Search results for: rule based systems.

Authors: L. Mion

Abstract:

The implementation of quality management systems in higher education in different countries is determined by national regulatory choices and supranational indications (such as the European Standard Guidelines for Quality Assurance). The effective functioning and transformative capacity of these quality management systems largely depend on the organizational context in which they are applied and, more specifically, on the culture of quality developed in single universities or in single countries. The University's concept of quality culture integrates the structural dimension of Quality Assurance (QA) (quality management manuals, process definitions, tools) with the value dimension of an organization (principles, skills, and attitudes). Within the EHEA (European Higher Education Area), countries such as Portugal, the Netherlands, the UK, Norway demonstrate a greater integration of QA principles in the various organizational levels and areas of competence of university institutions or have greater experience in implementation or scientific and political debate on the matter. Therefore, the study, through an integrative literature review, of the quality management systems of these countries, aimed at determining a framework of the culture of quality, helpful in defining the elements which, both in structural-organizational terms and in terms of values and skills and attitudes, have proved to be factors of success in the effective implementation of quality assurance systems in universities and in the countries considered in the research. In order for a QA system to effectively aim for continuous improvement in a complex and dynamic context such as the university one, it must embrace a holistic vision of quality from an integrative perspective, focusing on the objective of transforming the reality being evaluated.

Keywords: Higher Education, quality assurance, quality culture, Portugal, Norway, Netherlands, United Kingdom.

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

Abstract:

The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: EIoT, machine learning, anomaly detection, environment monitoring.

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Authors: Kittipob Kondee, Chutima Prommak

Abstract:

In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.

Keywords: Indoor positioning System, Optimization System design, Multi-Floor Building, Wireless Sensor Networks.

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Authors: Rohitash Chandra, Christian W. Omlin

Abstract:

We present a hybrid architecture of recurrent neural networks (RNNs) inspired by hidden Markov models (HMMs). We train the hybrid architecture using genetic algorithms to learn and represent dynamical systems. We train the hybrid architecture on a set of deterministic finite-state automata strings and observe the generalization performance of the hybrid architecture when presented with a new set of strings which were not present in the training data set. In this way, we show that the hybrid system of HMM and RNN can learn and represent deterministic finite-state automata. We ran experiments with different sets of population sizes in the genetic algorithm; we also ran experiments to find out which weight initializations were best for training the hybrid architecture. The results show that the hybrid architecture of recurrent neural networks inspired by hidden Markov models can train and represent dynamical systems. The best training and generalization performance is achieved when the hybrid architecture is initialized with random real weight values of range -15 to 15.

Keywords: Deterministic finite-state automata, genetic algorithm, hidden Markov models, hybrid systems and recurrent neural networks.

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Authors: Kwame B. O. Amoah

Abstract:

This paper focuses on retrofitting an old existing office building to a net-zero energy building (NZEB). An existing small office building in Melbourne, Florida, was chosen as a case study to integrate state-of-the-art design strategies and energy-efficient building systems to improve building performance and reduce energy consumption. The study aimed to explore possible ways to maximize energy savings and renewable energy generation sources to cover the building's remaining energy needs necessary to achieve net-zero energy goals. A series of retrofit options were reviewed and adopted with some significant additional decision considerations. Detailed processes and considerations leading to zero energy are well documented in this study, with lessons learned adequately outlined. Based on building energy simulations, multiple design considerations were investigated, such as emerging state-of-the-art technologies, material selection, improvements to the building envelope, optimization of the HVAC, lighting systems, and occupancy loads analysis, as well as the application of renewable energy sources. The comparative analysis of simulation results was used to determine how specific techniques led to energy saving and cost reductions. The research results indicate that this small office building can meet net-zero energy use after appropriate design manipulations and renewable energy sources.

Keywords: Energy consumption, building energy analysis, energy retrofits, energy-efficiency.

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Authors: M. Beisenbi, A. Sagymbay, S. Beisembina, A. Satpayeva

Abstract:

In this paper, the problem of unstable and deterministic chaotic processes in control systems is considered. The synthesis of a control system in the class of two-parameter structurally stable mappings is demonstrated. This is realized via the gradient-velocity method of Lyapunov vector functions. It is shown that the gradient-velocity method of Lyapunov vector functions allows generating an aperiodic robust stable system with the desired characteristics. A simple solution to the problem of synthesis of control systems for unstable and deterministic chaotic processes is obtained. Moreover, it is applicable for complex systems.

Keywords: Control system synthesis, deterministic chaotic processes, Lyapunov vector function, robust stability, structurally stable mappings.

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Authors: Jing Wu

Abstract:

In this paper, we discuss semiconvergence of the alternating iterative methods for solving singular systems. The semiconvergence theories for the alternating methods are established when the coefficient matrix is a singular matrix. Furthermore, the corresponding comparison theorems are obtained.

Keywords: Alternating iterative method, Semiconvergence, Singular matrix.

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Authors: An Chen, Huilin Ye

Abstract:

Mining sequential patterns from large customer transaction databases has been recognized as a key research topic in database systems. However, the previous works more focused on mining sequential patterns at a single concept level. In this study, we introduced concept hierarchies into this problem and present several algorithms for discovering multiple-level sequential patterns based on the hierarchies. An experiment was conducted to assess the performance of the proposed algorithms. The performances of the algorithms were measured by the relative time spent on completing the mining tasks on two different datasets. The experimental results showed that the performance depends on the characteristics of the datasets and the pre-defined threshold of minimal support for each level of the concept hierarchy. Based on the experimental results, some suggestions were also given for how to select appropriate algorithm for a certain datasets.

Keywords: Data Mining, Multiple-Level Sequential Pattern, Concept Hierarchy, Customer Transaction Database.

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Authors: Benjamin Osei-Tutu

Abstract:

Food contaminated with biological, chemical and physical hazards usually leads to foodborne illnesses which in turn increase the disease burden of developing and developed economies. Restaurants play a key role in the food service industry and violations in application of standardized food safety management systems in these establishments have been associated with foodborne disease outbreaks. This study was undertaken to assess the level of compliance to the Code of practice that was developed and implemented after conducting needs assessment of the food safety management systems employed by the Food Service Establishments in Ghana. Data on pre-licence inspections were reviewed to assess the compliance of the Food Service Establishments. During the period under review (2012-2016), 74.52% of the food service facilities in the hospitality industry were in compliance with the FDA’s code of practice. Main violations observed during the study bordered on facility layout and fabrication (61.8%) and this is because these facilities may not have been built for use as a food service establishment. Another fact that came to the fore was that the redesigning of the facilities to bring them into compliance required capital intensive investments, which some establishments are not prepared for. Other challenges faced by the industry regarded issues on records and documentations, personnel facilities and hygiene, raw materials acquisition, storage and control, and cold storage.

Keywords: Assessment, Accra, food safety management systems, restaurants, hotel.

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Authors: Kaushik Sathupadi, Sandesh Achar

Abstract:

Human action recognition (HAR) modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view Football datasets. Our HAR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH Multi-view Football datasets, respectively.

Keywords: Computer vision, human motion analysis, random forest, machine learning.

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Authors: Ivana Nacinovic, Lovorka Galetic, Nevenka Cavlek

Abstract:

Continuous innovation is becoming a necessity if firms want to stay competitive. Different factors influence the rate of innovation in a firm, among which corporate culture has often been recognized among the most important factors. In this paper we argue that the development of corporate culture that will support and foster innovation must be accompanied with an appropriate reward system. A research conducted among Croatian firms showed that a statistically significant relationship exists among corporate culture that supports innovations and reward system features.

Keywords: Corporate culture, innovation, reward systems, Croatia.

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Authors: Siyuan Jing, Kun She

Abstract:

Neighborhood Rough Sets (NRS) has been proven to be an efficient tool for heterogeneous attribute reduction. However, most of researches are focused on dealing with complete and noiseless data. Factually, most of the information systems are noisy, namely, filled with incomplete data and inconsistent data. In this paper, we introduce a generalized neighborhood rough sets model, called VPTNRS, to deal with the problem of heterogeneous attribute reduction in noisy system. We generalize classical NRS model with tolerance neighborhood relation and the probabilistic theory. Furthermore, we use the neighborhood dependency to evaluate the significance of a subset of heterogeneous attributes and construct a forward greedy algorithm for attribute reduction based on it. Experimental results show that the model is efficient to deal with noisy data.

Keywords: attribute reduction, incomplete data, inconsistent data, tolerance neighborhood relation, rough sets

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Authors: Thomas O. Olwal, Michael A. van Wyk, Barend J. van Wyk

Abstract:

In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.

Keywords: discrete polyphase matched filters, maximum likelihood estimators, soft timing phase estimation, wireless mobile systems.

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

Abstract:

One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: ATR, HRRP, motion compensation, SFW, TMP.

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Authors: Tawiwat Veeraklaew, Nathasit Phathana-im, Songkit Heama

Abstract:

Both the minimum energy consumption and smoothness, which is quantified as a function of jerk, are generally needed in many dynamic systems such as the automobile and the pick-and-place robot manipulator that handles fragile equipments. Nevertheless, many researchers come up with either solely concerning on the minimum energy consumption or minimum jerk trajectory. This research paper proposes a simple yet very interesting relationship between the minimum direct and indirect jerks approaches in designing the time-dependent system yielding an alternative optimal solution. Extremal solutions for the cost functions of direct and indirect jerks are found using the dynamic optimization methods together with the numerical approximation. This is to allow us to simulate and compare visually and statistically the time history of control inputs employed by minimum direct and indirect jerk designs. By considering minimum indirect jerk problem, the numerical solution becomes much easier and yields to the similar results as minimum direct jerk problem.

Keywords: Optimization, Dynamic, Linear Systems, Jerks.

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Authors: R. Sahraian, A. Karampour Haghighi, E. Ghasemi

Abstract:

Process planning and production scheduling play important roles in manufacturing systems. In this paper a multiobjective mixed integer linear programming model is presented for the integrated planning and scheduling of multi-product. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimization problem with substantially large solution space, suggesting that it is highly difficult to find the best solutions with the exact search method. To account for it, a PSO-based algorithm is proposed by fully utilizing the capability of the exploration search and fast convergence. To fit the continuous PSO in the discrete modeled problem, a solution representation is used in the algorithm. The numerical experiments have been performed to demonstrate the effectiveness of the proposed algorithm.

Keywords: Integrated process planning and scheduling, multi objective, MILP, Particle swarm optimization

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Authors: Philip Semaha, Zhongfang Lei, Ziwen Zhao, Sen Liu, Zhenya Zhang, Kazuya Shimizu

Abstract:

The increasing generation of saline wastewater through various industrial activities is becoming a global concern for activated sludge (AS) based biological treatment which is widely applied in wastewater treatment plants (WWTPs). As for the AS process, an increase in wastewater salinity has negative impact on its overall performance. The advent of conventional aerobic granular sludge (AGS) or bacterial AGS biotechnology has gained much attention because of its superior performance. The development of algal-bacterial AGS could enhance better nutrients removal, potentially reduce aeration cost through symbiotic algae-bacterial activity, and thus, can also reduce overall treatment cost. Nonetheless, the potential of salt stress to decrease biomass growth, microbial activity and nutrient removal exist. Up to the present, little information is available on saline wastewater treatment by algal-bacterial AGS. To the authors’ best knowledge, a comparison of the two AGS systems has not been done to evaluate nutrients removal capacity in the context of salinity increase. This study sought to figure out the impact of salinity on the algal-bacterial AGS system in comparison to bacterial AGS one, contributing to the application of AGS technology in the real world of saline wastewater treatment. In this study, the salt concentrations tested were 0 g/L, 1 g/L, 5 g/L, 10 g/L and 15 g/L of NaCl with 24-hr artificial illuminance of approximately 97.2 µmol m¯²s¯¹, and mature bacterial and algal-bacterial AGS were used for the operation of two identical sequencing batch reactors (SBRs) with a working volume of 0.9 L each, respectively. The results showed that salinity increase caused no apparent change in the color of bacterial AGS; while for algal-bacterial AGS, its color was progressively changed from green to dark green. A consequent increase in granule diameter and fluffiness was observed in the bacterial AGS reactor with the increase of salinity in comparison to a decrease in algal-bacterial AGS diameter. However, nitrite accumulation peaked from 1.0 mg/L and 0.4 mg/L at 1 g/L NaCl in the bacterial and algal-bacterial AGS systems, respectively to 9.8 mg/L in both systems when NaCl concentration varied from 5 g/L to 15 g/L. Almost no ammonia nitrogen was detected in the effluent except at 10 g/L NaCl concentration, where it averaged 4.2 mg/L and 2.4 mg/L, respectively, in the bacterial and algal-bacterial AGS systems. Nutrients removal in the algal-bacterial system was relatively higher than the bacterial AGS in terms of nitrogen and phosphorus removals. Nonetheless, the nutrient removal rate was almost 50% or lower. Results show that algal-bacterial AGS is more adaptable to salinity increase and could be more suitable for saline wastewater treatment. Optimization of operation conditions for algal-bacterial AGS system would be important to ensure its stably high efficiency in practice.

Keywords: Algal-bacterial aerobic granular sludge, bacterial aerobic granular sludge, nutrients removal, saline wastewater, sequencing batch reactor.

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Authors: V. Tawiwat, P. Jumnong

Abstract:

Both the minimum energy consumption and smoothness, which is quantified as a function of jerk, are generally needed in many dynamic systems such as the automobile and the pick-and-place robot manipulator that handles fragile equipments. Nevertheless, many researchers come up with either solely concerning on the minimum energy consumption or minimum jerk trajectory. This research paper proposes a simple yet very interesting when combining the minimum energy and jerk of indirect jerks approaches in designing the time-dependent system yielding an alternative optimal solution. Extremal solutions for the cost functions of the minimum energy, the minimum jerk and combining them together are found using the dynamic optimization methods together with the numerical approximation. This is to allow us to simulate and compare visually and statistically the time history of state inputs employed by combining minimum energy and jerk designs. The numerical solution of minimum direct jerk and energy problem are exactly the same solution; however, the solutions from problem of minimum energy yield the similar solution especially in term of tendency.

Keywords: Optimization, Dynamic, Linear Systems, Jerks.

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Authors: Carsten Röcker

Abstract:

This paper provides an introduction into the evolution of information and communication technology and illustrates its usage in the work domain. The paper is sub-divided into two parts. The first part gives an overview over the different phases of information processing in the work domain. It starts by charting the past and present usage of computers in work environments and shows current technological trends, which are likely to influence future business applications. The second part starts by briefly describing, how the usage of computers changed business processes in the past, and presents first Ambient Intelligence applications based on identification and localization information, which are already used in the production and retail sector. Based on current systems and prototype applications, the paper gives an outlook of how Ambient Intelligence technologies could change business processes in the future.

Keywords: Ambient Intelligence, Ubiquitous Computing, Business Applications, Radio Frequency Identification (RFID).

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Authors: Amir Lotfi, Seyed Hamid Hosseini

Abstract:

During the recent past, due to the increase of electrical energy demand and governmental resources constraints in creating additional capacity in the generation, transmission, and distribution, privatization, and restructuring in electrical industry have been considered. So, in most of the countries, different parts of electrical industry like generation, transmission, and distribution have been separated in order to create competition. Considering these changes, environmental issues, energy growth, investment of private equity in energy generation units and difficulties of transmission lines expansion, distributed generation (DG) units have been used in power systems. Moreover, reduction in the need for transmission and distribution, the increase of reliability, improvement of power quality, and reduction of power loss have caused DG to be placed in power systems. On the other hand, considering low liquidity need, private investors tend to spend their money for DGs. In this project, the main goal is to offer an algorithm for planning and placing DGs in order to reduce the need for transmission and distribution network.

Keywords: Planning, transmission, distributed generation, power security, power systems.

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Authors: Anna Maria Di Sciullo

Abstract:

Discourse pronominal anaphora resolution must be part of any efficient information processing systems, since the reference of a pronoun is dependent on an antecedent located in the discourse. Contrary to knowledge-poor approaches, this paper shows that syntax-semantic relations are basic in pronominal anaphora resolution. The identification of quantified expressions to which pronouns can be anaphorically related provides further evidence that pronominal anaphora is based on domains of interpretation where asymmetric agreement holds.

Keywords: asymmetric agreement, pronominal anaphora, quantifiers and indefinite expressions.

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Authors: Ali Mithad Emre

Abstract:

In military aviation, the use of flight simulators has proliferated recently in order to train fifth generation fighter pilots. With these simulators, pilots can carry out real-time flights resulting in seeing their faults and can perform emergency drills prior to real flights. Since we cannot risk losing the aircraft and the pilot himself/herself in the flight training process, flight simulators are of great importance to adapt the fighter pilots competently to real flights aboard the fifth generation aircraft. The real flights are impossible to simulate thoroughly on the ground. To some extent, the fixed-based simulators may assist the pilot to steer aircraft technically and visually but flight simulators can’t trick the pilot’s vestibular, sensory, and perceptual systems without motion platforms. This paper discusses the benefits of motion simulators for fifth generation fighter pilots’ training in preference to the fixed-based counterparts by analyzing their pros and cons.

Keywords: Centrifuge, g-loc, military, pilot, sickness, simulator, VMS.

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Authors: Jamal A. Gledan, Akrm H. Algnin

Abstract:

The Global Positioning System (GPS), satellite-based technology, has been utilized extensively in the last few years in a wide range of Geometrics and Geographic Information Systems’ (GIS) applications. One of the main challenges dealing with GPS-based heights consists of converting them into Mean Sea Level (MSL) heights, which is used in surveys and mapping.

In this research’s work, differences in heights of 50 points, in northern part of Libya has been carried out by using both ordinary leveling (in which Geoid is the reference datum) and GPS techniques (in which Ellipsoid is the reference datum). In addition, this study utilized the EGM2008 model to obtain the undulation values between the ellipsoidal and orthometric heights. From these values of ellipsoidal heights can be obtained from GPS observations to compute the orthomteric heights. This research presents a suitable alternative, from an economical point of view, to substitute the expensive traditional leveling technique, particularly, for topographic mapping.

Keywords: Geoid undulation, GPS, ordinary and geodetic leveling, orthometric height.

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Authors: Carsten Röcker

Abstract:

This paper provides an introduction into the evolution of information and communication technology and illustrates its usage in the work domain. The paper is sub-divided into two parts. The first part gives an overview over the different phases of information processing in the work domain. It starts by charting the past and present usage of computers in work environments and shows current technological trends, which are likely to influence future business applications. The second part starts by briefly describing, how the usage of computers changed business processes in the past, and presents first Ambient Intelligence applications based on identification and localization information, which are already used in the production and retail sector. Based on current systems and prototype applications, the paper gives an outlook of how Ambient Intelligence technologies could change business processes in the future.

Keywords: Ambient Intelligence, Ubiquitous Computing, Business Applications, Radio Frequency Identification (RFID)

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Authors: Nael Hirzallah, Sana Nseir

Abstract:

Merchants are competing to offer the use of mobile payment to encourage shopping. many mobile payment systems were made available in various locations worldwide; however, they have various drawbacks. This paper proposes a new mobile payment system that discusses the main drawbacks of these systems, namely security and speed of transaction. The proposal is featured by being simple to use by customers and merchants. Furthermore, the proposed system depends on a new authentication factor that is introduced in this paper and called by Two-Factors Authentication Plus, (2FA+).

Keywords: Electronic Commerce, Payment schemes, Mobile Payment, Authentication Factors, Mobile Applications.

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Authors: Osamah A. Alsayegh, Fatma A. Fairouz

Abstract:

This paper compares planning results of the electricity and water generation inventory up to year 2030 in the State of Kuwait. Currently, the generation inventory consists of oil and gas fired technologies only. The planning study considers two main cases. The first case, Reference case, examines a generation inventory based on oil and gas fired generation technologies only. The second case examines the inclusion of renewables as part of the generation inventory under two scenarios. In the first scenario, Ref-RE, renewable build-out is based on optimum economic performance of overall generation system. Result shows that the optimum installed renewable capacity with electric energy generation of 11% . In the second scenario, Ref-RE20, the renewable capacity build-out is forced to provide 20% of electric energy by 2030. The respective energy systems costs of Reference, Ref-RE and Ref-RE20 case scenarios reach US dollar 24, 10 and 14 billion annually in 2030.

Keywords: Generation inventory, solar, planning, TIMES, wind.

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Authors: Jieh-Shian Young, Chan Wei Hsu

Abstract:

This paper mainly studies the analyses of parameters in the intersection collision avoidance (ICA) system based on the radar sensors. The parameters include the positioning errors, the repeat period of the radar sensor, the conditions of potential collisions of two cross-path vehicles, etc. The analyses of the parameters can provide the requirements, limitations, or specifications of this ICA system. In these analyses, the positioning errors will be increased as the measured vehicle approach the intersection. In addition, it is not necessary to implement the radar sensor in higher position since the positioning sensitivities become serious as the height of the radar sensor increases. A concept of the safety buffer distances for front and rear of the measured vehicle is also proposed. The conditions for potential collisions of two cross-path vehicles are also presented to facilitate the computation algorithm.

Keywords: Intersection Collision Avoidance (ICA), Positioning Errors, Radar Sensors, Sensitivity of Positioning.

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Authors: Seung Woo Lee, So Jeong Nam, Jai-Kyung Lee

Abstract:

It can be said that the business sector is faced with a range of challenges–a rapidly changing business environment, an increase and diversification of customers- demands and the consequent need for quick response–for having in place flexible management and production info systems. As a matter of fact, many manufacturers have adopted production info management systems such as MES and ERP. Nevertheless, managers are having difficulties obtaining ever-changing production process information in real time, or responding quickly to any change in production related needs on the basis of such information. This is because they rely on poor production info systems which are not capable of providing real-time factory settings. If the manufacturer doesn-t have a capacity for collecting or digitalizing the 4 Ms (Man, Machine, Material, Method), which are resources for production, on a real time basis, it might to difficult to effectively maintain the information on production process. In this regard, this paper will introduce some new alternatives to the existing methods of collecting the 4 Ms in real time, which are currently comprise the production field.

Keywords: 4M, Acquisition of Data on shop-floor, Real-time machine interface

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Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

Abstract:

The rapid growth of telehealth Internet of Things (IoT) devices has raised concerns about energy consumption and efficient data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices with a fog and cloud computing-based platform, offering a sustainable and robust solution to overcome these challenges. Our model employs fog computing as a localized data processing layer while leveraging cloud computing for resource-intensive tasks, significantly reducing energy consumption. We incorporate adaptive energy-saving strategies. Simulation analysis validates our approach's effectiveness in enhancing energy efficiency for telehealth IoT systems integrated with localized fog nodes and both private and public cloud infrastructures. Future research will focus on further optimization of the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability in other healthcare and industry sectors.

Keywords: Energy-efficient, fog computing, IoT, telehealth.

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Authors: Zhiwen Pan, Jesus Pacheco, Salim Hariri, Yiqiang Chen, Bozhi Liu

Abstract:

The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Keywords: Internet of Things, network security, context awareness, intrusion detection

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