Search results for: face recognition system

Authors: R. Botrugno, S Basyuni, G. Nugent, I. Jenkyn, A. Ferro, H. Bennett, C. Hjalmarsson, J. Chu, V. Santhanam

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This trainee led randomised controlled trial (RCT) aims to assess various outcomes for resorbable versus non-resorbable sutures for traumatic lacerations to the face. Within this trial of resorbable versus non-resorbable sutures for traumatic lacerations of the face (TORNFace), patient recruitment was facilitated by trainees who were employed at an NHS University Teaching Hospital in the United Kingdom. The trainees received appropriate training prior to recruiting patients for the trial. This included the completion of a national research e-learning module and face-to-face training that was provided locally. The locally delivered training provided an understanding of the eligibility criteria for the trial and the consent process. Existing trainee skills were utilised involving clinical photography to record baseline data and delivering the intervention based on the treatment arm selected. Eligible patients who required primary closure of traumatic lacerations of the face were randomised into one of two treatment arms. These comprised of resorbable (vicryl rapide) or non-resorbable sutures (ethilon). Primarily the cosmetic outcome was assessed. Secondary outcomes included: complications rates, health care economics, and patient-reported outcomes. Remote follow-up of recruited patients utilised photographs of the facial laceration which had received the intervention. These took place at 1 week, 3 months and 6 months post-intervention. This study aims to demonstrate an example of trainee-led research within the specialty of oral and maxillofacial surgery. The available data for the randomised controlled trial will also be presented.

Keywords: laceration, suture, trauma, trial

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Authors: Gülay Dalgıç, Gildis Tachir

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Architectural design studios are ambiencein where architecture design is realized as a palpable product in architectural education. In the design studios that the architect candidate will use in the design processthe information, the methods of approaching the design problem, the solution proposals, etc., are set uptogetherwith the studio coordinators. The architectural design process, on the other hand, is complex and uncertain.Candidate architects work in a process that starts with abstre and ill-defined problems. This process starts with the generation of alternative solutions with the help of representation tools, continues with the selection of the appropriate/satisfactory solution from these alternatives, and then ends with the creation of an acceptable design/result product. In the studio ambience, many designs and thought relationships are evaluated, the most important step is the early design phase. In the early design phase, the first steps of converting the information are taken, and converted information is used in the constitution of the first design decisions. This phase, which positively affects the progress of the design process and constitution of the final product, is complex and fuzzy than the other phases of the design process. In this context, the aim of the study is to investigate the effects of face-to-face learning model and e-learning model on the early design phase. In the study, the early design phase was defined by literature research. The data of the defined early design phase criteria were obtained with the feedback graphics created for the architect candidates who performed e-learning in the first year of architectural education and continued their education with the face-to-face learning model. The findings of the data were analyzed with the common graphics program. It is thought that this research will contribute to the establishment of a contemporary architectural design education model by reflecting the evaluation of the data and results on architectural education.

Keywords: education modeling, architecture education, design education, design process

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Authors: Amin Pashaye Amiri

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Freedom of information, according to which the public has a right to have access to government-held information, is largely considered as a tool for improving transparency and accountability in governments, and as a requirement of self-governance and good governance. So far, more than ninety countries have recognized citizens’ right to have access to public information. This recognition often took place through the adoption of an act referred to as “freedom of information act”, “access to public records act”, and so on. A freedom of information act typically imposes a positive obligation on a government to initially and regularly release certain public information, and also obliges it to provide individuals with information they request. Such an act usually allows governmental bodies to withhold information only when it falls within a limited number of exemptions enumerated in the act such as exemptions for protecting privacy of individuals and protecting national security. Some steps have been taken at the national and international level towards the recognition of freedom of information as a human right. Freedom of information was recognized in a few countries as a part of freedom of expression, and therefore, as a human right. Freedom of information was also recognized by some international bodies as a human right. The Inter-American Court of Human Rights ruled in 2006 that Article 13 of the American Convention on Human Rights, which concerns the human right to freedom of expression, protects the right of all people to request access to government information. The European Court of Human Rights has recently taken a considerable step towards recognizing freedom of information as a human right. However, in spite of the measures that have been taken, public access to government information is not yet widely accepted as an international human right. The paper will consider the degree to which freedom of information has been recognized as a human right, and study the possibility of widespread recognition of such a human right in the future. It will also examine the possible benefits of such recognition for the development of the human right to free expression.

Keywords: freedom of information, freedom of expression, human rights, government information

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Authors: Yaron Covo, Tamar Kofman, Shira Palti

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Over the recent decades, debates about the engagement of fans in football governance have focused on the club level and national level, emphasizing the significance of fans’ involvement in increasing the connection of clubs with the community, and in safeguarding the transparency, accountability, and clubs’ financial stability. This paper will offer a different conceptual justification for providing fans with access to decision-making processes in football. First, it will suggest that the participation of fans is necessary for addressing discriminatory practices against women in football stadiums. Second, it will argue that fans’ involvement in football governance is important not only at the club and national level but also at the global level, relying on the principles of Global Administrative Law. In contemporary men’s football, female fans face different forms of discrimination. Iranian women are still prohibited from attending football games at the domestic level; In Saudi Arabia, female fans are only permitted to enter designated family areas; Qatar – the host of the 2022 FIFA world cup – requires women to attend matches wearing modest clothing. Similarly, in Turkey, Lebanon, UAE, and Algeria, women face cultural barriers when attending men’s football games. In other countries, female fans suffer from subtle discrimination, including micro-aggressions, misogyny, sexism, and noninstitutionalized exclusion. Despite the vital role of fans in world football and the importance of football for many women’s lives, little has been done to address this problem. While FIFA recognizes that these discriminatory practices contradict its statutes, this recognition fails to materialize into meaningful change. This paper will argue that FIFA’s omission stems from two interrelated characteristics of world football: (1) the ultra-masculine nature of the game; (2) the insufficient recognition of fans’ significance. While fans have been given a voice in various football bodies on the domestic level, FIFA has yet to allow the representation of fans as stakeholders in world football governance. Since fans are a more heterogeneous group than players, the voices of those fans who do not fit the ultra-masculine model are not heard. Thus, by focusing mainly on male players, FIFA reproduces the hegemonic masculinity that feeds back into fan dynamics and marginalizes female fans. To rectify this problem, we will call on FIFA to provide fans and female fans in particular, with voice mechanisms and access to decision-making processes. In addition to its impact on the formation of fans’ identities, such a move will allow fans to demand better enforcement of existing anti-discrimination norms and new regulations to address their needs. The literature has yet to address the relationship between fans’ gender discrimination and global football governance. Building on Global Administrative Law scholarship and feminist theories, this paper will aim to fill this gap.

Keywords: fans, FIFA, football governance, gender discrimination, global administrative law, human rights

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Natalia Strobel, Jan Kratzer

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Achieving effective innovation is a complex task and during this process firms (especially SMEs) often face obstacles. However, research into obstacles to innovation focusing on SMEs is very scarce. In this study, we propose a theoretical framework for describing these obstacles to innovation and investigate their influence on the innovative performance of SMEs. Data were collected in 2013 through face-to-face interviews with executives of 49 technology SMEs from Germany. The semi-structured interviews were designed on the basis of scales for measuring innovativeness, financial/competitive performance and obstacles to innovation, next to purely open questions. We find that the internal obstacles lack the know-how, capacity overloading, unclear roles and tasks, as well as the external obstacle governmental bureaucracy negatively influence the innovative performance of SMEs. However, in contrast to prior findings this study shows that cooperation ties of firms might also negatively influence the innovative performance.

Keywords: innovation, innovation process, obstacles, SME

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Authors: Tuiana A. Aiusheeva, Sergey S. Tamozhnikov, Alexander E. Saprygin, Arina A. Antonenko, Valentina V. Stepanova, Natalia N. Tolstykh, Alexander N. Savostyanov

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Situation of choice is an important condition for the formation of essential character qualities of a child, such as being initiative, responsible, hard-working. We have studied the behavioral and EEG reactions in Russian schoolchildren during recognition of syntactic errors in emotionally colored sentences that describe the choice situation. Twenty healthy children (mean age 9,0±0,3 years, 12 boys, 8 girls) were examined. Forty sentences were selected for the experiment; the half of them contained a syntactic error. The experiment additionally had the hidden condition: 50% of the sentences described the children's own choice and were emotionally colored (positive or negative). The other 50% of the sentences described the forced-choice situation, also with positive or negative coloring. EEG were recorded during execution of error-recognition task. Reaction time and quality of syntactic error detection were chosen as behavioral measures. Event-related spectral perturbation (ERSP) was applied to characterize the oscillatory brain activity of children. There were two time-frequency intervals in EEG reactions: (1) 500-800 ms in the 3-7 Hz frequency range (theta synchronization) and (2) 500-1000 ms in the 8-12 Hz range (alpha desynchronization). We found out that behavioral and brain reactions in child brain during recognition of positive and negative sentences describing forced-choice situation did not have significant differences. Theta synchronization and alpha desynchronization were stronger during recognition of sentences with children's own choice, especially with negative coloring. Also, the quality and execution time of the task were higher for this types of sentences. The results of our study will be useful for improvement of teaching methods and diagnostics of children affective disorders.

Keywords: choice situation, electroencephalogram (EEG), emotionally colored sentences, schoolchildren

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

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Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Youhang Zhou, Weimin Zeng, Qi Xie

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Abstract: In order to solve the wear recognition problem of the machine tool guide surface, a new machine tool guide surface recognition method based on the radar-graph barycentre feature is presented in this paper. Firstly, the gray mean value, skewness, projection variance, flat degrees and kurtosis features of the guide surface image data are defined as primary characteristics. Secondly, data Visualization technology based on radar graph is used. The visual barycentre graphical feature is demonstrated based on the radar plot of multi-dimensional data. Thirdly, a classifier based on the support vector machine technology is used, the radar-graph barycentre feature and wear original feature are put into the classifier separately for classification and comparative analysis of classification and experiment results. The calculation and experimental results show that the method based on the radar-graph barycentre feature can detect the guide surface effectively.

Keywords: guide surface, wear defects, feature extraction, data visualization

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Authors: Edwin Foo, Woei Wen, Lui, Meijun Zhao, Shigeru Kuchii, Chin Sai Wong, Chung Sern Goh, Yi Hao He

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This presentation presents an elderly care and assistive social robot development work. We named this robot JOS and he is restricted to table top operation. JOS is designed to have a maximum volume of 3600 cm3 with its base restricted to 250 mm and his mission is to provide companion, assist and help the elderly. In order for JOS to accomplish his mission, he will be equipped with perception, reaction and cognition capability. His appearance will be not human like but more towards cute and approachable type. JOS will also be designed to be neutral gender. However, the robot will still have eyes, eyelid and a mouth. For his eyes and eyelids, they will be built entirely with Robotis Dynamixel AX18 motor. To realize this complex task, JOS will be also be equipped with micro-phone array, vision camera and Intel i5 NUC computer and a powered by a 12 V lithium battery that will be self-charging. His face is constructed using 1 motor each for the eyelid, 2 motors for the eyeballs, 3 motors for the neck mechanism and 1 motor for the lips movement. The vision senor will be house on JOS forehead and the microphone array will be somewhere below the mouth. For the vision system, Omron latest OKAO vision sensor is used. It is a compact and versatile sensor that is only 60mm by 40mm in size and operates with only 5V supply. In addition, OKAO vision sensor is capable of identifying the user and recognizing the expression of the user. With these functions, JOS is able to track and identify the user. If he cannot recognize the user, JOS will ask the user if he would want him to remember the user. If yes, JOS will store the user information together with the capture face image into a database. This will allow JOS to recognize the user the next time the user is with JOS. In addition, JOS is also able to interpret the mood of the user through the facial expression of the user. This will allow the robot to understand the user mood and behavior and react according. Machine learning will be later incorporated to learn the behavior of the user so as to understand the mood of the user and requirement better. For the speech system, Microsoft speech and grammar engine is used for the speech recognition. In order to use the speech engine, we need to build up a speech grammar database that captures the commonly used words by the elderly. This database is built from research journals and literature on elderly speech and also interviewing elderly what do they want to robot to assist them with. Using the result from the interview and research from journal, we are able to derive a set of common words the elderly frequently used to request for the help. It is from this set that we build up our grammar database. In situation where there is more than one person near JOS, he is able to identify the person who is talking to him through an in-house developed microphone array structure. In order to make the robot more interacting, we have also included the capability for the robot to express his emotion to the user through the facial expressions by changing the position and movement of the eyelids and mouth. All robot emotions will be in response to the user mood and request. Lastly, we are expecting to complete this phase of project and test it with elderly and also delirium patient by Feb 2015.

Keywords: social robot, vision, elderly care, machine learning

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Authors: Ria Ghosh, Soumendra Singh, Dipanjan Mukherjee, Susmita Mondal, Monojit Das, Uttam Pal, Aniruddha Adhikari, Aman Bhushan, Surajit Bose, Siddharth Sankar Bhattacharyya, Debasish Pal, Tanusri Saha-Dasgupta, Maitree Bhattacharyya, Debasis Bhattacharyya, Asim Kumar Mallick, Ranjan Das, Samir Kumar Pal

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Drug delivery to a target without adverse effects is one of the major criteria for clinical use. Herein, we have made an attempt to explore the delivery efficacy of SDS surfactant in a monomer and micellar stage during the delivery of the model drug, Toluidine Blue (TB) from the micellar cavity to DNA. Molecular recognition of pre-micellar SDS encapsulated TB with DNA occurs at a rate constant of k1 ~652 s 1. However, no significant release of encapsulated TB at micellar concentration was observed within the experimental time frame. This originated from the higher binding affinity of TB towards the nano-cavity of SDS at micellar concentration which does not allow the delivery of TB from the nano-cavity of SDS micelles to DNA. Thus, molecular recognition controls the extent of DNA recognition by TB which in turn modulates the rate of delivery of TB from SDS in a concentration-dependent manner.

Keywords: DNA, drug delivery, micelle, pre-micelle, SDS, toluidine blue

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Alisher Agzamov, Hanan Al Harbi

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BACKGROUND: The timely assessment and treatment of ICU Surgical and Medical Oncology patients is important for Oncology surgeons and Medical Oncologists and Intensivists. We hypothesized that the use of Robot Physician’s (RP - 7) ICU management and care in ICU can improve ICU physician rapid response to unstable ICU Oncology patients. METHODS: This is a prospective study using a before-after, cohort-control design to test the effectiveness of RP. We have used RP to make multidisciplinary ICU rounds in the ICU and for Emergency cases. Data concerning several aspects of the RP interaction including the latency of the response, the problem being treated, the intervention that was ordered, and the type of information gathered using the RP were documented. The effect of RP on ICU length of stay and cost was assessed. RESULTS: The use of RP was associated with a reduction in latency of attending physician face-to-face response for routine and urgent pages compared to conventional care (RP: 10.2 +/- 3.3 minutes vs conventional: 220 +/- 80 minutes). The response latencies to Oncology Emergency (8.0 +/- 2.8 vs 150 +/- 55 minutes) and for Respiratory Failure (12 +/- 04 vs 110 +/- 45 minutes) were reduced (P < .001), as was the LOS for patients with AML (5 days) and ARDS (10 day). There was an increase in ICU occupancy by 20 % compared with the prerobot era, and there was an ICU cost savings of KD2.5 million attributable to the use of RP. CONCLUSION: The use of RP enabled rapid face-to-face ICU Intensivist - physician response to unstable ICU Oncology patients and resulted in decreased ICU cost and LOS.

Keywords: robot physician, oncology patients, rp - 7 in icu management, cost and icu occupancy

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Authors: Lisbeth Amhag

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The aim of the study is to describe and analyze the design of mobile teaching for students collaborative learning in distance higher education with a focus on mobile technologies as online webinars (web-based seminars or conferencing) by using laptops, smart phones, or tablets. These multimedia tools can provide face-to-face interactions, recorded flipped classroom videos and parallel chat communications. The data collection consists of interviews with 22 students and observations of online face-to-face webinars, as well two surveys. Theoretically, the study joins the research tradition of Computer Supported Collaborative learning, CSCL, as well as Computer Self-Efficacy, CSE concerned with individuals’ media and information literacy. Important conclusions from the study demonstrated mobile interactions increased student centered learning. As the students were appreciating the working methods, they became more engaged and motivated. The mobile technology using among student also contributes to increased flexibility between space and place, as well as media and information literacy.

Keywords: computer self-efficacy, computer supported collaborative learning, distance and open learning, educational design and technologies, media and information literacy, mobile learning

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: Rafikoddin Kazi

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Almost all the major religions of the world condemn the transactions based on interest which promotes self-centered and materialistic thinking. Still, it is amazing to note that it has become the tradition of transaction at world level hence it is called traditional financial system. The main feature of this system is that it considers economic aspects of the transaction only. This system supports the economic development and not the welfare of humankind. However, it is worth mentioning the fact that, except Islamic financial system no other financial system stood in front of it as a viable alternative system. Although many countries have tried to create financial infrastructure and system, still the Malaysian Islamic financial system has got its own peculiarity. It has made tremendous progress in creating sound Islamic Financial system. However, the historical aspect of this country which has passed through Islamic and traditional financial system has got its own advantages and disadvantages. The advantageous factor is that, despite having mix and heterogeneous culture, it has succeeded in creating Islamic Financial System based on the dual legal system to satisfy the needs of multi-cultural factors. This fact has proved that Islamic Financial System does not need purely Muslim population. However, due to adoption of the dual legal system, several legal issues have been taken place. According to this system, the application of Islamic Law has been limited only up to some family and religious matters. The rest of the matters are being dealt with under the traditional laws, the principles and practices of which are different from that of the Islamic Legal System. The matter becomes all the more complicated when the cases are partially or simultaneously concerned with traditional vis-à-vis Islamic Laws as it requires expertise in both the legal systems. However, the educational principles and systems are different in respect of both the systems. To face this problem, Shariah Advisory Council has been established. But the Multiplicity of Shariah authorities without judicial power has created confusion at various levels. Therefore, some experts have stressed the need for improving, empowering the Islamic financial, legal system to make it more integrated and holistic. In view of the above, an endeavor has been made in this paper to throw some light on the matters related to the adoption of the dual legal system. The paper is conceptual in nature and the method adopted is the intensive survey of literature thereby all the information has been gathered from the secondary sources.

Keywords: Islamic financial system, Islamic legal system, Islamic capital market (ICM) , traditional financial system

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Authors: Mojtaba Aghajari, Alireza Aghasi

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The first challenge which the current research faced has been the identification or determination of the level of knowledge in Isfahan public transportation corporation, and the second challenge has been the recognition and choice of a proper approach for the instructional system design. Responding these two challenges will present an appropriate model of instructional system design. In order to respond the first challenge or question, Nonaka and Takeuchi KM model has been utilized due to its universality among the 26 models proposed so far. The statistical population of this research included 2200 people, among which 200 persons were chosen as the sample of the research by the use of Morgan’s method. The data gathering has been carried out by the means of a questionnaire based on Nonaka and Takeuchi KM model, analysis of which has been done by SPSS program. The output of this questionnaire, yielding the point of 1.96 (out of 5 points), revealed that the general condition of Isfahan public transportation corporation is weak concerning its being knowledge-centered. After placing this output on Jonassen’s continuum, it was revealed that the appropriate approach for instructional system design is the system (or behavioral) approach. Accordingly, different steps of the general model of ADDIE, which covers all of the ISO10015 standards, were adopted in the act of designing. Such process in Isfahan public transportation corporation was designed and divided into three main steps, including: instructional designing and planning, instructional course planning, determination of the evaluation and the effectiveness of the instructional courses.

Keywords: instructional system design, system approach, knowledge management, employees

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Authors: Teagan Fink, Lynn Chong, Michael Hii, Brett Knowles

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Background: Telemedicine is a rapidly advancing field providing healthcare to patients at a distance from their treating clinician. There is a paucity of high-quality evidence detailing the safety and acceptability of telemedicine for postoperative outpatient follow-up. This randomized controlled trial – conducted prior to the COVID 19 pandemic – aimed to assess patient satisfaction and safety (as determined by readmission, reoperation and complication rates) of telephone compared to face-to-face clinic follow-up after uncomplicated general surgical procedures. Methods: Patients following uncomplicated laparoscopic appendicectomy or cholecystectomy and laparoscopic or open umbilical or inguinal hernia repairs were randomized to a telephone or face-to-face outpatient clinic follow-up. Data points including patient demographics, perioperative details and postoperative outcomes (eg. wound healing complications, pain scores, unplanned readmission to hospital and return to daily activities) were compared between groups. Patients also completed a Likert patient satisfaction survey following their consultation. Results: 103 patients were recruited over a 12-month period (21 laparoscopic appendicectomies, 65 laparoscopic cholecystectomies, nine open umbilical hernia repairs, six laparoscopic inguinal hernia repairs and two laparoscopic umbilical hernia repairs). Baseline patient demographics and operative interventions were the same in both groups. Patient or clinician-reported concerns on postoperative pain, use of analgesia, wound healing complications and return to daily activities at clinic follow-up were not significantly different between the two groups. Of the 58 patients randomized to the telemedicine arm, 40% reported high and 60% reported very high patient satisfaction. Telemedicine clinic mean consultation times were significantly shorter than face-to-face consultation times (telemedicine 10.3 +/- 7.2 minutes, face-to-face 19.2 +/- 23.8 minutes, p-value = 0.014). Rates of failing to attend clinic were not significantly different (telemedicine 3%, control 6%). There was no increased rate of postoperative complications in patients followed up by telemedicine compared to in-person. There were no unplanned readmissions, return to theatre, or mortalities in this study. Conclusion: Telemedicine follow-up of patients undergoing uncomplicated general surgery is safe and does not result in any missed diagnosis or higher rates of complications. Telemedicine provides high patient satisfaction and steps to implement this modality in inpatient care should be undertaken.

Keywords: general surgery, telemedicine, patient satisfaction, patient safety

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Authors: Sean W. T. Bayly, Daniel Glover, Don Horrell, Simon Horrocks, Barnes Callum, Stuart Gibson, Mac Misuira

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We assess suitability of recent, ∼7B parameter, instruction-tuned Language Models Mistral-v0.3, Llama-3, and Phi-3, for Generative Named Entity Recognition (GNER). Our proposed Multi-Level Information Retrieval method achieves notable improvements over finetuned entity-level and sentence-level methods. We consider recent developments at the cross roads of prompt engineering and Retrieval Augmented Generation (RAG), such as EmotionPrompt. We conclude that language models directed toward this task are highly capable when distinguishing between positive classes (precision). However, smaller models seem to struggle to find all entities (recall). Poorly defined classes such as ”Miscellaneous” exhibit substantial declines in performance, likely due to the ambiguity it introduces to the prompt. This is partially resolved through a self verification method using engineered prompts containing knowledge of the stricter class definitions, particularly in areas where their boundaries are in danger of overlapping, such as the conflation between the location ”Britain” and the nationality ”British”. Finally, we explore correlations between model performance on the GNER task with performance on relevant academic benchmarks.

Keywords: generative named entity recognition, information retrieval, lightweight artificial intelligence, prompt engineering, personal information identification, retrieval augmented generation, self verification

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Authors: Megan Weisbart

Abstract:

Background/Significance: The Intensive Care Unit (ICU) environment contributes to nurse burnout. Burnout costs include decreased employee compassion, missed workdays, worse patient outcomes, diminished job performance, high turnover, and higher organizational cost. Meaningful recognition, nurturing of interpersonal connections, and mindfulness-based interventions are associated with decreased burnout. The purpose of this quality improvement project was to decrease Neonatal ICU (NICU) nurse burnout using a Wellness Bundle that fosters meaningful recognition, interpersonal connections and includes mindfulness-based interventions. Methods: The Professional Quality of Life Scale Version 5 (ProQOL5) was used to measure burnout before Wellness Bundle implementation, after six months, and will be given yearly for three years. Meaningful recognition bundle items include Online submission and posting of staff shoutouts, recognition events, Nurses Week and Unit Practice Council member gifts, and an employee recognition program. Fostering of interpersonal connections bundle items include: Monthly staff games with prizes, social events, raffle fundraisers, unit blog, unit wellness basket, and a wellness resource sheet. Quick coherence techniques were implemented at staff meetings and huddles as a mindfulness-based intervention. Findings: The mean baseline burnout score of 14 NICU nurses was 20.71 (low burnout). The baseline range was 13-28, with 11 nurses experiencing low burnout, three nurses experiencing moderate burnout, and zero nurses experiencing high burnout. After six months of the Wellness Bundle Implementation, the mean burnout score of 39 NICU nurses was 22.28 (low burnout). The range was 14-31, with 22 nurses experiencing low burnout, 17 nurses experiencing moderate burnout, and zero nurses experiencing high burnout. Conclusion: A NICU Wellness Bundle that incorporated meaningful recognition, fostering of interpersonal connections, and mindfulness-based activities was implemented to improve work environments and decrease nurse burnout. Participation bias and low baseline response rate may have affected the reliability of the data and necessitate another comparative measure of burnout in one year.

Keywords: burnout, NICU, nurse, wellness

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Authors: Subir Gupta, Subhas Ganguly

Abstract:

In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Khaled Ben Oualid Medani, Samir Sayah

Abstract:

The Optimal Reactive Power Dispatch (ORPD) problem has been solved and analysed usually in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, power system analysis, real power loss minimization, contingency condition, metaheuristic technique, whale optimization algorithm

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Authors: Hong Dongchen, Chen Qiuxiao, Wu Shuang

Abstract:

Systematic science reveals the complex nonlinear mechanisms of behaviour in urban system. However, in China, when the current city planners face with the system, most of them are still taking simple linear thinking to consider the open complex giant system. This paper introduces the hyper-cycle theory, which is one of the basis theories of systematic science, based on the analysis of the reasons why the current urban planning failed, and proposals for optimization ideas that urban planning compilation should change, from controlling quantitative to the changes of relationship, from blueprint planning to progressive planning based on the nonlinear characteristics and from management control to dynamically monitor feedback.

Keywords: systematic science, hyper-cycle theory, urban planning, urban management

Procedia PDF Downloads 397

Authors: Eti Gilad, Shosh Millet

Abstract:

In light of the technological development and its introduction into the field of education, an online course was designed in parallel to the 'conventional' course for teaching the ''Qualitative Research Methods''. This course aimed to characterize learning-teaching processes in a 'Qualitative Research Methods' course studied in two different frameworks. Moreover its objective was to explore the difference between the culture of a physical learning environment and that of online learning. The research monitored four learner groups, a total of 72 students, for two years, two groups from the two course frameworks each year. The courses were obligatory for M.Ed. students at an academic college of education and were given by one female-lecturer. The research was conducted in the qualitative method as a case study in order to attain insights about occurrences in the actual contexts and sites in which they transpire. The research tools were open-ended questionnaire and reflections in the form of vignettes (meaningful short pictures) to all students as well as an interview with the lecturer. The tools facilitated not only triangulation but also collecting data consisting of voices and pictures of teaching and learning. The most prominent findings are: differences between the two courses in the change features of the learning environment culture for the acquisition of contents and qualitative research tools. They were manifested by teaching methods, illustration aids, lecturer's profile and students' profile.

Keywords: face to face course, online course, qualitative research, vignettes

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Authors: Chia-Feng Yen, Shyang-Woei Lin

Abstract:

Background: In Taiwan, people with disability can obtain national social welfare services after evaluation. All subsidies and services in- kind are pronounced in People with Disabilities Rights Protection Act. The new disability eligibility determination system base on ICF has carried out five years in Taiwan. There were no systematic outcomes to discuss the relationships between the evaluation results of activity and participation functioning (AP functioning) and ratification of social services for people with disability. The decision-making of welfare resources allocation is in local government, so the ratification could be affected by resource variations in every area (local governments). The purposes of this study are to compare the ratification rate between different areas (the equity of allocation), and to understand the ratification of social services for people with disability after needs assessment stage that can help to predict the resources allocation for local governments in the further. Methods: A cross-sectional study was used, and the data came from Disability Eligibility Determination System in Taiwan between 2013/11/04-2015/01/12. All samples were evaluated by FUNDES-adult version 7th and they all above 18 years old. The samples were collected face to face by physicians and AP evaluators. Result: In the needs assessment stage, the welfare ratification rates are significant differences between these local governments for the samples with the similar impairment and AP functioning.

Keywords: allocation, activity and participation, people with disability, justice

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Authors: Adam Johnbull

Abstract:

The paper discusses ICT in Education as a quest for quality learning in the 21st century. Education is the key that unlock the door to development, without adequate education of the citizenry, the development of a nation becomes a sham. Information Communication Technologies (ICTs) has revolutionized the way people work today and are now transforming education systems. As a result, if schools train children in yesterday’s skills and technologies they may not be effective and fit in tomorrow’s world. This is a sufficient reason for ICT’s to win global recognition and attention and thus ensure desire quality in our school system. Thus, the purpose of the paper is to discuss amongst others, what is ICT. The roles of ICT’s in education, limitation and key challenges of integrating ICT to education in the enhancement of student learning and experiences in other to encourage policy makers, school administrators and teachers pay the required attention to integrate this technology in the education system. The paper concludes that regardless of all the limitation characterizing it. ICT benefit education system to provide quality education in the 21st century.

Keywords: ICTs, quest, information, global, sham, century

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Authors: Samantha Vargas-Alfonso

Abstract:

The phenomenon of migration has been long-recorded since ancient history but never has mobility in huge numbers been so rapid and constant than that of the present. A significant portion of these migrants move for the promise of better economic subsistence by finding employment in foreign lands; while there are local and international instruments to protect these migrant workers, they still face human rights violations amongst other hurdles in integrating themselves into their host country. This research aims to look at the occurrence of Passport Confiscation for Filipino migrant workers (blue-collar workers) who are situated in Saudi Arabia. In addition to this, the study will look at the Kafala System which GCC countries practice regulating their foreign employees. The research attempts to prove that international conventions lack power in constraining the occurrence of passport confiscation and that while the kafala system exists, there is very little opportunity to address this issue.

Keywords: kafala, labor, migration, passport

Procedia PDF Downloads 447

Authors: Alisher Agzamov, Hanan Al Harbi

Abstract:

BACKGROUND: The timely assessment and treatment of ICU Surgical and Medical Oncology patients is important for Oncology surgeons and Medical Oncologists and Intensivists (1). We hypothesized that the use of Robot Physician’s (RP - 7) ICU management and care in ICU can improve ICU physician rapid response to unstable ICU Oncology patients. METHODS: This is a prospective study of 1501 oncology patients using a before-after, cohort-control design to test the effectiveness of RP. We have used RP to make multidisciplinary ICU rounds in the ICU and for Emergency cases. Data concerning several aspects of the RP interaction, including the latency of the response, the problem being treated, the intervention that was ordered, and the type of information gathered using the RP, were documented. The effect of RP on ICU length of stay and cost was assessed. RESULTS: The use of RP was associated with a reduction in latency of attending physician face-to-face response for routine and urgent pages compared to conventional care (RP: 10.2 +/- 3.3 minutes vs conventional: 210 +/- 40 minutes). The response latencies to Oncology Emergency (8.0 +/- 2.8 vs 140 +/- 35 minutes) and for Respiratory Failure (12 +/- 04 vs 110 +/- 45 minutes) were reduced (P < .001), as was the LOS for oncology patients (5 days) and ARDS (10 day). There was an increase in ICU occupancy by 29 % compared with the prerobot era, and there was an ICU cost savings of KD2.2 million attributable to the use of RP. CONCLUSION: The use of RP enabled rapid face-to-face ICU Intensivist - physician response to unstable ICU Oncology patients and resulted in decreased ICU cost and LOS.

Keywords: robot physician, oncology patients, icu management and care, cost and icu occupancy

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

Abstract:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

Procedia PDF Downloads 105