Search results for: early Alzheimer’s recognition

Authors: Somar Boubou, Tatsuo Narikiyo, Michihiro Kawanishi

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In this work, we address the problem of 3D object recognition with depth sensors such as Kinect or Structure sensor. Compared with traditional approaches based on local descriptors, which depends on local information around the object key points, we propose a global features based descriptor. Proposed descriptor, which we name as Differential Histogram of Normal Vectors (DHONV), is designed particularly to capture the surface geometric characteristics of the 3D objects represented by depth images. We describe the 3D surface of an object in each frame using a 2D spatial histogram capturing the normalized distribution of differential angles of the surface normal vectors. The object recognition experiments on the benchmark RGB-D object dataset and a self-collected dataset show that our proposed descriptor outperforms two others descriptors based on spin-images and histogram of normal vectors with linear-SVM classifier.

Keywords: vision in control, robotics, histogram, differential histogram of normal vectors

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Authors: Bubai Maji, Monorama Swain

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Speech is considered an essential and most natural medium for the interaction between machines and humans. However, extracting effective features for speech emotion recognition (SER) is remains challenging. The present studies show that the temporal information captured but high-level temporal-feature learning is yet to be investigated. In this paper, we present an efficient novel method using the Self-attention (SA) mechanism in a combination of Convolutional Neural Network (CNN) and Bi-directional Gated Recurrent Unit (Bi-GRU) network to learn high-level temporal-feature. In order to further enhance the representation of the high-level temporal-feature, we integrate a Bi-GRU output with learnable weights features by SA, and improve the performance. We evaluate our proposed method on our created SITB-OSED and IEMOCAP databases. We report that the experimental results of our proposed method achieve state-of-the-art performance on both databases.

Keywords: Bi-GRU, 1D-CNNs, self-attention, speech emotion recognition

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Authors: Chinedu Ifedi Okeke

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The behavioural orientations of fathers, which resonate in the way they relate to members of their families and other community members, appear to have a variety of implications for the early development of children. In this paper, a conceptual map of fathers’ lifestyles is adopted to provide an interconnected network of father lifestyles. Empirical evidence from a qualitative case study of 25 Black fathers, who had been purposively selected from a suburb in one rural Eastern Cape municipality in South Africa, is reported in this paper. Semi-structured in-depth interviews were used to obtain data, which was analysed thematically. Findings identify and provide evidence of father lifestyles that are incongruent with the kind of parental behaviour needed to support the healthy early development of children. Findings suggest that these negative lifestyles appear to incapacitate fathers who fail to make a positive contribution to their children’s early development. To ensure that fathers make the expected contributions to their children’s early development, policies aimed at rehabilitating fathers who are involved in the negative lifestyles reported in this paper should be put in place.

Keywords: childhood development, fathering, fathers, intervention strategies, lifestyles, South Africa

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Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

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Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha

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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Keywords: TDNN, neural networks, noise, speech recognition

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Authors: Jae-Hyun Choi, Sung-Soo Bae, Sangyoung Yoon, Hong-Ku Yun, Jiyoung Kwahk

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This study was conducted to investigate the effect of ocular dominance on recognition performance using a single-lens smart display designed for cycling. A total of 36 bicycle riders who have been cycling consistently were recruited and participated in the experiment. The participants were asked to perform tasks riding a bicycle on a stationary stand for safety reasons. Independent variables of interest include ocular dominance, bike usage, age group, and information layout. Recognition time (i.e., the time required to identify specific information measured with an eye-tracker), error rate (i.e. false answer or failure to identify the information in 5 seconds), and user preference scores were measured and statistical tests were conducted to identify significant results. Recognition time and error ratio showed significant difference by ocular dominance factor, while the preference score did not. Recognition time was faster when the single-lens see-through display on the dominant eye (average 1.12sec) than on the non-dominant eye (average 1.38sec). Error ratio of the information recognition task was significantly lower when the see-through display was worn on the dominant eye (average 4.86%) than on the non-dominant eye (average 14.04%). The interaction effect of ocular dominance and age group was significant with respect to recognition time and error ratio. The recognition time of the users in their 40s was significantly longer than the other age groups when the display was placed on the non-dominant eye, while no difference was observed on the dominant eye. Error ratio also showed the same pattern. Although no difference was observed for the main effect of ocular dominance and bike usage, the interaction effect between the two variables was significant with respect to preference score. Preference score of daily bike users was higher when the display was placed on the dominant eye, whereas participants who use bikes for leisure purposes showed the opposite preference patterns. It was found more effective and efficient to wear a see-through display on the dominant eye than on the non-dominant eye, although user preference was not affected by ocular dominance. It is recommended to wear a see-through display on the dominant eye since it is safer by helping the user recognize the presented information faster and more accurately, even if the user may not notice the difference.

Keywords: eye tracking, information recognition, ocular dominance, smart headware, wearable device

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Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

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Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

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Authors: Rabail Shafique Satti, Sidra Ejaz, Madiha Arshad, Marwa Khalid, Sadia Majeed

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The paper presents the development of an automated security system to automate the entry of visitors, providing more flexibility of managing their record and securing homes or workplaces. Face recognition is part of this system to authenticate the visitors. A cost effective and SMS based door security module has been developed and integrated with the GSM network and made part of this system to allow communication between system and owner. This system functions in real time as when the visitor’s arrived it will detect and recognizes his face and on the result of face recognition process it will open the door for authorized visitors or notifies and allows the owner’s to take further action in case of unauthorized visitor. The proposed system is developed and it is successfully ensuring security, managing records and operating gate without physical interaction of owner.

Keywords: SMS, e-mail, GSM modem, authenticate, face recognition, authorized

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Authors: Lin Yanyan

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This research set out to understand early childhood practitioners’ perceptions of continuous professional development (CPD) opportunities and its relationship to career progression and leadership roles in Singapore. The small-scale qualitative inductive study was conducted in two phases. Phase one used close-ended questionnaires with a total of 24 early years practitioner participants, while phase two included a total of 5 participants who were invited to participate in the second part of the data collection. Semi-structured interviews were used at phase two to elicit deeper responses from parents and teachers. Findings from the study were then thematically coded and analysed. The findings from both questionnaires and interviews showed that early years practitioners perceived CPD to be important to their professional growth, but there was no conclusive link that CPD necessarily led to the progression of leadership roles in the early years. Participants experience of CPD was strongly determined by their employer- the preschool operator, being government-funded or a private entity, which resulted in key differences emerging between their responses. Participants also experienced road blocks in their pursuit of CPD, in the form of staff shortage, budget constraints and lack of autonomy as their employers imposed specific CPD courses on them to suit the organisational needs, rather than their personal or professional needs.

Keywords: continuous professional development (CPD), early years practitioners (EYP), career progression, leadership

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Authors: Dong Seop Lee, Byung Sik Kim

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In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

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Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

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Authors: M. Naresh, Pratik Chaturvedi, Srishti Yadav, Varun Dutt, K. V. Uday

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Changes in the Earth’s climate are likely to increase natural hazards such as drought, floods, earthquakes, landslides, etc. The present study focusing on to early warning systems (EWS) of landslides, major issues in Himalayan region without prominence to deforestation, encroachments and un-engineered cutting of slopes and reforming for infrastructural purposes. EWS can be depicted by conducting a series of flume tests using micro-electro mechanical systems sensors data after reaching threshold values under controlled laboratory conditions. Based on the threshold value database, an alert will be sent via SMS.

Keywords: slope-instability, flume test, sensors, early warning system

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Authors: Khachen Kongpakwattana, Charungthai Dejthevaporn, Orapitchaya Krairit, Piyameth Dilokthornsakul, Devi Mohan, Nathorn Chaiyakunapruk

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Background: Although an increase in the burden of Alzheimer’s disease (AD) is evident worldwide, knowledge of costs and health-related quality of life (HR-QoL) associated with AD in Low- and Middle-Income Countries (LMICs) is still lacking. We, therefore, aimed to collect real-world cost and HR-QoL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand. Methods: We recruited AD patients aged ≥ 60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HR-QoL and caregiving information using standardized tools. The hospital’s database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HR-QoL. Results: Among 148 community-dwelling patients, average annual total societal costs of AD care were 8,014 US$ [95% Confidence Interval (95% CI): 7,295 US$ - 8,844 US$] per patient. Total costs of patients with severe stage (9,860 US$; 95% CI: 8,785 US$ - 11,328 US$) were almost twice as high as those of mild stage (5,524 US$; 95% CI: 4,649 US$ - 6,593 US$). The major cost driver was direct medical costs, particularly those incurred by AD prescriptions. Functional status was the strongest determinant for both total costs and patient’s HR-QoL (p-value < 0.001). Conclusions: Our real-world findings suggest the distinct major cost driver which results from expensive AD treatment, emphasizing the demand for country-specific cost evidence. Increases in cognitive and functional status are significantly associated with decreases in total costs of AD care and improvement on patient’s HR-QoL.

Keywords: Alzheimer's disease, associations, costs, disease-severity indicators, health-related quality of life

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Authors: Rana F. Obeidat, Suzanne S. Dickerson, Gregory G. Homish, Nesreen M. Alqaissi, Robin M. Lally

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Background: Despite the fact that breast cancer is the most prevalent cancer among Jordanian women, practically nothing is known about their perceptions of early stage breast cancer and surgical treatment. Objective: To gain understanding of the diagnosis and surgical treatment experience of Jordanian women diagnosed with early stage breast cancer. Methods: An interpretive phenomenological approach was used for this study. A purposive sample of 28 Jordanian women who were surgically treated for early stage breast cancer within 6 months of the interview was recruited. Data were collected using individual interviews and analyzed using Heideggerian hermeneutical methodology. Results: Fear had a profound effect on Jordanian women’s stories of diagnosis and surgical treatment of early stage breast cancer. Women’s experience with breast cancer and its treatment was shaped by their pre-existing fear of breast cancer, the disparity in the quality of care at various health care institutions, and sociodemographic factors (e.g., education, age). Conclusions: Early after the diagnosis, fear was very strong and women lost perspective of the fact that this disease was treatable and potentially curable. To control their fears, women unconditionally trusted God, the health care system, surgeons, family, friends, and/or neighbors, and often accepted treatment offered by their surgeons without questioning. Implications for practice: Jordanian healthcare providers have a responsibility to listen to their patients, explore meanings they ascribe to their illness, and provide women with proper education and support necessary to help them cope with their illness.

Keywords: breast cancer, early stage, Jordanian, experience, phenomenology

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Authors: Sunanta Klibthong

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In view of the Thailand government policy creating increasing awareness of opportunity for children with special needs, the number of children with disabilities enrolled in kindergartens in Thailand has increased. This study explores early childhood teachers’ experiences and concerns of teaching children with disabilities in inclusive classrooms. The population of the study was private early childhood teachers who teach in inclusive classrooms in Thailand. Quantitative data obtained through a questionnaire were supplemented by early childhood teachers’ interviews to identify key experiences and concerns of the teachers when teaching children with and without disabilities in the same classrooms. The results of this study indicated that many teachers face challenges including lack of professional development opportunities, difficulty identifying the needs of all children and how to use effective strategies to support inclusive practices in their classrooms. Teachers also expressed concern about parents’ lack of willingness to accept children without disabilities studying together with those with disabilities in the same classrooms. Findings from this study can inform program support for parents and professional support needs of teachers in the provision of high-quality inclusive programs for all students.

Keywords: the concern, early childhood, experience, inclusive education, Thailand

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Authors: Muhammad Tayyab, Saba Saira

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It is an established fact that organizations across the globe consider employees as their assets and try to advance their well-being. However, the local firms of developing countries are mostly profit oriented and do not have much concern about their employees’ engagement or commitment. Like other developing countries, the local organizations of Pakistan are also less concerned about the well-being of their employees. Especially public sector organizations lack concern regarding engagement, satisfaction or commitment of the employees. Therefore, this study aimed at investigating the impact of job recognition and job motivation on organizational commitment in the mediation role of employee engagement. The data were collected from land record officers of board of revenue, Punjab, Pakistan. Structured questionnaire was used to collect data through physically visiting land record officers and also through the internet. A total of 318 land record officers’ responses were finalized to perform data analysis. The data were analyzed through confirmatory factor analysis and structural equation modeling technique. The findings revealed that job recognition and job motivation have direct as well as indirect positive and significant impact on organizational commitment. The limitations, practical implications and future research indications are also explained.

Keywords: job motivation, job recognition, employee engagement, employee commitment, public sector, land record officers

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Authors: Simon B. N. Thompson

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Retinoblastoma is a rare type of childhood genetic cancer that affects children worldwide. The diagnosis is often missed due to lack of education and difficulty in presentation of the tumor. Frequently, the tumor on the retina is noticed by photography when the red-eye flash, commonly seen in normal eyes, is not produced. Instead, a yellow or white colored patch is seen or the child has a noticeable strabismus. Early detection can be life-saving though often results in removal of the affected eye. Remaining functioning in the healthy eye when the child is young has resulted in super-vision and high or above-average intelligence. Technological advancement of cameras has helped in early detection. Brain imaging has also made possible early detection of neurological diseases and, together with the monitoring of cortisol levels and yawning frequency, promises to be the next new early diagnostic tool for the detection of neurological diseases where cortisol insufficiency is particularly salient, such as multiple sclerosis and Cushing’s disease.

Keywords: cortisol, neurological disease, retinoblastoma, Thompson cortisol hypothesis, yawning

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Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim

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The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.

Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition

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Authors: Hsiang-Ru Lin

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Cholesterol plays an essential role in the regulation of the progression of numerous important diseases including atherosclerosis and Alzheimer disease so the generation of suitable cholesterol-lowering reagents is urgent to develop. Liver X receptor (LXR) is a ligand-activated transcription factor whose natural ligands are cholesterols, oxysterols and glucose. Once being activated, LXR can transactivate the transcription action of various genes including CYP7A1, ABCA1, and SREBP1c, involved in the lipid metabolism, glucose metabolism and inflammatory pathway. Essentially, the upregulation of ABCA1 facilitates cholesterol efflux from the cells and attenuates the production of beta-amyloid (ABeta) 42 in brain so LXR is a promising target to develop the cholesterol-lowering reagents and preventative treatment of Alzheimer disease. Engelhardia roxburghiana is a deciduous tree growing in India, China, and Taiwan. However, its chemical composition is only reported to exhibit antitubercular and anti-inflammatory effects. In this study, four compounds, engelheptanoxides A, C, engelhardiol A, and B isolated from the root of Engelhardia roxburghiana were evaluated for their agonistic activity against LXR by the transient transfection reporter assays in the HepG2 cells. Furthermore, their interactive modes with LXR ligand binding pocket were generated by molecular modeling programs. By using the cell-based biological assays, engelheptanoxides A, C, engelhardiol A, and B showing no cytotoxic effect against the proliferation of HepG2 cells, exerted obvious LXR agonistic effects with similar activity as T0901317, a novel synthetic LXR agonist. Further modeling studies including docking and SAR (structure-activity relationship) showed that these compounds can locate in LXR ligand binding pocket in the similar manner as T0901317. Thus, LXR is one of nuclear receptors targeted by pharmaceutical industry for developing treatments of Alzheimer and atherosclerosis diseases. Importantly, the cell-based assays, together with molecular modeling studies suggesting a plausible binding mode, demonstrate that engelheptanoxides A, C, engelhardiol A, and B function as LXR agonists. This is the first report to demonstrate that the extract of Engelhardia roxburghiana contains LXR agonists. As such, these active components of Engelhardia roxburghiana or subsequent analogs may show important therapeutic effects through selective modulation of the LXR pathway.

Keywords: Liver X receptor (LXR), Engelhardia roxburghiana, CYP7A1, ABCA1, SREBP1c, HepG2 cells

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Authors: Theophilus O. Odunlami, Hasan Haroglu, Nader Saleh-Matter

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The challenges facing the construction industry are often worsened by the compounded nature of projects coupled with the complexity of key stakeholders involved at different stages of the project. Projects are planned to achieve outlined benefits in line with the business case; however, a lack of effective management of key stakeholders can result in unrealistic delivery aspirations, unnecessary re-works, and overruns. The aim of this study is to examine the early stages of a project lifecycle and investigate the stakeholder management and involvement processes and their impact on the successful delivery of the project. The research engaged with conventional construction organisations and project personnel and stakeholders on diverse projects, using a research strategy to analyse existing project case studies, narrative enquiries, interviews, and surveys using a combined qualitative, quantitative, and mixed method of analysis. Research findings have shown that the involvement of stakeholders at different levels during the early stages has pronounced effects on project delivery; it helps to forge synergy and promotes a clear understanding of individual responsibilities, strengths, and weaknesses. This has often fostered a positive sense of productive collaboration right through the early stages of the project. These research findings intend to contribute to the development of a process framework for stakeholder and project team involvement in the early stages of a project. This framework will align with the selection criteria for stakeholders, contractors, and resources, ultimately contributing to the successful completion of projects. The primary question addressed in this study is stakeholder involvement and management of the early stages of a building project life cycle impacts project delivery. Findings showed that early-stage stakeholder involvement and collaboration between project teams and contractors significantly contribute to project success. However, a strong and healthy communication strategy would be required to maintain the flow of value-added ideas among stakeholders at the early stages to benefit the project at the execution stage.

Keywords: early stages, project lifecycle, stakeholders, decision-making strategy, project framework

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Authors: Hui Wei, Zheng Dong

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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

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Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran

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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.

Keywords: access control, multimodal biometrics, pattern recognition, security safe

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Authors: Shu-Ling Wang

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Background: Multiple studies showed early skin-to-skin contact (SSC) with mothers was beneficial to newborns such as breastfeeding and maternal childcare. In cases of newborns unable to have early SSC with mothers, fathers’ involvement could let early SSC continue without interruption. However, few studies had explored the effects of early SSC by fathers in comparison to early SSC with mothers. Paternal involvement of early SSC should be equally important in term of childcare and breastfeeding. The purpose of this study was to evaluate the efficacy of early SSC by fathers in particular in their support of breastfeeding. Methods: A quasi-experimental design was employed by the study. One hundred and forty-four father-infant pairs had participated the study, in which infants were assigned either to SSC with their fathers (n = 72) or to routine care (n = 72) as the control group. The study was conducted at a regional hospital in northern Taiwan. Participants included parents of both vaginal delivery (VD) and caesarean section birth (CS) infants. To be eligible for inclusion, infants must be over 37-week gestational ages. Data were collected twice: as pretest upon admission and as posttest with online questionnaire during first, second, and third postpartum months. The questionnaire included items for Breastfeeding Social Support, methods of feeding, and the mother-infant 24-hour rooming-in rate. The efficacy of early SSC with fathers was evaluated using the generalized estimating equation (GEE) modeling. Research Result: The primary finding was that SSC with fathers had positive impact on fathers’ support of breastfeeding. Analysis of the online questionnaire indicated that early SSC with fathers improved the support of breastfeeding than the control group (VD: t = -4.98, p < .001; CS: t = -2.37, p = .02). Analysis of mother-infant 24-hour rooming-in rate showed that SSC with fathers after CS had a positive impact on the rooming-in rate (χ² = 5.79, p = .02); however, with VD the difference between early SSC with fathers and the control group was insignificant (χ² = .23, p = .63). Analysis of the rate of exclusive breastfeeding indicated that early SSC with fathers had a higher rate than the control group during first three postpartum months for both delivery methods (VD: χ² = 12.51, p < .001 on 1st postpartum month, χ² = 8.13, p < .05 on 2nd postpartum month, χ² = 4.43, p < .05 on 3rd postpartum month; CS: χ² = 6.92, p < .05 on 1st postpartum month, χ² = 7.41, p < .05 on 2nd postpartum month, χ² = 6.24, p < .05 on 3rd postpartum month). No significant difference was found on the rate of exclusive breastfeeding with both methods of delivery between two groups during hospitalization. (VD: χ² =2 .00, p = .16; CS: χ² = .73, p = .39). Conclusion: Implementing early SSC with fathers has many benefits to both parents. The result of this study showed increasing fathers’ support of breastfeeding. This encourages our nursing personnel to focus the needs of father during breastfeeding, therefore further enhancing the quality of parental care, the rate and duration of breastfeeding.

Keywords: breastfeeding, skin-to-skin contact, support of breastfeeding, rooming-in

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Authors: Sultana Razia

Abstract:

The purpose of this study was to investigate the effect of early therapeutic intervention on children with an autism spectrum disorder. Participants were 140 children with autism spectrum disorder from Autism Corner in a selected rehabilitation center of Bangladesh. This study included children who are at aged of 18-month to 36-month and who were taking occupational therapy and speech and language therapy from the autism center. They were primarily screened using M-CHAT; however, children with other physical disabilities or medical conditions were excluded. 3-months interventions of 6 sessions per week are a minimum of 45-minutes long per session, one to one interaction followed by parent-led structured home-based therapy were provided. The results indicated that early intensive therapeutic intervention improves understanding, social skills and sensory skills. It can be concluded that therapeutic early intervention has a positive effect on diminishing symptoms of Autism Spectrum Disorder.

Keywords: autism, m-chat, reciprocal social behavior, CRP

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Authors: Akinwumi Omotayo, Badu-B Apraku, Joseph Olobasola, Petra Abdul Saghir, Yinka Sobowale

Abstract:

In southwestern Nigeria, climate change has led to loss of at least two months of rainfall. Consequently, only one cycle of maize can now be grown because of the shorter duration of rainy season as against two cycles in the past. The Early and Extra-early maturing varieties of maize were originally developed for the semi-arid and arid zones of West and Central Africa where there are seasonal challenges of water threatening optimum performance of the traditional maize grown, which are commonly late in maturity (115 to 120 days). The early varieties of maize mature in 90 to 95 days; while the Extra-Early maize varieties reach physiological maturity in less than 90 days. It was broadly hypothesized that the extra early varieties of maize could mitigate the effects of climate change in southwestern Nigeria with higher levels of rainfall by reinstating the original two cycles of rain-fed maize crop. Trials were therefore carried out in southwestern Nigeria on the possibility of adapting the extra early maize to mitigate the effects of climate change. The trial was the Mother/Baby design. The mother trial involves the evaluation of extra-early varieties following ideal recommendations and closely supervised centrally at the University research farm and the Agricultural Development Programmes (ADPs). This requires farmers to observe and evaluate the technology and the management regime meant to precede the second stage of evaluation at several satellite farmers field managed by selected farmers. The Baby Trial is expected to provide a realistic assessment of the technology by farmers in their own environment. A stratified selection of thirty farmers for the Baby Trial ensured appropriate representation across the different categories of the farming population by age and gender. Data from the trials indicate that extra early maize can be grown in two cycles rain fed in south west Nigeria and a third and fourth cycle could be obtained with irrigation. However the long duration varieties outyielded the extra early maize in both the mother and baby trials. When harvested green, the extra early maize served as source of food between March and May when there was scarcity of food. This represents a major advantage. The study recommends that further work needs to be done to improve the yield of extra early maize to encourage farmers to adopt.

Keywords: adaptation, climate change, extra early, maize varieties, mitigation

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Authors: St. Subaedah, A. Takdir, Netty, D. Hidrawati

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Maize development at the rainfed lowland after rice is often confronted with the occurrence of drought stress at the time of entering the generative phase, which will cause be hampered crop production. Consequently, in the utilization of the rainfed lowland areas optimally, an effort that can be done using the varieties of early maturity to minimize crop failures due to its short rainy season. The aim of this research was evaluating the potential yield of genotypes of candidates of maize early maturity in the rainfed lowland areas. The study was conducted during May to August 2016 at South Sulawesi, Indonesia. The study used randomized block design to compare 12 treatments and consists of 8 genotypes namely CH1, CH2, CH3, CH4, CH5, CH6, CH7, CH8 and the use of four varieties, namely Bima 3, Bima 7, Lamuru and Gumarang. The results showed that genotype of CH2, CH3, CH5, CH 6, CH7 and CH8 harvesting has less than 90 days. There are two genotypes namely genotypes of CH7 and CH8 that have a fairly high production respectively of 7.16 tons / ha and 8.11 tons/ ha and significantly not different from the superior varieties Bima3.

Keywords: evaluation, early maturity, maize, yield potential

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Authors: Brahim-Fares Zaidi, Malika Boudraa, Sid-Ahmed Selouani

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Our work aims to improve our Automatic Recognition System for Dysarthria Speech (ARSDS) based on the Hidden Models of Markov (HMM) and the Hidden Markov Model Toolkit (HTK) to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients (MFCC's) and Perceptual Linear Prediction (PLP's) and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.

Keywords: hidden Markov model toolkit (HTK), hidden models of Markov (HMM), Mel-frequency cepstral coefficients (MFCC), perceptual linear prediction (PLP’s)

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Authors: Majed Al Otaibi, Melissa Lessard-Beaudoin, Amel Loudghi, Raphael Chouinard-Watkins, Melanie Plourde, Frederic Calon, C. Alexandre Castellano, Stephen Cunnane, Helene Payette, Pierrette Gaudreau, Denis Gris, Rona K. Graham

Abstract:

Introduction: Alzheimer disease (AD) is a chronic disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction, and also alterations in attention, planning, language and overall cognitive function. Olfactory dysfunction is a common symptom of several neurological disorders including AD. Studying the mechanisms underlying the olfactory dysfunction may therefore lead to the discovery of potential biomarkers and/or treatments for neurodegenerative diseases. Objectives: To determine if olfactory dysfunction predicts future cognitive impairment in the aging population and to characterize the olfactory system in a murine model expressing a genetic factor of AD. Method: For the human study, quantitative olfactory tests (UPSIT and OMT) have been done on 93 subjects (aged 80 to 94 years) from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) cohort accepting to participate in the ORCA secondary study. The telephone Modified Mini Mental State examination (t-MMSE) was used to assess cognition levels, and an olfactory self-report was also collected. In a separate cohort, olfactory cortical volume was calculated using MRI results from healthy old adults (n=25) and patients with AD (n=18) using the AAL single-subject atlas and performed with the PNEURO tool (PMOD 3.7). For the murine study, we are using Western blotting, RT-PCR and immunohistochemistry. Result: Human Study: Based on the self-report, 81% of the participants claimed to not suffer from any problem with olfaction. However, based on the UPSIT, 94% of those subjects showed a poor olfactory performance and different forms of microsmia. Moreover, the results confirm that olfactory function declines with age. We also detected a significant decrease in olfactory cortical volume in AD individuals compared to controls. Murine study: Preliminary data demonstrate there is a significant decrease in expression levels of the proform of caspase-3 and the caspase substrate STK3, in the olfactory bulb of mice expressing human APOE4 compared with controls. In addition, there is a significant decrease in the expression level of the caspase-9 proform and caspase-8 active fragment. Analysis of the mature neuron marker, NeuN, shows decreased expression levels of both isoforms. The data also suggest that Iba-1 immunostaining is increased in the olfactory bulb of APOE4 mice compared to wild type mice. Conclusions: The activation of caspase-3 may be the cause of the decreased levels of STK3 through caspase cleavage and may play role in the inflammation observed. In the clinical study, our results suggest that seniors are unaware of their olfactory function status and therefore it is not sufficient to measure olfaction using the self-report in the elderly. Studying olfactory function and cognitive performance in the aging population will help to discover biomarkers in the early stage of the AD.

Keywords: Alzheimer's disease, APOE4, cognition, caspase, brain atrophy, neurodegenerative, olfactory dysfunction

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Authors: Sofia Hartati

Abstract:

This research is aimed at describing training in early childhood education program empirically, describing teachers ability to plan lessons empirically, and acquiring empirical data as well as analyzing the influence of guided and independent training toward teachers competence in planning early childhood learning program. The method used is an experiment. It collected data with a population of 76 early childhood educators in Tunjung Teja Sub District area through random sampling technique and grouped into two namely 38 people in an experiment class and 38 people in a controlled class. The technique used for data collections is a test. The result of the research shows that there is a significant influence between training for guided educators toward Teachers Ability toward Planning Early Childhood Learning Program. Guided training has been proven to improve the ability to comprehend planning a learning program. The ability to comprehend planning a learning program owned by teachers of early childhood program comprises of 1) determining the characteristics and competence of students prior to learning; 2) formulating the objective of the learning; 3) selecting materials and its sequences; 4) selecting teaching methods; 5) determining the means or learning media; 6) selecting evaluation strategy as a part of teachers pedagogic competence. The result of this research describes a difference in the competence level of teachers who have joined guided training which is relatively higher than the teachers who joined the independent training. Guided training is one of an effective way to improve the knowledge and competence of early childhood educators.

Keywords: competence, planning, teachers, training

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Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman

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Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.

Keywords: Automatic Speech Recognition System, children speech, adaptation, Malay

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