Search results for: Medical training

Authors: Rita C. Ramos

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Medical Surgical Nursing is one of the major subjects in nursing. This study examined the validity and reliability of the achievement examination utilizing the Classical Test Theory and Item Response Theory. The study answered the following objectives specifically : ( a) To establish the validity and reliability of the achievement examination utilizing Classical Test Theory and Item Response Theory ; ( b ) To determine the dimensionality measure of items and ( c ) to compare the item difficulty and item discrimination of the Medical Surgical Nursing Achievement examination using Classical Test Theory ( CTT ) and Item Response Theory ( IRT ). The developed instrument was administered to fourth year nursing students (N= 136) of a private university in Manila. The findings yielded the following results: The achievement examination is reliable both using CTT and IRT. The findings indicate person and item statistics from two frameworks are quite alike. The achievement examination formed a unidimensional construct.

Keywords: Achievement Examination, Item Response Theory, Medical Surgical, Nursing.

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Authors: Anchana Khemphila, Veera Boonjing

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In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.

Keywords: Data mining, classification, Parkinson disease, artificial neural networks, feature selection, information gain.

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Authors: M. Das Gupta, S. Banerjee

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Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.

Keywords: Case based reasoning, Exudates, Retina image, Similarity based retrieval.

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Authors: Aleksandra Zysk, Pawel Badura

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Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: Classification, singing, spectral analysis, vocal emission, vocal register.

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Authors: Sabina Jordan, Miha Tomšič, Friderik Knez, Marjana Šijanec Zavrl

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To determine the possibilities for the implementation of sustainable building indicators in Slovenia, testing of the first version of the indicators, developed in the CARE4CLIMATE project and based on the EU Level(s) framework, was carried out in 2022. Invited and interested stakeholders of the construction process were provided with video content and instructions on the Slovenian e-platform of sustainable building indicators. In addition, workshops and lectures with individual subjects were also performed. The final phase of the training and testing procedure included a questionnaire, which was used to obtain information about the participants' opinions regarding the indicators. The analysis of the results of the testing, which was focused on level 2, confirmed the key preliminary finding of the development group, namely that currently, due to the lack of certain knowledge, data, and tools, all indicators for this level are not yet feasible in practice. The research also highlighted the greater need for training and specialization of experts in this field. At the same time, it showed that the testing of the first version itself was a big challenge: only 30 experts fully participated and filled out the online questionnaire. This number seems alarmingly low at first glance, but compared to level(s) testing in the EU member states, it is much more than 50 times higher. However, for the further execution of the indicators in Slovenia, it will therefore be necessary to invest a lot of effort and engagement. It is likely that state support will also be needed, for example, in the form of financial mechanisms or incentives and/or legislative background.

Keywords: Sustainability, building indicator, project CARE4CLIMATE, alpha version SLO kTG, Level(s), sustainable construction stakeholders.

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Authors: Gurung S., Yadav B. N., Budhathoki SS.

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Problem based learning is one of the highly acclaimed learning methods in medical education since its first introduction at Mc-Master University in Canada in the 1960s. It has now been adopted as a teaching learning method in many medical colleges of Nepal. B.P. Koirala Institute of Health Sciences (BPKIHS), a health science deemed university is the second institute in Nepal to establish problem-based learning academic program and need-based teaching approach hence minimizing teaching through lectures since its inception. During the first two years of MBBS course, the curriculum is divided into various organ-systems incorporated with problem-based learning exercise each of one week duration.

Keywords: PBL, medical education.

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Authors: Natanya Meyer, Johann Landsberg

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Unemployment among the youth is a significant problem in South Africa. Large corporations and the public sector simply cannot create enough jobs. Too many youths in South Africa currently do not consider entrepreneurship as an option in order to become independent. Unlike the youth of the Netherlands, South African youth prefer to find employment in the public or private sector. The Netherlands has a much lower unemployment rate than South Africa and the Dutch are generally very entrepreneurial. From early on, entrepreneurship is considered a desirable career option in the Netherlands. The purpose of this study was to determine whether there is a difference in the perceptions of some Dutch and South African students in terms of unemployment and entrepreneurship. Questionnaires were distributed to students at the North West University's Vaal Triangle campus in Vanderbijlpark in Gauteng, South Africa and the Technical University of Delft in the Netherlands. A descriptive statistical analysis approach was followed and the means for the independent questions were calculated. The results demonstrate that the Dutch students are not as concerned about unemployment after completion of their studies as this is not as significant a problem as it is in South Africa. Both groups had positive responses towards the posed questions, but the South African group felt more strongly about the issues. Both groups of students felt that there was a need for more practical entrepreneurship training. The South African education system should focus on practical entrepreneurship training from a young age.

Keywords: Entrepreneurship development, entrepreneurship development programmes, entrepreneurship intention, Netherlands, South Africa, unemployment.

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Authors: M. Athar Hussain, N.B. Jumani, Munazza Sultana., M. Zafar Iqbal

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Language Reforms and potential use of ICTs has been a focal area of Higher Education Commission of Pakistan. Efforts are being accelerated to incorporate fast expanding ICTs to bring qualitative improvement in language instruction in higher education. This paper explores how university teachers are benefitting from ICTs to make their English class effective and what type of problems they face in practicing ICTs during their lectures. An in-depth qualitative study was employed to understand why language teachers tend to use ICTs in their instruction and how they are practicing it. A sample of twenty teachers from five universities located in Islamabad, three from public sector and two from private sector, was selected on non-random (Snowball) sampling basis. An interview with 15 semi-structured items was used as research instruments to collect data. The findings reveal that business English teaching is facilitated and improved through the use of ICTs. The language teachers need special training regarding the practices and implementation of ICTs. It is recommended that initiatives might be taken to equip university language teachers with modern methodology incorporating ICTs as focal area and efforts might be made to remove barriers regarding the training of language teachers and proper usage of ICTs.

Keywords: Information and communication technologies, internet assisted learning, teaching business English, online instructional content.

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Authors: Thanasit Suksutdhi

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This survey research aims to study the standard of service quality of food and beverage service staffs in hotel business by studying the service standard of three sample hotels, Siam Kempinski Hotel Bangkok, Four Seasons Resort Chiang Mai, and Banyan Tree Phuket. In order to find the international service standard of food and beverage service, triangular research, i.e. quantitative, qualitative, and survey were employed. In this research, questionnaires and in-depth interview were used for getting the information on the sequences and method of services. There were three parts of modified questionnaires to measure service quality and guest’s satisfaction including service facilities, attentiveness, responsibility, reliability, and circumspection. This study used sample random sampling to derive subjects with the return rate of the questionnaires was 70% or 280. Data were analyzed by SPSS to find arithmetic mean, SD, percentage, and comparison by t-test and One-way ANOVA. The results revealed that the service quality of the three hotels were in the international level which could create high satisfaction to the international customers. Recommendations for research implementations were to maintain the area of good service quality, and to improve some dimensions of service quality such as reliability. Training in service standard, product knowledge, and new technology for employees should be provided. Furthermore, in order to develop the service quality of the industry, training collaboration between hotel organization and educational institutions in food and beverage service should be considered.

Keywords: Service standard, food and beverage department, sequence of service, service method.

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Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

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The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural Language Processing (NLP) in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis.

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to prevent deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network. 

Keywords: Accident risks estimation, artificial neural network, deep learning, K-mean, road safety.

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Authors: Gaofetoge Lenetha, Malerato Moloi, Ntsoaki Malebo

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Microbial contamination of ready-to-eat foods and beverages sold by street vendors has become an important public health issue. In developing countries including South Africa, health risks related to such kinds of foods are thought to be common. Thus, this study assessed knowledge, attitude and practices of street food vendors. Street vendors in the city of Mangaung Metro were investigated in order to assess their knowledge, attitudes and handling practices. A semi-structured questionnaire and checklist were used in interviews to determine the status of the vending sites and associa. ted food-handling practices. Data was collected by means of a face-to-face interview. The majority of respondents were black females. Hundred percent (100%) of the participants did not have any food safety training. However, street vendors showed a positive attitude towards food safety. Despite the positive attitude, vendors showed some non-compliance when it comes to handling food. During the survey, it was also observed that the vending stalls lack basic infrastructures like toilets and potable water that is currently a major problem. This study indicates a need for improvements in the environmental conditions at these sites to prevent foodborne diseases. Moreover, based on the results observed food safety and food hygiene training or workshops for street vendors are highly recommended.

Keywords: Food hygiene, foodborne illnesses, food safety, street foods.

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Authors: G. Gürsel, K. H. Gülkesen, N. Zayim, A. Arifoğlu, O. Saka

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User satisfaction is one of the most used success indicators in the research of information system (IS). Literature shows user expectations have great influence on user satisfaction. Both expectation and satisfaction of users are important for Hospital Information Systems (HIS). Education, IS experience, age, attitude towards change, business title, sex and working unit of the hospital, are examined as the potential determinant of the medical users’ expectations. Data about medical user expectations are collected by the “Expectation Questionnaire” developed for this study. Expectation data are used for calculating the Expectation Meeting Ratio (EMR) with the evaluation framework also developed for this study. The internal consistencies of the answers to the questionnaire are measured by Cronbach´s Alpha coefficient. The multivariate analysis of medical user’s EMRs of HIS is performed by forward stepwise binary logistic regression analysis. Education and business title is appeared to be the determinants of expectations from HIS.

Keywords: Evaluation, Fuzzy Logic, Hospital Information System, User Expectation.

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Authors: Ion Smeureanu, Marian Dardala, Adriana Reveiu

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The new programming technologies allow for the creation of components which can be automatically or manually assembled to reach a new experience in knowledge understanding and mastering or in getting skills for a specific knowledge area. The project proposes an interactive framework that permits the creation, combination and utilization of components that are specific to mathematical training in high schools. The main framework-s objectives are: • authoring lessons by the teacher or the students; all they need are simple operating skills for Equation Editor (or something similar, or Latex); the rest are just drag & drop operations, inserting data into a grid, or navigating through menus • allowing sonorous presentations of mathematical texts and solving hints (easier understood by the students) • offering graphical representations of a mathematical function edited in Equation • storing of learning objects in a database • storing of predefined lessons (efficient for expressions and commands, the rest being calculations; allows a high compression) • viewing and/or modifying predefined lessons, according to the curricula The whole thing is focused on a mathematical expressions minicompiler, storing the code that will be later used for different purposes (tables, graphics, and optimisations). Programming technologies used. A Visual C# .NET implementation is proposed. New and innovative digital learning objects for mathematics will be developed; they are capable to interpret, contextualize and react depending on the architecture where they are assembled.

Keywords: Adaptor, automatic assembly learning component and user control.

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Authors: P. Prudtikul, S. Pathomsiri

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Most, if not all, public hospitals in Thailand have encountered a common problem regarding the increasing demand for medical services. The increasing number of patients causes so much strain on the hospital-s services, over-crowded, overloaded working hours, staff fatigue, medical error and long waiting time. This research studied the characteristics of operational processes of the medical care services at the medicine department in a large public university hospital. The research focuses on details regarding methods, procedures, processes, resources, and time management in overall processes. The simulation model is used as a tool to analyze the impact of various improvement strategies.

Keywords: Patient flow, medicine department, simulation, outpatient department.

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Authors: Y. Y. Su, K. T. Win, H. C. Chiu

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This study used Item Analysis, Exploratory Factor Analysis (EFA) and Reliability Analysis (Cronbach-s α value) to exam the Questions which selected by the Delphi method based on the issue of “Socio-technical system (STS)" and user-centered perspective. A structure questionnaire with seventy-four questions which could be categorized into nine dimensions (healthcare environment, organization behaviour, system quality, medical data quality, service quality, safety quality, user usage, user satisfaction, and organization net benefits) was provided to evaluate EMR of the Taiwanese healthcare environment.

Keywords: Instrument development, Reliability test, Validity test, Electronic Medical Record Evaluation.

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Authors: P. Maheshwari, M. Shapurkar

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The present research aimed at studying the awareness and attitudes of teachers towards inclusive education. The sample consisted of 60 teachers, teaching in the primary section (1st – 4th) of regular schools affiliated to the SSC board in Mumbai. Sample was selected by Multi-stage cluster sampling technique. A semi-structured self-constructed interview schedule and a self-constructed attitude scale was used to study the awareness of teachers about disability and Inclusive education, and their attitudes towards inclusive education respectively. Themes were extracted from the interview data and quantitative data was analyzed using SPSS package. Results revealed that teachers had some amount of awareness but an inadequate amount of information on disabilities and inclusive education. Disability to most (37) teachers meant “an inability to do something”. The difference between disability and handicap was stated by most as former being cognitive while handicap being physical in nature. With regard to Inclusive education, a large number (46) stated that they were unaware of the term and did not know what it meant. Majority (52) of them perceived maximum challenges for themselves in an inclusive set up, and emphasized on the role of teacher training courses in the area of providing knowledge (49) and training in teaching methodology (53). Although, 83.3% of teachers held a moderately positive attitude towards inclusive education, a large percentage (61.6%) of participants felt that being in inclusive set up would be very challenging for both children with special needs and without special needs. Though, most (49) of the teachers stated that children with special needs should be educated in regular classroom but they further clarified that only those should be in a regular classroom who have physical impairments of mild or moderate degree.

Keywords: Attitudes, awareness, inclusive education, teachers.

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Authors: Yazan M. Alatrash, Han-ok Kang, Hyun-gi Yoon, Shen Zhang, Juhyeon Yoon

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Flow coastdown phenomena are very important to secure nuclear fuel integrity during loss of off-site power accidents. In this study, primary coolant flow coastdown phenomena are investigated for the Jordan Research and Training Reactor (JRTR) using a simulation software package, Modular Modeling System (MMS). Two MMS models are built. The first one is a simple model to investigate the characteristics of the primary coolant pump only. The second one is a model for a simulation of the Primary Coolant System (PCS) loop, in which all the detailed design data of the JRTR PCS system are modeled, including the geometrical arrangement data. The same design data for a PCS pump are used for both models. Coastdown curves obtained from the two models are compared to study the PCS loop coolant inertia effect on a flow coastdown. Results showed that the loop coolant inertia effect is found to be small in the JRTR PCS loop, i.e., about one second increases in a coastdown half time required to halve the coolant flow rate. The effects of different flywheel inertia on the flow coastdown are also investigated. It is demonstrated that the coastdown half time increases with the flywheel inertia linearly. The designed coastdown half time is proved to be well above the design requirement for the fuel integrity.

Keywords: Flow Coastdown, Loop Coolant Inertia, Modeling, Research Reactor.

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Authors: Siau-Chuin Liew, Siau-Way Liew, Jasni Mohd Zain

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Digital watermarking in medical images can ensure the authenticity and integrity of the image. This design paper reviews some existing watermarking schemes and proposes a reversible tamper detection and recovery watermarking scheme. Watermark data from ROI (Region Of Interest) are stored in RONI (Region Of Non Interest). The embedded watermark allows tampering detection and tampered image recovery. The watermark is also reversible and data compression technique was used to allow higher embedding capacity.

Keywords: data compression, medical image, reversible, tamperdetection and recovery, watermark.

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Authors: Amudha Kadirvelu, Sunil Gurtu, Sivalal Sadasivan

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Pharmacology curriculum plays an integral role in medical education. Learning pharmacology to choose and prescribe drugs is a major challenge encountered by students. We developed pharmacology applied learning activities for first year medical students that included realistic clinical situations with escalating complications which required the students to analyze the situation and think critically to choose a safe drug. Tutor feedback was provided at the end of session. Evaluation was done to assess the students- level of interest and usefulness of the sessions in rational selection of drugs. Majority (98 %) of the students agreed that the session was an extremely useful learning exercise and agreed that similar sessions would help in rational selection of drugs. Applied learning sessions in the early years of medical program may promote deep learning and bridge the gap between pharmacology theory and clinical practice. Besides, it may also enhance safe prescribing skills.

Keywords: Medical education, pharmacology curriculum, applied learning, safe prescribing.

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Authors: M. Analoui, M. Fadavi Amiri

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The design of a pattern classifier includes an attempt to select, among a set of possible features, a minimum subset of weakly correlated features that better discriminate the pattern classes. This is usually a difficult task in practice, normally requiring the application of heuristic knowledge about the specific problem domain. The selection and quality of the features representing each pattern have a considerable bearing on the success of subsequent pattern classification. Feature extraction is the process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Many current feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and increasing classification efficiency, it does not necessarily reduce the number of features that must be measured since each new feature may be a linear combination of all of the features in the original pattern vector. In this paper a new approach is presented to feature extraction in which feature selection, feature extraction, and classifier training are performed simultaneously using a genetic algorithm. In this approach each feature value is first normalized by a linear equation, then scaled by the associated weight prior to training, testing, and classification. A knn classifier is used to evaluate each set of feature weights. The genetic algorithm optimizes a vector of feature weights, which are used to scale the individual features in the original pattern vectors in either a linear or a nonlinear fashion. By this approach, the number of features used in classifying can be finely reduced.

Keywords: Feature reduction, genetic algorithm, pattern classification, nearest neighbor rule classifiers (k-NNR).

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Authors: Chia-Jou Hsieh, Feng-Chuan Pan

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Oral health is particular important to the hospitalized patients with chronic schizophrenia for an extreme high potential of the respiratory infections. Due to the degeneration of physical capability, patients of this kind typically fall dependent in the activity of daily living (ADL). A very high percentage of patients had dental problems of which mostly could be easily avoid by easy regular tooth brushing. Purpose of the project is to develop a mechanism in helping the schizophrenia patients in rebuilding a tooth-cleaning habit. The project observed and evaluated the tooth-cleaning behavior of 100 male patients in a psychiatric hospital, and found the majority of them ignored such an activity in a three-month period of time. In the meantime, the primary care-givers were not aware or not convinced the importance of such a need of dental hygiene, and thus few if any tooth cleaning training or knowledge on dental hygiene were given to the patients. The project then developed a program based on the numerous observations and discussions. The improvement program included patients- group education, care-givers- training, and a tool-kit for tooth-brush holding was erected. The project launched with some incentive package. The outcomes were encouraging with 87% of the patients had rebuilt their tooth-brushing habits against previous 22%, and the tooth cleaning kits were 100% kept against 22% in the past. This project had significantly improved the oral health of the patients. The project, included the procedure and the tool-kit holder specific for this purpose, was a good examples for psychiatric hospitals.

Keywords: Schizophrenia, dental hygiene, tool-kit holder, health education

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Authors: Abd Aziz Bin Abd Shukor, Eftah Binti Moh Hj Abdullah

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This case study aims to identify teachers’ perception as regards integrity in School-Ba sed Assessment (PBS) practice. This descriptive study involved 9 teachers from 4 secondary schools in 3 districts in the state of Perak. The respondents had undergone an integrity in PBS Practice interview using a focused group discussion method. The overall findings showed that the teachers believed that integrity in PBS practice could be achieved by adjusting the teaching methods align with learning objectives and the students’ characteristics. Many teachers, parents and student did not understand the best practice of PBS. This would affect the integrity in PBS practice. Teachers did not emphasis the principles and ethics. Their integrity as an innovative public servant may also be affected with the frequently changing assessment system, lack of training and no prior action research. The analysis of findings showed that the teachers viewed that organizational integrity involving the integrity of PBS was difficult to be implemented based on the expectations determined by Malaysia Ministry of Education (KPM). A few elements which assisted in the achievement of PBS integrity were the training, students’ understanding, the parents’ understanding of PBS, environment (involving human resources such as support and appreciation and non-human resources such as technology infrastructure readiness and media). The implications of this study show that teachers, as the PBS implementers, have a strong influence on the integrity of PBS. However, the transformation of behavior involving PBS integrity among teachers requires the stabilisation of support and infrastructure in order to enable the teachers to implement PBS in an ethical manner.

Keywords: Assessment integrity, integrity, perception, school-based assessment.

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Authors: Ayman M. Mansour

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In this paper, we propose an intelligent system that is used for monitoring the health conditions of patients. Monitoring the health condition of patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The ability of making medical decisions, the quality of medical is expected to be improved.

Keywords: GSM, SMS, Patient, Monitoring system, Fuzzy Logic, Multi-agent system.

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Authors: H. Al-Khalaifa, A. Al-Nasser

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The viewpoint towards the use of drugs or vaccines against avian parasitic diseases is one of the most striking challenges in avian medical parasitology. This includes many difficulties associated with drug resistance and in developing prophylactic vaccines. In many instances, the potential success of a vaccination in controlling parasitic diseases in poultry is well-documented. However, some medical, technical and financial limitations are still paramount. On the other hand, chemotherapy is not very well-recommended due to a number of medical limitations. But in the absence of an effective vaccine, drugs are used against parasitic diseases. This paper sheds light on some the advantages and disadvantages of using vaccination and drugs in controlling parasitic diseases in poultry species. The usage of chemotherapeutic drugs is discussed with some examples. Then, more light will be shed on using vaccines as a potentially effective and promising control tool.

Keywords: Drugs, parasitology, poultry, vaccines.

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Authors: Shao-Hsia Chang, Nan-Ying Yu

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The objective of this study was to test how advanced digital technology enables a more effective training on the handwriting of children with handwriting deficit. This study implemented the graphomotor apparatuses to a computer-assisted instruction system. In a randomized controlled trial, the experiments for verifying the intervention effect were conducted. Forty two children with handwriting deficit were assigned to computer-assisted instruction, sensorimotor training or control (no intervention) group. Handwriting performance was measured using the Elementary reading/writing test and computerized handwriting evaluation before and after 6 weeks of intervention. Analysis of variance of change scores were conducted to show whether statistically significant difference across the three groups. Significant difference was found among three groups. Computer group shows significant difference from the other two groups. Significance was denoted in near-point, far-point copy, dictation test, and writing from phonetic symbols. Writing speed and mean stroke velocity in near-, far-point and short paragraph copy were found significantly difference among three groups. Computer group shows significant improvement from the other groups. For clinicians and school teachers, the results of this study provide a motor control based insight for the improvement of handwriting difficulties.

Keywords: Dysgraphia, computerized handwriting evaluation, sensorimotor program, computer assisted program.

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Authors: Parvinder S. Sandhu, Sandeep Khimta, Kiranpreet Kaur

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The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.

Keywords: Growing Neural Gas, data clustering, fault prediction.

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Authors: S.S.Mohanavalli, Sheila Anand

Abstract:

This paper proposes a novel architecture for At- Home medical care which enables senior citizens, patients with chronic ailments and patients requiring post- operative care to be remotely monitored in the comfort of their homes. This architecture is implemented using sensors and wireless networking for transmitting patient data to the hospitals, health- care centers for monitoring by medical professionals. Patients are equipped with sensors to measure their physiological parameters, like blood pressure, pulse rate etc. and a Wearable Data Acquisition Unit is used to transmit the patient sensor data. Medical professionals can be alerted to any abnormal variations in these values for diagnosis and suitable treatment. Security threats and challenges inherent to wireless communication and sensor network have been discussed and a security mechanism to ensure data confidentiality and source authentication has been proposed. Symmetric key algorithm AES has been used for encrypting the data and a patent-free, two-pass block cipher mode CCFB has been used for implementing semantic security.

Keywords: data confidentiality, integrity, remotemonitoring, source authentication

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

Abstract:

This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: Visual search, deep learning, convolutional neural network, machine learning.

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Authors: Abhinav Kumar, Raja Sekhar Bandaru, B Madhusudan Rao, Saket Kulkarni, Nilesh Ghatpande

Abstract:

This paper proposes an algorithm which automatically aligns and stitches the component medical images (fluoroscopic) with varying degrees of overlap into a single composite image. The alignment method is based on similarity measure between the component images. As applied here the technique is intensity based rather than feature based. It works well in domains where feature based methods have difficulty, yet more robust than traditional correlation. Component images are stitched together using the new triangular averaging based blending algorithm. The quality of the resultant image is tested for photometric inconsistencies and geometric misalignments. This method cannot correct rotational, scale and perspective artifacts.

Keywords: Histogram Matching, Image Alignment, ImageStitching, Medical Imaging.

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