Search results for: cloud radio access network

Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Abdul Rehman, Bo Liu

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Axial flow turbines are commonly designed with high loads that generate strong secondary flows and result in high secondary losses. These losses contribute to almost 30% to 50% of the total losses. Non-axisymmetric endwall profiling is one of the passive control technique to reduce the secondary flow loss. In this paper, the non-axisymmetric endwall profile construction and optimization for the stator endwalls are presented to improve the efficiency of a high pressure turbine. The commercial code NUMECA Fine/ Design3D coupled with Fine/Turbo was used for the numerical investigation, design of experiments and the optimization. All the flow simulations were conducted by using steady RANS and Spalart-Allmaras as a turbulence model. The non-axisymmetric endwalls of stator hub and shroud were created by using the perturbation law based on Bezier Curves. Each cut having multiple control points was supposed to be created along the virtual streamlines in the blade channel. For the design of experiments, each sample was arbitrarily generated based on values automatically chosen for the control points defined during parameterization. The Optimization was achieved by using two algorithms i.e. the stochastic algorithm and gradient-based algorithm. For the stochastic algorithm, a genetic algorithm based on the artificial neural network was used as an optimization method in order to achieve the global optimum. The evaluation of the successive design iterations was performed using artificial neural network prior to the flow solver. For the second case, the conjugate gradient algorithm with a three dimensional CFD flow solver was used to systematically vary a free-form parameterization of the endwall. This method is efficient and less time to consume as it requires derivative information of the objective function. The objective function was to maximize the isentropic efficiency of the turbine by keeping the mass flow rate as constant. The performance was quantified by using a multi-objective function. Other than these two classifications of the optimization methods, there were four optimizations cases i.e. the hub only, the shroud only, and the combination of hub and shroud. For the fourth case, the shroud endwall was optimized by using the optimized hub endwall geometry. The hub optimization resulted in an increase in the efficiency due to more homogenous inlet conditions for the rotor. The adverse pressure gradient was reduced but the total pressure loss in the vicinity of the hub was increased. The shroud optimization resulted in an increase in efficiency, total pressure loss and entropy were reduced. The combination of hub and shroud did not show overwhelming results which were achieved for the individual cases of the hub and the shroud. This may be caused by fact that there were too many control variables. The fourth case of optimization showed the best result because optimized hub was used as an initial geometry to optimize the shroud. The efficiency was increased more than the individual cases of optimization with a mass flow rate equal to the baseline design of the turbine. The results of artificial neural network and conjugate gradient method were compared.

Keywords: artificial neural network, axial turbine, conjugate gradient method, non-axisymmetric endwall, optimization

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Authors: Olga Kokoulina

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Today, algorithms are assuming a leading role in various areas of decision-making. Prompted by a promise to provide increased economic efficiency and fuel solutions for pressing societal challenges, algorithmic decision-making is often celebrated as an impartial and constructive substitute for human adjudication. But in the face of this implied objectivity and efficiency, the application of algorithms is also marred with mounting concerns about embedded biases, discrimination, and exclusion. In Europe, vigorous debates on risks and adverse implications of algorithmic decision-making largely revolve around the potential of data protection laws to tackle some of the related issues. For example, one of the often-cited venues to mitigate the impact of potentially unfair decision-making practice is a so-called 'right to explanation'. In essence, the overall right is derived from the provisions of the General Data Protection Regulation (‘GDPR’) ensuring the right of data subjects to access and mandating the obligation of data controllers to provide the relevant information about the existence of automated decision-making and meaningful information about the logic involved. Taking corresponding rights and obligations in the context of the specific provision on automated decision-making in the GDPR, the debates mainly focus on efficacy and the exact scope of the 'right to explanation'. In essence, the underlying logic of the argued remedy lies in a transparency imperative. Allowing data subjects to acquire as much knowledge as possible about the decision-making process means empowering individuals to take control of their data and take action. In other words, forewarned is forearmed. The related discussions and debates are ongoing, comprehensive, and, often, heated. However, they are also frequently misguided and isolated: embracing the data protection law as ultimate and sole lenses are often not sufficient. Mandating the disclosure of technical specifications of employed algorithms in the name of transparency for and empowerment of data subjects potentially encroach on the interests and rights of IPR holders, i.e., business entities behind the algorithms. The study aims at pushing the boundaries of the transparency debate beyond the data protection regime. By systematically analysing legal requirements and current judicial practice, it assesses the limits of the transparency requirement and right to access posed by intellectual property law, namely by copyrights and trade secrets. It is asserted that trade secrets, in particular, present an often-insurmountable obstacle for realising the potential of the transparency requirement. In reaching that conclusion, the study explores the limits of protection afforded by the European Trade Secrets Directive and contrasts them with the scope of respective rights and obligations related to data access and portability enshrined in the GDPR. As shown, the far-reaching scope of the protection under trade secrecy is evidenced both through the assessment of its subject matter as well as through the exceptions from such protection. As a way forward, the study scrutinises several possible legislative solutions, such as flexible interpretation of the public interest exception in trade secrets as well as the introduction of the strict liability regime in case of non-transparent decision-making.

Keywords: algorithms, public interest, trade secrets, transparency

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

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Authors: Nafiseh Noormohammadi, Ahmad Sobhani Najafabadi

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Hypericins (hypericin and pseudohypericin) are natural napthodianthrone derivatives produced by Hypericum perforatum (St. John’s Wort), which have many medicinal properties such as antitumor, antineoplastic, antiviral, and antidepressant activities. Production and accumulation of hypericin in the plant are influenced by both genetic and environmental conditions. Despite the existence of different high-throughput data on the plant, genetic dimensions of hypericin biosynthesis have not yet been completely understood. In this research, 21 high-quality RNA-seq data on different parts of the plant were integrated into metabolic data to reconstruct a coexpression network. Results showed that a cluster of 30 transcripts was correlated with total hypericin. The identified transcripts were divided into three main groups based on their functions, including hypericin biosynthesis genes, transporters, detoxification genes, and transcription factors (TFs). In the biosynthetic group, different isoforms of polyketide synthase (PKSs) and phenolic oxidative coupling proteins (POCPs) were identified. Phylogenetic analysis of protein sequences integrated into gene expression analysis showed that some of the POCPs seem to be very important in the biosynthetic pathway of hypericin. In the TFs group, six TFs were correlated with total hypericin. qPCR analysis of these six TFs confirmed that three of them were highly correlated. The identified genes in this research are a rich resource for further studies on the molecular breeding of H. perforatum in order to obtain varieties with high hypericin production.

Keywords: hypericin, St. John’s Wort, data mining, transcription factors, secondary metabolites

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Authors: Huazhen Lin, Ruihua Xu, Zhibin Jiang

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In this real-world case, timetabling the LRT network as a whole is rather challenging for the operator: they are supposed to create a timetable to avoid various route conflicts manually while satisfying a given interval and the number of rolling stocks, but the outcome is not satisfying. Therefore, the operator adopts a computerised timetabling tool, the Train Plan Maker (TPM), to cope with this problem. However, with various constraints in the dual-line network, it is still difficult to find an adequate pairing of turnback time, interval and rolling stocks’ number, which requires extra manual intervention. Aiming at current problems, a one-off model for timetabling is presented in this paper to simplify the procedure of timetabling. Before the timetabling procedure starts, this paper presents how the dual-line system with a ring and several branches is turned into a simpler structure. Then, a non-linear programming model is presented in two stages. In the first stage, the model sets a series of constraints aiming to calculate a proper timing for coordinating two lines by adjusting the turnback time at termini. Then, based on the result of the first stage, the model introduces a series of inequality constraints to avoid various route conflicts. With this model, an analysis is conducted to reveal the relation between the ratio of trains in different directions and the possible minimum interval, observing that the more imbalance the ratio is, the less possible to provide frequent service under such strict constraints.

Keywords: light rail transit (LRT), non-linear programming, railway timetabling, timetable coordination

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Authors: Rodolfo Alfonso, David Alonso, Albin Garcia, Jose Luis Alonso

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Recently a new kilovoltage radiotherapy unit model Xstrahl 200 - donated to the INOR´s Department of Radiotherapy (DR-INOR) in the framework of a IAEA's technical cooperation project- has been commissioned. This unit is able to treat shallow and low deep laying lesions, as it provides 8 discrete beam qualities, from 40 to 200 kV. As part of the patient-specific quality assurance program established at DR-INOR for external beam radiotherapy, it has been recommended to implement in vivo dose measurements (IVD), as they allow effectively discovering eventual errors or failures in the radiotherapy process. For that purpose a radio-photoluminescence (RPL) dosimetry system, model XXX, -also donated to DR-INOR by the same IAEA project- has been studied and commissioned. Main dosimetric parameters of the RPL system, such as reproducibility, linearity, and filed size influence were assessed. In a similar way, the response of radiochromic EBT3 type film was investigated for purposes of IVD. Both systems were calibrated in terms of entrance surface dose. Results of the dosimetric commissioning of RPL and EBT3 for IVD, and their pre-clinical implementation through end-to-end test cases are presented. The RPL dosimetry seems more recommendable for hyper-fractionated schemes with larger fields and curved patient contours, as those in chest wall irradiations, where the use of more than one dosimeter could be required. The radiochromic system involves smaller corrections with field size, but it sensibility is lower; hence it is more adequate for hypo-fractionated treatments with smaller fields.

Keywords: glass dosimetry, in vivo dosimetry, kilovotage radiotherapy, radiochromic dosimetry

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Authors: Adel. M. Sharaf, Foad H. Gandoman

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Nowadays, Photovoltaic-PV Farms/ Parks and large PV-Smart Grid Interface Schemes are emerging and commonly utilized in Renewable Energy distributed generation. However, PV-hybrid-Dc-Ac Schemes using interface power electronic converters usually has negative impact on power quality and stabilization of modern electrical network under load excursions and network fault conditions in smart grid. Consequently, robust FACTS based interface schemes are required to ensure efficient energy utilization and stabilization of bus voltages as well as limiting switching/fault onrush current condition. FACTS devices are also used in smart grid-Battery Interface and Storage Schemes with PV-Battery Storage hybrid systems as an elegant alternative to renewable energy utilization with backup battery storage for electric utility energy and demand side management to provide needed energy and power capacity under heavy load conditions. The paper presents a robust interface PV-Li-Ion Battery Storage Interface Scheme for Distribution/Utilization Low Voltage Interface using FACTS stabilization enhancement and dynamic maximum PV power tracking controllers. Digital simulation and validation of the proposed scheme is done using MATLAB/Simulink software environment for Low Voltage- Distribution/Utilization system feeding a hybrid Linear-Motorized inrush and nonlinear type loads from a DC-AC Interface VSC-6-pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion Storage Battery.

Keywords: AC FACTS, smart grid, stabilization, PV-battery storage, Switched Filter-Compensation (SFC)

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Authors: Marcella De Filippo, Delio Colangelo, Luca Farnia

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In recent decades, the hyper-competition of tourism scenario has implicated the maturity of many businesses, attributing a central role to innovative processes and their dissemination in the economy of company management. At the same time, it has defined the need for monitoring the application of innovations, in order to govern and improve the performance of companies and destinations. The study aims to analyze and define the innovation in the tourism sector. The research actions have concerned, on the one hand, some in-depth interviews with experts, identifying innovation in terms of process and product, digitalization, sustainability policies and, on the other hand, to evaluate the interaction between these factors, in terms of substitutability and complementarity in management scenarios, in order to identify which one is essential to be competitive in the global scenario. Fuzzy measures and Choquet integral were used to elicit Experts’ preferences. This method allows not only to evaluate the relative importance of each pillar, but also and more interestingly, the level of interaction, ranging from complementarity to substitutability, between pairs of factors. The results of the survey are the following: in terms of Shapley values, Experts assert that Innovation is the most important factor (32.32), followed by digitalization (31.86), Network (20.57) and Sustainability (15.25). In terms of Interaction indices, given the low degree of consensus among experts, the interaction between couples of criteria on average could be ignored; however, it is worth to note that the factors innovations and digitalization are those in which experts express the highest degree of interaction. However for some of them, these factors have a moderate level of complementarity (with a pick of 57.14), and others consider them moderately substitutes (with a pick of -39.58). Another example, although outlier is the interaction between network and digitalization, in which an expert consider them markedly substitutes (-77.08).

Keywords: innovation, business model, tourism, fuzzy

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Authors: Tim Steinhaus, Christian Beidl

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Urban air quality and climate protection are two major challenges for future mobility systems. Despite the steady reduction of pollutant emissions from vehicles over past decades, local immission load within cities partially still reaches heights, which are considered hazardous to human health. Although traffic-related emissions account for a major part of the overall urban pollution, modeling the exact interaction remains challenging. In this paper, a novel approach for the determination of the emission-immission interaction on the basis of neural network modeling for traffic induced NO2-immission load within a near-traffic hot-spot scenario is presented. In a detailed sensitivity analysis, the significance of relevant influencing variables on the prevailing NO2 concentration is initially analyzed. Based on this, the generation process of the model is described, in which not only environmental influences but also the vehicle fleet composition including its associated segment- and certification-specific real driving emission factors are derived and used as input quantities. The validity of this approach, which has been presented in the past, is re-examined in this paper using updated data on vehicle emissions and recent immission measurement data. Within the framework of a final scenario analysis, the future development of the immission load is forecast for different developments in the vehicle fleet composition. It is shown that immission levels of less than half of today’s yearly average limit values are technically feasible in hot-spot situations.

Keywords: air quality, emission, emission-immission-interaction, immission, NO2, zero impact

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Authors: Sa'ad Ali

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This study explores wasta as an example of a social network and how it impacts business practice in the Arab Middle East, drawing links with social network impact in different regions of the world. In doing so, particular attention will be paid to the socio-economic and cultural influences on business practice. In exploring relationships in business, concepts such as social network analysis, social capital and group identity are used to explore the different forms of social networks and how they influence business decisions and practices in the regions and countries where they prevail. The use of social networks to achieve objectives is known as guanxi in China, wasta in the Arab Middle East and blat in ex-Soviet countries. Wasta can be defined as favouritism based on tribal and family affiliation and is a widespread practice that has a substantial impact on political, social and business interactions in the Arab Middle East. Within the business context, it is used in several ways, such as to secure a job or promotion or to cut through bureaucracy in government interactions. The little research available is fragmented, and most studies reveal a negative attitude towards its usage in business. Paradoxically, while wasta is widely practised, people from the Arab Middle East often deny its influence. Moreover, despite the regular exhibition of a negative opinion on the practice of wasta, it can also be a source of great pride. This paper addresses this paradox by conducting a positional literature review, exploring the current literature on wasta and identifying how the identified paradox can be explained. The findings highlight how wasta, to a large extent, has been treated as an umbrella concept, whilst it is a highly complex practice which has evolved from intermediary wasta to intercessory wasta and therefore from bonding social capital relationships to more bridging social capital relationships. In addition, the research found that Islam, as the predominant religion in the region and the main source of ethical guidance for the majority of people from the region, plays a substantial role in this paradox. Specifically, it is submitted that wasta can be viewed positively in Islam when it is practised to aid others without breaking Islamic ethical guidelines, whilst it can be viewed negatively when it is used in contradiction with the teachings of Islam. As such, the unique contribution to knowledge of this study is that it ties together the fragmented literature on wasta, highlighting and helping us understand its complexity. In addition, it sheds light on the role of Islam in wasta practices, aiding our understanding of the paradoxical nature of the practice.

Keywords: Islamic ethics, social capital, social networks, Wasta

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Authors: Ni'mal Baroya, Andrei Ramani, Irma Prasetyowati

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The access to reproduction health services, including with safe and effective contraception were human rights regardless of social stratum and residence. In addition to individual factors, family and contextual factors were also believed to be the cause in the use of contraceptive methods. This study aimed to assess the determinants of long-term contraceptive methods (LTCM) by considering all the factors at either the individual level or contextual level. Thereby, this study could provide basic information for program development of prevalence enhancement of MKJP in East Java. The research, which used cross-sectional design, utilized Riskesdas 2013 data, particularly in East Java Province for further analysis about multilevel modeling of MKJP application. The sample of this study consisted of 20.601 married women who were not in pregnant that were drawn by using probability sampling following the sampling technique of Riskesdas 2013. Variables in this study were including the independent variables at the individual level that consisted of education, age, occupation, access to family planning services (KB), economic status and residence. As independent variables in district level were the Human Development Index (HDI, henceforth as IPM) in each districts of East Java Province, the ratio of field officers, the ratio of midwives, the ratio of community health centers and the ratio of doctors. As for the dependent variable was the use of Long-Term Contraceptive Method (LTCM or MKJP). The data were analyzed by using chi-square test and Pearson product moment correlation. The multivariable analysis was using multilevel logistic regression with 95% of Confidence Interval (CI) at the significance level of p < 0.05 and 80% of strength test. The results showed a low CPR LTCM was concentrated in districts in Madura Island and the north coast. The women which were 25 to 35 or more than 35 years old, at least high school education, working, and middle-class social status were more likely to use LTCM or MKJP. The IPM and low PLKB ratio had implications for poor CPR LTCM / MKJP.

Keywords: multilevel, long-term contraceptive methods, east java, contextual factor

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Authors: T. Botelho de Sousa, F. Raphael Cabral Furtado, O. Eduardo da Silva Ferri, A. Batista, W. Augusto Varella, C. Eduardo Pinto, J. Mimar Santa Cruz Yabarrena, S. Gibran Ruwer, F. Müller Guerrini, L. Adalberto Philippsen Júnior

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Lean Supply Chain Management (LSCM) is an emerging research field in Operations Management (OM). As a strategic model that focuses on reduced cost and waste with fulfilling the needs of customers, LSCM attracts great interest among researchers and practitioners. The purpose of this paper is to present an overview of Lean Supply Chains literature, based on bibliometric analysis through 57 papers published in indexed journals by SCOPUS and/or Web of Science databases. The results indicate that the last three years (2015, 2016, and 2017) were the most productive on LSCM discussion, especially in Supply Chain Management and International Journal of Lean Six Sigma journals. India, USA, and UK are the most productive countries; nevertheless, cross-country studies by collaboration among researchers were detected, by social network analysis, as a research practice, appearing to play a more important role on LSCM studies. Despite existing limitation, such as limited indexed journal database, bibliometric analysis helps to enlighten ongoing efforts on LSCM researches, including most used technical procedures and collaboration network, showing important research gaps, especially, for development countries researchers.

Keywords: Lean Supply Chains, Bibliometric Study, SCOPUS, Web of Science

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Authors: Bissonnette Jean-François, Dossa Fabrice

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The project focuses on analyzing the spatial and temporal evolution of mangrove forest ecosystems near the city of Douala, Cameroon, in response to increasing human and environmental pressures. The selected study area, located in the Wouri River estuary, has a unique combination of economic importance, and ecological prominence. The study included valuable insights by conducting semi-structured interviews with resource operators and local officials. The thorough analysis of socio-economic data, farmer surveys, and satellite-derived information was carried out utilizing quantitative approaches in Excel and SPSS. Simultaneously, qualitative data was subjected to rigorous classification and correlation with other sources. The use of ArcGIS and CorelDraw facilitated the visual representation of the gradual changes seen in various land cover classifications. The research reveals complex processes that characterize mangrove ecosystems on Manoka and Cape Cameroon Islands. The lack of regulations in urbanization and the continuous growth of infrastructure have led to a significant increase in land conversion, causing negative impacts on natural landscapes and forests. The repeated instances of flooding and coastal erosion have further shaped landscape alterations, fostering the proliferation of water and mudflat areas. The unregulated use of mangrove resources is a significant factor in the degradation of these ecosystems. Activities including the use of wood for smoking and fishing, together with the coastal pollution resulting from the absence of waste collection, have had a significant influence. In addition, forest operators contribute to the degradation of vegetation, hence exacerbating the harmful impact of invasive species on the ecosystem. Strategic interventions are necessary to guarantee the sustainable management of these ecosystems. The proposals include advocating for sustainable wood exploitation techniques, using appropriate techniques, along with regeneration, and enforcing rules to prevent wood overexploitation. By implementing these measures, the ecological balance can be preserved, safeguarding the long-term viability of these precious ecosystems. On a conceptual level, this paper uses the framework developed by Elinor Ostrom and her colleagues to investigate the consequences of open access resources, where local actors have not been able to enforce measures to prevent overexploitation of mangrove wood resources. Governmental authorities have demonstrated limited capacity to enforce sustainable management of wood resources and have not been able to establish effective relationships with local fishing communities and with communities involved in the purchase of wood. As a result, wood resources in the mangrove areas remain largely accessible, while authorities do not monitor wood volumes extracted nor methods of exploitation. There have only been limited and punctual attempts at forest restoration with no significant consequence on mangrove forests dynamics.

Keywords: Mangroves, forest management, governance, open access resources, Cameroon

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

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

Keywords: BPSD, reminiscence, tactile telecommunication, utterances

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Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: Bahram Khan, Anderson Rocha Ramos, Rui R. Paulo, Fernando J. Velez

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With the growing demand for a new blend of applications, the users dependency on the internet is increasing day by day. Mobile internet users are giving more attention to their own experiences, especially in terms of communication reliability, high data rates and service stability on move. This increase in the demand is causing saturation of existing radio frequency bands. To address these challenges, researchers are investigating the best approaches, Carrier Aggregation (CA) is one of the newest innovations, which seems to fulfill the demands of the future spectrum, also CA is one the most important feature for Long Term Evolution - Advanced (LTE-Advanced). For this purpose to get the upcoming International Mobile Telecommunication Advanced (IMT-Advanced) mobile requirements (1 Gb/s peak data rate), the CA scheme is presented by 3GPP, which would sustain a high data rate using widespread frequency bandwidth up to 100 MHz. Technical issues such as aggregation structure, its implementations, deployment scenarios, control signal techniques, and challenges for CA technique in LTE-Advanced, with consideration of backward compatibility, are highlighted in this paper. Also, performance evaluation in macro-cellular scenarios through a simulation approach is presented, which shows the benefits of applying CA, low-complexity multi-band schedulers in service quality, system capacity enhancement and concluded that enhanced multi-band scheduler is less complex than the general multi-band scheduler, which performs better for a cell radius longer than 1800 m (and a PLR threshold of 2%).

Keywords: component carrier, carrier aggregation, LTE-advanced, scheduling

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Authors: Sang Ho Lee, Yountaik Leem

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This paper reviews Korean cases of smart cities through the analysis framework of strategic foci, characteristics and effects. Firstly, national strategies including c(cyber), e(electronic), u(ubiquitous) and s(smart) Korea strategies were considered from strategic angles. Secondly, the characteristics of smart cities in Korea were looked through the smart cities examples such as Seoul, Busan, Songdo and Sejong cities etc. from the views on the by STIM (Service, Technology, Infrastructure and Management) analysis. Finally, the effects of smart cities on socio-economies were investigated from industrial perspective using the input-output model and structural path analysis. Korean smart city strategies revealed that there were different kinds of strategic foci. c-Korea strategy focused on information and communications network building and user IT literacy. e-Korea strategy encouraged e-government and e-business through utilizing high-speed information and communications network. u-Korea strategy made ubiquitous service as well as integrated information and communication operations center. s-Korea strategy is propelling 4th industrial platform. Smart cities in Korea showed their own features and trends such as eco-intelligence, high efficiency and low cost oriented IoT, citizen sensored city, big data city. Smart city progress made new production chains fostering ICTs (Information Communication Technologies) and knowledge intermediate inputs to industries.

Keywords: Korean smart cities, Korean smart city strategies, STIM, smart service, infrastructure, technologies, management, effect of smart city

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: T. R. Sreekrishnan, Mukesh Khare, Dinesh Upadhyay

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In a Rotating Biological Contactor (RBC), the biological film responsible for removal of pollutants is formed on the surface of discs. Evaluation studies of a pilot RBC designed to treat sewage of 150 persons with BOD Loading Rate: 8.2–26.7 g/m2/d, Discharge: 57.6 – 115.2 m3/day, HRT 1.25 – 2.5 hrs, at STP Yamuna Vihar Delhi. Removal of organic materials through use of fixed film reactors such as RBC is accomplished by means of a biological film on the fixed media. May and June in Delhi are dry summer months where the ambient temperature is in the range of 35oC to 45oC. July is a wet monsoon month that receives occasional precipitation, cloud cover, high humidity, with ambient temperature in the range of 30oC to 35oC. The organic and inorganic loads to the RBC employed in this study are actual city sewage conditions. Average in fluent BOD concentrations have been 330 mg/l, 245 mg/l and 160 mg/l and the average COD concentrations have been 670 mg/l, 500 mg/l, and 275 mg/l. The city sewage also has high concentration of ammonia, phosphorous, total suspended solids (TSS). pH of the city sewage is near neutral. Overall, the substrate conditions of city sewage are conducive for biological treatment though aerobic process. The presentation is a part of the ongoing collaborative research initiative between IIT Delhi and Karlsruhe Institute of Technology, Germany which is going on for last 15 years or so in the treatment of sewage waste of Delhi using semi-decentralized treatment system based on Rotating Biological Contactor.

Keywords: Rotating Biological Contactor (RBC), COD, BOD, HRT, STP

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Authors: Surarong Chinwong, Namthip Intarakumhang Na Rachasima, Siyaporn Kuikhiew, Dujrudee Chinwong

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Irrational use of medicines is a major problem in public health. Half of all patients take medicines incorrectly. An inappropriate use of antibiotics is one of the common types of irrational medicine use; for example, patients use antibiotic for treatment of common cold or diarrhea. Objectives: This cross-sectional study aimed to investigate the behaviors on antibiotic use, using amoxicillin and norfloxacin as examples, as well as sources of received health information. Methods: An online self-administered questionnaire was used to collect data from participants in Thailand between September and December 2015. Participants were asked about their behaviors on antibiotic use. Data were analyzed using descriptive statistics. Results: Of all 405 participants, most were female (65.3 %), aged 18-30 years (49.4 %), undergraduate or lower (69.7%), and civil servant or state enterprises (31.7 %). We found inappropriate behaviors in use of amoxicillin or norfloxacin: 1) there were 201/400 participants (50.3%) taking amoxicillin right away in case of having a common cold, such as having sore throat, running nose, and cough; 2) there were 170/405 participants (42.0%) using amoxicillin for relieving inflammatory symptoms, e.g. muscle inflammation or osteoarthritis; 3) there were 71/398 participants (17.8%) using amoxicillin as a muscle relaxant; 4) there were 135/398 participants (33.9%) using norfloxacin for treating diarrhea. Sources of health information received by the participants were from the internet (78.5%), the radio and/or television (42.2%), advertising publishing (33.3 %), and word of mouth (30.1%). Conclusion: This study showed improper behaviors in antibiotic use especially amoxicillin and norfloxacin. Health care providers including pharmacists should raise the public awareness on dangers of inappropriate antibiotic use and promote the rational use of antibiotics.

Keywords: antibiotic use, amoxicillin, norfloxacin, rational drug use

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Authors: M. Ibrahim Ali, M. El Dawi, M. A. Mohamed Ali

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In this study, the use of magnetic gradient survey, and the geoelectrical ground methods used together to explore archaeological features in Nuri’s pyramids area. Research methods used and the procedures and methodologies have taken full right during the study. The magnetic survey method was used to search for archaeological features using (Geoscan Fluxgate Gradiometer (FM36)). The study area was divided into a number of squares (networks) exactly equal (20 * 20 meters). These squares were collected at the end of the study to give a major network for each region. Networks also divided to take the sample using nets typically equal to (0.25 * 0.50 meter), in order to give a more specific archaeological features with some small bipolar anomalies that caused by buildings built from fired bricks. This definition is important to monitor many of the archaeological features such as rooms and others. This main network gives us an integrated map displayed for easy presentation, and it also allows for all the operations required using (Geoscan Geoplot software). The parallel traverse is the main way to take readings of the magnetic survey, to get out the high-quality data. The study area is very rich in old buildings that vary from small to very large. According to the proportion of the sand dunes and the loose soil, most of these buildings are not visible from the surface. Because of the proportion of the sandy dry soil, there is no connection between the ground surface and the electrodes. We tried to get electrical readings by adding salty water to the soil, but, unfortunately, we failed to confirm the magnetic readings with electrical readings as previously planned.

Keywords: archaeological features, independent grids, magnetic gradient, Nuri pyramid

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Authors: Varsha Tol, Laila Garda, Neelam Bhardwaj, Malata Usar

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In India, differently- abled girls suffer from a “dual stigma” of being female and physically challenged. The general consensus is that they are incapable of standing on their own two feet. It was observed that these girls do not have access to educational programs as most hostels do not keep them after the tenth grade. They are forced to return to a life of poverty and are often considered a liability by their families. Higher education is completely ignored. Parents focus on finding a husband and passing on their ‘burden’ to someone else. An innovative, intervention for differently-abled adolescent girls with the express purpose of mainstreaming them into society was started by Helplife. The objective was to enrich the lives of these differently abled adolescent girls through precise research, focused intervention and professionalism. This programme addresses physical, mental and social rehabilitation of the girls who come from impoverished backgrounds. These adolescents are reached by word of mouth, snowball technique and through the network of the NGO. Applications are invited from potential candidates which are scrutinized by a panel of experts. Selection criteria include her disability, socio-economic status, and desire and drive to make a difference in her own life. The six main areas of intervention are accommodation, education, health, professional courses, counseling and recreational activities. Each girl on an average resides in Helplife for a period of 2-3 years. Analysis of qualitative data collected at various time points indicates holistic development of character. A quality of life questionnaire showed a significant improvement in scores at three different time points in 75% of the current population under intervention i.e. 19 girls. Till date, 25 girls have successfully passed out from the intervention program completing their graduation/post-graduation. Currently, we have 19 differently abled girls housed in three flats in Pune district of Maharashtra. Out of which 14 girls are pursuing their graduation or post-graduation. Six of the girls are working in jobs in various sectors. In conclusion it may be noted with adequate support and guidance the sky is the limit. This journey of 12 years has been a learning for us with ups and downs modifying the intervention at every step. Helplife has a belief of impacting positively, individual lives of differently abled girls in order to empower them in a holistic manner. The intervention has a positive impact on differently abled girls. They serve as role models to other differently abled girls indicating that this is a road map to success by getting empowered to live with full potential and get integrated in the society in a dignified way.

Keywords: differently-abled, dual-stigma, empowerment, youth

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Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Lee Bih Ni

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This paper discusses that good learning involves all academic groups in the school. Blended learning is learning outside the classroom. Google Classroom is a free service learning app for schools, non-profit organizations and anyone with a personal Google account. Facilities accessed through computers and mobile phones are very useful for school teachers and students. Blended learning classrooms using both traditional and technology-based methods for teaching have become the norm for many educators. Using Google Classroom gives students access to online learning. Even if the teacher is not in the classroom, the teacher can provide learning. This is the supervision of the form of the teacher when the student is outside the school.

Keywords: blended learning, learning app, google classroom, schools

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Authors: Kaito Sugane, Mitsuhiro Shibata

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Self-healing polymers have attracted attention because their physical damage and cracks can be effectively repaired, thereby extending the lifetime of the materials. Self-healing polymers using host-guest interaction have the advantage that they are quickly repaired under mild temperature conditions when compared with self-healing polymer using dynamic covalent bonds such as Diels-Alder (DA)/retro-DA and disulfide metathesis reactions. Especially, it is known that hydrogels utilizing the host-guest interaction between cyclodextrin and various guest molecules are repeatedly self-repaired at room temperature. However, most of the works deal with hydrogels, and little attention has been paid for thermosetting resins as polyurethane, epoxy and unsaturated polyester resins. In this study, polyetherurethane networks (PUN-CD-Ads) incorporating cyclodextrin and adamantane moieties were prepared by the crosslinking reactions of β-cyclodextrin (CD), 1-adamantanol (AdOH), glycerol ethoxylate (GCE) and hexamethylene diisocyanate (HDI), and thermal, mechanical and self-healing properties of the polymer network films were investigated. Our attention was focused on the influences of molar ratio of CD/AdOH, GCE/CD and OH/NCO on the properties. The FT-IR, and gel fraction analysis revealed that the urethanization reaction smoothly progress to form polyurethane networks. When two cut pieces of the films were contacted at the cross-section at room temperature for 30 seconds, the two pieces adhered to produce a self-healed film. Especially, the PUN-CD-Ad prepared at GCE/CD = 5/1, CD/AdOH = 1/1, and OH/NCO = 1/1 film exhibited the highest healing efficiency for tensile strength. Most of the PUN-CD-Ads were successfully self-healed at room temperature.

Keywords: host-guest interaction, network polymer, polyurethane, self-healing

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Authors: Nasrin Hosseinzad, Ramin Ghasemi Shayan

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Chemotherapy is the most common procedure in the treatment of advanced cancers but is justsoberlyoperativeand toxic. Nevertheless, the efficiency of chemotherapy is restrictedowing to multiple drug resistance(MDR). Lately, plentiful preclinical experiments have revealedthatPaclitaxel-Curcumin could be an ultimateapproach to converse MDR and synergistically increase their efficiency. The connotationsamongst B-cell-lymphoma2(BCL-2) and multi-drug-resistance-associated-P-glycoprotein(MDR1) consequence of patients forecast the efficiency of paclitaxel-built chemoradiotherapy. There are evidences of the efficacy of paclitaxel in the treatment of surface-transmission of bladder-cell-carcinoma by manipulating bio-adhesive microspheres accomplishedthroughout measured release of drug at urine epithelium. In Genetically-Modified method, muco-adhesive oily constructionoftricaprylin, Tween 80, and paclitaxel group showed slighter toxicity than control in therapeutic dose. Postoperative chemotherapy-Paclitaxel might be more advantageous for survival than adjuvant chemo-radio-therapy, and coulddiminish postoperative complications in cervical cancer patients underwent a radical hysterectomy.HA-Se-PTX(Hyaluronic acid, Selenium, Paclitaxel) nanoparticles could observablyconstrain the proliferation, transmission, and invasion of metastatic cells and apoptosis. Furthermore, they exhibitedvast in vivo anti-tumor effect. Additionally, HA-Se-PTX displayedminor toxicity on mice-chef-organs. Briefly, HA-Se-PTX mightprogress into a respectednano-scale agentinrespiratory cancers. To sum up, Paclitaxel is considered a profitable anti-cancer drug in the treatment and anti-progress symptoms in malignant cancers.

Keywords: cancer, paclitaxel, chemotherapy, tumor

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

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Authors: Asuman Tezcan Mirer

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This proposed paper discusses nationalist socialist and communist propaganda struggles in the Turkish press during World War II. The paper aspires to analyze how government agencies directed and organized the Turkish press to prevent the "5th column" from influencing public opinion. During the Second World War, one of the most emphasized issues was propaganda and how Turkish citizens would be protected from the effects of disinformation. Istanbul became a significant headquarters for belligerent countries' intelligence services, and these services were involved in gathering intelligence and disseminating propaganda. The main motive of national socialist propaganda was "anti-communism" in Turkey. Subsidizing certain magazines, controlling German companies' advertisements and paper trade, spreading rumors, printing propaganda brochures, and showing German propaganda films are some tactics that the nationalist socialists applied before and during the Second World War. On the other hand, the communists targeted Turkish racist/ultra-nationalist groups and their publications, which were influenced by the Nazi regime. They were also involved in distributing Marxist publications, printing brochures, and broadcasting radio programs. This study composes of three parts. The first part describes the nationalist socialist and communist propaganda activities in Turkey during the Second World War. The second part addresses the debates over propaganda among selected newspapers representing different ideologies. Finally, the last part analyzes the Turkish government's press policy. It explains why the government allowed ideological debates in the press despite its authoritarian press policy and "active neutrality" stance in the international arena.

Keywords: propaganda, press, 5th column, World War II, Turkey

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