Search results for: the health improvement network (THIN)

Authors: Muhammad Abdullah Arafat, Nahrin Nowrose

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Wireless charging of electric vehicles is becoming more and more attractive as large amount of power can now be transferred to a reasonable distance using magnetic resonance coupling method. However, proper tuning of the compensation network is required to achieve maximum power transmission. Due to the variation of coil distance from the nominal value as a result of change in tire condition, change in weight or uneven road condition, the tuning of the compensation network has become challenging. In this paper, a tuning method has been described to determine the optimum values of the compensation network in order to maximize the average output power. The simulation results show that 5.2 percent increase in average output power is obtained for 10 percent variation in coupling coefficient using the optimum values without the need of additional space and electro-mechanical components. The proposed method is applicable to both static and dynamic charging of electric vehicles.

Keywords: coupling coefficient, electric vehicles, magnetic resonance coupling, tuning capacitor, wireless power transfer

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Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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Authors: Kaddi Mohammed, Benahmed Khelifa D. Benatiallah

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A sensor network consists of a large number of sensors deployed in areas to monitor and communicate with each other through a wireless medium. The collected routing data in the network consumes most of the energy of the sensor nodes. For this purpose, multiple routing approaches have been proposed to conserve energy resource at the sensors and to overcome the challenges of its limitation. In this work, we propose a new low energy consumption routing protocol for wireless sensor networks based on a meta-heuristic methods. Our protocol is to operate more fairly energy when routing captured data to the base station.

Keywords: WSN, routing, energy, heuristic

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Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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Authors: Andrzej Szewczak

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Study of the effect of high temperatures on polymer coatings represents an important field of research of their properties. Polymers, as materials with numerous features (chemical resistance, ease of processing and recycling, corrosion resistance, low density and weight) are currently the most widely used modern building materials, among others in the resin concrete, plastic parts, and hydrophobic coatings. Unfortunately, the polymers have also disadvantages, one of which decides about their usage - low resistance to high temperatures and brittleness. This applies in particular thin and flexible polymeric coatings applied to other materials, such a steel and concrete, which degrade under varying thermal conditions. Research about improvement of this state includes methods of modification of the polymer composition, structure, conditioning conditions, and the polymerization reaction. At present, ways are sought to reflect the actual environmental conditions, in which the coating will be operating after it has been applied to other material. These studies are difficult because of the need for adopting a proper model of the polymer operation and the determination of phenomena occurring at the time of temperature fluctuations. For this reason, alternative methods are being developed, taking into account the rapid modeling and the simulation of the actual operating conditions of polymeric coating’s materials in real conditions. The nature of a duration is typical for the temperature influence in the environment. Studies typically involve the measurement of variation one or more physical and mechanical properties of such coating in time. Based on these results it is possible to determine the effects of temperature loading and develop methods affecting in the improvement of coatings’ properties. This paper contains a description of the stability studies of silicone coatings deposited on the surface of a ceramic brick. The brick’s surface was hydrophobized by two types of inorganic polymers: nano-polymer preparation based on dialkyl siloxanes (Series 1 - 5) and an aqueous solution of the silicon (series 6 - 10). In order to enhance the stability of the film formed on the brick’s surface and immunize it to variable temperature and humidity loading, the nano silica was added to the polymer. The right combination of the polymer liquid phase and the solid phase of nano silica was obtained by disintegration of the mixture by the sonification. The changes of viscosity and surface tension of polymers were defined, which are the basic rheological parameters affecting the state and the durability of the polymer coating. The coatings created on the brick’s surfaces were then subjected to a temperature loading of 100° C and moisture by total immersion in water, in order to determine any water absorption changes caused by damages and the degradation of the polymer film. The effect of moisture and temperature was determined by measurement (at specified number of cycles) of changes in the surface hardness (using a Vickers’ method) and the absorption of individual samples. As a result, on the basis of the obtained results, the degradation process of polymer coatings related to their durability changes in time was determined.

Keywords: silicones, siloxanes, surface hardness, temperature, water absorption

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Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

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Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas

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Authors: Toni Buterin, Robert Doričić

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Mainstream bioethics, narrowed down mainly to human medicine and research, can hardly be expected to efficiently face modern challenges related to environmental issues. Departing from the interpretation of "European Bioethics" as a discipline considering ethical duties not only toward fellow humans, but to all living beings, this paper presents the results of a study conducted in three communities in Croatian Northern Adriatic region, selected for their recent experience of ecological threats (Labin – thermo-electric power plant; Bakar – cokery), or representing a highly-valuable and vulnerable natural insular pocket (Mali Lošinj – health tourism, dolphin wildlife refuge, fragrant gardens programme, etc.). After targeted workshops and interviews had been organised in those communities, the results of the obtained insights were combined with experts' opinion and a list of around hundred “bioethical standards” was formed. "Bioethical standards" represent a set of principles and measures of the correct attitude of people towards their own health, animals, plants, and the eco-system as a whole. "Bioethical standards" charter might improve the level of local community environmental consciousness, and provide direct guidance for its sustainable development (including its tourism-advertising ace card). The present paper discusses the standards' potential benefits and some implementational risks.

Keywords: bioethical standards, croatia, European bioethics, local communities

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Authors: Hsin-Yi Lo, Huang-Ju Jiun, Yu-Chiao Chu

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Hemodynamic monitoring is an important in the intensive care unit. Advances in medical technology in recent years, more diversification of intensive care equipment, there are many kinds of instruments available for monitoring of hemodynamics, Edwards Lifesciences Hemodynamic Monitoring (FloTrac) is one of them. The recent medical safety incidents in parameters were changed, nurses have not to notify doctor in time, therefore, it is hoped to analyze the current problems and find effective improvement strategies. In August 2021, the survey found that only 74.0% of FloTrac correctness of operation, reasons include lack of education, the operation manual is difficulty read, lack of audit mechanism, nurse doesn't know those numerical changes need to notify doctor, work busy omission, unfamiliar with operation and have many nursing records then omissions. Improvement methods include planning professional nurse education, formulate the secret arts of FloTrac, enacting an audit mechanism, establish FloTrac action learning, make「follow the sun」care map, hold simulated training and establish monitoring data automatically upload nursing records. After improvement, FloTrac correctness of operation increased to 98.8%. The results are good, implement to the ICU of the hospital.

Keywords: hemodynamic monitoring, edwards lifesciences hemodynamic monitoring, multiple strategies, intensive care

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Authors: Valerie Isaak

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This study examines the effectiveness of an intervention program aimed at enhancing a unit-level safety climate as a way to minimize the risk of employees being injured by patient violence. The intervention program conducted in maximum security units in one of the psychiatric hospitals in Israel included a three day workshop. Safety climate was examined before and after the implementation of the intervention. We also collected data regarding incidents involving patient violence. Six months after the intervention a significant improvement in employees’ perceptions regarding management’s commitment to safety were found as well as a marginally significant improvement in communication concerning safety issues. Our research shows that an intervention program aimed at enhancing a safety climate is associated with a decrease in the number of aggressive incidents. We conclude that such an intervention program is likely to return the sense of safety and reduce the scope of violence.

Keywords: violence, intervention, safety climate, performance, public sector

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Authors: Yudhajit Datta

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Will is a phenomenon that has puzzled humanity for a long time. It is a belief that Will Power of an individual affects the success achieved by an individual in life. It is thought that a person endowed with great will power can overcome even the most crippling setbacks of life while a person with a weak will cannot make the most of life even the greatest assets. Behavioral aspects of the human experience such as will are rarely subjected to quantitative study owing to the numerous uncontrollable parameters involved. This work is an attempt to subject the phenomena of will to the test of an artificial neural network. The claim being tested is that will power of an individual largely determines success achieved in life. In the study, an attempt is made to incorporate the behavioral phenomenon of will into a computational model using data pertaining to the success of individuals obtained from an experiment. A neural network is to be trained using data based upon part of the model, and subsequently used to make predictions regarding will corresponding to data points of success. If the prediction is in agreement with the model values, the model is to be retained as a candidate. Ultimately, the best-fit model from among the many different candidates is to be selected, and used for studying the correlation between success and will.

Keywords: will power, will, success, apathy factor, random factor, characteristic function, life story

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Li Shuping, Shu Huaping, Yi Chaofan, Tao Jiang

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Equestrian practice is often considered having a unique effect on improving symptoms in children with autism. This study evaluated and measured the changes in daily behavior, morphological, physical function, and fitness indexes of two group children with autism by means of 12 weeks of equestrian and basketball exercises. 19 clinically diagnosed children with moderate/mild autism were randomly divided into equestrian group (9 children, age=10.11±1.90y) and basketball group (10 children, age=10.70±2.16y). Both the equestrian and basketball groups practiced twice a week for 45 to 60 minutes each time. Three scales, the Autism Behavior Checklist (ABC), the Childhood Autism Rating Scale (CARS) and the Clancy Autism Behavior Scale (CABS) were used to assess their human behavior and psychology. Four morphological, seven physical function and fitness indicators were measured to evaluate the effects of the two exercises on the children’s body. The evaluations were taken by every four weeks ( pre-exercise, the 4th week, the 8th week and 12th week (post exercise). The result showed that the total scores of ABC, CARS and CABS, the dimension scores of ABC on the somatic motor, language and life self-care obtained after exercise were significantly lower than those obtained before 12 week exercises in both groups. The ABC feeling dimension scores of equestrian group and ABC communication dimension score of basketball group were significantly lower,and The upper arm circumference, sitting forward flexion, 40 second sit-up, 15s lateral jump, vital capacity, and single foot standing of both groups were significantly higher than that of before exercise.. The BMI of equestrian group was significantly reduced. The handgrip strength of basketball group was significantly increased. In conclusion, both types of exercises could improve daily behavior, morphological, physical function, and fitness indexes of the children with autism. However, the behavioral psychological scores, body morphology and function indicators and time points were different in the middle and back of the two interventions.But the indicators and the timing of the improvement were different. To the group of equestrian, the improvement of the flexibility occurred at week 4, the improvement of the sensory perception, control and use their own body, and promote the development of core strength endurance, coordination and cardiopulmonary function occurred at week 8，and the improvement of core strength endurance, coordination and cardiopulmonary function occurred at week 12. To the group of basketball, the improvement of the hand strength, balance, flexibility and cardiopulmonary function occurred at week 4, the improvement of the self-care ability and language expression ability, and core strength endurance and coordination occurred at week 8, the improvement of the control and use of their own body and social interaction ability occurred at week 12. In comparison of the exercise effects, the equestrian exercise improved the physical control and application ability appeared earlier than that of basketball group. Basketball exercise improved the language expression ability, self-care ability, balance ability and cardiopulmonary function of autistic children appeared earlier than that of equestrian group.

Keywords: intervention, children with autism, equestrain, basketball

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Authors: Muhammad Rehan Usman, Muhammad Arslan Usman, Soo Young Shin

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The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment.

Keywords: frame freezing, mean opinion score, objective assessment, subjective evaluation

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Authors: Michele L. Tilstra, Tiffany J. Peets

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Interprofessional collaboration in behavioral healthcare education is increasingly recognized for its value in training students to address diverse client needs. While interprofessional education (IPE) is well-documented in occupational therapy education to address physical health, limited research exists on collaboration with counselors to address mental health concerns and the psychosocial needs of individuals receiving care. Counseling education literature primarily examines the collaboration of counseling students with psychiatrists, psychologists, social workers, and marriage and family therapists. This pretest/posttest survey research study explored changes in attitudes toward interprofessional teams among 56 Master of Occupational Therapy (MOT) (n = 42) and Counseling and Human Development (CHD) (n = 14) students participating in the Counselors and Occupational Therapists Professionally Engaged in the Community (COPE) program. The COPE program was designed to strengthen the behavioral health workforce in high-need and high-demand areas. Students accepted into the COPE program were divided into small MOT/CHD groups to complete multiple interprofessional multicultural learning modules using videos, case studies, and online discussion board posts. The online modules encouraged reflection on various behavioral healthcare roles, benefits of team-based care, cultural humility, current mental health challenges, personal biases, power imbalances, and advocacy for underserved populations. Using the Student Perceptions of Interprofessional Clinical Education- Revision 2 (SPICE-R2) scale, students completed pretest and posttest surveys using a 5-point Likert scale (Strongly Agree = 5 to Strongly Disagree = 1) to evaluate their attitudes toward interprofessional teamwork and collaboration. The SPICE-R2 measured three different factors: interprofessional teamwork and team-based practice (Team), roles/responsibilities for collaborative practice (Roles), and patient outcomes from collaborative practice (Outcomes). The mean total scores for all students improved from 4.25 (pretest) to 4.43 (posttest), Team from 4.66 to 4.58, Roles from 3.88 to 4.30, and Outcomes from 4.08 to 4.36. A paired t-test analysis for the total mean scores resulted in a t-statistic of 2.54, which exceeded both one-tail and two-tail critical values, indicating statistical significance (p = .001). When the factors of the SPICE-R2 were analyzed separately, only the Roles (t Stat=4.08, p =.0001) and Outcomes (t Stat=3.13, p = .002) were statistically significant. The item ‘I understand the roles of other health professionals’ showed the most improvement from a mean score for all students of 3.76 (pretest) to 4.46 (posttest). The significant improvement in students' attitudes toward interprofessional teams suggests that the unique integration of OT and CHD students in the COPE program effectively develops a better understanding of the collaborative roles necessary for holistic client care. These results support the importance of IPE through structured, engaging interprofessional experiences. These experiences are essential for enhancing students' readiness for collaborative practice and align with accreditation standards requiring interprofessional education in OT and CHD programs to prepare practitioners for team-based care. The findings contribute to the growing body of evidence supporting the integration of IPE in behavioral healthcare curricula to improve holistic client care and encourage students to engage in collaborative practice across healthcare settings.

Keywords: behavioral healthcare, counseling education, interprofessional education, mental health education, occupational therapy education

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Authors: Ayman M. Mansour, Bilal Hawashin, Hesham Alsalem

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Faster delivery of laboratory test results is one of the most noticeable signs of good laboratory service and is often used as a key performance indicator of laboratory performance. Despite the availability of technology, the delivery time of clinical laboratory test results continues to be a cause of customer dissatisfaction which makes patients feel frustrated and they became careless to get their laboratory test results. The Medical Clinical Laboratory test results are highly sensitive and could harm patients especially with the severe case if they deliver in wrong time. Such results affect the treatment done by physicians if arrived at correct time efforts should, therefore, be made to ensure faster delivery of lab test results by utilizing new trusted, Robust and fast system. In this paper, we proposed a distributed Multi-Agent System to enhance and faster the process of laboratory test results delivery using SMS. The developed system relies on SMS messages because of the wide availability of GSM network comparing to the other network. The software provides the capability of knowledge sharing between different units and different laboratory medical centers. The system was built using java programming. To implement the proposed system we had many possible techniques. One of these is to use the peer-to-peer (P2P) model, where all the peers are treated equally and the service is distributed among all the peers of the network. However, for the pure P2P model, it is difficult to maintain the coherence of the network, discover new peers and ensure security. Also, security is a quite important issue since each node is allowed to join the network without any control mechanism. We thus take the hybrid P2P model, a model between the Client/Server model and the pure P2P model using GSM technology through SMS messages. This model satisfies our need. A GUI has been developed to provide the laboratory staff with the simple and easy way to interact with the system. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: multi-agent system, delivery process, GSM technology, clinical laboratory results

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Strahinja Kovačević, Jelena Vladić, Senka Vidović, Zoran Zeković, Lidija Jevrić, Sanja Podunavac Kuzmanović

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Supercritical extracts of highly valuated medicinal plant Satureja montana were prepared by application of supercritical carbon dioxide extraction in the carbon dioxide pressure range from 125 to 350 bar and temperature range from 40 to 60°C. Using GC/MS method of analysis chemical profiles (aromatic constituents) of S. montana extracts were obtained. Self-training artificial neural networks were applied to predict the retention time of the analyzed terpenes in GC/MS system. The best ANN model obtained was multilayer perceptron (MLP 11-11-1). Hidden activation was tanh and output activation was identity with Broyden–Fletcher–Goldfarb–Shanno training algorithm. Correlation measures of the obtained network were the following: R(training) = 0.9975, R(test) = 0.9971 and R(validation) = 0.9999. The comparison of the experimental and predicted retention times of the analyzed compounds showed very high correlation (R = 0.9913) and significant predictive power of the established neural network.

Keywords: ANN regression, GC/MS, Satureja montana, terpenes

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Authors: Keigo Nishitani, Kohei Mizuta Mizuta, Kazuyoshi Kurita, Yukinori Taniguchi

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To establish mass production process of Ti capsule which has Fe powder inside as magnetic hyperthermia implant, we assumed that Ti thin sheet can be drawn into a φ1.0 mm die hole through the medium of Fe Powder and becomes outer shell of capsule. This study discusses mechanism of powder assisted deep drawing process by both of numerical simulation and experiment. Ti thin sheet blank was placed on die, and was covered by Fe powder layer without pressurizing. Then upper punch was indented on the Fe powder layer, and the blank can be drawn into die cavity as pressurized powder particles were extruded into die cavity from behind of the drawn blank. Distinct Element Method (DEM) has been used to demonstrate the process. To identify bonding parameters on Fe particles which are cohesion, tensile bond stress and inter particle friction angle, axial and diametrical compression failure test of Fe powder compact was conducted. Several density ratios of powder compacts in range of 0.70 - 0.85 were investigated and relationship between mean stress and equivalent stress was calculated with consideration of critical state line which rules failure criterion in consolidation of Fe powder. Since variation of bonding parameters with density ratio has been experimentally identified, and good agreement has been recognized between several failure tests and its simulation, demonstration of powder assisted sheet forming by using DEM becomes applicable. Results of simulation indicated that indent/drawing length of Ti thin sheet is promoted by smaller Fe particle size, larger indent punch diameter, lower friction coefficient between die surface and Ti sheet and certain degrees of die inlet taper angle. In the deep drawing test, we have made die-set with φ2.4 mm punch and φ1.0 mm die bore diameter. Pure Ti sheet with 100 μm thickness, annealed at 650 deg. C has been tested. After indentation, indented/drawn capsule has been observed by microscope, and its length was measured to discuss the feasibility of this capsulation process. Longer drawing length exists on progressive loading pass comparing with the case of single stroke loading. It is expected that progressive loading has an advantage of which extrusion of powder particle into die cavity with Ti sheet is promoted since powder particle layer can be rebuilt while the punch is withdrawn from the layer in each loading steps. This capsulation phenomenon is qualitatively demonstrated by DEM simulation. Finally, we have fabricated Ti capsule which has Fe powder inside for magnetic hyperthermia cancer care treatment. It is concluded that suggested method is possible to use the manufacturing of Ti capsule implant for magnetic hyperthermia cancer care.

Keywords: metal powder compaction, metal forming, distinct element method, cancer care, magnetic hyperthermia

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Authors: Benjamin Mugisha Bugingo

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Healthcare staffhas been considered as asignificant pillar to the health care system. However, the contest of human resources for health in terms of the turnover of health workers in Uganda has been more distinct in the latest years. The objective of the paper, therefore, were to investigate the influence Role Human resource management functions in on employeeperformance of professional health workers in public district hospitals in Kampala. The study objectives were: to establish the effect of performance management function, financialincentives, non-financial incentives, participation, and involvement in the decision-making on the employee performance of professional health workers in public district hospitals in Kampala. The study was devised in the social exchange theory and the equity theory. This study adopted a descriptive research design using quantitative approaches. The study used a cross-sectional research design with a mixed-methods approach. With a population of 402 individuals, the study considered a sample of 252 respondents, including doctors, nurses, midwives, pharmacists, and dentists from 3 district hospitals. The study instruments entailed a questionnaire as a quantitative data collection tool and interviews and focus group discussions as qualitative data gathering tools. To analyze quantitative data, descriptive statistics were used to assess the perceived status of Human resource management functions and the magnitude of intentions to stay, and inferential statistics were used to show the effect of predictors on the outcome variable by plotting a multiple linear regression. Qualitative data were analyzed in themes and reported in narrative and verbatim quotes and were used to complement descriptive findings for a better understanding of the magnitude of the study variables. The findings of this study showed a significant and positive effect of performance management function, financialincentives, non-financial incentives, and participation and involvement in decision-making on employee performance of professional health workers in public district hospitals in Kampala. This study is expected to be a major contributor for the improvement of the health system in the country and other similar settings as it has provided the insights for strategic orientation in the area of human resources for health, especially for enhanced employee performance in relation with the integrated human resource management approach

Keywords: human resource functions, employee performance, employee wellness, profecial workers

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Authors: Cindy Sithole, Didier Nyembwe, Peter Olubambi

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The sand casting process involves pattern making, mould making, metal pouring and shake out. Every step in the sand moulding process is very critical for production of good quality castings. However, waste generated during the sand moulding operation and lack of quality are matters that influences performance inefficiencies and lack of competitiveness in South African foundries. Defects produced from the sand moulding process are only visible in the final product (casting) which results in increased number of scrap, reduced sales and increases cost in the foundry. The purpose of this Research is to propose six sigma technique (DMAIC, Define, Measure, Analyze, Improve and Control) intervention in sand moulding foundries and to reduce variation caused by deficiencies in the sand moulding process in South African foundries. Its objective is to create sustainability and enhance productivity in the South African foundry industry. Six sigma is a data driven method to process improvement that aims to eliminate variation in business processes using statistical control methods .Six sigma focuses on business performance improvement through quality initiative using the seven basic tools of quality by Ishikawa. The objectives of six sigma are to eliminate features that affects productivity, profit and meeting customers’ demands. Six sigma has become one of the most important tools/techniques for attaining competitive advantage. Competitive advantage for sand casting foundries in South Africa means improved plant maintenance processes, improved product quality and proper utilization of resources especially scarce resources. Defects such as sand inclusion, Flashes and sand burn on were some of the defects that were identified as resulting from the sand moulding process inefficiencies using six sigma technique. The courses were we found to be wrong design of the mould due to the pattern used and poor ramming of the moulding sand in a foundry. Six sigma tools such as the voice of customer, the Fishbone, the voice of the process and process mapping were used to define the problem in the foundry and to outline the critical to quality elements. The SIPOC (Supplier Input Process Output Customer) Diagram was also employed to ensure that the material and process parameters were achieved to ensure quality improvement in a foundry. The process capability of the sand moulding process was measured to understand the current performance to enable improvement. The Expected results of this research are; reduced sand moulding process variation, increased productivity and competitive advantage.

Keywords: defects, foundries, quality improvement, sand moulding, six sigma (DMAIC)

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Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Jessica Raven Gates, Gemma Wilson-Menzfeld, Professor Alison Steven

Abstract:

In 2019, the Primary Care system in the UK National Health Service (NHS) was subject to reform and restructuring. Primary Care Networks (PCNs) were established, which aligned with a trend towards integrated care both within the NHS and internationally. The introduction of PCNs brought groups of GP practices in a locality together, to operate as a network, build on existing services and collaborate at a larger scale. PCNs were expected to bring a range of benefits to patients and address some of the workforce pressures in the NHS, through an expanded and collaborative workforce. The early establishment of PCNs was disrupted by the emerging COVID-19 pandemic. This study, set in the context of the pandemic, aimed to explore experiences of the PCN workforce, and their perceptions of the establishment of PCNs. Specific objectives focussed on examining factors perceived as enabling or hindering the success of a PCN, the impact on day-to-day work, the approach to implementing change, and the influence of the COVID-19 pandemic upon PCN development. This study is part of a three-phase PhD project that utilized qualitative approaches and was underpinned by social constructionist philosophy. Phase 1: a systematic narrative review explored the provision of preventative healthcare services in UK primary settings and examined facilitators and barriers to delivery as experienced by the workforce. Phase 2: informed by the findings of phase 1, semi-structured interviews were conducted with fifteen participants (PCN workforce). Phase 3: follow-up interviews were conducted with original participants to examine any changes to their experiences and perceptions of PCNs. Three main themes span across phases 2 and 3 and were generated through a Framework Analysis approach: 1) working together at scale, 2) network infrastructure, and 3) PCN leadership. Findings suggest that through efforts to work together at scale and collaborate as a network, participants have broadly accepted the concept of PCNs. However, the workforce has been hampered by system design and system complexity. Operating against such barriers has led to a negative psychological impact on some PCN leaders and others in the PCN workforce. While the pandemic undeniably increased pressure on healthcare systems around the world, it also acted as a disruptor, offering a glimpse into how collaboration in primary care can work well. Through the integration of findings from all phases, a new theoretical model has been developed, which conceptualises the findings from this Ph.D. study and demonstrates how the workforce has experienced change associated with the establishment of PCNs. The model includes a contextual component of the COVID-19 pandemic and has been informed by concepts from Complex Adaptive Systems theory. This model is the original contribution to knowledge of the PhD project, alongside recommendations for practice, policy and future research. This study is significant in the realm of health services research, and while the setting for this study is the UK NHS, the findings will be of interest to an international audience as the research provides insight into how the healthcare workforce may experience imposed policy and service changes.

Keywords: health services research, qualitative research, NHS workforce, primary care

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Authors: Leila Keshavarz Afshar, Hedieh Sajedi

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Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

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Authors: A. Sri Janani, K. Immanuel Arokia James

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Cognitive radio ad hoc networks different unlicensed users may acquire different available channel sets. This non-uniform spectrum availability imposes special design challenges for broadcasting in CR ad hoc networks. Cognitive radio automatically detects available channels in wireless spectrum. This is a form of dynamic spectrum management. Cross-layer optimization is proposed, using this can allow far away secondary users can also involve into channel work. So it can increase the throughput and it will overcome the collision and time delay.

Keywords: cognitive radio, cross layer optimization, CR mesh network, heterogeneous spectrum, mesh topology, random routing optimization technique

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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Authors: Elisabete Alberdi, Irantzu Álvarez, Laura Girón

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The objective of this work is to propose a cycle path or network of paths to the UPV/EHU Campus in Leioa. The proposal will be presented from the point of view of sustainability. In order to achieve this, the roads that are already built will be used, and the road or network will be proposed to be built with the least amount of money possible. To select the most suitable route for the bike lane, various sources of information have been used. Through this data, we analyse the transport infrastructure and the mobility around the UPV/EHU Campus in Leioa. This work aims to satisfy the mobility needs of users on the University Campus to contribute to the sustainability of the campus.

Keywords: cycle lane, sustainability, accessibility, transport, agenda 2030

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Authors: Natalie Tyldesley-Marshall, Janette Parr, Anna Brown, Yen-Fu Chen, Amy Grove

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It is widely recognised in policy and research that the provision of services for children and young people (CYP) with Special Educational Needs and Disabilities (SEND) is enhanced when health and social care, and education services collaborate and interact effectively. In the UK, there have been significant changes to policy and provisions which support and improve collaboration. However, professionals responsible for implementing these changes face multiple challenges, including a lack of specific implementation guidance or framework to illustrate how effective multi-agency working could or should work. This systematic review will identify the key components of effective multi-agency working in services for CYP with SEND; and the most effective forms of partnership working in this setting. The review highlights interventions that lead to service improvements; and the conditions in the local area that support and encourage success. A protocol was written and registered with PROSPERO registration: CRD42022352194. Searches were conducted on several health, care, education, and applied social science databases from the year 2012 onwards. Citation chaining has been undertaken, as well as broader grey literature searching to enrich the findings. Qualitative, quantitative, mixed methods studies and systematic reviews were included, assessed independently, and critically appraised or assessed for risk of bias using appropriate tools based on study design. Data were extracted in NVivo software and checked by a more experienced researcher. A convergent segregated approach to synthesis and integration was used in which the quantitative and qualitative data were synthesised independently and then integrated using a joint display integration matrix. Findings demonstrate the key ingredients for effective partnership working for services delivering SEND. Interventions deemed effective are described, and lessons learned across interventions are summarised. Results will be of interest to educators and health and social care professionals that provide services to those with SEND. These will also be used to develop policy recommendations for how UK healthcare, social care, and education services for CYP with SEND aged 0-25 can most effectively collaborate and achieve service improvement. The review will also identify any gaps in the literature to recommend areas for future research. Funding for this review was provided by the Department for Education.

Keywords: collaboration, joint commissioning, service delivery, service improvement

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Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

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Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: mininet, OpenFlow, POX controller, SDN

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Authors: A. Barratt, M. H. Granat, S. Buttress, B. Roy

Abstract:

Introduction: Physiotherapy is an essential part of the treatment of patients with shoulder problems. The focus of treatment is usually centred on addressing specific physiotherapy goals, ultimately resulting in the improvement in pain and function. This study investigates if computerised physiotherapy using gamification principles are as effective as standard physiotherapy. Methods: Physiotherapy exergames were created using a combination of commercially available hardware, the Microsoft Kinect, and bespoke software. The exergames used were validated by mapping physiotherapy goals of physiotherapy which included; strength, range of movement, control, speed, and activation of the kinetic chain. A multicenter, randomised prospective controlled trial investigated the use of exergames on patients with Shoulder Impingement Syndrome who had undergone Arthroscopic Subacromial Decompression surgery. The intervention group was provided with the automated sensor-based technology, allowing them to perform exergames and track their rehabilitation progress. The control group was treated with standard physiotherapy protocols. Outcomes from different domains were used to compare the groups. An important metric was the assessment of shoulder range of movement pre- and post-operatively. The range of movement data included abduction, forward flexion and external rotation which were measured by the software, pre-operatively, 6 weeks and 12 weeks post-operatively. Results: Both groups show significant improvement from pre-operative to 12 weeks in elevation in forward flexion and abduction planes. Results for abduction showed an improvement for the interventional group (p < 0.015) as well as the test group (p < 0.003). Forward flexion improvement was interventional group (p < 0.0201) with the control group (p < 0.004). There was however no significant difference between the groups at 12 weeks for abduction (p < 0.118067) , forward flexion (p < 0.189755) or external rotation (p < 0.346967). Conclusion: Exergames may be used as an alternative to standard physiotherapy regimes; however, further analysis is required focusing on patient engagement.

Keywords: shoulder, physiotherapy, exergames, gamification

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