Search results for: cognitive image dimension

Authors: Naveen Kumar, Shyambihari Prajapati

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Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.

Keywords: Industry4.0, sensor dashboard design, cyber-physical production system, Interface designer

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Authors: M. Krishna

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The study was intended to identify if scalp cooling therapy is effective on preventing chemotherapy-induced hair loss among cancer patients. Critical literature of non-randomized controlled trials was used to investigate whether scalp cooling therapy is effective on preventing chemotherapy-induced alopecia. The review identified that scalp cooling therapy is effective on preventing chemotherapy-induced alopecia. Most of the patients receiving chemotherapy experience alopecia. It is also perceived as the worst effect of chemotherapy. This may be severe and lead the patients to withdraw the chemo treatment. The image disturbance caused by alopecia will make the patient depressed and will lead to declined immunity. With the knowledge on effectiveness of scalp cooling therapy on preventing chemotherapy-induced alopecia, patient undergoing chemotherapy will not be hesitant to undergo the treatment. Patients are recommended to go through scalp cooling therapy every chemo cycle and the proper therapy duration is 30 minutes before, during chemo. The suggested duration of the scalp cooling therapy is 45-90 minutes for an effective and positive outcome. This finding is excluding other factors of alopecia such as menopause, therapeutic drugs, poor hair density, liver function problems, and drug regimes.

Keywords: alopecia, cancer, chemotherapy, scalp cooling therapy

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology mapping, R-GNN, knowledge extraction, large language models, NER, knowlege graph

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Authors: Pietro Mortini, Marco Losa

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Objective: Resection of large lesions growing into the third ventricle remains a demanding surgery, sometimes at risk of severe post-operative complications. Transcallosal and transcortical routes were considered as approaches of choice to access the third ventricle, however neurological consequences like memory loss have been reported. We report clinical results of the previously described combined interhemispheric sub-commissural translaminaterminalis approach (CISTA) for the resection of large lesions located in the third ventricle. Methods: Authors conducted a retrospective analysis on 10 patients, who were operated through the CISTA, for the resection of lesions growing into the third ventricle. Results: Total resection was achieved in all cases. Cognitive worsening occurred only in one case. No perioperative deaths were recorded and, at last follow-up, all patients were alive. One year after surgery 80% of patients had an excellent outcome with a KPS 100 and Glasgow Outcome score (GOS) Conclusion: The CISTA represents a safe and effective alternative to transcallosal and transcortical routes to resect lesions growing into the third ventricle. It allows for a multiangle trajectory to access the third ventricle with a wide working area free from critical neurovascular structures, without any section of the corpus callosum, the anterior commissure and the fornix.

Keywords: craniopharingioma, surgery, sub-commissural translaminaterminalis approach (CISTA),

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Authors: Lee Bih Ni, Zulfhikar Rabe, Nurul Asyikin Hassan

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The Ministry of Education Malaysia dynamically and drastically made the subject of History mandatory to be in force in 2013. This is in recognition of the nation's heritage and treasures in maintaining true facts and information for future generations of the State. History reveals the civilization of a nation and the fact of national cultural heritage. Civilization needs to be preserved as a legacy of sovereign heritage. Today's generation is the catalyst for future heirs who will support the principle and direction of the country. In line with the National Education Philosophy that aims to shape the potential development of individuals holistically and uniquely in order to produce a balanced and harmonious student in terms of intellectual, spiritual, emotional and physical. Hence, understanding the importance of studying the history subject as a pillar of identity and the history of nationhood is to be a priority in the pursuit of knowledge and empowering the spirit of statehood that is nurtured through continuous learning at school. Judging from the aspect of teacher leadership role in integrating history in a combined way based on Teacher Education Philosophy. It empowers the teaching profession towards the teacher to support noble character. It also supports progressive and scientific views. Teachers are willing to uphold the State's aspirations and celebrate the country's cultural heritage. They guarantee individual development and maintain a united, democratic, progressive and disciplined society. Teacher's role as a change and leadership agent in education begins in the classroom through formal or informal educational processes. This situation is expanded in schools, communities and countries. The focus of this paper is on the role of teacher leadership influencing the effectiveness of teaching and learning history in the classroom environment. Leadership guides to teachers' perceptions on the role of teacher leadership, teaching leadership, and the teacher leadership role and effective teacher leadership role. Discussions give emphasis on aspects of factors affecting the classroom environment, forming the classroom agenda, effective classroom implementation methods, suitable climate for historical learning and teacher challenges in implicating the effectiveness of teaching and learning processes.

Keywords: teacher leadership, leadership lessons, effective classroom, effective teacher

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Authors: T. Garba, T. O. Quddus, Y. Y. Babanyara, M. A. Modibbo

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Desertification is define as the changing of productive land into a desert as the result of ruination of land by man-induced soil erosion, which forces famers in the affected areas to move migrate or encourage into reserved areas in search of a fertile land for their farming activities. This study therefore used remote sensing imageries to determine the level of changes in the vegetative areas. To achieve that Normalized Difference of the Vegetative Index (NDVI), classified imageries and image slicing derived from landsat TM 1986, land sat ETM 1999 and Nigeria sat 1 2007 were used to determine changes in vegetations. From the Classified imageries it was discovered that there a more natural vegetation in classified images of 1986 than that of 1999 and 2007. This finding is also future in the three NDVI imageries, it was discovered that there is increased in high positive pixel value from 0.04 in 1986 to 0.22 in 1999 and to 0.32 in 2007. The figures in the three histogram also indicted that there is increased in vegetative areas from 29.15 Km2 in 1986, to 60.58 Km2 in 1999 and then to 109 Km2 in 2007. The study recommends among other things that there is need to restore natural vegetation through discouraging of farming activities in and around the natural vegetation in the study area.

Keywords: vegetative index, classified imageries, change detection, landsat, vegetation

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Authors: Yu-Chen Wei, Dan-Leng Wang

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This study examines whether the reputation from media press affect the financial performance and market abnormal returns around the announcement of corporate social responsibility (CSR) award in the Taiwan Stock Market. The differences between this study and prior literatures are that the media reputation of media coverage and net optimism are constructed by using content analyses. The empirical results show the corporation which won CSR awards could promote financial performance next year. The media coverage and net optimism related to CSR winner are higher than the non-CSR companies prior and after the CSR award is announced, and the differences are significant, but the difference would decrease when the day was closing to announcement. We propose that non-CSR companies may try to manipulate media press to increase the coverage and positive image received by investors compared to the CSR winners. The cumulative real returns and abnormal returns of CSR winners did not significantly higher than the non-CSR samples however the leading returns of CSR winners would higher after the award announcement two months. The comparisons of performances between CSR and non-CSR companies could be the consideration of portfolio management for mutual funds and investors.

Keywords: corporate social responsibility, financial performance, abnormal returns, media, reputation management

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Authors: Andi Syahputra, R. H. Jatmiko, D. R. Hizbaron

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Land surface temperature (LST) in an area is influenced by conditions of vegetation density, building density, and the number of inhabitants who live in the area. Medan City is one of the largest cities in Indonesia, with a high rate of change from vegetation to developed land. This study aims to identify the relationship between the percentage of building density and land surface temperature in Medan City. Pixel image analysis method is carried out to obtain the value of building density in pixel images of Landsat 8 images with the help of WorldView-2 satellite imagery. The results showed the highest land surface temperature in 2018 of 35, 4°C was found in Medan Perjuangan District, and the lowest was 22.5°C in Medan Belawan District. Building density samples with a density level of 889.17 m were also found in Medan Perjuangan District, while the lowest building density sample was found in Medan Timur District. Linear regression analysis of the effect of building density with land surface temperature obtained a correlation (R) was 0.64, and a coefficient of determination (R²) was 0.411 and modeling of building density based on the LST has a correlation (R), and a coefficient of determination (R²) was 0.72 with The RMSE obtained 0.853.

Keywords: land surface temperature, Landsat, imagery, building density, vegetation, density

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Nazmul Shahadat, Anthony S. Maida

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In recent years, hypercomplex inspired neural networks improved deep CNN architectures due to their ability to share weights across input channels and thus improve cohesiveness of representations within the layers. The work described herein studies the effect of replacing existing layers in an Axial Attention ResNet with their quaternion variants that use cross-channel weight sharing to assess the effect on image classification. We expect the quaternion enhancements to produce improved feature maps with more interlinked representations. We experiment with the stem of the network, the bottleneck layer, and the fully connected backend by replacing them with quaternion versions. These modifications lead to novel architectures which yield improved accuracy performance on the ImageNet300k classification dataset. Our baseline networks for comparison were the original real-valued ResNet, the original quaternion-valued ResNet, and the Axial Attention ResNet. Since improvement was observed regardless of which part of the network was modified, there is a promise that this technique may be generally useful in improving classification accuracy for a large class of networks.

Keywords: axial attention, representational networks, weight sharing, cross-channel correlations, quaternion-enhanced axial attention, deep networks

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Authors: Shinhao Yang, Hsiao-Chien Huang, Chin-Hsiang Luo

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The leakage of protective clothing is an important issue in the occupational health field. There is no quantitative method for measuring the leakage of personal protective equipment. This work aims to measure the quantitative leakage of the personal protective equipment by using the fluorochrome aerosol tracer. The fluorescent aerosols were employed as airborne particulates in a controlled chamber with ultraviolet (UV) light-detectable stickers. After an exposure-and-leakage test, the protective equipment was removed and photographed with UV-scanning to evaluate areas, color depth ratio, and aerosol deposition and shielding effects of the areas where fluorescent aerosols had adhered to the body through the protective equipment. Thus, this work built a calculation software for quantitative leakage ratio of protective clothing based on fluorescent illumination depth/aerosol concentration ratio, illumination/Fa ratio, aerosol deposition and shielding effects, and the leakage area ratio on the segmentation. The results indicated that the two-repetition total leakage rate of the X, Y, and Z type protective clothing for subject T were about 3.05, 4.21, and 3.52 (mg/m2). For five-repetition, the leakage rate of T were about 4.12, 4.52, and 5.11 (mg/m2).

Keywords: fluorochrome, deposition, shielding effects, digital image processing, leakage ratio, personal protective equipment

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Authors: Itsuo Yokoyama, Rika Kikuti, Naoko Watabe

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Introduction: It has been known that chronic kidney disease (CKD) patients can benefit from physical exercise during dialysis therapy improving aerobic capacity, muscle function, cardiovascular function, and overall health-related quality of life. This study aimed to evaluate the effectiveness of dialysis rehabilitation. Materials and Methods: A total of 55 patients underwent two-hour resistance exercise training during each hemodialysis session for three consecutive months. Various routine clinical data were collected, including the calculation of the planar dimension of the muscle area in both upper legs at the level of the ischial bone. This area calculation was possible in 26 patients who had yearly plain abdominal computed tomography (CT) scans. DICOM files from the CT scans were used with 3D Slicer software for area calculation. An age and sex-matched group of 26 patients without dialysis rehabilitation also had yearly CT scans during the study period for comparison. Clinical data were compared between the two groups: Group A (rehabilitation) and Group B (non-rehabilitation). Results: There were no differences in basic laboratory data between the two groups. The average muscle area before and after rehabilitation in Group A was 212 cm² and 216 cm², respectively. In Group B, the average areas were 230.0 cm² and 225.8 cm². While there was no significant difference in absolute values, the average percentage increase in muscle area was +1.2% (ranging from -7.6% to 6.54%) for Group A and -2.0% (ranging from -12.1% to 4.9%) for Group B, which was statistically significant. In Group A, 9 of 26 were diabetic (DM), and 13 of 26 in Group B were non-DM. The increase in muscle area for DM patients was 4.9% compared to -0.7% for non-DM patients, which was significantly different. There were no significant differences between the two groups in terms of nutritional assessment, Kt/V, or incidence of clinical complications such as cardiovascular events. Considerations: Dialysis rehabilitation has been reported to prevent muscle atrophy by increasing muscle fibers and capillaries. This study demonstrated that muscle volume increased after dialysis exercise, as evidenced by the increased muscle area in the thighs. Notably, diabetic patients seemed to benefit more from dialysis exercise than non-diabetics. Although this study is preliminary due to its relatively small sample size, it suggests that intradialytic physical training may improve insulin utilization in muscle fiber cells, particularly in type II diabetic patients where insulin receptor function and signaling are altered. Further studies are needed to investigate the detailed mechanisms underlying the muscle hypertrophic effects of dialysis exercise.

Keywords: dialysis, excercise, muscle, hypertrophy, diabetes, insulin

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

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Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

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Authors: A. I. A. Rahman, Sh-Hussain Salleh, K. Ahmad, K. Anuar

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Analysis of vocal fold vibration is essential for understanding the mechanism of voice production and for improving clinical assessment of voice disorders. This paper presents a Dynamic Time Warping (DTW) based approach to analyze and objectively classify vocal fold vibration patterns. The proposed technique was designed and implemented on a Glottal Area Waveform (GAW) extracted from high-speed laryngeal images by delineating the glottal edges for each image frame. Feature extraction from the GAW was performed using Linear Predictive Coding (LPC). Several types of voice reference templates from simulations of clear, breathy, fry, pressed and hyperfunctional voice productions were used. The patterns of the reference templates were first verified using the analytical signal generated through Hilbert transformation of the GAW. Samples from normal speakers’ voice recordings were then used to evaluate and test the effectiveness of this approach. The classification of the voice patterns using the technique of LPC and DTW gave the accuracy of 81%.

Keywords: dynamic time warping, glottal area waveform, linear predictive coding, high-speed laryngeal images, Hilbert transform

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Authors: Hailemariam Gebremichael Gebretsadik, Abrham Hagos Tesfaslasea

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To satisfy the high need for ICT entrepreneurship and rectify the weak entrepreneurial culture in Ethiopia, the country has established ICT Business incubation centers with the intention of preventing business failures, promoting innovation, and accelerating the growth and success of firms. This study investigates the role of business incubators and social capital on the innovation and growth of firms in Ethiopia. In this research, innovation and growth of firms were considered as dependent variables, whereas business incubation and social capital were treated as independent variables. The researcher employed an e-mail survey among 137 tenant Firms (Firms that joined and/or graduated to/from the Business incubation centers available in Ethiopia) to collect the data and obtained 113 responses that were appropriate for this research. The result of this study reveals that the dimensions of business incubation (physical resource, business support, and networking) have a significant effect on the innovation of Firms, but these dimensions of business incubation do not show a significant effect on the growth of firms. On the other hand, the dimensions of social capital (structural, cognitive, and relational) show a significant positive impact on the likelihood of Firms' growth but not on the innovation of firms. Moreover, the result of this study indicates that the dimensions of business incubation and social capital together have a significant effect on the likelihood of tenant firms innovating and growing.

Keywords: business incubation, innovation, social capital, tenant firms

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: Eirini Oikonomopoulou

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Paper is dealing with gentrification of a poor central historic district of Fener and Balat in Istanbul, Turkey and propose ålans and principles of a neighborhood. Istanbul is located in a special geographic place, just in the meeting of Europe and Asia and it has a long and great history, facts that had affected the urban form of the city. Trough the time different civilizations inhabited in the city and they changed it by giving different character to its parts. The modernization of Istanbul brought western ideas into the historic organic urban fabric and put in the first priority the need for a clear and strong car-road/highway network in order to improve the car accessibility along the city. Following that model, transformation of public spaces was based on the driving experience. New public spaces was formulated to be the new symbol of Turkish Republic, to give a beautiful and clean image of the modern Turkish city, as well as work as landmarks across the highway network. Even if city is upgraded, bad quality neighborhoods still exist, far and near to the historic city center. One of them is Fener/Balat, which is located in Fatih district on the European side of Istanbul. This project aims to analyze the urban qualities of that neighborhood (mahalle) and propose a better, qualitative urban space towards a denser, greener and more inclusive neighborhood which could be an example for the whole city.

Keywords: urban design, upgrade neighborhood, Istanbul, sustanability

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Authors: Vanshika Chutani, Priya Bhatnagar

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The pandemic has brought us to a standpoint where stress as a physical, cognitive, and behavioral construct is inevitable. The current research provides an overview of the relationship between stress and dysfunctional eating behavior during the challenging time of the COVID-19 pandemic. The present paper also aims to highlight the gender-specific differences in perception of stress and its correlation with dysfunctional eating behavior in the COVID-19 pandemic. Perceived Stress Scale-10 (PSS) and Adult Eating Behavior questionnaire (AEBQ) were used on a heterogeneous sample between 20-40 years. The research was conducted on 50 participants, 25 male, and 25 female. Quantitative analysis was done with SPSS 22.0. The results of the investigation revealed a significant difference in stress level, t(48)=2.01, p<0.01, with women (M=22.24. SD=5.23) having a higher stress level than men (M=19.04, SD=4.89). There was no significant difference in dysfunctional eating behavior between males and females. There was a significant positive correlation between stress and dysfunctional eating behavior in females, whereas, in males, there was no significant positive correlation between stress and dysfunctional eating behavior. The research extrapolates that the pandemic led to elevated stress levels in both genders and gender differences existed, and males & females responded differently on dysfunctional eating behavior. The research has also outlined intervention to help individuals cope with stress and dysfunctional eating behavior. The findings of the research propose the execution of different intervention programs and psychological first aid to help individuals who are predisposed to develop eating disorders.

Keywords: stress, dysfunctional eating behavior, gender-specific differences, COVID-19

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Authors: Shi-Yu Xu

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The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

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Authors: Wenqiu Cao

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Suicide prevention is a global problem that needs to be taken seriously. Investigating the mechanisms of suicide in major depressive disorder (MDD) separately through neuroimaging technology is essential for effective suicide prevention. And it’s particularly urgent in geriatric depressive patients since older adults are more likely to use rapidly deadly means, and suicidal behavior is more lethal for older adults. The current study reviews five studies related to suicide in geriatric MDD that uses neuroimaging methodology in order to analyze the relevant neurobiological mechanisms. The majority of the studies found significant white matter and grey matter reduction or lesion widespread in multiple brain regions, including the frontal and parietal regions, the midbrain, the external capsule, and the cerebellum. Regarding the cognitive impairment in geriatric MDD, the reward signals were found weakened in the paralimbic cortex. The functional magnetic resonance imaging (fMRI) studies also found hemodynamic changes in the right dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), and right frontopolar cortex (FPC) regions in late-life MDD patients with suicidal ideation. Future studies should consider the age of depression onset, more accurate measurements of suicide, larger sample size, and longitudinal design.

Keywords: brain imaging, geriatric major depressive disorder, suicidality, suicide

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Authors: Hanady Al-Zagheer

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The purpose of this paper research is to introduce the role of the social media (face book) in growing small and medium enterprises in Jordan, Today’s developments of information technologies are dazzling. Using information technologies results in having advantages in competition, decreasing costs, gaining time, and getting and sharing information. Now it is possible to state that there are different types of usage within the information technologies. Small and medium enterprises have been grown rapidly in recent years and continue to grow. Jordanian females have played a large role in the growth of entrepreneurship and have made an impact on household economics. Virtual storefronts have allowed these women to balance roles assigned by tradition and culture while becoming successful providers. If you have a small business with a limited public relations and advertising budget, Facebook can be a cost effective way to promote your services because opening an account is free. However, this can work against you if you do not maintain the page. A Face book page without frequent updates can destroy your brand value and image. According to a 2009 Computerworld article by Lisa Hoover, having a Facebook page that looks abandoned is worse than having no page at all. You might need to hire someone or pay an employee to update your business’s Facebook page.

Keywords: social media, social media small, medium enterprises, Jordan

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Authors: L. Ngowi, N. H. Mvungi

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This paper critically examines the evolution of socio-technical systems theory, its practices, and challenges in system design and development. It examines concepts put forward by researchers focusing on the application of the theory in software engineering. There are various methods developed that use socio-technical concepts based on systems engineering without remarkable success. The main constraint is the large amount of data and inefficient techniques used in the application of the concepts in system engineering for developing time-bound systems and within a limited/controlled budget. This paper critically examines each of the methods, highlight bottlenecks and suggest the way forward. Since socio-technical systems theory only explains what to do, but not how doing it, hence engineers are not using the concept to save time, costs and reduce risks associated with new frameworks. Hence, a new framework, which can be considered as a practical approach is proposed that borrows concepts from soft systems method, agile systems development and object-oriented analysis and design to bridge the gap between theory and practice. The approach will enable the development of systems using socio-technical systems theory to attract/enable the system engineers/software developers to use socio-technical systems theory in building worthwhile information systems to avoid fragilities and hostilities in the work environment.

Keywords: socio-technical systems, human centered design, software engineering, cognitive engineering, soft systems, systems engineering

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Authors: Beruk Berhanu Desalegn, Gelana Mulu

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Adolescence, especially for females, is a period of an ongoing risk behavior that triggers development of adverse health outcomes during adulthood. This study aimed to investigate the weight control practice and its associated factors among high school female-adolescents in Hawassa town, Ethiopia. A school-based cross-sectional study was conducted on 552 female-adolescents in Hawassa town. The study was conducted between December, 2020 to January, 2021. SPSS version 26 was used to analyse the data from the pre-tested questionnaire of socio-demographic, economic, socio-cultural, and related information. Among the total female-adolescents, 38.6% [95% CI= 34.5-42.8%] took on weight control practices. The study further revealed the condition of the weight control practice to be healthy (20.5%), unhealthy(25.9%, and the rest to be both healthyand unhealthy(7.8%). The multivariate regression model, cutoff p < 0.05, disclosed that predicters like late adolescent age [AOR=1.98; 95% CI=1.33-2.95], middle wealth status [AOR=2.72; 95% CI=1.60-4.63], high wealth status [AOR=5.69; 95% CI=3.43-9.46], normal BMI [AOR=2.36; 95% CI=1.18-4.71], overweight [AOR=2.45; 95% CI=1.13-5.28], mild depression [AOR=1.72; 95% CI=1.12-2.66] and dissatisfied own mid-torso body image [AOR=2.68; 95% CI=1.52-4.73] were found to have significant association with weight control practice. Therefore, it may be benefiting to consider the findings of this study for interventions associated with female adolescents weight control practices.

Keywords: female-adolescents, highschool, weight control practice, Ethiopia

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Authors: Benoît Bucher, Hika Kuroshima, Kazuo Fujita

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Although altruism is commonly observed in humans and is considered one of the most important factors in the survival of our species, its cognitive mechanisms and evolutionary roots are yet to be explained. This study is based on the previous findings that bonobos (Pan Paniscus) preferred to share a limited amount of food with others regardless of their relationships with the others. Findings such as this suggest that humans’ propensity for altruistic food-sharing may be shared among apes and may have evolved much longer ago than previously considered. We thus adapted the previous experimental design using tufted capuchins (Cebus apella), New World monkeys separating from humans about 40 million years ago. In order to achieve this, 12 pairs of capuchins (consisting of a benefactors and a partner) were tested in a row of two adjacent cages separated by a swinging door locked by a key (Fig.1). We observed whether the monkeys in possession of food (the benefactors) would allow their partner to enter their cage by unlocking the door between them. Results showed that the monkeys clearly preferred to monopolize the food for themselves, even though they in a few cases unlocked the door after eating the preferred food. This suggests that this species, which has been shown to be sensitive to the others’ welfare, would not actively share food at a cost of their own. Although further studies are needed, our results suggest the existence of significant differences in the evolutionary development of the pro social tendencies between bonobos and capuchin monkeys.

Keywords: altruism, capuchin monkeys, food sharing, pro social behaviors

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Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Sari Myréen

Abstract:

The aim of this study was to evaluate the role of multisensory elements in enhancing and facilitating foreign language acquisition among adult students in a language classroom. The use of multisensory elements enables the creation of a student-centered classroom, where the focus is on individual learner’s language learning process, perceptions and motivation. Multisensory language learning is a pedagogical approach where the language learner uses all the senses more effectively than in a traditional in-class environment. Language learning is facilitated due to multisensory stimuli which increase the number of cognitive connections in the learner and take into consideration different types of learners. A living lab called Multisensory Space creates a relaxed and receptive state in the learners through various multisensory stimuli, and thus promotes their natural foreign language acquisition. Qualitative and quantitative data were collected in two questionnaire inquiries among the Finnish students of a higher education institute at the end of their basic French courses in December 2014 and 2016. The inquiries discussed the effects of multisensory elements on the students’ motivation to study French as well as their learning outcomes. The results show that the French classes in the Multisensory Space provide the students with an encouraging and pleasant learning environment, which has a positive impact on their motivation to study the foreign language as well as their language learning outcomes.

Keywords: foreign language acquisition, pedagogical approach, multisensory learning, transcultural learning

Procedia PDF Downloads 388

Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

Abstract:

Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, features extraction, offline signature verification, voting-based classifier

Procedia PDF Downloads 381

Authors: Abe Degale D., Cheng Jian

Abstract:

When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

Procedia PDF Downloads 111

Authors: Kay Thinzar Phu, Lwin Lwin Oo

Abstract:

In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

Procedia PDF Downloads 315

Authors: Elyas Akbari, Jafar Hasani, Newsha Dehestani, Mohammad Khaleghi, Alireza Moradi

Abstract:

The aim of the present study was to assess the effect of emotional experience induction in the mirror neurons systems (MNS) activity with regard to the spectrum of depressive symptoms. For this purpose, at first stage, 449 students of Kharazmi University of Tehran were selected randomly and completed the second version of the Beck Depression Inventory (BDI-II). Then, 36 students with standard Z-score equal or above +1.5 and equal or equal or below -1.5 were selected to construct two groups of high and low spectrum of depressive symptoms. In the next stage, the basic activity of MNS was recorded (mu wave) before presenting the positive and negative emotional video clips by Electroencephalography (EEG) technique. The findings related to emotion induction (neutral, negative and positive emotion) demonstrated that the activity of recorded mirror neuron areas had a significant difference between the depressive and non-depressive groups. These findings suggest that probably processing of negative emotions in depressive individuals is due to the idea that the mirror neurons in motor cortex matched up the activity of cognitive regions with the person’s schema. Considering the results of the present study, it could be said that the MNS provides a substrate where emotional disorders can be studied and evaluated.

Keywords: emotional experiences, mirror neurons, depressive symptoms, negative and positive emotion

Procedia PDF Downloads 360