Search results for: multiple criteria decision making (MCDM)

Authors: A. S. Adesuyi, Z. Munch

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This study investigates the use of a time-series of MODIS NDVI data to identify agricultural land cover change on an annual time step (2007 - 2012) and characterize the trend. Following an ISODATA classification of the MODIS imagery to selectively mask areas not agriculture or semi-natural, NDVI signatures were created to identify areas cereals and vineyards with the aid of ancillary, pictometry and field sample data for 2010. The NDVI signature curve and training samples were used to create a decision tree model in WEKA 3.6.9 using decision tree classifier (J48) algorithm; Model 1 including ISODATA classification and Model 2 not. These two models were then used to classify all data for the study area for 2010, producing land cover maps with classification accuracies of 77% and 80% for Model 1 and 2 respectively. Model 2 was subsequently used to create land cover classification and change detection maps for all other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices. Over the years as predicted by the land cover classification. Forty one percent of the catchment comprised of cereals with 35% possibly following a crop rotation system. Vineyards largely remained constant with only one percent conversion to vineyard from other land cover classes.

Keywords: Change detection, Land cover, NDVI, time-series.

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Authors: S. Wongkoon, M. Jaroensutasinee, K. Jaroensutasinee, W. Preechaporn, S. Chumkiew

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This study investigated the number of Aedes larvae, the key breeding sites of Aedes sp., and the relationship between climatic factors and the incidence of DHF in Samui Islands. We conducted our questionnaire and larval surveys from randomly selected 105 households in Samui Islands in July-September 2006. Pearson-s correlation coefficient was used to explore the primary association between the DHF incidence and all climatic factors. Multiple stepwise regression technique was then used to fit the statistical model. The results showed that the positive indoor containers were small jars, cement tanks, and plastic tanks. The positive outdoor containers were small jars, cement tanks, plastic tanks, used cans, tires, plastic bottles, discarded objects, pot saucers, plant pots, and areca husks. All Ae. albopictus larval indices (i.e., CI, HI, and BI) were higher than Ae. aegypti larval indices in this area. These larval indices were higher than WHO standard. This indicated a high risk of DHF transmission at Samui Islands. The multiple stepwise regression model was y = –288.80 + 11.024xmean temp. The mean temperature was positively associated with the DHF incidence in this area.

Keywords: Dengue vectors, Aedes aegypti, Aedes albopictus, Container Index, House Index, Breteau Index, Aedes indices, Climatic factors, Temperature.

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Authors: Yanling Zhu, Kai Wang

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By means of Mawhin’s continuation theorem, we study a kind of third-order p-Laplacian functional differential equation with distributed delay in the form: ϕp(x (t)) = g  t,  0 −τ x(t + s) dα(s)  + e(t), some criteria to guarantee the existence of periodic solutions are obtained.

Keywords: p–Laplacian, distributed delay, periodic solution, Mawhin's continuation theorem.

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Authors: H. Al-Baghli, F. Al-Asfour

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The current applied asphalt technology for Kuwait roads pavement infrastructure is the hot mix asphalt (HMA) pavement, including both pen grade and polymer modified bitumen (PMBs), that is produced and compacted at high temperature levels ranging from 150 to 180 °C. There are no current specifications for warm and cold mix asphalts in Kuwait’s Ministry of Public Works (MPW) asphalt standard and specifications. The process of the conventional HMA is energy intensive and directly responsible for the emission of greenhouse gases and other environmental hazards into the atmosphere leading to significant environmental impacts and raising health risk to labors at site. Warm mix asphalt (WMA) technology, a sustainable alternative preferred in multiple countries, has many environmental advantages because it requires lower production temperatures than HMA by 20 to 40 °C. The reduction of temperatures achieved by WMA originates from multiple technologies including foaming and chemical or organic additives that aim to reduce bitumen and improve mix workability. This paper presents a literature review of WMA technologies and techniques followed by an experimental study aiming to compare the results of produced WMA samples, using a water containing additive (foaming process), at different compaction temperatures with the HMA control volumetric properties mix designed in accordance to the new MPW’s specifications and guidelines.

Keywords: Warm-mix asphalt, water-bearing additives, foaming-based process, chemical additives, organic additives.

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Authors: David Calderón Villegas, Thomas Kalitzky

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Run-of-river (RoR) hydropower projects represent a viable, clean, and cost-effective alternative to dam-based plants and provide decentralized power production. However, RoR schemes’ cost-effectiveness depends on the proper selection of site and design flow, which is a challenging task because it requires multivariate analysis. In this respect, this study presents the development of an investment decision support tool for assessing the optimal size of an RoR scheme considering the technical, environmental, and cost constraints. The net present value (NPV) from a project perspective is used as an objective function for supporting the investment decision. The tool has been tested by applying it to an actual RoR project recently proposed in Colombia. The obtained results show that the optimum point in financial terms does not match the flow that maximizes energy generation from exploiting the river's available flow. For the case study, the flow that maximizes energy corresponds to a value of 5.1 m3/s. In comparison, an amount of 2.1 m3/s maximizes the investors NPV. Finally, a sensitivity analysis is performed to determine the NPV as a function of the debt rate changes and the electricity prices and the CapEx. Even for the worst-case scenario, the optimal size represents a positive business case with an NPV of 2.2 USD million and an internal rate of return (IRR) 1.5 times higher than the discount rate. 

Keywords: small hydropower, renewable energy, RoR schemes, optimal sizing, financial analysis

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Authors: Su-Yan Tang, Wei Zhang, Shan Mei, Yi-Fan Zhu

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Network-Centric Air Defense Missile Systems (NCADMS) represents the superior development of the air defense missile systems and has been regarded as one of the major research issues in military domain at present. Due to lack of knowledge and experience on NCADMS, modeling and simulation becomes an effective approach to perform operational analysis, compared with those equation based ones. However, the complex dynamic interactions among entities and flexible architectures of NCADMS put forward new requirements and challenges to the simulation framework and models. ABS (Agent-Based Simulations) explicitly addresses modeling behaviors of heterogeneous individuals. Agents have capability to sense and understand things, make decisions, and act on the environment. They can also cooperate with others dynamically to perform the tasks assigned to them. ABS proves an effective approach to explore the new operational characteristics emerging in NCADMS. In this paper, based on the analysis of network-centric architecture and new cooperative engagement strategies for NCADMS, an agent-based simulation framework by expanding the simulation framework in the so-called System Effectiveness Analysis Simulation (SEAS) was designed. The simulation framework specifies components, relationships and interactions between them, the structure and behavior rules of an agent in NCADMS. Based on scenario simulations, information and decision superiority and operational advantages in NCADMS were analyzed; meanwhile some suggestions were provided for its future development.

Keywords: air defense missile systems, network-centric, agent-based simulation, simulation framework, information superiority, decision superiority, operational advantages

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Authors: Laura Álvarez Antón, Joaquín Díaz

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The construction industry is turning towards sustainability. It is a well-known fact that sustainability is based on a balance between environmental, social and economic aspects. In order to achieve sustainability efficiently, these three criteria should be taken into account in the initial project phases, since that is when a project can be influenced most effectively. Thus the aim must be to integrate important tools like BIM and LCA at an early stage in order to make full use of their potential. With the synergies resulting from the integration of BIM and LCA, a wider approach to sustainability becomes possible, covering the three pillars of sustainability.

Keywords: Building Information Modeling (BIM), Construction Industry, Design Phase, Life Cycle Assessment (LCA), Sustainability.

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Authors: Rodrigo T. Lourenço, Margarida Mano

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Higher Education Institutions (HEI), and other levels of Education, face important challenges. One of the most relevant one is the ability to adapt to a society that is changing over time, whilst guarantying levels of training that do not merely react to such changes. Thus, interacting with society, particularly with surrounding communities and key stakeholders, has become an essential requirement for the sustainability of these institutions. One of the formal mechanisms implemented in European educational institutions has been the design of organizational structures that include a top governance body sharing its constitution with both internal members, students and external members. Such frame holds the core mission of involving communities in the governance of educational institutions, assuming, both strategic decision-making functions, with the approval of the institutions’ strategic plans, and a supervision function, approved by activity reports. It also plays an essential role in the life of institutions by holding the responsibility of electing its top executives. In Portugal, it has been almost a decade since the publication of RJIES, the legal framework of Higher Education, such bodies being designated by General Councils. Thus, one may highlight that there has been a better understanding of the operative process of these bodies, as well as their added value to the education system. It has also been possible to analyse the extent to which their core mission has been fulfilled and to understand its growing relevance, particularly regarding the autonomy of institutions. This article aims to contribute to this theme by presenting the results of a study on the role of these bodies in the governance of Public Portuguese HEI, with a special focus on the supervisory competence of organizational performance. Through questionnaires made to board members and interviews with chairpersons of the bodies and top managers of the institutions, it was possible to conclude that there is a high concern with the connections to the external environment. However, regarding organizational performance and the role of the Council as a supervisor of that performance, the activity of the bodies has fallen short of what would be expected. Several reasons may be identified. It is important to emphasize the importance of the profile of the external members and the relationship between the organ’s standard functioning and the election of the head of the institution.

Keywords: Governance, stakeholders, supervision, organizational performance.

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The modern Artificial Narrow Intelligence (ANI) models cannot: a) independently, situationally, and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, and cognize under uncertainty and changing of the environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU). This system uses a neural network as its computational memory, and activates functions of the perception, identification of real objects, fuzzy situational control, and forming images of these objects. These images and objects are used for modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision Making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, and Wisdom. In doing so are performed analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge of the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of situational control, fuzzy logic, psycholinguistics, informatics, and modern possibilities of data science were applied. The proposed self-controlled system of brain and mind is oriented on use as a plug-in in multilingual subject applications.

Keywords: Computational psycholinguistic cognitive brain and mind system, situational fuzzy control, uncertainty, AI.

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Authors: Arunesh Chandra, Pankaj Chandna, Surinder Deswal, Rajesh Kumar Mishra, Rajender Kumar

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The arm length, hand length, hand breadth and middle finger length of 1540 right-handed industrial workers of Haryana state was used to assess the relationship between the upper limb dimensions and stature. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then simple and multiple linear regression models were used to estimate stature using SPSS (version 17). There was a positive correlation between upper limb measurements (hand length, hand breadth, arm length and middle finger length) and stature (p < 0.01), which was highest for hand length. The accuracy of stature prediction ranged from ± 54.897 mm to ± 58.307 mm. The use of multiple regression equations gave better results than simple regression equations. This study provides new forensic standards for stature estimation from the upper limb measurements of male industrial workers of Haryana (India). The results of this research indicate that stature can be determined using hand dimensions with accuracy, when only upper limb is available due to any reasons likewise explosions, train/plane crashes, mutilated bodies, etc. The regression formula derived in this study will be useful for anatomists, archaeologists, anthropologists, design engineers and forensic scientists for fairly prediction of stature using regression equations.

Keywords: Anthropometric dimensions, Forensic identification, Industrial workers, Stature prediction.

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Authors: Yoonjung An, Yongtae Park

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Offering a Product-Service System (PSS) is a well-accepted strategy that companies may adopt to provide a set of systemic solutions to customers. PSSs were initially provided in a simple form but now take diversified and complex forms involving multiple services, products and technologies. With the growing interest in the PSS, frameworks for the PSS development have been introduced by many researchers. However, most of the existing frameworks fail to examine various relations existing in a complex PSS. Since designing a complex PSS involves full integration of multiple products and services, it is essential to identify not only product-service relations but also product-product/ service-service relations. It is also equally important to specify how they are related for better understanding of the system. Moreover, as customers tend to view their purchase from a more holistic perspective, a PSS should be developed based on the whole system’s requirements, rather than focusing only on the product requirements or service requirements. Thus, we propose a framework to develop a complex PSS that is coordinated fully with the requirements of both worlds. Specifically, our approach adopts a multi-domain matrix (MDM). A MDM identifies not only inter-domain relations but also intra-domain relations so that it helps to design a PSS that includes highly desired and closely related core functions/ features. Also, various dependency types and rating schemes proposed in our approach would help the integration process.

Keywords: Inter-domain relations, intra-domain relations, multi-domain matrix, product-service system design.

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Authors: Kanthida Kusonmano, Michael Netzer, Bernhard Pfeifer, Christian Baumgartner, Klaus R. Liedl, Armin Graber

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Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.

Keywords: Classification, High dimensional data, Machine learning

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Authors: Orkide Donma, Mustafa M. Donma

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Morbid obesity is a health threatening condition particularly in children. Generally, it leads to the development of metabolic syndrome (MetS) characterized by central obesity, elevated fasting blood glucose (FBG), triglyceride (TRG), blood pressure values and suppressed high density lipoprotein cholesterol (HDL-C) levels. However, some ambiguities exist during the diagnosis of MetS in children below 10 years of age. Therefore, clinicians are in the need of some surrogate markers for the laboratory assessment of pediatric MetS. In this study, the aim is to develop an index, which will be more helpful during the evaluation of further risks detected in morbid obese (MO) children. A total of 235 children with normal body mass index (N-BMI), with varying degrees of obesity; overweight (OW), obese (OB), MO as well as MetS participated in this study. The study was approved by the Institutional Ethical Committee. Informed consent forms were obtained from the parents of the children. Obesity states of the children were classified using BMI percentiles adjusted for age and sex. For the purpose, tabulated data prepared by WHO were used. MetS criteria were defined. Systolic and diastolic blood pressure values were measured. Parameters related to glucose and lipid metabolisms were determined. FBG, insulin (INS), HDL-C, TRG concentrations were determined. Diagnostic Obesity Notation Model Assessment Laboratory (DONMA_LAB) Index [ln TRG/HDL-C*INS] was introduced. Commonly used insulin resistance (IR) indices such as Homeostatic Model Assessment for IR (HOMA-IR) as well as ratios such as TRG/HDL-C, TRG/HDL-C*INS, HDL-C/TRG*INS, TRG/HDL-C*INS/FBG, log, and ln versions of these ratios were calculated. Results were interpreted using statistical package program (SPSS Version 16.0) for Windows. The data were evaluated using appropriate statistical tests. The degree for statistical significance was defined as 0.05. 35 N, 20 OW, 47 OB, 97 MO children and 36 with MetS were investigated. Mean ± SD values of TRG/HDL-C were 1.27 ± 0.69, 1.86 ± 1.08, 2.15 ± 1.22, 2.48 ± 2.35 and 4.61 ± 3.92 for N, OW, OB, MO and MetS children, respectively. Corresponding values for the DONMA_LAB index were 2.17 ± 1.07, 3.01 ± 0.94, 3.41 ± 0.93, 3.43 ± 1.08 and 4.32 ± 1.00. TRG/HDL-C ratio significantly differed between N and MetS groups. On the other hand, DONMA_LAB index exhibited statistically significant differences between N and all the other groups except the OW group. This index was capable of discriminating MO children from those with MetS. Statistically significant elevations were detected in MO children with MetS (p < 0.05). Multiple parameters are commonly used during the assessment of MetS. Upon evaluation of the values obtained for N, OW, OB, MO groups and for MO children with MetS, the [ln TRG/HDL-C*INS] value was unique in discriminating children with MetS.

Keywords: Children, index, laboratory, metabolic syndrome, obesity.

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Authors: Valeria Tatano, Francesca Guidolin, Francesca Peltrera

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The preservation of historical Italian heritage, at the urban and architectural scale, has to consider restrictions and requirements connected with conservation issues and usability needs, which are often at odds with historical heritage preservation. Recent decades have been marked by the search for increased accessibility not only of public and private buildings, but to the whole historical city, also for people with disability. Moreover, in the last years the concepts of Smart City and Healthy City seek to improve accessibility both in terms of mobility (independent or assisted) and fruition of goods and services, also for historical cities. The principles of Inclusive Design have introduced new criteria for the improvement of public urban space, between current regulations and best practices. Moreover, they have contributed to transforming “special needs” into an opportunity of social innovation. These considerations find a field of research and analysis in the historical city of Venice, which is at the same time a site of UNESCO world heritage, a mass tourism destination bringing in visitors from all over the world and a city inhabited by an aging population. Due to its conformation, Venetian urban fabric is only partially accessible: about four thousand bridges divide thousands of islands, making it almost impossible to move independently. These urban characteristics and difficulties were the base, in the last 20 years, for several researches, experimentations and solutions with the aim of eliminating architectural barriers, in particular for the usability of bridges. The Venetian Municipality with the EBA Office and some external consultants realized several devices (e.g. the “stepped ramp” and the new accessible ramps for the Venice Marathon) that should determine an innovation for the city, passing from the use of mechanical replicable devices to specific architectural projects in order to guarantee autonomy in use. This paper intends to present the state-of-the-art in bridges accessibility, through an analysis based on Inclusive Design principles and on the current national and regional regulation. The purpose is to evaluate some possible strategies that could improve performances, between limits and possibilities of interventions. The aim of the research is to lay the foundations for the development of a strategic program for the City of Venice that could successfully bring together both conservation and improvement requirements.

Keywords: Accessibility and inclusive design, historical heritage preservation, technological and social innovation.

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Authors: B. Frączek

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The paper analyses the usage of the Internet by university students in Visegrad Countries (4V Countries) who study economic fields in their formal and informal financial education and captures the areas of untapped potential of Internet in educational processes. Higher education and training, technological readiness, and the financial market development are in the group of pillars, that are key for efficiency driven economies. These three pillars have become an inspiration to the research on using the Internet in the financial education among economic university students as the group of the best educated people in finance. The financial education is a process that allows for improving the level of financial literacy. In turn, the financial literacy it is the set of financial knowledge, skills, awareness and patterns influencing the financial decisions. The level of financial literacy influences the level of financial well-being of individuals, determines the scale of saving of households and at the same time gives the greater chance for sustainable and more predictable development of the financial market with the positive impact on economy. The financial literacy is necessary for each group of society but its appropriate level is desirable especially in respect of economics students as future participants of financial markets as well as the experts and advisors in financial decision making. The low level of financial literacy is the great problem of many target groups in both developing and developed countries and the financial education is seen as the best way of improving this situation. Also the financial inclusion plays the special role in enhancing the level of financial literacy in the aspect of education by practice as well as due to interrelation between level of financial literacy and degree of financial inclusion. Despite many initiatives under financial education, the level of financial literacy is still very low. Scientists still search for new ways of solving this problem. One of the proposal is more effective usage of the new technology in financial education, especially the Internet, because of the growing popularity of e-learning and the increasing number of Internet users, especially among young people who are called the Generation Net. Due to special role of the university students studying the economics fields for the future financial markets, students of four universities from Visegrad Countries (Czech Republic, Hungary, Poland and Slovakia) were invited to participate in the survey. The aim of the article is to present the level and ways of using the Internet technology in financial education and indicating the so far unused or underused opportunities.

Keywords: Financial education, financial inclusion, financial literacy, usage of Internet in education.

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Authors: Nicolas Zufferey

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The vehicle routing problem (VRP) is a famous combinatorial optimization problem. Because of its well-known difficulty, metaheuristics are the most appropriate methods to tackle large and realistic instances. The goal of this paper is to highlight the key ideas for designing VRP metaheuristics according to the following criteria: efficiency, speed, robustness, and ability to take advantage of the problem structure. Such elements can obviously be used to build solution methods for other combinatorial optimization problems, at least in the deterministic field.

Keywords: Vehicle routing problem, Metaheuristics, Combinatorial optimization.

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Authors: Ekprasit Promtun, Sridhar Seshagiri

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This paper considers the control of the longitudinal flight dynamics of an F-16 aircraft. The primary design objective is model-following of the pitch rate q, which is the preferred system for aircraft approach and landing. Regulation of the aircraft velocity V (or the Mach-hold autopilot) is also considered, but as a secondary objective. The problem is challenging because the system is nonlinear, and also non-affine in the input. A sliding mode controller is designed for the pitch rate, that exploits the modal decomposition of the linearized dynamics into its short-period and phugoid approximations. The inherent robustness of the SMC design provides a convenient way to design controllers without gain scheduling, with a steady-state response that is comparable to that of a conventional polynomial based gain-scheduled approach with integral control, but with improved transient performance. Integral action is introduced in the sliding mode design using the recently developed technique of “conditional integrators", and it is shown that robust regulation is achieved with asymptotically constant exogenous signals, without degrading the transient response. Through extensive simulation on the nonlinear multiple-input multiple-output (MIMO) longitudinal model of the F-16 aircraft, it is shown that the conditional integrator design outperforms the one based on the conventional linear control, without requiring any scheduling.

Keywords: Sliding-mode Control, Integral Control, Model Following, F-16 Longitudinal Dynamics, Pitch-Rate Control.

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Authors: Mustafa M. Donma, Erkut Karasu, Burcu Ozdilek, Burhan Turgut, Birol Topcu, Burcin Nalbantoglu, Orkide Donma

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The mechanisms underlying the association between obesity and asthma may be related to a decreased immunological tolerance induced by a defective function of regulatory T cells (Tregs). The aim of this study is to establish the potential link between these diseases and CD4+, CD25+ FoxP3+ Tregs as well as T helper cells (Ths) in children. This is a prospective case control study. Obese (n:40), asthmatic (n:40), asthmatic obese (n:40) and healthy children (n:40), who don't have any acute or chronic diseases, were included in this study. Obese children were evaluated according to WHO criteria. Asthmatic patients were chosen based on GINA criteria. Parents were asked to fill up the questionnaire. Informed consent forms were taken. Blood samples were marked with CD4+, CD25+ and FoxP3+ in order to determine Tregs and Ths by flow cytometric method. Statistical analyses were performed. p≤0.05 was chosen as meaningful threshold. Tregs exhibiting anti-inflammatory nature were significantly lower in obese (0,16%; p≤0,001), asthmatic (0,25%; p≤0,01) and asthmatic obese (0,29%; p≤0,05) groups than the control group (0,38%). Ths were counted higher in asthma group than the control (p≤0,01) and obese (p≤0,001) groups. T cell immunity plays important roles in obesity and asthma pathogeneses. Decreased numbers of Tregs found in obese, asthmatic and asthmatic obese children may help to elucidate some questions in pathophysiology of these diseases. For HOMA-IR levels, any significant difference was not noted between control and obese groups, but statistically higher values were found for obese asthmatics. The values obtained in all groups were found to be below the critical cut off points. This finding has made the statistically significant difference observed between Tregs of obese, asthmatic, obese asthmatic and control groups much more valuable. These findings will be useful in diagnosis and treatment of these disorders and future studies are needed. The production and propagation of Tregs may be promising in alternative asthma and obesity treatments.

Keywords: Asthma, flow cytometry, pediatric obesity, T cells.

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Authors: Jong-Moon Chung, Hyung-Weon Cho, Ki-Yong Jin, Min-Hee Cho

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In this paper, we present an analytical framework for the evaluation of the uplink performance of multihop cellular networks based on dynamic time division duplex (TDD). New wireless broadband protocols, such as WiMAX, WiBro, and 3G-LTE apply TDD, and mobile communication protocols under standardization (e.g., IEEE802.16j) are investigating mobile multihop relay (MMR) as a future technology. In this paper a novel MMR TDD scheme is presented, where the dynamic range of the frame is shared to traffic resources of asymmetric nature and multihop relaying. The mobile communication channel interference model comprises of inner and co-channel interference (CCI). The performance analysis focuses on the uplink due to the fact that the effects of dynamic resource allocation show significant performance degradation only in the uplink compared to time division multiple access (TDMA) schemes due to CCI [1-3], where the downlink results to be the same or better.The analysis was based on the signal to interference power ratio (SIR) outage probability of dynamic TDD (D-TDD) and TDMA systems,which are the most widespread mobile communication multi-user control techniques. This paper presents the uplink SIR outage probability with multihop results and shows that the dynamic TDD scheme applying MMR can provide a performance improvement compared to single hop applications if executed properly.

Keywords: Co-Channel Interference, Dynamic TDD, MobileMultihop Reply, Cellular Network, Time Division Multiple Access.

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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: Shin-Hyung Cho, Dong-Kyu Kim, Seung-Young Kho

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Truck-involved crashes have higher crash severity than non-truck-involved crashes. There have been many studies about the frequency of crashes and the development of severity models, but those studies only analyzed the relationship between observed variables. To identify why more people are injured or killed when trucks are involved in the crash, we must examine to quantify the complex causal relationship between severity of the crash and risk factors by adopting the latent factors of crashes. The aim of this study was to develop a structural equation or model based on truck-involved and non-truck-involved crashes, including five latent variables, i.e. a crash factor, environmental factor, road factor, driver’s factor, and severity factor. To clarify the unique characteristics of truck-involved crashes compared to non-truck-involved crashes, a confirmatory analysis method was used. To develop the model, we extracted crash data from 10,083 crashes on Korean freeways from 2008 through 2014. The results showed that the most significant variable affecting the severity of a crash is the crash factor, which can be expressed by the location, cause, and type of the crash. For non-truck-involved crashes, the crash and environment factors increase severity of the crash; conversely, the road and driver factors tend to reduce severity of the crash. For truck-involved crashes, the driver factor has a significant effect on severity of the crash although its effect is slightly less than the crash factor. The multiple group analysis employed to analyze the differences between the heterogeneous groups of drivers.

Keywords: Crash severity, structural equation modeling, truck-involved crashes, multiple group analysis, crash on freeway.

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Authors: Excellence Favor, Bakari M. M. Mwinyiwiwa

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Access to information holds the key to the empowerment of everybody despite where they are living. This research has been carried out in respect of the people living in developing countries, considering their plight and complex geographical, demographic, social-economic conditions surrounding the areas they live, which hinder access to information and of professionals providing services such as medical workers, which has led to high death rates and development stagnation. Research on Unified Communications and Integrated Collaborations (UCIC) system in the health sector of developing countries aims at creating a possible solution of bridging the digital canyon among the communities. The system is meant to deliver services in a seamless manner to assist health workers situated anywhere to be accessed easily and access information which will enhance service delivery. The proposed UCIC provides the most immersive telepresence experience for one-to-one or many-to-many meetings. Extending to locations anywhere in the world, the transformative platform delivers Ultra-low operating costs through the use of general purpose networks and using special lenses and track systems. The essence of this study is to create a security model for the deployment of the UCIC system in the health sector of developing countries. The model approach used for building the UCIC system security carefully considers the specific requirements for the health sector environment organization such as data centre, national, regional and district hospitals, and health centers IV, III, II and I and then builds the single best possible secure network to meet their needs. The security model demonstrates on how the components of the UCIC system will be protected physically and logically in the health sector environment. The UCIC system once adopted and implemented correctly will bring enhancement to the speed and quality of services offered by health workers. The capacities of UCIC will help health workers shorten decision cycles, accelerate service delivery and save lives by speeding access to information and by making it possible for all health workers and patients to collaborate ubiquitously.

Keywords: Developing Countries, Health Sector Environment, Security, Unified Communications and Integrated Collaborations.

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: Search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization.

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Authors: Adnene Arbi, Chaouki Aouiti, Abderrahmane Touati

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In this paper, we consider the global exponential stability of the equilibrium point of Hopfield neural networks with delays and impulsive perturbation. Some new exponential stability criteria of the system are derived by using the Lyapunov functional method and the linear matrix inequality approach for estimating the upper bound of the derivative of Lyapunov functional. Finally, we illustrate two numerical examples showing the effectiveness of our theoretical results.

Keywords: Hopfield Neural Networks, Exponential stability.

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Authors: Frances Turner

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Gloves are significant physical objects, being one of the oldest forms of dress. Glove culture is part of every facet of life; its extraordinary history encompasses practicality, and symbolism reflecting a wide range of social practices. The survival of not only the gloves but associated articles enables the possibility to analyse real lives, however so far this area has been largely neglected. Limited information is available to students, researchers, or those involved with the design and making of gloves. There are several museums and independent collectors in England that hold collections of gloves (some from as early as 16th century), machinery, tools, designs and patterns, marketing materials and significant archives which demonstrate the rich heritage of English glove design and manufacturing, being of national significance and worthy of international interest. Through a research glove network which now exists thanks to research grant funding, there is potential for the holders of glove collections to make connections and explore links between these resources to promote a stronger understanding of the significance, breadth and heritage of the English glove industry. The network takes an interdisciplinary approach to bring together interested parties from academia, museums and manufacturing, with expert knowledge of the production, collections, conservation and display of English leather gloves. Academics from diverse arts and humanities disciplines benefit from the opportunities to share research and discuss ideas with network members from non-academic contexts including museums and heritage organisations, industry, and contemporary designers. The fragmented collections when considered in entirety provide an overview of English glove making since earliest times and those who wore them. This paper makes connections and explores links between these resources to promote a stronger understanding of the significance, breadth and heritage of the English Glove industry. The following areas are explored: current content and status of the individual museum collections, potential links, sharing of information histories, social and cultural and relationship to history of fashion design, manufacturing and materials, approaches to maintenance and conservation, access to the collections and strategies for future understanding of their national significance. The facilitation of knowledge exchange and exploration of the collections through the network informs organisations’ future strategies for the maintenance, access and conservation of their collections. By involving industry in the network, it is possible to ensure a contemporary perspective on glove-making in addition to the input from heritage partners. The slow fashion movement and awareness of artisan craft and how these can be preserved and adopted for glove and accessory design is addressed. Artisan leather glove making was a skilled and significant industry in England that has now declined to the point where there is little production remaining utilising the specialist skills that have hardly changed since earliest times. This heritage will be identified and preserved for future generations of the rich cultural history of gloves may be lost.

Keywords: Artisan glove making skills, English leather gloves, glove culture, glove network.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: Deep learning, long-short-term memory, energy, renewable energy load forecasting.

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Authors: S. K. Fasogbon, T. M. Oladosu, O. S. Osasuyi

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Plastic extrusion has been an important process of plastic production since 19^th century. Meanwhile, in plastic extrusion process, wide variation in temperature along the extrudate usually leads to scraps formation on the side of finished products. To avoid this situation, there is a need to deeply understand temperature distribution along the extrudate in plastic extrusion process. This work developed an analytical model that predicts the temperature distribution over the billet (the polymers melt) along the extrudate during extrusion process with the limitation that the polymer in question does not cover biopolymer such as DNA. The model was solved and simulated. Results for two different plastic materials (polyvinylchloride and polycarbonate) using self-developed MATLAB code and a commercially developed software (ANSYS) were generated and ultimately compared. It was observed that there is a thermodynamic heat transfer from the entry level of the billet into the die down to the end of it. The graph plots indicate a natural exponential decay of temperature with time and along the die length, with the temperature being 413 K and 474 K for polyvinylchloride and polycarbonate respectively at the entry level and 299.3 K and 328.8 K at the exit when the temperature of the surrounding was 298 K. The extrusion model was validated by comparison of MATLAB code simulation with a commercially available ANSYS simulation and the results favourably agree. This work concludes that the developed mathematical model and the self-generated MATLAB code are reliable tools in predicting temperature distribution along the extrudate in plastic extrusion process.

Keywords: ANSYS, extrusion process, MATLAB, plastic making, thermal analysis.

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Authors: Visuwan D., Phruksaphanrat B

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In this research, computer simulation is used for Electronic Manufacturing Service (EMS) plant layout analysis. The current layout of this manufacturing plant is a process layout, which is not suitable due to the nature of an EMS that has high-volume and high-variety environment. Moreover, quick response and high flexibility are also needed. Then, cellular manufacturing layout design was determined for the selected group of products. Systematic layout planning (SLP) was used to analyze and design the possible cellular layouts for the factory. The cellular layout was selected based on the main criteria of the plant. Computer simulation was used to analyze and compare the performance of the proposed cellular layout and the current layout. It found that the proposed cellular layout can generate better performances than the current layout. In this research, computer simulation is used for Electronic Manufacturing Service (EMS) plant layout analysis. The current layout of this manufacturing plant is a process layout, which is not suitable due to the nature of an EMS that has high-volume and high-variety environment. Moreover, quick response and high flexibility are also needed. Then, cellular manufacturing layout design was determined for the selected group of products. Systematic layout planning (SLP) was used to analyze and design the possible cellular layouts for the factory. The cellular layout was selected based on the main criteria of the plant. Computer simulation was used to analyze and compare the performance of the proposed cellular layout and the current layout. It found that the proposed cellular layout can generate better performances than the current layout. 

Keywords: Layout, Electronic Manufacturing Service Plant (EMS), Computer Simulation, Cellular Manufacturing System (CMS).

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Authors: Bernard Kumi-Boateng, Issaka Yakubu

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Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: Forest risk, GIS, remote sensing, Goaso.

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluates the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: lexical semantics, feature representation, semantic decision, convolutional neural network, electronic medical record

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