Search results for: end-user trained information extraction

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Giulio Nisoli, Jonas Brüngger, Karin Hostettler, Nicole Stoller, Katrin Fischer

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Technical operators in the railway domain are experts responsible for the supervisory control of the railway power grid as well as of the railway tunnels. The technical systems used to master these demanding tasks are constantly increasing in their degree of automation. It becomes therefore difficult for technical operators to maintain the control over the technical systems and the processes of their job. In particular, the operators must have the necessary experience and knowledge in dealing with a malfunction situation or unexpected event. For this reason, it is of growing importance that the skills relevant for the execution of the job are maintained and further developed beyond the basic training they receive, where they are educated in respect of technical knowledge and the work with guidelines. Training methods aimed at improving the cognitive skills needed by technical operators are still missing and must be developed. Goals of the present study were to identify which are the relevant cognitive skills of technical operators in the railway domain and to define which topics should be addressed by the training of these skills. Observational interviews were conducted in order to identify the main tasks and the organization of the work of technical operators as well as the technical systems used for the execution of their job. Based on this analysis, the most demanding tasks of technical operators could be identified and described. The cognitive skills involved in the execution of these tasks are those, which need to be trained. In order to identify and analyze these cognitive skills a cognitive task analysis (CTA) was developed. CTA specifically aims at identifying the cognitive skills that employees implement when performing their own tasks. The identified cognitive skills of technical operators were summarized and grouped in training topics. For every training topic, specific goals were defined. The goals regard the three main categories; knowledge, skills and attitude to be trained in every training topic. Based on the results of this study, it is possible to develop specific training methods to train the relevant cognitive skills of the technical operators.

Keywords: cognitive skills, cognitive task analysis, technical operators in the railway domain, training topics

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Authors: Ejaz Ashraf, Raheel Babar, Muhammad Yaseen, Hafiz Khurram Shurjeel, Nosheen Fatima

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Main purpose of this study was to assess adoption level of farmers for quinoa cultivation after they had been taught through training and visit extension approach. At this time of the 21^st century, population structure, climate change, food requirements and eating habits of people are changing rapidly. In this scenario, farmers must play their key role in sustainable crop development and production through adoption of new crops that may also be helpful to overcome the issue of food insecurity as well as reducing poverty in rural areas. Its cultivation in Pakistan is at the early stages and there is a need to raise awareness among farmers to grow quinoa crops. In the middle of the 2015, a training and visit extension approach was used to raise awareness and convince farmers to grow quinoa in the area. During training and visit extension program, 80 farmers were randomly selected for the training of quinoa cultivation. Later on, these farmers trained 60 more farmers living into their neighborhood. After six months, a survey was conducted with all 140 farmers to assess the impact of the training and visit program on adoption level of respondents for the quinoa crop. The survey instrument was developed with the help of literature review and other experts of the crop. Validity and reliability of the instrument were checked before complete data collection. The data were analyzed by using SPSS. Multiple regression analysis was used for interpretation of the results from the survey, which indicated that factors like information/ training, change in agronomic and plant protection practices play a key role in the adoption of quinoa cultivation by respondents. In addition, the model explains more than 50% of variation in the adoption level of respondents. It is concluded that farmers need timely information for improved knowledge of agronomic and plant protection practices to adopt cultivation of the quinoa crop in the area.

Keywords: farmers, quinoa, adoption, contact, training and visit

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Waleerak Sittisom

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The objectives of this research were to analyze transportation route management, to identify potential cost reductions in logistic operation. In-depth interview techniques and small group discussions were utilized with 25 participants from various backgrounds in the areas of logistics. The findings of this research revealed that there were four areas that companies are able to effectively manage a logistic cost reduction: managing the space within the transportation vehicles, managing transportation personnel, managing transportation cost, and managing control of transportation. On the other hand, there were four areas that companies were unable to effectively manage a logistic cost reduction: the working process of transportation, the route planning of transportation, the service point management, and technology management. There are five areas that cost reduction is feasible: personnel management, process of working, map planning, service point planning, and technology implementation. To be able to reduce costs, the transportation companies should suggest that customers use a file system to save truck space. Also, the transportation companies need to adopt new technology to manage their information system so that packages can be reached easy, safe, and fast. Staff needs to be trained regularly to increase knowledge and skills. Teamwork is required to effectively reduce the costs.

Keywords: cost reduction, management, logistics, transportation

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Authors: Mohammad Hadi Khorashadi Zadeh, Amin Karkon, Hamid Golnari

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This study aimed to investigate the impact of information technology on the quality of accounting information was made in 2014. A survey of 425 executives of listed companies in Tehran Stock Exchange, using the Cochran formula simple random sampling method, 84 managers of these companies as the sample size was considered. Methods of data collection based on questionnaire information technology some of the questions of the impact of information technology was standardized questionnaires and the questions were designed according to existing components. After the distribution and collection of questionnaires, data analysis and hypothesis testing using structural equation modeling Smart PLS2 and software measurement model and the structure was conducted in two parts. In the first part of the questionnaire technical characteristics including reliability, validity, convergent and divergent validity for PLS has been checked and in the second part, application no significant coefficients were used to examine the research hypotheses. The results showed that IT and its dimensions (timeliness, relevance, accuracy, adequacy, and the actual transfer rate) affect the quality of accounting information of listed companies in Tehran Stock Exchange influence.

Keywords: information technology, information quality, accounting, transfer speed

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Luisa Maria Arrechea Fajardo, Luz Stella Cadavid Rodriguez

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Fish is one of the most commercialized foods worldwide. However, this industry only takes advantage of about 55% of the product's weight, the rest is converted into waste, which is mainly composed of viscera, gills, scales and spines. Consequently, if these wastes are not used or disposed of properly, they cause serious environmental impacts. This is the case of Tumaco (Colombia), the second largest producer of marine fisheries on the Colombian Pacific coast, where artisanal fishermen process more than 50% of the commercialized volume. There, fishing waste is disposed primarily in the ocean, causing negative impacts on the environment and society. Therefore, in the present research, a proposal was made to take advantage of fishing waste through anaerobic treatments, through which it is possible to obtain products with high added value from organic waste. The research was carried out in four stages. First, the production of volatile fatty acids (VFA) in semi-continuous 4L reactors was studied, evaluating three hydraulic retention times (HRT) (10, 7 and 5 days) with four organic loading rates (OLR) (16, 14, 12 and 10 gVS/L/day), the experiment was carried out for 150 days. Subsequently, biogas production was evaluated from the solid digestate generated in the VFA production reactors, initially evaluating the biochemical methane potential (BMP) of 4 total solid concentrations (1, 2, 4 and 6% TS), for 40 days and then, with the optimum TS concentration (2 gVS/L/day), 2 HRT (15 and 20 days) in semi-continuous reactors, were evaluated for 100 days. Finally, the integration of the processes was carried out with the best conditions found, a first phase of VFA production from fishing waste and a second phase of biogas production from unrecovered VFAs and unprocessed material Additionally, an VFA membrane extraction system was included. In the first phase, a liquid digestate with a concentration and VFA production yield of 59.04 gVFA/L and 0.527 gVFA/gVS, respectively, was obtained, with the best condition found (HRT:7 days and OLR: 16 gVS/L/día), where acetic acid and isobutyric acid were the predominant acids. In the second phase of biogas production, a BMP of 0.349 Nm3CH4/KgVS was reached, and it was found as best HRT 20 days. In the integration, the isovaleric, butyric and isobutyric acid were the VFA with the highest percentage of extraction, additionally a 106.67% increase in biogas production was achieved. This research shows that anaerobic treatments are a promising technology for an environmentally safe management of fishing waste and presents the basis of a possible biorefinery.

Keywords: biogas production, fishing waste, VFA membrane extraction, VFA production

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Authors: Dyana Zainudin, Atta Ur-Rahman, Thaier Hamed

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This paper explains about human nature concept as to understand the significance of information security in employees’ mentality including leaders in an organisation. By studying on a theory concept of the latest Von Solms fourth waves, information security governance basically refers to the concept of a set of methods, techniques and tools that responsible for protecting resources of a computer system to ensure service availability, confidentiality and integrity of information. However, today’s information security dilemma relates to the acceptance of employees mentality. The major causes are a lack of communication and commitment. These types of management in an organisation are labelled as immoral/amoral management which effects on information security compliance. A recovery action is taken based on ‘learn a lesson from incident events’ rather than prevention. Therefore, the paper critically analysed the Von Solms fourth waves’ theory with current human events and its correlation by studying secondary data and also from qualitative analysis among employees in public sectors. ‘Three-dimensions to failure’ of information security dilemma are explained as deny, don’t know and don’t care. These three-dimensions are the most common vulnerable behaviour owned by employees. Therefore, by avoiding the three-dimensions to failure may improve the vulnerable behaviour of employees which is often related to immoral/amoral management.

Keywords: information security management system, information security behaviour, information security governance, information security culture

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Authors: Vitalijus Leibenka

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After 2014 the world of Russia’s actions in annexing Crimea has seen a hybrid war that has helped Russia achieve its goals. The world and NATO nations have pointed out that hybrid action can help achieve not only military but also economic and political goals. One of the weapons of action in hybrid warfare is information warfare tools, the use of which helps to carry out actions in the context of hybrid warfare as a whole. In addition, information war tools can be used alone, over time and for long-term purposes. Although forms of information war, such as propaganda and disinformation, have been used in the past, in old conflicts and wars, new forms of information war have emerged as a result of technological development, making the dissemination of information faster and more efficient. The world understands that information is becoming a weapon, but not everyone understands that both information war and information warfare differ in their essence and full content. In addition, the damage and impact of the use of information war, which may have worse consequences than a brief military conflict, is underestimated. Lithuania is also facing various interpretations of the information war. Some believe that the information attack is an information war and the understanding of the information war is limited to a false message in the press. Others, however, deepen and explain the essence of the information war. Society has formed in such a way that not all people are able to assess the threats of information war, to separate information war from information attack. Recently, the Lithuanian government has been taking measures in the context of the information war, making decisions that allow the development of the activities of the state and state institutions in order to create defense mechanisms in the information war. However, this is happening rather slowly and incompletely. Every military conflict, related to Lithuania in one way or another, forces Lithuanian politicians to take up the theme of information warfare again. As a result, a national cyber security center is being set up, and Russian channels spreading lies are banned. However, there is no consistent development and continuous improvement of action against information threats. Although a sufficiently influential part of society (not a political part) helps to stop the spread of obscure information by creating social projects such as “Demaskuok” and “Laikykis ten su Andriumi tapinu”, it goes without saying that it will not become a key tool in the fight against information threats. Therefore, in order to achieve clean dissemination of information in Lithuania, full-fledged and substantial political decisions are necessary, the adoption of which would change the public perception of the information war, its damage, impact and actions that would allow to combat the spread. Political decisions should cover the educational, military, economic and political areas, which are one of the main and most important in the state, which would allow to fundamentally change the situation against the background of information war.

Keywords: information war, information warfare, hybrid war, hybrid warfare, NATO, Lithuania, Russia

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Authors: Arshia Ayoub, Zahid Ashraf Wani

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With the introduction of online social Q&A sites, people are able to reach each other efficiently for information seeking and simultaneously creating social bonds. There prevails an issue of low or no response for some questions posed by an information seeker on these sites. So this study tries to understand the effect of question type on responses in Social Q & A sites. The study found that among the answered queries, majority of them were answered within 24 hours of posting the questions and surprisingly most replies were received within one hour of posting. It was observed that questions of general information type were most likely to be answered followed by verification type.

Keywords: community‐based services, information seeking, social search, social Q&A site

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Authors: F. Slaven, M. Uys, Y. Erasmus

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The South African National Mental Health Education Programme (SANMHEP) was a National Department of Health (NDoH) initiative to strengthen mental health services in South Africa in collaboration with the Foundation for Professional Development (FPD), SANOFI and the various provincial departments of health. The programme was implemented against the backdrop of a number of challenges in the management of mental health in the country related to staff shortages and infrastructure, the intersection of mental health with the growing burden of non-communicable diseases and various forms of violence, and challenges around substance abuse and its relationship with mental health. The Mental Health Care Act (No. 17 of 2002) prescribes that mental health should be integrated into general health services including primary, secondary and tertiary levels to improve access to services and reduce stigma associated with mental illness. In order for the provisions of the Act to become a reality, and for the journey of mental health patients through the system to improve, sufficient and skilled health care providers are critical. SANMHEP specifically targeted Medical Doctors and Professional Nurses working within the facilities that are listed to conduct 72-hour assessments, as well as District Hospitals. The aim of the programme was to improve the clinical diagnosis and management of mental disorders/conditions and the understanding of and compliance with the Mental Health Care Act and related Regulations and Guidelines in the care, treatment and rehabilitation of mental health care users. The course used a blended-learning approach and trained 1 120 health care providers through 36 workshops between February and November 2019. Of those trained, 689 (61.52%) were Professional Nurses, 337 (30.09%) were Medical Doctors, and 91 (8.13%) indicated their occupation as ‘other’ (of these more than half were psychologists). The pre- and post-evaluation of the face-to-face training sessions indicated a marked improvement in knowledge and confidence level scores (both clinical and legislative) in the care, treatment and rehabilitation of mental health care users by participants in all the training sessions. There was a marked improvement in the knowledge and confidence of participants in performing certain mental health activities (on average the ratings increased by 2.72; or 27%) and in managing certain mental health conditions (on average the ratings increased by 2.55; or 25%). The course also required that participants obtain 70% or higher in their formal assessments as part of the online component. The 337 participants who completed and passed the course scored 90% on average. This illustrates that when participants attempted and completed the course, they did very well. To further assess the effect of the course on the knowledge and behaviour of the trained mental health care practitioners a mixed-method outcome evaluation is currently underway consisting of a survey with participants three months after completion, follow-up interviews with participants, and key informant interviews with department of health officials and course facilitators. This will enable a more detailed assessment of the impact of the training on participants' perceived ability to manage and treat mental health patients.

Keywords: mental health, public health facilities, South Africa, training

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Authors: Shahruhaida Adayu Mohd Paili, Abd Latif Abdul Rahman, Asmadi Mohammed Ghazali

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Digital library was developed by many organizations, especially universities. The digital library can be considered as a new information system. Digital library brings many benefits to the users. There are many researches that have investigated the importance of the digital library, the acceptance, and continuance use of digital library. The investigation towards the digital library is important and it is crucial to understand the reason why users accept and continued use of digital library. Users can search the information and available resources through the digital library website. It is important to know the user’s perception towards the aesthetics of the digital library. Besides that, because of digital library provided information to the users, the researcher also needed to investigate the quality of information in digital library. This study used Extending the Unified Theory of Acceptance and Use of Technology (UTAUT2) in order to know the user’s intention to continued use of digital library.

Keywords: digital library, aesthetics, information quality, intention to continued use of digital library, UTAUT2

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Authors: Thomas Adi Purnomo Sidhi

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The importance of designing a pregnancy interactive information design for a mobile application is felt in order to assist pregnant women to get an easy access of highly credible pregnancy-related information on which often fail to be fulfilled, while it has been a very critical one. Thus, an observation of needs assessment for designing a pregnancy interactive information system design for a mobile application at iOS becomes current objective study. A comparative study of the top five pregnancy interactive information design available at the Apple Store conducted in order to fulfill it. Whilst, an observation of user experiences included for deeper analyzes. Moreover, a literature study conducted to support the arguments that being provided in the current study. The findings, surprisingly, also reveal the advantages of local wisdom in pregnancy that never been attached to those top five applications before.

Keywords: information system design, interactive design, local wisdom, pregnancy

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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Authors: Kiran Kumar K., Ramesh Babu Bejjam, Atul Najan

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A thermosyphon system is a heat transfer loop which operates on the basis of gravity and buoyancy forces. It guarantees a good reliability and low maintenance cost as it does not involve any mechanical pump. Therefore it can be used in many industrial applications such as refrigeration and air conditioning, electronic cooling, nuclear reactors, geothermal heat extraction, etc. But flow instabilities and loop configuration are the major problems in this system. Several previous researchers studied that stabilities can be suppressed by using nanofluids as loop fluid. In the present study a rectangular thermosyphon loop with end heat exchangers are considered for the study. This configuration is more appropriate for many practical applications such as solar water heater, geothermal heat extraction, etc. In the present work, steady-state analysis is carried out on thermosyphon loop with parallel flow coaxial heat exchangers at heat source and heat sink. In this loop nano fluid is considered as the loop fluid and water is considered as the external fluid in both hot and cold heat exchangers. For this analysis one-dimensional homogeneous model is developed. In this model, conservation equations like conservation of mass, momentum, energy are discretized using finite difference method. A computer code is written in MATLAB to simulate the flow in thermosyphon loop. A comparison in terms of heat transfer is made between water and nano fluid as working fluids in the loop.

Keywords: heat exchanger, heat transfer, nanofluid, thermosyphon loop

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Authors: Farid Habibi Tanha, Hawati Janor, Mojtaba Jahanbazi

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The purpose of this study is to examine the effect of asymmetric information on the composition of capital inflows. This study uses the stock market microstructure to capture the asymmetric information. Such an approach allows one to capture the level and extent of the asymmetric information from a firm’s perspective. This study focuses on the two-dimensional measure of the market microstructure in capturing asymmetric information. The composition of capital inflows is measured by running six models simultaneously. By employing the panel data technique, the main finding of this research shows an increase in the asymmetric information of the stock market, in any of the two dimensions of width and depth. This leads to the reduction of foreign investments in both forms of foreign portfolio investment (FPI) and foreign direct investment (FDI), while the reduction in FPI is higher than that of the FDI. The significant effect of asymmetric information on capital inflows implicitly suggests for policymakers to control the changes of foreign capital inflows through transparency in the level of the market.

Keywords: capital flows composition, asymmetric information, stock market microstructure, foreign portfolio investment, foreign direct investment

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Authors: Venkat Kamavaram, Ravi Pare

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Modern warfighters experience extreme environmental conditions in many of their operational and training activities. In temperatures exceeding 95°F, the body’s temperature regulation can no longer cool through convection and radiation. In this case, the only cooling mechanism is evaporation. However, evaporative cooling is often compromised by excessive humidity. Natural cooling mechanisms can be further compromised by clothing and protective gear, which trap hot air and moisture close to the body. Creating an efficient heat extraction apparel system that is also lightweight without hindering dexterity or mobility of personnel working in extreme temperatures is a difficult technical challenge and one that needs to be addressed to increase the probability for the future success of the US military. To address this challenge, Oceanit Laboratories, Inc. has developed and patented a Liquid Cooled Garment (LCG) more effective than any on the market today. Oceanit’s LCG is a form-fitting garment with a network of thermally conductive tubes that extracts body heat and can be worn under all authorized and chemical/biological protective clothing. Oceanit specifically designed and developed ThermoCore®, a thermally conductive polymer, for use in this apparel, optimizing the product for thermal conductivity, mechanical properties, manufacturability, and performance temperatures. Thermal Manikin tests were conducted in accordance with the ASTM test method, ASTM F2371, Standard Test Method for Measuring the Heat Removal Rate of Personal Cooling Systems Using a Sweating Heated Manikin, in an environmental chamber using a 20-zone sweating thermal manikin. Manikin test results have shown that Oceanit’s LCG provides significantly higher heat extraction under the same environmental conditions than the currently fielded Environmental Control Vest (ECV) while at the same time reducing the weight. Oceanit’s LCG vests performed nearly 30% better in extracting body heat while weighing 15% less than the ECV. There are NO cooling garments in the market that provide the same thermal extraction performance, form-factor, and reduced weight as Oceanit’s LCG. The two cooling garments that are commercially available and most commonly used are the Environmental Control Vest (ECV) and the Microclimate Cooling Garment (MCG).

Keywords: thermally conductive composite, tubing, garment design, form fitting vest, thermocore

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Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

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Authors: T. Nalowa, L. Foncha, S. Eposi

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Prostate enlargement, prostate cancer are major global health problems affecting many men as they advance in age. It is highly recommended to encourage older men to get Prostate Specific Antigen test screening frequently. Conventional treatments like radiation, chemotherapy are associated with many side effects. And this situation is a call for concern. Traditional medicine is affordable, easily prepared with little or no side effects and it contains many phytochemicals. The study aims to find the cure for prostate cancer and prostate enlargement by extracting products from plant tissues of specific herbs to determine anti-inflammatory, anti-cancer, and anti-hematuria properties. Descriptive statistical analysis was applied to describe the data process. The commonly used method of preparation was extraction. Overall, 40 patients were classified based on their medical conditions on their underlying user report. Rural communities in Fako are rich sources of plants with medicinal properties. The used plants consequently provide basic information and aid to investigate the cure of prostate cancer and prostate enlargement, with great significance.

Keywords: cancer, enlargement, metastases, prostate

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Authors: Sakshi V. Tantak, Vishap K. Malik, Neelanjney Pilarisetty

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A patent is an exclusive right granted for an invention. It can be a product or a process that provides an innovative method of doing something, or offers a new technical perspective or solution to a problem. A patent can be obtained by making the technical information and details about the invention publicly available. The patent owner has exclusive rights to prevent or stop anyone from using the patented invention for commercial uses. Any commercial usage, distribution, import or export of a patented invention or product requires the patent owner’s consent. It has been observed that the central and important parts of patents are scripted in idiosyncratic and complex linguistic structures that can be difficult to read, comprehend or interpret for the masses. The abstracts of these patents tend to obfuscate the precise nature of the patent instead of clarifying it via direct and simple linguistic constructs. This makes it necessary to have an efficient access to this knowledge via concise and transparent summaries. However, as mentioned above, due to complex and repetitive linguistic constructs and extremely long sentences, common extraction-oriented automatic text summarization methods should not be expected to show a remarkable performance when applied to patent documents. Other, more content-oriented or abstractive summarization techniques are able to perform much better and generate more concise summaries. This paper proposes an efficient summarization system for patents using artificial intelligence, natural language processing and deep learning techniques to condense the knowledge and essential information from a patent document into a single summary that is easier to understand without any redundant formatting and difficult jargon.

Keywords: abstractive summarization, deep learning, natural language Processing, patent document

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Authors: Desmond Chinedu Oparaku, Pearl C. Akanwa, Oyemike Victor Benson

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This paper examines the challenges facing library and information centers (LICs) in managing indigenous knowledge in academic libraries in developing countries. The need for managing an indigenous knowledge in library and information centers in developing nations is becoming more critical. There is an ever increasing output of indigenous knowledge; effective management of indigenous knowledge becomes necessary to enable the next generation benefit from them. This paper thus explores the concept of indigenous knowledge (IK), nature of indigenous knowledge (IK), the various forms of indigenous knowledge (IK), sources of indigenous knowledge (IK), and relevance of indigenous knowledge (IK). The expectations of library and information professionals towards effective management of indigenous knowledge and the challenges to effective management of indigenous knowledge were highlighted. Recommendations were made based on the identified challenges.

Keywords: library, indigenous knowledge, information centres, information professionals

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Authors: Sanjeev Sharma, Suman Lata

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With the availability of diverse printed, electronic literature and web sites on medical and health related information, it is impossible for the medical professional to get the information he seeks in the shortest possible time. For all these problems information literacy is the only solution. Thus, information literacy is recognized as an important aspect of medical education. In the present study, an attempt has been made to know the information literacy skills of the faculty and students at medical colleges of Haryana, Punjab and Chandigarh. The scope of the study was confined to the 12 selected medical colleges of three States (Haryana, Punjab, and Chandigarh). The findings of the study were based on the data collected through 1018 questionnaires filled by the respondents of the medical colleges. It was found that Online Medical Websites (such as WebMD, eMedicine and Mayo Clinic etc.) were frequently used by 63.43% of the respondents of Chandigarh which is slightly more than Haryana (61%) and Punjab (55.65%). As well, 30.86% of the respondents of Chandigarh, 27.41% of Haryana and 27.05% of Punjab were familiar with the controlled vocabulary tool; 25.14% respondents of Chandigarh, 23.80% of Punjab, 23.17% of Haryana were familiar with the Boolean operators; 33.05% of the respondents of Punjab, 28.19% of Haryana and 25.14% of Chandigarh were familiar with the use and importance of the keywords while searching an electronic database; and 51.43% of the respondents of Chandigarh, 44.52% of Punjab and 36.29% of Haryana were able to make effective use of the retrieved information. For accessing information in electronic format, 47.74% of the respondents rated their skills high, while the majority of respondents (76.13%) were unfamiliar with the basic search technique i.e. Boolean operator used for searching information in an online database. On the basis of the findings, it was suggested that a comprehensive training program based on medical professionals information needs should be organized frequently. Furthermore, it was also suggested that information literacy may be included as a subject in the health science curriculum so as to make the medical professionals information literate and independent lifelong learners.

Keywords: information, information literacy, medical professionals, medical colleges

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Authors: Khaled M. Alhawiti

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This paper investigates the future of medicine and the use of Natural language processing. The importance of having correct clinical information available online is remarkable; improving patient care at affordable costs could be achieved using automated applications to use the online clinical information. The major challenge towards the retrieval of such vital information is to have it appropriately coded. Majority of the online patient reports are not found to be coded and not accessible as its recorded in natural language text. The use of Natural Language processing provides a feasible solution by retrieving and organizing clinical information, available in text and transforming clinical data that is available for use. Systems used in NLP are rather complex to construct, as they entail considerable knowledge, however significant development has been made. Newly formed NLP systems have been tested and have established performance that is promising and considered as practical clinical applications.

Keywords: clinical information, information retrieval, natural language processing, automated applications

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Authors: Waleed A. El-Said, Dina M. Fouad, Mohamed H. Aly, Mohamed A. El-Gahami

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Green synthesis of nanomaterials has received increasing attention as an eco-friendly technology in materials science. Here, we have used two types of extractions from green tea leaf (i.e. total extraction and tannin extraction) as reducing agents for a rapid, simple and one step synthesis method of mesoporous silica nanoparticles (MSNPs)/iron oxide (Fe3O4) nanocomposite based on deposition of Fe3O4 onto MSNPs. MSNPs/Fe3O4 nanocomposite were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive X-ray, vibrating sample magnetometer, N2 adsorption, and high-resolution transmission electron microscopy. The average mesoporous silica particle diameter was found to be around 30 nm with high surface area (818 m2/gm). MSNPs/Fe3O4 nanocomposite was used for removing lindane pesticide (an environmental hazard material) from aqueous solutions. Fourier transform infrared, UV-vis, High-performance liquid chromatography and gas chromatography techniques were used to confirm the high ability of MSNPs/Fe3O4 nanocomposite for sensing and capture of lindane molecules with high sorption capacity (more than 89%) that could develop a new eco-friendly strategy for detection and removing of pesticide and as a promising material for water treatment application.

Keywords: green synthesis, mesoporous silica, magnetic iron oxide NPs, adsorption Lindane

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Authors: Mbongeni Mabaso, Kandasamy Moodley, Gan Redhi

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The recovery of industrially valuable organic solvents from liquid waste, generated in chemical processes, is economically crucial to countries which need to import organic solvents. In view of this, the main objective of this study was to determine the ability of selected ionic liquids, namely, 1-ethyl-3-methylimidazolium ethylsulphate, [EMIM] [ESO4] and 1-ethyl-3-methylpyridinium ethylsulphate, [EMpy][ESO4] to recover aromatic components from spent paint solvents. Preliminary studies done on the liquid waste, received from a paint manufacturing company, showed that the aromatic components were present in the range 6 - 21 % by volume. The separation of the aromatic components was performed with the ionic liquids listed above. The phases, resulting from the separation of the mixtures, were analysed with a Gas Chromatograph (GC) coupled to a FID detector. Chromatograms illustrate that the chosen ZB-Wax-Plus column gave excellent separation of all components of interest from the mixtures, including the isomers of xylene. The concentrations of aromatics recovered from the spent solvents were found to be the % ranges 13-33 and 23-49 respectively for imidazolium and pyridinium ionic liquids. These results also show that there is a significant correlation between π-character of ionic liquids and the level of extraction. It is therefore concluded that ionic liquids have the potential for macro-scale recovery of re-useable solvents present in liquid waste emanating from paint manufacture.

Keywords: synthesis, ionic liquid, imidazolium, pyridinium, extraction, aromatic solvents, spent paint organic solvents

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: Sandra Tapin-Lingua, Katia Ruel, Jean-Paul Joseleau, Daouia Messaoudi, Olivier Fahy, Michel Petit-Conil

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The preservative efficacy of organic biocides is strongly related to their capacity of penetration and retention within wood tissues. The specific detection of the pyrethroid insecticide is currently obtained after extraction followed by chemical analysis by chromatography techniques. However visualizing the insecticide molecule within the wood structure requires specific probes together with microscopy techniques. Therefore, the aim of the present work was to apply a new methodology based on antibody-antigen recognition and electronic microscopy to visualize directly pyrethroids in the wood material. A polyclonal antibody directed against cypermethrin was developed and implement it on Pinus sylvestris wood samples coated with technical cypermethrin. The antibody was tested on impregnated wood and the specific recognition of the insecticide was visualized in transmission electron microscopy (TEM). The immunogold-TEM assay evidenced the capacity of the synthetic biocide to penetrate in the wood. The depth of penetration was measured on sections taken at increasing distances from the coated surface of the wood. Such results correlated with chemical analyzes carried out by GC-ECD after extraction. In addition, the immuno-TEM investigation allowed visualizing, for the first time at the ultrastructure scale of resolution, that cypermethrin was able to diffuse within the secondary wood cell walls.

Keywords: cypermethrin, insecticide, wood penetration, wood retention, immuno-transmission electron microscopy, polyclonal antibody

Procedia PDF Downloads 411