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Authors: A. A. Ghanim

Abstract:

The Kingdom of Saudi Arabia (KSA) is heading towards a severe and rapidly expanding water crisis, which can have negative impacts on the country’s environment and economy. Of the total water consumption in KSA, the agricultural sector accounts for nearly 87% of the total water use and, therefore, any attempt that overlooks this sector will not help in improving the sustainability of the country’s water resources. KSA Vision 2030 gives priority of water use in the agriculture sector for the regions that have natural renewable water resources. It means that there is little concern for making reuse of municipal wastewater for irrigation purposes in any region in general and in water-scarce regions in particular. The use of treated wastewater is very limited in Saudi Arabia, but it has very considerable potential for future expansion due its numerous beneficial uses. This study reviews the current situation of water resources in Saudi Arabia, providing more highlights on agriculture and wastewater reuse. The reviewed study is proposing some corrective measures for development and better management of water resources in the Kingdom. Suggestions also include consideration of treated water as an alternative source for irrigation in some regions of the country. The study concluded that a sustainable solution for the water crisis in KSA requires implementation of multiple measures in an integrated manner. The integrated solution plan should focus on two main directions: first, improving the current management practices of the existing water resources; second, developing new water supplies from both conventional and non-conventional sources.

Keywords: Saudi Arabia, water resources, water crisis, treated wastewater.

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Authors: P. Aragonés-Beltrán, F. Chaparro-González, J. P. Pastor Ferrando, M. García-Melón

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In this paper the Analytic Network Process (ANP) is applied to the selection of photovoltaic (PV) solar power projects. These projects follow a long management and execution process from plant site selection to plant start-up. As a consequence, there are many risks of time delays and even of project stoppage. In the case study presented in this paper a top manager of an important Spanish company that operates in the power market has to decide on the best PV project (from four alternative projects) to invest based on risk minimization. The manager identified 50 project execution delay and/or stoppage risks. The influences among elements of the network (groups of risks and alternatives) were identified and analyzed using the ANP multicriteria decision analysis method. After analyzing the results the main conclusion is that the network model can manage all the information of the real-world problem and thus it is a decision analysis model recommended by the authors. The strengths and weaknesses ANP as a multicriteria decision analysis tool are also described in the paper.

Keywords: Multicriteria decision analysis, Analytic Network Process, Photovoltaic solar power projects.

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Authors: D. Abdelrazek, M. NaguibAly, A. A. Badawi, Asmaa G. Abo Elnour, A. A. El-Kafas

Abstract:

This work is developed within IAEA Coordinated Research Program 1496, “Innovative methods in research reactor analysis: Benchmark against experimental data on neutronics and thermal-hydraulic computational methods and tools for operation and safety analysis of research reactors”.

The study investigates the capability of Code RELAP5/Mod3.4 to solve complex geometry complexity. Its results are compared to the results of PARET, a common code in thermal hydraulic analysis for research reactors, belonging to MTR-PC groups.

The WWR-SM reactor at the Institute of Nuclear Physics (INP) in the Republic of Uzbekistan is simulated using both PARET and RELAP5 at steady state. Results from the two codes are compared.

REALP5 code succeeded in solving the complex fuel geometry. The PARET code needed some calculations to obtain the final result. Although the final results from the PARET are more accurate, the small differences in both results makes using RELAP5 code recommended in case of complex fuel assemblies. 

Keywords: Complex fuel geometry, PARET, RELAP5, WWR-SM reactor.

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Authors: Gopalu Karunakaran, Matheswaran Jagathambal, Nguyen Van Minh, Evgeny Kolesnikov, Denis Kuznetsov

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This work investigated the use of Beijerinckia indica extracellular extract for the synthesis of silver nanoparticles using AgNO₃. The formation of nanoparticles was confirmed by different methods, such as UV-Vis absorption spectroscopy, XRD, FTIR, EDX, and TEM analysis. The formation of silver nanoparticles (AgNPs) was confirmed by the change in color from light yellow to dark brown. The absorbance peak obtained at 430 nm confirmed the presence of silver nanoparticles. The XRD analysis showed the cubic crystalline phase of the synthesized nanoparticles. FTIR revealed the presence of groups that acts as stabilizing and reducing agents for silver nanoparticles formation. The synthesized silver nanoparticles were generally found to be spherical in shape with size ranging from 5 to 20 nm, as evident by TEM analysis. These nanoparticles were found to inhibit pathogenic bacterial strains. This work proved that the bacterial extract is a potential eco-friendly candidate for the synthesis of silver nanoparticles with promising antibacterial and antioxidant properties. 

Keywords: Antioxidant activity, antimicrobial activity, Beijerinckia indica, characterisation, extracellular extracts, silver nanoparticles.

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Authors: Abdallah S. Abdallah, A. Lynn Abbott, Mohamad Abou El-Nasr

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This paper presents a new technique for detection of human faces within color images. The approach relies on image segmentation based on skin color, features extracted from the two-dimensional discrete cosine transform (DCT), and self-organizing maps (SOM). After candidate skin regions are extracted, feature vectors are constructed using DCT coefficients computed from those regions. A supervised SOM training session is used to cluster feature vectors into groups, and to assign “face" or “non-face" labels to those clusters. Evaluation was performed using a new image database of 286 images, containing 1027 faces. After training, our detection technique achieved a detection rate of 77.94% during subsequent tests, with a false positive rate of 5.14%. To our knowledge, the proposed technique is the first to combine DCT-based feature extraction with a SOM for detecting human faces within color images. It is also one of a few attempts to combine a feature-invariant approach, such as color-based skin segmentation, together with appearance-based face detection. The main advantage of the new technique is its low computational requirements, in terms of both processing speed and memory utilization.

Keywords: Face detection, skin color segmentation, self-organizingmap.

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Authors: Alexander Y. Vaninsky

Abstract:

This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.

Keywords: Data Envelopment Analysis, Perfect object, Partially perfect object, Partial efficiency, Explicit solution, Simplified algorithm.

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Authors: Abu Salim Mustafa

Abstract:

The comparisons of mycobacterial genomes have identified several Mycobacterium tuberculosis-specific genomic regions that are absent in other mycobacteria and are known as regions of differences. Due to M. tuberculosis-specificity, the peptides encoded by these regions could be useful in the specific diagnosis of tuberculosis. To explore this possibility, overlapping synthetic peptides corresponding to 39 proteins predicted to be encoded by genes present in regions of differences were tested for antibody-reactivity with sera from tuberculosis patients and healthy subjects. The results identified four immunodominant peptides corresponding to four different proteins, with three of the peptides showing significantly stronger antibody reactivity and rate of positivity with sera from tuberculosis patients than healthy subjects. The fourth peptide was recognized equally well by the sera of tuberculosis patients as well as healthy subjects. Predication of antibody epitopes by bioinformatics analyses using ABCpred server predicted multiple linear epitopes in each peptide. Furthermore, peptide sequence analysis for sequence identity using BLAST suggested M. tuberculosis-specificity for the three peptides that had preferential reactivity with sera from tuberculosis patients, but the peptide with equal reactivity with sera of TB patients and healthy subjects showed significant identity with sequences present in nob-tuberculous mycobacteria. The three identified M. tuberculosis-specific immunodominant peptides may be useful in the serological diagnosis of tuberculosis.

Keywords: Genomic regions of differences, Mycobacterium tuberculosis, peptides, serodiagnosis.

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

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

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

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Authors: Toby Gibbs, Suwaree Yordchim

Abstract:

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

Keywords: Litecoin, Mining, Confirmations.

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Authors: Petr Seďa

Abstract:

This paper deals with heterogeneous autoregressive models of realized volatility (HAR-RV models) on high-frequency data of stock indices in the USA. Its aim is to capture the behavior of three groups of market participants trading on a daily, weekly and monthly basis and assess their role in predicting the daily realized volatility. The benefits of this work lies mainly in the application of heterogeneous autoregressive models of realized volatility on stock indices in the USA with a special aim to analyze an impact of the global financial crisis on applied models forecasting performance. We use three data sets, the first one from the period before the global financial crisis occurred in the years 2006-2007, the second one from the period when the global financial crisis fully hit the U.S. financial market in 2008-2009 years, and the last period was defined over 2010-2011 years. The model output indicates that estimated realized volatility in the market is very much determined by daily traders and in some cases excludes the impact of those market participants who trade on monthly basis.

Keywords: Global financial crisis, heterogeneous autoregressive model, in-sample forecast, realized volatility, U.S. stock market.

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Authors: Abdullah M. Algarni, Yashwant K. Malaiya

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Some of the key aspects of vulnerability—discovery, dissemination, and disclosure—have received some attention recently. However, the role of interaction among the vulnerability discoverers and vulnerability acquirers has not yet been adequately addressed. Our study suggests that a major percentage of discoverers, a majority in some cases, are unaffiliated with the software developers and thus are free to disseminate the vulnerabilities they discover in any way they like. As a result, multiple vulnerability markets have emerged. In some of these markets, the exchange is regulated, but in others, there is little or no regulation. In recent vulnerability discovery literature, the vulnerability discoverers have remained anonymous individuals. Although there has been an attempt to model the level of their efforts, information regarding their identities, modes of operation, and what they are doing with the discovered vulnerabilities has not been explored.

Reports of buying and selling of the vulnerabilities are now appearing in the press; however, the existence of such markets requires validation, and the natures of the markets need to be analyzed. To address this need, we have attempted to collect detailed information. We have identified the most prolific vulnerability discoverers throughout the past decade and examined their motivation and methods. A large percentage of these discoverers are located in Eastern and Western Europe and in the Far East. We have contacted several of them in order to collect firsthand information regarding their techniques, motivations, and involvement in the vulnerability markets. We examine why many of the discoverers appear to retire after a highly successful vulnerability-finding career. The paper identifies the actual vulnerability markets, rather than the hypothetical ideal markets that are often examined. The emergence of worldwide government agencies as vulnerability buyers has significant implications. We discuss potential factors that can impact the risk to society and the need for detailed exploration.

Keywords: Risk management, software security, vulnerability discoverers, vulnerability markets.

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Authors: R. Chanajaree, D. Luanwiset, K. Pongpratea

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Dye removal is an environmental concern because the textile industries have been increasing by world population and industrialization. Adsorption is the technique to find adsorbents to remove dyes from wastewater. This method is low-cost and effective for dye removal. This work tries to develop effective adsorbents using the computational approach because it will be able to predict the possibility of the adsorbents for specific dyes in terms of binding free energies. The computational approach is faster and cheaper than the experimental approach in case of finding the best adsorbents. All starting structures of dyes and adsorbents are optimized by quantum calculation. The complexes between dyes and adsorbents are generated by the docking method. The obtained binding free energies from docking are compared to binding free energies from the experimental data. The calculated energies can be ranked as same as the experimental results. In addition, this work also shows the possible orientation of the complexes. This work used two experimental groups of the complexes of the dyes and adsorbents. In the first group, there are chitosan (adsorbent) and two dyes (reactive red (RR) and direct sun yellow (DY)). In the second group, there are poly(1,2-epoxy-3-phenoxy) propane (PEPP), which is the adsorbent, and 2 dyes of bromocresol green (BCG) and alizarin yellow (AY).

Keywords: Dye removal, binding free energies, quantum calculation, docking.

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Authors: Anomi Bearden, Brooke Goodyear, Alicia Khan

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This repeated-measures experiment explored the effects of six weeks of gratitude practice on college students (N = 67) on relationship satisfaction and perceived superiority. Replicating previous research on gratitude practice, it was hypothesized that after consistent gratitude practice, participants in the experimental group (n = 32) would feel increased levels of relationship satisfaction compared to the control group (n = 35). Of particular interest was whether the level of perceived superiority would moderate the effect of gratitude practice on relationship satisfaction. The gratitude group evidenced significantly higher appreciation and marginally higher relationship satisfaction at post-test than the control group (both groups being equal at pre-test). Significant enhancements in gratitude, satisfaction, and feeling both appreciative and appreciated were found in the gratitude group, as well as significant enhancements in gratitude, satisfaction, and feeling appreciated in the control group. Appreciation for one’s partner was the only measure that improved in the gratitude group and not the control group from pre-test to post-test. Perceived superiority did not change significantly from pre-test to post-test in either group, supporting the prevalence and stability of this bias within people’s overall perceptions of their relationships.

Keywords: Gratitude, relationship satisfaction, perceived superiority, partner appreciation.

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Authors: Ting Wang, Huiqin Yang, Buxin Han

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Background: This investigated the mental health of the elderly survivors six months, ten months and two years after the “5.12 Wenchuan" earthquake. Methods: Two hundred and thirty-two physically healthy older survivors from earthquake-affected Mianyang County were interviewed. The measures included the Revised Impact of Event Scale (IES-R, Chinese version, for PTSD) and a Chinese Mental Health Inventory for the Elderly (MHIE). A repeated measures ANOVA test was used for statistical analysis. Results: The follow-up group had a statistically significant lower IES-R score and lower MHIE score than the initial group ten months after the earthquake. Two years later, the score of IES-R in follow-up group were still lower than that of non-follow-up group, but no differences were significant on the score of MHIE between groups. Furthermore, a negative relationship was found between scores of IES-R and MHIE. Conclusion: The earthquake has had a persistent negative impact on older survivors- mental health within the two-year period and that although the PTSD level declined significantly with time, it did not disappear completely.

Keywords: Elderly survivors, follow-up, mental health, post-Wenchuan earthquake.

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Authors: I. Nur Hilwani, R. Nasibah, S. Nurdiana, M. J. Norashirene

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Impaired fertility may be the result of indirect consumption of anti-fertility agents through food. Monosodium glutamate (MSG) has been widely used as food additive, flavour enhancer and included in vaccines. This study focuses in determining the gonadotoxic and cytotoxic effect of MSG on selected sperm parameters such as sperm viability, sperm membrane integrity and testes cytoarchitecture of male mice via histological examination to determine its effect on spermatogenesis. Twenty-four Mus musculus were randomly divided into 4 groups and given intraperitoneal injections (IP) daily for 14 days of different MSG concentrations at 250, 500 and 1000mg/kg MSG to body weight to induce obesity. Saline was given to control group. Mice were sacrificed and analysis revealed abnormalities in values for sperm parameters and damages to testes cytoarchitecture of male mice. The results recorded decreased viability (p<0.05) and integrity of sperm membrane (p>0.05) with degenerative structures in seminiferous tubule of testes. The results indicated various implications of MSG on male mice reproductive system which has consequences in fertility potential.

Keywords: Sperm parameter, sperm viability, sperm membrane integrity and testes histology.

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Authors: Mohamed Haffar, Lombe Ngome Enongene, Mohammed Hamdan, Gbolahan Gbadamosi

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Despite the considerable body of literature investigating the influence of National Culture (NC) dimensions on consumer behaviour, there is a lack of studies comparing the influence of NC in Africa with Western European countries. This study is intended to fill the vacuum in knowledge by exploring how NC affects consumer buyer behavior in Nigeria and the United Kingdom. The primary data were collected through in depth, semi-structured interviews conducted with three groups of individuals: British students, Nigerian students in the United Kingdom, and Nigerian-based students. This approach and new frontier to analyze culture and consumer behaviour could help understand residual cultural threads of people (that are ingrained in their being) irrespective of exposure to other cultures. The findings of this study show that Nigerian and British consumers differ remarkably in cultural orientations such as symbols, values and psychological standpoints. This ultimately affects the choices made at every stage of the decision building process, and proves beneficial for international retail marketing.

Keywords: National culture, consumer behaviour, international business, Nigeria, UK.

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Authors: Young-Hyun Seo, Hyunwoo Park, Dong-Kyu Kim, Seung-Young Kho

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The purpose of this study is providing an improved mode choice model considering parameters including age grouping of prime-aged and old age. In this study, 2010 Household Travel Survey data were used and improper samples were removed through the analysis. Chosen alternative, date of birth, mode, origin code, destination code, departure time, and arrival time are considered from Household Travel Survey. By preprocessing data, travel time, travel cost, mode, and ratio of people aged 45 to 55 years, 55 to 65 years and over 65 years were calculated. After the manipulation, the mode choice model was constructed using LIMDEP by maximum likelihood estimation. A significance test was conducted for nine parameters, three age groups for three modes. Then the test was conducted again for the mode choice model with significant parameters, travel cost variable and travel time variable. As a result of the model estimation, as the age increases, the preference for the car decreases and the preference for the bus increases. This study is meaningful in that the individual and households characteristics are applied to the aggregate model.

Keywords: Age grouping, aging, mode choice model, multinomial logit model.

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Authors: Emad Alenany, M. Adel El-Baz

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In this paper, the flow of different classes of patients into a hospital is modelled and analyzed by using the queueing network analyzer (QNA) algorithm and discrete event simulation. Input data for QNA are the rate and variability parameters of the arrival and service times in addition to the number of servers in each facility. Patient flows mostly match real flow for a hospital in Egypt. Based on the analysis of the waiting times, two approaches are suggested for improving performance: Separating patients into service groups, and adopting different service policies for sequencing patients through hospital units. The separation of a specific group of patients, with higher performance target, to be served separately from the rest of patients requiring lower performance target, requires the same capacity while improves performance for the selected group of patients with higher target. Besides, it is shown that adopting the shortest processing time and shortest remaining processing time service policies among other tested policies would results in, respectively, 11.47% and 13.75% reduction in average waiting time relative to first come first served policy.

Keywords: Queueing network, discrete-event simulation, health applications, SPT.

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: Consensus, curse of correlation, imbalanced classification, rank-based chain-mode ensemble.

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Authors: Carmen Grigoraş, Victor Grigoraş, Daniela Boişteanu

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The standard investigational method for obstructive sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG), which consists of a simultaneous, usually overnight recording of multiple electro-physiological signals related to sleep and wakefulness. This is an expensive, encumbering and not a readily repeated protocol, and therefore there is need for simpler and easily implemented screening and detection techniques. Identification of apnea/hypopnea events in the screening recordings is the key factor for the diagnosis of OSAS. The analysis of a solely single-lead electrocardiographic (ECG) signal for OSAS diagnosis, which may be done with portable devices, at patient-s home, is the challenge of the last years. A novel artificial neural network (ANN) based approach for feature extraction and automatic identification of respiratory events in ECG signals is presented in this paper. A nonlinear principal component analysis (NLPCA) method was considered for feature extraction and support vector machine for classification/recognition. An alternative representation of the respiratory events by means of Kohonen type neural network is discussed. Our prospective study was based on OSAS patients of the Clinical Hospital of Pneumology from Iaşi, Romania, males and females, as well as on non-OSAS investigated human subjects. Our computed analysis includes a learning phase based on cross signal PSG annotation.

Keywords: Artificial neural networks, feature extraction, obstructive sleep apnea syndrome, pattern recognition, signalprocessing.

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Authors: Siyu Wang, Anthony Ward

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Emotional intelligence (EI) is a well-established personal characteristic. It has been viewed as a critical factor which can influence an individual's academic achievement, ability to work and potential to succeed. When working in a group, EI is fundamentally connected to the group members' interaction and ability to work as a team. The ability of a group member to intelligently perceive and understand own emotions (Intrapersonal EI), to intelligently perceive and understand other members' emotions (Interpersonal EI), and to intelligently perceive and understand emotions between different groups (Cross-boundary EI) can be considered as Group emotional intelligence (Group EI). In this research, a more representative Group EI measurement approach, which incorporates the information of the composition of a group and an individual’s role in that group, is proposed. To demonstrate the claim of being more representative Group EI measurement approach, this study adopts a multi-method research design, involving a combination of both qualitative and quantitative techniques to establish a metric of Group EI. From the results, it can be concluded that by introducing the weight coefficient of each group member on group work into the measurement of Group EI, Group EI will be more representative and more capable of understanding what happens during teamwork than previous approaches.

Keywords: Emotional intelligence, EI, Group EI, multi-method research, teamwork.

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Authors: B. Mohebi, N. Asadi, F. Kazemi

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Inelastic deformation of the brace in Special Concentrically Braced Frame (SCBF) creates inelastic damages on gusset plate connections such as buckling at edges. In this study, to improve the seismic performance of SCBFs connections, an analytical study was undertaken. To improve the gusset plate connection, this study proposes using ‎edge’s stiffeners in both sides of gusset plate.‎ For this purpose, in order to examine edge’s stiffeners effect on gusset plate connections, two groups of modeling with and without considering edge’s stiffener and different types of braces were modeled using ABAQUS software. The results show that considering the edge’s stiffener reduces the equivalent plastic strain values at a connection region of gusset plate with beam and column, which can improve the seismic performance of gusset plate. Furthermore, considering the edge’s stiffeners significantly decreases the strain concentration at regions where gusset plates have been connected to beam and column. Moreover, considering 2t_pl distance causes reduction in the plastic strain.

Keywords: Special concentrically braced frame, gusset plate, edge’s stiffener, seismic performance.

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Authors: Toby Gibbs, Suwaree Yordchim

Abstract:

This research analyzes factors affecting the success of Bitcoin Value within Thailand and develops a guideline for self-reliance for effective business implementation. Samples in this study included 121 people through surveys. The results revealed four main factors affecting the success as follows: 1) A great majority didn't know what Bitcoin was. 2) Didn't grasp the concept of a digital currency or see the benefit of a digital currency. 3) There is a great need to educate the next generation of learners on the benefits of Bitcoin within the community. 4) Future Career training should be pursued in applied Bitcoin development.

The guideline for self-reliance planning consisted of 4 aspects: 1) Local communities need to develop awareness of the usefulness of Bitcoin and share the value of Bitcoin among friends and family. 2) Computer Science and Business Management staff should develop skills to expand on the benefits of Bitcoin within their departments. 3) Further research should be pursued on how Bitcoin Value can improve business and tourism within Thailand. Local communities should focus on developing Bitcoin awareness by encouraging street vendors to accept Bitcoin as another form of payment for services rendered. 4) Development planning: by arranging meet up groups to conduct further education on Bitcoin and share solutions on adoption into every day usage.

Keywords: Bitcoin, Cryptocurrency, Decentralized.

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Authors: Farzana Sharmin, Mohammad Tipu Sultan, Benqian Li

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Advancement of new media technology and consumption of social media have altered the way of communication in the tourism industry, mostly for consumers’ travel planning, online purchase, and experience sharing activity. There is an accelerating trend among young consumers’ to utilize this new media technology. This paper aims to analyze the attitude of young consumers’ about social media use for travel purposes. The convenience random sample method used to collect data from an urban area of Shanghai (China), consists of 225 young consumers’. This survey identified behavioral determinants of social media consumption by the extended theory of planned behavior (TPB). The instrument developed support on previous research to test hypotheses. The results of structural analyses indicate that attitude towards the use of social media is affected by external factors such as availability and accessibility of technology. In addition, subjective norm and perceived behavioral control have partially influenced the attitude of respondents’. The results of this study could help to improve social media travel marketing and promotional strategies for respective groups.

Keywords: Social media, theory of planned behavior, travel behavior, young consumer.

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

Abstract:

Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: Diabetes, glucose level, linear, near-infrared (NIR), non-invasive, prediction system.

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Authors: Nurcihan Hacioglu, Cigdem Gul, Murat Tosunoglu

Abstract:

In this article, the antibiogram and heavy metal resistance profile of the bacteria isolated from total 34 studied animals (Pelophylax ridibundus = 12; Mauremys rivulata = 14; Natrix natrix = 8) captured around the Biga Stream, are described. There was no database information on antibiogram and heavy metal resistance profile of bacteria from these area’s amphibians and reptiles. A total of 200 bacteria were successfully isolated from cloaca and oral samples of the aquatic amphibians and reptiles as well as from the water sample. According to Jaccard’s similarity index, the degree of similarity in the bacterial flora was quite high among the amphibian and reptile species under examination, whereas it was different from the bacterial diversity in the water sample. The most frequent isolates were A. hydrophila (31.5%), B. pseudomallei (8.5%), and C. freundii (7%). The total numbers of bacteria obtained were as follows: 45 in P. ridibundus, 45 in N. natrix 30 in M. rivulata, and 80 in the water sample. The result showed that cefmetazole was the most effective antibiotic to control the bacteria isolated in this study and that approximately 93.33% of the bacterial isolates were sensitive to this antibiotic. The multiple antibiotic resistances (MAR) index indicated that P. ridibundus (0.95) > N. natrix (0.89) > M. rivulata (0.39). Furthermore, all the tested heavy metals (Pb+2, Cu+2, Cr+3, and Mn+2) inhibit the growth of the bacterial isolates at different rates. Therefore, it indicated that the water source of the animals was contaminated with both antibiotic residues and heavy metals.

Keywords: Amphibian, Bacteriological Quality, Reptile, Antibiotic & Heavy Metal Resistance.

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Authors: Giovanni Luca Masala

Abstract:

Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Keywords: Computer Aided Detection, mammary tumor, pattern recognition, dissimilarity

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Authors: Seksan Chunothaisawat, Pongchanun Luangpaiboon

Abstract:

There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.

Keywords: Ant colony optimisation, metaheuristics, modified simplex, non-linear, rigid simplex.

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Authors: Lae-Jeong Park

Abstract:

The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: Pedestrian detection, color segmentation, false positives, feature extraction.

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