologies is possibly underlying CSB. By induction of autophagy, the migration phenotype could be partially rescued, suggesting a crucial role of disturbed autophagy in defective neural migration of the disease lines. Altered autophagy may also lead to inefficient mitophagy. Accordingly, disease cell lines were shown to have a lower mitochondrial base activity and a higher susceptibility to mitochondrial stress induced by rotenone. Since mitochondria play an important role in neurotransmitter cycling, we suggest that defective mitochondria may lead to altered electrical activity in the disease cell lines. Failure to clear the defective mitochondria by mitophagy and thus missing initiation cues for new mitochondrial production could potentiate this problem. With our data, we aim at establishing a disease adverse outcome pathway (AOP), thereby adding to the in-depth understanding of this multi-faced disorder and subsequently contributing to alternative drug development.

Keywords: autophagy, disease modeling, in vitro, pluripotent stem cells

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Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Zeynep R. Ege, Aydin Akan, Faik N. Oktar, Betul Karademir, Oguzhan Gunduz

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Early detection of cancer could save human life and quality in insidious cases by advanced biomedical imaging techniques. Designing targeted detection system is necessary in order to protect of healthy cells. Electrospun nanofibers are efficient and targetable nanocarriers which have important properties such as nanometric diameter, mechanical properties, elasticity, porosity and surface area to volume ratio. In the present study, indocyanine green (ICG) organic dye was stabilized and encapsulated in polymer matrix which polyethylene oxide (PEO) and chitosan (CHI) multilayer nanofibers via co-axial electrospinning method at one step. The co-axial electrospun nanofibers were characterized as morphological (SEM), molecular (FT-IR), and entrapment efficiency of Indocyanine Green (ICG) (confocal imaging). Controlled release profile of PEO/CHI/ICG nanofiber was also evaluated up to 40 hours.

Keywords: chitosan, coaxial electrospinning, controlled releasing, drug delivery, indocyanine green, polyethylene oxide

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Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: Dalia Elleuch

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Narcissistic Personality Disorder (NPD) manifests as a personality disorder marked by inflated self-importance, heightened sensitivity to criticism, a lack of empathy, a preoccupation with appearance over substance, and features such as arrogance, grandiosity, a constant need for admiration, a tendency to exploit others, and an inclination towards demanding special treatment due to a sense of excessive entitlement (APA, 2013). This interdisciplinary study delves into NPD through the systematic synthesis of psycholinguistic analysis and neuroscientific correlates. The cognitive and emotional dimensions of NPD reveal linguistic patterns, including grandiosity, entitlement, and manipulative communication. Neuroscientific investigations reveal structural brain differences and alterations in functional connectivity, further explaining the neural underpinnings of social cognition deficits observed in individuals with NPD. Genetic predispositions and neurotransmitter imbalances add a layer of complexity to the understanding of NPD. The necessity for linguistic intervention in diagnosing and treating Narcissistic Personality Disorder is underscored by an interdisciplinary study that intricately synthesizes psycholinguistic analysis and neuroscientific correlates, offering a comprehensive understanding of NPD’s cognitive, emotional, and neural dimensions and paving the way for future practical, theoretical, and pedagogical approaches to address the complexities of this personality disorder.

Keywords: Narcissistic Personality Disorder (NPD), psycholinguistic analysis, neuroscientific correlates, interpersonal dysfunction, cognitive empathy

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Authors: Kuek Teik Sheng, Leaw Zee Guan, Lim Wah Kien, Ting Tin Tin

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Educational technology such as YouTube and Kahoot have arisen as an alternative to effective learning among higher education institutions. There are many researches done in carrying out experiments to test different educational technologies and received positive feedback from students. Yet, similar study is hardly found in Malaysia especially study that includes the latest educational technologies. As a developing country, it is crucial to ensure that these emerging technologies are assisting students in learning process before it is widely adopted in institutions. This paper conducted a study to explore the perception of higher education institution students on the current educational technologies in Malaysia which include online educational games, online videos/course, social media, presentation tools and resource management tool. Some of these technologies have not been looked into its potential in effective learning process. An online survey using questionnaire is conducted among a target of 300 university/college. In the survey, the result shows that majority of the target students in Malaysia agree that the current educational technologies help them in learning, understanding and manage their studies. It is necessary to discover students’ perceptions on the educational technologies in order to provide guidelines for the educators/institutions in selecting appropriate technology to conduct the lecture/tutorial efficiently and effectively.

Keywords: education, educational technology, Facebook, PowerPoint, YouTube

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Authors: Ira Slabodar

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Autonomous learning in English as a Foreign Language (EFL) refers to the use of target language, learner collaboration and students’ responsibility for their learning. Teachers play a vital role of mediators and facilitators in self-regulated method. Thus, their perception of self-guided practices dictates their implementation of this approach. While research has predominantly focused on inadequate administration of autonomous learning in school mostly due to lack of appropriate teacher training, this study examined whether novice teachers who were exposed to extensive autonomous practices were likely to implement this method in their teaching. Twelve novice teachers were interviewed to examine their perception of learner autonomy and their administration of this method. It was found that three-thirds of the respondents experienced a gap between familiarity with autonomous learning and a favorable attitude to this approach and their deficient integration of self-directed learning. Although learner-related and institution-oriented factors played a role in this gap, it was mostly caused by the respondents’ not being genuinely autonomous. This may be due to indirect exposure rather than explicit introduction of the learner autonomy approach. The insights of this research may assist curriculum designers and heads of teacher training programs to rethink course composition to guarantee the transfer of methodologies into EFL classes.

Keywords: learner autonomy, teacher training, english as a foreign language (efl), genuinely autonomous teachers, explicit instruction, self-determination theory

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Authors: Mary Anne Roa

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Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially for today’s very high speed networks. To address this undeniably global issue, the study focuses on the development of a fuzzy-based congestion control model concerned with allocating the resources of a computer network such that the system can operate at an adequate performance level when the demand exceeds or is near the capacity of the resources. Fuzzy logic based models have proven capable of accurately representing a wide variety of processes. The model built is based on bandwidth, the aggregate incoming traffic and the waiting time. The theoretical analysis and simulation results show that the proposed algorithm provides not only good utilization but also low packet loss.

Keywords: congestion control, queue management, computer networks, fuzzy logic

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Authors: Paulo Sergio Altman Ferreira

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Relationship development plays an essential role in every logistics company. Logistics companies are service-based businesses essentially performing the flow of materials, housing, and inventory management for a wide range of customers. The service encounter between the logistics provider’s personnel and the customers may form a connection that will demonstrate a strong impact, not only to the customers' overall satisfaction but may also provide the perception of individualized services. Logistics services must drive value. It also shows a close influence on the quality and costs of client-centered services. If we describe logistics value creation as the function of quality perception of the client divided by service costs, there is a requirement to better outline and explain the measures and analytics for logistics costs and relationship performance. This critical shift to understand logistics services is a relevant contribution to capture how relationship value can be quantified. This might involve changing our current perspective on logistics providers beyond uniquely measuring the services in terms of activities, personnel levels, and financial/costs ratios. This paper argues that measuring value creation accomplishments of logistics services needs to consider the relational improvements for the wider range of logistics companies. Accurate logistics value requires a description of the financial impact of the relational perspective of the service.

Keywords: logistics services providers, financial metrics, relationship management, value creation

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Authors: Humayun Murshed

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There is growing importance of ‘social enterprise’ among the researchers and policy makers around the globe. Such enterprises have been viewed as alternative means for addressing the concerns relating to financing of corporate enterprises and social empowerment. This, some cases, has led to relatively unrealistic and higher level of expectations among policy makers and the members of the society at large. There is a general perception among different social actors that these enterprises provide universal and magic solution towards employment generation, and thus resulting in eradicating poverty, and ensuring equitable distribution of income and wealth. However, in many cases, these enterprises find a challenging journey in terms of prevailing market structure, socio-political environment, and unrealistic perception and expectations of social participants. This paper is focused on reviewing case studies based on empirical research and information from secondary sources and geared to looking at the challenges that social enterprises face. The research will draw the experience primarily from the developing countries’ perspective by adopting case study methodology. A tentative action plan will be suggested for further review by the policy makers and researchers in this growing arena of discipline. This research will attempt to highlight the myths and realities surrounding the operation of social enterprises.

Keywords: social enterprises, social empowerment, economic development, financing need

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Authors: Sonia Anand Knowlton

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In many ways, judges can express their personality within and beyond their role as a judge. Judges can use their unique backgrounds and life experiences to inform their legal reasons and can also participate in certain extrajudicial activities outside of their role on the bench. For many judges, the line between the expression of this judicial personality, on the one hand, and the consequence of jeopardizing the public’s perception of their impartiality, on the other, is ambiguous if not wholly unclear. In the famous Canadian decision R v RDS, for instance, a Black judge who was hearing a case about police violence against a Black person was accused of being biased after she acknowledged that her community’s racial dynamics may have impacted the police’s conduct. Many within the legal community might find comfort in the belief that judges do not need to bring their ‘personality’ to the bench in order to uncover the law’s truths and impartially apply it. Indeed, and for a good reason, judges are often discouraged from allowing their personality to shine through in their role as a judge – because the expression of judicial personality can compromise the public perception of the impartiality of the administration of justice. This paper evaluates the theoretical constraints on the expression of judicial personality as a tool for legal decision-making and argues that judges from minority groups are held to a higher level of impartiality. Specifically, minority judges are disproportionately constrained from 1) using life experience to apply the law and 2) engaging in certain extrajudicial activities.

Keywords: judging, legal decision making, judicial personality, extrajudicial activities

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Authors: Ghada Shahrour, Nusiebeh Ananbh, Heyam Dalky, Mohammad Rababa, Fatmeh Alzoubi

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Positive teacher-student relationship has been found to affect students’ attitudes towards bullying and, in turn, their engagement in bullying behavior. However, no investigation has been conducted to explore whether teacher-student relationship affects teachers’ attitudes towards bullying. The aim of this study was to examine the role of teacher-student relationship on teachers’ attitudes towards bullying in terms of bullying seriousness, empathic responding, and likelihood to intervene in bullying situation. A cross-sectional, descriptive design was employed among a convenience sample of 173 school teachers (50.9% female) of 12 to 17-year-old students. The teachers were recruited from secondary public schools of three governorates in the Northern district of Jordan. Each group of students has multiple teachers for different subjects. Results showed that teacher-student relationship is partially related to teachers’ attitudes towards bullying. More specifically, having a close teacher-student relationship significantly increased teachers’ perception of bullying seriousness and empathy but not the likelihood to intervene. Research is needed to examine teachers’ obstacles for not providing bullying interventions, as the barriers may be culturally contextualized. Meanwhile, interventions that promote quality teacher-student relationship are necessary to increase teachers’ perception of bullying seriousness and empathy. Students have been found to adopt the values of their teachers, and this may deter them from engaging in bullying behavior.

Keywords: school bullying, teachers’ attitudes, teacher-student relationship, adolescent students

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

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Authors: Silvio Ricardo Rodrigues Sanches, Bianca Cogo Barbosa, Beatriz Regina Brum, Cléber Gimenez Corrêa

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To evaluate the quality of a segmentation algorithm, the authors use subjective or objective metrics. Although subjective metrics are more accurate than objective ones, objective metrics do not require user feedback to test an algorithm. Objective metrics require subjective experiments only during their development. Subjective experiments typically display to users some videos (generated from frames with segmentation errors) that simulate the environment of an application domain. This user feedback is crucial information for metric definition. In the subjective experiments applied to develop some state-of-the-art metrics used to test segmentation algorithms, the videos displayed during the experiments did not contain audio. Audio is an essential component in applications such as videoconference and augmented reality. If the audio influences the user’s perception, using only videos without audio in subjective experiments can compromise the efficiency of an objective metric generated using data from these experiments. This work aims to identify if the audio influences the user’s perception of segmentation quality in background substitution applications with audio. The proposed approach used a subjective method based on formal video quality assessment methods. The results showed that audio influences the quality of segmentation perceived by a user.

Keywords: background substitution, influence of audio, segmentation evaluation, segmentation quality

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Authors: Roongtiwa Chobchuen, Siriporn Mongkholthawornchai, Boonsong Hatawaikarn, Uriwan Chaichangreet, Kobkaew Thongtid, Pusda Pukdeekumjorn, Panita Limpawattana

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Background: Age-friendly nursing service system in Srinagarind Hospital has been developed continuously based on the value and cultural background of Thailand which corporates with the modified WHO’s Age friendly Primary Care Service System. It consists of 3 issues; 1) development of staff training, 2) age-friendly service and 3) appropriate physical environment. Objective: To evaluate the efficacy of Age-friendly Nursing Service System: KKU (AFNS:KKU) model and to evaluate factors associated with nursing perception with AFN:KKU. Study design: Descriptive study Setting: 31 wards that served older patients in Srinagarind Hospital Populations: Nursing staff from 11 departments (31 wards) Instrument: Age-friendly nursing care scale as perceived by hospitalized older person Procedure and statistical analysis: All participants were asked questions using age-friendly nursing care scale as perceived by hospitalized older person questionnaires. Descriptive statistics and multiple logistic regression analyses were used to analyse the outcomes. Results: There were 337 participants recruited in this study. The majority of them were women (92%) with the mean ages of 29 years and 77.45% were nurse practitioners. They had average nursing experiences of 5 years. The average scores of age-friendly nursing care scale were high and highest in the area of attitude and communication. Age, sex, educational level, duration of work among, and having experience in aging training were not associated with nursing perception where type of department was an independent factor. Nurses from department of Surgery and Orthopedic, Eye and ENT, special ward and Obstetrics and Gynecological had significant greater perception than nurses from Internal Medicine Department (p < 0.05). Conclusion: Nurses had high scores in all dimensions of age-friendly concept. The result indicates that nurses have good attitude to aging care which can lead to improve quality of care. Organization should support other domains of ageing care to achieve greater effectiveness in geriatric care.

Keywords: age-friendly, nursing service system, excellence model, geriatric care

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Suha Alawadhi, Malak Alrasheed

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In the recent past, public participation in governments has been declined to a great extent, as citizens have been isolated from community life and their ability to articulate demands for good government has been noticeably decreased. However, the Internet has introduced new forms of interaction that could enhance different types of relationships, including government-public relationship. In fact, technology-enabled government has become a catalyst for enabling social inclusion. This exploratory study seeks to investigate public perceptions in Kuwait regarding the use of social media networks in government where social capital is built to achieve social inclusion. Social capital has been defined as social networks and connections amongst individuals, that are based on shared trust, ideas and norms, enable participants of a network to act effectively to pursue a shared objective. The quantitative method was used to generate empirical evidence. A questionnaire was designed to address the research objective and reflect the identified constructs: social capital dimensions (bridging, bonding and maintaining social capital), social inclusion, and social equality. In this pilot study, data was collected from a random sample of 61 subjects. The results indicate that all participants have a positive attitude towards the dimensions of social capital (bridging, bonding and maintaining), social inclusion and social equality constructs. Tests of identified constructs against demographic characteristics indicate that there are significant differences between male and female as they perceived bonding and maintaining social capital, social inclusion and social equality whereas no difference was identified in their perceptions of bridging social capital. Also, those who are aged 26-30 perceived bonding and maintaining social capital, social inclusion and social equality negatively compared to those aged 20-25, 31-35, and 40-above whose perceptions were positive. With regard to education, the results also show that those holding high school, university degree and diploma perceived maintaining social capital positively higher than with those who hold graduate degrees. Moreover, a regression model is proposed to study the effect of bridging, bonding, and maintaining social capital on social inclusion via social equality as a mediator. This exploratory study is necessary for testing the validity and reliability of the questionnaire which will be used in the main study that aims to investigate the perceptions of individuals towards building social capital to achieve social inclusion.

Keywords: government, social capital, social inclusion, social networks

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Authors: Bunki Enid Pitsoane

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This study was influenced by the radical change in the tutorial system of UNISA, immigrating from face to face to E-tutoring. The study was undertaken to investigate the perceptions, experiences, and views of E-tutors in relation to active learning. The study is aimed at capturing the views and experiences of E-tutors as they are deemed to implement active learning within their E-tutoring. The problem was traced from Developmental and behaviorist’s theorists perspective and factors related to perception, experience, and views of E-tutors on active learning. The research is aligned with the views of constructivism which put more emphasis on situated learning, chaos, and digital factors. The basis of the theory is that learning is developmental, situational and context-sensitive and also digital. The theorists further purports that the tutor’s conception of teaching and learning influence their tutoring style. In order to support or reject the findings of the literature study, qualitative research in the form of interviews and document analysis were conducted. The sample of the study constituted of 10 E-tutors who are involved in tutoring modules from the College of Education. The identified E-tutors were randomly selected based on their availability. The data concerning E-tutors perception and experience was analysed and interpreted. The results of the empirical study indicated that some tutors are struggling to implement active learning because they are digital immigrants or they lack in digital knowledge which affect productivity in their teaching.

Keywords: E-Tutoring, active learning, perceptions, views

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Authors: Mohamed Adnan Landolsi, Ali F. Almutairi

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The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics.

Keywords: UWB, propagation, LOS, NLOS, identification

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Authors: Konstans Ruseva, Kristina Ivanova, Katerina Todorova, Margarita Gabrashanska, Tzanko Tzanov, Elena Vassileva

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Zwitterionic polymers (ZP) are well-known with their ultralow biofouling. They are successfully competing with poly(ethylene glycols) (PEG), which are considered as the “golden standard” in this respect. These unique properties are attributed to their strong hydration capacity, defined by the dipole-dipole interactions, arising between the ZP pendant groups as well as to the dipoles interaction with water molecules. Beside, ZP are highly resistant to bacterial adhesion thus ensuring an excellent anti-biofilm formation ability. Moreover, ZP are able to respond upon external stimuli such as temperature, pH, salt concentration changes which in combination with their anti-biofouling effect render this type of polymers as materials with a high potential in biomedical applications. The present work is focused on the development of zwitterionic hydrogels for efficient treatment of highly exudating and hard-to-heal chronic wounds. To this purpose, two types of ZP networks with different crosslinking degree were synthesized - polysulfobetaine (PSB) and polycarboxybetaine (PCB) ones. They were characterized in terms of their physico-mechanical properties, e.g. microhardness, swelling ability, smart behaviour. Furthermore, the potential of ZP networks to resist biofilm formation towards Staphylococcus aureus and Escherichia coli was studied. Their ability to reduce the high levels of myeloperoxidase and metalloproteinase, two enzymes that are part of the chronic wounds enviroenment, was revealed. Moreover, the in vitro cytotoxic assessment of PSB and PCB networks along with their in vivo performance in rats was also studied to reveal their high biocompatibility.

Keywords: absorption properties, biocompatibility, enzymatic inhibition activity, wound healing, zwitterionic polymers

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

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Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

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Authors: Freddy Rodriguez Saza, Erika Sanabria, Jair Tibana

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Currently, the important role of neurosciences in the professional training of the physical educator is known, highlighting in the teaching-learning process aspects such as the nervous structures involved in the adjustment of posture and movement, the neurophysiology of locomotion, the process of nerve impulse transmission, and the relationship between physical activity, learning, and cognition. The teaching-learning process of neurosciences is complex, due to the breadth of the contents, the diversity of teaching contexts required, and the demanding ability to relate concepts from different disciplines, necessary for the correct understanding of the function of the nervous system. This text presents the results of the application of a didactic environment based on the Allosteric Learning Model in morphophysiology students of the Faculty of Military Physical Education, Military School of Cadets of the Colombian Army (Bogotá, Colombia). The research focused then, on analyzing the change in the cognitive structure of the students on neurosciences. Methodology. [1] The predominant learning styles were identified. [2] Students' cognitive structure, core concepts, and threshold concepts were analyzed through the construction of Pathfinder Associative Networks. [3] Didactic Units in Neuroscience were designed to favor metacognition, the development of Executive Functions (working memory, cognitive flexibility, and inhibitory control) that led students to recognize their errors and conceptual distortions and to overcome them. [4] The Teacher's Professional Knowledge and the role of the assessment strategies applied were taken into account, taking into account the perspective of the Dynamizer, Obstacle, and Questioning axes. In conclusion, the study found that physical education students achieved significant learning in neuroscience, favored by the development of executive functions and by didactic environments oriented with the predominant learning styles and focused on increasing cognitive networks and overcoming difficulties, neuromyths and neurophobia.

Keywords: allosteric learning model, military physical education, neurosciences, pathfinder associative networks, teacher professional knowledge

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Authors: Humeyra Bolakar Tosun

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The transport sector has an undisputed place in human life. People need transport access to continuous increase day by day with growing population. The number of rail network, urban transport planning, infrastructure improvements, transportation management and other related areas is a key factor affecting our country made it quite necessary to improve the work of transportation. In this context, it plays an important role in domestic rail freight demand planning. Alternatives that the increase in the transportation field and has made it mandatory requirements such as the demand for improving transport quality. In this study generally is known and used in studies by the definition, rail freight transport, railway line length, population, energy consumption. In this study, Iron Road Load Net Demand was modeled by multiple regression and ANN methods. In this study, model dependent variable (Output) is Iron Road Load Net demand and 6 entries variable was determined. These outcome values extracted from the model using ANN and regression model results. In the regression model, some parameters are considered as determinative parameters, and the coefficients of the determinants give meaningful results. As a result, ANN model has been shown to be more successful than traditional regression model.

Keywords: railway load carrying, neural network, modelling transport, transportation

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Authors: Shathya Duobiene, Gediminas Račiukaitis

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Wireless Sensor Networks (WSNs) are an emerging technology that opens up a new field of research. The significant advance in WSN leads to an increasing prevalence of various monitoring applications and real-time assistance in labs and factories. Selective surface activation induced by laser (SSAIL) is a promising technology that adapts to the WSN design freedom of shape, dimensions, and material. This article proposes and implements a WSN-based temperature and humidity monitoring system, and its deployed architectures made for the monitoring task are discussed. Experimental results of newly developed sensor nodes implemented in university campus laboratories are shown. Then, the simulation and the implementation results obtained through monitoring scenarios are displayed. At last, a convenient solution to keep the WSN alive and functional as long as possible is proposed. Unlike other existing models, on success, the node is self-powered and can utilise minimal power consumption for sensing and data transmission to the base station.

Keywords: IoT, network formation, sensor nodes, SSAIL technology

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Authors: Rima Al Garni, Emad Al Shdaifat, Sahar Elmetwalli, Mohammad Alzaid, Abdulrahman Alghothayyan, Sara Al Abd Al Hai, Seham Al Rashidi

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Aim: To investigate the prevalence of non-adherence of patients on haemodialysis and explore their perception of the importance of adherence to the therapeutic regime and estimate the predictors for adherence to the therapeutic regime. Background: End-stage renal disease is commonly treated by haemodialysis. Haemodialysis treatment alone is not effective in replacing kidney function. Diet and fluid restrictions, along with supplementary medications, are mandatory for the survival and well-being of patients. Hence, adherence to this therapeutic regimen is essential. However, non-adherence to diet and fluid restrictions, medications, and dialysis is common among patients on haemodialysis. Design: Descriptive cross-sectional method was applied to investigate the prevalence of non-adherence to treatment, including adherence to diet and fluid restrictions, medications, and dialysis sessions. Methods: Structured interviews were conducted using the Arabic version of the End-Stage Renal Disease Adherence Questionnaire. The sample included 230 patients undergoing haemodialysis in the Eastern Region of Saudi Arabia. Data were analysed using descriptive statistics and multiple regressions. Results/Findings: Most patients had good adherence (71.3%), and only 3.9% had poor adherence. The divorced or widowed patient had higher adherence compared with single (P=0.011) and married participants (P=0.045) through using the post hoc test. Patients above 60 years had higher adherence compared to patients below 40 years old (P=0.016) using the post hoc test. For the perception of the importance of adherence to the therapeutic regime subscale, two-thirds of the patients had lower scores (<=11). Conclusion: Adherence to therapeutic regime is high for three fourth of patients undergoing haemodialysis in the Eastern Region of Saudi Arabia; this finding is similar to results abstracted from the local literature. This result would help us highlight the needs of patients who are not compliant with their treatment plans and investigate the consequences of non-adherence on their well-being and general health. Hence, plan individualised therapeutic programmes that could raise their awareness and influence their adherence to therapeutic regimes.

Keywords: adherence to treatment, haemodialysis, end stage renal disease, diet and fluid restrictions

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Authors: Erimias Firre

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This study is situated within the religio-cultural milieu of Coptic Orthodox Christians of the Tigrinya ethnic group in Eritrea. With this ethnic group being conservative and traditionally bound, extended family structures dissected along various clans and expansive community networks are the distinguishing mark of its members. Notably, Coptic Tigrinya constitutes the largest percentage of all Christian denominations in Eritrea. As religious, cultural beliefs, rituals and teachings permeate in all aspects of social life, a distinct worldview and traditionalized health and illness conceptualization are common. Accordingly, this study argues that religio-culturally bound illness ideologies immensely determine the perception, help seeking behavior and healing preference of Coptic Tigrinya in Eritrea. The study bears significance in the sense that it bridges an important knowledge gap, given that it is ethno-linguistically (within the Tigrinya ethnic group), spatially (central region of Eritrea) and religiously (Coptic Christianity) specific. The conceptual framework guiding this research centered on the social determinants of mental health, and explores through the lens of critical theory how existing systems generate social vulnerability and structural inequality, providing a platform to reveal how the psychosocial model has the capacity to emancipate and empower those with mental disorders to live productive and meaningful lives. A case study approach was employed to explore the interrelationship between religio-cultural beliefs and practices and perception of common mental disorders of depression, anxiety, bipolar affective, schizophrenia and post-traumatic stress disorders and the impact of these perceptions on people with those mental disorders. Purposive sampling was used to recruit 41 participants representing seven diverse cohorts; people with common mental disorders, family caregivers, general community members, ex-fighters , priests, staff at St. Mary’s and Biet-Mekae Community Health Center; resulting in rich data for thematic analysis. Findings highlighted current religio-cultural perceptions, causes and treatment of mental disorders among Coptic Tigrinya result in widespread labelling, stigma and discrimination, both of those with mental disorders and their families. Traditional healing sources are almost exclusively tried, sometimes for many years, before families and sufferers seek formal medical assessment and treatment, resulting difficult to treat illness chronicity. Service gaps in the formal medical system result in the inability to meet the principles enshrined in the WHO Mental Health Action Plan 2013-2020 to which the Eritrean Government is a signatory. However, the study found that across all participant cohorts, there was a desire for change that will create a culture whereby those with mental disorders will have restored hope, connectedness, healing and self-determination.

Keywords: Coptic Tigrinya, mental disorders, psychosocial model social integration and recovery, traditional healing

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Authors: A. Mohammadpour, Ebrahim Najafi Kajabad, Ghazale Ipakchi

Abstract:

Presently, computer networks’ security rise in importance and many studies have also been conducted in this field. By the penetration of the internet networks in different fields, many things need to be done to provide a secure industrial and non-industrial network. Fire walls, appropriate Intrusion Detection Systems (IDS), encryption protocols for information sending and receiving, and use of authentication certificated are among things, which should be considered for system security. The aim of the present study is to use the outcome of several algorithms, which cause decline in IDS errors, in the way that improves system security and prevents additional overload to the system. Finally, regarding the obtained result we can also detect the amount and percentage of more sub attacks. By running the proposed system, which is based on the use of multi-algorithmic outcome and comparing that by the proposed single algorithmic methods, we observed a 78.64% result in attack detection that is improved by 3.14% than the proposed algorithms.

Keywords: intrusion detection systems, clustering, k-means, k-medoids, SV clustering, ensemble

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Authors: Neda Mozaffari

Abstract:

This study represents an investigation into the poetics of space within Annie Ernaux's autobiographical work La honte, highlighting the intricate interplay among space, the individual, and society. The research aims to dissect the spatial dimension of the town Yvetot, the referential locale of the author's childhood, drawing upon the frameworks of geocriticism and geopoetics. Our analysis exposes a profound dialectical tension fundamentally predicated on the binaries of "interior/exterior" and "here/there," emphasizing how space and its occupants may reciprocally influence each other. This endeavor aspires to attribute meaning to space in Ernaux's writing in La honte and to forge a connection between spatial elements and the author's autobiographical perspective, heavily imprinted by social dynamics. Ernaux's approach fluctuates between certain binaries that segment space according to the collective perception of social hierarchy, thus unveiling the author's preoccupation with social distancing. Consequently, space transforms into a structured milieu that transfers fear and insecurity to the child, where spatial and architectural segregation further cements class divisions in terms of the language employed by its inhabitants. Ernaux's depiction of space serves both as a repository of collective memory and an instrument of social distinction, where her autobiographical perception echoes within a collective geography marked by class determinism and culture.

Keywords: geocriticism, literary study, social class, social space, spatial analysis

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Authors: Anna Siegler, Sara Bigazzi, Sara Serdult, Ildiko Bokretas

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Social identity emerging from group membership defines the representational processes of our social reality. Based on our theoretical assumption the subjective perception of identity threat leads to an instable identity structure. The need to re-establish the positive identity will lead us to strengthen group boundaries. Prejudice in our perspective offer psychological security those who thinking in exclusive barriers, and we suggest that those who identify highly with their ingroup/national identity and less with superordinate identities take distance from others and this is related to their perception of threat. In our study we used a newly developed questionnaire, the Multiple Threat and Prejudice Questionnaire (MTPQ) which measure identity threat at different dimensions of identification (national, existential, gender, religious) and the distancing of different outgroups, over and above we worked with Social Dominance Orientation (SDO) and Identification with All Humanity Scale (IWAH). We conduct one data collection (N=1482) in a Hungarian sample to examine the connection between national threat and distance-taking, and this survey includes the investigation (N=218) of identification with different group categories. Our findings confirmed that those who feel themselves threatened in their national identity aspects are less likely to identify themselves with superordinate groups and this correlation is much stronger when they think about the nation as a bio-cultural unit, while if nation defined as a social-economy entity this connection is less powerful and has just the opposite direction.

Keywords: group boundaries, identity threat, prejudice, superordinate groups

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Authors: Amit Verma, Pardeep Kaur

Abstract:

In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there.

Keywords: component based development, clustering, back propagation algorithm, keyword based retrieval

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