Search results for: air data system

Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

Procedia PDF Downloads 499

Authors: Jeisson A. Estrella, Laura C. Herrera, Cristian A. Arenas

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The Colombian electricity sector has been transforming through the insertion of new energy sources to generate electricity, one of them being solar energy, which is being promoted by companies interested in photovoltaic technology. The study of this technology is important for electricity generation in general and for the planning of the sector from the perspective of energy complementarity. Precisely in this last approach is where the project is located; we are interested in answering the concerns about the reliability of the electrical system when climatic phenomena such as El Niño occur or in defining whether it is viable to replace or expand thermoelectric plants. Reliability of the electrical system when climatic phenomena such as El Niño occur, or to define whether it is viable to replace or expand thermoelectric plants with renewable electricity generation systems. In this regard, some difficulties related to the basic information on renewable energy sources from measured data must first be solved, as these come from automatic weather stations. Basic information on renewable energy sources from measured data, since these come from automatic weather stations administered by the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM) and, in the range of study (2005-2019), have significant amounts of missing data. For this reason, the overall objective of the project is to complete the global solar irradiance datasets to obtain time series to develop energy complementarity analyses in a subsequent project. Global solar irradiance data sets to obtain time series that will allow the elaboration of energy complementarity analyses in the following project. The filling of the databases will be done through numerical and statistical methods, which are basic techniques for undergraduate students in technical areas who are starting out as researchers technical areas who are starting out as researchers.

Keywords: time series, global solar irradiance, imputed data, energy complementarity

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Hajara Abdulkarim Aliyu, Abdulbasid Ismail Isa

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This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions.

Keywords: electrohydraulic, fuzzy logic, modelling, NZ-PID

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Authors: Dana M. Ragab, Jasim A Ghaeb

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The Voltage Unbalance Factor (VUF) index is recommended to evaluate system performance under unbalanced operation. However, its calculation requires complex algebra which limits its use in the field. Furthermore, one system cycle is required at least to detect unbalance using the VUF. Ideally unbalance mitigation must be performed within 10 ms for 50 Hz systems. In this work, a linear relation for VUF evaluation in three-phase electrical power system using space vector (SV) is derived. It is proposed to determine the voltage unbalance quickly and accurately and to overcome the constraints associated with the traditional methods of VUF evaluation. Aqaba-Qatrana-South Amman (AQSA) power system is considered to study the system performance under unbalanced conditions. The results show that both the complexity of calculations and the time required to evaluate VUF are reduced significantly.

Keywords: power quality, space vector, unbalance evaluation, three-phase power system

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Authors: Galu Papy Yuma

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This paper presents a new dynamic simulation of a power system consisting of four machines equipped with the Generalized Unified Power Flow Controller (GUPFC) to improve power system stability. The dynamic simulation of the GUPFC consists of one shunt converter and two series converters based on voltage source converter, and DC link capacitor installed in the power system. MATLAB/Simulink is used to arrange the dynamic simulation of the GUPFC, where the power system is simulated in order to investigate the impact of the controller on power system oscillation damping and to show the simulation program reliability. The Improved Chaotic- Harmony Search (IC-HS) Algorithm is used to provide the parameter controller in order to lead-lag compensation design. The results obtained by simulation show that the power system with four machines is suitable for stability analysis. The use of GUPFC and IC-HS Algorithm provides the excellent capability in fast damping of power system oscillations and improve greatly the dynamic stability of the power system.

Keywords: GUPFC, IC-HS algorithm, Matlab/Simulink, damping oscillation

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

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Authors: Seungsik Yu, Minho Kang

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As the threat of terrorism to nuclear facilities is increasing globally after the attacks of September 11, we are striving to recognize the physical protection system and strengthen the emergency response system. Since 2015, Korea has implemented physical protection security exercise for nuclear facilities. The exercise should be carried out with full cooperation between the operator and response forces. Performance testing of the physical protection system should include appropriate exercises, for example, force-on-force exercises, to determine if the response forces can provide an effective and timely response to prevent sabotage. Significant deficiencies and actions taken should be reported as stipulated by the competent authority. The IAEA(International Atomic Energy Agency) is also preparing force-on-force exercise program documents to support exercise of member states. Currently, ROK(Republic of Korea) is implementing exercise on the force-on-force exercise evaluation system which is developed by itself for the nuclear power plant, and it is necessary to establish the exercise procedure considering the use of the force-on-force exercise evaluation system. The purpose of this study is to establish the work procedures of the three major organizations related to the force-on-force exercise of nuclear power plants in ROK, which conduct exercise using force-on-force exercise evaluation system. The three major organizations are composed of licensee, KINAC (Korea Institute of Nuclear Nonproliferation and Control), and the NSSC(Nuclear Safety and Security Commission). Major activities are as follows. First, the licensee establishes and conducts an exercise plan, and when recommendations are derived from the result of the exercise, it prepares and carries out a force-on-force result report including a plan for implementation of the recommendations. Other detailed tasks include consultation with surrounding units for adversary, interviews with exercise participants, support for document evaluation, and self-training to improve the familiarity of the MILES (Multiple Integrated Laser Engagement System). Second, KINAC establishes a force-on-force exercise plan review report and reviews the force-on-force exercise plan report established by licensee. KINAC evaluate force-on-force exercise using exercise evaluation system and prepare training evaluation report. Other detailed tasks include MILES training, adversary consultation, management of exercise evaluation systems, and analysis of exercise evaluation results. Finally, the NSSC decides whether or not to approve the force-on-force exercise and makes a correction request to the nuclear facility based on the exercise results. The most important part of ROK's force-on-force exercise system is the analysis through the exercise evaluation system implemented by KINAC after the exercise. The analytical method proceeds in the order of collecting data from the exercise evaluation system and analyzing the collected data. The exercise application process of the exercise evaluation system introduced in ROK in 2016 will be concretely set up, and a system will be established to provide objective and consistent conclusions between exercise sessions. Based on the conclusions drawn up, the ultimate goal is to complement the physical protection system of licensee so that the system makes licensee respond effectively and timely against sabotage or unauthorized removal of nuclear materials.

Keywords: Force-on-Force exercise, nuclear power plant, physical protection, sabotage, unauthorized removal

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Authors: Mohammadreza Ashouri, Majid Bayatian

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Analysis of fire data is a way for the implementation of any plan to improve the level of safety in cities. Such an analysis is able to reveal signs of changes in a given period and can be used as a measure of safety. The information of about 66,341 fires (from 2002 to 2012) released by Tehran Safety Services and Fire-Fighting Organization and data on the population and the number of households provided by Tehran Municipality and the Statistical Yearbook of Iran were extracted. Using the data, the fire changes, the rate of injuries, and mortality rate were determined and analyzed. The rate of injuries and mortality rate of fires per one million population of Tehran were 59.58% and 86.12%, respectively. During the study period, the number of fires and fire stations increased by 104.38% and 102.63%, respectively. Most fires (9.21%) happened in the 4th District of Tehran. The results showed that the recorded fire data have not been systematically planned for fire prevention since one of the ways to reduce injuries caused by fires is to develop a systematic plan for necessary actions in emergency situations. To determine a reliable source for fire prevention, the stages, definitions of working processes and the cause and effect chains should be considered. Therefore, a comprehensive statistical system should be developed for reported and recorded fire data.

Keywords: fire statistics, fire analysis, accident prevention, Tehran

Procedia PDF Downloads 169

Authors: Sung Hyun Yoo, In Hwan Choi, Jun Ho Jung, Choon Ki Ahn, Myo Taeg Lim

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Home energy management system (HEMS) has been issued to reduce the power consumption. The HEMS performs electric power control for the indoor electric device. However, HEMS commonly treats the smart devices. In this paper, we suggest the output estimation of home legacy device using the artificial neural fuzzy inference system (ANFIS). This paper discusses the overview and the architecture of the system. In addition, accurate performance of the output estimation using the ANFIS inference system is shown via a numerical example.

Keywords: artificial neural fuzzy inference system (ANFIS), home energy management system (HEMS), smart device, legacy device

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Authors: Tsai-Pei Liu, Zhi-Rou Zheng, Tzu-Tzu Wen

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Innovative logistics system simulation teaching is to extract the characteristics of the system through simulation methodology. The system has randomness and interaction problems in the execution time. Therefore, the simulation model can usually deal with more complex logistics process problems, giving students different learning modes. Students have more autonomy in learning time and learning progress. System simulation has become a new educational tool, but it still needs to accept many tests to use it in the teaching field. Although many business management departments in Taiwan have started to promote, this kind of simulation system teaching is still not popular, and the prerequisite for popularization is to be supported by students. This research uses an extension of Integration Unified Theory of Acceptance and Use of Technology (UTAUT2) to explore the acceptance of students in universities of science and technology to use system simulation as a learning tool. At the same time, it is hoped that this innovation can explore the effectiveness of the logistics system simulation after the introduction of teaching. The results indicated the significant influence of performance expectancy, social influence and learning value on students’ intention towards confirmed the influence of facilitating conditions and behavioral intention. The extended UTAUT2 framework helps in understanding students’ perceived value in the innovative logistics system teaching context.

Keywords: UTAUT2, logistics system simulation, learning value, Taiwan

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Authors: Yingkun Huang, Li Guo, Zekang Lan, Kai Tian

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Hard disk drives (HDD) failure of the exascale supercomputing system may lead to service interruption and invalidate previous calculations, and it will cause permanent data loss. Therefore, initiating corrective actions before hard drive failures materialize is critical to the continued operation of jobs. In this paper, a highly accurate analysis model based on CNN-LSTM and oversampling technique was proposed, which can correctly predict the necessity of a disk replacement even ten days in advance. Generally, the learning-based method performs poorly on a training dataset with long-tail distribution, especially fault prediction is a very classic situation as the scarcity of failure data. To overcome the puzzle, a new oversampling was employed to augment the data, and then, an improved CNN-LSTM with the shortcut was built to learn more effective features. The shortcut transmits the results of the previous layer of CNN and is used as the input of the LSTM model after weighted fusion with the output of the next layer. Finally, a detailed, empirical comparison of 6 prediction methods is presented and discussed on a public dataset for evaluation. The experiments indicate that the proposed method predicts disk failure with 0.91 Precision, 0.91 Recall, 0.91 F-measure, and 0.90 MCC for 10 days prediction horizon. Thus, the proposed algorithm is an efficient algorithm for predicting HDD failure in supercomputing.

Keywords: HDD replacement, failure, CNN-LSTM, oversampling, prediction

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Authors: Abdulaziz F. Ettir, Ghait Bashir, Tarek S. Duzan

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A proper well planning is very vital to achieve any successful drilling program on the basis of preventing, overcome all drilling problems and minimize cost operations. Since the hydraulic system plays an active role during the drilling operations, that will lead to accelerate the drilling effort and lower the overall well cost. Likewise, an improperly designed hydraulic system can slow drill rate, fail to clean the hole of cuttings, and cause kicks. In most cases, common sense and commercially available computer programs are the only elements required to design the hydraulic system. Drilling optimization is the logical process of analyzing effects and interactions of drilling variables through applied drilling and hydraulic equations and mathematical modeling to achieve maximum drilling efficiency with minimize drilling cost. In this paper, practical software adopted in this paper to define drilling optimization models including four different optimum keys, namely Opti-flow, Opti-clean, Opti-slip and Opti-nozzle that can help to achieve high drilling efficiency with lower cost. The used data in this research from vertical and horizontal wells were recently drilled in Waha Oil Company fields. The input data are: Formation type, Geopressures, Hole Geometry, Bottom hole assembly and Mud reghology. Upon data analysis, all the results from wells show that the proposed program provides a high accuracy than that proposed from the company in terms of hole cleaning efficiency, and cost break down if we consider that the actual data as a reference base for all wells. Finally, it is recommended to use the established Optimization calculations software at drilling design to achieve correct drilling parameters that can provide high drilling efficiency, borehole cleaning and all other hydraulic parameters which assist to minimize hole problems and control drilling operation costs.

Keywords: optimum keys, namely opti-flow, opti-clean, opti-slip and opti-nozzle

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: M. Shadmand, T. Enayaty Ahangar, S. Kazemi

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Insulation system of electrical machineries is the most critical point for their durability. Depending on generator nominal voltage, its insulation system is designed. In this research, a new stator insulation system is designed by new type of mica tapes which will consequently enables us to decrease the nominal ground-wall insulation thickness for the same voltage level. By keeping constant the slot area, it will be possible to increase the copper value in stator bars which will consequently able us to increase the nominal output current of turbo-generator. This will affect the cooling capability of machinery to some extent. But by considering the thermal conductivity of new insulating system which is improved, it is possible to increase the output power of generator up to 6% more. This research is done practically on a 200 MVA and 15.75 kV turbo-generators which its insulating system is Resin Rich (RR).

Keywords: insulation system, resin rich, VPI, upgrading

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Authors: Macdonald Kanyangale, Sandram Naluso

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Globally, researchers have struggled over time to adequately define the notion of health system to inform research. This study is significant because it proposes an integrative framework for a robust definition of the health system. The objective of this article is to examine major pitfalls in definitions of health system used in prior literature and implications of these for research and management. The study used methodological steps of a scoping review proposed by Arksey and O'Malley to identify and examine 24 definitions of a health system in articles selected from six databases and web search engines. Thematic analysis was used to delineate and categorise definitional pitfalls into broader themes. There are a plethora of five major pitfalls in the extant definitions of a health system which may easily scupper any unsuspecting researcher if not avoided or addressed in research. These definitional pitfalls are reductionist assumptions which ignore dynamic and complex connections, overly wide boundary and lack of specification of levels in a health system, and limited focus on process in a health system. In addition, there is the tendency of treating different components of the health system as equal and simplifying of the ontological complexity of the health system. Future scholars are advised to avoid or address the identified five major pitfalls if they are to develop robust definitions of an HS. The use of an integrative framework for a robust definition of a health system is recommended, while implications of the pitfalls are discussed as a basis and catalyst for complexity-informed research and managing interactively.

Keywords: complexity management, health system, pitfalls, reductionism, research

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: M. Ndaw, G. Mendy, S. Ouya

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Information system risk management helps to reduce or eliminate risk by implementing appropriate controls. In this paper, we propose a quantification model of controls impact on information system risks by automatizing the residual criticality estimation step of FMECA which is based on a inductive reasoning. For this, we defined three equations based on type and maturity of controls. For testing, the values obtained with the model were compared to estimated values given by interlocutors during different working sessions and the result is satisfactory. This model allows an optimal assessment of controls maturity and facilitates risk analysis of information system.

Keywords: information system, risk, control, FMECA method

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Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

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Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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It presents a heating system using low cost alternative solar collectors to promote the disinfection of water in low income communities that take water contaminated by bacteria. The system consists of two solar collectors, with total area of 4 m² and was built using PET bottles and cans of beer and soft drinks. Each collector is made up of 8 PVC tubes, connected in series and work in continuous flow. It will determine the flux the most appropriate to generate the temperature to promote the disinfection. Will be presented results of the efficiency and thermal loss of system and results of analysis of water after undergoing the process of heating.

Keywords: disinfection of water, solar heating system, poor communities, PVC

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: Manop Aorpimai, Ponthep Navakitkanok

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In this paper, the development of the ephemeris generation module used for the Thaichote satellite operations is presented. It is a vital part of the flight dynamics system, which comprises, the orbit determination, orbit propagation, event prediction and station-keeping maneuver modules. In the generation of the spacecraft ephemeris data, the estimated orbital state vector from the orbit determination module is used as an initial condition. The equations of motion are then integrated forward in time to predict the satellite states. The higher geopotential harmonics, as well as other disturbing forces, are taken into account to resemble the environment in low-earth orbit. Using a highly accurate numerical integrator based on the Burlish-Stoer algorithm the ephemeris data can be generated for long-term predictions, by using a relatively small computation burden and short calculation time. Some events occurring during the prediction course that are related to the mission operations, such as the satellite’s rise/set viewed from the ground station, Earth and Moon eclipses, the drift in ground track as well as the drift in the local solar time of the orbital plane are all detected and reported. When combined with other modules to form a flight dynamics system, this application is aimed to be applied for the Thaichote satellite and successive Thailand’s Earth-observation missions.

Keywords: flight dynamics system, orbit propagation, satellite ephemeris, Thailand’s Earth Observation Satellite

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Authors: Maulana Ayoub Ali, Pradeep Kulshrestha

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Laws of any given secular state have a huge contribution in the growth of the Islamic banking system because the system uses conventional laws to govern its activities. Therefore, the former should be ready to accommodate the latter in order to make the Islamic banking system work properly without affecting the current conventional banking system and therefore without affecting its system. Islamic financial rules have been practiced since the birth of Islam. Following the recent world economic challenges in the financial sector, a quick rebirth of the contemporary Islamic ethical banking system took place. The coming of the Islamic banking system is due to various reasons including but not limited to the failure of the interest based economy in solving financial problems around the globe. Therefore, the Islamic banking system has been adopted as an alternative banking system in order to recover the highly damaged global financial sector. But the Islamic banking system has been facing a number of challenges which hinder its smooth operation in different parts of the world. It has not been the aim of this paper to discuss other challenges rather than the legal ones, but the same was partly discussed when it was justified that it was proper to do so. Generally, there are so many things which have been discovered in the course of writing this paper. The most important part is the issue of the regulatory and supervisory framework for the Islamic banking system in Tanzania and in other nations is considered to be a crucial part for the development of the Islamic banking industry. This paper analyses what has been observed in the study on that area and recommends for necessary actions to be taken on board in a bid to make Islamic banking system reach its climax of serving the larger community by providing ethical, equitable, affordable, interest-free and society cantered banking system around the globe.

Keywords: Islamic banking, interest free banking, ethical banking, legal framework

Procedia PDF Downloads 136

Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

Procedia PDF Downloads 353

Authors: F. Benhamida, A. Graa, L. Benameur, I. Ziane

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The state estimation of the electrical power system operation state is very important for supervising task. With the nonlinearity of the AC power flow model, the state estimation problem (SEP) is a nonlinear mathematical problem with many local optima. This paper treat the mathematical model for the SEP and the monitoring of the nonlinear systems of great dimensions with an application on power electrical system, the modelling, the analysis and state estimation synthesis in order to supervise the power system behavior. in fact, it is very difficult, to see impossible, (for reasons of accessibility, techniques and/or of cost) to measure the excessive number of the variables of state in a large-sized system. It is thus important to develop software sensors being able to produce a reliable estimate of the variables necessary for the diagnosis and also for the control.

Keywords: power system, state estimation, robustness, observability

Procedia PDF Downloads 504

Authors: Tabrej Khan

Abstract:

Examination Scheduling System (ESS) is a scheduling system that targets as an exam committee in any academic institute to help them in managing the exams automatically. We present an algorithm for Examination Scheduling System. Nowadays, many universities have challenges with creating examination schedule fast with less confliction compared to hand works. Our aims are to develop a computerized system that can be used in examination scheduling in an academic institute versus available resources (Time, Hall, Invigilator and instructor) with no contradiction and achieve fairness among students. ESS was developed using HTML, C# language, Crystal Report and ASP.NET through Microsoft Visual Studio 2010 as developing tools with integrated SQL server database. This application can produce some benefits such as reducing the time spent in creating an exam schedule and achieving fairness among students

Keywords: examination scheduling system (ESS), algorithm, ASP.NET, crystal report

Procedia PDF Downloads 385

Authors: Synthia Atas Sari, Engkos Achmad Kuncoro, Haryadi Sarjono

Abstract:

The purpose of this paper is to examine the impact of reward system which is determined by government over the work of Board of Commissioners in implementing good corporate governance in Indonesian state-owned enterprises. To do so, this study analyses the adequacy of the remuneration, the job attractiveness, and the board commitment and dedication with the remuneration system. Qualitative method used to examine the significant features and challenges to the government policy over the remuneration determination for the board of commissioners to their roles. Data are gathered through semi-structure in-depth interview to the 21 participants over 10 Indonesian stated-owned enterprises and written documents. Findings in this study indicate that government policies over the remuneration system is not effective to increase the performance of board of commissioners in implementing good corporate governance in Indonesian state-owned enterprises due to unattractiveness of the remuneration amount, demotivate active members, and conflict interest over members of the remuneration committee.

Keywords: reward system, board of commissioners, state-owned enterprises, good corporate governance

Procedia PDF Downloads 368

Authors: Ankita Wadhawan, Parteek Kumar, Umesh Kumar

Abstract:

Gesture is any body movement that expresses some attitude or any sentiment. Gestures as a sign language are used by deaf people for conveying messages which helps in eliminating the communication barrier between deaf people and normal persons. Nowadays, everybody is using mobile phone and computer as a very important gadget in their life. But there are some physically challenged people who are blind/deaf and the use of mobile phone or computer like device is very difficult for them. So, there is an immense need of a system which works on body gesture or sign language as input. In this research, Microsoft Kinect Sensor, SDK V2 and Hidden Markov Toolkit (HTK) are used to recognize the object, motion of object and human body joints through Touch less NUI (Natural User Interface) in real-time. The depth data collected from Microsoft Kinect has been used to recognize gestures of Indian Sign Language (ISL). The recorded clips are analyzed using depth, IR and skeletal data at different angles and positions. The proposed system has an average accuracy of 85%. The developed Touch less NUI provides an interface to recognize gestures and controls the cursor and click operation in computer just by waving hand gesture. This research will help deaf people to make use of mobile phones, computers and socialize among other persons in the society.

Keywords: gesture recognition, Indian sign language, Microsoft Kinect, natural user interface, sign language

Procedia PDF Downloads 290