Search results for: clinical psychology training

Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Lauren Zammerilla Westcott, Ronald C. Jones, James W. Fleshman

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The surgical treatment of breast cancer has rapidly evolved over the past 50 years, progressing from Halsted’s radical mastectomy to a public campaign of surgical options, aesthetic reconstruction, and patient empowerment. This article examines the happenings that led to the transition of breast surgery as a subset of general surgery to its own specialized field. Sparked by the research of Dr. Bernard Fisher and the first National Surgical Adjuvant Breast and Bowel Project trial in 1971, the field of breast surgery underwent significant growth over the next several decades, enabling general surgeons to limit their practices to the breast. High surgical volumes eventually led to the development of the first formal breast surgical oncology fellowship in a large community-based hospital at Baylor University Medical Center in 1982. The establishment of the American Society of Breast Surgeons, as well several landmark clinical trials and public campaign efforts, further contributed to the advancement of breast surgery, making it the specialized field of the current era.

Keywords: breast cancer, breast fellowship, breast surgery, surgical history

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Authors: Dominika Collett

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AI applications, such as machine learning, require access to a vast amount of data in the training phase, which can often be the subject of copyright protection. During later usage, the various content with which the application works can be recorded or made available on the basis of which it produces the resulting output. The EU has recently adopted new legislation to secure machine access to protected works under the DSM Directive; but, the issue of machine use of copyright works is not clearly addressed. However, such clarity is needed regarding the increasing importance of AI and its development. Therefore, this paper provides a basic background of the technology used in the development of applications in the field of computer creativity. The second part of the paper then will focus on a legal analysis of machine use of the authors' works from the perspective of existing European and Czech legislation. The main results of the paper discuss the potential collision of existing legislation in regards to machine use of works with special focus on exceptions and limitations. The legal regulation of machine use of copyright work will impact the development of AI technology.

Keywords: copyright, artificial intelligence, legal use, infringement, Czech law, EU law, text and data mining

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Authors: Abdelbasit Gadour

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A great number of children in mainstream schools across Libya are currently living with emotional, behavioral difficulties. This study aims to explore teachers’ perceptions of children’s emotional and behavioral difficulties (EBD) and their attributions of the causes of EBD. The relevance of this area of study to current educational practice is illustrated in the fact that primary school teachers in Libya find classroom behavior problems one of the major difficulties they face. The information presented in this study was gathered from 182 teachers that responded back to the survey, of whom 27 teachers were later interviewed. In general, teachers’ perceptions of EBD reflect personal experience, training, and attitudes. Teachers appear from this study to use words such as indifferent, frightened, withdrawn, aggressive, disobedient, hyperactive, less ambitious, lacking concentration, and academically weak to describe pupils with emotional and behavioral difficulties (EBD). The implications of this study are envisaged as being extremely important to support teachers addressing children’s EBD and shed light on the contributing factors to EBD for a successful teaching-learning process in Libyan primary schools.

Keywords: children, emotional and behavior difficulties, learning, teachers'

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Authors: Radesh Palakurthi

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The purpose of this study was to determine the impact of experiential learning on learning outcomes in hospitality education. This paper presents the results of an online survey of students from the U.S. studying abroad and their self-reported change in learning outcomes as assessed using the Core Competencies Model for the Hospitality Industry developed by Employment and Training Development Office of the U.S. Department of Labor. The impact of student learning styles on learning outcomes is also evaluated in this study. Kolb’s Learning Styles Inventory Model was used to assess students’ learning style. The results show that students reported significant improvements in their learning outcomes because of engaging in study abroad experiential learning programs. The learning styles of the students had significant effect on one of core learning outcomes- personal effectiveness.

Keywords: hospitality competencies, hospitality education, Kolb’s learning style inventory, learning outcomes, study abroad

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Authors: Pieter van den Berg, Retief Broodryk, Bert Moolman

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Firstly, this study aimed to identify which performance indicators (PIs) discriminate between winning and losing university-level Rugby Union (RU) teams and, secondly, to compare the significant PIs in RU and Rugby Union Sevens (RS) at university level. Understanding the importance of PIs and their effect on match outcomes could assist coaching staff to prioritise specific game aspects during training to increase performance. Twenty randomly selected round-robin matches of the 2018 Varsity Cup (n=20), and Varsity Sports sevens (n=20) tournaments were analysed. A linear mixed model was used to determine statistical significant differences set at p≤0.05 while effect size was reported according to Cohen's d value. Results revealed that various PIs discriminated between winning and losing RU teams and that specific PIs could be observed as significant in both RU and RS. Therefore, specific identified tactical aspects of RU and RS should be prioritised to optimise performance

Keywords: match success, notational analysis, performance analysis, rugby, video analysis

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Authors: Ruth Elvish, Alex Turner, Jen Wells

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Over recent years there has been an increasing interest in the topic of well-being at work, and staff support is an area of continued growth. The present qualitative study explored the impact of a staff well-being service that was specifically attached to a five-year multi-site research programme (the Neighbourhoods and Dementia Study, funded by the ESRC/NIHR). The well-being service was led by a clinical psychologist, who offered 1:1 sessions for staff and co-researchers with dementia. To our knowledge, this service was the first of its kind. Methodology: Interviews were undertaken with staff who had used the service and who opted to take part in the study (n=7). Thematic analysis was used as the method of analysis. Findings: Themes included: triggers, mechanisms of change, impact/outcomes, and unique aspects of a dedicated staff well-being service. Conclusions: The study highlights stressors that are pertinent amongst staff within academic settings, and shows the ways in which a dedicated staff well-being service can impact on both professional and personal lives. Positive change was seen in work performance, self-esteem, relationships, and coping. This exploratory study suggests that this well-being service model should be further trialled and evaluated.

Keywords: academic, service, staff, support, well-being

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Authors: Abdul Wahid

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Inner speech, also known as verbal thinking, self-talk or private speech, is characterized by the subjective language experience in the absence of overt or audible speech. It is a psychological form of verbal activity which is being rehearsed without the articulation of any sound wave. In Psychology, self-limiting speech means the type of speech which contains information that inhibits the development of the self. People, in most cases, experience inner speech in their first language. It is very frequent in Bangladesh where the Bangla (L1) speaking students lose track of speech during their presentations in English (L2). This paper investigates into the long pauses (more than 0.4 seconds long) in English (L2) presentations by Bangla speaking students (18-21 year old) and finds the intervention of Bangla (L1) inner speech as one of its causes. The overt speeches of the presenters are placed on Audacity Audio Editing software where the length of pauses are measured in milliseconds. Varieties of inner speech questionnaire (VISQ) have been conducted randomly amongst the participants out of whom 20 were selected who have similar phenomenology of inner speech. They have been interviewed to describe the type and content of the voices that went on in their head during the long pauses. The qualitative interview data are then codified and converted into quantitative data. It was observed that in more than 80% cases students experience self-limiting inner speech/self-talk during their unwanted pauses in L2 presentations.

Keywords: Bangla-English Bilinguals, inner speech, L1 intervention in bilingualism, motor schema, pauses, phonological loop, phonological store, working memory

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Authors: Yijie Wang, Tianyue Wang

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In the past two decades, there has been a great ‘piano lesson frenzy’ among Chinese middle-class families, with a large number of parents adding piano training to children’s extra-curriculum lists. Superficially, the frenzy reflects a rather ‘leisurely’ attitude: parents typically claim that pianos lessons are ‘just for fun’ and will hopefully render children’s life more exciting. However, a closer scrutiny reveals that there is great social-status anxiety hidden beneath this ‘leisurely’ surface. Based on pre-interviews of six Chinese middle-class parents who have enthusiastically signed their children up for piano lessons, several tentative analysis are made: 1. Owing to a series of historical and social factors, the Chinese middle-class have yet to establish their cultural norms in the past few decades, resulting in great confusion concerning how to cultivate cultural tastes in their offspring. And partly due to the fact that the middle-class status of the past Chinese generation is mostly self-acquired rather than inherited, parents are much less confident about their cultural resources—which require long-time accumulation—than material ones. Both factors combine to lead to a sort of blind, overcompensating enthusiasm in culture-related education, and the piano frenzy is but a demonstration. 2. The piano has been chosen to be the object of the frenzy partly because of its inherent characteristics as well as socially-constructed ones. Costly, large in size, imported from another culture and so forth, the piano has acquired the meaning of being exclusive, high-end and exotic, which renders it a token of top-tier status among Chinese people, and piano lessons for offspring have therefore become parents’ paths towards a kind of ‘symbolic elevation’. A child playing piano is an exhibition as well as psychological assurance of the families’ middle-class status. 3. A closer look at children’s piano training process reveals that there is much more anxiety than leisurely elements involved. Despite parents’ claim that ‘piano is mainly for kids to have fun,’ the whole process is evidently of a rather ‘ascetic’ nature, with the demands of diligence and senses of time urgency throughout, and techniques rather than flair or styles are emphasized. This either means that the apparent ‘piano-for-fun’ stance is unauthentic and is only other motives in disguise, or that the Chinese middle-class parents are not yet capable of shaking off the sense of anxiety even if they sincerely intend to. 4. When viewed in relation to Chinese formal school system as well as the job market at large, it can be said that by signing children up for piano lessons, parents are consciously or unconsciously seeking to prepare for, or reduce the risks of, their children’s future social mobility. In face of possible failures in the highly-crucial, highly-competitive formal school system, piano-playing as an extra-curriculum activity may be conveniently transferred into an alternative career path. Besides, in contemporary China, as the occupational structure goes through change, and the school-related certificates decline in value, aspects such as a person’s overall deportment, which can be gained or proved by piano-learning, have been gaining in significance.

Keywords: extra-curriculum activities, middle class, piano lesson frenzy, status anxiety

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Authors: Antoine Miguel Borromeo, Kristian Anthony Menez, Moira Louise Ordonez, David Carl Rabaya

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This study aimed to test if induced mood and normative conformity have any effect specifically on prosocial behavior, which was operationalized as the willingness to donate to a non-government organization. The effect of current attitude towards the object of the prosocial behavior was also considered with a covariate test. Undergraduates taking an introductory course on psychology (N = 132) from the University of the Philippines Diliman were asked how much money they were willing to donate after being presented a video about coral reef destruction and a website that advocates towards saving the coral reefs. A 3 (Induced mood: Positive vs Fear and Sadness vs Anger, Contempt, and Disgust) x 2 (Normative conformity: Presence vs Absence) between-subjects analysis of covariance was used for experimentation. Prosocial behavior was measured by presenting a circumstance wherein participants were given money and asked if they were willing to donate an amount to the non-government organization. An analysis of covariance revealed that the mood induced has no significant effect on prosocial behavior, F(2,125) = 0.654, p > 0.05. The analysis also showed how normative conformity has no significant effect on prosocial behavior, F(1,125) = 0.238, p > 0.05, as well as their interaction F(2, 125) = 1.580, p > 0.05. However, the covariate, current attitude towards corals was revealed to be significant, F(1,125) = 8.778, p < 0.05. From this, we speculate that inherent attitudes of people have a greater effect on prosocial behavior than temporary factors such as mood and conformity.

Keywords: attitude, induced mood, normative conformity, prosocial behavior

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Authors: Ibrahim Ercan, Mustafa Arikan

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In recent years, alternative dispute resolution methods have attracted the attention of many country’s legislators. Instead of solving the disputes by litigation, putting the end to a dispute by parties themselves is more important for the preservation of social peace. Therefore, alternative dispute resolution methods (ADR) have been discussed more intensively in Turkey as well as the whole world. After these discussions, Mediation Act was adopted on 07.06.2012 and entered into force on 21.06.2013. According to the Mediation Act, it is only possible to mediate issues arising from the private law. Also, it is not compulsory to go to mediation in Turkish law, it is optional. Therefore, the parties are completely free to choose mediation method in dispute resolution. Mediators need to be a lawyer with experience in five years. Therefore, it is not possible to be a mediator who is not lawyers. Beyond five years of experience, getting education and success in exams about especially body language and psychology is also very important to be a mediator. If the parties compromise as a result of mediation, a document is issued. This document will also have the ability to exercising availability under certain circumstances. Thus, the parties will not need to apply to the court again. On the contrary, they will find the opportunity to execute this document, so they can regain their debts. However, the Mediation Act has entered into force in a period of nearly two years of history; it is possible to say that the interest in mediation is not at the expected level. Therefore, making mediation mandatory for some disputes has been discussed recently. At this point, once the mediation becomes mandatory and good results follows it, this institution will be able to find a serious interest in Turkey. Otherwise, if the results will not be satisfying, the mediation method will be removed.

Keywords: alternative dispute resolution methods, mediation act, mediation, mediator, mediation in Turkey

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Authors: Janki Shankar, Shu-Ping Chen

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This Canadian study explored the perspectives of recent immigrant workers regarding occupational health and safety (OHS) and workplace conditions that increase workers’ vulnerability to sustaining injury or illness. Using an interpretive research approach and semi structured qualitative interviews, 42 recent immigrant workers from a range of industries operating in two cities in a province in Canada were interviewed. A constant comparative approach was used to identify key themes across the workers’ experiences. The findings revealed that these workers have an incomplete understanding of OHS. In many workplaces, poor job training, little worker support, lack of power in the workplace, and a poor workplace safety culture make it difficult for recent immigrant workers to acquire OHS information and implement safe work practices. This study proposes workplace policies and practices that will improve worker OHS awareness and make workplaces safer for immigrant workers.

Keywords: new immigrant workers, occupational health and safety, workplace challenges, policy, practice

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Authors: D. Furuya, H. Ryujin, S. Takahira, Y. Sekine, Y. Oya, K. Sonoda, H. Ogawa, Y. Nomura, R. Maruyama, H. Kim, T. Kudo, A. Nakano, T. Saruta, S. Sugita, M. Nemoto, N. Tanahashi

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Purpose: To study the clinical characteristics of hypoglycemic coma in adult patients with type 1 or type 2 diabetes mellitus (DM). Methods: Participants in this retrospective study comprised 91 patients (54 men, 37 women; mean age ± standard deviation, 71.5 ± 12.6 years; range, 42-97 years) brought to our emergency department by ambulance with disturbance of consciousness in the 7 years from April 2007 to March 2014. Patients with hypoglycemia caused by alcoholic ketoacidosis, nutrition disorder, malignancies and psychological disorder were excluded. Results: Patients with type 1 (8 of 91) or type 2 DM (83 of 91) were analyzed. Mean blood sugar level was 31.6 ± 10.4 in all patients. A sulfonylurea (SU) was more commonly used in elderly (>75 years old; n=44)(70.5%) than in younger patients (36.2%, p < 0.05). Cases showing prolonged unconsciousness (range, 1 hour to 21 days; n=30) included many (p < 0.05) patients with dementia (13.3%; 0.5% without dementia) and fewer (p < 0.05) patients with type 1 DM (0%; 13.1% in type 2 DM). Specialists for DM (n=33) used SU less often (24.2%) than general physicians (69.0%, p < 0.05). Conclusion: In cases of hypoglycemic coma, SU was frequently used in elderly patients with DM.

Keywords: hypoglycemic coma, Diabetes mellitus, unconsciousness, elderly patients

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Authors: Matan Cohen, Maxim Shoshany

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Climatic, topographic and geological diversity, together with frequent disturbance and recovery cycles, produce highly complex spatial patterns of trees, shrubs, dwarf shrubs and bare ground patches. Assessment of spatial and temporal variations of these life-forms patterns under climate change is of high ecological priority. Here we report on one of the first attempts to discriminate between images of three Mediterranean life-forms patterns at three densities. The development of an extensive database of orthophoto images representing these 9 pattern categories was instrumental for training and testing pre-trained and newly-trained DL models utilizing DenseNet architecture. Both models demonstrated the advantages of using Deep Learning approaches over existing spectral and spatial (pattern or texture) algorithmic methods in differentiation 9 life-form spatial mixtures categories.

Keywords: texture classification, deep learning, desert fringe ecosystems, climate change

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Ernest Moles, Patricia Urbán, María Belén Jiménez-Díaz, Sara Viera-Morilla, Iñigo Angulo-Barturen, Maria Antònia Busquets, Xavier Fernàndez-Busquets

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Bearing in mind the absence of an effective vaccine against malaria and its severe clinical manifestations causing nearly half a million deaths every year, this disease represents nowadays a major threat to life. Besides, the basic rationale followed by currently marketed antimalarial approaches is based on the administration of drugs on their own, promoting the emergence of drug-resistant parasites owing to the limitation in delivering drug payloads into the parasitized erythrocyte high enough to kill the intracellular pathogen while minimizing the risk of causing toxic side effects to the patient. Such dichotomy has been successfully addressed through the specific delivery of immunoliposome (iLP)-encapsulated antimalarials to Plasmodium falciparum-infected red blood cells (pRBCs). Unfortunately, this strategy has not progressed towards clinical applications, whereas in vitro assays rarely reach drug efficacy improvements above 10-fold. Here, we show that encapsulation efficiencies reaching >96% can be achieved for the weakly basic drugs chloroquine (CQ) and primaquine using the pH gradient active loading method in liposomes composed of neutrally charged, saturated phospholipids. Targeting antibodies are best conjugated through their primary amino groups, adjusting chemical crosslinker concentration to retain significant antigen recognition. Antigens from non-parasitized RBCs have also been considered as targets for the intracellular delivery of drugs not affecting the erythrocytic metabolism. Using this strategy, we have obtained unprecedented nanocarrier targeting to early intraerythrocytic stages of the malaria parasite for which there is a lack of specific extracellular molecular tags. Polyethylene glycol-coated liposomes conjugated with monoclonal antibodies specific for the erythrocyte surface protein glycophorin A (anti-GPA iLP) were capable of targeting 100% RBCs and pRBCs at the low concentration of 0.5 μM total lipid in the culture, with >95% of added iLPs retained into the cells. When exposed for only 15 min to P. falciparum in vitro cultures synchronized at early stages, free CQ had no significant effect over parasite viability up to 200 nM drug, whereas iLP-encapsulated 50 nM CQ completely arrested its growth. Furthermore, when assayed in vivo in P. falciparum-infected humanized mice, anti-GPA iLPs cleared the pathogen below detectable levels at a CQ dose of 0.5 mg/kg. In comparison, free CQ administered at 1.75 mg/kg was, at most, 40-fold less efficient. Our data suggest that this significant improvement in drug antimalarial efficacy is in part due to a prophylactic effect of CQ found by the pathogen in its host cell right at the very moment of invasion.

Keywords: immunoliposomal nanoparticles, malaria, prophylactic-therapeutic polyvalent activity, targeted drug delivery

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Viyango Pandian, Kumaresh Athiyappan

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Pelvic congestion Syndrome (PCS) is usually seen in multiparous women who give history of chronic dull-aching pelvic pain. We report a case of a 17 year old unmarried female, who presented with acute onset of chronic dull-aching abdominal pain in the left iliac fossa, which particularly increased during menstruation and was finally diagnosed to be pelvic congestion syndrome. On ultrasonography, multiple tortuous and dilated veins were observed in the left adnexa. Both ovaries appeared normal in size, volume and echotexture. Computed tomography (CT) angiography was performed to precisely delineate the venous pathway and to assess any associated abnormality; which showed a dilated and tortuous left ovarian vein with an anomalous course around the left kidney and draining into the left renal vein. Clinical parameters and hormonal levels were within normal limits. This is a rare case of anomalous course of left ovarian vein associated with pelvic congestion syndrome.

Keywords: anomalous course of ovarian vein, computed tomography, pelvic congestion syndrome, ultrasonography

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Authors: Clemens Bulitta, Sasan Sadrizadeh, Sebastian Buhl

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Introduction: Ventilation technology in operating theatres (OT)is internationally regulated by dif-ferent standards, which define basic specifications for technical equipment and many times also the necessary operating and performance parameters. This confronts the operators of healthcare facilities with the question of finding the best ventilation and air conditioning system for the OT in order to achieve the goal of a large and robust surgicalworkzone with appropriate air quality and climate for patient safety and occupational health. Additionally, energy consumption and the potential need for clothing that limits transmission of bacteria must be considered as well as the total life cycle cost. However, the evaluation methodology of ventilation systems regarding these matters are still a topic of discussion. To date, there are neither any uniform standardized specifications nor any common validation criteria established. Thus, this study aimed to review data in the literature and add ourown research results to compare and assess the performance of different ventilations systems regarding infection preventive effects, energy efficiency, and staff comfort. Methods: We have conducted a comprehensive literature review on OT ventilation-related topics to understand the strengths and limitations of different ventilation systems. Furthermore, data from experimental assessments on OT ventilation systems at the University of Amberg-Weidenin Germany were in-cluded to comparatively assess the performance of Laminar Airflow (LAF), Turbulent Mixing Air-flow(TMA), and Temperature-controlled Airflow (TcAF) with regards to patient and occupational safety as well as staff comfort including indoor climate.CFD simulations from the Royal Institute of Technology in Sweden (KTH) were also studied to visualize the differences between these three kinds of ventilation systems in terms of the size of the surgical workzone, resilience to obstacles in the airflow, and energy use. Results: A variety of ventilation concepts are in use in the OT today. Each has its advantages and disadvantages, and thus one may be better suited than another depend-ing on the built environment and clinical workflow. Moreover, the proper functioning of OT venti-lation is also affected by multiple external and internal interfering factors. Based on the available data TcAF and LAF seem to provide the greatest effects regarding infection control and minimizing airborne risks for surgical site infections without the need for very tight surgical clothing systems. Resilience to obstacles, staff comfort, and energy efficiency seem to be favourable with TcAF. Conclusion: Based on literature data in current publications and our studies at the Technical Uni-versity of Applied Sciences Amberg-Weidenand the Royal Institute of Technoclogy, LAF and TcAF are more suitable for minimizing the risk for surgical site infections leading to improved clin-ical outcomes. Nevertheless, regarding the best management of thermal loads, atmosphere, energy efficiency, and occupational safety, overall results and data suggest that TcAF systems could pro-vide the economically most efficient and clinically most effective solution under routine clinical conditions.

Keywords: ventilation systems, infection control, energy efficiency, operating theatre, airborne infection risks

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Authors: Mohamed Mokhtar, Mostafa F. Shaaban

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Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

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Authors: Oladimeji Adetona Adeyeye, Emmanuel Rotimi Sadiku, Oluwaseun Olayinka Adeyeye

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In order to resuscitate soybean production and post-harvest processing especially, in term of threshing, there is need to develop an affordable threshing machine which will reduce drudgery associated with manual soybean threshing. Soybean thresher was fabricated and evaluated at Institute of Agricultural Research and Training IAR&T Apata Ibadan. The machine component includes; hopper, threshing unit, shaker, cleaning unit and the seed outlet, all working together to achieve the main objective of threshing and cleaning. TGX1835 - 10E variety was used for evaluation because of its high resistance to pests, rust and pustules. The final moisture content of the used sample was about 15%. The sample was weighed and introduced into the machine. The parameters evaluated includes moisture content, threshing efficiency, cleaning efficiency, machine capacity and speed. The threshing efficiency and capacity are 74% and 65.9kg/hr respectively. All materials used were sourced locally which makes the cost of production of the machine extremely cheaper than the imported soybean thresher.

Keywords: efficiency, machine capacity, speed, soybean, threshing

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Authors: Ana Maghfiroh

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Learning a foreign language needs a big effort from the learner itself to make their language ability grows better day by day. Among those, they also need a support from all around them including teacher, friends, as well as activities which support them to speak the language. When those activities developed well as a habit which are done regularly, it will help improving the students’ language competence. It was a qualitative research which aimed to find out and describe some activities implemented in Pesantren Al Mawaddah, Ponorogo, in order to teach the students a foreign language. In collecting the data, the researcher used interview, questionnaire, and documentation. From the study, it was found that Pesantren Al Mawaddah had successfully built the language habit on the students to speak the target language. More than 15 hours a day students were compelled to speak foreign language, Arabic or English, in turn. It aimed to habituate the students to keep in touch with the target language. The habit was developed through daily language activities, such as dawn vocabs giving, dictionary handling, daily language use, speech training and language intensive course, daily language input, and night vocabs memorizing. That habit then developed the students awareness towards the language learned as well as promoted their language mastery.

Keywords: habit, communicative competence, daily language activities, Pesantren

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Authors: Karthikeyan M., Paul M. J.

Abstract:

This case report discusses a 54-year-old woman from Salem, Tamilnadu, who presented with a rare case of papillary thyroid carcinoma (PTC), manifesting as a hypervascular mass in the left carotid sheath. The patient had a two-and-a-half-month history of non-progressive neck swelling, with symptoms including dysphagia and a choking sensation. Clinical examination and investigations such as FNAC and CECT revealed a large vascular mass in the left neck region, initially perplexing the diagnosis. The patient underwent total thyroidectomy and excision of the left carotid sheath mass. Histopathology confirmed PTC. Postoperatively, the patient received Iodine-131 ablation and showed good recovery with no recurrence. This case highlights the diagnostic challenge and atypical presentation of PTC as a vascular neck mass, emphasizing the importance of a comprehensive approach in evaluating thyroid and neck lesions.

Keywords: lateral neck vascular mass, lateral aberrant thyroid, thyroid vascular swelling, smooth post op recovery

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Authors: Anas H. Aljemely, Jianping Xuan

Abstract:

Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

Abstract:

Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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Authors: David Parmenter, Brian Millar

Abstract:

Obstructive sleep apnoea is a common condition which is generally under-diagnosed. Poorly managed obstructive sleep apnoea carries serious health risks and can greatly impact on the sufferer's quality of life. This publication covers the aetiology, symptoms, and treatment of sleep apnoea. The treatment of Obstructive Sleep Apnoea is an emerging field, and the useful role of the Dental Team is relatively unknown, therefor this paper will highlight the role of the dental team in its treatment. The concept of mandibular advancement appliances, along with the clinical and laboratory stages for constructing them, are documented. It is the hope of the author that this publication will educate healthcare professionals on the role of dental practitioners in the multidisciplinary team for treating sleep apnoea. Objective: Individuals should be more aware of the demographic of patients at risk of sleep apnoea, how it is diagnosed and which group of sleep apnoea patients are suitable to refer for mandibular appliance therapy. Individuals should also be aware of what a mandibular advancement appliance is and how it helps treat obstructive sleep apnoea.

Keywords: sleep apnoea, snoring, sleep appliances, mandibular advancement appliance

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Authors: Gaurav Sancheti

Abstract:

This study presents an impacting approach of Artificial Neural Networks (ANNs) in determining the quantity of High Tensile Steel (HTS) strands required in post-tensioned (PT) slabs. Various PT slab configurations were generated by varying the span and depth of the slab. For each of these slab configurations, quantity of required HTS strands were recorded. ANNs with backpropagation algorithm and varying architectures were developed and their performance was evaluated in terms of Mean Square Error (MSE). The recorded data for the quantity of HTS strands was used as a feeder database for training the developed ANNs. The networks were validated using various validation techniques. The results show that the proposed ANNs have a great potential with good prediction and generalization capability.

Keywords: artificial neural networks, back propagation, conceptual design, high tensile steel strands, post tensioned slabs, validation techniques

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Authors: Stephen O. Amaraihu

Abstract:

This research investigated the effect of Computer Based Instruction on Students’ interest, achievement, and retention in Algebra in Abia State College of Education (Technical), Arochukwu. Three research questions and two hypotheses guided the study. Two instruments, Maths Achievement Test (MAT) and Maths Interest Inventory were employed, to test a population of three hundred and sixteen (316) NCE 1 students in algebra. It is expected that this research will lead to the improvement of students’ performance and enhance their interest and retention of basic algebraic concept. It was found that the majority of students in the college are not proficient in the use of ICT as a result of a lack of trained personnel. It was concluded that the state government was not ready to implement the usage of mathematics in Abia State College of Education. The paper recommends, amongst others, the employment of mathematics Lectures with competent skills in ICT and the training of lecturers of mathematics.

Keywords: achievement, computer based instruction, interest, retention

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Authors: Emma Garcia-Meca, Jennifer Martinez-Ferrero, Camino Ramon Llorens

Abstract:

This paper provides insights into how narcissistic Chief Executive Officers (CEOs) influence the presence of women in top management teams (TMT). We also study whether a CEO's power and gender and the gender diversity of the firm's board moderate the relationship between CEO narcissism and TMT gender diversity. Our results reveal that narcissistic CEOs are less likely to support women in TMTs, confirming that CEO personality traits influence team structure. Further results suggest that this aversion increases as the CEO's power grows when female representation on boards decreases and when the CEO is a woman. This paper integrates theories that use the social psychology and upper echelon theories, offering a greater understanding of how CEO personality traits influence the structure of firms. We also contribute to the knowledge about how different governance characteristics can moderate the influence of narcissistic CEOs on women in TMTs, highlighting the relevance of governance traits that increase the effect of narcissism. The results demonstrate different female behavior toward promoting TMT gender equality depending on the specific position of women in the firm's hierarchy and their psychological attributes. We find that women directors support social identity values, and narcissistic female CEOs act like queen bees.

Keywords: gender diversity, board, corporate governance, female CEO, management

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Authors: Sanele E. Nene L., Lia M. Hewitt

Abstract:

Background: Artificial intelligence (AI) has a high value in healthcare, various applications have been developed for the efficiency of clinical operations, such as appointment/surgery scheduling, diagnostic image analysis, prognosis, prediction and management of specific ailments. Purpose: The purpose of this study was to explore, describe, contrast, evaluate, and develop the various leadership strategies as a conceptual framework, applied by public health Operational Managers (OMs) to embrace AI benefits, with the aim to improve the healthcare system in a public hospital. Design and Method: A qualitative, exploratory, descriptive and contextual research design was followed and a descriptive phenomenological approach. Five phases were followed to conduct this study. Phenomenological individual interviews and focus groups were used to collect data and a phenomenological thematic data analysis method was used. Findings and conclusion: Three themes surfaced as the experiences of AI by the OMs; Positive experiences related to AI, Management and leadership processes in AI facilitation, and Challenges related to AI.

Keywords: ambivalence, embracing, Artificial intelligence, public hospital

Procedia PDF Downloads 70