Search results for: multiple scales

Authors: Bryan Jenkins

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Introduction: The expansion of irrigation in the Canterbury region has led to the sustainability limits being reached for water availability and the cumulative effects of land use intensification. The institutional framework under New Zealand’s Resource Management Act was found to be an inadequate basis for managing water at sustainability limits. An alternative paradigm for water management was developed based on collaborative governance and nested adaptive systems. This led to the formulation and implementation of the Canterbury Water Management Strategy. Methods: The nested adaptive system approach was adopted. Sustainability issues were identified at multiple spatial and time scales and defined potential failure pathways for the water resource system. These included biophysical and socio-economic issues such as water availability, cumulative effects on water quality due to land use intensification, projected changes in climate, public health, institutional arrangements, economic outcomes and externalities, and, social effects of changing technology. This led to the derivation of sustainability strategies to address these failure pathways. The collaborative governance approach involved stakeholder participation and community engagement to decide on a regional strategy; regional and zone committees of community and rūnanga (Māori groups) members to develop implementation programmes for the strategy; and, farmer collectives for operational management. Findings: The strategy identified improvements in the efficiency of use of water already allocated was more effective in improving water availability than a reliance on increased storage alone. New forms of storage with less adverse impacts were introduced, such as managed aquifer recharge and off-river storage. Reductions of nutrients from land use intensification by improving management practices has been a priority. Solutions packages for addressing the degradation of vulnerable lakes and rivers have been prepared. Biodiversity enhancement projects have been initiated. Greater involvement of Māori has led to the incorporation of kaitiakitanga (resource stewardship) into implementation programmes. Emerging issues are the need for improved integration of surface water and groundwater interactions, increased use of modelling of water and financial outcomes to guide decision making, and, equity in allocation among existing users as well as between existing and future users. Conclusions: However, sustainability analysis indicates that the proposed levels of management interventions are not sufficient to achieve community targets for water management. There is a need for more proactive recovery and rehabilitation measures. Managing to environmental limits is not sufficient, rather managing adaptive cycles is needed. Better measurement and management of water use efficiency is required. Proposed implementation packages are not sufficient to deliver desired water quality outcomes. Greater attention to targets important to environmental and recreational interests is needed to maintain trust in the collaborative process. Implementation programmes don’t adequately address climate change adaptations and greenhouse gas mitigation. Affordability is a constraint on adaptive capacity of farmers and communities. More funding mechanisms are required to implement proactive measures. The legislative and institutional framework needs to be changed to incorporate water framework legislation, regional sustainability strategies and water infrastructure coordination.

Keywords: collaborative governance, irrigation management, nested adaptive systems, sustainable water management

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: Chhavi Saxena

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FinFETs can be a replacement for bulk-CMOS transistors in many different designs. Its low leakage/standby power property makes FinFETs a desirable option for memory sub-systems. Memory modules are widely used in most digital and computer systems. Leakage power is very important in memory cells since most memory applications access only one or very few memory rows at a given time. As technology scales down, the importance of leakage current and power analysis for memory design is increasing. In this paper, we discover an option for low power interconnect synthesis at the 32nm node and beyond, using Fin-type Field-Effect Transistors (FinFETs) which are a promising substitute for bulk CMOS at the considered gate lengths. We consider a mechanism for improving FinFETs efficiency, called variable supply voltage schemes. In this paper, we’ve illustrated the design and implementation of FinFET based 4x4 SRAM cell array by means of one bit 7T SRAM. FinFET based 7T SRAM has been designed and analysis have been carried out for leakage current, dynamic power and delay. For the validation of our design approach, the output of FinFET SRAM array have been compared with standard CMOS SRAM and significant improvements are obtained in proposed model.

Keywords: FinFET, 7T SRAM cell, leakage current, delay

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Authors: Andreas Kunz, Ali Alavi

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In this paper, we present a simple active stylus for interactive IR-based tabletop systems. Such tables offer a set of tags for realizing tangible user interfaces, which can only be applied to objects having a relatively big contacting area with the interactive surface. The stylus has a unique address and thus can be clearly distinguished from other styli, objects or finger touches that might simultaneously occur on the interactive surface.

Keywords: interactive screens, pen, tangibles, user interfaces

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Authors: Stanley Fore

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The case study company is one of the leading newsprint companies in South Africa. The company has achieved this status through operational expansion, diversification and investing in cutting-edge technology. They have a reputation for the highest quality and personalised service that transcends borders and industries. The company offers a wide variety of small and large scales printing services. The company is faced with the challenge of significant waste production during normal operations. The company generates 1200 kg of plastic waste and 60 – 70 tonnes of paper waste per month. The company operates a waste management process currently, whereby waste paper is sold, at low cost, to recycling firms for further processing. Having considered the quantity of waste being generated, the company has embarked on a venture to find a more profitable solution to its current waste production. As waste management and recycling is not the company’s core business, the aim of the venture is to implement a secondary profitable waste process business. The venture will be expedited as a strategic project. This research aims to estimate the financial feasibility of a selected solution as well as the impact of non-financial considerations thereof. The financial feasibility is analysed using metrics such as Payback period; internal rate of return and net present value.

Keywords: waste, printing industry, up-cycling, management

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Authors: Mark Linden, Trisha Forbes, Michael Brown, Lynne Marsh, Maria Truesdale, Stuart Todd, Nathan Hughes

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Background The COVID-19 pandemic resulted in a reduction of health care services for many family carers of people with profound and multiple intellectual disabilities (PMID). Due to lack of services, family carers turned to charities for support during the pandemic. We explored the views of charity workers across the UK and Ireland who supported family carers during the COVID-19 pandemic and explored their views on effective online support programmes for family carers. Methods This was a qualitative study using online focus groups with participants (n = 24) from five charities across the UK and Ireland. Questions focused on challenges, supports, coping and resources which helped during lockdown restrictions. Focus groups were audio recorded, transcribed verbatim, and analysed through thematic analysis. Findings Four themes were identified (i) ‘mental and emotional health’, (ii) ‘they who shout the loudest’ (fighting for services), (iii) ‘lack of trust in statutory services’ and (iv) ‘creating an online support programme’. Mental and emotional health emerged as the most prominent theme and included three subthemes named as ‘isolation’, ‘fear of COVID-19’ and ‘the exhaustion of caring’. Conclusions The withdrawal of many services during the COVID-19 pandemic further isolated and placed strain on family carers. Even after the end of the pandemic family cares continue to report on the struggle to receive adequate support. There is a critical need to design services, including online support programmes, in partnership with family carers which adequately address their needs.

Keywords: intellectual disability, family carers, COVID-19, charities

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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Authors: Ruvaitha Banu, Amaladhithyan Krishnamoorthy

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IoT networks today solve various consumer problems, from home automation systems to aiding in driving autonomous vehicles with the exploration of multiple devices. For example, in an autonomous vehicle environment, multiple sensors are available on roads to monitor weather and road conditions and interact with each other to aid the vehicle in reaching its destination safely and timely. IoT systems are predominantly dependent on the cloud environment for data storage, and computing needs that result in latency problems. With the advent of Fog networks, some of this storage and computing is pushed to the edge/fog nodes, saving the network bandwidth and reducing the latency proportionally. Managing the data stored in these fog nodes becomes crucial as it might also store sensitive information required for a certain application. Data management in fog nodes is strenuous because Fog networks are dynamic in terms of their availability and hardware capability. It becomes more challenging when the nodes in the network also live a short span, detaching and joining frequently. When an end-user or Fog Node wants to access, read, or write data stored in another Fog Node, then a new protocol becomes necessary to access/manage the data stored in the fog devices as a conventional static way of managing the data doesn’t work in Fog Networks. The proposed solution discusses a protocol that acts by defining sensitivity levels for the data being written and read. Additionally, a distinct data distribution and replication model among the Fog nodes is established to decentralize the access mechanism. In this paper, the proposed model implements stewardship towards the data stored in the Fog node using the application of Reinforcement Learning so that access to the data is determined dynamically based on the requests.

Keywords: IoT, fog networks, data stewardship, dynamic access policy

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Authors: Shivani Kuttuva, Bridget Fergie, Andrew Mishreki, Shovkat Mir, Fintan Bergin

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Diaphragm disease (DD) of the small bowel is a condition wherein the bowel lumen is divided into a series of short compartments by multiple circumferential membranes of mucosa and submucosa, leading to pinhole lumen and subsequent obstruction. It is a rare condition commonly attributed to non-steroidal anti-inflammatory drugs (NSAIDs) usage. Herein we present a 31-yr-old-female with a history of NSAIDs usage for one year following neurosurgery, who presented with recurrent idiopathic small bowel obstruction, recalcitrant anaemia, and impaction of capsule endoscope on investigating for anaemia. The capsule endoscopy images demonstrated multiple circumferential strictures with ulcers at its tip and villous atrophy in the proximal bowel, suggestive of NSAIDs related damage. However, due to the lack of awareness of the detrimental effects of NSAIDs on bowel mucosa distal to the duodenum, the underlying aetiology of this clinical presentation remained a mystery for a significant duration. The patient had to undergo repeated laparotomies in order to relieve the symptoms of recurring acute small bowel obstruction. Upon examining the resected specimen under microscopy, the histopathological hallmark of expanded, fibrotic, and congested submucosa was picked up, leading to the confirmation of diaphragm disease. Thus, this case report aims to widen the awareness among clinicians and aid surgeons in devising a management plan for young individuals presenting with recurring episodes of obstruction due to Diaphragm disease.

Keywords: capsule endoscopy, diaphragm disease, NSAIDs, recurrent small bowel obstruction

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Authors: Ping Tan, Xiaomeng Su, Yi Shen

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The motion intention in the motor imagery braincomputer interface is identified by classifying the event-related desynchronization (ERD) and event-related synchronization ERS characteristics of sensorimotor rhythm (SMR) in EEG signals. When the subject imagines different limbs or different parts moving, the rhythm components and bandwidth will change, which varies from person to person. How to find the effective sensorimotor frequency band of subjects is directly related to the classification accuracy of brain-computer interface. To solve this problem, this paper proposes a Minimum Distance to Riemannian Mean Classification method based on Non-Uniform Filter Banks. During the training phase, the EEG signals are decomposed into multiple different bandwidt signals by using multiple band-pass filters firstly; Then the spatial covariance characteristics of each frequency band signal are computered to be as the feature vectors. these feature vectors will be classified by the MDRM (Minimum Distance to Riemannian Mean) method, and cross validation is employed to obtain the effective sensorimotor frequency bands. During the test phase, the test signals are filtered by the bandpass filter of the effective sensorimotor frequency bands, and the extracted spatial covariance feature vectors will be classified by using the MDRM. Experiments on the BCI competition IV 2a dataset show that the proposed method is superior to other classification methods.

Keywords: non-uniform filter banks, motor imagery, brain-computer interface, minimum distance to Riemannian mean

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Authors: Mohammad Amjad, Muhammad Iqbal Zafar, Ashfaq Ahmed Maan, Muhammad Tayyab Kashif

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Obesity is an abnormal physical condition where an increased and undesirable fat accumulates in the human body. Obesity is an international phenomenon. In the present study, 12 schools were randomly selected from each district considering the areas i.e. Elite Private Schools in the private sector, Government schools in urban areas and Government schools in rural areas. Interviews were conducted with male students studying in grade 5 to grade 9 in each school. The sample size was 600 students; 300 from Faisalabad district and 300 from Rawalpindi district in Pakistan. A well-structured and pre-tested questionnaire was used for data collection. The calibrated scales were used to attain the heights and weights of the respondents. Obesity of school-going children depends on family types, family size, family history, junk food consumption, mother’s education, weekly time spent in walking, and sports facility at school levels. Academic performance, physical health and psychological health of school going children are affected with obesity. Concrete steps and policies could minimize the incidence of obesity in children in Pakistan.

Keywords: body mass index, cardiovascular disease, fast food, morbidity, overweight

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Authors: Sony Baral, Bijendra Basnyat, Kalyan Gauli

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Forests are depleted throughout the world in the 1990s, and since then, various efforts have been undertaken for the restoration of the forest. A government of Nepal promoted various community based forest management in which leasehold forestry was the one introduce in 1990s, aiming to restore degraded forests land. However, few attempts have been made to systematically evaluate its cost effectiveness. Hence the study assesses the cost effectiveness of leasehold forestry intervention in the mid-hill district of Nepal following the cost and benefit analysis approach. The study followed quasi-experimental design and collected costs and benefits information from 320 leasehold forestry groups (with intervention) and 154 comparison groups (without intervention) through household survey, forest inventory and then validated with the stakeholders’ consultative workshop. The study found that both the benefits and costs from intervention outweighed without situation. The members of leasehold forestry groups were generating multiple benefits from the forests, such as firewood, grasses, fodder, and fruits, whereas those from comparison groups were mostly getting a single benefit. Likewise, extent of soil carbon is high in leasehold forests. Average expense per unit area is high in intervention sites due to high government investment for capacity building. Nevertheless, positive net present value and internal rate of return was observed for both situations. However, net present value from intervention, i.e., leasehold forestry, is almost double compared to comparison sites, revealing that community are getting higher benefits from restoration. The study concludes that leasehold forestry is a highly cost-effective intervention that contributes towards forest restoration that brings multiple benefits to rural poor.

Keywords: cost effectiveness, economic efficiency, intervention, restoration, leasehold forestry, nepal

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Authors: Keiko Shimazu, Yasuhiro Maida, Tetsuya Sugata, Daisuke Tamakoshi, Kenji Makabe, Haruki Suzuki

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In this paper, we report how to acquire serious victims’ locations in the Acute Stage of Large-scale Disasters, in an Emergency Information Network System designed by us. The background of our concept is based on the Great East Japan Earthquake occurred on March 11^th, 2011. Through many experiences of national crises caused by earthquakes and tsunamis, we have established advanced communication systems and advanced disaster medical response systems. However, Japan was devastated by huge tsunamis swept a vast area of Tohoku causing a complete breakdown of all the infrastructures including telecommunications. Therefore, we noticed that we need interdisciplinary collaboration between science of disaster medicine, regional administrative sociology, satellite communication technology and systems engineering experts. Communication of emergency information was limited causing a serious delay in the initial rescue and medical operation. For the emergency rescue and medical operations, the most important thing is to identify the number of casualties, their locations and status and to dispatch doctors and rescue workers from multiple organizations. In the case of the Tohoku earthquake, the dispatching mechanism and/or decision support system did not exist to allocate the appropriate number of doctors and locate disaster victims. Even though the doctors and rescue workers from multiple government organizations have their own dedicated communication system, the systems are not interoperable.

Keywords: crisis management, disaster mitigation, messing, MGRS, military grid reference system, satellite communication system

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Authors: Prince Amartey

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Bees are clever creatures, thus, capturing bees implies that the hives are intelligent in the sense that they have all of the required circumstances to attract and trap the bees. If the hive goes above and beyond to keep the bees in the hive and to keep the activities of in-hive pests to a minimal in order for the bees to develop to their maximum potential, the hive is becoming or is more 'intelligent'. Some bee pests, such as tiny beehive beetles, are endemic to Africa; however, the way we now extract honey by cutting off the combs and pressing for honey prevents the spread of these bees' insect enemies. However, when we explore entering the commercialization. When freshly collected combs are returned to the hives following the adoption of the frame and other systems, there is a need to consider putting in strategies to manage the accompanying pest concerns that arise with unprotected combs.The techniques for making hives more'intelligent' are thus more important presently, given that the African apicultural business does not wish to encourage the use of pesticides in the hives. This include changing the hive's entrance holes in order to improve the bees' own mechanism for defending the entry sites, as well as collecting pests by setting exterior and in-hive traps to prevent pest infiltration into hives by any means feasible. Material and Methods: The following five (5) mechanisms are proposed to make the hives more 'intelligent.' i. The usage of modified frames with five (5) beetle traps positioned horizontally on the vertical 'legs' to catch the beetle along the combs' surfaces-multiple bee ii. Baited bioelectric frame traps, which has both vertical sections of frame covered with a 3mm mesh that allows pest entry but not bees. The pest is attracted by strips of combs of honey, open brood, pollen on metal plates inserted horizontally on the vertical ‘legs’ of the frames. An electrical ‘mine’ system in place that electrocutes the pests as they step on the wires in the trap to enter the frame trap iii. The ten rounded hive entry holes are adapted as the bees are able to police the entrance to prevent entry of pest. The holes are arranged in two rows, with one on top of the other What Are the Main Contributions of Your Research?-Results Discussions and Conclusions The techniques implemented decrease pest ingress, while in-hive traps capture those that escape entry into the hives. Furthermore, the stand alteration traps larvae and stops their growth into adults. As beekeeping commercialization grows throughout Africa, these initiatives will minimize insect infestation in hives and necessarily enhance honey output.

Keywords: bee pests, modified frames, multiple beetle trap, Baited bioelectric frame traps

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Authors: Yo Fukutani, Shuji Moriguchi, Takuma Kotani, Terada Kenjiro

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If risk management of the assets owned by companies, risk assessment of real estate portfolio, and risk identification of the entire region are to be implemented, it is necessary to consider simultaneous damage to multiple buildings. In this research, the Sagami Trough earthquake tsunami that could have a significant effect on the Japanese capital region is focused on, and a method is proposed for simultaneous damage assessment using copulas that can take into consideration the correlation of tsunami depths and building damage between two sites. First, the tsunami inundation depths at two sites were simulated by using a nonlinear long-wave equation. The tsunamis were simulated by varying the slip amount (five cases) and the depths (five cases) for each of 10 sources of the Sagami Trough. For each source, the frequency distributions of the tsunami inundation depth were evaluated by using the response surface method. Then, Monte-Carlo simulation was conducted, and frequency distributions of tsunami inundation depth were evaluated at the target sites for all sources of the Sagami Trough. These are marginal distributions. Kendall’s tau for the tsunami inundation simulation at two sites was 0.83. Based on this value, the Gaussian copula, t-copula, Clayton copula, and Gumbel copula (n = 10,000) were generated. Then, the simultaneous distributions of the damage rate were evaluated using the marginal distributions and the copulas. For the correlation of the tsunami inundation depth at the two sites, the expected value hardly changed compared with the case of no correlation, but the damage rate of the ninety-ninth percentile value was approximately 2%, and the maximum value was approximately 6% when using the Gumbel copula.

Keywords: copulas, Monte-Carlo simulation, probabilistic risk assessment, tsunamis

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Authors: Hajer Najjar, Riad Bourguiba, Jaouhar Mouine

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Reduced instruction set computer (RISC) processors are widely used because of their multiple advantages. In fact, they are based on a simple instruction set so that they increase the speed of the processor and reduce its energy consumption. In this paper, we will present a basic RISC architecture processor that will be developed later to converge to a new architecture with runtime reconfiguration.

Keywords: processor, RISC, DLX, pipeline, runtime reconfiguration

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Authors: Rana Muhammad Ayyub, Muhammad Bilal, Tahir Mahmood

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In multicultural societies, food preferences are taking dimensions in both minorities as well as majority ethnic groups. The food consumption behavior of minority ethnic groups has been studied adequately; however, this paper intends to study the consumer behavioral dimensions of majority ethnic groups regarding Halal foods (a minority-related food) in the USA. In this quantitative study, the online questionnaire survey (n=223) was collected through surveymonkey.com from non-Muslims living in various cities in the USA through random sampling. The theory of consumer animosity was a theoretical underpinning. The validated scales were adopted and adapted for all constructs. AMOS 24 was used to apply structural equation modelling (SEM) to the data. Among the majority of ethnic groups, it was found that consumer racism (β= -25) and consumer animosity (β= - 27) negatively affect intention to choose Halal foods, whereas food neophobia has a positive effect (β=36) on this intention. This study will prove instrumental in removing the blame of “Marketing Myopia” from marketing academics and will highlight the importance of prevalent market realities for one of the fastest growing ethnic food markets, i.e., Halal of the world. It has practical implications for Halal food marketers in particular and other ethnic food marketers in general.

Keywords: consumer racism, animosity, Halal foods, ethnic consumption, food neophobia

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Authors: Laurisa Peters, Usha Barahmand, Maria Stalias-Mantzikos, Naila Shamsina, Kerry Aguero

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In the current study, the authors sought to examine whether the links between moral and sexual disgust and misophonia are mediated by mental contamination. An internationally diverse sample of 283 adults (193 females, 76 males, and 14 non-binary individuals) ranging in age from 18 to 60 years old was recruited from online social media platforms and survey recruitment sites. The sample completed an online battery of scales that consisted of the New York Misophonia Scale, State Mental Contamination Scale, and the Three-Domain Disgust Scale. The hypotheses were evaluated using a series of mediations performed using the PROCESS add-on in SPSS. Correlations were found between emotional and aggressive-avoidant reactions in misophonia, mental contamination, pathogen disgust, and sexual disgust. Moral disgust and non-aggressive reactions in misophonia failed to correlate significantly with any of the other constructs. Sexual disgust had direct and indirect effects, while pathogen disgust had only direct effects on aspects of misophonia. These findings partially support our hypothesis that mental contamination mediates the link between disgust propensity and misophonia while also confirming that pathogen-based disgust is not associated with mental contamination. Findings imply that misophonia is distinct from obsessive-compulsive disorder. Further research into the conceptualization of moral disgust is warranted.

Keywords: misophonia, moral disgust, pathogen disgust, sexual disgust, mental contamination

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Authors: Ju Yeon Lee, Seol Ah Oh, Hong il Kim, Hae Yong Do, Sung Won Choi

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The purpose of this study was to develop a Well-being and Moments Scale (WAMS) for evaluating the efficacy of ‘vacationing’ as a form of mental health recuperation. ‘Vacationing’ is defined as a going outside one’s usual environment to seek refreshment and relief from one’s daily life. To develop WAMS, we followed recommended procedures for scale development, including reviewing related studies, conducting focus group interviews to elucidate the need for this assessment area, and modifying items based on expert opinion. Through this process, we developed the WAMS. The psychometric properties of the WAMS were then tested in two separate samples. Exploratory factor analysis (EFA) was conducted using 1.41 participants (mean age = 30.45 years; range: 20-50 years) to identify the underlying 3-factor structure of 'Positive Emotions', 'Life Satisfaction' and 'Self-Confidence.' The 26 items retained based on the EFA procedures were associated with excellent reliability (i.e., α = 0.93). Confirmatory factor analysis was then conducted using 200 different participants (mean age = 29.51 years; range: 20-50 years) and revealed good model fit for our hypothesized 3-factor model. Convergent validity tests also revealed correlations with other scales in the expected direction and range. Study limitations as well as the importance and utility of WMAS are also discussed.

Keywords: vacationing, positive affect, life satisfaction, self-confidence, WAMS

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Authors: Chih Jou Hsiao, Chung Ming Lo, Li Chun Hsieh

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Brain tumor is not the cancer having high incidence rate, but its high mortality rate and poor prognosis still make it as a big concern. On clinical examination, the grading of brain tumors depends on pathological features. However, there are some weak points of histopathological analysis which can cause misgrading. For example, the interpretations can be various without a well-known definition. Furthermore, the heterogeneity of malignant tumors is a challenge to extract meaningful tissues under surgical biopsy. With the development of magnetic resonance imaging (MRI), tumor grading can be accomplished by a noninvasive procedure. To improve the diagnostic accuracy further, this study proposed a computer-aided diagnosis (CAD) system based on MRI features to provide suggestions of tumor grading. Gliomas are the most common type of malignant brain tumors (about 70%). This study collected 34 glioblastomas (GBMs) and 73 lower-grade gliomas (LGGs) from The Cancer Imaging Archive. After defining the region-of-interests in MRI images, multiple quantitative morphological features such as region perimeter, region area, compactness, the mean and standard deviation of the normalized radial length, and moment features were extracted from the tumors for classification. As results, two of five morphological features and three of four image moment features achieved p values of <0.001, and the remaining moment feature had p value <0.05. Performance of the CAD system using the combination of all features achieved the accuracy of 83.18% in classifying the gliomas into LGG and GBM. The sensitivity is 70.59% and the specificity is 89.04%. The proposed system can become a second viewer on clinical examinations for radiologists.

Keywords: brain tumor, computer-aided diagnosis, gliomas, magnetic resonance imaging

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Authors: Wafa Baccouch, Adel Ghith, Xavier Legrand, Faten Fayala

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Textile waste recycling has become a necessity considering the augmentation of the amount of waste generated each year and the ecological problems that landfilling and burning can cause. Textile waste can be recycled into many different forms according to its composition and its final utilization. Using this waste as reinforcement to composite panels is a new recycling area that is being studied. Compared to virgin fabrics, recycled ones present the disadvantage of having lower structural characteristics, when they are eco-friendly and with low cost. The objective of this work is transforming textile waste into composite material with good characteristic and low price. In this study, we used sewing as a method to improve the characteristics of the recycled textile waste in order to use it as reinforcement to composite material. Textile non-woven waste was afforded by a local textile recycling industry. Performances tests were evaluated using tensile testing machine and based on the testing direction for both reinforcements and composite panels; machine and transverse direction. Tensile tests were conducted on sewed and non sewed fabrics, and then they were used as reinforcements to composite panels via epoxy resin infusion method. Rule of mixtures is used to predict composite characteristics and then compared to experimental ones.

Keywords: composite material, epoxy resin, non woven waste, recycling, sewing, textile

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Authors: Anna Petr Safrankova, Karla Hrbackova

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The education of socially disadvantaged students is in the long term spotlight of many pedagogical researches in both Czech and foreign environment. These researches among others investigate this topic from the point of view of individual compensatory measure which tries to overcome or remove the social disadvantage. The focus of the study is to highlight the important role of teachers in the education of this specific group of students, among others in terms of their (teachers´) pre-graduate training. The aim of the study is to point out the importance of teachers´ self-efficacy. The study is based on the assumption that the teacher's self-efficacy may significantly affect the teacher's perception of a particular group of students and thereby affect the education of the students. The survey involved 245 teachers from the two regions in the Czech Republic. In the research were used TES questionnaire (with the dimensions personal teaching efficacy – PTE and general teaching efficacy – GTE) by Gibson and Dembo and the semantic differential (containing 12 scales with bipolar adjectives) which investigated the components of teachers' attitudes toward socially disadvantaged students. It was found that teachers’ self-efficacy significantly affects the teachers’ perception of the group of socially disadvantaged students. Based on this finding we believe that it is necessary to work with this concept (prepare teachers to educate this specific group of students) already during higher education and especially during the pre-graduate teachers training.

Keywords: teachers, socially disadvantaged students, semantic differential, teachers self-efficacy

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Authors: Lule Basha, Eralda Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

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Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

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It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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Authors: Odey Moses Ogah, Felix Terhemba Ikyereve

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The study was carried out to analyzed risks in financing agriculture by agricultural cooperatives in Benue State, Nigeria. The study made use of research questionnaires for data collection. A multistage sampling technique was used to select a sample of 210 respondents from 21 agricultural cooperatives. Both descriptive and inferential statistics were employed in data analysis. Loan defaulting (66.7%) and reduction in savings by members (51.4%) were the major causes of risks faced by agricultural cooperatives in financing agriculture in the study area. Other causes include adverse changes in commodity prices (48.6%), disaster (45.7%), among others. It was found that risks adversely influence the profitability and competition of agricultural cooperatives (82.9%). Multiple regression analysis results showed that the coefficient of multiple determinations was 0.67, implying that the explanatory variables included in the model accounted for 67% of the variation in the level of profitability of agricultural cooperatives. The number of loans, average amount of loan and the interest rate were significant and important determinants of profitability of the cooperatives. The majority of the respondents (88.6%) made use of loan guarantors as a strategy of managing loan default/no repayment. It was found that the majority (70%) of the respondents were faced with the challenge of lack of insurance cover. The study recommends that agricultural cooperative officials should be encouraged to undergo formal training and education to easily acquire administrative skills in the management of agricultural loans; Farmer's loan size should be increased and released on time to enable them to use it effectively. Policies that enhance insuring farm activities should be put in place to discourage farmers from risk aversion.

Keywords: agriculture, analysis, cooperative, finance, risks

Procedia PDF Downloads 113

Authors: Fayad Ghawbar

Abstract:

The significance of the Multiple Input Multiple Output (MIMO) system in the 5G wireless communication system is essential to enhance channel capacity and provide a high data rate resulting in a need for dual-polarization in vertical and horizontal. Furthermore, size reduction is critical in a MIMO system to deploy more antenna elements requiring a compact, low-profile design. A compact dual-band 4-MIMO antenna system has been presented in this paper with pattern and polarization diversity. The proposed single antenna structure has been designed using two antenna layers with a C shape in the front layer and a partial slot with a U-shaped cut in the ground to enhance isolation. The single antenna is printed on an FR4 dielectric substrate with an overall size of 18 mm×18 mm×1.6 mm. The 4-MIMO antenna elements were printed orthogonally on an FR4 substrate with a size dimension of 36 × 36 × 1.6 mm3 with zero edge-to-edge separation distance. The proposed compact 4-MIMO antenna elements resonate at 3.4-3.6 GHz and 4.8-5 GHz. The s-parameters measurement and simulation results agree, especially in the lower band with a slight frequency shift of the measurement results at the upper band due to fabrication imperfection. The proposed design shows isolation above -15 dB and -22 dB across the 4-MIMO elements. The MIMO diversity performance has been evaluated in terms of efficiency, ECC, DG, TARC, and CCL. The total and radiation efficiency were above 50 % across all parameters in both frequency bands. The ECC values were lower than 0.10, and the DG results were about 9.95 dB in all antenna elements. TARC results exhibited values lower than 0 dB with values lower than -25 dB in all MIMO elements at the dual-bands. Moreover, the channel capacity losses in the MIMO system were depicted using CCL with values lower than 0.4 Bits/s/Hz.

Keywords: compact antennas, MIMO antenna system, 5G communication, dual band, ECC, DG, TARC

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Authors: Raj K. Gupta, X. Gary Tan, Andrzej Przekwas

Abstract:

Bomb blasts from Improvised Explosive Devices (IEDs) account for vast majority of terrorist attacks worldwide. Injuries caused by IEDs result from a combination of the primary blast wave, penetrating fragments, and human body accelerations and impacts. This paper presents a multiscale computational model of coupled blast physics, whole human body biodynamics and injury biomechanics of sensitive organs. The disparity of the involved space- and time-scales is used to conduct sequential modeling of an IED explosion event, CFD simulation of blast loads on the human body and FEM modeling of body biodynamics and injury biomechanics. The paper presents simulation results for blast-induced brain injury coupling macro-scale brain biomechanics and micro-scale response of sensitive neuro-axonal structures. Validation results on animal models and physical surrogates are discussed. Results of our model can be used to 'replicate' filed blast loadings in laboratory controlled experiments using animal models and in vitro neuro-cultures.

Keywords: blast waves, improvised explosive devices, injury biomechanics, mathematical models, traumatic brain injury

Procedia PDF Downloads 249

Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Deng Qiaoshan

Abstract:

With the rise of feminism in the global film industry, feminist expressions in Chinese films have also evolved, reflecting societal focus on gender issues. This article focuses on young Chinese female directors such as Yang Lina, Teng Congcong, and Yang Mingming. Their films now present richer female perspectives and consciously incorporate unique female life experiences. They highlight women's real-life struggles, portraying ’struggling’ female identities—characters facing professional failures and desire identity issues, ultimately returning to family roles. These films commonly explore the ‘mother-daughter relationship’, with some using genre storytelling for commercial appeal and others deconstructing the ‘myth of motherhood’ to reflect reality, rewriting traditional maternal roles. The ‘struggling’ female identity in these directors' films shows an aesthetic of ‘pseudo-reality’, blending realistic situations with poetic, lyrical elements, reflecting their creative traits and internal conflicts. These contradictions are closely related to the unique creative context of Chinese cinema in which they operate. Emerging under China's strict film censorship system, film industrialization, consumerist culture, and internet environment, new-generation directors face multiple demands. How to ‘survive’ amidst complex commercial requirements while creating films with a clear feminist consciousness is the fundamental dilemma faced by young Chinese female directors.

Keywords: female directors, feminism film, female dilemma, film censorship system

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Authors: Khadijah Saeed Khan

Abstract:

One of the major current societal issues of Swedish society is to integrate newcomer refugees well into the host society. The cultural integration issue is one of the under debated topic in the literature, and this study intends to meet this gap from the Swedish perspective. The purpose of this study is to explore the role and types of cultural landscapes of refugee women in Sweden and how these landscapes help or hinder the settlement process. The cultural landscapes are referred to as a set of multiple cultural activities or practices which refugees perform in a specific context and circumstances (i.e., being in a new country) to seek, share or use relevant information for their settlement. Information plays a vital role in various aspects of newcomers' lives in a new country. This article has an intention to highlight the importance of multiple cultural landscapes as a source of information (regarding employment, language learning, finding accommodation, immigration matters, health concerns, school and education, family matters, and other everyday matters) for refugees to settle down in Sweden. Some relevant theories, such as information landscapes and socio-cultural theories, are considered in this study. A qualitative research design is employed, including semi-structured deep interviews and participatory observation with 20 participants. The initial findings show that the refugee women encounter many information-related and integration-related challenges in Sweden and have built a network of cultural landscapes in which they practice various co-ethnic cultural and religious activities at different times of the year. These landscapes help them to build a sense of belonging with people from their own or similar land and assist them to seek and share relevant information in everyday life in Sweden.

Keywords: cultural integration, cultural landscapes, information, women refugees

Procedia PDF Downloads 142