Search results for: sustainable urban water management.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5916

Search results for: sustainable urban water management.

276 School Emergency Drills Evaluation through E-PreS Monitoring System

Authors: A. Kourou, A. Ioakeimidou, V. Avramea

Abstract:

Planning for natural disasters and emergencies is something every school or educational institution must consider, regardless of its size or location. Preparedness is the key to save lives if a disaster strikes. School disaster management mirrors individual and family disaster prevention, and wider community disaster prevention efforts. This paper presents the usage of E-PreS System as a helpful, managerial tool during the school earthquake drill, in order to support schools in developing effective disaster and emergency plans specific to their local needs. The project comes up with a holistic methodology using real-time evaluation involving different categories of actors, districts, steps and metrics. The main outcomes of E-PreS project are the development of E-PreS web platform that host the needed data of school emergency planning; the development of E-PreS System; the implementation of disaster drills using E-PreS System in educational premises and local schools; and the evaluation of E-PreS System. Taking into consideration that every disaster drill aims to test and valid school plan and procedures; clarify and train personnel in roles and responsibilities; improve interagency coordination; identify gaps in resources; improve individual performance; and identify opportunities for improvement, E-PreS Project was submitted and approved by the European Commission (EC).

Keywords: Disaster drills, earthquake preparedness, E-PreS system, school emergency plans.

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275 An Analysis of Economic Capital Allocation of Global Banks

Authors: Petr Teply, Ondrej Vejdovec

Abstract:

There are three main ways of categorizing capital in banking operations: accounting, regulatory and economic capital. However, the 2008-2009 global crisis has shown that none of these categories adequately reflects the real risks of bank operations, especially in light of the failures Bear Stearns, Lehman Brothers or Northern Rock. This paper deals with the economic capital allocation of global banks. In theory, economic capital should reflect the real risks of a bank and should be publicly available. Yet, as discovered during the global financial crisis, even when economic capital information was publicly disclosed, the underlying assumptions rendered the information useless. Specifically, some global banks that reported relatively high levels of economic capital before the crisis went bankrupt or had to be bailed-out by their government. And, only 15 out of 50 global banks reported their economic capital during the 2007-2010 period. In this paper, we analyze the changes in reported bank economic capital disclosure during this period. We conclude that relative shares of credit and business risks increased in 2010 compared to 2007, while both operational and market risks decreased their shares on the total economic capital of top-rated global banks. Generally speaking, higher levels of disclosure and transparency of bank operations are required to obtain more confidence from stakeholders. Moreover, additional risks such as liquidity risks should be included in these disclosures.

Keywords: global crisis, economic capital, risk management, risk allocation, bank

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274 Prediction of Time to Crack Reinforced Concrete by Chloride Induced Corrosion

Authors: Anuruddha Jayasuriya, Thanakorn Pheeraphan

Abstract:

In this paper, a review of different mathematical models which can be used as prediction tools to assess the time to crack reinforced concrete (RC) due to corrosion is investigated. This investigation leads to an experimental study to validate a selected prediction model. Most of these mathematical models depend upon the mechanical behaviors, chemical behaviors, electrochemical behaviors or geometric aspects of the RC members during a corrosion process. The experimental program is designed to verify the accuracy of a well-selected mathematical model from a rigorous literature study. Fundamentally, the experimental program exemplifies both one-dimensional chloride diffusion using RC squared slab elements of 500 mm by 500 mm and two-dimensional chloride diffusion using RC squared column elements of 225 mm by 225 mm by 500 mm. Each set consists of three water-to-cement ratios (w/c); 0.4, 0.5, 0.6 and two cover depths; 25 mm and 50 mm. 12 mm bars are used for column elements and 16 mm bars are used for slab elements. All the samples are subjected to accelerated chloride corrosion in a chloride bath of 5% (w/w) sodium chloride (NaCl) solution. Based on a pre-screening of different models, it is clear that the well-selected mathematical model had included mechanical properties, chemical and electrochemical properties, nature of corrosion whether it is accelerated or natural, and the amount of porous area that rust products can accommodate before exerting expansive pressure on the surrounding concrete. The experimental results have shown that the selected model for both one-dimensional and two-dimensional chloride diffusion had ±20% and ±10% respective accuracies compared to the experimental output. The half-cell potential readings are also used to see the corrosion probability, and experimental results have shown that the mass loss is proportional to the negative half-cell potential readings that are obtained. Additionally, a statistical analysis is carried out in order to determine the most influential factor that affects the time to corrode the reinforcement in the concrete due to chloride diffusion. The factors considered for this analysis are w/c, bar diameter, and cover depth. The analysis is accomplished by using Minitab statistical software, and it showed that cover depth is the significant effect on the time to crack the concrete from chloride induced corrosion than other factors considered. Thus, the time predictions can be illustrated through the selected mathematical model as it covers a wide range of factors affecting the corrosion process, and it can be used to predetermine the durability concern of RC structures that are vulnerable to chloride exposure. And eventually, it is further concluded that cover thickness plays a vital role in durability in terms of chloride diffusion.

Keywords: Accelerated corrosion, chloride diffusion, corrosion cracks, passivation layer, reinforcement corrosion.

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273 Geochemical Study of Natural Bitumen, Condensate and Gas Seeps from Sousse Area, Central Tunisia

Authors: A. Belhaj Mohamed, M. Saidi, N. Boucherb, N. Ourtani, A. Soltani, I. Bouazizi, M. Ben Jrad

Abstract:

Natural hydrocarbon seepage has helped petroleum exploration as a direct indicator of gas and/or oil subsurface accumulations. Surface macro-seeps are generally an indication of a fault in an active Petroleum Seepage System belonging to a Total Petroleum System. This paper describes a case study in which multiple analytical techniques were used to identify and characterize trace petroleum-related hydrocarbons and other volatile organic compounds in groundwater samples collected from Sousse aquifer (Central Tunisia). The analytical techniques used for analyses of water samples included gas chromatography-mass spectrometry (GCMS), capillary GC with flame-ionization detection, Compound Specific Isotope Analysis, Rock Eval Pyrolysis. The objective of the study was to confirm the presence of gasoline and other petroleum products or other volatile organic pollutants in those samples in order to assess the respective implication of each of the potentially responsible parties to the contamination of the aquifer. In addition, the degree of contamination at different depths in the aquifer was also of interest. The oil and gas seeps have been investigated using biomarker and stable carbon isotope analyses to perform oil-oil and oil-source rock correlations. The seepage gases are characterized by high CH4 content, very low δ13CCH4 values (-71,9 ‰) and high C1/C1–5 ratios (0.95–1.0), light deuterium–hydrogen isotope ratios (- 198 ‰) and light δ13CC2 and δ13CCO2 values (-23,8‰ and-23,8‰ respectively) indicating a thermogenic origin with the contribution of the biogenic gas. An organic geochemistry study was carried out on the more ten oil seep samples. This study includes light hydrocarbon and biomarkers analyses (hopanes, steranes, n-alkanes, acyclic isoprenoids, and aromatic steroids) using GC and GC-MS. The studied samples show at least two distinct families, suggesting two different types of crude oil origins: the first oil seeps appears to be highly mature, showing evidence of chemical and/or biological degradation and was derived from a clay-rich source rock deposited in suboxic conditions. It has been sourced mainly by the lower Fahdene (Albian) source rocks. The second oil seeps was derived from a carbonate-rich source rock deposited in anoxic conditions, well correlated with the Bahloul (Cenomanian-Turonian) source rock.

Keywords: Biomarkers, oil and gas seeps, organic geochemistry, source rock.

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272 An Educational Data Mining System for Advising Higher Education Students

Authors: Heba Mohammed Nagy, Walid Mohamed Aly, Osama Fathy Hegazy

Abstract:

Educational  data mining  is  a  specific  data   mining field applied to data originating from educational environments, it relies on different  approaches to discover hidden knowledge  from  the  available   data. Among these approaches are   machine   learning techniques which are used to build a system that acquires learning from previous data. Machine learning can be applied to solve different regression, classification, clustering and optimization problems.

In  our  research, we propose  a “Student  Advisory  Framework” that  utilizes  classification  and  clustering  to  build  an  intelligent system. This system can be used to provide pieces of consultations to a first year  university  student to  pursue a  certain   education   track   where  he/she  will  likely  succeed  in, aiming  to  decrease   the  high  rate   of  academic  failure   among these  students.  A real case study  in Cairo  Higher  Institute  for Engineering, Computer  Science  and  Management  is  presented using  real  dataset   collected  from  2000−2012.The dataset has two main components: pre-higher education dataset and first year courses results dataset. Results have proved the efficiency of the suggested framework.

Keywords: Classification, Clustering, Educational Data Mining (EDM), Machine Learning.

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271 On Combining Support Vector Machines and Fuzzy K-Means in Vision-based Precision Agriculture

Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

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One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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270 An Efficient Biometric Cryptosystem using Autocorrelators

Authors: R. Bremananth, A. Chitra

Abstract:

Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person-s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes.

Keywords: Autocorrelators, biometrics cryptography, irispatterns, wavelets.

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269 The Impact of Character Strengths on Employee Well-Being: The Mediating Effect of Work-Family Relationship

Authors: Jing Wang, Yong Wang

Abstract:

For organizational development, employee well-being is critical and has been influenced deeply by character strengths. Therefore, investigating the relationship between character strengths and employee well-being and its inner mechanism is crucial. In this study, we explored the features of Chinese employees' character strengths, studied the relationship between character strengths and employees' subjective well-being, work well-being and psychological well-being respectively, and examined the mediating effect of work-family relationship (both enrichment and conflict). An online survey was conducted. The results showed that: (1) The top five character strengths of Chinese employees were gratitude, citizenship, kindness, appreciation of beauty and excellence, justice, while the bottom five ones were creativity, authenticity, bravery, spirituality, open-mindedness. (2) Subjective well-being was significantly correlated to courage, humanity, transcendence and justice. Work well-being was significantly correlated to wisdom, courage, humanity, justice and transcendence. Psychological well-being was significantly correlated to all the above five character strengths and temperance. (3) Wisdom and humanity influenced Chinese employees’ subjective well-being through work-family enrichment. Justice enhanced psychological well-being via work-family enrichment; meanwhile, it also played a positive role in subjective well-being, work well-being, and psychological well-being by decreasing the family-work conflict. At the end of this paper, some theoretical and practical contributions to organizational management were further discussed.

Keywords: Character strengths, work-family conflict, work-family enrichment, employee well-being, work well-being.

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268 Innovative Teaching in Systems Analysis and Design - an Action Research Project

Authors: Imelda Smit

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Systems Analysis and Design is a key subject in Information Technology courses, but students do not find it easy to cope with, since it is not “precise" like programming and not exact like Mathematics. It is a subject working with many concepts, modeling ideas into visual representations and then translating the pictures into a real life system. To complicate matters users who are not necessarily familiar with computers need to give their inputs to ensure that they get the system the need. Systems Analysis and Design also covers two fields, namely Analysis, focusing on the analysis of the existing system and Design, focusing on the design of the new system. To be able to test the analysis and design of a system, it is necessary to develop a system or at least a prototype of the system to test the validity of the analysis and design. The skills necessary in each aspect differs vastly. Project Management Skills, Database Knowledge and Object Oriented Principles are all necessary. In the context of a developing country where students enter tertiary education underprepared and the digital divide is alive and well, students need to be motivated to learn the necessary skills, get an opportunity to test it in a “live" but protected environment – within the framework of a university. The purpose of this article is to improve the learning experience in Systems Analysis and Design through reviewing the underlying teaching principles used, the teaching tools implemented, the observations made and the reflections that will influence future developments in Systems Analysis and Design. Action research principles allows the focus to be on a few problematic aspects during a particular semester.

Keywords: Action Research, Project Development, Systems Analysis and Design, Technology in Teaching.

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267 Traffic Forecasting for Open Radio Access Networks Virtualized Network Functions in 5G Networks

Authors: Khalid Ali, Manar Jammal

Abstract:

In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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266 Transformation of the Business Model in an Occupational Health Care Company Embedded in an Emerging Personal Data Ecosystem: A Case Study in Finland

Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

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Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: Ecosystem, business model, personal data, preventive healthcare.

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265 Influence of Instructors in Engaging Online Graduate Students in Active Learning in the United States

Authors: Ehi E. Aimiuwu

Abstract:

As of 2017, many online learning professionals, institutions, and journals are still wondering how instructors can keep student engaged in the online learning environment to facilitate active learning effectively. The purpose of this qualitative single-case and narrative research is to explore whether online professors understand their role as mentors and facilitators of students’ academic success by keeping students engaged in active learning based on personalized experience in the field. Data collection tools that were used in the study included an NVivo 12 Plus qualitative software, an interview protocol, a digital audiotape, an observation sheet, and a transcription. Seven online professors in the United States from LinkedIn and residencies were interviewed for this study. Eleven online teaching techniques from previous research were used as the study framework. Data analysis process, member checking, and key themes were used to achieve saturation. About 85.7% of professors agreed on rubric as the preferred online grading technique. About 57.1% agreed on professors logging in daily, students logging in about 2-5 times weekly, knowing students to increase accountability, email as preferred communication tool, and computer access for adequate online learning. About 42.9% agreed on syllabus for clear class expectations, participation to show what has been learned, and energizing students for creativity.

Keywords: Class facilitation, class management, online teaching, online education, pedagogy.

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264 Qualitative and Quantitative Characterization of Generated Waste in Nouri Petrochemical Complex, Assaluyeh, Iran

Authors: L. Heidari, M. Jalili Ghazizade

Abstract:

In recent years, different petrochemical complexes have been established to produce aromatic compounds. Among them, Nouri Petrochemical Complex (NPC) is the largest producer of aromatic raw materials in the world, and is located in south of Iran. Environmental concerns have been raised in this region due to generation of different types of solid waste generated in the process of aromatics production, and subsequently, industrial waste characterization has been thoroughly considered. The aim of this study is qualitative and quantitative characterization of industrial waste generated in the aromatics production process and determination of the best method for industrial waste management. For this purpose, all generated industrial waste during the production process was determined using a checklist. Four main industrial wastes were identified as follows: spent industrial soil, spent catalyst, spent molecular sieves and spent N-formyl morpholine (NFM) solvent. The amount of heavy metals and organic compounds in these wastes were further measured in order to identify the nature and toxicity of such a dangerous compound. Then industrial wastes were classified based on lab analysis results as well as using different international lists of hazardous waste identification such as EPA, UNEP and Basel Convention. Finally, the best method of waste disposal is selected based on environmental, economic and technical aspects. 

Keywords: Spent industrial soil, spent molecular sieve, spent normal ¬formyl -morpholine solvent.

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263 Influence of Seasons on Honeybee Wooden Hives Attack by Termites in Port Harcourt, Nigeria

Authors: A. A. Aiyeloja, G.A. Adedeji, S. L. Larinde

Abstract:

Termites have been observed as major pre-colonisation and post-colonisation pest insect of honeybees’ wooden hives in Nigeria. However, pest situation studies in modern beekeeping have been largely directed towards those pests that affect honeybees rather than the biological structure (wood) which houses the honeybees and the influence of seasons on the pests’ activities against the hives. This study, therefore, investigated the influence of seasons on the intensity of hives attacks by termites for 2 years in University of Port Harcourt, Rivers State using visual inspection. The Experimental Apiary was established with 15 Kenyan’s top bar hives made of Triplochiton scleroxylon wood that were strategically placed and observed within the Department of Forestry and Wildlife Management arboretum. The colonies hives consistently showed comparatively lower termite’s infestation levels in the dry season and, consequently, also lower attacks on the colonized hives. The result indicated raining season as a distinct period for more destructive activities of termites on the hives and strongly associated with dryness of the hives. Since previous study and observations have linked colonization with dry season coupled with minimal attacked on colonized hives; the non-colonised hives should be removed from the field at the onset of raining season and returned two weeks prior to dry season to reduce hives degradation by pests.

Keywords: Attack, hives degradation, Nigeria, seasons, termites.

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262 The Relevance of Data Warehousing and Data Mining in the Field of Evidence-based Medicine to Support Healthcare Decision Making

Authors: Nevena Stolba, A Min Tjoa

Abstract:

Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.

Keywords: data mining, data warehousing, decision-support systems, evidence-based medicine.

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261 A Multiple Linear Regression Model to Predict the Price of Cement in Nigeria

Authors: Kenneth M. Oba

Abstract:

This study investigated factors affecting the price of cement in Nigeria, and developed a mathematical model that can predict future cement prices. Cement is key in the Nigerian construction industry. The changes in price caused by certain factors could affect economic and infrastructural development; hence there is need for proper proactive planning. Secondary data were collected from published information on cement between 2014 and 2019. In addition, questionnaires were sent to some domestic cement retailers in Port Harcourt in Nigeria, to obtain the actual prices of cement between the same periods. The study revealed that the most critical factors affecting the price of cement in Nigeria are inflation rate, population growth rate, and Gross Domestic Product (GDP) growth rate. With the use of data from United Nations, International Monetary Fund, and Central Bank of Nigeria databases, amongst others, a Multiple Linear Regression model was formulated. The model was used to predict the price of cement for 2020-2025. The model was then tested with 95% confidence level, using a two-tailed t-test and an F-test, resulting in an R2 of 0.8428 and R2 (adj.) of 0.6069. The results of the tests and the correlation factors confirm the model to be fit and adequate. This study will equip researchers and stakeholders in the construction industry with information for planning, monitoring, and management of present and future construction projects that involve the use of cement.

Keywords: Cement price, multiple linear regression model, Nigerian Construction Industry, price prediction.

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260 The Automated Soil Erosion Monitoring System (ASEMS)

Authors: George N. Zaimes, Valasia Iakovoglou, Paschalis Koutalakis, Konstantinos Ioannou, Ioannis Kosmadakis, Panagiotis Tsardaklis, Theodoros Laopoulos

Abstract:

The advancements in technology allow the development of a new system that can continuously measure surface soil erosion. Continuous soil erosion measurements are required in order to comprehend the erosional processes and propose effective and efficient conservation measures to mitigate surface erosion. Mitigating soil erosion, especially in Mediterranean countries such as Greece, is essential in order to maintain environmental and agricultural sustainability. In this paper, we present the Automated Soil Erosion Monitoring System (ASEMS) that measures surface soil erosion along with other factors that impact erosional process. Specifically, this system measures ground level changes (surface soil erosion), rainfall, air temperature, soil temperature, and soil moisture. Another important innovation is that the data will be collected by remote communication. In addition, stakeholder’s awareness is a key factor to help reduce any environmental problem. The different dissemination activities that were utilized are described. The overall outcomes were the development of a new innovative system that can measure erosion very accurately. These data from the system help study the process of erosion and find the best possible methods to reduce erosion. The dissemination activities enhance the stakeholders and public's awareness on surface soil erosion problems and will lead to the adoption of more effective soil erosion conservation practices in Greece.

Keywords: Soil management, climate change, new technologies, conservation practices.

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259 Soil Organic Carbon Pool Assessment and Chemical Evaluation of Soils in Akure North and South Local Government Area of Ondo State

Authors: B. F. Dada, B. S. Ewulo, M. A. Awodun, S. O. Ajayi

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Aggregate soil carbon distribution and stock in the soil in the form of a carbon pool is important for soil fertility and sequestration. The amount of carbon pool and other nutrients statues of the soil are to benefit plants, animal and the environment in the long run. This study was carried out at Akure North and South Local Government; the study area is one of the 18 Local Government Areas of Ondo State in the Southwest geo-political zone of Nigeria. The sites were divided into Map Grids and geo-referenced with Global Positioning System (GPS). Horizons were designated and morphological description carried out on the field. Pedons were characterized and classified according to USDA soil taxonomy. The local government area shares boundaries with; Ikere Local Government (LG) in the North, Ise Orun LG in the northwest, Ifedore LG in the northeast Akure South LG in the East, Ose LG in the South East, and Owo LG in the South. SOC-pool at Federal College of Agriculture topsoil horizon A2 is significantly higher than all horizons, 67.83 th⁻¹. The chemical properties of the pedons have shown that the soil is very strongly acidic to neutral reaction (4.68 – 6.73). The nutrients status of the soil topsoil A1 and A2 generally indicates that the soils have a low potential for retaining plant nutrients, and therefore call for adequate soil management.

Keywords: Soil organic carbon, horizon, pedon, Akure.

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258 Artificial Intelligence: A Comprehensive and Systematic Literature Review of Applications and Comparative Technologies

Authors: Z. M. Najmi

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Over the years, the question around Artificial Intelligence has always been one with many answers. Whether by means of use in business and industry or complicated algorithmic programming, management of these technologies has always been the core focus. More recently, technologies have been questioned in industry and society alike as to whether they have improved human-centred design, assisted choices and objectives, and had a hand in systematic processes across the board. With these questions the answer may lie within AI technologies, and the steps needed in removing common human error. Elements such as Machine Learning, Deep Learning, Recommender Systems and Natural Language Processing will all be features to consider moving forward. Our previous intervention with AI applications has resulted in increased productivity, however, raised concerns for the continuation of traditional human-centred occupations. Emerging technologies such as Augmented Reality and Virtual Reality have all played a part in this during AI’s prominent rise. As mentioned, AI has been constantly under the microscope; the benefits and drawbacks may seem endless is wide, but AI is something we must take notice of and adapt into our everyday lives. The aim of this paper is to give an overview of the technologies surrounding A.I. and its’ related technologies. A comprehensive review has been written as a timeline of the developing events and key points in the history of Artificial Intelligence. This research is gathered entirely from secondary research, academic statements of knowledge and gathered to produce an understanding of the timeline of AI.

Keywords: Artificial Intelligence, Deep Learning, Augmented Reality, Reinforcement Learning, Machine Learning, Supervised Learning.

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257 Modelling Hydrological Time Series Using Wakeby Distribution

Authors: Ilaria Lucrezia Amerise

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The statistical modelling of precipitation data for a given portion of territory is fundamental for the monitoring of climatic conditions and for Hydrogeological Management Plans (HMP). This modelling is rendered particularly complex by the changes taking place in the frequency and intensity of precipitation, presumably to be attributed to the global climate change. This paper applies the Wakeby distribution (with 5 parameters) as a theoretical reference model. The number and the quality of the parameters indicate that this distribution may be the appropriate choice for the interpolations of the hydrological variables and, moreover, the Wakeby is particularly suitable for describing phenomena producing heavy tails. The proposed estimation methods for determining the value of the Wakeby parameters are the same as those used for density functions with heavy tails. The commonly used procedure is the classic method of moments weighed with probabilities (probability weighted moments, PWM) although this has often shown difficulty of convergence, or rather, convergence to a configuration of inappropriate parameters. In this paper, we analyze the problem of the likelihood estimation of a random variable expressed through its quantile function. The method of maximum likelihood, in this case, is more demanding than in the situations of more usual estimation. The reasons for this lie, in the sampling and asymptotic properties of the estimators of maximum likelihood which improve the estimates obtained with indications of their variability and, therefore, their accuracy and reliability. These features are highly appreciated in contexts where poor decisions, attributable to an inefficient or incomplete information base, can cause serious damages.

Keywords: Generalized extreme values (GEV), likelihood estimation, precipitation data, Wakeby distribution.

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256 Mathematical Study for Traffic Flow and Traffic Density in Kigali Roads

Authors: Kayijuka Idrissa

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This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: Statistical methods, Poisson distribution, car moving techniques, traffic flow.

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255 A Hybrid Neural Network and Traditional Approach for Forecasting Lumpy Demand

Authors: A. Nasiri Pour, B. Rostami Tabar, A.Rahimzadeh

Abstract:

Accurate demand forecasting is one of the most key issues in inventory management of spare parts. The problem of modeling future consumption becomes especially difficult for lumpy patterns, which characterized by intervals in which there is no demand and, periods with actual demand occurrences with large variation in demand levels. However, many of the forecasting methods may perform poorly when demand for an item is lumpy. In this study based on the characteristic of lumpy demand patterns of spare parts a hybrid forecasting approach has been developed, which use a multi-layered perceptron neural network and a traditional recursive method for forecasting future demands. In the described approach the multi-layered perceptron are adapted to forecast occurrences of non-zero demands, and then a conventional recursive method is used to estimate the quantity of non-zero demands. In order to evaluate the performance of the proposed approach, their forecasts were compared to those obtained by using Syntetos & Boylan approximation, recently employed multi-layered perceptron neural network, generalized regression neural network and elman recurrent neural network in this area. The models were applied to forecast future demand of spare parts of Arak Petrochemical Company in Iran, using 30 types of real data sets. The results indicate that the forecasts obtained by using our proposed mode are superior to those obtained by using other methods.

Keywords: Lumpy Demand, Neural Network, Forecasting, Hybrid Approach.

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254 Standalone Docking Station with Combined Charging Methods for Agricultural Mobile Robots

Authors: Leonor Varandas, Pedro D. Gaspar, Martim L. Aguiar

Abstract:

One of the biggest concerns in the field of agriculture is around the energy efficiency of robots that will perform agriculture’s activity and their charging methods. In this paper, two different charging methods for agricultural standalone docking stations are shown that will take into account various variants as field size and its irregularities, work’s nature to which the robot will perform, deadlines that have to be respected, among others. Its features also are dependent on the orchard, season, battery type and its technical specifications and cost. First charging base method focuses on wireless charging, presenting more benefits for small field. The second charging base method relies on battery replacement being more suitable for large fields, thus avoiding the robot stop for recharge. Existing many methods to charge a battery, the CC CV was considered the most appropriate for either simplicity or effectiveness. The choice of the battery for agricultural purposes is if most importance. While the most common battery used is Li-ion battery, this study also discusses the use of graphene-based new type of batteries with 45% over capacity to the Li-ion one. A Battery Management Systems (BMS) is applied for battery balancing. All these approaches combined showed to be a promising method to improve a lot of technical agricultural work, not just in terms of plantation and harvesting but also about every technique to prevent harmful events like plagues and weeds or even to reduce crop time and cost.

Keywords: Agricultural mobile robot, charging base methods, battery replacement method, wireless charging method.

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253 Web-Content Analysis of the Major Spanish Tourist Destinations Evaluation by Russian Tourists

Authors: Natalia Polkanova, Sergey Kazakov

Abstract:

In the second decade of the XXI century the role of tourism destination attractiveness is becoming increasingly important for destination management. Competition in tourism market moves from ordinary service quality to provision of unforgettable emotional experience for tourists. The main purpose of the present study is to identify the perception of the tourism destinations based on the number of factors related to its tourist attractiveness. The content analysis method was used to analyze the on-line tourist feedback data immensely available in Social Media and in travel related sites. The collected data made it possible to procure the information which is necessary to understand the perceived attractiveness of the destinations and key destination appeal factors that are important for Russian leisure travelers. Results of the present study demonstrate key attractiveness factors or destination ‘properties’ that were unveiled as the most important for Russian leisure tourists. The study targeted five main Spanish tourism destinations that initially were determined by in-depth interview with a number of Russian nationals who had visited Spain at least once. The research results can be useful for Spanish Tourism Organization Representation office in Russia as well as for the other national tourism organizations in order to promote their respective destinations for Russian travelers focusing on main attractiveness factors identified in this study.

Keywords: Tourism destination, destination attractiveness, destination competitiveness, content analysis, unstructured image.

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252 Nanostructured Pt/MnO2 Catalysts and Their Performance for Oxygen Reduction Reaction in Air Cathode Microbial Fuel Cell

Authors: Maksudur Rahman Khan, Kar Min Chan, Huei Ruey Ong, Chin Kui Cheng, Wasikur Rahman

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Microbial fuel cells (MFCs) represent a promising technology for simultaneous bioelectricity generation and wastewater treatment. Catalysts are significant portions of the cost of microbial fuel cell cathodes. Many materials have been tested as aqueous cathodes, but air-cathodes are needed to avoid energy demands for water aeration. The sluggish oxygen reduction reaction (ORR) rate at air cathode necessitates efficient electrocatalyst such as carbon supported platinum catalyst (Pt/C) which is very costly. Manganese oxide (MnO2) was a representative metal oxide which has been studied as a promising alternative electrocatalyst for ORR and has been tested in air-cathode MFCs. However the single MnO2 has poor electric conductivity and low stability. In the present work, the MnO2 catalyst has been modified by doping Pt nanoparticle. The goal of the work was to improve the performance of the MFC with minimum Pt loading. MnO2 and Pt nanoparticles were prepared by hydrothermal and sol gel methods, respectively. Wet impregnation method was used to synthesize Pt/MnO2 catalyst. The catalysts were further used as cathode catalysts in air-cathode cubic MFCs, in which anaerobic sludge was inoculated as biocatalysts and palm oil mill effluent (POME) was used as the substrate in the anode chamber. The asprepared Pt/MnO2 was characterized comprehensively through field emission scanning electron microscope (FESEM), X-Ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and cyclic voltammetry (CV) where its surface morphology, crystallinity, oxidation state and electrochemical activity were examined, respectively. XPS revealed Mn (IV) oxidation state and Pt (0) nanoparticle metal, indicating the presence of MnO2 and Pt. Morphology of Pt/MnO2 observed from FESEM shows that the doping of Pt did not cause change in needle-like shape of MnO2 which provides large contacting surface area. The electrochemical active area of the Pt/MnO2 catalysts has been increased from 276 to 617 m2/g with the increase in Pt loading from 0.2 to 0.8 wt%. The CV results in O2 saturated neutral Na2SO4 solution showed that MnO2 and Pt/MnO2 catalysts could catalyze ORR with different catalytic activities. MFC with Pt/MnO2 (0.4 wt% Pt) as air cathode catalyst generates a maximum power density of 165 mW/m3, which is higher than that of MFC with MnO2 catalyst (95 mW/m3). The open circuit voltage (OCV) of the MFC operated with MnO2 cathode gradually decreased during 14 days of operation, whereas the MFC with Pt/MnO2 cathode remained almost constant throughout the operation suggesting the higher stability of the Pt/MnO2 catalyst. Therefore, Pt/MnO2 with 0.4 wt% Pt successfully demonstrated as an efficient and low cost electrocatalyst for ORR in air cathode MFC with higher electrochemical activity, stability and hence enhanced performance.

Keywords: Microbial fuel cell, oxygen reduction reaction, Pt/MnO2, palm oil mill effluent, polarization curve.

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251 Design and Development of iLON Smart Server Based Remote Monitoring System for Induction Motors

Authors: G. S. Ayyappan, M. Raja Raghavan, R. Poonthalir, Kota Srinivas, B. Ramesh Babu

Abstract:

Electrical energy demand in the World and particularly in India, is increasing drastically more than its production over a period of time. In order to reduce the demand-supply gap, conserving energy becomes mandatory. Induction motors are the main driving force in the industries and contributes to about half of the total plant energy consumption. By effective monitoring and control of induction motors, huge electricity can be saved. This paper deals about the design and development of such a system, which employs iLON Smart Server and motor performance monitoring nodes. These nodes will monitor the performance of induction motors on-line, on-site and in-situ in the industries. The node monitors the performance of motors by simply measuring the electrical power input and motor shaft speed; coupled to genetic algorithm to estimate motor efficiency. The nodes are connected to the iLON Server through RS485 network. The web server collects the motor performance data from nodes, displays online, logs periodically, analyzes, alerts, and generates reports. The system could be effectively used to operate the motor around its Best Operating Point (BOP) as well as to perform the Life Cycle Assessment of Induction motors used in the industries in continuous operation.

Keywords: Best operating point, iLON smart server, motor asset management, LONWORKS, Modbus RTU, motor performance.

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250 A Dynamic Mechanical Thermal T-Peel Test Approach to Characterize Interfacial Behavior of Polymeric Textile Composites

Authors: J. R. Büttler, T. Pham

Abstract:

Basic understanding of interfacial mechanisms is of importance for the development of polymer composites. For this purpose, we need techniques to analyze the quality of interphases, their chemical and physical interactions and their strength and fracture resistance. In order to investigate the interfacial phenomena in detail, advanced characterization techniques are favorable. Dynamic mechanical thermal analysis (DMTA) using a rheological system is a sensitive tool. T-peel tests were performed with this system, to investigate the temperature-dependent peel behavior of woven textile composites. A model system was made of polyamide (PA) woven fabric laminated with films of polypropylene (PP) or PP modified by grafting with maleic anhydride (PP-g-MAH). Firstly, control measurements were performed with solely PP matrixes. Polymer melt investigations, as well as the extensional stress, extensional viscosity and extensional relaxation modulus at -10°C, 100 °C and 170 °C, demonstrate similar viscoelastic behavior for films made of PP-g-MAH and its non-modified PP-control. Frequency sweeps have shown that PP-g-MAH has a zero phase viscosity of around 1600 Pa·s and PP-control has a similar zero phase viscosity of 1345 Pa·s. Also, the gelation points are similar at 2.42*104 Pa (118 rad/s) and 2.81*104 Pa (161 rad/s) for PP-control and PP-g-MAH, respectively. Secondly, the textile composite was analyzed. The extensional stress of PA66 fabric laminated with either PP-control or PP-g-MAH at -10 °C, 25 °C and 170 °C for strain rates of 0.001 – 1 s-1 was investigated. The laminates containing the modified PP need more stress for T-peeling. However, the strengthening effect due to the modification decreases by increasing temperature and at 170 °C, just above the melting temperature of the matrix, the difference disappears. Independent of the matrix used in the textile composite, there is a decrease of extensional stress by increasing temperature. It appears that the more viscous is the matrix, the weaker the laminar adhesion. Possibly, the measurement is influenced by the fact that the laminate becomes stiffer at lower temperatures. Adhesive lap-shear testing at room temperature supports the findings obtained with the T-peel test. Additional analysis of the textile composite at the microscopic level ensures that the fibers are well embedded in the matrix. Atomic force microscopy (AFM) imaging of a cross section of the composite shows no gaps between the fibers and matrix. Measurements of the water contact angle show that the MAH grafted PP is more polar than the virgin-PP, and that suggests a more favorable chemical interaction of PP-g-MAH with PA, compared to the non-modified PP. In fact, this study indicates that T-peel testing by DMTA is a technique to achieve more insights into polymeric textile composites.

Keywords: Dynamic mechanical thermal analysis, interphase, polyamide, polypropylene, textile composite, T-peel test.

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249 Energy Harvesting and Storage System for Marine Applications

Authors: Sayem Zafar, Mahmood Rahi

Abstract:

Rigorous international maritime regulations are in place to limit boat and ship hydrocarbon emissions. The global sustainability goals are reducing the fuel consumption and minimizing the emissions from the ships and boats. These maritime sustainability goals have attracted a lot of research interest. Energy harvesting and storage system is designed in this study based on hybrid renewable and conventional energy systems. This energy harvesting and storage system is designed for marine applications, such as, boats and small ships. These systems can be utilized for mobile use or off-grid remote electrification. This study analyzed the use of micro power generation for boats and small ships. The energy harvesting and storage system has two distinct systems i.e. dockside shore-based system and on-board system. The shore-based system consists of a small wind turbine, photovoltaic (PV) panels, small gas turbine, hydrogen generator and high-pressure hydrogen storage tank. This dockside system is to provide easy access to the boats and small ships for supply of hydrogen. The on-board system consists of hydrogen storage tanks and fuel cells. The wind turbine and PV panels generate electricity to operate electrolyzer. A small gas turbine is used as a supplementary power system to contribute in case the hybrid renewable energy system does not provide the required energy. The electrolyzer performs the electrolysis on distilled water to produce hydrogen. The hydrogen is stored in high-pressure tanks. The hydrogen from the high-pressure tank is filled in the low-pressure tanks on-board seagoing vessels to operate the fuel cell. The boats and small ships use the hydrogen fuel cell to provide power to electric propulsion motors and for on-board auxiliary use. For shore-based system, a small wind turbine with the total length of 4.5 m and the disk diameter of 1.8 m is used. The small wind turbine dimensions make it big enough to be used to charge batteries yet small enough to be installed on the rooftops of dockside facility. The small dimensions also make the wind turbine easily transportable. In this paper, PV, sizing and solar flux are studied parametrically. System performance is evaluated under different operating and environmental conditions. The parametric study is conducted to evaluate the energy output and storage capacity of energy storage system. Results are generated for a wide range of conditions to analyze the usability of hybrid energy harvesting and storage system. This energy harvesting method significantly improves the usability and output of the renewable energy sources. It also shows that small hybrid energy systems have promising practical applications.

Keywords: Energy harvesting, fuel cell, hybrid energy system, hydrogen, wind turbine.

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248 Use of Locomotor Activity of Rainbow Trout Juveniles in Identifying Sublethal Concentrations of Landfill Leachate

Authors: Tomas Makaras, Gintaras Svecevičius

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Landfill waste is a common problem as it has an economic and environmental impact even if it is closed. Landfill waste contains a high density of various persistent compounds such as heavy metals, organic and inorganic materials. As persistent compounds are slowly-degradable or even non-degradable in the environment, they often produce sublethal or even lethal effects on aquatic organisms. The aims of the present study were to estimate sublethal effects of the Kairiai landfill (WGS: 55°55‘46.74“, 23°23‘28.4“) leachate on the locomotor activity of rainbow trout Oncorhynchus mykiss juveniles using the original system package developed in our laboratory for automated monitoring, recording and analysis of aquatic organisms’ activity, and to determine patterns of fish behavioral response to sublethal effects of leachate. Four different concentrations of leachate were chosen: 0.125; 0.25; 0.5 and 1.0 mL/L (0.0025; 0.005; 0.01 and 0.002 as part of 96-hour LC50, respectively). Locomotor activity was measured after 5, 10 and 30 minutes of exposure during 1-minute test-periods of each fish (7 fish per treatment). The threshold-effect-concentration amounted to 0.18 mL/L (0.0036 parts of 96-hour LC50). This concentration was found to be even 2.8-fold lower than the concentration generally assumed to be “safe” for fish. At higher concentrations, the landfill leachate solution elicited behavioral response of test fish to sublethal levels of pollutants. The ability of the rainbow trout to detect and avoid contaminants occurred after 5 minutes of exposure. The intensity of locomotor activity reached a peak within 10 minutes, evidently decreasing after 30 minutes. This could be explained by the physiological and biochemical adaptation of fish to altered environmental conditions. It has been established that the locomotor activity of juvenile trout depends on leachate concentration and exposure duration. Modeling of these parameters showed that the activity of juveniles increased at higher leachate concentrations, but slightly decreased with the increasing exposure duration. Experiment results confirm that the behavior of rainbow trout juveniles is a sensitive and rapid biomarker that can be used in combination with the system for fish behavior monitoring, registration and analysis to determine sublethal concentrations of pollutants in ambient water. Further research should be focused on software improvement aimed to include more parameters of aquatic organisms’ behavior and to investigate the most rapid and appropriate behavioral responses in different species. In practice, this study could be the basis for the development and creation of biological early-warning systems (BEWS).

Keywords: Fish behavior biomarker, landfill leachate, locomotor activity, rainbow trout juveniles, sublethal effects.

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247 Analysis of Key Factors for Formation of Strategic Alliances in Liner Shipping Company: Service Quality Perspective on Asia/Europe Route after Global Economic Crisis

Authors: Sheng Teng Huang, Shigeru Yoshida

Abstract:

Strategic alliances generally mean the cooperation or collaboration between firms which pursue for a synergy that each member hopes the benefits from the alliances would be much more than those from individual efforts. Past researches provide us sufficient theories and considerations for alliance forming in liner shipping market. This research reviews important academic journals for the past decade regarding to the most important reasons to form the alliances. We would explain the motive of alliances and details of shipping cooperation in literature review. The paper also empirically investigates the key service quality requirements improved through alliances by using quality function deployment (QFD). Moreover, the research investigates famous shipping reports, shipping consultant websites and most recent shipping publications to find out the executive-s viewpoint of several leading carriers among top 20 to assess current shipping strategic alliance on Asia/Europe route. These comments provide meaningful managerial reasons to consider alliance formations and search if there is any gap between the theories and industrial practice. Analysis of the empirical investigation and top management-s perspective on current market situation will contribute us some meaningful managerial suggestions to evaluate these theories applied to current strategic alliances.

Keywords: Liner shipping, Strategic alliances, quality function deployment, service quality.

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