Search results for: customer information system

Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

Procedia PDF Downloads 401

Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

Procedia PDF Downloads 125

Authors: Runliang Wang, Jianhua Liu, Duo Jia, Xiaoyu Ding

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The contact between sealing surfaces plays a vital role in guaranteeing the sealing performance of various seals. To date, analyses of sealing structures have rarely considered both structural parameters (macroscale) and surface roughness information (microscale) of sealing surfaces due to the complex modeling process. Meanwhile, most of the contact analyses applied to seals were conducted only under normal loading, which still existssome distance from real loading conditions in engineering. In this paper, a multiscale rough contact model, which took both macrostructural parameters of seals and surface roughness information of sealing surfaces into consideration for the cone-cone seal, was established. By using the finite element method (FEM), the combined normal and tangential loading was applied to the model to simulate the assembly process of the cone-cone seal. The evolution of the contact behaviors during the assembly process, such as the real contact area (RCA), the distribution of contact pressure, and contact status, are studied in detail. The results showed the non-linear relationship between the RCA and the load, which was different from the normal loading cases. In addition, the evolution of the real contact area of cone-cone seals with isotropic and anisotropic rough surfaces are also compared quantitatively.

Keywords: contact mechanics, FEM, randomly rough surface, real contact area, sealing

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Authors: Yusuf Bulale, Mark Prince, Geoff Tansley, Peter Brett

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Cochlear Implantation (CI) which became a routine procedure for the last decades is an electronic device that provides a sense of sound for patients who are severely and profoundly deaf. Today, cochlear implantation technology uses electrode array (EA) implanted manually into the cochlea. The optimal success of this implantation depends on the electrode technology and deep insertion techniques. However, this manual insertion procedure may cause mechanical trauma which can lead to a severe destruction of the delicate intracochlear structure. Accordingly, future improvement of the cochlear electrode implant insertion needs reduction of the excessive force application during the cochlear implantation which causes tissue damage and trauma. This study is examined tool-tissue interaction of large prototype scale digit embedded with distributive tactile sensor based upon cochlear electrode and large prototype scale cochlea phantom for simulating the human cochlear which could lead to small-scale digit requirements. The digit, distributive tactile sensors embedded with silicon-substrate was inserted into the cochlea phantom to measure any digit/phantom interaction and position of the digit in order to minimize tissue and trauma damage during the electrode cochlear insertion. The digit has provided tactile information from the digit-phantom insertion interaction such as contact status, tip penetration, obstacles, relative shape and location, contact orientation and multiple contacts. The tests demonstrated that even devices of such a relative simple design with low cost have a potential to improve cochlear implant surgery and other lumen mapping applications by providing tactile sensory feedback information and thus controlling the insertion through sensing and control of the tip of the implant during the insertion. In that approach, the surgeon could minimize the tissue damage and potential damage to the delicate structures within the cochlear caused by current manual electrode insertion of the cochlear implantation. This approach also can be applied to other minimally invasive surgery applications as well as diagnosis and path navigation procedures.

Keywords: cochlear electrode insertion, distributive tactile sensory feedback information, flexible digit, minimally invasive surgery, tool/tissue interaction

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Authors: Nikolai Brosch, Alwine Mohnen

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Academics and business leaders increasingly call for a (re)definition of a corporate purpose beyond profit-maximization to contribute to the welfare of society. This study investigates the effect of communicating such a pro-social corporate purpose on three employee-level outcomes that constitute major cost components for most organizations: workers reservation wage, work quality, and work misbehavior. To provide causal evidence, two natural field experiments were conducted with almost 2,000 workers recruited from different online labor marketplaces. Workers were randomly assigned to treatments manipulating whether or not they received information about the employer’s corporate purpose and subsequently performed a short, real-effort task for payment. The main findings in both experiments show that receiving information about an employer’s pro-social corporate purpose causes workers to accept lower wages (9% lower in the first experiment and 28% lower in the second experiment) for the same job. Workers that personally assess high importance to organizations having a pro-social purpose are most responsive. At the same time, sacrificing wage for a corporate purpose comes at no cost of quality and even decreases the likelihood of engaging in work misbehavior. In a broader context, the results provide some evidence that the (re)definition of corporate purpose in commercial organizations is not ultimately at odds with creating profits.

Keywords: corporate purpose, natural field experiment, reservation wage, work misbehavior, work quality

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Authors: Muhammad Awais, Wei Li, Anjum Munir

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Biomass gasification is a process of converting solid biomass ingredients into a combustible gas which can be used in electricity generation. Regardless of their applications in many fields, biomass gasification technology is still facing many cleaning issues of syngas. Tar production in biomass gasification process is one of the biggest challenges for this technology. The aimed of this study is to evaluate the tar contents in syngas produced from wood chips, corn cobs, coconut shells and mixture of corn cobs and wood chips as biomass fuel and tar removal efficiency of different cleaning units integrated with gassifier. Performance of different cleaning units, i.e., cyclone separator, wet scrubber, biomass filter, and auxiliary filter was tested under two biomass fuels. Results of this study indicate that wood chips produced less tar of 1736 mg/Nm³ as compared to corn cobs which produced tor 2489 mg/Nm³. It is also observed that coconut shells produced a high amount of tar. It was observed that when wood chips were used as a fuel, syngas tar contents were reduced from 6600 to 112 mg/Nm³ while in case of corn cob, they were reduced from 7500 mg/Nm³ to 220 mg/Nm³. Overall tar removal efficiencies of cyclone separator, wet scrubber, biomass filter, and auxiliary filter was 72%, 63%, 74%, 35% respectively.

Keywords: biomass, gasification, tar, cleaning system, biomass filter

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Authors: Lubabatu Sada Sodangi

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The rapid growth in exchange and accessibility of information via the internet makes many organisations acquire data on their own operation. The aim of data mining is to analyse the different behaviour of a dataset using observation. Although, the subset of the dataset being analysed may not display all the behaviours and relationships of the entire data and, therefore, may not represent other parts that exist in the dataset. There is a range of techniques used in data mining to determine the hidden or unknown information in datasets. In this paper, the performance of two algorithms Chi-Square Automatic Interaction Detection (CHAID) and multilayer perceptron (MLP) would be matched using an Adult dataset to find out the percentage of an/the adults that earn > 50k and those that earn <= 50k per year. The two algorithms were studied and compared using IBM SPSS statistics software. The result for CHAID shows that the most important predictors are relationship and education. The algorithm shows that those are married (husband) and have qualification: Bachelor, Masters, Doctorate or Prof-school whose their age is > 41<57 earn > 50k. Also, multilayer perceptron displays marital status and capital gain as the most important predictors of the income. It also shows that individuals that their capital gain is less than 6,849 and are single, separated or widow, earn <= 50K, whereas individuals with their capital gain is > 6,849, work > 35 hrs/wk, and > 27yrs their income will be > 50k. By comparing the two algorithms, it is observed that both algorithms are reliable but there is strong reliability in CHAID which clearly shows that relation and education contribute to the prediction as displayed in the data visualisation.

Keywords: data mining, CHAID, multi-layer perceptron, SPSS, Adult dataset

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Authors: Linda Dusman, Linda Baker

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The Bearman Study of Audience Engagement examined the potential for real-time music education during online symphony orchestra concerts. It follows on the promising results of a preliminary study of STEAM (Science, Technology, Engineering, Arts, and Mathematics) education during live concerts, funded by the National Science Foundation with the Baltimore Symphony Orchestra. For the Bearman Study, audience groups were recruited to attend two previously recorded concerts of the National Orchestral Institute (NOI) in 2020 or the Utah Symphony in 2021. They used a smartphone app called EnCue to present real-time program notes about the music being performed. Short notes along with visual information (photos and score fragments) were designed to provide historical, cultural, biographical, and theoretical information at specific moments in the music where that information would be most pertinent, generally spaced 2-3 minutes apart to avoid distraction. The music performed included Dvorak Symphony No. 8 and Mahler Symphony No. 5 at NOI, and Mendelssohn Scottish Symphony and Richard Strauss Metamorphosen with the Utah Symphony, all standard repertoire for symphony orchestras. During each phase of the study (2020 and 2021), participants were randomly assigned to use the app to view program notes during the first concert or to use the app during the second concert. A total of 139 participants (67 in 2020 and 72 in 2021) completed three online questionnaires, one before attending the first concert, one immediately after the concert, and the third immediately after the second concert. Questionnaires assessed demographic background, expertise in music, engagement during the concert, learning of content about the composers and the symphonies, and interest in the future use of the app. In both phases of the study, participants demonstrated that they learned content presented on the app, evidenced by the fact that their multiple-choice test scores were significantly higher when they used the app than when they did not. In addition, most participants indicated that using the app enriched their experience of the concert. Overall, they were very positive about their experience using the app for real-time learning and they expressed interest in using it in the future at both live and streaming concerts. Results confirmed that informal real-time learning during concerts is possible and can generate enhanced engagement and interest in classical music.

Keywords: audience engagement, informal education, music technology, real-time learning

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Authors: Piotr Kacejko, Mariusz Duk, Miroslaw Wendeker

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This paper presents an adaptive controller to track the maximum power point of a photovoltaic modules (PV) under fast irradiation change on the city-bus roof. Photovoltaic systems have been a prominent option as an additional energy source for vehicles. The Municipal Transport Company (MPK) in Lublin has installed photovoltaic panels on its buses roofs. The solar panels turn solar energy into electric energy and are used to load the buses electric equipment. This decreases the buses alternators load, leading to lower fuel consumption and bringing both economic and ecological profits. A DC–DC boost converter is selected as the power conditioning unit to coordinate the operating point of the system. In addition to the conversion efficiency of a photovoltaic panel, the maximum power point tracking (MPPT) method also plays a main role to harvest most energy out of the sun. The MPPT unit on a moving vehicle must keep tracking accuracy high in order to compensate rapid change of irradiation change due to dynamic motion of the vehicle. Maximum power point track controllers should be used to increase efficiency and power output of solar panels under changing environmental factors. There are several different control algorithms in the literature developed for maximum power point tracking. However, energy performances of MPPT algorithms are not clarified for vehicle applications that cause rapid changes of environmental factors. In this study, an adaptive MPPT algorithm is examined at real ambient conditions. PV modules are mounted on a moving city bus designed to test the solar systems on a moving vehicle. Some problems of a PV system associated with a moving vehicle are addressed. The proposed algorithm uses a scanning technique to determine the maximum power delivering capacity of the panel at a given operating condition and controls the PV panel. The aim of control algorithm was matching the impedance of the PV modules by controlling the duty cycle of the internal switch, regardless of changes of the parameters of the object of control and its outer environment. Presented algorithm was capable of reaching the aim of control. The structure of an adaptive controller was simplified on purpose. Since such a simple controller, armed only with an ability to learn, a more complex structure of an algorithm can only improve the result. The presented adaptive control system of the PV system is a general solution and can be used for other types of PV systems of both high and low power. Experimental results obtained from comparison of algorithms by a motion loop are presented and discussed. Experimental results are presented for fast change in irradiation and partial shading conditions. The results obtained clearly show that the proposed method is simple to implement with minimum tracking time and high tracking efficiency proving superior to the proposed method. This work has been financed by the Polish National Centre for Research and Development, PBS, under Grant Agreement No. PBS 2/A6/16/2013.

Keywords: adaptive control, photovoltaic energy, city bus electric load, DC-DC converter

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Authors: Adeyemi Kamil Hamzah

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The contiguity of nations in international system suggests that world is a composite of socio-economic unit with people exploring and exploiting the potentials in the world via migrations. Thus, cross border migration has made positive contributions to social and economic development of individuals and nations by increasing the household incomes of the host countries. However, the cross border migrations in West Africa are becoming part of a dynamic and unstable world migration system. This is due to the nature and consequences of trans-border crimes in West Africa, with both short and long term effects on the socio-economic viability of developing countries like West African States. The paper identified that migration influenced cross-border crimes as well as the high spate of insurgencies in the sub-region. Furthermore, the consequential effect of a global village has imbalanced population flows, making some countries host and parasites to others. Also, stern and deft cross-border rules and regulations, as well as territorial security and protections, ameliorate cross border crimes and migration in West African sub-regions. Therefore, the study concluded that cross border migration is the linchpin of all kinds of criminal activities which affect the security of states in the sub-region.

Keywords: cross-border migration, border crimes, security, West Africa, development, globalisation

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Authors: Salha Abdullah Ali Al-Shamrani, Maha Muhammad Dhaher Aljuhani, Eman Ali Ahmed Aldhaheri

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With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: internet of things, spoofing, IoT, access control, blockchain, raspberry pi

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Authors: Mohammed Elsayed Lotfy Elsayed Abouzeid, Tomonobu Senjyu

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A novel multi-objective park and ride control approach is presented in this research. Park and ride will encourage the owners of the vehicles to leave their cars in the nearest points (on the edges of the crowded cities) and use public transportation facilities (train, bus, metro, or mon-rail) to reach their work inside the crowded city. The proposed control scheme is used to design electric vehicle charging stations (EVCS) to charge 1000 electric vehicles (EV) during their owners' work time. Cairo, Egypt is used as a case study. Photovoltaic (PV) and battery energy storage system (BESS) are used to meet the EVCS demand. Two multi-objective optimization techniques (MOGA and epsilon-MOGA) are utilized to get the optimal sizes of PV and BESS so as to meet the load demand and minimize the total life cycle cost. Detailed analysis and comparison are held to investigate the performance of the proposed control scheme using MATLAB.

Keywords: Battery Energy Storage System, Electric Vehicle, Park and Ride, Photovoltaic, Multi-objective

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Authors: Haythem H. Abdullah, Hesham Elkady

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With the fast increase in radio frequency identification (RFID) applications such as medical recording, library management, etc., the limitation of active tags stems from its need to external batteries as well as passive or active chips. The chipless RFID tag reduces the cost to a large extent but at the expense of utilizing the spectrum. The reduction of the cost of chipless RFID is due to the absence of the chip itself. The identification is done by utilizing the spectrum in such a way that the frequency response of the tags consists of some resonance frequencies that represent the bits. The system capacity is decided by the number of resonators within the pre-specified band. It is important to find a solution to enhance the spectrum utilization when using chipless RFID. Target identification is a process that results in a decision that a specific target is present or not. Several target identification schemes are present, but one of the most successful techniques in radar target identification in the oscillatory region is the extinction pulse technique (E-Pulse). The E-Pulse technique is used to identify targets via its characteristics (natural) modes. By introducing an innovative solution for chipless RFID reader and tag designs, the spectrum utilization goes to the optimum case. In this paper, a novel capacity enhancement scheme based on the E-pulse technique is introduced to improve the performance of the chipless RFID system.

Keywords: chipless RFID, E-pulse, natural modes, resonators

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Authors: Liang Zhao, Chongquan Zhong

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Introduction: According to statistics, people spend 80% to 90% of time indoor, so indoor air quality, either at home or in the office, greatly impacts the quality of life, health and work efficiency. Therefore, indoor air quality is very important to human activities. With the acceleration of urbanization, people are spending more time in indoor activity. The time in indoor environment, the living space, and the frequency interior decoration are all increasingly increased. However, housing decoration materials contain formaldehyde and other harmful substances, causing environmental and air quality problems, which have brought serious damage to countless families and attracted growing attention. According to World Health Organization statistics, the indoor environments in more than 30% of buildings in China are polluted by poisonous and harmful gases. Indoor pollution has caused various health problems, and these widespread public health problems can lead to respiratory diseases. Long-term inhalation of low-concentration formaldehyde would cause persistent headache, insomnia, weakness, palpitation, weight loss and vomiting, which are serious impacts on human health and safety. On the other hand, as for offices, some surveys show that good indoor air quality helps to enthuse the staff and improve the work efficiency by 2%-16%. Therefore, people need to further understand the living and working environments. There is a need for easy-to-use indoor environment monitoring instruments, with which users only have to power up and monitor the environmental parameters. The corresponding real-time data can be displayed on the screen for analysis. Environment monitoring should have the sensitive signal alarm function and send alarm when harmful gases such as formaldehyde, CO, SO2, are excessive to human body. System design: According to the monitoring requirements of various gases, temperature and humidity, we designed a portable, light, real-time and accurate monitor for various environmental parameters, including temperature, humidity, formaldehyde, methane, and CO. This monitor will generate an alarm signal when a target is beyond the standard. It can conveniently measure a variety of harmful gases and provide the alarm function. It also has the advantages of small volume, convenience to carry and use. It has a real-time display function, outputting the parameters on the LCD screen, and a real-time alarm function. Conclusions: This study is focused on the research and development of a portable parameter monitoring instrument for indoor environment. On the platform of an STM32 development board, the monitored data are collected through an external sensor. The STM32 platform is for data acquisition and processing procedures, and successfully monitors the real-time temperature, humidity, formaldehyde, CO, methane and other environmental parameters. Real-time data are displayed on the LCD screen. The system is stable and can be used in different indoor places such as family, hospital, and office. Meanwhile, the system adopts the idea of modular design and is superior in transplanting. The scheme is slightly modified and can be used similarly as the function of a monitoring system. This monitor has very high research and application values.

Keywords: indoor air quality, gas concentration detection, embedded system, sensor

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Authors: Hameda Suwaed

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In today's world, knowledge and information are increasing in a way that no one can learn everything about every subject and the jobs that students will get after graduation may not yet exist. Therefore, teaching them just facts without teaching them how to use the facts in real life, how to work in a team and how to think critically is no longer enough. In Libya, a country characterized by using traditional methods of teaching, how can English language teachers train students to use such skills? And what type of activities and adaptations to classroom teaching methods will be necessary to do this? Using action research and classroom research gathered data, this study adjusts Heath's (2010) model of change that includes giving students clear directions, sufficient motivation and supportive environment. These steps were applied by encouraging students to participate actively in the classroom by using group work and variety of activities to train them how to find, interpret and use information. The findings of the study showed that following the suggested model can broaden students' perspectives on studying in their environment starting with their classroom and ending with their country. In conclusion, although this was a small scale study, the students' participation in the classroom shows that they gained self confidence in using practices such as group work, critical thinking, time management, creativity and how to present their ideas and accepting different opinions. What was remarkable is that most students were aware that is what we need in Libya nowadays.

Keywords: change, classroom practice, skills, Libya, group work

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Elham Fakhrpoor, Daryush Mohammadi Zanjirani, Maziyar Nojaba

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Business process reengineering is one of the most important strategies in banks in recent years that not only it increases customers’ satisfaction, but also it increases performance of banks. The purpose of elementary (initial) business process reengineering is reinforcing banks abilities to obtain new customers and making long-term relationships with existed customers and increasing customers’ satisfaction among service quality in global level. Banks specially the private ones are the main streams of state, because cash flow is necessary to survive a state. What guarantees survival and permanency of financial institutes’ activities is providing favorite, certain, and proper services. Capital market being small and state financial system being bank-oriented needs optimum usage from banks. According to this fact and role and importance of developing banking system, the present study tried to offer a constructed model using Lisrel and also spss software to evaluate effects of business process reengineering on performance of private banks. We have one min hypothesis and four sub-hypotheses. The main hypothesis says reengineering factors have positive effects on bank performances (balanced- scores card aspects). These hypotheses were tested by structural equations modeling.

Keywords: effect, business, reengineering, private bank

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Authors: Hanlin Liu, Hua Li, Yintan AI

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Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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Authors: Menelaos N. Katsantonis, Athanasios Manikas, Alexandros Chatzis, Stavros Doropoulos, Anastasios Avramis, Ioannis Mavridis

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Museums enhance their potential by adopting new technologies and techniques to appeal to more visitors and engage them in creative and joyful activities. In this study, the Haptic Cycle is presented, a cycle of museum activities proposed for the development of museum learning approaches with optimized effectiveness and engagement. Haptic Cycle envisages the improvement of the museum’s services by offering a wide range of activities. Haptic Cycle activities make the museum’s exhibitions more approachable by bringing them closer to the visitors. Visitors can interact with the museum’s artifacts and explore them haptically and sonically. Haptic Cycle proposes constructivist learning activities in which visitors actively construct their knowledge by exploring the artifacts, experimenting with them and realizing their importance. Based on the Haptic Cycle, we developed the HapticSOUND system, an innovative virtual reality system that includes an advanced user interface that employs gesture-based technology. HapticSOUND’s interface utilizes the leap motion gesture recognition controller and a 3D-printed traditional Cretan lute, utilized by visitors to perform various activities such as exploring the lute and playing notes and songs.

Keywords: haptic cycle, HapticSOUND, museum learning, gesture-based, leap motion

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Authors: A. Alao Olumuyiwa

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Health hazards reported to be associated with exposure to electromagnetic radiations which include brain tumors, genotoxic effects, neurological effects, immune system deregulation, allergic responses and some cardiovascular effects are discussed under a closed tabular model in this study. This review however showed that there is strong and robust evidence that chronic exposures to electromagnetic frequency across the spectrum, through strength, consistency, biological plausibility and many dose-response relationships, may result in brain cancer and other carcinogenic disease symptoms. There is therefore no safe threshold because of the genotoxic nature of the mechanism that may however be involved. The discussed study explains that the cell phone has induced effects upon the blood –brain barrier permeability and the cerebellum exposure to continuous long hours RF radiation may result in significant increase in albumin extravasations. A physical Biomodeling approach is however employed to review this health effects using Specific Absorption Rate (SAR) of different GSM machines to critically examine the symptoms such as a decreased loco motor activity, increased grooming and reduced memory functions in a variety of animal spices in classified grouped and sub grouped models.

Keywords: brain cancer, electromagnetic radiations, physical biomodeling, specific absorption rate (SAR)

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Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Dae-gun Kim, Hyun-joo Kang

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Purpose: The purpose of this study was to investigate the effects of aging on center of pressure, gait angle and gait time. Methods: 29 healthy female college students(FCS) and 28 elderly women (EW) were recruited to participate in this study. A gait analysis system( Gaitview, Korea) was used to collect the center of pressure in static state and gait angle with gait time in dynamic state. Results: Results of the center of pressure do not have significant differences between two groups. In the gait angle test, the FCS showed 1.56±5.2° on their left while the EW showed 9.76±6.54° on their left. In their right, the FCS showed 2.85±6.47° and the EW showed 10.27±6.97°. In the gait angle test, there was a significant difference in the gait time between the female college students and elderly women. A significant difference was evident in the gait time. The FCS on the left was 0.87±0.1sec while the EW’s was 1.28±0.44sec. The FCS on the right was 0.86±0.09sec and the EW was 1.1±0.21sec. The results of this study revealed that the elderly participants aging musculoskeletal system and subsequent changes in their posture altered gait angle and gait time. Therefore, this widening is due to their need to leave their feet on the ground longer for stability slowing their movement. Conclusions: In conclusion, it is advisable to develop an exercise program for the elderly focusing on stability the prevention of falls.

Keywords: center of pressure, gait angle, gait time, elderly women

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Authors: Cao Jiayu, Lan Ximing, Huang Jingjia, Burra Venkata Durga Kumar

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The first virus to attack personal computers was born in early 1986, called C-Brain, written by a pair of Pakistani brothers. In those days, people still used dos systems, manipulating computers with the most basic command lines. In the 21st century today, computer performance has grown geometrically. But computer viruses are also evolving and escalating. We never stop fighting against security problems. Stack overflow is one of the most common security vulnerabilities in operating systems. It may result in serious security issues for an operating system if a program in it has a vulnerability with administrator privileges. Certain viruses change the value of specific memory through a stack overflow, allowing computers to run harmful programs. This study developed a mechanism to detect and respond to time whenever a stack overflow occurs. We demonstrate the effectiveness of standard machine learning algorithms and control flow enforcement techniques in predicting computer OS security using generating suspicious vulnerability functions (SVFS) and associated suspect areas (SAS). The method can minimize the possibility of stack overflow attacks occurring.

Keywords: operating system, security, stack overflow, buffer overflow, machine learning, control-flow enforcement technology

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Authors: Awatif Habeeb Al-Shamare

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The number of social media users amongst special education teachers and parents of children with Down Syndrome (DS) is increasing annually. This is also the case in the Kingdom of Saudi Arabia (KSA). However, according to the best of the author’s knowledge, there are no qualitative studies which testify to the true nature of the interaction between teachers and parents when using social media, nor the role of social media in supporting and assisting parents and teachers with regards to the children’s educational needs in KSA. Therefore, this ongoing study aims to identify the role of social media in supporting parents and teachers of DS students, with a special emphasis on early intervention services in KSA. By bridging the knowledge gap on social media and special education in KSA and presenting socially relevant and applied information on the topic, this research provides a theoretical and practical base for the establishment of appropriate and effective programmes between the ministries of Information and Special Education in particular. A qualitative approach was selected because it was the most suitable approach for exploring the participants’ experiences, which could not be determined through scientific tests. Interviewing, chosen as the research instrument, allowed the researcher to obtain a detailed understanding of the topic linked to the study objectives. Initially, a pilot study was conducted at the Daycare Center in May 2016. Its aim was to examine and refine the methodology and assess whether the questions were understood with the potential for re-drafting them, if necessary. The main study consists of five teachers and five mothers with experience of using social media and with links to the Daycare Center. Thematic Analysis has been chosen for analysing the findings because it is a flexible method that allows themes to emerge from the data. Results of the current study are still in the initial stages, but the preliminary findings are as follows: (1) social media is an important tool in encouraging parents and teachers to access the necessary information and knowledge about, and experience in, early intervention services; (2) it acts as a support network for the parents; (3) it helps raise awareness about DS and the need for early intervention; (4) it can be used to put pressure on the government for an expansion in early intervention services, and finally (5) its use can be problematic in that parents and teachers face some difficulties and challenges when using the different platforms. It can be concluded that social media plays a significant role in the lives of teachers and parents with special needs children in KSA.

Keywords: down syndrome, early intervention services, social media, support parents and teachers

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Authors: G. W. Greubel, A. Kalam

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South Africa finds itself at a confluence of forces where the national electricity supply system is constrained with under-supply primarily from old and failing coal-fired power stations and congested and inadequate transmission and distribution systems. Simultaneously the country attempts to meet carbon reduction targets driven by both an alignment with international goals and a consumer-driven requirement. The constrained electricity system is an aspect of an economy characterized by very low economic growth, high unemployment, and frequent and significant load shedding. The fiscus does not have the funding to build new generation capacity or strengthen the grid. The under-supply is increasingly alleviated by the penetration of wind and solar generation capacity and embedded roof-top solar. However, this increased penetration results in less inertia, less synchronous generation, and less capability for fast frequency response, with resultant instability. The renewable energy facilities assist in solving the under-supply issues, but merely ‘kick the can down the road’ by not contributing to grid stability or by substituting the lost inertia, thus creating an expanding issue for the grid to manage. By technically balancing its electricity demand and supply a company with facilities located across the country can be spared the effects of load shedding, and thus ensure financial and production performance, protect jobs, and contribute meaningfully to the economy. By treating the company’s load (across the country) and its various distributed generation facilities as a ‘virtual grid’ which by design will provide ancillary services to the grid one is able to create a win-win situation for both the company and the grid. This paper provides a review of the technical problems facing the South African electricity system and discusses a hypothetical ‘virtual grid’ concept that may assist in solving the problems. The proposed solution has potential application across emerging markets with constrained power infrastructure or for companies who wish to be entirely powered by renewable energy.

Keywords: load shedding, renewable energy integration, smart grid, virtual grid

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Authors: Kenneth O. Otasowie, Matthew Ikuabe, Clinton Aigbavboa, Ayodeji Oke

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The quantity surveying (QS) profession is one of the professions in the construction industry, and it is saddled with the responsibility of measuring the number of materials as well as the workmanship required to get work done in the industry. This responsibility is vital to the success of a construction project as it determines if a project will be completed on time, within budget, and up to the required standard. However, the practice has been criticised severally for failure to accurately execute her responsibility. The need to reduce errors, inaccuracies and omissions has made the adoption of modern technologies such as building information modeling (BIM) inevitable in its practice. Nevertheless, there are barriers to the adoption of BIM in QS practice in South Africa (SA). Thus, this study aims to investigate these barriers. A survey design was adopted. A total number of one hundred and fifteen (115) questionnaires were administered to quantity surveyors in Guateng Province, SA, and ninety (90) were returned and found suitable for analysis. Collected data were analysed using percentage, mean item score, standard deviation, one-sample t-test, and Kruskal-Wallis. The findings show that lack of BIM expertise, lack of government enforcement, resistance to change, and no client demand for BIM are the most significant barriers to the adoption of BIM in QS practice. As a result, this study recommends that trainings on BIM technology be prioritised, and government must take the lead in BIM adoption in the country, particularly in public projects.

Keywords: barriers, BIM, quantity surveying practice, South Africa

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Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

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Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

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Authors: Areej Al-Hamad, Cheryl Forchuk, Abe Oudshoorn, Gerald Patrick Mckinley

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Syrian refugee women face many obstacles when accessing health services in host countries that are influenced by various cultural, structural, and practical factors. This paper is based on critical ethnographic research undertaken in Canada to explore Syrian refugee women's migration experiences. Also, we aim to critically examine how the intersection of gender, trauma, violence and the political and economic conditions of Syrian refugee women shapes their everyday lives and health. The study also investigates the strategies and practices by which Syrian refugee women are currently addressing their healthcare needs and the models of care that are suggested for meeting their physical and mental health needs. Findings show that these women experienced constant worries, hardship, vulnerability, and intrusion of dignity. These experiences and challenges were aggravated by the structure of the Canadian social and health care system. This study offers a better understanding of the impact of migration and trauma on Syrian refugee women's roles, responsibilities, gender dynamics, and interaction with Ontario's healthcare system to improve interaction and outcomes. Health care models should address these challenges among Syrian refugee families in Canada.

Keywords: Syrian refugee women, intersectionality, critical ethnography, migration

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Authors: Kurt Willems

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This research examines complaints against grading in higher education institutions in four different European regions: England and Wales, Flanders, the Netherlands, and France. The aim of the research is to examine the correlation between the applicable type of complaint handling on the one hand, and selected qualities of the higher education landscape and of public law on the other hand. All selected regions report a rising number of complaints against grading decisions, not only as to internal complaint handling within the institution but also judicially if the dispute persists. Some regions deem their administrative court system appropriate to deal with grading disputes (France) or have even erected a specialty administrative court to facilitate access (Flanders, the Netherlands). However, at the same time, different types of (governmental) dispute resolution bodies have been established outside of the judicial court system (England and Wales, and to lesser extent France and the Netherlands). Those dispute procedures do not seem coincidental. Public law issues such as the underlying legal nature of the education institution and, eventually, the grading decision itself, have an impact on the way the academic complaint procedures are developed. Indeed, in most of the selected regions, contractual disputes enjoy different legal protection than administrative decisions, making the legal qualification of the relationship between student and higher education institution highly relevant. At the same time, the scope of competence of government over different types of higher education institutions; albeit direct or indirect (o.a. through financing and quality control) is relevant as well to comprehend why certain dispute handling procedures have been established for students. To answer the above questions, the doctrinal and comparative legal method is used. The normative framework is distilled from the relevant national legislative rules and their preparatory texts, the legal literature, the (published) case law of academic complaints and the available governmental reports. The research is mainly theoretical in nature, examining different topics of public law (mainly administrative law) and procedural law in the context of grading decisions. The internal appeal procedure within the education institution is largely left out of the scope of the research, as well as different types of non-governmental-imposed cooperation between education institutions, given the public law angle of the research questions. The research results in the categorization of different academic complaint systems, and an analysis of the possibility to introduce each of those systems in different countries, depending on their public law system and higher education system. By doing so, the research also adds to the debate on the public-private divide in higher education systems, and its effect on academic complaints handling.

Keywords: higher education, legal qualification of education institution, legal qualification of grading decisions, legal protection of students, academic litigation

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Authors: Zainab Bashir

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There has been a lot of quantitative research on end-stage renal disease (ESRD), its implications, psychological effects and so on across the world, however little qualitative information is available on coping strategies and illness role adaptations specific to renal failure. This article attempts to learn about illness roles and coping strategies specific to aged ESRD patients on hemodialysis in Lahore. The patients were interviewed on a structured schedule and were asked questions on tasks and coping related to physical, psychological, and social consequences of renal failure. Standardised techniques and methods of grounded theory were used to analyse and code the information in this small-scale, in-depth study. An analysis of tasks faced by the ESRD patients and coping they employ to fulfill or overcome those tasks were done. This analysis was based on three different types of data: experiential accounts of ESRD patients with respect to tasks and strategies for coping, coping styles and illness roles typologies, and monographs of coping styles. In the information gathered using interviews with respondents, three styles of problem focused coping, and two styles of emotion focused coping could be identified. Problem focused coping included making physical adjustments to suit the requirements of the health condition, including dialysis and medical regime as integral part of patients’ lives, and altering future plans according to the course of the disease. Emotion focused coping included seeking help to manage stress/anxiety and resenting the disease condition and giving up. These coping styles are linked to the illness roles assigned to the respondents. In conclusion, there is no single formula to deal with the disease, however, some typologies can be established. In most of the cases discussed in the paper, adjustment to a regular dialysis routine, restriction in bodily function, inability to work and negative impacts on family life, especially spousal relationships have come to fore as common problems. A large part of coping with these problems had to do with mentally accepting the disease and carrying on despite. These cannot be seen as deviant adaptations to the depressive situation arising from renal failure, but more of patterned ways in which patients can approximate a close to normal lifestyle despite the terminal disease.

Keywords: coping strategies, ESRD patients, hemodialysis, illness roles

Procedia PDF Downloads 107