Search results for: data driven decision making

Authors: Artem Kim, Clara Savary, Christele Dubourg, Wilfrid Carre, Houda Hamdi-Roze, Valerie Dupé, Sylvie Odent, Marie De Tayrac, Veronique David

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Holoprosencephaly (HPE) is a rare congenital brain malformation resulting from the incomplete separation of the two cerebral hemispheres. It is characterized by a wide phenotypic spectrum and a high degree of locus heterogeneity. Genetic defects in 16 genes have already been implicated in HPE, but account for only 30% of cases, suggesting that a large part of genetic factors remains to be discovered. HPE has been recently redefined as a complex multigenic disorder, requiring the joint effect of multiple mutational events in genes belonging to one or several developmental pathways. The onset of HPE may result from accumulation of the effects of multiple rare variants in functionally-related genes, each conferring a moderate increase in the risk of HPE onset. In order to decipher the genetic basis of HPE, unconventional patterns of inheritance involving multiple genetic factors need to be considered. The primary objective of this study was to uncover possible disease causing combinations of multiple rare variants underlying HPE by performing trio-based Whole Exome Sequencing (WES) of familial cases where no molecular diagnosis could be established. 39 families were selected with no fully-penetrant causal mutation in known HPE gene, no chromosomic aberrations/copy number variants and without any implication of environmental factors. As the main challenge was to identify disease-related variants among a large number of nonpathogenic polymorphisms detected by WES classical scheme, a novel variant prioritization approach was established. It combined WES filtering with complementary gene-level approaches: transcriptome-driven (RNA-Seq data) and clinically-driven (public clinical data) strategies. Briefly, a filtering approach was performed to select variants compatible with disease segregation, population frequency and pathogenicity prediction to identify an exhaustive list of rare deleterious variants. The exome search space was then reduced by restricting the analysis to candidate genes identified by either transcriptome-driven strategy (genes sharing highly similar expression patterns with known HPE genes during cerebral development) or clinically-driven strategy (genes associated to phenotypes of interest overlapping with HPE). Deeper analyses of candidate variants were then performed on a family-by-family basis. These included the exploration of clinical information, expression studies, variant characteristics, recurrence of mutated genes and available biological knowledge. A novel bioinformatics pipeline was designed. Applied to the 39 families, this final integrated workflow identified an average of 11 candidate variants per family. Most of candidate variants were inherited from asymptomatic parents suggesting a multigenic inheritance pattern requiring the association of multiple mutational events. The manual analysis highlighted 5 new strong HPE candidate genes showing recurrences in distinct families. Functional validations of these genes are foreseen.

Keywords: complex genetic disorder, holoprosencephaly, multiple rare variants, whole exome sequencing

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Najam U. Saqib

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Self-construal or an individual’s view of him or herself is an important variable by which culture affects the way people think and act. This notion of self-construal is identified with two distinct perspectives on the self. Within the independent construal, the self is seen as different from others, a way of defining the self, prominent in Western societies. The interdependent perspective which is typical for Eastern cultures emphasizes the connectedness of the self to others. The degree of independence-interdependence in one’s self-construal is thought to affect behavior, acceptance of social values, and decision making. This paper manipulates self-construal of Qatari consumers and investigates its effects on accepting incongruent changes in culture as a result of adopting market offerings and behavior that may be perceived as inconsistent with their self-construal. The research recommends strategies for policy makers in Qatar for successful advocacy of initiatives of national importance such as reducing diabetes and obesity by applying self-construal theory.

Keywords: cross-cultural, consumer behavior, self-construal, GCC (Gulf Cooperation Council)

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Authors: Terungwa Simon Yange, Agana Moses A.

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This paper studied steganography and designed a simplistic approach to a steganographic tool for hiding information in image files with the view of addressing the security challenges with data by hiding data from unauthorized users to improve its security. The Structured Systems Analysis and Design Method (SSADM) was used in this work. The system was developed using Java Development Kit (JDK) 1.7.0_10 and MySQL Server as its backend. The system was tested with some hypothetical health records which proved the possibility of protecting data from unauthorized users by making it secret so that its existence cannot be easily recognized by fraudulent users. It further strengthens the confidentiality of patient records kept by medical practitioners in the health setting. In conclusion, this work was able to produce a user friendly steganography software that is very fast to install and easy to operate to ensure privacy and secrecy of sensitive data. It also produced an exact copy of the original image and the one carrying the secret message when compared with each.

Keywords: steganography, cryptography, encryption, decryption, secrecy

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Authors: Karolína Vozková, Matěj Kuc

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Net fee and commission income is one of the key elements of a bank’s core income. In the current low-interest rate environment, this type of income is gaining importance relative to net interest income. This paper analyses the effects of bank and country specific determinants of net fee and commission income on a set of cooperative banks from European countries in the 2007-2014 period. In order to do that, dynamic panel data methods (system Generalized Methods of Moments) were employed. Subsequently, alternative panel data methods were run as robustness checks of the analysis. Strong positive impact of bank concentration on the share of net fee and commission income was found, which proves that cooperative banks tend to display a higher share of fee income in less competitive markets. This is probably connected with the fact that they stick with their traditional deposit-taking and loan-providing model and fees on these services are driven down by the competitors. Moreover, compared to commercial banks, cooperatives do not expand heavily into non-traditional fee bearing services under competition and their overall fee income share is therefore decreasing with the increased competitiveness of the sector.

Keywords: cooperative banking, dynamic panel data models, net fee and commission income, system GMM

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Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

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Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

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Authors: Trinh Hoang Hong Hue

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Citizen Participation has been largely considered as an important objective of improving democracy and government decision-making in Vietnam recently. The Public Administration Performance Index Survey data (PAPI) indicated that citizens in provinces that have a higher proportion of male often less participate in local governance than those in provinces that have lower proportion of male. That means Vietnamese women more actively participate at the local governance rather than men. Thus this study will explore factors involving gender differences that impact on citizen participation at the local level. Applying qualitative approach, mainly in-depth interview, this study explores four diverse perspectives on enhancing citizen participation for both women and men at the local governance including civic knowledge; the trust of citizens; suitable policies of local government; and the role of NGOs. Furthermore, this study also points out two crucial reasons that are leading to the gender differences of citizen participation at the local level. Firstly, because Vietnamese women play the main role in family financial management; then they are willing to highly contribute to ‘voluntary contributions’; one of the four sub-dimensions of the concept ‘citizen participation’ of PAPI. Secondly, in Vietnam, women are deeply prone to be interested in the small issues at the local governance; whereas men are much keen on the bigger issues at national and international governance.

Keywords: citizen participation, gender, women, local governance, PAPI, Vietnam

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Authors: Nerella Srinivas

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This study explores the significance of patent protection for artificial intelligence (AI) innovations in the pharmaceutical sector, emphasizing applications in drug discovery, personalized medicine, and clinical trial optimization. The challenges of patenting AI-driven inventions are outlined, focusing on the classification of algorithms as abstract ideas, meeting the non-obviousness standard, and issues around defining inventorship. The methodology includes examining case studies and existing patents, with an emphasis on how companies like Benevolent AI and Insilico Medicine have successfully secured patent rights. Findings demonstrate that a strategic approach to patent protection is essential, with particular attention to showcasing AI’s technical contributions to pharmaceutical advancements. Conclusively, the study underscores the critical role of understanding patent law and innovation strategies in leveraging intellectual property rights in the rapidly advancing field of AI-driven pharmaceuticals.

Keywords: artificial intelligence, pharmaceutical industry, patent protection, drug discovery, personalized medicine, clinical trials, intellectual property, non-obviousness

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Authors: Siddharth Krishnaswamy

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Problem Statement: Currently, when analyzing household food security, the most commonly studied food access indicators are household income and expenditure. Larger studies do take into account other indices such as credit and employment. But these are baselines studies and by definition are conducted infrequently. Food security analysis for access is usually dedicated to analyzing income and expenditure indicators. And both these indicators are notoriously inconsistent. Yet this data can very often end up being the basis on which household food access is calculated; and by extension, be used for decision making. Objectives: This paper argues that along with income and expenditure, credit and debit information should be collected so that an accurate analysis of household food security (and in particular) food access can be determined. The lack of collection and analysis of this information routinely means that there is often a “masking” of the actual situation; a household’s food access and food availability patterns may be adequate mainly as a result of borrowing and may even be due to a long- term dependency (a debt cycle). In other words, such a household is, in reality, worse off than it appears a factor masked by its performance on basic access indicators. Procedures/methodologies/approaches: Existing food security data sets collected in 2005 in Azerbaijan, 2010 across Myanmar and 2014-15 across Uganda were used to support the theory that analyzing income and expenditure of a HHs and analyzing the same in addition to data on credit & borrowing patterns will result in an entirely different scenario of food access of the household. Furthermore, the data analyzed depicts food consumption patterns across groups of households and then relates this to the extent of dependency on credit, i.e. households borrowing money in order to meet food needs. Finally, response options that were based on analyzing only income and expenditure; and response options based on income, expenditure, credit, and borrowing – from the same geographical area of operation are studied and discussed. Results: The purpose of this work was to see if existing methods of household food security analysis could be improved. It is hoped that food security analysts will collect household level information on credit and debit and analyze them against income, expenditure and consumption patterns. This will help determine if a household’s food access and availability are dependent on unsustainable strategies such as borrowing money for food or undertaking sustained debts. Conclusions: The results clearly show the amount of relevant information that is missing in Food Access analysis if debit and borrowing of the household is not analyzed along with the typical Food Access indicators that are usually analyzed. And the serious repercussions this has on Programmatic response and interventions.

Keywords: analysis, food security indicators, response, resilience analysis

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Authors: Javad Khazaei, Rick Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: consensus tracking, distributed control, model-free control, sparse identification of dynamical systems

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Authors: Somayeh Nezami

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The management of financial and human resources of police in metropolitans requires many information and exact plans to reduce a rate of crime and increase the safety of the society. Geographical Information Systems have an important role in providing crime maps and their analysis. By using them and identification of crime hot spots along with spatial presentation of the results, it is possible to allocate optimum resources while presenting effective methods for decision making and preventive solutions. In this paper, we try to explain and compare between some of the methods of hot spots analysis such as Mode, Fuzzy Mode and Nearest Neighbour Hierarchical spatial clustering (NNH). Then the spots with the highest crime rates of drug smuggling for one province in Iran with borderline with Afghanistan are obtained. We will show that among these three methods NNH leads to the best result.

Keywords: GIS, Hot spots, nearest neighbor hierarchical spatial clustering, NNH, spatial analysis of crime

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Authors: S. Khakurel, R. P. Dhakal, T. Z. Yeow

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Downtime is one of the major sources (alongside damage and injury/death) of financial loss incurred by a structure in an earthquake. The length of downtime associated with a building after an earthquake varies depending on the time taken for the reaction (to the earthquake), decision (on the future course of action) and execution (of the decided course of action) phases. Post-earthquake assessment of buildings is a key step in the decision making process to decide the appropriate safety placarding as well as to decide whether a damaged building is to be repaired or demolished. The aim of the present study is to develop a model to quantify downtime associated with the post-earthquake building-assessment phase in terms of two parameters; i) duration of the different assessment phase; and ii) probability of different colour tagging. Post-earthquake assessment of buildings includes three stages; Level 1 Rapid Assessment including a fast external inspection shortly after the earthquake, Level 2 Rapid Assessment including a visit inside the building and Detailed Engineering Evaluation (if needed). In this study, the durations of all three assessment phases are first estimated from the total number of damaged buildings, total number of available engineers and the average time needed for assessing each building. Then, probability of different tag colours is computed from the 2010-11 Canterbury earthquake Sequence database. Finally, a downtime model for the post-earthquake building inspection phase is proposed based on the estimated phase length and probability of tag colours. This model is expected to be used for rapid estimation of seismic downtime within the Loss Optimisation Seismic Design (LOSD) framework.

Keywords: assessment, downtime, LOSD, Loss Optimisation Seismic Design, phase length, tag color

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, Ayse Karacaorenli

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Maintenance strategies can be classified into two types, which are reactive and proactive, with respect to the time of the failure and maintenance. If the maintenance activity is done after a breakdown, it is called reactive maintenance. On the other hand, proactive maintenance, which is further divided as preventive and predictive, focuses on maintaining components before a failure occurs to prevent expensive halts. Recently, the number of interacting components in a system has increased rapidly and therefore, the structure of the systems have become more complex. This situation has made it difficult to provide the right maintenance decisions. Herewith, determining effective decisions has played a significant role. In multi-component systems, many methodologies and strategies can be applied when a component or a system has already broken down or when it is desired to identify and avoid proactively defects that could lead to future failure. This study focuses on the comparison of various maintenance strategies on a multi-component dynamic system. Components in the system are hidden, although there exists partial observability to the decision maker and they deteriorate in time. Several predefined policies under corrective, preventive and predictive maintenance strategies are considered to minimize the total maintenance cost in a planning horizon. The policies are simulated via Dynamic Bayesian Networks on a multi-component system with different policy parameters and cost scenarios, and their performances are evaluated. Results show that when the difference between the corrective and proactive maintenance cost is low, none of the proactive maintenance policies is significantly better than the corrective maintenance. However, when the difference is increased, at least one policy parameter for each proactive maintenance strategy gives significantly lower cost than the corrective maintenance.

Keywords: decision making, dynamic Bayesian networks, maintenance, multi-component systems, reliability

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Authors: Somayeh Bahrami, Seyed Jalal Dehghani Firoozabadi

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Environmental governance is an interdisciplinary concept in political ecology and environmental policy focusing on the necessity of embedding the environmental issues in all levels of decision-making and act of states. Similar to sustainable development the concept of environmental governance believes that economic and political life of societies and countries need to be considered as a subset of the environment. This concept has been accepted by North Countries, those that have done the most irreparable environmental damage since the Industrial Revolution. Although North Countries are more responsible for damage to the environment, considering the global fluidity logic of environmental challenges, such an impression doesn’t cause developing countries to disavow responsibility for regional and international cooperation to protect the environment. Establishing an environmental governance at all levels of local, national, regional and global is one of the most significant ways to improve sustainable development. Given to the various political and economic difficulties developing countries including the Middle East face, building environmental governance in these countries is difficult but feasible, as these difficulties have not impeded their mutual partnership for confronting joint environmental issues. However, the environmental issues wouldn’t be solved only by mutual partnership but by establishing environmental governance, establishing regional environmental institutions (an introduction to building Regional Environmental Governance) and delegation of some environmental authorities to the mentioned institutions. The research is aimed at examining necessities, opportunities, and barriers to establishing Regional Environmental Governance in the Middle East. Therefore, this research seeks to answer the question of whether establishing Regional Environmental Governance is possible in the Middle East and if so then why. This study used descriptive-analytical methods and the inferential methodology has been used to reach the goals. Data has been collected by using library and internet sources as well as news sources on the basis of objective-historical data.

Keywords: environmental democracy (ED), environmental governance (EG), middle east (ME), regional environmental governance (REG)

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Authors: Mohammad Rahmani Rezaiyeh, Mojtaba Rahmani Rezaiyeh, Mehrdad Rahmani Rezaiyeh

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Smart speed bump is a new invention and I am invented it. Smart speed bump is a system that can change the position of speed bumps either active or passive in necessary situations. The basic system of smart speed bumps is based on a robotic system which includes mechanic, electronic and artificial intelligence. The smart speed bump is capable of smart decision making and can change its position by anticipating the peak of terrific hours. It can be noted to the advantages of this system such as preventing the waste of petrol while crossing speed bumps, traffic management, accelerating, flowing and securing traffic, reducing accidents and judicial records.

Keywords: invention, smart, robotic system, speed bump, traffic, management

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Authors: Mehak Masood

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Education is critical for promoting sustainable development and improving the capacity of people to address environment and development issues. It is also critical for achieving environmental and ethical awareness, values and attitudes, skills and behaviour consistent with sustainable development and for effective public participation in decision-making. In this regard, The British Council Pakistan have conducted a need assessment study conducted during the training sessions with three different groups of educationists belonging to both government and public sectors on the topic of Climate Change and Environmental Education (CCEE). This study aims to review perceptions about climate change and environmental education and analyze its need and importance according to educationists of Pakistan.

Keywords: environmental education, climate change, resilience development, awareness

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Authors: Justin A. Udie, Subhes C. Bhatthacharyya, Leticia Ozawa-Meida

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The impact of climate change is severe in the Niger Delta and critical oil and gas infrastructures are vulnerable. This is partly due to lack of specific impact assessment framework to assess impact indices on both existing and new infrastructures. The purpose of this paper is to develop a framework for the assessment of climate change impact on critical oil and gas infrastructure in the region. Comparative and documentary methods as well as analysis of frameworks were used to develop a flexible, integrated and conceptual four dimensional framework underpinning; 1. Scoping – the theoretical identification of inherent climate burdens, review of exposure, adaptive capacities and delineation of critical infrastructure; 2. Vulnerability assessment – presents a systematic procedure for the assessment of infrastructure vulnerability. It provides real time re-scoping, practical need for data collection, analysis and review. Physical examination of systems is encouraged to complement the scoped data and ascertain the level of exposure to relevant climate risks in the area; 3. New infrastructure – consider infrastructures that are still at developmental level. It seeks to suggest the inclusion of flexible adaptive capacities in original design of infrastructures in line with climate threats and projections; 4. The Mainstreaming Climate Impact Assessment into government’s environmental decision making approach. Though this framework is designed specifically for the estimation of exposure, adaptive capacities and criticality of vulnerable oil and gas infrastructures in the Niger Delta to climate burdens; it is recommended for researchers and experts as a first-hand generic and practicable tool which can be used for the assessment of other infrastructures perceived as critical and vulnerable. The paper does not provide further tools that synch into the methodological approach but presents pointers upon which a pragmatic methodology can be developed.

Keywords: adaptation, assessment, conceptual, climate, change, framework, vulnerability

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Authors: Mohammad Safaeipour, Yousef Amer

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This study directs its focus on developing a conceptual model to offer a systematic and integrated method to weigh the related measures and evaluate a competence of hospitals and rank of the selected hospitals that involve and consider the stakeholders’ key performance indicators (KPI’s). The Analytical Hierarchy Process (AHP) approach will use to weigh the dimensions and related sub- components. The weights and performance scores will combine by using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and rank the selected hospitals. The results of this study provide interesting insight into the necessity of process improvement implementation in which hospital that received the lowest ranking score.

Keywords: performance measurement system, PMS, hospitals, AHP, TOPSIS

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Authors: Susmita Ghosh, Bhaskar Bhowmick

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Market is an important factor for start-ups to look into during decision-making in product development and related areas. Emerging country markets are more uncertain in terms of information availability and institutional supports. The literature review of market uncertainty reveals the need for identifying factors representing the market uncertainty. This paper identifies factors for market uncertainty using Exploratory Factor Analysis (EFA) and confirms the number of factor retention using an alternative factor retention criterion, ‘Parallel Analysis’. 500 entrepreneurs, engaged in start-ups from all over India participated in the study. This paper concludes with the factor structure of ‘market uncertainty’ having dimensions of uncertainty in industry orientation, uncertainty in customer orientation and uncertainty in marketing orientation.

Keywords: uncertainty, market, orientation, competitor, demand

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Authors: Pankhudi Khandelwal

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The revenue models of digital giants such as Facebook and Google, use targeted advertising for revenues. Such a model requires huge amounts of consumer data. While the data protection law deals with the protection of personal data, however, this data is acquired by the companies on the basis of consent, performance of a contract, or legitimate interests. This paper analyses the role that competition law can play in evading these loopholes for the protection of data and privacy of online consumers. Digital markets have certain distinctive features such as network effects and feedback loop, which gives incumbents of these markets a first-mover advantage. This creates a situation where the winner takes it all, thus creating entry barriers and concentration in the market. It has been also seen that this dominant position is then used by the undertakings for leveraging in other markets. This can be harmful to the consumers in form of less privacy, less choice, and stifling innovation, as seen in the cases of Facebook Cambridge Analytica, Google Shopping, and Google Android. Therefore, the article aims to provide a legal framework wherein the data protection law and competition law can come together to provide a balance in regulating digital markets. The issue has become more relevant in light of the Facebook decision by German competition authority, where it was held that Facebook had abused its dominant position by not complying with data protection rules, which constituted an exploitative practice. The paper looks into the jurisdictional boundaries that the data protection and competition authorities can work from and suggests ex ante regulation through data protection law and ex post regulation through competition law. It further suggests a change in the consumer welfare standard where harm to privacy should be considered as an indicator of low quality.

Keywords: data protection, dominance, ex ante regulation, ex post regulation

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Authors: Udeh Nneka Evelyn

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The shortcomings of traditional costing system, in terms of validity, accuracy, consistency and relevance increased the need for modern management accounting system. ABC (Activity-Based Costing) can be used as a modern tool for planning, control and decision making for management. Past studies on activity-based costing (ABC) system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing techniques in service oriented business organisations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on activity-based costing (ABC). Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry, and government organizations. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: Identification of the most profitable customers; more accurate product and service pricing; increase product profitability; well-organized process costs.

Keywords: profitability, activity-based costing (ABC), management accounting, manufacture

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Authors: Dina Magdy Abdo, Ayat N. El-Shazly, Hamdy Maamoun Abdel-Ghafar, E. A. Abdel-Aal

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Forward osmosis (FO) is one of the important processes during the wastewater treatment system for environmental remediation and fresh water regeneration. Both Egypt and China are troubled by over millions of tons of wastewater every year, including domestic and industrial wastewater. However, traditional FO process in wastewater treatment usually suffers low efficiency and high energy consumption because of the continuously diluted draw solution. An additional concentration process is necessary to keep running of FO separation, causing energy waste. Based on the previous study on photothermal membrane, a sun-driven evaporation process is integrated into the draw solution side of FO system. During the sun-driven evaporation, not only the draw solution can be concentrated to maintain a stable and sustainable FO system, but fresh water can be directly separated for regeneration. Solar energy is the ultimate energy source of everything we have on Earth and is, without any doubt, the most renewable and sustainable energy source available to us. Additionally, the FO membrane process is rationally designed to limit the concentration polarization and fouling. The FO membrane’s structure and surface property will be further optimized by the adjustment of the doping ratio of controllable nano-materials, membrane formation conditions, and selection of functional groups. A novel kind of nano-composite functional separation membrane with bi-interception layers and high hydrophilicity will be developed for the application in wastewater treatment. So, herein we aim to design a new wastewater treatment system include forward osmosis with high-efficiency energy recovery via the integration of photothermal membrane.

Keywords: forword, membrane, solar, water treatment

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Adan Valdez, Shawn Gallaher, James Morison, Jordan Aragon

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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport and modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116 km3/year. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff. The total climatological freshwater content is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity driven pycnocline as opposed to the temperature driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and remotely sensed dynamic ocean topography (DOT). In-situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time consuming. NASA’s Advanced Topographic Laser Altimeter System (ATLAS) derived dynamic ocean topography (DOT), and Air Expendable CTD (AXCTD) derived Freshwater Content are used to develop a linear regression model. In-situ data for the regression model is collected across the 150° West meridian, which typically defines the centerline of the Beaufort Gyre. Two freshwater content models are determined by integrating the freshwater volume between the surface and an isopycnal corresponding to reference salinities of 28.7 and 34.8. These salinities correspond to those of the winter pycnocline and total climatological freshwater content, respectively. Using each model, we determine the strength of the linear relationship between freshwater content and satellite derived DOT. The result of this modeling study could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non in-situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: ICESat-2, dynamic ocean topography, freshwater content, beaufort gyre

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Authors: Yurii Bloshko, Oksana Olar

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This paper presents the analysis of 6 different classes of Petri nets: fuzzy Petri nets (FPN), generalized fuzzy Petri nets (GFPN), parameterized fuzzy Petri nets (PFPN), T2GFPN, flexible generalized fuzzy Petri nets (FGFPN), binary Petri nets (BPN). These classes were simulated in the special software PNeS® for the analysis of its pros and cons on the example of models which are dedicated to the decision-making process of passenger transport logistics. The paper includes the analysis of two approaches: when input values are filled with the experts’ knowledge; when fuzzy expectations represented by output values are added to the point. These approaches fulfill the possibilities of triples of functions which are replaced with different combinations of t-/s-norms.

Keywords: fuzzy petri net, intelligent computational techniques, knowledge representation, triangular norms

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Authors: Puja Sharma, S. R. Dhiman, Bhararti Kashyap, Y. C. Gupta, Shabnam Pangtu

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The experiments were carried out for mass multiplication and domestication of an endangered native tree spp, an orchid and an ornamental shrub having high medicinal value. Floriculture industry is novelty driven, hence the potential of these native ornamentals was assessed for their utilization as a novelty in the industry. For the mass propagation of endangered tree Oroxylum indicum, seed propagation and vegetative propagation techniques were successfully utilized. Highest seed germination was recorded in a medium containing cocopeat and perlite (1:1 v/v). Semi hard wood cuttings treated with IBA 2000 ppm planted in cocopeat+ sand+ perlite medium and maintained at 80% RH has resulted in about 90% rooting. The low growing tree was successfully domestication and has potential to be utilized in landscape industry. In the present study, cutting propagation and division of clump were used as methods for multiplication of Aerides multiflora, a native orchid spp. Soft wood cuttings treated with IBA 500 ppm planted in cocopeat medium was found to be the most suitable vegetative method resulting in 90 % rooting. It was domesticated as pot plant and for making hanging baskets. Propagation through seeds and cuttings was carried out for Pyracantha crenulata, a native ornamental shrub which is a cardiovascular medicine. For vegetative propagation, treatment of basal end of semi- hardwood cuttings of Pyracantha with IBA 3000 ppm (quick dip) and planting in cocopeat under mist chamber maintained at a relative humidity of 70-80% resulted in about 90% rooting out of all applied treatments in the study. For seed propagation, treatment of seeds in boiling water for 20 minutes and planting in cocopeat resulted in 82.55 % germination. The shrub was domesticated for its use as pot plant, protective hedge and for making bonsai.

Keywords: native, endangered, multiplication, domestication, oroxylum, aerides, pyracantha

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

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Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

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Authors: Ernesto A. Lagarda-Leyva, Manuel A. Valenzuela L., José G. Oshima C., Arnulfo A. Naranjo-Flores

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From August to December of 2016, a diagnostic and strategic planning study was carried out on the supply chain of the company Agropecuaria GABO S.A. de C.V. The final product of the study was the development of the strategic plan and a project portfolio to meet the demands of the three links in the supply chain of the Roma tomato exported annually to the United States of America. In this project, the strategic objective of ensuring the proper handling of the product was selected and one of the goals associated with this was the employment of quantitative methods to support decision making. Considering the antecedents, the objective of this case study was to develop a model to analyze the behavioral dynamics in the distribution chain, from the logistics of storage and shipment of Roma tomato in 81-case pallets (11.5 kg per case), to the two pre-cooling rooms and eventual loading onto transports, seeking to reduce the bottleneck and the associated costs by means of a dynamic interface. The methodology used was that of system dynamics, considering four phases that were adapted to the purpose of the study: 1) the conceptualization phase; 2) the formulation phase; 3) the evaluation phase; and 4) the communication phase. The main practical conclusions lead to the possibility of reducing both the bottlenecks in the cooling rooms and the costs by simulating scenarios and modifying certain policies. Furthermore, the creation of the dynamic interface between the model and the stakeholders was achieved by generating interaction with buttons and simple instructions that allow making modifications and observing diverse behaviors.

Keywords: agrilogistics, distribution, scenarios, system dynamics

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Authors: Yafa Haron, Hanna Adami

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Background: World Health Organization emphasizes the contribution of nurses in planning and implementing health policies and reforms. Aim: To evaluate nursing students’ attitudes towards nurses’ involvement in health policy issues. Methods: Mixed-methods; qualitative and quantitative – a descriptive study. Participants - nursing students who were enrolled in their last year in the undergraduate program (BSN). Qualitative data included two open-ended questions: What is health policy and what is the importance of studying health policy, and 18 statements on the Likert Scale range 1-5. Results: Qualitativeanalysisrevealed that the majority of students defined health policy as a set of rules and regulations that defined procedures, borders, and proper conduct. 73% of students responded that nurses should be active in policymaking, but only 22% thought that nurses were currently involved in political issues. 28% thought that nurses do not have the knowledge and the time needed (60%) for political activity. 77% thought that the work environment did not encourage nurses to be politically active. Nursing students are aware of the importance towards nurses’ involvement in health policy issues, however, they do not have role models based on their low evaluation regarding nurses’ involvement in the health policy decision making process at the local or national level. Conclusions: Results emphasize the importance and the need of implementation the recommendation to include “advance policy changes” as core competency in nursing education and practice.

Keywords: health policy, nursing education, health systems, student perceptions

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