Search results for: gravitational search algorithm

Authors: Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin

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The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Nokoue Lake in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Nokoue Lake, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué Lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

Keywords: forecasting, long short-term memory cell, recurrent artificial neural network, Nokoué lake

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Authors: Laura Canagueral-Pellice, Antonio Munar-Frau, Adaia Valls-Ontanon, Joao Carames, Federico Hernandez-Alfaro, Jordi Caballe-Serrano

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Objective: Guided bone regeneration (GBR) aims to replace the missing bone with a new structure to achieve long-term stability of rehabilitations. The aim of the present systematic review and meta-analysis is to determine the effect of barrier membranes on histological outcomes after GBR procedures. Moreover, the effect of the grafting material and tissue gain were analyzed. Materials & methods: Two independent reviewers performed an electronic search in Pubmed and Scopus, identifying all eligible publications up to March 2020. Only randomized controlled trials (RCTs) assessing a histological analysis of augmented areas were included. Results: A total of 6 publications were included for the present systematic review. A total of 110 biopsied sites were analysed; 10 corresponded to vertical bone augmentation procedures, whereas 100 analysed horizontal regeneration procedures. A mean tissue gain of 3 ± 1.48mm was obtained for horizontal defects. Histological assessment of new bone formation, residual particle and sub-epithelial connective tissue (SCT) was reported. The four main barrier membranes used were natural collagen membranes, e-PTFE, polylactic resorbable membranes and acellular dermal matrix membranes (AMDG). The analysis demonstrated that resorbable membranes result in higher values of new bone formation and lower values of residual particles and SCT. Xenograft resulted in lower new bone formation compared to allograft; however, no statistically significant differences were observed regarding residual particle and SCT. Overall, regeneration procedures adding autogenous bone, plasma derivate or growth factors achieved in general greater new bone formation and tissue gain. Conclusions: There is limited evidence favoring the effect of a certain type of barrier membrane in GBR. Data needs to be evaluated carefully; however, resorbable membranes are correlated with greater new bone formation values, especially when combined with allograft materials and/or the addition of autogenous bone, platelet reach plasma (PRP) or growth factors in the regeneration area. More studies assessing the histological outcomes of different GBR protocols and procedures testing different biomaterials are needed to maximize the clinical and histological outcomes in bone regeneration science.

Keywords: barrier membrane, graft material, guided bone regeneration, implant surgery, histology

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Authors: Ekaterina G. Lipatova

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The developing potential of a video task in teaching foreign languages involves the opportunities to improve four aspects of speech production process: listening, reading, speaking and writing. A video represents the sequence of actions, realized in the pictures logically connected and verbalized speech flow that simplifies and stimulates the process of perception. In this connection listening skills of students are developed effectively as well as their intellectual properties such as synthesizing, analyzing and generalizing the information. In terms of teaching capacity, a video task, in our opinion, is more stimulating than a traditional listening, since it involves the student into the plot of the communicative situation, emotional background and potentially makes them react to the gist in the cognitive and communicative ways. To be an effective method of teaching the video task should be structured in the way of psycho-linguistic characteristics of speech production process, in other words, should include three phases: before-watching, while-watching and after-watching. The system of tasks provided to each phase might involve the situations on reflecting to the video content in the forms of filling-the-gap tasks, multiple choice, True-or-False tasks (reading skills), exercises on expressing the opinion, project fulfilling (writing and speaking skills). In the before-watching phase we offer the students to adjust their perception mechanism to the topic and the problem of the chosen video by such task as “what do you know about such a problem?”, “is it new for you?”, “have you ever faced the situation of…?”. Then we proceed with the lexical and grammatical analysis of language units that form the body of a speech sample to lessen the perception and develop the student’s lexicon. The goal of while-watching phase is to build the student’s awareness about the problem presented in the video and challenge their inner attitude towards what they have seen by identifying the mistakes in the statements about the video content or making the summary, justifying their understanding. Finally, we move on to development of their speech skills within the communicative situation they observed and learnt by stimulating them to search the similar ideas in their backgrounds and represent them orally or in the written form or express their own opinion on the problem. It is compulsory to highlight, that a video task should contain the urgent, valid and interesting event related to the future profession of the student, since it will help to activate cognitive, emotional, verbal and ethic capacity of students. Also, logically structured video tasks are easily integrated into the system of e-learning and can provide the opportunity for the students to work with the foreign language on their own.

Keywords: communicative situation, perception mechanism, speech production process, speech skills

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Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

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Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530

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Authors: Khrystyna Pavlyk

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In the OECD countries, percentage of adults with higher education degrees has increased by 10 % during 2000-2010. Continuously increasing demand for higher education gives universities a chance of becoming key players in socio-economic development of a territory (region or city) via knowledge creation, knowledge transfer, and knowledge spillovers. During previous decade, universities have tried to support spin-offs and start-ups, introduced courses on sustainability and corporate social responsibility. While much has been done, new trends are starting to emerge in search of better approaches. Recently a number of universities created centers that conduct research in a field social entrepreneurship, which in turn underpin educational programs run at these universities. The list includes but is not limited to the Centre for Social Economy at University of Liège, Institute for Social Innovation at ESADE, Skoll Centre for Social Entrepreneurship at Oxford, Centre for Social Entrepreneurship at Rosklide, Social Entrepreneurship Initiative at INSEAD. Existing literature already examined social entrepreneurship centers in terms of position in the institutional structure, initial and additional funding, teaching initiatives, research achievements, and outreach activities. At the same time, Universities can become social enterprises themselves. Previous research revealed that universities use both business and social entrepreneurship models. Universities which are mainly driven by a social mission are more likely to transform into social entrepreneurial institutions. At the same time, currently, there is no clear understanding of what social entrepreneurship in higher education is about and thus social entrepreneurship in higher education needs to be studied and promoted at the same time. Main roles which socially oriented university can play in city development include: buyer (implementation of socially focused local procurement programs creates partnerships focused on local sustainable growth.); seller (centers created by universities can sell socially oriented goods and services, e.g. in consultancy.); employer (Universities can employ socially vulnerable groups.); business incubator (which will help current student to start their social enterprises). In the paper, we will analyze these in more detail. We will also examine a number of indicators that can be used to assess the impact, both direct and indirect, that universities can have on city's economy. At the same time, originality of this paper mainly lies not in methodological approaches used, but in countries evaluated. Social entrepreneurship is still treated as a relatively new phenomenon in post-transitional countries where social services were provided only by the state for many decades. Paper will provide data and example’s both from developed countries (the US and EU), and those located in CIS and CEE region.

Keywords: social enterprise, university, regional economic development, comparative study

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Authors: Mohammed Bnebaghdad, Feriel Betouche, Malika Semmani

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Image processing become more sophisticated over time due to technological advances, especially artificial intelligence (AI) technology. Currently, AI image processing is used in many areas, including surveillance, industry, science, and medicine. AI in medical image processing can help doctors diagnose diseases faster, with minimal mistakes, and with less effort. Among these diseases is malaria, which remains a major public health challenge in many parts of the world. It affects millions of people every year, particularly in tropical and subtropical regions. Early detection of malaria is essential to prevent serious complications and reduce the burden of the disease. In this paper, we propose and implement a scheme based on AI image processing to enhance malaria disease diagnosis through automated analysis of blood smear images. The scheme is based on the convolutional neural network (CNN) method. So, we have developed a model that classifies infected and uninfected single red cells using images available on Kaggle, as well as real blood smear images obtained from the Central Laboratory of Medical Biology EHS Laadi Flici (formerly El Kettar) in Algeria. The real images were segmented into individual cells using the watershed algorithm in order to match the images from the Kaagle dataset. The model was trained and tested, achieving an accuracy of 99% and 97% accuracy for new real images. This validates that the model performs well with new real images, although with slightly lower accuracy. Additionally, the model has been embedded in a Raspberry Pi4, and a graphical user interface (GUI) was developed to visualize the malaria diagnostic results and facilitate user interaction.

Keywords: medical image processing, malaria parasite, classification, CNN, artificial intelligence

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Authors: Rudy Bahouth, Farouk Benmeddour, Emmanuel Moulin, Jamal Assaad

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Guided ultrasonic waves are used in Non-Destructive Testing (NDT) and Structural Health Monitoring (SHM) for inspection and damage detection. Recently, wireless data transmission using ultrasonic waves in solid metallic channels has gained popularity in some industrial applications such as nuclear, aerospace and smart vehicles. The idea is to find a good substitute for electromagnetic waves since they are highly attenuated near metallic components due to Faraday shielding. The proposed solution is to use ultrasonic guided waves such as Lamb waves as an information carrier due to their capability of propagation for long distances. In addition to this, valuable information about the health of the structure could be extracted simultaneously. In this work, the reliable frequency bandwidth for communication is extracted experimentally from dispersion curves at first. Then, an experimental platform for wireless communication using Lamb waves is described and built. After this, coherent demodulation algorithm used in telecommunications is tested for Amplitude Shift Keying, On-Off Keying and Binary Phase Shift Keying modulation techniques. Signal processing parameters such as threshold choice, number of cycles per bit and Bit Rate are optimized. Experimental results are compared based on the average Bit Error Rate. Results have shown high sensitivity to threshold selection for Amplitude Shift Keying and On-Off Keying techniques resulting a Bit Rate decrease. Binary Phase Shift Keying technique shows the highest stability and data rate between all tested modulation techniques.

Keywords: lamb waves communication, wireless communication, coherent demodulation, bit error rate

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Authors: Shi-xia Xu, Zai-wen Zhang, Ru-xue Chen, Shan Zhou, Xiang-feng Tang

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Objective: The clinical influence of HLA-DPB1 mismatches on clinical outcome of HSCT is less clear. This is the first meta-analysis to study the HLA-DPB1 matching statues on clinical outcomes after unrelated donor HSCT. Methods: We searched the CIBMTR, Cochrane Central Register of Controlled Trials (CENTRAL) and related databases (1995.01–2017.06) for all relevant articles. Comparative studies were used to investigate the HLA-DPB1 loci mismatches on clinical outcomes after unrelated donor HSCT, such as the disease-free survival (DFS), overall survival, GVHD, relapse, and transplant-related mortality (TRM). We performed meta-analysis using Review Manager 5.2 software and funnel plot to assess the bias. Results: At first, 1246 articles were retrieved, and 18 studies totaling 26368 patients analyzed. Pooled comparisons of studies found that the HLA-DPB1 mismatched group had a lower rate of DFS than the DPB1-matched group, and lower OS in non-T cell depleted transplantation. The DPB1 mismatched group has a higher incidence of aGVHD and more severe ( ≥ III degree) aGvHD, lower rate of relapse and higher TRM. Moreover, compared with 1-antigen mismatch, 2-antigen mismatched led to a higher risk of TRM and lower relapse rate. Conclusions: This meta-analysis indicated HLA-DPB1 has important influence on survival and transplant-related complications during unrelated donor HSCT and HLA-DPB1 donor selection strategies have been proposed based on a personalized algorithm.

Keywords: human leukocyte antigen, DPB1, transplant, meta-analysis, outcome

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Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

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Authors: Elisabetta Cianfanelli, Margherita Tufarelli, Paolo Pupparo

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The dialectical mediation between desires and objects or between mass production and consumption continues to evolve over time. This relationship is influenced both by variable geometries of contexts that are distant from the mere design of product form and by aspects rooted in the very definition of industrial design. In particular, the overcoming of macro-areas of innovation in the technological, social, cultural, formal, and morphological spheres, supported by recent theories in critical and speculative design, seems to be moving further and further away from the design of the formal dimension of advanced products. The articulated fabric of theories and practices that feed the definition of “hyperobjects”, and no longer objects describes a common tension in all areas of design and production of industrial products. The latter are increasingly detached from the design of the form and meaning of the same in mass productions, thus losing the quality of products capable of social transformation. For years we have been living in a transformative moment as regards the design process in the definition of the industrial product. We are faced with a dichotomy in which there is, on the one hand, a reactionary aversion to the new techniques of industrial production and, on the other hand, a sterile adoption of the techniques of mass production that we can now consider traditional. This ambiguity becomes even more evident when we talk about industrial products, and we realize that we are moving further and further away from the concepts of "form" as a synthesis of a design thought aimed at the aesthetic-emotional component as well as the functional one. The design of forms and their contents, as statutes of social acts, allows us to investigate the tension on mass production that crosses seasons, trends, technicalities, and sterile determinisms. The design culture has always determined the formal qualities of objects as a sum of aesthetic characteristics functional and structural relationships that define a product as a coherent unit. The contribution proposes a reflection and a series of practical experiences of research on the form of advanced products. This form is understood as a kaleidoscope of relationships through the search for an identity, the desire for democratization, and between these two, the exploration of the aesthetic factor. The study of form also corresponds to the study of production processes, technological innovations, the definition of standards, distribution, advertising, the vicissitudes of taste and lifestyles. Specifically, we will investigate how the genesis of new forms for new meanings introduces a change in the relative innovative production techniques. It becomes, therefore, fundamental to investigate, through the reflections and the case studies exposed inside the contribution, also the new techniques of production and elaboration of the forms of the products, as new immanent and determining element inside the planning process.

Keywords: industrial design, product advanced design, mass productions, new meanings

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Authors: Mulugeta K. Tefera, Xiaolong Yang, Jian Liu

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Detection and tracking of moving objects are very important in many application contexts such as detection and recognition of people, visual surveillance and automatic generation of video effect and so on. However, the task of detecting a real shape of an object in motion becomes tricky due to various challenges like dynamic scene changes, presence of shadow, and illumination variations due to light switch. For such systems, once the moving object is detected, tracking is also a crucial step for those applications that used in military defense, video surveillance, human computer interaction, and medical diagnostics as well as in commercial fields such as video games. In this paper, an object presents in dynamic background is detected using adaptive mixture of Gaussian based analysis of the video sequences. Then the detected moving object is tracked using the region based moving object tracking and inter-frame differential mechanisms to address the partial overlapping and occlusion problems. Firstly, the detection algorithm effectively detects and extracts the moving object target by enhancing and post processing morphological operations. Secondly, the extracted object uses region based moving object tracking and inter-frame difference to improve the tracking speed of real-time moving objects in different video frames. Finally, the plotting method was applied to detect the moving objects effectively and describes the object’s motion being tracked. The experiment has been performed on image sequences acquired both indoor and outdoor environments and one stationary and web camera has been used.

Keywords: background modeling, Gaussian mixture model, inter-frame difference, object detection and tracking, video surveillance

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Authors: Kwaku Damoah

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The agricultural sector is characterized by continuous transformation, driven by factors such as demographic shifts, evolving consumer preferences, climate change, and migration trends. This dynamic environment presents complex challenges for key stakeholders including farmers, governments, and investors, who must navigate these changes to achieve optimal investment returns. To effectively predict market trends and uncover promising investment opportunities, a systematic, data-driven approach is essential. This paper introduces the Structural Evolution Index (SEI), a machine learning-based methodology. SEI is specifically designed to analyse long-term trends and forecast the potential of emerging agricultural products for investment. Versatile in application, it evaluates various agricultural metrics such as production, yield, trade, land use, and consumption, providing a comprehensive view of the evolution within agricultural markets. By harnessing data from the UN Food and Agricultural Organisation (FAOSTAT), this study demonstrates the SEI's capabilities through Comparative Exploratory Analysis and evaluation of international trade in agricultural products, focusing on Malaysia and Singapore. The SEI methodology reveals intricate patterns and transitions within the agricultural sector, enabling stakeholders to strategically identify and capitalize on emerging markets. This predictive framework is a powerful tool for decision-makers, offering crucial insights that help anticipate market shifts and align investments with anticipated returns.

Keywords: agricultural investment, algorithm, comparative exploratory analytics, machine learning, market trends, predictive analytics, structural evolution index

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Authors: Ariq Bani Hardi

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Empowerment of smartphone technology is growing very rapidly in various fields of science. One of the mobile operating systems that dominate the smartphone market today is Android by Google. Unfortunately, the expansion of mobile technology is misused by criminals to hide the information that they store or exchange with each other. It makes law enforcement more difficult to prove crimes committed in the judicial process (anti-forensic). One of technique that used to hide the information is encryption, such as the usages of SMS encryption applications. A Mobile Forensic Examiner or an investigator should prepare a countermeasure technique if he finds such things during the investigation process. This paper will discuss an extension procedure if the investigator found unreadable SMS in android evidence because of encryption. To define the extended procedure, we create and analyzing a dataset of android SMS encryption application. The dataset was grouped by application characteristics related to communication permissions, as well as the availability of source code and the documentation of encryption scheme. Permissions indicate the possibility of how applications exchange the data and keys. Availability of the source code and the encryption scheme documentation can show what the cryptographic algorithm specification is used, how long the key length, how the process of key generation, key exchanges, encryption/decryption is done, and other related information. The output of this paper is an extended or alternative procedure for examination and analysis process of android digital forensic. It can be used to help the investigators while they got a confused cause of SMS encryption during examining and analyzing. What steps should the investigator take, so they still have a chance to discover the encrypted SMS in android evidence?

Keywords: anti-forensic countermeasure, SMS encryption android, examination and analysis, digital forensic

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Authors: María Reveles-Miranda, Daniella Pacheco-Catalán

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Sierra Papacal commissary is located north of Merida, Yucatan, México, where the indigenous Maya population predominates. Due to its location, the region has an elevation of fewer than 4.5 meters above sea level, with a high risk of flooding associated with storms and hurricanes and a high vulnerability of infrastructure and housing in the presence of strong gusts of wind. In environmental contingencies, the challenge is providing an autonomous electrical supply using renewable energy sources that cover vulnerable populations' health, food, and water pumping needs. To address this challenge, a hybrid energy storage module is proposed for the emergency photovoltaic (PV) system of the community shelter in Sierra Papacal, Yucatán, which combines high-energy-density batteries and high-power-density supercapacitors (SC) in a single module, providing a quick response to energy demand, reducing the thermal stress on batteries and extending their useful life. Incorporating SC in energy storage modules can provide fast response times to power variations and balanced energy extraction, ensuring a more extended period of electrical supply to vulnerable populations during contingencies. The implemented control strategy increases the module's overall performance by ensuring the optimal use of devices and balanced energy exploitation. The operation of the module with the control algorithm is validated with MATLAB/Simulink® and experimental tests.

Keywords: batteries, community shelter, environmental contingencies, hybrid energy storage, isolated photovoltaic system, supercapacitors

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Authors: I. L. Kim, J. Y. Lee, A. K. Tekile

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In consequence of the very high urbanization rate of Korea, the number of traffic noise damages in areas congested with population and facilities is steadily increasing. The current environmental noise levels data in major cities of the country show that the noise levels exceed the standards set for both day and night times. This research was about comparative analysis in search for optimal soundproof panel shape and design factor that can minimize sound reflection noise. In addition to the normal flat-type panel shape, the reflection noise reduction of swelling-type, combined swelling and curved-type, and screen-type were evaluated. The noise source model Nord 2000, which often provides abundant information compared to models for the similar purpose, was used in the study to determine the overall noise level. Based on vehicle categorization in Korea, the noise levels for varying frequency from different heights of the sound source (directivity heights of Harmonize model) have been calculated for simulation. Each simulation has been made using the ray-tracing method. The noise level has also been calculated using the noise prediction program called SoundPlan 7.2, for comparison. The noise level prediction was made at 15m (R1), 30 m (R2) and at middle of the road, 2m (R3) receiving the point. By designing the noise barriers by shape and running the prediction program by inserting the noise source on the 2nd lane to the noise barrier side, among the 6 lanes considered, the reflection noise slightly decreased or increased in all noise barriers. At R1, especially in the cases of the screen-type noise barriers, there was no reduction effect predicted in all conditions. However, the swelling-type showed a decrease of 0.7~1.2 dB at R1, performing the best reduction effect among the tested noise barriers. Compared to other forms of noise barriers, the swelling-type was thought to be the most suitable for reducing the reflection noise; however, since a slight increase was predicted at R2, further research based on a more sophisticated categorization of related design factors is necessary. Moreover, as swellings are difficult to produce and the size of the modules are smaller than other panels, it is challenging to install swelling-type noise barriers. If these problems are solved, its applicable region will not be limited to other types of noise barriers. Hence, when a swelling-type noise barrier is installed at a downtown region where the amount of traffic is increasing every day, it will both secure visibility through the transparent walls and diminish any noise pollution due to the reflection. Moreover, when decorated with shapes and design, noise barriers will achieve a visual attraction than a flat-type one and thus will alleviate any psychological hardships related to noise, other than the unique physical soundproofing functions of the soundproof panels.

Keywords: reflection noise, shaped noise barriers, sound proof panel, traffic noise

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Authors: Umer Malik, David Armstrong, Mark Ashworth, Alex Dregan, Veline L'Esperance, Lucy McDonnell, Mariam Molokhia, Patrick White

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Introduction: The microbiota lining epithelial surfaces is thought to play an important role in many human physiological functions including defense against pathogens and modulation of immune response. The microbiota is susceptible to disruption from external influences such as exposure to antibiotic medication. It is thought that antibiotic-induced disruption of the microbiota could predispose to pathogen overgrowth and invasion. We hypothesized that antibiotic use would be associated with increased risk of future infections. We carried out a systematic review of evidence of associations between antibiotic use and subsequent risk of community-acquired infections. Methods: We conducted a review of the literature for observational studies assessing the association between antibiotic use and subsequent community-acquired infection. Eligible studies were published before April 29th, 2016. We searched MEDLINE, EMBASE, and Web of Science and screened titles and abstracts using a predefined search strategy. Infections caused by Clostridium difficile, drug-resistant organisms and fungal organisms were excluded as their association with prior antibiotic use has been examined in previous systematic reviews. Results: Eighteen out of 21,518 retrieved studies met the inclusion criteria. The association between past antibiotic exposure and subsequent increased risk of infection was reported in 16 studies, including one study on Campylobacter jejuni infection (Odds Ratio [OR] 3.3), two on typhoid fever (ORs 5.7 and 12.2), one on Staphylococcus aureus skin infection (OR 2.9), one on invasive pneumococcal disease (OR 1.57), one on recurrent furunculosis (OR 16.6), one on recurrent boils and abscesses (Risk ratio 1.4), one on upper respiratory tract infection (OR 2.3) and urinary tract infection (OR 1.1), one on invasive Haemophilus influenzae type b (Hib) infection (OR 1.51), one on infectious mastitis (OR 5.38), one on meningitis (OR 2.04) and five on Salmonella enteric infection (ORs 1.4, 1.59, 1.9, 2.3 and 3.8). The effect size in three studies on Salmonella enteric infection was of marginal statistical significance. A further two studies on Salmonella infection did not demonstrate a statistically significant association between prior antibiotic exposure and subsequent infection. Conclusion: We have found an association between past antibiotic exposure and subsequent risk of a diverse range of infections in the community setting. Our findings provide evidence to support the hypothesis that prior antibiotic usage may predispose to future infection risk, possibly through antibiotic-induced alteration of the microbiota. The findings add further weight to calls to minimize inappropriate antibiotic prescriptions.

Keywords: antibiotic, infection, risk factor, side effect

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Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

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Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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Authors: Nasim Hashemi, Abbas Sheikhtaheri

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Telemedicine is the use of telecommunication and information technologies to provide health care services that would often not be consistently available in distant rural communities to people at these remote areas. Teleophthalmology is a branch of telemedicine that delivers eye care through digital medical equipment and telecommunications technology. Thus, teleophthalmology can overcome geographical barriers and improve quality, access, and affordability of eye health care services. Since teleophthalmology has been widespread applied in recent years, the aim of this study was to determine the different applications of teleophthalmology in the world. To this end, three bibliographic databases (Medline, ScienceDirect, Scopus) were comprehensively searched with these keywords: eye care, eye health care, primary eye care, diagnosis, detection, and screening of different eye diseases in conjunction with telemedicine, telehealth, teleophthalmology, e-services, and information technology. All types of papers were included in the study with no time restriction. We conducted the search strategies until 2015. Finally 70 articles were surveyed. We classified the results based on the’type of eye problems covered’ and ‘the type of telemedicine services’. Based on the review, from the ‘perspective of health care levels’, there are three level for eye health care as primary, secondary and tertiary eye care. From the ‘perspective of eye care services’, the main application of teleophthalmology in primary eye care was related to the diagnosis of different eye diseases such as diabetic retinopathy, macular edema, strabismus and aged related macular degeneration. The main application of teleophthalmology in secondary and tertiary eye care was related to the screening of eye problems i.e. diabetic retinopathy, astigmatism, glaucoma screening. Teleconsultation between health care providers and ophthalmologists and also education and training sessions for patients were other types of teleophthalmology in world. Real time, store–forward and hybrid methods were the main forms of the communication from the perspective of ‘teleophthalmology mode’ which is used based on IT infrastructure between sending and receiving centers. In aspect of specialists, early detection of serious aged-related ophthalmic disease in population, screening of eye disease processes, consultation in an emergency cases and comprehensive eye examination were the most important benefits of teleophthalmology. Cost-effectiveness of teleophthalmology projects resulted from reducing transportation and accommodation cost, access to affordable eye care services and receiving specialist opinions were also the main advantages of teleophthalmology for patients. Teleophthalmology brings valuable secondary and tertiary care to remote areas. So, applying teleophthalmology for detection, treatment and screening purposes and expanding its use in new applications such as eye surgery will be a key tool to promote public health and integrating eye care to primary health care.

Keywords: applications, telehealth, telemedicine, teleophthalmology

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Authors: Yogendra K. Karna, Lauren T. Bennett

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Fire-tolerant eucalypt forests are one of the major forest ecosystems of south-eastern Australia and thought to be highly resistant to frequent high severity wildfires. However, the impact of different severity wildfires on the canopy structure of fire-tolerant forest type is under-studied, and there are significant knowledge gaps in relation to the assessment of tree and stand level canopy structural dynamics and recovery after fire. Assessment of canopy structure is a complex task involving accurate measurements of the horizontal and vertical arrangement of the canopy in space and time. This study examined the utility of multitemporal, small-footprint lidar data to describe the changes in the horizontal and vertical canopy structure of fire-tolerant eucalypt forests seven years after wildfire of different severities from the tree to stand level. Extensive ground measurements were carried out in four severity classes to describe and validate canopy cover and height metrics as they change after wildfire. Several metrics such as crown height and width, crown base height and clumpiness of crown were assessed at tree and stand level using several individual tree top detection and measurement algorithm. Persistent effects of high severity fire 8 years after both on tree crowns and stand canopy were observed. High severity fire increased the crown depth but decreased the crown projective cover leading to more open canopy.

Keywords: canopy gaps, canopy structure, crown architecture, crown projective cover, multi-temporal lidar, wildfire severity

Procedia PDF Downloads 175

Authors: Mokopane Charles Marakalala

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Research shows that mobile fraud has grown exponentially in South Africa during the lockdown caused by the COVID-19 pandemic. According to the South African Banking Risk Information Centre (SABRIC), fraudulent online banking and transactions resulted in a sharp increase in cybercrime since the beginning of the lockdown, resulting in a huge loss to the banking industry in South Africa. While the Financial Intelligence Centre Act, 38 of 2001, regulate financial transactions, it is evident that criminals are making use of technology to their advantage. Money-laundering ranks among the major crimes, not only in South Africa but worldwide. This paper focuses on the impact of biometric-based solutions in combatting mobile fraud at the South African Risk Information. SABRIC had the challenges of a successful mobile fraud; cybercriminals could hijack a mobile device and use it to gain access to sensitive personal data and accounts. Cybercriminals are constantly looting the depths of cyberspace in search of victims to attack. Millions of people worldwide use online banking to do their regular bank-related transactions quickly and conveniently. This was supported by the SABRIC, who regularly highlighted incidents of mobile fraud, corruption, and maladministration in SABRIC, resulting in a lack of secure their banking online; they are vulnerable to falling prey to fraud scams such as mobile fraud. Criminals have made use of digital platforms since the development of technology. In 2017, 13 438 instances involving banking apps, internet banking, and mobile banking caused the sector to suffer gross losses of more than R250,000,000. The final three parties are forced to point fingers at one another while the fraudster makes off with the money. A non-probability sampling (purposive sampling) was used in selecting these participants. These included telephone calls and virtual interviews. The results indicate that there is a relationship between remote online banking and the increase in money-laundering as the system allows transactions to take place with limited verification processes. This paper highlights the significance of considering the development of prevention mechanisms, capacity development, and strategies for both financial institutions as well as law enforcement agencies in South Africa to reduce crime such as money-laundering. The researcher recommends that strategies to increase awareness for bank staff must be harnessed through the provision of requisite training and to be provided adequate training.

Keywords: biometric-based solution, investigation, cybercrime, forensic investigation, fraud, combatting

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Authors: Brenda Thean I. Lim, Safurah Jaafar

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Augmented reality (AR) in the healthcare industry has been gaining popularity in recent years, principally in areas of medical education, patient care and digital health solutions. One of the drivers in deciding to invest in AR technology is the potential economic benefits it could bring for patients and healthcare providers, including the pharmaceutical and medical technology sectors. Works of literature have shown that the benefits and impact of AR technologies have left trails of achievements in improving medical education and patient health outcomes. However, little has been published on the economic impact of AR in healthcare, a very resource-intensive industry. This systematic review was performed on studies focused on the benefits and impact of AR in healthcare to appraise if they meet the founded quality criteria so as to identify relevant publications for an in-depth analysis of the economic impact assessment. The literature search was conducted using multiple databases such as PubMed, Cochrane, Science Direct and Nature. Inclusion criteria include research papers on AR implementation in healthcare, from education to diagnosis and treatment. Only papers written in English language were selected. Studies on AR prototypes were excluded. Although there were many articles that have addressed the benefits of AR in the healthcare industry in the area of medical education, treatment and diagnosis and dental medicine, there were very few publications that identified the specific economic impact of technology within the healthcare industry. There were 13 publications included in the analysis based on the inclusion criteria. Out of the 13 studies, none comprised a systematically comprehensive cost impact evaluation. An outline of the cost-effectiveness and cost-benefit framework was made based on an AR article from another industry as a reference. This systematic review found that while the advancements of AR technology is growing rapidly and industries are starting to adopt them into respective sectors, the technology and its advancements in healthcare were still in their early stages. There are still plenty of room for further advancements and integration of AR into different sectors within the healthcare industry. Future studies will require more comprehensive economic analyses and costing evaluations to enable economic decisions for or against implementing AR technology in healthcare. This systematic review concluded that the current literature lacked detailed examination and conduct of economic impact and benefit analyses. Recommendations for future research would be to include details of the initial investment and operational costs for the AR infrastructure in healthcare settings while comparing the intervention to its conventional counterparts or alternatives so as to provide a comprehensive comparison on impact, benefit and cost differences.

Keywords: augmented reality, benefit, economic impact, healthcare, patient care

Procedia PDF Downloads 209

Authors: Yu-Ting Tsai, Chiun-Chieh Hsu, Yu-Chun Chu

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In recent years, due to the development of wireless network technology, many researchers have devoted to the study of wireless sensor networks. The applications of wireless sensor network mainly use the sensor nodes to collect the required information, and send the information back to the users. Since the sensed area is difficult to reach, there are many restrictions on the design of the sensor nodes, where the most important restriction is the limited energy of sensor nodes. Because of the limited energy, researchers proposed a number of ways to reduce energy consumption and balance the load of sensor nodes in order to increase the network lifetime. In this paper, we proposed the Energy-Balanced Clustering method with Auxiliary Members on Wireless Sensor Networks（EBCAM）based on the cluster routing. The main purpose is to balance the energy consumption on the sensed area and average the distribution of dead nodes in order to avoid excessive energy consumption because of the increasing in transmission distance. In addition, we use the residual energy and average energy consumption of the nodes within the cluster to choose the cluster heads, use the multi hop transmission method to deliver the data, and dynamically adjust the transmission radius according to the load conditions. Finally, we use the auxiliary cluster members to change the delivering path according to the residual energy of the cluster head in order to its load. Finally, we compare the proposed method with the related algorithms via simulated experiments and then analyze the results. It reveals that the proposed method outperforms other algorithms in the numbers of used rounds and the average energy consumption.

Keywords: auxiliary nodes, cluster, load balance, routing algorithm, wireless sensor network

Procedia PDF Downloads 275

Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li, Shuo Zhu, Shiming Duan, Xuezhe Yao

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Accurate calculation of wellbore pressure is of great significance to prevent wellbore risk during drilling. The traditional mechanism model needs a lot of iterative solving procedures in the calculation process, which reduces the calculation efficiency and is difficult to meet the demand of dynamic control of wellbore pressure. In recent years, many scholars have introduced artificial intelligence algorithms into wellbore pressure calculation, which significantly improves the calculation efficiency and accuracy of wellbore pressure. However, due to the ‘black box’ property of intelligent algorithm, the existing intelligent calculation model of wellbore pressure is difficult to play a role outside the scope of training data and overreacts to data noise, often resulting in abnormal calculation results. In this study, the multi-phase flow mechanism is embedded into the objective function of the neural network model as a constraint condition, and an intelligent prediction model of wellbore pressure under the constraint condition is established based on more than 400,000 sets of pressure measurement while drilling (MPD) data. The constraint of the multi-phase flow mechanism makes the prediction results of the neural network model more consistent with the distribution law of wellbore pressure, which overcomes the black-box attribute of the neural network model to some extent. The main performance is that the accuracy of the independent test data set is further improved, and the abnormal calculation values basically disappear. This method is a prediction method driven by MPD data and multi-phase flow mechanism, and it is the main way to predict wellbore pressure accurately and efficiently in the future.

Keywords: multiphase flow mechanism, pressure while drilling data, wellbore pressure, mechanism constraints, combined drive

Procedia PDF Downloads 175

Authors: Mona Mohamed Shawkt Ragab, Heba Mohamed Darwish

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Context: Comfort properties of garments are crucial for the wearer, and with the increasing demand for cotton fabric, there is a need to explore alternative fabrics that can offer similar or superior comfort properties. This study focuses on comparing the comfort properties of tencel/cotton single jersey fabric and cotton single jersey fabric, with the aim of identifying fabrics that are more suitable for summer clothes. Research Aim: The aim of this study is to evaluate the comfort properties of tencel/cotton single jersey fabric and cotton single jersey fabric, with the goal of identifying fabrics that can serve as alternatives to cotton, considering their comfort properties for summer clothing. Methodology: An experimental, analytical approach was employed in this study. Two circular knitting machines were used to produce the fabrics, one with a 24 inches gauge and the other with a 28 inches gauge. Both fabrics were knitted with three different loop lengths (3.05 mm, 2.9 mm, and 2.6 mm) to obtain loose, medium, and tight fabrics for evaluation. Various comfort properties, including air permeability, water vapor permeability, wickability, and thermal resistance, were measured for both fabric types. Findings: The study found a significant difference in comfort properties between tencel/cotton single jersey fabric and cotton single jersey fabric. Tencel/cotton fabric exhibited higher air permeability, water vapor permeability, and wickability compared to cotton fabric. These findings suggest that tencel fabric is more suitable for summer clothes due to its superior ventilation and absorption properties. Theoretical Importance: This study contributes to the exploration of alternative fabrics to cotton by evaluating their comfort properties. By identifying fabrics that offer better comfort properties than cotton, particularly in terms of water usage, the study provides valuable insights into sustainable fabric choices for the fashion industry. Data Collection and Analysis Procedures: The comfort properties of the fabrics were measured using appropriate testing methods. Paired comparison t-tests were conducted to determine the significant differences between tencel/cotton fabric and cotton fabric in the measured properties. Correlation coefficients were also calculated to examine the relationships between the factors under study. Question Addressed: The study addresses the question of whether tencel/cotton single jersey fabric can serve as an alternative to cotton fabric for summer clothes, considering their comfort properties. Conclusion: The study concludes that tencel/cotton single jersey fabric offers superior comfort properties compared to cotton single jersey fabric, making it a suitable alternative for summer clothes. The findings also highlight the importance of considering fabric properties, such as air permeability, water vapor permeability, and wickability, when selecting materials for garments to enhance wearer comfort. This research contributes to the search for sustainable alternatives to cotton and provides valuable insights for the fashion industry in making informed fabric choices.

Keywords: comfort properties, cotton fabric, tencel fabric, single jersey

Procedia PDF Downloads 76

Authors: Karl Erickson I. Ebora

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Science and technology are two inseparable terms which bring wonders to all aspects of life such as education, medicine, food production and even the environment. In education, technology has become an integral part as it brings many benefits to the teaching-learning process. However, in the Philippines, being one of the developing countries resources are scarce and not all schools enjoy the fruits brought by technology. Much of this ordeal impacts that of multigrade instruction. These schools are often the last priority in resources allocation since these have limited number of students. In fact, it is not surprising that these schools do not have even a single computer unit much more a computer laboratory. This paper sought to present a plan on how public schools would receive its e-classroom. Specifically, this paper sought to answer questions like the level of the school readiness in terms of facilities and equipment; the attitude of the respondents towards the use of e-classroom; level of teacher’s familiarity in using different e-classroom software and the plans of interventions undertaken by the school to make it e-classroom ready. After gathering and analysing the necessary data, this paper came up with the following conclusions that in terms of facilities and equipment, Guisguis Talon Elementary School (Main), though a multigrade school, is ready to receive e-classroom.; that the respondents show positive disposition in technology utilization in teaching after they strongly agree that technology plays essential role in the teaching-learning process. Also, they strongly agree that technology is a good motivator; it makes the teaching and learning more interesting and effective; it makes teaching easy; and that technology enhances student’s learning. Additionally, Teacher-respondents in Guisguis Talon Elementary School (Main) show familiarity in using software. They are very familiar with MS Word; MS Excel; MS PowerPoint; and internet and email. Moreover, they are very familiar with basic e-classroom computer operations and basic application software. They are very familiar with MS office and can do simple editing and formatting; in accessing and saving information from CD/DVD, external hard drives, USB and the like; and in browsing effectively different search engines and educational sites, download and upload files. Likewise respondents strongly agree to the interventions undertaken by the school to make it e-classroom ready. They strongly agree that funding and support are needed by the school; that stakeholders should be encouraged to consider donating of equipment; and that school and community should try to mobilize their resources in order to help the school; that the teachers should be provided with trainings in order for them to be technologically competent; and that principals and administrators should motivate their teachers to undergo continuous professional development.

Keywords: e-classroom, multi-grade school, DCP, classroom computers

Procedia PDF Downloads 202

Authors: Ajibola Isola, Shattri Mansor, Ojogbane Sani, Olugbemi Tope

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The cadastral map is the rationale behind city management planning and development. For years, cadastral maps have been produced by ground and photogrammetry platforms. Recent evolution in photogrammetry and remote sensing sensors ignites the use of Unmanned Aerial Vehicle systems (UAVs) for cadastral mapping. Despite the time-saving and multi-dimensional cost-effectiveness of the UAV platform, issues related to cadastral map accuracy are a hindrance to the wide applicability of UAVs' cadastral mapping. This study aims to present an approach leading to the generation and assessing the credibility of UAV cadastral mapping. Different sets of Red, Green, and Blue (RGB) photos were obtained from the Tarot 680-hexacopter UAV platform flown over the Universiti Putra Malaysia campus sports complex at an altitude range of 70 m, 100 m, and 250. Before flying the UAV, twenty-eight ground control points were evenly established in the study area with a real-time kinematic differential global positioning system. The second phase of the study utilizes an image-matching algorithm for photos alignment wherein camera calibration parameters and ten of the established ground control points were used for estimating the inner, relative, and absolute orientations of the photos. The resulting orthoimages are exported to ArcGIS software for digitization. Visual, tabular, and graphical assessments of the resulting cadastral maps showed a different level of accuracy. The results of the study show a gradual approach for generating UAV cadastral mapping and that the cadastral map acquired at 70 m altitude produced better results.

Keywords: aerial mapping, orthomosaic, cadastral map, flying altitude, image processing

Procedia PDF Downloads 85

Authors: Stephen L. Roberts

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This article offers a critical analysis of the rise of syndromic surveillance systems for the advanced detection of pandemic threats within contemporary global health security frameworks. The article traces the iterative evolution and ascendancy of three such novel syndromic surveillance systems for the strengthening of health security initiatives over the past two decades: 1) The Program for Monitoring Emerging Diseases (ProMED-mail); 2) The Global Public Health Intelligence Network (GPHIN); and 3) HealthMap. This article demonstrates how each newly introduced syndromic surveillance system has become increasingly oriented towards the integration of digital algorithms into core surveillance capacities to continually harness and forecast upon infinitely generating sets of digital, open-source data, potentially indicative of forthcoming pandemic threats. This article argues that the increased centrality of the algorithm within these next-generation syndromic surveillance systems produces a new and distinct form of infectious disease surveillance for the governing of emergent pathogenic contingencies. Conceptually, the article also shows how the rise of this algorithmic mode of infectious disease surveillance produces divergences in the governmental rationalities of global health security, leading to the rise of an algorithmic governmentality within contemporary contexts of Big Data and these surveillance systems. Empirically, this article demonstrates how this new form of algorithmic infectious disease surveillance has been rapidly integrated into diplomatic, legal, and political frameworks to strengthen the practice of global health security – producing subtle, yet distinct shifts in the outbreak notification and reporting transparency of states, increasingly scrutinized by the algorithmic gaze of syndromic surveillance.

Keywords: algorithms, global health, pandemic, surveillance

Procedia PDF Downloads 187

Authors: J. K Adedeji, O. H Olowomofe, C. O Alo, S.T Ijatuyi

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The issue of high blood sugar level, the effects of which might end up as diabetes mellitus, is now becoming a rampant cardiovascular disorder in our community. In recent times, a lack of awareness among most people makes this disease a silent killer. The situation calls for urgency, hence the need to design a device that serves as a monitoring tool such as a wrist watch to give an alert of the danger a head of time to those living with high blood glucose, as well as to introduce a mechanism for checks and balances. The neural network architecture assumed 8-15-10 configuration with eight neurons at the input stage including a bias, 15 neurons at the hidden layer at the processing stage, and 10 neurons at the output stage indicating likely symptoms cases. The inputs are formed using the exclusive OR (XOR), with the expectation of getting an XOR output as the threshold value for diabetic symptom cases. The neural algorithm is coded in Java language with 1000 epoch runs to bring the errors into the barest minimum. The internal circuitry of the device comprises the compatible hardware requirement that matches the nature of each of the input neurons. The light emitting diodes (LED) of red, green, and yellow colors are used as the output for the neural network to show pattern recognition for severe cases, pre-hypertensive cases and normal without the traces of diabetes mellitus. The research concluded that neural network is an efficient Accu-Chek design tool for the proper monitoring of high glucose levels than the conventional methods of carrying out blood test.

Keywords: Accu-Check, diabetes, neural network, pattern recognition

Procedia PDF Downloads 147

Authors: Sonal Sethi, Mukesh Yadav, Abhimanyu Gupta

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The upcoming field of radiogenomics has the potential to upgrade the role of imaging in lung cancer management by noninvasive characterization of tumor histology and genetic microenvironment. Receptor positivity like epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) genotyping are critical in lung adenocarcinoma for treatment. As conventional identification of receptor positivity is an invasive procedure, we analyzed the features on non-invasive computed tomography (CT), which predicts the receptor positivity in lung adenocarcinoma. Retrospectively, we did a comprehensive study from 77 proven lung adenocarcinoma patients with CT images, EGFR and ALK receptor genotyping, and clinical information. Total 22/77 patients were receptor-positive (15 had only EGFR mutation, 6 had ALK mutation, and 1 had both EGFR and ALK mutation). Various morphological characteristics and metastatic distribution on CT were analyzed along with the clinical information. Univariate and multivariable logistic regression analyses were used. On multivariable logistic regression analysis, we found spiculated margin, lymphangitic spread, air bronchogram, pleural effusion, and distant metastasis had a significant predictive value for receptor mutation status. On univariate analysis, air bronchogram and pleural effusion had significant individual predictive value. Conclusions: Receptor positive lung cancer has characteristic imaging features compared with nonreceptor positive lung adenocarcinoma. Since CT is routinely used in lung cancer diagnosis, we can predict the receptor positivity by a noninvasive technique and would follow a more aggressive algorithm for evaluation of distant metastases as well as for the treatment.

Keywords: lung cancer, multidisciplinary cancer care, oncologic imaging, radiobiology

Procedia PDF Downloads 136