Search results for: adaptive radio resource allocation

Authors: Sharmina Begum, M. G. Rasul, Delwar Akbar

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Solid waste can be considered as an urban burden or as a valuable resource depending on how it is managed. To meet the rising demand for energy and to address environmental concerns, a conversion from conventional energy systems to renewable resources is essential. For the sustainability of human civilization, an environmentally sound and techno-economically feasible waste treatment method is very important to treat recyclable waste. Several technologies are available for realizing the potential of solid waste as an energy source, ranging from very simple systems for disposing of dry waste to more complex technologies capable of dealing with large amounts of industrial waste. There are three main pathways for conversion of waste material to energy: thermo chemical, biochemical and physicochemical. This paper investigates the thermo chemical conversion of solid waste for energy recovery. The processes, advantages and dis-advantages of various thermo chemical conversion processes are discussed and compared. Special attention is given to Gasification process as it provides better solutions regarding public acceptance, feedstock flexibility, near-zero emissions, efficiency and security. Finally this paper presents comparative statements of thermo chemical processes and introduces an integrated waste management system.

Keywords: Gasification, Incineration, Pyrolysis, Thermo chemical conversion.

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Authors: C. Murat, T. Elifnaz

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Today, with globalization, human mobility has increased the interaction between countries significantly, and this contact has also increased the possibility of epidemics, although this contact has moved societies forward in terms of civilization. The coronavirus (COVID-19) epidemic, which caused the most loss of life from these epidemics, quickly swept the whole world with the effect of globalization. The coronavirus epidemic has affected the world economically as well as health problems. While some businesses around the world experienced an extraordinary increase in demand, some businesses temporarily stopped their activities or were forced to do so. Businesses affected by the crisis had to adapt to new legal regulations but had to make changes in matters such as working styles, human resources practices, and policies. One of the measures considered is the reduction of the workforce. The current COVID-19 crisis has created serious challenges for many organizations and has led to an unprecedented wave of termination notices. In this study, examples of companies that were affected by the pandemic process and changed their working policies after the pandemic were examined. This study aims to reveal the impact of the global COVID-19 epidemic on human resources policies and employees and how these situations will affect businesses in the future.

Keywords: COVID-19, human resource management, crisis management, business function.

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Authors: Adarsh Patil, David A. Power, John P. Morrison

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Grid environments consist of the volatile integration of discrete heterogeneous resources. The notion of the Grid is to unite different users and organisations and pool their resources into one large computing platform where they can harness, inter-operate, collaborate and interact. If the Grid Community is to achieve this objective, then participants (Users and Organisations) need to be willing to donate or share their resources and permit other participants to use their resources. Resources do not have to be shared at all times, since it may result in users not having access to their own resource. The idea of reward-based computing was developed to address the sharing problem in a pragmatic manner. Participants are offered a reward to donate their resources to the Grid. A reward may include monetary recompense or a pro rata share of available resources when constrained. This latter point may imply a quality of service, which in turn may require some globally agreed reservation mechanism. This paper presents a platform for economybased computing using the WebCom Grid middleware. Using this middleware, participants can configure their resources at times and priority levels to suit their local usage policy. The WebCom system accounts for processing done on individual participants- resources and rewards them accordingly.

Keywords: WebCom, Economy-based computing, WebComGrid Bank Reward, Condensed Graph, Distributor, Accounting, GridPoint.

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Authors: Salha Alshamrani, Maha Aljohni, Eman Aldhaheri

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With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: Internet of Thing, Spoofing, IoT, Access control, Blockchain, Raspberry pi.

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: Distillation, machine learning, neural networks, quantization.

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Authors: Jucelia Appio, Danielle Deimling De Carli, Bruno Henrique Rocha Fernandes, Nelson Natalino Frizon

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The purpose of this paper is to investigate if there are positive and significant correlations between the dimensions of Person-Environment Fit (Person-Job, Person-Organization, Person-Group and Person-Supervisor) at the “Best Companies to Work for” in Brazil in 2017. For that, a quantitative approach was used with a descriptive method being defined as a research sample the "150 Best Companies to Work for", according to data base collected in 2017 and provided by Fundação Instituto of Administração (FIA) of the University of São Paulo (USP). About the data analysis procedures, asymmetry and kurtosis, factorial analysis, Kaiser-Meyer-Olkin (KMO) tests, Bartlett sphericity and Cronbach's alpha were used for the 69 research variables, and as a statistical technique for the purpose of analyzing the hypothesis, Pearson's correlation analysis was performed. As a main result, we highlight that there was a positive and significant correlation between the dimensions of Person-Environment Fit, corroborating the H1 hypothesis that there is a positive and significant correlation between Person-Job Fit, Person-Organization Fit, Person-Group Fit and Person-Supervisor Fit.

Keywords: Human resource management, person-environment fit, strategic people management, best companies to work for.

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Authors: Ahmed Amin Mousa, M. Abd El-Salam

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This study discusses a simple solution for the problem of shortage in learning resources for kindergarten teachers. Occasionally, kindergarten teachers cannot access proper resources by usual search methods as libraries or search engines. Furthermore, these methods require a long time and efforts for preparing. The study is expected to facilitate accessing learning resources. Moreover, it suggests a potential direction for using QR code inside the classroom. The present work proposes that QR code can be used for digitizing kindergarten curriculums and accessing various learning resources. It investigates using QR code for saving information related to the concepts which kindergarten teachers use in the current educational situation. The researchers have established a guide for kindergarten teachers based on the Egyptian official curriculum. The guide provides different learning resources for each scientific and mathematical concept in the curriculum, and each learning resource is represented as a QR code image that contains its URL. Therefore, kindergarten teachers can use smartphone applications for reading QR codes and displaying the related learning resources for students immediately. The guide has been provided to a group of 108 teachers for using inside their classrooms. The results showed that the teachers approved the guide, and gave a good response.

Keywords: Kindergarten, child, learning resources, QR code, smart phone, mobile.

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Authors: G. Chakhaia, S. Gogilava, L. Tsulukidze, Z. Laoshvili, I. Khubulava, S. Bosikashvili, T. Gugushvili

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The work reviewed and evaluated various genesis debris flow phenomena recently formatted in the Mletiskhevi, accordingly it revealed necessity of treatment modern debris flow against measures. Based on this, it is proposed the debris flow against truncated semi cone shape construction, which elements are contained in the car’s secondary tires. its constituent elements (sections), due to the possibilities of amortization and geometric shapes is effective and sustainable towards debris flow hitting force. The construction is economical, because after crossing the debris flows in the river bed, the riverbed is not cleanable, also the elements of the building are resource saving. For assessment of influence of cohesive debris flow at the construction and evaluation of the construction effectiveness have been implemented calculation in the specific assumptions with approved methodology. According to the calculation, it was established that after passing debris flow in the debris flow construction (in 3 row case) its hitting force reduces 3 times, that causes reduce of debris flow speed and kinetic energy, as well as sedimentation on a certain section of water drain in the lower part of the construction. Based on the analysis and report on the debris flow against construction, it can be said that construction is effective, inexpensive, technically relatively easy-to-reach measure, that’s why its implementation is prospective.

Keywords: Construction, debris flow, sections, theoretical calculation.

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Authors: Kayode A. Olaniyi, Adeola A. Ogunleye, Tola M. Osifeko

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Electric Vehicles (EV) appear to be gaining increasing patronage as a feasible alternative to Internal Combustion Engine Vehicles (ICEVs) for having low emission and high operation efficiency. The EV energy storage systems are required to handle high energy and power density capacity constrained by limited space, operating temperature, weight and cost. The choice of strategies for energy storage evaluation, monitoring and control remains a challenging task. This paper presents review of various energy storage technologies and recent researches in battery evaluation techniques used in EV applications. It also underscores strategies for the hybrid energy storage management and control schemes for the improvement of EV stability and reliability. The study reveals that despite the advances recorded in battery technologies there is still no cell which possess both the optimum power and energy densities among other requirements, for EV application. However combination of two or more energy storages as hybrid and allowing the advantageous attributes from each device to be utilized is a promising solution. The review also reveals that State-of-Charge (SoC) is the most crucial method for battery estimation. The conventional method of SoC measurement is however questioned in the literature and adaptive algorithms that include all model of disturbances are being proposed. The review further suggests that heuristic-based approach is commonly adopted in the development of strategies for hybrid energy storage system management. The alternative approach which is optimization-based is found to be more accurate but is memory and computational intensive and as such not recommended in most real-time applications.

Keywords: Hybrid electric vehicle, hybrid energy storage, battery state estimation, ate of charge, state of health.

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Authors: Monika Kulikowska-Pawlak, Katarzyna Bratnicka-Myśliwiec, Tomasz Ingram

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This study seeks to contribute to the literature on firm competitiveness by advancing the perspective of organizational politics that views this process as a driver which creates identifiable differences in firm performance. The hypothesized relationships were tested on the basis of data from 355 Polish medium and large-sized enterprises. Data were analyzed using correlation analysis, EFA and robustness tests. The main result of the conducted analyses proved the coexistence, previously examined in the literature, of corporate entrepreneurship and firm performance. The obtained research findings made it possible to add organizational politics to a wide range of elements determining corporate entrepreneurship, followed by competitive advantage, in addition to antecedents such as strategic leadership, corporate culture, opportunity-oriented resource-based management, etc. Also, the empirical results suggest that four dimensions of organizational politics (dominant coalition, influence exertion, making organizational changes, and information openness) are positively related to firm competitiveness. In addition, these findings seem to underline a supposition that corporate entrepreneurship is an important mediator which strengthens the competitive effects of organizational politics.

Keywords: Corporate entrepreneurship, firm competitiveness organizational politics, sensemaking.

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Authors: Yun Mi, Ko, Hye Jung, Joo

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This study develops a relation to explore the factors influencing management and technology capabilities in strategic alliances. Alliances between firms are recognizing increasingly popular as a vehicle to create and extract greater value from the market. Firm’s alliance can be described as the collaborative problem solving process to solve problems jointly. This study starts from research questions what factors of firm’s management and technology characteristics affect performance of firms which are formed alliances. In this study, we investigated the effect of strategic alliances on company performance. That is, we try to identify whether firms made an alliance with other organizations are differed by characteristics of management and technology. And we test that alliance type and alliance experiences moderate the relationship between firm’s capabilities and its performance. We employ problem-solving perspective and resource-based view perspective to shed light on this research questions. The empirical work is based on the Survey of Business Activities conducted from2006 to 2008 by Statistics Korea. We verify correlations between to point out that these results contribute new empirical evidence on the effect of strategic alliances on company performance.

Keywords: Problem solving process, strategic alliance.

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Authors: Manisha Chaudhary, Joydip Dhar, Govind Prasad Sahu

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A mathematical model is proposed considering the forest biomass density B(t), density of wood based industries W(t) and density of synthetic industries S(t). It is assumed that the forest biomass grows logistically in the absence of wood based industries, but depletion of forestry biomass is due to presence of wood based industries. The growth of wood based industries depends on B(t), while S(t) grows at a constant rate, independent of B(t). Further there is a competition between W(t) and S(t) according to market demand. The proposed model has four ecologically feasible steady states, namely, E1: forest biomass free and wood industries free equilibrium; E2: wood industries free equilibrium and two coexisting equilibria E∗1 , E∗2 . Behavior of the system near all feasible equilibria is analyzed using the stability theory of differential equations. In the proposed model, the natural depletion rate h1 is a crucial parameter and system exhibits Hopf-bifurcation about the non-trivial equilibrium with respect to h1. The analytical results are verified using numerical simulation.

Keywords: A mathematical model, Competition between wood based and synthetic industries, Hopf-bifurcation, Stability analysis.

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Authors: Henrik Prinzhorn, Peter Nyhuis, Johannes Wagner, Peter Burggräf, Torben Schmitz, Christina Reuter

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Assembling large-scale products, such as airplanes, locomotives, or wind turbines, involves frequent process interruptions induced by e.g. delayed material deliveries or missing availability of resources. This leads to a negative impact on the logistical performance of a producer of xxl-products. In industrial practice, in case of interruptions, the identification, evaluation and eventually the selection of an alternative order of assembly activities (‘assembly alternative’) leads to an enormous challenge, especially if an optimized logistical decision should be reached. Therefore, in this paper, an innovative, optimization model for the identification of assembly alternatives that addresses the given problem is presented. It describes make-to-order, large-scale product assembly processes as a resource constrained project scheduling (RCPS) problem which follows given restrictions in practice. For the evaluation of the assembly alternative, a cost-based definition of the logistical objectives (delivery reliability, inventory, make-span and workload) is presented.

Keywords: Assembly scheduling, large-scale products, make-to-order, rescheduling, optimization.

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Authors: Jamie Otelsberg, Nagarajan Akshay, Rao R. Bhavani

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This paper discusses our preliminary experiences in the design of a user interface of a computerized content-rich vocational training courseware meant for users with little or no computer experience. In targeting a growing population with limited access to skills training of any sort, we faced numerous challenges, including language and cultural differences, resource limits, gender boundaries and, in many cases, the simple lack of trainee motivation. With the size of the unskilled population increasing much more rapidly than the numbers of sufficiently skilled teachers, there is little choice but to develop teaching techniques that will take advantage of emerging computer-based training technologies. However, in striving to serve populations with minimal computer literacy, one must carefully design the user interface to accommodate their cultural, social, educational, motivational and other differences. Our work, which uses computer based and haptic simulation technologies to deliver training to these populations, has provided some useful insights on potential user interface design approaches.

Keywords: User interface design, digitally illiterate, vocational training, navigation issues, computer human interaction, human factors.

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Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: Human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence.

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Authors: Amir Hossein Ghaffari Nejad, Forouhar Ferdowsi, Reza Mashhadi

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In the interest-free banking system of Iran, the savings of society are in the form of bank deposits, and banks using the Islamic contracts, allocate the resources to applicants for obtaining facilities and credit. In the meantime, the central bank, with the aim of introducing monetary policy, determines the maximum interest rate on bank deposits in terms of macroeconomic requirements. But in recent years, the country's economic constraints with the stagflation and the consequence of the institutional weaknesses of the financial market of Iran have resulted in massive disturbances in the balance sheet of the banking system, resulting in a period of mismatch maturity in the banks' assets and liabilities and the implementation of a Ponzi game. This issue caused determination of the interest rate in long-term bank deposit contracts to be associated with non-observance of the maximum rate set by the central bank. The result of this condition was in the allocation of new sources of equipment to meet past commitments towards the old depositors and, as a result, a significant part of the supply of equipment was leaked out of the facilitating cycle and credit crunch emerged. The purpose of this study is to identify the most important factors affecting the occurrence of non-confirmatory financial banking behavior using data from 19 public and private banks of Iran. For this purpose, the causes of this non-confirmatory behavior of banks have been investigated using the panel vector autoregression method (PVAR) for the period of 2007-2015. Granger's causality test results suggest that the return of parallel markets for bank deposits, non-performing loans and the high share of the ratio of facilities to banks' deposits are all a cause of the formation of non-confirmatory behavior. Also, according to the results of impulse response functions and variance decomposition, NPL and the ratio of facilities to deposits have the highest long-term effect and also have a high contribution to explaining the changes in banks' non-confirmatory behavior in determining the interest rate on deposits.

Keywords: Non-conformity behavior, Ponzi game, panel vector autoregression, nonperforming loans.

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Authors: S. Da Costa, D. Páez, F. Sánchez

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We examine the causal role of positive affect on creativity, the association of creativity or innovation in the ideation phase with functional emotional regulation, successful adjustment to stress and dispositional emotional creativity, as well as the predictive role of creativity for positive emotions and social adjustment. The study examines the effects of modification of positive affect on creativity. Participants write three poems, narrate an infatuation episode, answer a scale of personal growth after this episode and perform a creativity task, answer a flow scale after creativity task and fill a dispositional emotional creativity scale. High and low positive effect was induced by asking subjects to write three poems about high and low positive connotation stimuli. In a neutral condition, tasks were performed without previous affect induction. Subjects on the condition of high positive affect report more positive and less negative emotions, more personal growth (effect size r = .24) and their last poem was rated as more original by judges (effect size r = .33). Mediational analysis showed that positive emotions explain the influence of the manipulation on personal growth - positive affect correlates r = .33 to personal growth. The emotional creativity scale correlated to creativity scores of the creative task (r = .14), to the creativity of the narration of the infatuation episode (r = .21). Emotional creativity was also associated, during performing the creativity task, with flow (r = .27) and with affect balance (r = .26). The mediational analysis showed that emotional creativity predicts flow through positive affect. Results suggest that innovation in the phase of ideation is associated with a positive affect balance and satisfactory performance, as well as dispositional emotional creativity is adaptive.

Keywords: Affectivity, creativity, induction, innovation, psychological factors.

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Authors: Piyush Pal, Rahul Dev

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Water is essential for life and fresh water is a finite resource that is becoming scarce day by day even though it is recycled by hydrological cycle. The fresh water reserves are being polluted due to expanding irrigation, industries, urban population and its development. Contaminated water leads to several health problems. With the increasing demand of fresh water, solar distillation is an alternate solution which uses solar energy to evaporate water and then to condense it, thereby collecting distilled water within or outside the same system to use it as potable water. The structure that houses the process is known as a 'solar still'. In this paper, ‘Modified double slope solar still (MDSSS)’ & 'Modified double slope basin type multiwick solar still (MDSBMSS)' have been designed to convert saline, brackish water into drinking water. In this work two different modified solar stills are fabricated to study the performance of these solar stills. For modification of solar stills, Fibre Reinforced Plastic (FRP) and Acrylic sheets are used. The experiments in MDSBMSS and MDSSS was carried on 10 September 2015 & 5 November 2015 respectively. Performances of the stills were investigated. The amount of distillate has been found 3624 Ml/day in MDSBMSS on 10 September 2015 and 2400 Ml/day in MDSSS on 5 November 2015.

Keywords: Contaminated water, Conventional solar still, Modified solar still, Wick.

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Authors: Z. Abdollahi Biron, P. Pisu

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Connected vehicles are one of the promising technologies for future Intelligent Transportation Systems (ITS). A connected vehicle system is essentially a set of vehicles communicating through a network to exchange their information with each other and the infrastructure. Although this interconnection of the vehicles can be potentially beneficial in creating an efficient, sustainable, and green transportation system, a set of safety and reliability challenges come out with this technology. The first challenge arises from the information loss due to unreliable communication network which affects the control/management system of the individual vehicles and the overall system. Such scenario may lead to degraded or even unsafe operation which could be potentially catastrophic. Secondly, faulty sensors and actuators can affect the individual vehicle’s safe operation and in turn will create a potentially unsafe node in the vehicular network. Further, sending that faulty sensor information to other vehicles and failure in actuators may significantly affect the safe operation of the overall vehicular network. Therefore, it is of utmost importance to take these issues into consideration while designing the control/management algorithms of the individual vehicles as a part of connected vehicle system. In this paper, we consider a connected vehicle system under Co-operative Adaptive Cruise Control (CACC) and propose a fault diagnosis scheme that deals with these aforementioned challenges. Specifically, the conventional CACC algorithm is modified by adding a Kalman filter-based estimation algorithm to suppress the effect of lost information under unreliable network. Further, a sliding mode observer-based algorithm is used to improve the sensor reliability under faults. The effectiveness of the overall diagnostic scheme is verified via simulation studies.

Keywords: Fault diagnostics, communication network, connected vehicles, packet drop out, platoon.

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Authors: Chia-Jung Chen, Rong-Shine Lin, Rong-Guey Chang

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As networking has become popular, Web-learning tends to be a trend while designing a tool. Moreover, five-axis machining has been widely used in industry recently; however, it has potential axial table colliding problems. Thus this paper aims at proposing an efficient web-learning collision detection tool on five-axis machining. However, collision detection consumes heavy resource that few devices can support, thus this research uses a systematic approach based on web knowledge to detect collision. The methodologies include the kinematics analyses for five-axis motions, separating axis method for collision detection, and computer simulation for verification. The machine structure is modeled as STL format in CAD software. The input to the detection system is the g-code part program, which describes the tool motions to produce the part surface. This research produced a simulation program with C programming language and demonstrated a five-axis machining example with collision detection on web site. The system simulates the five-axis CNC motion for tool trajectory and detects for any collisions according to the input g-codes and also supports high-performance web service benefiting from C. The result shows that our method improves 4.5 time of computational efficiency, comparing to the conventional detection method.

Keywords: Collision detection, Five-axis machining, Separating axis.

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Authors: Beena Sethi

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This work involves the degradation of plastic waste in the presence of three different nanocatalysts. A thin film of LLDPE was formed with all three nanocatalysts separately in the solvent. Thermo Gravimetric Analysis (TGA) and Differential Scanning Calorimetric (DSC) analysis of polymers suggest that the presence of these catalysts lowers the degradation temperature and the change mechanism of degradation. Gas chromatographic analysis was carried out for two films. In gas chromatography (GC) analysis, it was found that degradation of pure polymer produces only 32% C3/C4 hydrocarbons and 67.6% C5/C9 hydrocarbons. In the presence of these catalysts, more than 80% of polymer by weight was converted into either liquid or gaseous hydrocarbons. Change in the mechanism of degradation of polymer was observed therefore more C3/C4 hydrocarbons along with valuable feedstock are produced. Adjustment of dose of nanocatalyst, use of nano-admixtures and recycling of catalyst can make this catalytic feedstock recycling method a good tool to get sustainable environment. The obtained products can be utilized as fuel or can be transformed into other useful products. In accordance with the principles of sustainable development, chemical recycling i.e. tertiary recycling of polymers along with the reuse (zero order recycling) of plastics can be the most appropriate and promising method in this direction. The tertiary recycling is attracting much attention from the viewpoint of the energy resource.

Keywords: Degradation, differential scanning calorimetry, feedstock recycling, gas chromatography, thermogravimetric analysis. DSC.

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Authors: Azadeh Vaziri

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Using effluent as a sustainable water resource for agriculture not only could provide part of water needs but also would save the existing water resources, durably. Vinasse, the effluent of ethyl alcohol factories, a by-product, which is derived from sugarcane molasses, is one of the water resources that could be effectively utilized for agricultural purposes. In the present study in order to investigate the application of different ratios of water: vinasse on germination and growth of barley seedlings an experiment was designed in pots with completely randomized design with three replications and control treatment. The consequences of four irrigation levels were studied with different water: effluent ratios (100% water, 90% water & 10% effluent, 75% water & 25% effluent, 50% water & 50% effluent) on germination and growth of barley seedling components in sandy-loam soil. The results showed that, with increasing the percentage of vinasse in the irrigation admixture, the germination percentage in barley seedlings decreased, significantly, so that the decrease in germination in comparison with the control samples in the second and third treatments was 20% and 93.33%, respectively. Seed germination percentage was about 46.66. The average stem length in seedlings was 14.3 mm and the average root length was 9.37 mm. The averages of the soils Electrical Conductivity (EC) and pH which were under irrigation with different ratios of vinasse (dSm-1) were 5.85 and 7.32, respectively, which showed a 76.2% increase in soil salinity.

Keywords: Electrical Conductivity, effluent, germination, vinasse, barley.

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Authors: P. Ninduangdee, V. I. Kuprianov

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Palm kernel shell is an important bioenergy resource in Thailand. However, due to elevated alkali content in biomass ash, this oil palm residue shows high tendency to bed agglomeration in a fluidized-bed combustion system using conventional bed material (silica sand). In this study, palm kernel shell was burned in the conical fluidized-bed combustor (FBC) using alumina and dolomite as alternative bed materials to prevent bed agglomeration. For each bed material, the combustion tests were performed at 45kg/h fuel feed rate with excess air within 20–80%. Experimental results revealed rather weak effects of the bed material type but substantial influence of excess air on the behavior of temperature, O2, CO, CxHy, and NO inside the reactor, as well as on the combustion efficiency and major gaseous emissions of the conical FBC. The optimal level of excess air ensuring high combustion efficiency (about 98.5%) and acceptable level of the emissions was found to be about 40% when using alumina and 60% with dolomite. By using these alternative bed materials, bed agglomeration can be prevented when burning the shell in the proposed conical FBC. However, both bed materials exhibited significant changes in their morphological, physical and chemical properties in the course of the time.

Keywords: Palm kernel shell, fluidized-bed combustion, alternative bed materials, combustion and emission performance, bed agglomeration prevention.

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Authors: Hyunchul Ahn, Kyoung-Jae Kim

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Corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has been one of the attractive research topics in the literature. In recent years, multiclass classification models such as artificial neural network (ANN) or multiclass support vector machine (MSVM) have become a very appealing machine learning approaches due to their good performance. However, most of them have only focused on classifying samples into nominal categories, thus the unique characteristic of the credit rating - ordinality - has been seldom considered in their approaches. This study proposes new types of ANN and MSVM classifiers, which are named OMANN and OMSVM respectively. OMANN and OMSVM are designed to extend binary ANN or SVM classifiers by applying ordinal pairwise partitioning (OPP) strategy. These models can handle ordinal multiple classes efficiently and effectively. To validate the usefulness of these two models, we applied them to the real-world bond rating case. We compared the results of our models to those of conventional approaches. The experimental results showed that our proposed models improve classification accuracy in comparison to typical multiclass classification techniques with the reduced computation resource.

Keywords: Artificial neural network, Corporate credit rating, Support vector machines, Ordinal pairwise partitioning

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Authors: Futoshi Kakuta, Takashi Ishida

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Sewage sludge is a biomass resource that can create a solid fuel and electricity. Utilizing sewage sludge as a renewable energy can contribute to the reduction of greenhouse gases. In Japan, the "National Plan for the Promotion of Biomass Utilization" and the “Priority Plan for Social Infrastructure Development" were approved at cabinet meetings in December 2010 and August 2012, respectively, to promote the energy utilization of sewage sludge. This study investigated costs and greenhouse gas emission in different sewage sludge treatments with technologies for energy from sewage sludge. Expenses were estimated based on capital costs and O&M costs including energy consumption of solid fuel plants and biogas power generation plants for sewage sludge. Results showed that the cost of sludge digestion treatment with solid fuel technologies was 8% lower than landfill disposal. The greenhouse gas emission of sludge digestion treatment with solid fuel technologies was also 6,390t as CO2 smaller than landfill disposal. Biogas power generation reduced the electricity of a wastewater treatment plant by 30% and the cost by 5%.

Keywords: Global warming counter measure, energy technology, solid fuel production, biogas.

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Authors: Eric P. Jiang

Abstract:

As the Internet continues to grow at a rapid pace as the primary medium for communications and commerce and as telecommunication networks and systems continue to expand their global reach, digital information has become the most popular and important information resource and our dependence upon the underlying cyber infrastructure has been increasing significantly. Unfortunately, as our dependency has grown, so has the threat to the cyber infrastructure from spammers, attackers and criminal enterprises. In this paper, we propose a new machine learning based network intrusion detection framework for cyber security. The detection process of the framework consists of two stages: model construction and intrusion detection. In the model construction stage, a semi-supervised machine learning algorithm is applied to a collected set of network audit data to generate a profile of normal network behavior and in the intrusion detection stage, input network events are analyzed and compared with the patterns gathered in the profile, and some of them are then flagged as anomalies should these events are sufficiently far from the expected normal behavior. The proposed framework is particularly applicable to the situations where there is only a small amount of labeled network training data available, which is very typical in real world network environments.

Keywords: classification, data analysis and mining, network intrusion detection, semi-supervised learning.

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Authors: Chanisada Choosuk, Napisporn Memongkol Runchana Sinthavalai, Fareeda Lambensah

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The objective of this research is to explore the role of actors at the local level in managing the Pre-hospital Emergency Medical Service (EMS) system in Thailand. The research method was done through documentary research, individual interviews, and one forum conducted in each province. This paper uses the case of three provinces located in three regions in Thailand including; Ubon Ratchathani (North-eastern region), Lampang (Northern Region), and Songkhla (Southern Region). The result shows that, recently, the role of the local government in being the service provider for their local people is increasingly concerned. In identifying the key success factors towards the EMS system, it includes; (i) the local executives- vision and influence that the decisions made by them, for both PAO (Provincial Administration Organisation (PAO) and TAO (Tambon Administration Organisation), is vital to address the overall challenges in EMS development, (ii) the administrative system through reforming their working style create the flexibility in running the EMS task, (iii) the network-based management among different agencies at the local level leads to the better EMS practices, and (iv) the development in human resource is very vital in delivering the effective services.

Keywords: Local governments, Management, Emergency Medical Services (EMS), Thailand

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

Abstract:

Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: Binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform.

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Authors: Ang Ling Weay, Mona Masood

Abstract:

This paper discusses the potential benefits of an interactive multimedia information representation in enhancing students’ critical thinking aligned with history reasoning in learning history amongst Secondary School students in Malaysia. Two modes of multimedia information representation were implemented; chronologic and thematic information representations. A qualitative study of an unstructured interview was conducted among two history teachers, one history education lecturer, two i-think experts, and five students from Form Four secondary school. The interview was to elicit their opinions on the implementation of thinking maps and interactive multimedia information representation in history learning. The key elements of the interactive multimedia (e.g. multiple media, user control, interactivity and use of timelines and concept maps) were then considered to improve the learning process. Findings of the preliminary investigation reveal that the interactive multimedia information representations have the potential benefits to be implemented as an instructional resource in enhancing students’ higher order thinking skills (HOTs). This paper concludes by giving suggestions for future work.

Keywords: Multimedia Information Representation, Critical Thinking, History Reasoning, Chronological and Thematic Information Representation.

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Authors: P. Martínez-Nieto, M. Vanegas-Hoyos, M. Zapata-Pineda, J. Robles-Camargo

Abstract:

The aquatic plants are a promising renewable energy resource. Lake Fúquene polluting macrophytes, water hyacinth (Eichhornia crassipes C. Mart.) and Brazilian elodea (Egeria densa Planch.), were saccharifiedby different treatments and fermented to ethanol by native yeasts. Among the tested chemical and biological methods for the saccharification, Pleurotus ostreatus at 10% (m/v) was chosen as the best pre-treatment in both macrophytes (P<0.01). Subsequently 49 yeasts were isolated from Lake Fúquene and nine strains were selected, which presented the highest precipitates characteristic of ethanol in the iodoform test. The fermentations from water hyacinth and Brazilian elodea hydrolysates using these yeasts produced ethanol at a rate between 0.38 to 0.80gL-1h-1 and 0.15 to 0.27gL-1h-1 respectively. The ethanol presence was confirmed by gas chromatography–mass spectrometry. The nine yeasts chosen were preliminarily identified as belonging to the genera Candida spp., Brettanomyces sp. and Hansenula spp.

Keywords: Bio-ethanol, Chemical hydrolysis, Invasive aquatic macrophytes, Native yeasts fermenting, P. ostreatus

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