Search results for: decision tree model

Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart

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The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.

Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition

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Authors: Minna-Maari Harmaala, Hanna Harilainen

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Estimates of the economic value of transitioning to circular economy models vary but it has been estimated to represent $1 trillion worth of new business into the global economy. In Europe alone, estimates claim that adopting circular-economy principles could not only have environmental and social benefits but also generate a net economic benefit of €1.8 trillion by 2030. Proponents of a circular economy argue that it offers a major opportunity to increase resource productivity, decrease resource dependence and waste, and increase employment and growth. A circular system could improve competitiveness and unleash innovation. Yet, most companies are not capturing these opportunities and thus the even abundant circular opportunities remain uncaptured even though they would seem inherently profitable. Service design in broad terms relates to developing an existing or a new service or service concept with emphasis and focus on the customer experience from the onset of the development process. Service design may even mean starting from scratch and co-creating the service concept entirely with the help of customer involvement. Service design methodologies provide a structured way of incorporating customer understanding and involvement in the process of designing better services with better resonance to customer needs. A business model is a depiction of how the company creates, delivers, and captures value; i.e. how it organizes its business. The process of business model development and adjustment or modification is also called business model innovation. Innovating business models has become a part of business strategy. Our hypothesis is that in addition to linear models still being easier to adopt and often with lower threshold costs, companies lack an understanding of how circular models can be adopted into their business and how customers will be willing and ready to adopt the new circular business models. In our research, we use robust service design methodology to develop circular economy solutions with two case study companies. The aim of the process is to not only develop the service concepts and portfolio, but to demonstrate the willingness to adopt circular solutions exists in the customer base. In addition to service design, we employ business model innovation methods to develop, test, and validate the new circular business models further. The results clearly indicate that amongst the customer groups there are specific customer personas that are willing to adopt and in fact are expecting the companies to take a leading role in the transition towards a circular economy. At the same time, there is a group of indifferents, to whom the idea of circularity provides no added value. In addition, the case studies clearly show what changes adoption of circular economy principles brings to the existing business model and how they can be integrated.

Keywords: business model innovation, circular economy, circular economy business models, service design

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Authors: Abbas Al-Refaie

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The research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC.

Keywords: cluster analysis, telecom industry, switching cost, customer churn

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Authors: Agata Zakrzewska, Dominik Kopeć, Adrian Ochtyra

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The growing number of new cameras, sensors, and research methods allow for a broader application of thermal data in remote sensing vegetation studies. The aim of this research was to check whether it is possible to use thermal infrared data with a spectral range (3.6-4.9 μm) obtained during the day and the night to assess the health condition of selected species of deciduous trees in an urban environment. For this purpose, research was carried out in the city center of Warsaw (Poland) in 2020. During the airborne data acquisition, thermal data, laser scanning, and orthophoto map images were collected. Synchronously with airborne data, ground reference data were obtained for 617 studied species (Acer platanoides, Acer pseudoplatanus, Aesculus hippocastanum, Tilia cordata, and Tilia × euchlora) in different health condition states. The results were as follows: (i) healthy trees are cooler than trees in poor condition and dying both in the daytime and nighttime data; (ii) the difference in the canopy temperatures between healthy and dying trees was 1.06oC of mean value on the nighttime data and 3.28oC of mean value on the daytime data; (iii) condition classes significantly differentiate on both daytime and nighttime thermal data, but only on daytime data all condition classes differed statistically significantly from each other. In conclusion, the aerial thermal data can be considered as an alternative to hyperspectral data, a method of assessing the health condition of trees in an urban environment. Especially data obtained during the day, which can differentiate condition classes better than data obtained at night. The method based on thermal infrared and laser scanning data fusion could be a quick and efficient solution for identifying trees in poor health that should be visually checked in the field.

Keywords: middle wave infrared, thermal imagery, tree discoloration, urban trees

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Authors: Olga Blasco-Blasco, Vicente Liern

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The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

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Authors: Mohammad Abu-Taleb

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The final report of the Royal Commission into Australian financial services misconduct, released in February 2019, has had a significant impact on the financial advice industry. The recommendations released in the Commissioner’s final report include changes to ongoing fee arrangements, a new disciplinary system for financial advisers, and mandatory reporting of compliance concerns. This thesis aims to explore the impact of the Royal Commission’s recommendations on the operating model of financial advice firms in terms of advice products, processes, delivery models, and customer segments. Also, this research seeks to investigate whether the Royal Commission’s outcome has accelerated the use of enhanced technology solutions within the operating model of financial advice firms. And to identify the key challenges confronting financial advice firms whilst implementing the Commissioner’s recommendations across their operating models. In order to achieve the objectives of this thesis, a qualitative research design has been adopted through semi-structured in-depth interviews with 24 financial advisers and managers who are engaged in the operation of financial advice services. The study used the thematic analysis approach to interpret the qualitative data collected from the interviews. The findings of this thesis reveal that customer-centric operating models will become more prominent across the financial advice industry in response to the Commissioner’s final report. And the Royal Commission’s outcome has accelerated the use of advice technology solutions within the operating model of financial advice firms. In addition, financial advice firms have started more than before using simpler and more automated web-based advice services, which enable financial advisers to provide simple advice in a greater scale, and also to accelerate the use of robo-advice models and digital delivery to mass customers in the long term. Furthermore, the study identifies process and technology changes as, long with technical and interpersonal skills development, as the key challenges encountered financial advice firms whilst implementing the Commissioner’s recommendations across their operating models.

Keywords: hayne royal commission, financial planning advice, operating model, advice products, advice processes, delivery models, customer segments, digital advice solutions

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Authors: Dariush Jafari, S. Mostafa Nowee

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In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.

Keywords: thermodynamic modeling, ANN, solubility, ternary electrolyte system

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Authors: Chalermpol Tapsai

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The objectives of this research were to develop and find the efficiency of integrated online lessons by investigating the usage of online lessons, the relationship between learners’ background knowledge, and the achievement after learning with online lessons. The sample group in this study consisted of 97 students randomly selected from 121 students registering in 1/2012 at Trimitwittayaram Learning Center. The sample technique employed stratified sample technique of 4 groups according to their proficiency, i.e. high, moderate, low, and non-knowledge. The research instrument included online lessons in integration model on the topic of Java Programming, test after each lesson, the achievement test at the end of the course, and the questionnaires to find learners’ satisfaction. The results showed that the efficiency of online lessons was 90.20/89.18 with the achievement of after learning with the lessons higher than that before the lessons at the statistically significant level of 0.05. Moreover, the background knowledge of the learners on the programming showed the positive relationship with the achievement learning at the statistically significant level at 0.05. Learners with high background knowledge employed less exercises and samples than those with lower background knowledge. While learners with different background in the group of moderate and low did not show the significant difference in employing samples and exercises.

Keywords: integration model, online lessons, learners’ background knowledge, efficiency

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Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

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Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Ida Bagus Made Putra Jandhana, Teuku Yuri M. Zagloel, Rahmat Nurchayo

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Having several crises that affect industrial sector performance in the past decades, decision makers should utilize measurement application that enables them to measure industrial resiliency more precisely. It provides not only a framework for the development of resilience measurement application, but also several theories for the concept building blocks, such as performance measurement management, and resilience engineering in real world environment. This research is a continuation of previously published paper on performance measurement in the industrial sector. Finally, this paper contributes an alternative performance measurement method in industrial sector based on resilience concept. Moreover, this research demonstrates how applicable the concept of resilience engineering is and its method of measurement.

Keywords: industrial, measurement, resilience, sector

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Authors: N. Massoum, B. Bouazza

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In this paper, we have developed a numerical simulation model to describe the electrical properties of GaInP MESFET with submicron gate (Lg = 0.5 µm). This model takes into account the three-dimensional (3D) distribution of the load in the short channel and the law effect of mobility as a function of electric field. Simulation software based on a stochastic method such as Monte Carlo has been established. The results are discussed and compared with those of the experiment. The result suggests experimentally that, in a very small gate length in our devices (smaller than 40 nm), short-channel tunneling explains the degradation of transistor performance, which was previously enhanced by velocity overshoot.

Keywords: Monte Carlo simulation, transient electron transport, MESFET device, simulation software

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Authors: Mohd Adib Abd Muin, Shuhairimi Abdullah, Azizan Bahari

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Problem: The research problem is lacking of model on social entrepreneurship that focus on Islamic perspective. Objective: The objective of this paper is to analyse the existing model on social entrepreneurship and to identify the research gap on Islamic perspective from existing models. Research Methodology: The research method used in this study is literature review and comparative analysis from 6 existing models of social entrepreneurship. Finding: The research finding shows that 6 existing models on social entrepreneurship has been analysed and it shows that the existing models on social entrepreneurship do not emphasize on Islamic perspective.

Keywords: social entrepreneurship, Islamic perspective, research gap, business management

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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Authors: Iyad A. A. Abusahloub

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This research aimed to measure the level of perception and application of Integrated Talent Management according to IBM standards, by the upper and middle categories in Palestinian government institutions in Gaza, using a descriptive-analytical method. Using a questionnaire based on the standards of the IBM Institute for Business Value, the researcher added a second section to measure the perception of integrated talent management, the sample was 248 managers. The SPSS package was used for statistical analysis. The results showed that government institutions in Gaza apply Integrated Talent Management according to IBM standards at a medium degree did not exceed 59.8%, there is weakness in the perception of integrated talent management at the level of 53.6%, and there is a strong correlation between (Integrated Talent Management) and (the perception of the integrated talent management) amounted to 92.9%, and 88.9% of the change in the perception of the integrated talent management is by (motivate and develop, deploy and manage, connect and enable, and transform and sustain) talents, and 11.1% is by other factors. Conclusion: This study concluded that the integrated talent management model presented by IBM with its six dimensions is an effective model to reach your awareness and understanding of talent management, especially that it must rely on at least four basic dimensions out of the six dimensions: 1- Stimulating and developing talent. 2- Organizing and managing talent. 3- Connecting with talent and empowering it. 4- Succession and sustainability of talent. Therefore, this study recommends the adoption of the integrated talent management model provided by IBM to any organization across the world, regardless of its specialization or size, to reach talent sustainability.

Keywords: HR, talent, talent management, IBM

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Authors: Natarajan Ramasamy, Gurulingamurthy Haralur, Ramesh Nivarthu, Nikhil Kumar Singha

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Elastomers are polymeric materials with varied backbone architectures ranging from linear to dendrimeric structures and wide varieties of monomeric repeat units. These elastomers show strongly viscous and weakly elastic when it is not cross-linked. But when crosslinked, based on the extent the properties of these elastomers can range from highly flexible to highly stiff nature. Lightly cross-linked systems are well studied and reported. Understanding the nature of highly cross-linked rubber based upon chemical structure and architecture is critical for varieties of applications. One of the critical parameters is cross-link density. In the current work, we have studied the highly cross-linked state of linear, lightly branched to star-shaped branched elastomers and determined the cross-linked density by using different models. Change in hardness, shift in Tg, change in modulus and swelling behavior were measured experimentally as a function of the extent of curing. These properties were analyzed using varied models to determine cross-link density. We used hardness measurements to examine cure time. Hardness to the extent of curing relationship is determined. It is well known that micromechanical transitions like Tg and storage modulus are related to the extent of crosslinking. The Tg of the elastomer in different crosslinked state was determined by DMA, and based on plateau modulus the crosslink density is estimated by using Nielsen’s model. Usually for lightly crosslinked systems, based on equilibrium swelling ratio in solvent the cross link density is estimated by using Flory–Rhener model. When it comes to highly crosslinked system, Flory-Rhener model is not valid because of smaller chain length. So models based on the assumption of polymer as a Non-Gaussian chain like 1) Helmis–Heinrich–Straube (HHS) model, 2) Gloria M.gusler and Yoram Cohen Model, 3) Barbara D. Barr-Howell and Nikolaos A. Peppas model is used for estimating crosslink density. In this work, correction factors are determined to the existing models and based upon it structure-property relationship of highly crosslinked elastomers was studied.

Keywords: dynamic mechanical analysis, glass transition temperature, parts per hundred grams of rubber, crosslink density, number of networks per unit volume of elastomer

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Authors: Kunihisa Kakumoto

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This technical paper is for the prototype of solar energy utilization for finding sustainable conditions. This model has been simulated under the climate conditions in Japan. At the beginning of the study, the solar model house was built up on site. And the concerned data was collected in this model house for several years. On the basis of these collected data, the concept on the solar community was built up. For the finding sustainable conditions, the amount of the solar energy generation and its reduction of carbon dioxide and the reduction of carbon dioxide by the green planting and the amount of carbon dioxide according to the normal daily life in the solar community and the amount of the necessary water for the daily life in the solar community and the amount of the water supply by the rainfall on-site were calculated. These all values were taken into consideration. The relations between each calculated result are shown in the expression of inequality. This solar community and its consideration for finding sustainable conditions can be one prototype to do the feasibility study for our life in the future

Keywords: carbon dioxide, green planting, smart city, solar community, sustainable condition, water activity

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Authors: Li-Ching Chen

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The case-control design has been widely applied in clinical and epidemiological studies to investigate the association between risk factors and a given disease. The retrospective design can be easily implemented and is more economical over prospective studies. To adjust effects for confounding factors, methods such as stratification at the design stage and may be adopted. When some major confounding factors are difficult to be quantified, a matching design provides an opportunity for researchers to control the confounding effects. The matching effects can be parameterized by the intercepts of logistic models and the conditional logistic regression analysis is then adopted. This study demonstrates an information-matrix-based goodness-of-fit statistic to test the validity of the logistic regression model for matched case-control data. The asymptotic null distribution of this proposed test statistic is inferred. It needs neither to employ a simulation to evaluate its critical values nor to partition covariate space. The asymptotic power of this test statistic is also derived. The performance of the proposed method is assessed through simulation studies. An example of the real data set is applied to illustrate the implementation of the proposed method as well.

Keywords: conditional logistic model, goodness-of-fit, information matrix, matched case-control studies

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Authors: Bolawole F. Ogunbodede, Mokolade Johnson, Adetunji Adejumo

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High population growth rate, reactive infrastructure provision, inability of physical planning to cope with developmental pace are responsible for waste water crisis in the Lagos Metropolis. Septic tank is still the most prevalent waste-water holding system. Unfortunately, there is a dearth of septage treatment infrastructure. Public waste-water treatment system statistics relative to the 23 million people in Lagos State is worrisome. 1.85 billion Cubic meters of wastewater is generated on daily basis and only 5% of the 26 million population is connected to public sewerage system. This is compounded by inadequate budgetary allocation and erratic power supply in the last two decades. This paper explored community participatory waste-water management alternative at Oworonshoki Municipality in Lagos. The study is underpinned by decentralized Waste-water Management systems in built-up areas. The initiative accommodates 5 step waste-water issue including generation, storage, collection, processing and disposal through participatory decision making in two Oworonshoki Community Development Association (CDA) areas. Drone assisted mapping highlighted building footage. Structured interviews and focused group discussion of land lord associations in the CDA areas provided collaborator platform for decision-making. Water stagnation in primary open drainage channels and natural retention ponds in framing wetlands is traceable to frequent of climate change induced tidal influences in recent decades. Rise in water table resulting in septic-tank leakage and water pollution is reported to be responsible for the increase in the water born infirmities documented in primary health centers. This is in addition to unhealthy dumping of solid wastes in the drainage channels. The effect of uncontrolled disposal system renders surface waters and underground water systems unsafe for human and recreational use; destroys biotic life; and poisons the fragile sand barrier-lagoon urban ecosystems. Cluster decentralized system was conceptualized to service 255 households. Stakeholders agreed on public-private partnership initiative for efficient wastewater service delivery.

Keywords: health, infrastructure, management, septage, well-being

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Authors: Farwa Rizvi, Joanne Williams, Humaira Maheen, Elizabeth Hoban

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There is an increase in risky sexual behavior and unsafe sex in adolescent girls and young women aged 15 to 24 years in Cambodia, which negatively affects their reproductive health by increasing the risk of contracting sexually transmitted infections and unintended pregnancies. Risky sexual behavior includes ‘having sex at an early age, having multiple sexual partners, having sex while under the influence of alcohol or drugs, and unprotected sexual behaviors’. A systematic review of quantitative research conducted in Cambodia was undertaken, using the theoretical framework of the Social Ecological Model to identify the personal, social and cultural factors associated with risky sexual behavior and unsafe sex in young Cambodian women. PRISMA guidelines were used to search databases including Medline Complete, PsycINFO, CINAHL Complete, Academic Search Complete, Global Health, and Social Work Abstracts. Additional searches were conducted in Science Direct, Google Scholar and in the grey literature sources. A risk-of-bias tool developed explicitly for the systematic review of cross-sectional studies was used. Summary item on the overall risk of study bias after the inter-rater response showed that the risk-of-bias was high in two studies, moderate in one study and low in one study. The search strategy included a combination of subject terms and free text terms. The medical subject headings (MeSH) terms included were; contracept* or ‘birth control’ or ‘family planning’ or pregnan* or ‘safe sex’ or ‘protected intercourse’ or ‘unprotected intercourse’ or ‘protected sex’ or ‘unprotected sex’ or ‘risky sexual behaviour*’ or ‘abort*’ or ‘planned parenthood’ or ‘unplanned pregnancy’ AND ( barrier* or obstacle* or challenge* or knowledge or attitude* or factor* or determinant* or choic* or uptake or discontinu* or acceptance or satisfaction or ‘needs assessment’ or ‘non-use’ or ‘unmet need’ or ‘decision making’ ) AND Cambodia*. Initially, 300 studies were identified by using key words and finally, four quantitative studies were selected based on the inclusion criteria. The four studies were published between 2010 and 2016. The study participants ranged in age from 10-24 years, single or married, with 3 to 10 completed years of education. The mean age at sexual debut was reported to be 18 years. Using the perspective of the Social Ecological Model, risky sexual behavior was associated with individual-level factors including young age at sexual debut, low education, unsafe sex under the influence of alcohol and substance abuse, multiple sexual partners or transactional sex. Family level factors included living away from parents, orphan status and low levels of family support. Peer and partner level factors included peer delinquency and lack of condom use. Low socioeconomic status at the society level was also associated with risky sexual behaviour. There is scant research on sexual and reproductive health of adolescent girls and young women in Cambodia. Individual, family and social factors were significantly associated with risky sexual behaviour. More research is required to inform potential preventive strategies and policies that address young women’s sexual and reproductive health.

Keywords: adolescents, high-risk sex, sexual activity, unplanned pregnancies

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Authors: Arun Jyothi Bheemagani, Chakrapani Pullagummi, Anupalli Roja Rani

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Exploration of the chemical constituents of the plants and pharmacological screening may provide us the basis for the development of novel agents. Plants have provided us some of the very important life saving drugs used in the modern medicine. The aim of our work was to screen the phytochemical constituents and antimicrobial and antioxidant activities of methanol extract of leaves of Annona cherimola Mill plant from Tirumala forest, Tirupathi. It was originally called Chirimuya by the Inca people who lived where it was growing in the Andes of South America, is an edible fruit-bearing species of the genus Annona from the family Annonaceae. Annona cherimola Mill is a multipurpose tree with edible fruits and is one of the sources of the medicinal products. The antibacterial activity was measured by agar well diffusion method; the diameter of the zone of bacterial growth inhibition was measured after incubation of plates. The inhibitory effect was studied against the pathogenic bacteria (Klebsiella pneumonia, Bacillus subtilis, Staphylococcus aureus and Escherichia coli (E. coli). Antioxidant assays were also performed for the same extracts by spectrophotometric methods using known standard antioxidants as reference. The studied plant extracts were found to be very effective against the pathogenic microorganisms tested. The methanolic extract of Annona cherimola Mill from showed maximum activity against Escherichia coli and Staphylococcus aureus and the least concentration required showing the activity was 0.5mg/ml. Phytochemical screening of the plants revealed the presence of flavonoids, alkaloids, steroids and carbohydrates. Good presence of antioxidants was also found in the methanolic extracts.

Keywords: annona cherimola, phytochemicals, antioxidant and antibacterial activity, methanol extract

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Authors: Jacques Lamarche, Juhani Dickinson

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This paper introduces a computational model of a Grammar as Logic of Labeling (GLL), where the lexical primitives of morphosyntax are phonological matrixes, the form of words, understood as labels that apply to realities (or targets) assumed to be outside of grammar altogether. The hypothesis is that even though a lexical label relates to its target arbitrarily, this label in a complex (constituent) label is part of a labeling pattern which, depending on its value (i.e., N, V, Adj, etc.), imposes language-specific restrictions on what it targets outside of grammar (in the world/semantics or in cognitive knowledge). Lexical forms categorized as nouns, verbs, adjectives, etc., are effectively targets of labeling patterns in use. The paper illustrates GLL through a computer model of basic patterns in English NPs. A constituent label is a binary object that encodes: i) alignment of input forms so that labels occurring at different points in time are understood as applying at once; ii) endocentric structuring - every grammatical constituent has a head label that determines the target of the constituent, and a limiter label (the non-head) that restricts this target. The N or A values are restricted to limiter label, the two differing in terms of alignment with a head. Consider the head initial DP ‘the dog’: the label ‘dog’ gets an N value because it is a limiter that is evenly aligned with the head ‘the’, restricting application of the DP. Adapting a traditional analysis of ‘the’ to GLL – apply label to something familiar – the DP targets and identifies one reality familiar to participants by applying to it the label ‘dog’ (singular). Consider next the DP ‘the large dog’: ‘large dog’ is nominal by even alignment with ‘the’, as before, and since ‘dog’ is the head of (head final) ‘large dog’, it is also nominal. The label ‘large’, however, is adjectival by narrow alignment with the head ‘dog’: it doesn’t target the head but targets a property of what dog applies to (a property or value of attribute). In other words, the internal composition of constituents determines that a form targets a property or a reality: ‘large’ and ‘dog’ happen to be valid targets to realize this constituent. In the presentation, the computer model of the analysis derives the 8 possible sequences of grammatical values with three labels after the determiner (the x y z): 1- D [ N [ N N ]]; 2- D [ A [ N N ] ]; 3- D [ N [ A N ] ]; 4- D [ A [ A N ] ]; 5- D [ [ N N ] N ]; 5- D [ [ A N ] N ]; 6- D [ [ N A ] N ] 7- [ [ N A ] N ] 8- D [ [ Adv A ] N ]. This approach that suggests that a computer model of these grammatical patterns could be used to construct ontologies/knowledge using speakers’ judgments about the validity of lexical meaning in grammatical patterns.

Keywords: syntactic theory, computational linguistics, logic and grammar, semantics, knowledge and grammar

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

Abstract:

Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

Abstract:

In an urban area the determination of transportation routes should be planned so as to minimize the provoked pollution taking into account the cost of such routes. In the sequel these routes are cited as pollution routes. The transportation network is expressed by a weighted graph G= (V, E, D, P) where every vertex represents a location to be served and E contains unordered pairs (edges) of elements in V that indicate a simple road. The distances/cost and a weight that depict the provoked air pollution by a vehicle transition at every road are assigned to each road as well. These are the items of set D and P respectively. Furthermore the investigated pollution routes must not exceed predefined corresponding values concerning the route cost and the route pollution level during the vehicle transition. In this paper we present an algorithm that generates such routes in order that the decision maker selects the most appropriate one.

Keywords: bi-criteria, pollution, shortest paths, computation

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Authors: Godwin Chigozie Okpara, William Chimee Nwaoha

Abstract:

The paper set out to stress on how financial inclusion index could be calculated and also investigated the impact of inclusive finance on inclusive growth in an emerging economy. In the light of these objectives, chi-wins method was used to calculate indexes of financial inclusion while co-integration and error correction model were used for evaluation of the impact of financial inclusion on inclusive growth. The result of the analysis revealed that financial inclusion while having a long-run relationship with GDP growth is an insignificant function of the growth of the economy. The speed of adjustment is correctly signed and significant. On the basis of these results, the researchers called for tireless efforts of government and banking sector in promoting financial inclusion in developing countries.

Keywords: chi-wins index, co-integration, error correction model, financial inclusion

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Authors: Kyaw Zin Htut

Abstract:

In this article, the synthesis of the efficiency of intelligent diagnostic system in the aircraft measuring devices is described. The technology developments of the diagnostic system are considered based on the model errors of the gyro instruments, which are used to measure the parameters of the aircraft. The synthesis of the diagnostic intelligent system is considered on the example of the problem of assessment and forecasting errors of the gyroscope devices on the onboard aircraft. The result of the system is to detect of faults of the aircraft measuring devices as well as the analysis of the measuring equipment to improve the efficiency of its work.

Keywords: diagnostic, dynamic system, errors of gyro instruments, model errors, assessment, prognosis

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Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

Abstract:

Recognition of human activities from sensor data is an active research area, and the main objective is to obtain a high recognition rate. In this work, we propose a recognition system based on expert systems. The proposed system makes the recognition based on the objects, object states, and gestures, taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions, and the activity). This work focuses on complex activities which are decomposed into simple easy to recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

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Authors: Chiao-Chen Chang, Yang-Chieh Chin

Abstract:

Social media has created a change in the way the network community is clustered, especially from the location of the community, from the original virtual space to the intertwined network, and thus the communication between people will change from face to face communication to social media-based communication model. However, social media users who have had a fixed engagement may have an intention to switch to another service provider because of the emergence of new forms of social media. For example, some of Facebook or Twitter users switched to Instagram in 2014 because of social media messages or image overloads, and users may seek simpler and instant social media to become their main social networking tool. This study explores the impact of system features overload, information overload, social monitoring concerns, problematic use and privacy concerns as the antecedents on social media fatigue, dissatisfaction, and alternative attractiveness; further influence social media switching. This study also uses the online questionnaire survey method to recover the sample data, and then confirm the factor analysis, path analysis, model fit analysis and mediating analysis with the structural equation model (SEM). Research findings demonstrated that there were significant effects on multiple paths. Based on the research findings, this study puts forward the implications of theory and practice.

Keywords: social media, switching, social media fatigue, alternative attractiveness

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Authors: Eyad Almaita

Abstract:

In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

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Authors: Sekou Kangoye, Alexis Todoskoff, Mihaela Barreau

Abstract:

Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that is highly recommended or required for safety-critical software coverage. Therefore, many testing standards include this criterion and require it to be satisfied at a particular level of testing (e.g. validation and unit levels). However, an important amount of time is needed to meet those requirements. In this paper we propose to automate MC/DC test data generation. Thus, we present an approach to automatically generate MC/DC test data, from software module description written over a dedicated language. We introduce a new merging approach that provides high MC/DC coverage for the description, with only a little number of test cases.

Keywords: domain-specific language, MC/DC, test data generation, safety-critical software coverage

Procedia PDF Downloads 448