Search results for: Knowledge Management Approach

Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: Communication signal, feature extraction, holder coefficient, improved cloud model.

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Authors: Dixit Garg, S. Luthra, A. Haleem

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During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection among society. Organizations are trying to achieve the goals of improvement in environment, low cost, high quality, flexibility and more customer satisfaction. Performance measurement frameworks are very useful to monitor the performance of any organization. The basic goal of this paper is to identify performance measures and ranking of these performance measures of GSCM performance measurement towards sustainability framework. Five perspectives (Environment, Economic, Social, Operational and Cost performances) and nineteen performance measures of GSCM performance towards sustainability have been have been identified from extensive literature review. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of these performance perspectives and measures. All pair comparisons in AHP have been made on the basis on the experts’ opinions (selected from academia and industry). Ranking of these performance perspectives and measures will help to understand the importance of environmental, economic, social, operational performances and cost performances in the supply chain.

Keywords: Analytical Hierarchy Process (AHP), Green Supply Chain Management, Performance Measures (PM), Sustainability.

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Authors: Okolo Chimaobi Valentine

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This paper seeks to assess the implications of bank consolidation on the performance of small and medium scale enterprises in the Nigerian economy. Multiple linear regression technique and correlation matrix test were employed to measure the extent to which small and medium scale enterprises asset size, survival and access to credit were influenced. The result showed that bank deposit (BD) and bank credit (L or BC) impacted on asset size and survival of small and medium scale enterprises. None of the variables had significant impact on SMEs access to credit. There is a shift of focus by commercial banks away from small and medium scale enterprises (small customers), which is evidenced by the significant negative influence of bank credit to both the survival and asset size of small and medium enterprises. While micro finance banks work hard at providing funds to small and medium scale entrepreneurs, their capacity to meet the needs of these entrepreneurs is constrained. CBN should make policies that will boost micro finance bank’s capital and also monitor closely the management of the banks to ensure prudent financing of small and medium scale investments.

Keywords: Bank consolidation, small and medium enterprises.

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Authors: Pascal Gliesche, Kathrin Seibert, Christian Kowalski, Dominik Domhoff, Max Pfingsthorn, Karin Wolf-Ostermann, Andreas Hein

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Robotic assistance in nursing care is an increasingly important area of research and development. Facing a shortage of labor and an increasing number of people in need of care, the German Nursing Care Innovation Center (Pflegeinnovationszentrum, PIZ) aims to address these challenges from the side of technology. Little is known about nurses experiences with existing robotic assistance systems. Especially nurses perspectives on starting points for the development of robotic solutions, that target recurring burdensome tasks in everyday nursing care, are of interest. This paper presents findings focusing on robotics resulting from an explanatory mixed-methods study on nurses experiences with and their expectations for innovative technologies in nursing care in stationary and ambulant care facilities and hospitals in Germany. Based on the findings, eight scenarios for robotic assistance are identified based on the real needs of practitioners. An initial system addressing a single use-case is described to show perspectives for the use of robots in nursing care.

Keywords: Robotics and automation, engineering management, engineering in medicine and biology, medical services, public healthcare.

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Authors: Ryuji Yamazaki, Masahiro Kochi, Weiran Zhu, Hiroko Kase

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In care for older adults, behavioral and psychological symptoms of dementia (BPSD) like agitation and aggression are distressing for patients and their caretakers, often resulting in premature institutionalization with increased costs of care. To improve mood and mitigate symptoms, as a non-pharmaceutical approach, emotion-oriented therapy like reminiscence work is adopted in face-to-face communication. Telecommunication support is expected to be provided by robotic media as a bridge for digital divide for those with dementia and facilitate social interaction both verbally and nonverbally. The purpose of this case study is to explore the conditions in which robotic media can effectively attract attention from older adults with dementia and promote their well-being. As a pilot study, we introduced the pillow-phone Hugvie^®, a huggable humanly shaped communication medium to five residents with dementia at a care facility, to investigate how the following conditions work for the elderly when they use the medium; 1) no sound, 2) radio, non-interactive, 3) daily conversation, and 4) reminiscence work. As a result, under condition 4, reminiscence work, the five participants kept concentration in interacting with the medium for a longer duration than other conditions. In condition 4, they also showed larger amount of utterances than under other conditions. These results indicate that providing topics related to personal histories through robotic media could affect communication positively and should, therefore, be further investigated. In addition, the issue of ethical implications by using persuasive technology that affects emotions and behaviors of older adults is also discussed.

Keywords: BPSD, reminiscence, tactile telecommunication, utterances.

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Authors: Yi-Feng Su, Chia-Tseng Chen, Hsueh-Lung Liao

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The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.

Keywords: Lane mark detection, lane departure warning (LDW), dynamic range of interesting (DROI), forward collision warning (FCW), adaptive front-lighting system (AFS).

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Authors: Molly P. M. Wong

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In this study, a blended and interactive e-learning Courseware that our team developed will be introduced, and our team’s experiences on how the e-learning Courseware and the flipped classroom benefit student learning in bioethics in the medical program will be shared. This study is a continuation of the previously established study, which provides a summary of the well-developed e-learning Courseware in a blended learning approach and an update on its efficiency and efficacy. First, a collection of animated videos capturing selected topics of bioethics and related ethical issues and dilemma will be introduced. Next, a selection of problem-based learning videos (“simulated doctor-patient role play”) with pop-up questions and discussions will be further discussed. Our findings demonstrated that these activities launched by the Courseware strongly engaged students in bioethics education and enhanced students’ critical thinking and creativity. Moreover, the educational benefits of the online art exhibition, art jamming and competition will be discussed, through which students could express bioethics through arts and enrich their learning in medical research in an interactive, fun and entertaining way, strengthening their interests in bioethics. Furthermore, online survey questionnaires and focus group interviews were conducted. Our results indicated that implementing the e-learning Courseware with a flipped classroom in bioethics education enhanced both active learning and student engagement. In conclusion, our Courseware not only reinforces education in art, bioethics and medicine, but also benefits students in understanding and critical thinking in socio-ethical issues, and serves as a valuable learning tool in bioethics teaching and learning.

Keywords: Bioethics, courseware, e-learning, flipped classroom.

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Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

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This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: Land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle.

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Authors: Mahmoud A. Mahmoud, Ashraf Osman

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In this study, the different approaches currently followed by design codes to assess the stability of buildings utilizing concrete moment resisting frames structural system are evaluated. For such purpose, a parametric study was performed. It involved analyzing group of concrete moment resisting frames having different slenderness ratios (height/width ratios), designed for different lateral loads to vertical loads ratios and constructed using ordinary reinforced concrete and high strength concrete for stability check and overall buckling using code approaches and computer buckling analysis. The objectives were to examine the influence of such parameters that directly linked to frames’ lateral stiffness on the buildings’ stability and evaluates the code approach in view of buckling analysis results. Based on this study, it was concluded that, the most susceptible buildings to instability and magnification of second order effects are buildings having high aspect ratios (height/width ratio), having low lateral to vertical loads ratio and utilizing construction materials of high strength. In addition, the study showed that the instability limits imposed by codes are mainly mathematical to ensure reliable analysis not a physical ones and that they are in general conservative. Also, it has been shown that the upper limit set by one of the codes that second order moment for structural elements should be limited to 1.4 the first order moment is not justified, instead, the overall story check is more reliable.

Keywords: Buckling, lateral stability, p-delta, second order.

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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Authors: Yujin Jeong, Youkyung Son, Myounghwan Choi, Sanghyub Lee, Sangyeol Lee, Changho Hwang, Kyo-in Koo

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Dysphasia is difficulty in swallowing food because of oral cavity impairments induced by stroke, muscle damage, tumor. Intermittent oro-esophageal (IOE) tube feeding is one of the well-known feeding methods for the dysphasia patients. However, it is hard to insert at the proper position in esophagus. In this study, we design and fabricate the IOE tube guide using 3-dimensional (3D) printer. The printed IOE tube is tested in a mannequin (Airway Management Trainer, Co., Ltd., Copenhagen, Denmark) mimicking human’s esophagus. The gag reflex point is measured as the design point in the mannequin. To avoid the gag reflex, we design various shapes of IOE tube guide. One structure is separated into three parts; biting part, part through oral cavity, connecting part to oro-esophageal. We designed 6 types of IOE tube guide adjusting length and angle of these three parts. To evaluate the IOE tube guide, it is inserted in the mannequin, and through the inserted guide, an endoscopic camera successfully arrived at the oro-esophageal. We had planned to apply this mannequin-based design experience to patients in near future.

Keywords: Dysphagia, feeding method, IOE tube guide, 3-D printer.

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Authors: I. V. Pinto, M. R. Sooriyarachchi

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It can be frequently observed that the data arising in our environment have a hierarchical or a nested structure attached with the data. Multilevel modelling is a modern approach to handle this kind of data. When multilevel modelling is combined with a binary response, the estimation methods get complex in nature and the usual techniques are derived from quasi-likelihood method. The estimation methods which are compared in this study are, marginal quasi-likelihood (order 1 & order 2) (MQL1, MQL2) and penalized quasi-likelihood (order 1 & order 2) (PQL1, PQL2). A statistical model is of no use if it does not reflect the given dataset. Therefore, checking the adequacy of the fitted model through a goodness-of-fit (GOF) test is an essential stage in any modelling procedure. However, prior to usage, it is also equally important to confirm that the GOF test performs well and is suitable for the given model. This study assesses the suitability of the GOF test developed for binary response multilevel models with respect to the method used in model estimation. An extensive set of simulations was conducted using MLwiN (v 2.19) with varying number of clusters, cluster sizes and intra cluster correlations. The test maintained the desirable Type-I error for models estimated using PQL2 and it failed for almost all the combinations of MQL. Power of the test was adequate for most of the combinations in all estimation methods except MQL1. Moreover, models were fitted using the four methods to a real-life dataset and performance of the test was compared for each model.

Keywords: Goodness-of-fit test, marginal quasi-likelihood, multilevel modelling, type-I error, penalized quasi-likelihood, power, quasi-likelihood.

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: Computer vision, deep learning, object detection, semiconductor.

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Authors: Sujata Upgupta, Prasoon Kumar Singh

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The expansion of large scale coal mining into forest areas is a potential hazard for the local biodiversity and wildlife. The objective of this study is to provide a picture of the threat that coal mining poses to the forests of the East Bokaro landscape. The vulnerable forest areas at risk have been assessed and the priority areas for conservation have been presented. The forested areas at risk in the current scenario have been assessed and compared with the past conditions using classification and buffer based overlay approach. Forest vulnerability has been assessed using an analytical framework based on systematic indicators and composite vulnerability index values. The results indicate that more than 4 km² of forests have been lost from 1973 to 2016. Large patches of forests have been diverted for coal mining projects. Forests in the northern part of the coal field within 1-3 km radius around the coal mines are at immediate risk. The original contiguous forests have been converted into fragmented and degraded forest patches. Most of the collieries are located within or very close to the forests thus threatening the biodiversity and hydrology of the surrounding regions. Based on the vulnerability values estimated, it was concluded that more than 90% of the forested grids in East Bokaro are highly vulnerable to mining. The forests in the sub-districts of Bermo and Chandrapura have been identified as the most vulnerable to coal mining activities. This case study would add to the capacity of the forest managers and mine managers to address the risk and vulnerability of forests at a small landscape level in order to achieve sustainable development.

Keywords: Coal mining, forest, indicators, vulnerability.

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Authors: Nikola Radovanovic, Petros Gkotsis, Mathieu Doussineau

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Aeronautics is regarded as a strategically important sector for European competitiveness. It was at the heart of European entrepreneurial development since the industry was born. Currently, the EU is the world leader in the production of civil aircraft, including helicopters, aircraft engines, parts, and components. It is recording a surplus in trade relating to aerospace products, which are exported all over the globe. Also, this industry shows above-average investments in research and development, as demonstrated in the patent activity in this area. The post-pandemic recovery of the industry will partly depend on the possibilities to streamline collaboration in further research and innovation activities. Aeronautics features as one of the often-selected priority domains in smart specialisation, which represents the main regional and national approach in developing and implementing innovation policies in Europe. The basis for the selection of priority domains for smart specialisation lies in the mapping of innovative potential, with research and patent activities being among the key elements of this analysis. This research is aimed at identifying characteristics of the trends in research and patent activities in the regions and countries that base their competitiveness on the aeronautics sector. It is also aimed at determining the scope and patterns of collaborations in aeronautics between innovators from the European regions, focusing on revealing new technology areas that emerge from these collaborations. For this purpose, we developed a methodology based on desk research and the analysis of the PATSTAT patent database as well as the databases of R&I framework programmes.

Keywords: aeronautics, smart specialisation, innovation policy, regional policy.

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Authors: Nikhil, Bestamin Özkaya, Ari Visa, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

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The performance of a sucrose-based H2 production in a completely stirred tank reactor (CSTR) was modeled by neural network back-propagation (BP) algorithm. The H2 production was monitored over a period of 450 days at 35±1 ºC. The proposed model predicts H2 production rates based on hydraulic retention time (HRT), recycle ratio, sucrose concentration and degradation, biomass concentrations, pH, alkalinity, oxidation-reduction potential (ORP), acids and alcohols concentrations. Artificial neural networks (ANNs) have an ability to capture non-linear information very efficiently. In this study, a predictive controller was proposed for management and operation of large scale H2-fermenting systems. The relevant control strategies can be activated by this method. BP based ANNs modeling results was very successful and an excellent match was obtained between the measured and the predicted rates. The efficient H2 production and system control can be provided by predictive control method combined with the robust BP based ANN modeling tool.

Keywords: Back-propagation, biohydrogen, bioprocessmodeling, neural networks.

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Authors: Yimeng Deng, Klarissa T.T. Chang

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The proliferation of user-generated content (UGC) results in huge opportunities to explore event patterns. However, existing event recommendation systems primarily focus on advanced information technology users. Little work has been done to address novice and low-literacy users. The next billion users providing and consuming UGC are likely to include communities from developing countries who are ready to use affordable technologies for subsistence goals. Therefore, we propose a design framework for providing event recommendations to address the needs of such users. Grounded in information integration theory (IIT), our framework advocates that effective event recommendation is supported by systems capable of (1) reliable information gathering through structured user input, (2) accurate sense making through spatial-temporal analytics, and (3) intuitive information dissemination through interactive visualization techniques. A mobile pest management application is developed as an instantiation of the design framework. Our preliminary study suggests a set of design principles for novice and low-literacy users.

Keywords: Event recommendation, iconic interface, information integration, spatial-temporal clustering, user-generated content, visualization techniques

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Authors: Mohd Iskandar Illyas Tan, Raziah Noor Razali, Zuhra Junaida Husny

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The purpose of this study is i) to investigate the driving factors and barriers of the adoption of Information and Communication Technology (ICT) in Halal logistic and ii) to develop an ICT adoption framework for Halal logistic service provider. The Halal LSPs selected for the study currently used ICT service platforms, such as accounting and management system for Halal logistic business. The study categorizes the factors influencing the adoption decision and process by LSPs into four groups: technology related factors, organizational and environmental factors, Halal assurance related factors, and government related factors. The major contribution in this study is the discovery that technology related factors (ICT compatibility with Halal requirement) and Halal assurance related factors are the most crucial factors among the Halal LSPs applying ICT for Halal control in transportation-s operation. Among the government related factors, ICT requirement for monitoring Halal included in Halal Logistic Standard on Transportation (MS2400:2010) are the most influencing factors in the adoption of ICT with the support of the government. In addition, the government related factors are very important in the reducing the main barriers and the creation of the atmosphere of ICT adoption in Halal LSP sector.

Keywords: Information and communication technology (ICT), Halal logistic, Halal transportation, Technology adoption

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Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant Kumar Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373 and 0.9428 respectively.

Keywords: Bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE.

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Authors: Ali Hajiesmaeili, Mehdi Rahimi, Ehsan Jaberi, Amir Abbas Hosseini

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The purpose of this study is investigating the influences of logistics performance on organizational performance including both marketing & financial aspects, and showing the financial impacts of selecting the right marketing and logistics priorities in line with their supply chain type, and also giving the practitioners an advance identification of their priorities and participation types of supply chain, and the best combination of their strategies and resources in this regard. We made use of the original model’s questionnaire to gather all expert’s data and also SPSS and AMOS Ver.22 to analyze the gathered data. CFA method was also used to test whether a relationship between observed variables and their underlying latent constructs exists. Supply chain strategy implementation leads to logistics performance improvement, and marketing performance will be affected as well. Logistics service providers should focus on enhancement of supply chain performance, since logistics performance has been considered as a basis of evaluation of supply chain management strategy. Consequently, performance of the organization will be enhanced. This case is the first research made in Iran that analyzes the relationship between Logistics & Organizational performance in Home Appliances and Home Entertainment companies.

Keywords: Logistics, organizational performance, supply chain, supply chain strategy.

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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Authors: H. Alaleh, N. Hedayat, A. Alaleh, H. Ayazi, A. Ruhani

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Run-offs are considered as important hydrological factors in feasibility studies of river engineering and irrigation-related projects under arid and semi-arid condition. Flood control is one of the crucial factor, the management of which while mitigates its destructive consequences, abstracts considerable volume of renewable water resources. The methodology applied here was based on Mizumura, which applied a mathematical model for simple tank to simulate the rainfall-run-off process in a particular water basin using the data from the observational hydrograph. The model was applied in the Dez River water basin adjacent to Greater Dezful region, Iran in order to simulate and estimate the floods. Results indicated that the calculated hydrographs using the simple tank method, SCS-CN model and the observation hydrographs had a close proximity. It was also found that on average the flood time and discharge peaks in the simple tank were closer to the observational data than the CN method. On the other hand, the calculated flood volume in the CN model was significantly closer to the observational data than the simple tank model.

Keywords: Simple tank, Dez River, run-off, lag time, excess rainfall.

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Authors: Zhanna Mingaleva, Irina Mirskikh

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Part IV of the Civil Code of the Russian Federation dedicated to legal regulation of Intellectual property rights came into force in 2008. It is a first attempt of codification in Intellectual property sphere in Russia. That is why a lot of new norms appeared. The main problem of the Russian Civil Code (part IV) is that many rules (norms of Law) contradict the norms of International Intellectual property Law (i.e. protection of inventions, creations, ideas, know-how, trade secrets, innovations). Intellectual property rights protect innovations and creations and reward innovative and creative activity. Intellectual property rights are international in character and in that respect they fit in rather well with the economic reality of the global economy. Inventors prefer not to take out a patent for inventions because it is a very difficult procedure, it takes a lot of time and is very expensive. That-s why they try to protect their inventions as ideas, know-how, confidential information. An idea is the main element of any object of Intellectual property (creation, invention, innovation, know-how, etc.). But ideas are not protected by Civil Code of Russian Federation. The aim of the paper is to reveal the main problems of legal regulation of Intellectual property in Russia and to suggest possible solutions. The authors of this paper have raised these essential issues through different activities. Through the panel survey, questionnaires which were spread among the participants of intellectual activities the main problems of implementation of innovations, protecting of the ideas and know-how were identified. The implementation of research results will help to solve economic and legal problems of innovations, transfer of innovations and intellectual property.1

Keywords: Innovation activities, intellectual property rights, know-how, patents, indicators of innovation activities

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Authors: Giwrgos S. Gkarmpounis, Aikaterini G. Rokkou, Marios N. Moschakis

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Increased energy consumption in the academic buildings, creates the need to implement energy saving measures and to take advantage of the renewable energy sources to cover the electrical needs of those buildings. An Academic Library will be used as a case study. With the aid of RETScreen software that takes into account the energy consumptions and characteristics of the Library Building, it is proved that measures such as the replacement of fluorescent lights with led lights, the installation of outdoor shading, the replacement of the openings and Building Management System installation, provide a high level of energy savings. Moreover, given the available space of the building and the climatic data, the installation of a photovoltaic system of 100 kW can also cover a serious amount of the building energy consumption, unlike a wind system that seems uncompromising. Lastly, HOMER software is used to compare the use of a photovoltaic system against a wind system in order to verify the results that came up from the RETScreen software concerning the renewable energy sources.

Keywords: Energy saving measures, homer software, renewable energy sources, RETScreen software, energy efficiency and quality.

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Authors: Zita I. Šereš, Ljubica P. Dokić, Dragana M. Šoronja Simović, Cecilia Hodur, Zsuzsanna Laszlo, Ivana Nikolić, Nikola Maravić

Abstract:

In this work the concentration of steepwater from corn starch industry is monitored using ultrafiltration membrane. The aim was to examine the conditions of ultrafiltration of steepwater by applying the membrane of 2.5nm. The parameters that vary during the course of ultrafiltration, were the transmembrane pressure, flow rate, while the permeate flux and the dry matter content of permeate and retentate were the dependent parameter constantly monitored during the process. Experiments of ultrafiltration are conducted on the samples of steepwater, which were obtained from the starch wet milling plant „Jabuka“ Pancevo. The procedure of ultrafiltration on a single-channel 250mm lenght, with inner diameter of 6.8mm and outer diameter of 10mm membrane were carried on. The membrane is made of a-Al₂O₃ with TiO₂ layer obtained from GEA (Germany). The experiments are carried out at a flow rate ranging from 100 to 200lh^-1 and transmembrane pressure of 1-3 bars. During the experiments of steepwater ultrafiltration, the change of permeate flux, dry matter content of permeate and retentate, as well as the absorbance changes of the permeate and retentate were monitored. The experimental results showed that the maximum flux reaches about 40lm^-2h^-1. For responses obtained after experiments, a polynomial model of the second degree is established to evaluate and quantify the influence of the variables. The quadratic equitation fits with the experimental values, where the coefficient of determination for flux is 0.96. The dry matter content of the retentate is increased for about 6%, while the dry matter content of permeate was reduced for about 35-40%, respectively. During steepwater ultrafiltration in permeate stays 40% less dry matter compared to the feed.

Keywords: Ultrafiltration, steepwater, starch industry, ceramic membrane.

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Authors: Toby Gibbs, Suwaree Yordchim

Abstract:

This research analyzes factors affecting the success of Litecoin Value within Thailand and develops a guideline for selfreliance for effective business implementation. Samples in this study included 119 people through surveys. The results revealed four main factors affecting the success as follows: 1) Future Career training should be pursued in applied Litecoin development. 2) Didn't grasp the concept of a digital currency or see the benefit of a digital currency. 3) There is a great need to educate the next generation of learners on the benefits of Litecoin within the community. 4) A great majority didn't know what Litecoin was. The guideline for self-reliance planning consisted of 4 aspects: 1) Development planning: by arranging meet up groups to conduct further education on Litecoin and share solutions on adoption into every day usage. Local communities need to develop awareness of the usefulness of Litecoin and share the value of Litecoin among friends and family. 2) Computer Science and Business Management staff should develop skills to expand on the benefits of Litecoin within their departments. 3) Further research should be pursued on how Litecoin Value can improve business and tourism within Thailand. 4) Local communities should focus on developing Litecoin awareness by encouraging street vendors to accept Litecoin as another form of payment for services rendered.

Keywords: Litecoin, Mining, Confirmations.

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Authors: Zaza Tabagari, Zaza Sanikidze, George Giorgobiani

Abstract:

Abovepresented work deals with the new scope of application of information and communication technologies for the improvement of the election process in the biased environment. We are introducing a new concept of construction of the information-communication system for the election participant. It consists of four main components: Software, Physical Infrastructure, Structured Information and the Trained Stuff. The Structured Information is the bases of the whole system and is the collection of all possible events (irregularities among them) at the polling stations, which are structured in special templates, forms and integrated in mobile devices.The software represents a package of analytic modules, which operates with the dynamic database. The application of modern communication technologies facilities the immediate exchange of information and of relevant documents between the polling stations and the Server of the participant. No less important is the training of the staff for the proper functioning of the system. The e-training system with various modules should be applied in this respect. The presented methodology is primarily focused on the election processes in the countries of emerging democracies.It can be regarded as the tool for the monitoring of elections process by the political organization(s) and as one of the instruments to foster the spread of democracy in these countries.

Keywords: ICT, elections, structured information, dynamic databases, e-training.

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Authors: Charles D. Otine, Samuel B. Kucel, Lena Trojer

Abstract:

Selecting the data modeling technique for an information system is determined by the objective of the resultant data model. Dimensional modeling is the preferred modeling technique for data destined for data warehouses and data mining, presenting data models that ease analysis and queries which are in contrast with entity relationship modeling. The establishment of data warehouses as components of information system landscapes in many organizations has subsequently led to the development of dimensional modeling. This has been significantly more developed and reported for the commercial database management systems as compared to the open sources thereby making it less affordable for those in resource constrained settings. This paper presents dimensional modeling of HIV patient information using open source modeling tools. It aims to take advantage of the fact that the most affected regions by the HIV virus are also heavily resource constrained (sub-Saharan Africa) whereas having large quantities of HIV data. Two HIV data source systems were studied to identify appropriate dimensions and facts these were then modeled using two open source dimensional modeling tools. Use of open source would reduce the software costs for dimensional modeling and in turn make data warehousing and data mining more feasible even for those in resource constrained settings but with data available.

Keywords: About Database, Data Mining, Data warehouse, Dimensional Modeling, Open Source.

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Authors: Pongsiri Kingkan

Abstract:

This paper aims to study the role and activities of the participants and the impact of activities created in the local area in order to sustainably develop the local areas. This study applied both qualitative and quantitative approaches presented in descriptive style; the data was collected via survey, observation and in-depth interviews with samples. The results illustrated five sorts of roles of participants of the Cicada Walking-street and four types of creative activities; recreation based, art based, cultural based, and live events. Integration of local characteristics, arts and cultures were presented creatively and interestingly. Participants are various. The roles of the participants found in the Cicada Market are group of the property and area management, entrepreneurs, leisure (entertaining persons), local people, and tourists. The good impacts on local communities are those in terms of economy, environmental friendly and local arts and cultures promoting. On the other hand, the traffic congestion, waste and the increasing of energy consumption are negative impacts from area development.

Keywords: Creative Tourism Activity, Destination Development, Sustainable Development, Walking Street.

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Authors: Adam Pitluk

Abstract:

In a time period populated by legacy newspaper readers who throw around the term “fake news” as though it has long been a part of the lexicon, journalism schools must convince would-be students that their degree is still viable and that they are not teaching a curriculum of deception. As such, journalism schools’ academic administrators tasked with creating and maintaining conversant curricula must stay ahead of legacy newspaper industry trends – both in the print and online products – and ensure that what is being taught in the classroom is both fresh and appropriate to the demands of the evolving legacy newspaper industry. This study examines the information obtained from the result of interviews of journalism academic administrators in order to identify institutional pedagogy for recent journalism school graduates interested in pursuing careers at legacy newspapers. This research also explores the existing relationship between journalism school academic administrators and legacy newspaper editors. The results indicate the value administrators put on various academy teachings, and they also highlight a perceived disconnect between journalism academic administrators and legacy newspaper hiring editors.

Keywords: Academic administration, education, journalism, media management, newspapers.

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