Search results for: data infrastructure

Authors: Komlan Sedzro

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We apply the non-parametric, unconditional, hyperbolic order-α quantile estimator to appraise the relative efficiency of Microfinance Institutions in Africa in terms of outreach. Our purpose is to verify if these institutions, which must constantly try to strike a compromise between their social role and financial sustainability are operationally efficient. Using data on African MFIs extracted from the Microfinance Information eXchange (MIX) database and covering the 2004 to 2006 periods, we find that more efficient MFIs are also the most profitable. This result is in line with the view that social performance is not in contradiction with the pursuit of excellent financial performance. Our results also show that large MFIs in terms of asset and those charging the highest fees are not necessarily the most efficient.

Keywords: data envelopment analysis, microfinance institutions, quantile estimation of efficiency, social and financial performance

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Authors: Rindra Rantoson, Hichem Nouira, Nabil Anwer, Charyar Mehdi-Souzani

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Multiple measurements by means of various data acquisition systems are generally required to measure the shape of freeform workpieces for accuracy, reliability and holisticity. The obtained data are aligned and fused into a common coordinate system within a registration technique involving coarse and fine registrations. Standardized iterative methods have been established for fine registration such as Iterative Closest Points (ICP) and its variants. For coarse registration, no conventional method has been adopted yet despite a significant number of techniques which have been developed in the literature to supply an automatic rough matching between data sets. Two main issues are addressed in this paper: the coarse registration and the fine registration. For coarse registration, two novel automated methods based on the exploitation of discrete curvatures are presented: an enhanced Hough Transformation (HT) and an improved Ransac Transformation. The use of curvature features in both methods aims to reduce computational cost. For fine registration, a new variant of ICP method is proposed in order to reduce registration error using curvature parameters. A specific distance considering the curvature similarity has been combined with Euclidean distance to define the distance criterion used for correspondences searching. Additionally, the objective function has been improved by combining the point-to-point (P-P) minimization and the point-to-plane (P-Pl) minimization with automatic weights. These ones are determined from the preliminary calculated curvature features at each point of the workpiece surface. The algorithms are applied on simulated and real data performed by a computer tomography (CT) system. The obtained results reveal the benefit of the proposed novel curvature-based registration methods.

Keywords: discrete curvature, RANSAC transformation, hough transformation, coarse registration, ICP variant, point-to-point and point-to-plane minimization combination, computer tomography

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Authors: Radhwane Boudjelthia

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The most recent earthquakes that occurred in the world and particularly in Algeria, have killed thousands of people and severe damage. The example that is etched in our memory is the last earthquake in the regions of Boumerdes and Algiers (Boumerdes earthquake of May 21, 2003). For all the actors involved in the building process, the earthquake is the litmus test for construction. The goal we set ourselves is to contribute to the implementation of a thoughtful approach to the seismic protection of structures. For many engineers, the most conventional approach protection works (buildings and bridges) the effects of earthquakes is to increase rigidity. This approach is not always effective, especially when there is a context that favors the phenomenon of resonance and amplification of seismic forces. Therefore, the field of earthquake engineering has made significant inroads among others catalyzed by the development of computational techniques in computer form and the use of powerful test facilities. This has led to the emergence of several innovative technologies, such as the introduction of special devices insulation between infrastructure and superstructure. This approach, commonly known as "seismic isolation" to absorb the significant efforts without the structure is damaged and thus ensuring the protection of lives and property. In addition, the restraints to the construction by the ground shaking are located mainly at the supports. With these moves, the natural period of construction is increasing, and seismic loads are reduced. Thus, there is an attenuation of the seismic movement. Likewise, the insulation of the base mechanism may be used in combination with earthquake dampers in order to control the deformation of the insulation system and the absolute displacement of the superstructure located above the isolation interface. On the other hand, only can use these earthquake dampers to reduce the oscillation amplitudes and thus reduce seismic loads. The use of damping devices represents an effective solution for the rehabilitation of existing structures. Given all these acceleration reducing means considered passive, much research has been conducted for several years to develop an active control system of the response of buildings to earthquakes.

Keywords: earthquake, building, seismic forces, displacement, resonance, response

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Authors: S. Fahiminiya, J. Nadaf, F. Rauch, L. Jerome-Majewska, J. Majewski

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Background: Sequencing of protein coding regions of human genome (Whole Exome Sequencing; WES), has demonstrated a great success in the identification of causal mutations for several rare genetic disorders in human. Generally, most of WES studies have focused on rare variants in coding exons and splicing-sites where missense substitutions lead to the alternation of protein product. Although focusing on this category of variants has revealed the mystery behind many inherited genetic diseases in recent years, a subset of them remained still inconclusive. Here, we present the result of our WES studies where analyzing only rare variants in coding regions was not conclusive but further investigation revealed the involvement of non-coding variants and copy number variations (CNV) in etiology of the diseases. Methods: Whole exome sequencing was performed using our standard protocols at Genome Quebec Innovation Center, Montreal, Canada. All bioinformatics analyses were done using in-house WES pipeline. Results: To date, we successfully identified several disease causing mutations within gene coding regions (e.g. SCARF2: Van den Ende-Gupta syndrome and SNAP29: 22q11.2 deletion syndrome) by using WES. In addition, we showed that variants in non-coding regions and CNV have also important value and should not be ignored and/or filtered out along the way of bioinformatics analysis on WES data. For instance, in patients with osteogenesis imperfecta type V and in patients with glucocorticoid deficiency, we identified variants in 5'UTR, resulting in the production of longer or truncating non-functional proteins. Furthermore, CNVs were identified as the main cause of the diseases in patients with metaphyseal dysplasia with maxillary hypoplasia and brachydactyly and in patients with osteogenesis imperfecta type VII. Conclusions: Our study highlights the importance of considering non-coding variants and CNVs during interpretation of WES data, as they can be the only cause of disease under investigation.

Keywords: whole exome sequencing data, non-coding variants, copy number variations, rare diseases

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Authors: Teguh R. Hakim, Frenny F. F. Kairupan, Alberta M. Mantiri

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The face of the coastal city is generally the same as other cities face showing the dualistic, traditional and modern, rural and urbanity, planned and unplanned, slum and high quality. Manado city is located on the northern coastal areas of the island of Sulawesi, Indonesia. Manado city is located on the northern coastal areas of the island of Sulawesi, Indonesia. Urban environmental problems ever occurred in this city, which is the impact of dualistic urban. Overcrowding, inadequate infrastructure, and limited human resources become the main cause of untidiness the coastal settlements in Malalayang. This has an impact on the activities of social, economic, public health level in the environment of coastal City of Manado, Malalayang. This is becoming a serious problem which must be tackled jointly by the government, private parties, and the community. Community-based settlement environment setup, into one solution to realize the city's coastal settlements livable. As for this research aims to analyze the involvement of local communities in arrangements of the settlement. The participatory approach of the model used in this study. Its application is mainly at macro and meso-scale (region, city, and environment) or community architecture. Model participatory approach leads more operational research approach to find a solution/answer to the problems of settlement. The participatory approach is a model for research that involves researchers and society as an object at the same time the subject of research, which in the process in addition to researching also developed other forms of participation in the design and build together. The expected results of this study were able to provide education to the community about environmental and set up a livable settlement for the sake of improving the quality of life. The study also becomes inputs to the government in applying the pattern of development that will be implemented in the future.

Keywords: arrangements the coastal environment, community participation, urban environmental problems, livable settlement

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Authors: Sun-Ki Hong, Ki-Seok Kim, Yong-Ho Jo

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Lots of motors have been being used in industry. Therefore many researchers have studied about the failure diagnosis of motors. In this paper, the effect of measuring environment for diagnosis of gear fault connected to a motor shaft is studied. The fault diagnosis is executed through the comparison of normal gear and abnormal gear. The measured FFT data are compared with the normal data and analyzed for q-axis current, noise and vibration. For bad and good environment, the diagnosis results are compared. From these, it is shown that the bad measuring environment may not be able to detect exactly the motor gear fault. Therefore it is emphasized that the measuring environment should be carefully prepared.

Keywords: motor fault, diagnosis, FFT, vibration, noise, q-axis current, measuring environment

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Authors: Walter E. Allen, Robert D. Murray

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Many large transit agencies have adopted RFID technology and electronic automatic fare collection (AFC) or smart card systems, but small and rural agencies remain tied to obsolete manual, cash-based fare collection. Small countries or transit agencies can benefit from the implementation of smart card AFC technology with the promise of increased passenger convenience, added passenger satisfaction and improved agency efficiency. For transit agencies, it reduces revenue loss, improves passenger flow and bus stop data. For countries, further implementation into security, distribution of social services or currency transactions can provide greater benefits. However, small countries or transit agencies cannot afford expensive proprietary smart card solutions typically offered by the major system suppliers. Deployment of Contactless Fare Media System (CFMS) Standard eliminates the proprietary solution, ultimately lowering the cost of implementation. Acumen Building Enterprise, Inc. chose the Yuma County Intergovernmental Public Transportation Authority (YCIPTA) existing proprietary YCAT smart card system to implement CFMS. The revised system enables the purchase of fare product online with prepaid debit or credit cards using the Payment Gateway Processor. Open and interoperable smart card standards for transit have been developed. During the 90-day Pilot Operation conducted, the transit agency gathered the data from the bus AcuFare 200 Card Reader, loads (copies) the data to a USB Thumb Drive and uploads the data to the Acumen Host Processing Center for consolidation of the data into the transit agency master data file. The transition from the existing proprietary smart card data format to the new CFMS smart card data format was transparent to the transit agency cardholders. It was proven that open standards and interoperability design can work and reduce both implementation and operational costs for small transit agencies or countries looking to expand smart card technology. Acumen was able to avoid the implementation of the Payment Card Industry (PCI) Data Security Standards (DSS) which is expensive to develop and costly to operate on a continuing basis. Due to the substantial additional complexities of implementation and the variety of options presented to the transit agency cardholder, Acumen chose to implement only the Directed Autoload. To improve the implementation efficiency and the results for a similar undertaking, it should be considered that some passengers lack credit cards and are averse to technology. There are more than 1,300 small and rural agencies in the United States. This grows by 10 fold when considering small countries or rural locations throughout Latin American and the world. Acumen is evaluating additional countries, sites or transit agency that can benefit from the smart card systems. Frequently, payment card systems require extensive security procedures for implementation. The Project demonstrated the ability to purchase fare value, rides and passes with credit cards on the internet at a reasonable cost without highly complex security requirements.

Keywords: automatic fare collection, near field communication, small transit agencies, smart cards

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Authors: Marc Sader, Michiel Stock, Bernard De Baets

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Considering a large amount of adsorption data of adsorbate gases on adsorbent materials in literature, it is interesting to predict such adsorption data without experimentation. A quantitative structure-activity relationship (QSAR) is developed to correlate molecular characteristics of gases and existing knowledge of materials with their respective adsorption properties. The application of Random Forest, a machine learning method, on a set of adsorption isotherms at a wide range of partial pressures and concentrations is studied. The predicted adsorption isotherms are fitted to several adsorption equations to estimate the adsorption properties. To impute the adsorption properties of desired gases on desired materials, leave-one-out cross-validation is employed. Extensive experimental results for a range of settings are reported.

Keywords: adsorption, predictive modeling, QSAR, random forest

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Authors: L. Siva Rama Krishna, Sriram Venkatesh, M. Sastish Kumar, M. Uma Maheswara Chary

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Rapid Prototyping (RP) is a technology that produces models and prototype parts from 3D CAD model data, CT/MRI scan data, and model data created from 3D object digitizing systems. There are several RP process like Stereolithography (SLA), Solid Ground Curing (SGC), Selective Laser Sintering (SLS), Fused Deposition Modelling (FDM), 3D Printing (3DP) among them SLS and FDM RP processes are used to fabricate pattern of custom cranial implant. RP technology is useful in engineering and biomedical application. This is helpful in engineering for product design, tooling and manufacture etc. RP biomedical applications are design and development of medical devices, instruments, prosthetics and implantation; it is also helpful in planning complex surgical operation. The traditional approach limits the full appreciation of various bony structure movements and therefore the custom implants produced are difficult to measure the anatomy of parts and analyse the changes in facial appearances accurately. Cranioplasty surgery is a surgical correction of a defect in cranial bone by implanting a metal or plastic replacement to restore the missing part. This paper aims to do a comparative study on the dimensional error of CAD and SLS RP Models for reconstruction of cranial defect by comparing the virtual CAD with the physical RP model of a cranial defect.

Keywords: rapid prototyping, selective laser sintering, cranial defect, dimensional error

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Authors: Rachida Benabbou, Sang Hun Park, Hee Chung Lee

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The world’s population is increasing with unprecedented speed, leading to fast growing urbanization pace. Cities since the Industrial revolution had evolved to fit the growing demand on infrastructure, roads, transportation, and housing. Through this evolution, cities had grown into grey, polluted, and vehicle-oriented urban areas with a significant lack of green spaces. Consequently, we ended up with low quality of life for citizens. Therefore, many cities, nowadays, are revising the way we think urbanism and try to grow into more livable and citizen-friendly, by creating change from the inside out. Thus, cities are trying to bring back nature in its crowded grey centers and regenerate many urban areas as green public spaces not only as a way to give new breath to the city, but also as a way to create change either in the environmental, social and economic levels. The city of Seoul is one of the fast growing global cities. Its population is over 12 million and it is expected to continue to grow to a point where the quality of life may seriously deteriorate. As most green areas in Seoul are located in the suburbs in form of mountains, the city’s urban areas suffer from lack of accessible green spaces in a walking distance. Understanding the gravity and consequences of this issue, Seoul city is undergoing major changes. Many of its projects are oriented to be green public spaces where citizens can enjoy the public life in healthy outdoors. The aim of this paper is to explore the results of urban conversions into green public spaces. Starting with different locations, nature, size, and scale, these conversions can lead to significant change in the surrounding areas, thus can be used as an efficient tool of regeneration for urban areas. Through a comparative analysis of three different types of urban conversions projects in the city of Seoul, we try to show the positive urban influence of the outcomes, in order to encourage cities to use green spaces as a strategic tool for urban regeneration and redevelopment.

Keywords: urban conversion, green public space, change, urban regeneration

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Authors: Dalia Rimawi, Walid Salameh, Amal Al-Omari, Hadeel AbdelKhaleq

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Predication of Survival time of patients with cancer, is a core factor that influences oncologist decisions in different aspects; such as offered treatment plans, patients’ quality of life and medications development. For a long time proportional hazards Cox regression (ph. Cox) was and still the most well-known statistical method to predict survival outcome. But due to the revolution of data sciences; new predication models were employed and proved to be more flexible and provided higher accuracy in that type of studies. Artificial neural network is one of those models that is suitable to handle time to event predication. In this study we aim to compare ph Cox regression with artificial neural network method according to data handling and Accuracy of each model.

Keywords: Cox regression, neural networks, survival, cancer.

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Authors: Al Omari Mohammed Ahmed

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This paper focuses on Maximum Likelihood Estimator with Covariate. Covariates are incorporated into the Weibull model. Under this regression model with regards to maximum likelihood estimator, the parameters of the covariate, shape parameter, survival function and hazard rate of the Weibull regression distribution with right censored data are estimated. The mean square error (MSE) and absolute bias are used to compare the performance of Weibull regression distribution. For the simulation comparison, the study used various sample sizes and several specific values of the Weibull shape parameter.

Keywords: weibull regression distribution, maximum likelihood estimator, survival function, hazard rate, right censoring

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Authors: Forrest Kaatz, Adhemar Bultheel

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Au-Cu and Pt-M (M = Fe, Co, and Ni) nanocluster alloys are currently being investigated worldwide by many researchers for their interesting catalytic and nanophase properties. The low-temperature behavior of the phase diagrams is not well understood for alloys with nanometer sizes and shapes. These systems have similar bulk phase diagrams with the L12 (Au3Cu, Pt3M, AuCu3, and PtM3) structurally ordered intermetallics and the L10 structure for the AuCu and PtM intermetallics. We consider three models for low temperature ordering in the phase diagrams of Au–Cu and Pt–M nanocluster alloys. These models are valid for sizes ~ 5 nm and approach bulk values for sizes ~ 20 nm. We study the phase transition in nanoclusters with cubic, octahedral, and cuboctahedral shapes, covering the compositions of interest. These models are based on studying the melting temperatures in nanoclusters using the regular solution, mixing model for alloys. Experimentally, it is extremely challenging to determine thermodynamic data on nano–sized alloys. Reasonable agreement is found between these models and recent experimental data on nanometer clusters in the Au–Cu and Pt–M nanophase systems. From our data, experiments on nanocubes about 5 nm in size, of stoichiometric AuCu and PtM composition, could help differentiate between the models. Some available evidence indicates that ordered intermetallic nanoclusters have better catalytic properties than disordered ones. We conclude with a discussion of physical mechanisms whereby ordering could improve the catalytic properties of nanocluster alloys.

Keywords: catalytic reactions, gold nanoalloys, phase transitions, platinum nanoalloys

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Authors: Nadiah Mohamad, Wan Samiati Andriana Wan Mohd Daud, M. Suhaimi Tohid, Mohd Fazli Othman, Mohamad Rizal Salleh

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This is a collaborative project of the mural art between The Department of Fine Art from Universiti Teknologi MARA (UiTM) and Petronas Dagangan Berhad (PDB), the most leading retailer and marketer of downstream oil and gas products in Malaysia. Five different states in the Peninsular of Malaysia that has been identified in showcasing the National Identity of Malaysia at each Petronas gas station, this also includes the Air Keroh in Melaka, Pasir Pekan in Kelantan, Pontian in Johor, Simpang Pulai in Perak, and also Wakaf Bharu in Terengganu. This project is to analyze the element of national identity that has been demonstrated at the Petronas's Mural. The ultimate aim of the mural is to let the community and local people to be aware about what Malaysians are consists and proud of and how everyone is able to connect with the idea through visual art. The method that is being explained in this research is by using visual data through research and also self-experience in collecting the visual data in identifying what images is considered as the national identity and idea development and visual analysis is being transferred based upon the visual data collection. In this stage, elements and principles of design will be the key in highlighting what is necessary for a work of art. In conclusion, visual image of the National Identity of Malaysia is able to connect to the audience from local and also to the people from outside the country to learn and understand the beauty and diversity of Malaysia as a unique country with art through the wall of five Petronas gas station.

Keywords: community, fine art, mural art, national identity

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Hans Schumann, Colin Domnauer, Louis Rosenberg

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In this study, machine learning techniques were deployed on real-time human swarm data to forecast the likelihood of outcomes for English Premier League matches in the 2020/21 season. These techniques included ensemble models in combination with neural networks and were tested against an industry standard of Vegas Oddsmakers. Predictions made from the collective intelligence of human swarm participants managed to achieve a positive return on investment over a full season on matches, empirically proving the usefulness of a new artificial intelligence valuing human instinct and intelligence.

Keywords: artificial intelligence, data science, English Premier League, human swarming, machine learning, sports betting, swarm intelligence

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Authors: Mardi Falck, André Theron

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Traffic congestion on the Northern side of Table Bay is a major problem. In Gauteng, the implementation of the Gautrain between Pretoria and Johannesburg, solved their traffic congestion. In 2002 two entrepreneurs endeavoured to implement a hovercraft ferry service across the bay from Table View to the Port of Cape Town. However, the EIA process proved that disgruntled residents from the area did not agree with their location for a launch site. 17 years later the traffic problem has not gone away, but instead the congestion has increased. While property prices in the City Bowl of Cape Town are ever increasing, people tend to live more on the outskirts of the CBD and commute to work. This means more vehicles on the road every day and the public transport services cannot keep up with the demand. For this reason, the study area of the previous hovercraft plans is being extended further North. The study’s aim is thus to determine the feasibility of a launch site North of Bloubergstrand to launch and receive a public transport ferry across Table Bay. The feasibility is being established by researching ferry services across the world and on what makes them successful. Different types of ferries and their operational capacities in terms of weather and waves are researched and by establishing the offshore and nearshore wind and wave climate for the area, an appropriate protected launch site is determined. It was concluded that travel time could potentially be halved. A hovercraft proved to be the most feasible ferry type, because it does not require a conventional harbour. Other types of vessels require a protected launch site because of the wave climate. This means large breakwaters that influence the cost substantially. The Melkbos Cultural Centre proved to be the most viable option for the location of the launch site, because it already has buildings and infrastructure. It is recommended that, if a harbour is chosen for the proposed ferry service, it could be used for more services like fishing, eco-tourism and leisure. Further studies are recommended to optimise the feasibility of such a harbour.

Keywords: Cape Town, ferry, public, Table Bay

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Authors: Lavanya Dharmendran, Shenuka Singh, Sona Baburathanam

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The aim of the study is to understand the level of awareness in a community of a specific region of Kuwait regarding oral cancer and its screening methods so as to enhance the uptake of oral cancer screening methods. This is a cross-sectional study comprising 100 adult participants residing in the governate of Farwaniya, Kuwait. Participants of above 18 years of both genders will be selected using convenience sampling. Data collection includes the administration of a self-administered questionnaire. The questionnaire comprises three sections, each section assessing the knowledge, attitudes and practices of the participants’ opinions about oral cancer and screening methods. Data will be analyzed using Humphris Oral Cancer Knowledge Scale. Inferential statistics will be done using Chi-Square or Fisher’s exact test for categorical data. A level of p<.05 will be established as being significant. All ethical considerations, such as respect for personal confidentiality and informed consent, will be applied in this study. This study revealed that although respondents were aware of the term oral cancer, more than half of the study participants were unaware of the symptoms associated with this condition. Smoking and alcohol were identified as risk factors for oral cancer, but the majority of participants did not identify the Human Papilloma Virus (HPV) as an added risk factor. This suggests a greater need for dental practitioners to include educational strategies in routine dental visits to ensure greater awareness of oral cancer.

Keywords: oral cancer, oral screening, oral public health, oral health

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Authors: Nattabhorn Leamcharaskul

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This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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Authors: Sajid Aman

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Jobs in the banking sector in Pakistan are perceived as very tough, due to which employee turnover is very high. However, the managerial role is very important in influencing employees’ attitudes toward their turnout. This paper explores the manager’s role in influencing employees’ effectiveness on the job. The paper adopted a pragmatic approach by combining both qualitative and quantitative data. The study employed an exploratory sequential strategy under a mixed-method research design. Qualitative data was analyzed using thematic analysis. Five major themes, such as the manager’s attitude towards employees, his leadership style, listening to employee’s personal problems, provision of personal loans without interest and future career prospects, emerged as key factors increasing employee’s effectiveness in the banking sector. The quantitative data revealed that a manager’s attitude, leadership style, availability to listen to employees’ personal problems, and future career prospects and listening to employee’s personal problems are strongly associated with employees’ effectiveness at the job. However, personal loan without interest was noted as having no significant association with employee’s effectiveness at the job. The study concludes manager’s role is more important in the effectiveness of the employees at their job in the banking sector. It is suggested that managers should have a positive attitude towards employees and give time to listening to employee’s problems, even personal ones.

Keywords: banking sector, employee’s effectiveness, manager’s role, leadership style

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Authors: A. Benatiallah, D. Benatiallah, F. Abaidi, B. Nasri, A. Harrouz, S. Mansouri

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The region of Adrar is located in the south-western Algeria and covers a total area of 443.782 km², occupied by a population of 432,193 inhabitants. The main activity of population is agriculture, mainly based on the date palm cultivation occupies a total area of 23,532 ha. Adrar region climate is a continental desert characterized by a high variation in temperature between months (July, August) it exceeds 48°C and coldest months (December, January) with 16°C. Rainfall is very limited in frequency and volume with an aridity index of 4.6 to 5 which corresponds to a type of arid climate. Geologically Adrar region is located on the edge North West and is characterized by a Precambrian basement cover stolen sedimentary deposit of Phanerozoic age transgressive. The depression is filled by Touat site Paleozoic deposits (Cambrian to Namurian) of a vast sedimentary basin extending secondary age of the Saharan Atlas to the north hamada Tinhirt Tademaït and the plateau of south and Touat Gourara west to Gulf of Gabes in the Northeast. In this work we have study geothermal potential of Adrar region from the borehole data eatable in various sites across the area of 400,000 square kilometres; from these data we developed a GIS (Adrar_GIS) that plots data on the various points and boreholes in the region specifying information on available geothermal potential has variable depths.

Keywords: sig, geothermal, potenteil, temperature

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Authors: Liliana Rusu

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The goal of the proposed work is to provide a more comprehensive picture of the wind and wave climate in the Romanian nearshore, using the results provided by numerical models. The Romanian coastal environment is located in the western side of the Black Sea, the more energetic part of the sea, an area with heavy maritime traffic and various offshore operations. Information about the wind and wave climate in the Romanian waters is mainly based on observations at Gloria drilling platform (70 km from the coast). As regards the waves, the measurements of the wave characteristics are not so accurate due to the method used, being also available for a limited period. For this reason, the wave simulations that cover large temporal and spatial scales represent an option to describe better the wave climate. To assess the wind climate in the target area spanning 1992–2016, data provided by the NCEP-CFSR (U.S. National Centers for Environmental Prediction - Climate Forecast System Reanalysis) and consisting in wind fields at 10m above the sea level are used. The high spatial and temporal resolution of the wind fields is good enough to represent the wind variability over the area. For the same 25-year period, as considered for the wind climate, this study characterizes the wave climate from a wave hindcast data set that uses NCEP-CFSR winds as input for a model system SWAN (Simulating WAves Nearshore) based. The wave simulation results with a two-level modelling scale have been validated against both in situ measurements and remotely sensed data. The second level of the system, with a higher resolution in the geographical space (0.02°×0.02°), is focused on the Romanian coastal environment. The main wave parameters simulated at this level are used to analyse the wave climate. The spatial distributions of the wind speed, wind direction and the mean significant wave height have been computed as the average of the total data. As resulted from the amount of data, the target area presents a generally moderate wave climate that is affected by the storm events developed in the Black Sea basin. Both wind and wave climate presents high seasonal variability. All the results are computed as maps that help to find the more dangerous areas. A local analysis has been also employed in some key locations corresponding to highly sensitive areas, as for example the main Romanian harbors.

Keywords: numerical simulations, Romanian nearshore, waves, wind

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Authors: Nadia Yaghoobi, Seyed Majid Esmaeilzadeh

Abstract:

Due to advancements in wireless communication, new sensor capabilities have been created. In addition to the automation industry, the Internet of Things (IoT) has been used in environmental issues and has provided the possibility of communication between different devices for data collection and exchange. Water quality depends on many factors which are essential for maintaining the minimum sustainability of water. Regarding the great dependence of fishes on the quality of the aquatic environment, water quality can directly affect their activity. Therefore, monitoring water quality is an important issue to consider, especially in the fish farming industry. The conventional method of water quality testing is to collect water samples manually and send them to a laboratory for testing and analysis. This time-consuming method is a waste of manpower and is not cost-effective. The water quality measurement system implemented in this project monitors water quality in real-time through various sensors (parameters: water temperature, water level, dissolved oxygen, humidity and ambient temperature, water turbidity, PH). The Wi-Fi module, ESP8266, transmits data collected by sensors wirelessly to ThingSpeak and the smartphone app. Also, with the help of these instantaneous data, water temperature and water level can be controlled by using a heater and a water pump, respectively. This system can have a detailed study of the pollution and condition of water resources and can provide an environment for safe fish farming.

Keywords: dissolved oxygen, IoT, monitoring, ThingSpeak, water level, water quality, WiFi module

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Authors: Guofan Shao, Lina Tang, Hao Zhang

Abstract:

The values of image classification accuracy are affected by class size distributions and classification schemes, making it difficult to compare the performance of classification algorithms across different remote sensing data sources and classification systems. Based on the term efficacy from medicine and pharmacology, we have developed the metrics of image classification efficacy at the map and class levels. The novelty of this approach is that a baseline classification is involved in computing image classification efficacies so that the effects of class statistics are reduced. Furthermore, the image classification efficacies are interpretable and comparable, and thus, strengthen the assessment of image data classification methods. We use real-world and hypothetical examples to explain the use of image classification efficacies. The metrics of image classification efficacy meet the critical need to rectify the strategy for the assessment of image classification performance as image classification methods are becoming more diversified.

Keywords: accuracy assessment, efficacy, image classification, machine learning, uncertainty

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Authors: Kanamon Suwantada

Abstract:

The purpose of this research is to understand customer’s expectations towards homestays and to establish the precise strategies to increase numbers of tourists for homestay business in Amphawa district, Samutsongkram, Thailand. The researcher aims to ensure that each host provides experiences to travelers who are looking for and determining new targets for homestay business in Amphawa as well as creating sustainable homestay using marketing strategies to increase customers. The methods allow interview and questionnaire to gain both overview data from the tourists and qualitative data from the homestay owner’s perspective to create a GAP analysis. The data was collected from 200 tourists, during 15th May - 30th July, 2011 from homestay in Amphawa Community. The questionnaires were divided into three sections: the demographic profile, customer information and influencing on purchasing position, and customer expectation towards homestay. The analysis, in fact, will be divided into two methods which are percentage and correlation analyses. The result of this research revealed that homestay had already provided customers with reasonable prices in good locations. Antithetically, activities that they offered still could not have met the customer’s requirements. Homestay providers should prepare additional activities such as village tour, local attraction tour, village daily life experiences, local ceremony participation, and interactive conversation with local people. Moreover, the results indicated that a price was the most important factor for choosing homestay.

Keywords: ecotourism, homestay, marketing, sufficiency economic philosophy

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

Abstract:

Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: palm oil, fatty acid, NIRS, regression

Procedia PDF Downloads 489

Authors: Haifeng Wang, Haili Zhang

Abstract:

Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

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Authors: Hamid Reza Behnood, Esmaeel Ayati, Tom Brijs, Mohammadali Pirayesh Neghab

Abstract:

Investment projects in road safety planning can benefit from an effectiveness evaluation regarding their expected safety outcomes. The objective of this study is to develop a decision support system (DSS) to support policymakers in taking the right choice in road safety planning based on the efficiency of previously implemented safety measures in a set of regions in Iran. The measures considered for each region in the study include performance indicators about (1) police operations, (2) treated black spots, (3) freeway and highway facility supplies, (4) speed control cameras, (5) emergency medical services, and (6) road lighting projects. To this end, inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators (i.e., road safety measures) which should be minimized. The relative inefficiency for each region is modeled by the Data Envelopment Analysis (DEA) technique. In a next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA analysis into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety.

Keywords: performance indicators, road safety, decision support system, data envelopment analysis, fuzzy reasoning

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Authors: Amin Khamoosh, Hamed Faramarzifar

Abstract:

In the capital of Iran, Tehran, numerous buildings constructed when extreme climates were not prevalent now face the need for rehabilitation, typically within their first decade. Our data delves into the performance metrics and economic advantages of sustainable rehabilitation practices compared to traditional methods. With a focus on the scarcity of water resources, we specifically scrutinize water-efficient techniques throughout construction, rehabilitation, and usage. Examining design elements that optimize natural light while efficiently managing heat transmission is crucial, given the reliance on water for cooling devices in this region. The data aims to present a comprehensive strategy, addressing immediate structural concerns while harmonizing with Iran's unique environmental conditions.

Keywords: sustainable rehabilitation, concrete buildings, iran, solar energy, water-efficient techniques

Procedia PDF Downloads 42