Search results for: user identification

Authors: Abdullah Alshehab

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Governments worldwide are intensely focused on digitizing public transactions to establish reliable e-government services. The advent of new digital technologies and ongoing advancements in ICT have profoundly transformed business operations. Citizen engagement and participation in e-government services are crucial for the system's success. However, it is essential to measure and enhance citizen satisfaction levels to effectively evaluate and improve these systems. Citizen satisfaction is a key criterion that allows government institutions to assess the quality of their services. There is a strong connection between information quality, service quality, and system quality, all of which directly impact user satisfaction. Additionally, both system quality and information quality have indirect effects on citizen satisfaction. A causal map, which is a network diagram representing causes and effects, can illustrate these relationships. According to the literature, the main factors influencing citizen satisfaction are trust, reliability, citizen support, convenience, and transparency. This paper investigates the causal relationships among these factors and identifies any interrelatedness between them.

Keywords: e-government services, e-satisfaction, citizen satisfaction, causal map.

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Authors: Ching-Sung Wang, Teng-Wei Wang, Zhen-Ting Zheng

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This study mainly concerns a safety device designed for child care. When children are out of sight or the caregivers cannot always pay attention to the situation, through the functions of this device, caregivers can immediately be informed to make sure that the children do not get lost or hurt, and thus, ensure their safety. Starting from this concept, a device is produced based on the relatively low-cost Bluetooth piconet system and a three-axis gyroscope sensor. This device can transmit data to a mobile phone app through Bluetooth, in order that the user can learn the situation at any time. By simply clipping the device in a pocket or on the waist, after switching on/starting the device, it will send data to the phone to detect the child’s fall and distance. Once the child is beyond the angle or distance set by the app, it will issue a warning to inform the phone owner.

Keywords: children care, piconet system, three-axis gyroscope, distance detection, falls detection

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Authors: Muhammad Denny Abdillah, Mochammad Rasyid Poedjijanto

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Batu, East Java, Indonesia is located in highland about 680-1,200 meters above ocean surface and has temperature 15-19 degree Celsius. With this condition, so the main profession of people around is a farmer. But, along with era’s developing, now Batu is started to improve their development in tourism sector and show up them as an icon of tourism in Indonesia. Such as: playground, museum, and paralayang’s summit. That is made Batu in nowadays well known as the one of recommended city to visit. The change of the development from farming sector to tourism sector make people around prefer doing job in trade than engage in farming. That’s make authors want to observe about this social phenomenon which is happening in Batu, whereas from the beginning the primary profession is a farmer, now changed to be a trader around the tourism place.

Keywords: development, profession, tourism, Batu

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Authors: Laidi Maamar, Hanini Salah

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The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: Attaullah Khawaja, Amna Shabbir

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Channel inversion is one of the simplest techniques for multiuser downlink systems with single-antenna users. In this paper regularized channel inversion under equal power constraint in the multiuser multiple input multiple output (MU-MIMO) broadcast channels has been considered. Sum capacity with plain channel inversion also known as Zero Forcing Beam Forming (ZFBF) and optimum sum capacity using Dirty Paper Coding (DPC) has also been investigated. Analysis and simulations show that regularization enhances the system performance and empower linear growth in Sum Capacity and specially work well at low signal to noise ratio (SNRs) regime.

Keywords: broadcast channel, channel inversion, multiple antenna multiple-user wireless, multiple-input multiple-output (MIMO), regularization, dirty paper coding (DPC), sum capacity

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Authors: Chetna Tyagi, Ambuj Tripathi, Devesh Avasthi

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Graphene oxide consists of sp³ hybridization along with sp² hybridization due to the presence of different oxygen-containing functional groups on its edges and basal planes. However, its sp³ / sp² hybridization can be tuned by various methods to utilize it in different applications, like transistors, solar cells and biosensors. Ion beam irradiation can also be one of the methods to optimize sp² and sp³ hybridization ratio for its desirable properties. In this work, graphene oxide films were irradiated with 100 keV Argon ions at different fluences varying from 10¹³ to 10¹⁶ ions/cm². Synchrotron X-ray diffraction measurements showed an increase in crystallinity at the low fluence of 10¹³ ions/cm². Raman spectroscopy performed on irradiated samples determined the defects induced by the ion beam qualitatively. Also, identification of different groups and their removal with different fluences was done using Fourier infrared spectroscopy technique.

Keywords: graphene oxide, ion beam irradiation, spectroscopy, X-ray diffraction

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Authors: S. K. Ashiquer Rahman

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This paper presents a knowledge mediation platform, “ePLANETe Blue” that addresses the challenge of building knowledge partnerships for higher education. The purpose is to present, as an institutional perception, the ‘ePLANETe' idea and functionalities as a practical and pedagogical innovation program contributing to the collaborative learning goals in higher education. In consequence, the set of functionalities now amalgamated in ‘ePLANETe’ can be seen as an investigation of the challenges of “Collaborative Learning Digital Process.” It can exploit the system to facilitate collaborative education, research and student learning in higher education. Moreover, the platform is projected to support the identification of best practices at explicit levels of action and to inspire knowledge interactions in a “virtual community” and thus to advance in deliberation and learning evaluation of higher education through the engagement of collaborative activities of different sorts.

Keywords: mediation, collaboration, deliberation, evaluation

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Authors: K. Jarmkom, P. Eakwaropas, W. Khobjai, S. Techaeoi

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Ancient Thai perfumed powder was used as a fragrance for clothing, food, and the body. Plant-based natural Thai perfume products are known as Pang-Rum. The objective of this study was to evaluate the stability of essential oils after six months of incubation. The chemical compositions were determined by gas chromatography-mass spectrometry (GC-MS), in terms of the qualitative composition of the isolated essential oil. The isolation of the essential oil of natural products by incubate sample for 5 min at 40 ºC is described. The volatile components were identified by percentage of total peak areas comparing their retention times of GC chromatograph with NIST mass spectral library. The results show no significant difference in the seven chromatograms of perfumed powder (Pang-Rum) both with binder and without binder. Further identification was done by GC-MS. Some components of Pang-Rum with/without binder were changed by temperature and time.

Keywords: GC-MS analysis, essential oils, stability, Pang-Rum

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Authors: Rasmila Kawan, Sanjay Juvekar, Sandeep Salvi, Gufran Beig, Rainer Sauerborn

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Background: Indoor air pollution especially from the use of biomass fuels, remains a potentially large global health threat. The inefficient use of such fuels in poorly ventilated conditions results in high levels of indoor air pollution, most seriously affecting women and young children. Objectives: The main aim of this study was to measure and compare the lung function of the women exposed in the biomass fuels and LPG fuels and relate it to the indoor emission measured using a structured questionnaire, spirometer and filter based low volume samplers respectively. Methodology: This cross-sectional comparative study was conducted among the women (aged > 18 years) living in rural villages of Pune district who were not diagnosed of chronic pulmonary diseases or any other respiratory diseases and using biomass fuels or LPG for cooking for a minimum period of 5 years or more. Data collection was done from April to June 2017 in dry season. Spirometer was performed using the portable, battery-operated ultrasound Easy One spirometer (Spiro bank II, NDD Medical Technologies, Zurich, Switzerland) to determine the lung function over Forced expiratory volume. The primary outcome variable was forced expiratory volume in 1 second (FEV1). Secondary outcome was chronic obstruction pulmonary disease (post bronchodilator FEV1/ Forced Vital Capacity (FVC) < 70%) as defined by the Global Initiative for Obstructive Lung Disease. Potential confounders such as age, height, weight, smoking history, occupation, educational status were considered. Results: Preliminary results showed that the lung function of the women using Biomass fuels (FEV1/FVC = 85% ± 5.13) had comparatively reduced lung function than the LPG users (FEV1/FVC = 86.40% ± 5.32). The mean PM 2.5 mass concentration in the biomass user’s kitchen was 274.34 ± 314.90 and 85.04 ± 97.82 in the LPG user’s kitchen. Black carbon amount was found higher in the biomass users (black carbon = 46.71 ± 46.59 µg/m³) than LPG users (black carbon=11.08 ± 22.97 µg/m³). Most of the houses used separate kitchen. Almost all the houses that used the clean fuel like LPG had minimum amount of the particulate matter 2.5 which might be due to the background pollution and cross ventilation from the houses using biomass fuels. Conclusions: Therefore, there is an urgent need to adopt various strategies to improve indoor air quality. There is a lacking of current state of climate active pollutants emission from different stove designs and identify major deficiencies that need to be tackled. Moreover, the advancement in research tools, measuring technique in particular, is critical for researchers in developing countries to improve their capability to study the emissions for addressing the growing climate change and public health concerns.

Keywords: black carbon, biomass fuels, indoor air pollution, lung function, particulate matter

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Authors: Magdi. M. Nabi, Ding-Li Yu

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Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward, feedback control

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Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

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Authors: Maria Komal, Zaineb Khalil, Mehreen Sirshar

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Due to the recent technological advancements, Games have become one of the most demanding applications. Gaming industry is rapidly growing and the key to success in this industry is the development of good quality games, which is a highly competitive issue. The ultimate goal of game developers is to provide player’s satisfaction by developing high-quality games. This research is the comprehensive survey of techniques followed by game industries to ensure games quality. After analysis of various techniques, it has been found that quality simulation according to ISO standards and play test methods are used to ensure games quality. Because game development requires cross-disciplined team, an increasing trend towards distributed game development has been observed. This paper evaluates the strengths and weaknesses of current methodologies used in game industry and draws a conclusion. We have also proposed quality parameters which can be used as a heuristic framework to identify those attributes which have high testing priorities.

Keywords: game development, computer games, video games, gaming industry, quality assurance, playability, user experience

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Authors: Zaid Jamal Saeed Almahmoud

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Smart Grid is the vision of the future power system that combines advanced monitoring and communication technologies to provide energy in a smart, efficient, and user-friendly manner. This proposal considers a demand response model in the Smart Grid based on utility maximization. Given a set of consumers with conflicting preferences in terms of consumption and a utility company that aims to minimize the peak demand and match demand to supply, we study the problem of aggregating these preferences while modelling the problem as a game. We also investigate whether an equilibrium can be reached to maximize the social benefit. Based on such equilibrium, we propose a dynamic pricing heuristic that computes the equilibrium and sets the prices accordingly. The developed approach was analysed theoretically and evaluated experimentally using real appliances data. The results show that our proposed approach achieves a substantial reduction in the overall energy consumption.

Keywords: heuristics, smart grid, aggregation, mechanism design, equilibrium

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Authors: Ahmad S. Mohd Noor, Emma A. Sirajudin, Nur F. Mat Zain

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Reliability is an important property for knowledge repository system. National Marine Bioinformatics System or NABTICS is a marine knowledge repository portal aimed to provide a baseline for marine biodiversity and a tool for researchers and developers. It is intended to be a large and growing online database and also a metadata system for inputs of research analysis. The trends of present large distributed systems such as Cloud computing are the delivery of computing as a service rather than a product. The goal of this research is to make NABTICS a system of greater availability by integrating it with Cloud based Neighbor Replication and Failure Recovery (NRFR). This can be achieved by implementation of NABTICS into distributed environment. As a result, the user can experience minimum downtime while using the system should the server is having a failure. Consequently the online database application is said to be highly available.

Keywords: cloud, availability, distributed system, marine repository, database replication

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Authors: André Jesus, Yanjie Zhu, Irwanda Laory

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Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

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Authors: Bashaiar Alsanaa

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The process of decision making requires environment surveillance and public opinion monitoring, both of which can be attained through effective use of social media. This study aims to investigate the extent to which new media influence the decision making process by the Kuwaiti government. The research explores how unprecedented access to information as well as dynamic user-interaction made possible by new technologies play a significant role in all aspects of decision making whether on the end of the public or decision makers themselves. The research analyzes two case studies where public opinion was forceful on social media in order to explore how such media create interactive and liberal environments for individuals to participate in the process of taking action with regards to political, economic and social issues. The findings of this descriptive study indicate the overwhelming extent to which social media are being used in Kuwait to create new social reform by the government based on citizen interaction with current topics.

Keywords: communication, descriptive, new media technologies, social media.

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Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

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Authors: David Pettitt, Benjamin Davies, Georg Holländer, David Brindley

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Cellular based therapies, whose origins can be traced from the intertwined concepts of tissue engineering and regenerative medicine, have the potential to transform the current medical landscape and offer an approach to managing what were once considered untreatable diseases. However, despite a large increase in basic science activity in the cell therapy arena alongside a growing portfolio of cell therapy trials, the number of industry products available for widespread clinical use correlates poorly with such a magnitude of activity, with the number of cell-based therapeutics in mainstream use remaining comparatively low. This research serves to quantitatively assess the barriers to the clinical adoption of cell-based therapeutics through identification of unique barriers, specific challenges and opportunities facing the development and adoption of such therapies.

Keywords: cell therapy, clinical adoption, commercialization, translation

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Authors: Rahy Farooq, Maria Ahmad Khan, Ayesha Isani Majeed

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Objective: The main aim of this research is to assess the knowledge, attitude and practices of female nursing staff and nursing students regarding breast cancer, to provide a baseline for monitoring trends of breast cancer awareness in them. Background: Healthcare professionals are a direct source of information for the patients and the general public as a whole. It is, therefore, essential that the information they convey be accurate and helps in building additional awareness. However, clinical experience does not influence the knowledge, attitude and practices regarding breast cancer. Nurses, being the prime part of the healthcare professionals, play a significant role and hence, their awareness regarding this pressing issue is pertinent. Lack of awareness regarding common presenting symptoms or breast cancer risk factors translates to poor breast cancer screening practices and late diagnosis. Methodology: A cross-sectional study of 280 female nurses was conducted at a tertiary care hospital in Islamabad, Pakistan. A pre-tested structured questionnaire with additional variables like cultural barriers to seeking medical help was used. The scores for outcome variables including knowledge, attitude and practices were pre-defined. Data was analyzed using SPSSv23. Results: Of the 280 participants with a mean age of 28.99±9.98 years, 142 (50.7%) were married, and 138 (49.3%) were unmarried. Mean scores were computed to be 6.14±2.93 (out of 12), 0.30±0.7 (out of 3) and 9.53±1.92 (out of 16) for knowledge, attitude and practice respectively. Using independent sample T-test, a statistically significant correlation was found when means for the score of Attitude was compared with age. With a p-value of 0.018, 117 nurses of age more than 30 years, faced more practical, financial, emotional and service barriers as compared to 163 women younger than 30 years of age. Knowledge of age-related lifetime risks was also significantly poor more in single women; with a p-value of 0.006 for identification of correct age as a risk factor and a p-value of 0.005 for correct identification of risk for development of breast cancer in the lifetime of women. By application of Chi-square test, there was a significant correlation between marital status and cultural barriers to seeking medical help, showing that single women (58.7%) shy away from talking about breast cancer considering it a taboo (p-value 0.028) whereas, more married nurses (59.2%) were apprehensive that they might be considered at fault by the society, as compared to 40.8% of single nurses. (p-value 0.038). Conclusion: Owing to the scarcity of awareness among nurses, this study recognizes the need for delivering effective information to the female nurses regarding breast cancer. Educating patients is likely to be effective if the female nurses play their part and have correct attitudes towards breast cancer practices. A better understanding of the knowledge and practices regarding breast cancer among the nursing population will enable high-risk patients to be recognized early. Therefore, we recommend arrangement of special courses and seminars for all healthcare professionals including the nursing staff.

Keywords: breast cancer, cultural barriers, kap, nurses

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Authors: Rajesh A. Rane, Shital S. Naphade, Rajshekhar Karpoormath

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Thiozolidin-4-one, a mimic of thiazolobenzimidazole (TBZ) has drawn many attentions due to its potent and selective inhibition against the HIV-1 and low toxicity by binding to the allosteric site of the reverse transcriptase (RT) as a non-nucleoside RT inhibitor (NNRTI). Similarly, marine bromopyrrole alkaloids are well known for their diverse array of anti-infective properties. Hence, we have reported synthesis and in vitro HIV-1 RT inhibitory activity of a series of 4-thiazolidinone-bromopyrrole alkaloid hybrids tethered with amide linker. The results of in vitro HIV-1 RT kit assay showed that some of the compounds, such as 4c, 4d, and 4i could effectively inhibit RT activity. Among them, compounds 4c having 4-chlorophenyl substituted 4-thiazolidione ring was the best one with the IC50 value of 0.26 µM. The sturdy emerges with key structure-activity relationship that pyrrole-NH-free core benefited inhibition against HIV-1 RT inhibition. This study identified conjugate 4c with potent activity and selectivity as promising compound for further drug development to HIV.

Keywords: antiviral drugs, bromopyrrole alkaloids, HIV-1 RT inhibition, 4-thiazolidinone

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Authors: A. K. Sarathe, N. P. Patidar

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The Indian automobile sector is comprised of independent manufacturers and joint ventures with their foreign counterpart companies by making use of the Foreign Direct Investment policy of the Government of India. These manufacturers started capturing the hearts of Indian customers with their choice of technological and innovative product features, with quality and reliability. This transformed the automobile scene from a “sellers market to buyers market”. The potential benefits from the auto sector have been recognized by the planners, managers, and administrators of both the sectors –government and private. Generation of employment for the readily available technical workforce has been achieved not only through the manufacturers, but also through the growing ancillaries and service providers of the auto industries. The main purpose of this paper is to come up with the identification of possible working areas and associated job functions of mechanical and automobile diploma holders having employment opportunities in auto sector of India.

Keywords: automobile sector, diploma holder, employment, job description

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Authors: Yufen Qin

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Topic-to-Essay generation is a challenging task in Natural language processing, which aims to generate novel, diverse, and topic-related text based on user input. Previous research has overlooked the generation of articles under the constraints of event elements, resulting in issues such as incomplete event elements and logical inconsistencies in the generated results. To fill this gap, this paper proposes an event-constrained approach for a topic-to-essay generation that enforces the completeness of event elements during the generation process. Additionally, a language model is employed to verify the logical consistency of the generated results. Experimental results demonstrate that the proposed model achieves a better BLEU-2 score and performs better than the baseline in terms of subjective evaluation on a real dataset, indicating its capability to generate higher-quality topic-related text.

Keywords: event element, language model, natural language processing, topic-to-essay generation.

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Authors: Abdulrahman S. Alturki, John S. Loomis

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This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

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Authors: Jaiden X. Schraut

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Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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Authors: Shilan Rahmani Azr, Siavash Emtiyaz

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Recent development in computing and communicative technologies leads to much easier mobile accessibility to the information. Users can access to the information in different places using various deceives in which the care variety of abilities. Meanwhile, the format and details of electronic documents are changing each day. In these cases, a mismatch is created between content and client’s abilities. Recently the service-oriented content adaption has been developed which the adapting tasks are dedicated to some extended services. In this method, the main problem is to choose the best appropriate service among accessible and distributed services. In this paper, a method for determining the optimal path to the best services, based on the quality control parameters and user preferences, is proposed using max heap tree. The efficiency of this method in contrast to the other previous methods of the content adaptation is related to the determining the optimal path of the best services which are measured. The results show the advantages and progresses of this method in compare of the others.

Keywords: service-oriented content adaption, QoS, max heap tree, web services

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Authors: Lovepreet Kaur Dhugga, Dwijendra P. Singh

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Calcium copper titanate (CCTO) was synthesized via the sol-gel auto-combustion method. The precursor was calcined at 800°C and 1000°C for 6 hours providing brown-coloured powders, which were pelletized and sintered at 1000°C for 12 hrs to determine their dielectric behaviour in the frequency range (100Hz-10MHz) at room temperature. The dielectric constant(εr) and loss tangent (tanδ) has been found to be ~ 6153 and 0.5 for 800°C and ~ 5504 and 0.2 for 1000°C respectively, at frequency 1kHz. Microstructure study revealed maximum grain growth occurs in sample calcined at 800°C, responsible for its high dielectric constant. Phase identification of CaCu₃Ti₄O₁₂ has been carried out through X-ray diffraction. It can be used in various electronic applications as it shows large εᵣ and low tanδ values over a wide frequency spectrum, including energy storage devices, microwave shielding, and sensors.

Keywords: calcium copper titanate, dielectric behaviour, microstructure, X-ray diffraction

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Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

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Authors: Shu-Lu Hsu, Fang-Yi Chu

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With the advances in information and communications technology, mobile context-aware applications have become powerful marketing tools. In Apple online store, there are numerous mobile applications (APPs) developed for destination tour. This study investigated the determinants of adoption of context-aware APPs for destination tour services. A model is proposed based on Technology Acceptance Model and privacy concern theory. The model was empirically tested based on a sample of 259 users of a tourism APP published by Kaohsiung Tourism Bureau, Taiwan. The results showed that the fitness of the model is well and, among all the factors, the perceived usefulness and perceived ease of use have the most significant influences on the intention to adopt context-aware destination APPs. Finally, contrary to the findings of previous literature, the effect of privacy concern on the adoption intention of context-aware APP is insignificant.

Keywords: mobile application, context-aware, privacy concern, TAM

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Authors: Andrea Ghermandi

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Natural treatment systems such as constructed wetlands and waste stabilization ponds are increasingly used to treat water and wastewater from a variety of sources, including stormwater and polluted surface water. The provision of ancillary benefits in the form of cultural ecosystem services makes these systems unique among water and wastewater treatment technologies and greatly contributes to determine their potential role in promoting sustainable water management practices. A quantitative analysis of these benefits, however, has been lacking in the literature. Here, a critical assessment of the recreational and educational benefits in natural treatment systems is provided, which combines observed public use from a survey of managers and operators with estimated public use as obtained using geotagged photos from social media as a proxy for visitation rates. Geographic Information Systems (GIS) are used to characterize the spatial boundaries of 273 natural treatment systems worldwide. Such boundaries are used as input for the Application Program Interfaces (APIs) of two popular photo-sharing websites (Flickr and Panoramio) in order to derive the number of photo-user-days, i.e., the number of yearly visits by individual photo users in each site. The adequateness and predictive power of four univariate calibration models using the crowdsourced data as a proxy for visitation are evaluated. A high correlation is found between photo-user-days and observed annual visitors (Pearson's r = 0.811; p-value < 0.001; N = 62). Standardized Major Axis (SMA) regression is found to outperform Ordinary Least Squares regression and count data models in terms of predictive power insofar as standard verification statistics – such as the root mean square error of prediction (RMSEP), the mean absolute error of prediction (MAEP), the reduction of error (RE), and the coefficient of efficiency (CE) – are concerned. The SMA regression model is used to estimate the intensity of public use in all 273 natural treatment systems. System type, influent water quality, and area are found to statistically affect public use, consistently with a priori expectations. Publicly available information regarding the home location of the sampled visitors is derived from their social media profiles and used to infer the distance they are willing to travel to visit the natural treatment systems in the database. Such information is analyzed using the travel cost method to derive monetary estimates of the recreational benefits of the investigated natural treatment systems. Overall, the findings confirm the opportunities arising from an integrated design and management of natural treatment systems, which combines the objectives of water quality enhancement and provision of cultural ecosystem services through public use in a multi-functional approach and compatibly with the need to protect public health.

Keywords: constructed wetlands, cultural ecosystem services, ecological engineering, waste stabilization ponds

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Authors: Shuqi Zhang

Abstract:

Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%.

Keywords: federated learning, secure aggregation, backdoor attack, cluster analysis, neuron pruning

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