Search results for: patient related elbow evaluation scale

Authors: Florian Müller, Christian Kukla, Thomas Lucyshyn, Clemens Holzer

Abstract:

In this paper, the influencing parameters of a novel purely mechanical wireless in-mould injection moulding sensor were investigated. The sensor is capable of detecting the melt front at predefined locations inside the mould. The sensor comprises a movable pin which acts as the sensor element generating structure-borne sound triggered by the passing melt front. Due to the sensor design, melt pressure is the driving force. For pressure level measurement during pin movement a pressure transducer located at the same position as the movable pin. By deriving a mathematical model for the mechanical movement, dominant process parameters could be investigated towards their impact on the melt front detection characteristic. It was found that the sensor is not affected by the investigated parameters enabling it for reliable melt front detection. In addition, it could be proved that the novel sensor is in comparable range to conventional melt front detection sensors.

Keywords: Injection Moulding, In-Mould Sensor, Structure-Borne Sound, Wireless Sensor

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Authors: Amalia Suzianti

Abstract:

This research elaborates decision models for product innovation in the early phases, focusing on one of the most widely implemented method in marketing research: conjoint analysis and the related conjoint-based models with special focus on heuristics programming techniques for the development of optimal product innovation. The concept, potential, requirements and limitations of conjoint analysis and its conjoint-based heuristics successors are analysed and the development of conceptual framework of Genetic Algorithm (GA) as one of the most widely implemented heuristic methods for developing product innovations are discussed.

Keywords: Product Innovation, Conjoint Analysis, Heuristic Model, Genetic Algorithm

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Authors: Liping Yang, Curran Crawford, Jr. Ren, Zhengyi Ren

Abstract:

Considering the cost evaluation and the stress analysis, a fuzzy satisfactory optimization (FSO) method has been developed for a hybrid composite flywheel. To evaluate the cost, the cost coefficients of the flywheel components are obtained through calculating the weighted sum of the scores of the material manufacturability, the structure character, and the material price. To express the satisfactory degree of the energy, the cost, and the mass, the satisfactory functions are proposed by using the decline function and introducing a satisfactory coefficient. To imply the different significance of the objectives, the object weight coefficients are defined. Based on the stress analysis of composite material, the circumferential and radial stresses are considered into the optimization formulation. The simulations of the FSO method with different weight coefficients and storage energy density optimization (SEDO) method of a flywheel are contrasted. The analysis results show that the FSO method can satisfy different requirements of the designer and the FSO method with suitable weight coefficients can replace the SEDO method.

Keywords: Flywheel energy storage, fuzzy, optimization, stress analysis.

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Authors: Masaki Yamaguchi, Akira Ito, Noriaki Okamoto, Yoshinori Kawabe, Masamichi Kamihira

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Heat-inducible gene expression vectors are useful for hyperthermia-induced cancer gene therapy, because the combination of hyperthermia and gene therapy can considerably improve the therapeutic effects. In the present study, we developed an enhanced heat-inducible transgene expression system in which a heat-shock protein (HSP) promoter and tetracycline-responsive transactivator were combined. When the transactivator plasmid containing the tetracycline-responsive transactivator gene was co-transfected with the reporter gene expression plasmid, a high level of heat-induced gene expression was observed compared with that using the HSP promoter without the transactivator. In vitro evaluation of the therapeutic effect using HeLa cells showed that heat-induced therapeutic gene expression caused cell death in a high percentage of these cells, indicating that this strategy is promising for cancer gene therapy.

Keywords: Inducible gene expression, Gene therapy, Hyperthermia, Heat shock protein, Tetracycline transactivator.

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Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

Abstract:

This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: Land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle.

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Authors: N. David, H. O. Gao

Abstract:

Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.

Keywords: Air pollution, commercial microwave links, rainfall.

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Authors: Sunmyeng Kim

Abstract:

IEEE 802.11a/b/g standards provide multiple transmission rates, which can be changed dynamically according to the channel condition. Cooperative communications were introduced to improve the overall performance of wireless LANs with the help of relay nodes with higher transmission rates. The cooperative communications are based on the fact that the transmission is much faster when sending data packets to a destination node through a relay node with higher transmission rate, rather than sending data directly to the destination node at low transmission rate. To apply the cooperative communications in wireless LAN, several MAC protocols have been proposed. Some of them can result in collisions among relay nodes in a dense network. In order to solve this problem, we propose a new protocol. Relay nodes are grouped based on their transmission rates. And then, relay nodes only in the highest group try to get channel access. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and collision probability.

Keywords: Cooperative communications, MAC protocol, relay node, WLAN.

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Authors: Kazuki Murakami, Takashige Nakamura, Noriko Sakamoto, Kunio Aizawa

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A Watson-Crick automaton is recently introduced as a computational model of DNA computing framework. It works on tapes consisting of double stranded sequences of symbols. Symbols placed on the corresponding cells of the double-stranded sequences are related by a complimentary relation. In this paper, we investigate a variation of Watson-Crick automata in which both heads read the tape in reverse directions. They are called reverse Watson-Crick finite automata (RWKFA). We show that all of following four classes, i.e., simple, 1-limited, all-final, all-final and simple, are equal to non-restricted version of RWKFA.

Keywords: automaton, DNA computing, formal languages, Watson-Crick automaton

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Authors: S. Qaedi, S. Seyedtabaii

Abstract:

Non-Destructive evaluation of in-service power transformer condition is necessary for avoiding catastrophic failures. Dissolved Gas Analysis (DGA) is one of the important methods. Traditional, statistical and intelligent DGA approaches have been adopted for accurate classification of incipient fault sources. Unfortunately, there are not often enough faulty patterns required for sufficient training of intelligent systems. By bootstrapping the shortcoming is expected to be alleviated and algorithms with better classification success rates to be obtained. In this paper the performance of an artificial neural network, K-Nearest Neighbour and support vector machine methods using bootstrapped data are detailed and shown that while the success rate of the ANN algorithms improves remarkably, the outcome of the others do not benefit so much from the provided enlarged data space. For assessment, two databases are employed: IEC TC10 and a dataset collected from reported data in papers. High average test success rate well exhibits the remarkable outcome.

Keywords: Dissolved gas analysis, Transformer incipient fault, Artificial Neural Network, Support Vector Machine (SVM), KNearest Neighbor (KNN)

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Authors: Amin Almasi

Abstract:

Design and evaluation of reciprocating compressors should include a pulsation study. The object is to ensure that predicted pulsation levels meet guidelines to limit vibration, shaking forces, noise, associated pressure drops, horsepower losses and fabrication cost and time to acceptable levels. This paper explains procedures and recommendations to select and size pulsation suppression devices to obtain optimum arrangement in terms of pulsation, vibration, shaking forces, performance, reliability, safety, operation, maintenance and commercial conditions. Model and advanced formulations for pulsation study are presented. The effect of the full fluid dynamic model on the prediction of pulsation waves and resulting frequency spectrum distributions are discussed. Advanced and optimum methods of controlling pulsations are highlighted. Useful recommendations and guidelines for pulsation control, piping pulsation analysis, pulsation vessel design, shaking forces, low pressure drop orifices, pulsation study report and devices to mitigate pulsation and shaking problems are discussed.

Keywords: Pulsation, Reciprocating Compressor.

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Authors: F.S.Tashimova, A. Mirzabekova, Z. Ismagambetova, Y. Massanov, Z. Gabit

Abstract:

In the globalization process, when the struggle for minds and values of the people is taking place, the impact of the virtual space can cause unexpected effects and consequences in the process of adjustment of young people in this world. Their special significance is defined by unconscious influence on the underlying process of meaning and therefore the values preached by them are much more effective and affect both the personal characteristics and the peculiarities of adjustment process. Related to this the challenge is to identify factors influencing the reflection characteristics of virtual subjects and measures their impact on the personal characteristics of the students.

Keywords: Coping behavior, overcoming, personalization (representation), psychological defense, values, virtual space, virtual subject, subjective reflection.

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Authors: Cesar H. Ortega Jimenez, Ignacio Eguia Salinas, Pedro Garrido Vega, Jose A. Dominguez Machuca

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The aim of this study is to identify the conditions of implementation for reconfigurability in summarizing past flexible manufacturing systems (FMS) research by drawing overall conclusions from many separate High Performance Manufacturing (HPM) studies. Meta-analysis will be applied to links between HPM programs and their practices related to FMS and manufacturing performance with particular reference to responsiveness performance. More specifically, an application of meta-analysis will be made with reference to two of the main steps towards the development of an empirically-tested theory: testing the adequacy of the measurement of variables and testing the linkages between the variables.

Keywords: FMS (flexible manufacturing system), HPM (highperformance manufacturing), reconfigurability, RMS (reconfigurablemanufacturing system), responsiveness

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Authors: Marina Diković

Abstract:

By giving personal opinions, suggestions and criticism through e-democracy, young people can reinforce the adoption of decisions which they have an impact on. The purpose of this research was to examine the opinion of university students about the possibility of their decision-making by using information and communication technology (ICT). The questionnaire examined young people's values and behaviour associated with e-democracy and the related decision-making. Students are most active online when it comes to finding information connected with their academic responsibilities, but less frequently take part in democratic processes in society, both at the national and local level. E-democracy as a tool can be learned in programmes of Human Rights Education and Citizenship Education. 

Keywords: Active citizens, e-democracy, information and communication technology, university students.

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Authors: M. Almohaimeed, Y. Alhaidari, H. Alhamdan, A. Alfaries, A. Ater Kranov

Abstract:

A university-wide survey to obtain baseline data regarding the perceptions of key terms related to e-learning and distance learning among students, faculty and staff was conducted to help achieve the goals of Princess Nourah bint Abdulrahman University’s and the Kingdom of Saudi Arabia’s National Center for e-learning and Distance Learning. This paper comprises a relevant literature review, the survey methodology, preliminary data analysis, discussion, and recommendations for further research. The major findings indicate a deep and wide differentiation of understanding among users of critical key terms.

Keywords: E-learning, distance learning, on-line learning, perceptions of learning environments.

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Authors: Emad Hazbkhah, Abdolreza Zahiri, Hossein Ghorbanizade Kharazi, Afshin Kiani

Abstract:

Establishing pumping stations is one of the most common ways of providing water from rivers. There are many issues involved in the design and operation of pumping stations most important of which is the problem of sedimentation. One of the significant issues which must be taken into consideration in designing pumping stations is the operation method and technical matters related to it. Safety and convenience of operation is one of the issues that must be always considered by the designer. Some of the major issues in making decisions regarding the type of design for the station are geographical condition, the location of the station and availability of experts in maintenance and operation of the station. Dimensions of the station must allow free movement for checking and operating pumps after installation of pumps and plumbing system.

Keywords: Boneh Basht, Iran, pumping station.

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Authors: Mandla T. Nene, Edgar.Jembere, Matthew O. Adigun, Themba Shezi, Siyabonga S. Cebekhulu

Abstract:

The drastic increase in the usage of SMS technology has led service providers to seek for a solution that enable users of mobile devices to access services through SMSs. This has resulted in the proposal of solutions towards SMS-based service invocation in service oriented environments. However, the dynamic nature of service-oriented environments coupled with sudden load peaks generated by service request, poses performance challenges to infrastructures for supporting SMS-based service invocation. To address this problem we adopt load balancing techniques. A load balancing model with adaptive load balancing and load monitoring mechanisms as its key constructs is proposed. The load balancing model then led to realization of Least Loaded Load Balancing Framework (LLLBF). Evaluation of LLLBF benchmarked with round robin (RR) scheme on the queuing approach showed LLLBF outperformed RR in terms of response time and throughput. However, LLLBF achieved better result in the cost of high processing power.

Keywords: SMS (Short Message Service), LLLBF (Least Loaded Load Balancing Framework), Service Oriented Computing (SOC).

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Authors: Abeer Aljohani

Abstract:

The COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred as corona virus which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as Omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. Numerous COVID-19 cases have produced a huge burden on hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease based on the symptoms and medical history of the patient. As machine learning is a widely accepted area and gives promising results for healthcare, this research presents an architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard University of California Irvine (UCI) dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques on the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and Principal Component Analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, Receiver Operating Characteristic (ROC) and Area under Curve (AUC). The results depict that Decision tree, Random Forest and neural networks outperform all other state-of-the-art ML techniques. This result can be used to effectively identify COVID-19 infection cases.

Keywords: Supervised machine learning, COVID-19 prediction, healthcare analytics, Random Forest, Neural Network.

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Authors: Chit Su Htwe, Win Htay

Abstract:

The iris recognition technology is the most accurate, fast and less invasive one compared to other biometric techniques using for example fingerprints, face, retina, hand geometry, voice or signature patterns. The system developed in this study has the potential to play a key role in areas of high-risk security and can enable organizations with means allowing only to the authorized personnel a fast and secure way to gain access to such areas. The paper aim is to perform the iris region detection and iris inner and outer boundaries localization. The system was implemented on windows platform using Visual C# programming language. It is easy and efficient tool for image processing to get great performance accuracy. In particular, the system includes two main parts. The first is to preprocess the iris images by using Canny edge detection methods, segments the iris region from the rest of the image and determine the location of the iris boundaries by applying Hough transform. The proposed system tested on 756 iris images from 60 eyes of CASIA iris database images.

Keywords: Canny, C#, hough transform, image preprocessing.

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Authors: H.K. Luk, Y.M. Lai, L. Qin, C.W. Chan, Z. Liu, Y.P. Huang, Y.P. Zheng

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Ultrasound is useful in demonstrating bone mineral density of regenerating osseous tissue as well as structural alterations. A proposed ultrasound method, which included ultrasonography and acoustic parameters measurement, was employed to evaluate its efficacy in monitoring the bone callus changes in a rabbit tibial distraction osteogenesis (DO) model. The findings demonstrated that ultrasonographic images depicted characteristic changes of the bone callus, typical of histology findings, during the distraction phase. Follow-up acoustic parameters measurement of the bone callus, including speed of sound, reflection and attenuation, showed significant linear changes over time during the distraction phase. The acoustic parameters obtained during the distraction phase also showed moderate to strong correlation with consolidated bone callus density and micro-architecture measured by micro-computed tomography at the end of the consolidation phase. The results support the preferred use of ultrasound imaging in the early monitoring of bone callus changes during DO treatment.

Keywords: Bone Callus Growth, Rabbit Tibial DistractionOsteogenesis, Ultrasonography, Ultrasonometry

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Authors: Michiko Miyamoto

Abstract:

The market for "functional foods" and "foods with functional claims" that are effective in maintaining and improving health, has expanded year by year due to the entry of major food and beverage manufacturers following the introduction of the specified health food system in 1991 in Japan. To bring health claims related products or services to the market, it is necessary to let consumers to learn about these products or services; an effective marketing through advertising are important. This research proposes a framework for an effective advertisement medium for the food supplement industry by using survey data of 2,500 people.

Keywords: Functional foods, dietary supplements, marketing strategy, structural equation modeling.

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Authors: Takeshi Takeda

Abstract:

The author conducted post-test analysis with the RELAP5/MOD3.3 code for an experiment using the ROSA/LSTF (rig of safety assessment/large-scale test facility) that simulated a 1% cold leg small-break loss-of-coolant accident under the failure of scram in a pressurized water reactor. The LSTF test assumed total failure of high-pressure injection system of emergency core cooling system. In the LSTF test, natural circulation contributed to maintain core cooling effect for a relatively long time until core uncovery occurred. The post-test analysis result confirmed inadequate prediction of the primary coolant distribution. The author created the phenomena identification and ranking table (PIRT) for each component. The author investigated the influences of uncertain parameters determined by the PIRT on the cladding surface temperature at a certain time during core uncovery within the defined uncertain ranges.

Keywords: LSTF, LOCA, scram, RELAP5.

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Authors: Bharat Raj Singh, Onkar Singh

Abstract:

This paper deals with new concept of using compressed atmospheric air as a zero pollution power source for running motorbikes. The motorbike is equipped with an air turbine in place of an internal combustion engine, and transforms the energy of the compressed air into shaft work. The mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine is presented in this paper. The effect of isobaric admission and adiabatic expansion of high pressure air for different rotor to casing diameter ratios with respect to different vane angles (number of vanes) have been considered and analyzed. It is found that the shaft work output is optimum for some typical values of rotor / casing diameter ratios at a particular value of vane angle (no. of vanes). In this study, the maximum power is obtained as 4.5kW - 5.3kW (5.5-6.25 HP) when casing diameter is taken 100 mm, and rotor to casing diameter ratios are kept from 0.65 to 0.55. This value of output is sufficient to run motorbike.

Keywords: zero pollution, compressed air, air turbine, vane angle, rotor / casing diameter ratio

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Authors: Nikhil, Bestamin Özkaya, Ari Visa, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

Abstract:

The performance of a sucrose-based H2 production in a completely stirred tank reactor (CSTR) was modeled by neural network back-propagation (BP) algorithm. The H2 production was monitored over a period of 450 days at 35±1 ºC. The proposed model predicts H2 production rates based on hydraulic retention time (HRT), recycle ratio, sucrose concentration and degradation, biomass concentrations, pH, alkalinity, oxidation-reduction potential (ORP), acids and alcohols concentrations. Artificial neural networks (ANNs) have an ability to capture non-linear information very efficiently. In this study, a predictive controller was proposed for management and operation of large scale H2-fermenting systems. The relevant control strategies can be activated by this method. BP based ANNs modeling results was very successful and an excellent match was obtained between the measured and the predicted rates. The efficient H2 production and system control can be provided by predictive control method combined with the robust BP based ANN modeling tool.

Keywords: Back-propagation, biohydrogen, bioprocessmodeling, neural networks.

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Authors: Kien Tsong Chau, Zarina Samsudin, Wan Ahmad Jaafar Wan Yahaya

Abstract:

The paper examined the capability of a prototype of a tangible multimedia system that was augmented with tangible objects in motivating young preschoolers in learning. Preschoolers’ learning behaviour is highly captivated and motivated by external physical stimuli. Hence, conventional multimedia which solely dependent on digital visual and auditory formats for knowledge delivery could potentially place them in inappropriate state of circumstances that are frustrating, boring, or worse, impede overall learning motivations. This paper begins by discussion with the objectives of the research, followed by research questions, hypotheses, ARCS model of motivation adopted in the process of macro-design, and the research instrumentation, Persuasive Multimedia Motivational Scale was deployed for measuring the level of motivation of subjects towards the experimental tangible multimedia. At the close, a succinct description of the findings of a relevant research is provided. In the research, a total of 248 preschoolers recruited from seven Malaysian kindergartens were examined. Analyses revealed that the tangible multimedia system improved preschoolers’ learning motivation significantly more than conventional multimedia. Overall, the findings led to the conclusion that the tangible multimedia system is a motivation conducive multimedia for preschoolers.

Keywords: Tangible multimedia, preschooler, motivation, multimedia.

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Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

Abstract:

Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: Beta distribution, PERT, Monte Carlo Simulation, skewness, project completion time distribution.

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

Abstract:

The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: Joan Iliopoulou-Georgudaki, Chris Theodoropoulos, Danae Venieri, Maria Lagkadinou

Abstract:

Monitoring of microbial flora in aquacultured sea bream, in relation to the physicochemical parameters of the rearing seawater, ended to a model describing the influence of the last to the quality of the fisheries. Fishes were sampled during eight months from four aqua farms in Western Greece and analyzed for psychrotrophic, H2S producing bacteria, Salmonella sp., heterotrophic plate count (PCA), with simultaneous physical evaluation. Temperature, dissolved oxygen, pH, conductivity, TDS, salinity, NO3 - and NH4 + ions were recorded. Temperature, dissolved oxygen and conductivity were correlated, respectively, to PCA, Pseudomonas sp. and Shewanella sp. counts. These parameters were the inputs of the model, which was driving, as outputs, to the prediction of PCA, Vibrio sp., Pseudomonas sp. and Shewanella sp. counts, and fish microbiological quality. The present study provides, for the first time, a ready-to-use predictive model of fisheries hygiene, leading to an effective management system for the optimization of aquaculture fisheries quality.

Keywords: Microbiological, model, physicochemical, Seabream.

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Authors: Jatinderkumar R. Saini, Apurva A. Desai

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In recent times, the problem of Unsolicited Bulk Email (UBE) or commonly known as Spam Email, has increased at a tremendous growth rate. We present an analysis of survey based on classifications of UBE in various research works. There are many research instances for classification between spam and non-spam emails but very few research instances are available for classification of spam emails, per se. This paper does not intend to assert some UBE classification to be better than the others nor does it propose any new classification but it bemoans the lack of harmony on number and definition of categories proposed by different researchers. The paper also elaborates on factors like intent of spammer, content of UBE and ambiguity in different categories as proposed in related research works of classifications of UBE.

Keywords: E-mail, Scams, Spam Email, Unsolicited Bulk Email(UBE)

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Authors: Wen Po Cheng, Chi Hua Fu, Ping Hung Chen, Ruey Fang Yu

Abstract:

Recovering resources from water purification sludge (WPS) have been gradually stipulated in environmental protection laws and regulations in many nations. Hence, reusing the WPS is becoming an important topic, and recovering alum from WPS is one of the many practical alternatives. Most previous research efforts have been conducted on studying the amphoteric characteristic of aluminum hydroxide for investigating the optimum pH range to dissolve the Al(III) species from WPS, but it has been lack of reaction kinetics or mechanisms related discussion. Therefore, in this investigation, water purification sludge (WPS) solution was broken by ultrasound to make particle size of reactants smaller, specific surface area larger. According to the reaction kinetics, these phenomena let the dissolved aluminum salt quantity increased and the reaction rate go faster.

Keywords: Aluminum, Acidification, Sludge, Recovery.

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Authors: A. Golmohammadi, B. Jahandideh

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One of the determinants of a firm-s prosperity is the customers- perceived service quality and satisfaction. While service quality is wide in scope, and consists of various dimensions, there may be differences in the relative importance of these dimensions in affecting customers- overall satisfaction of service quality. Identifying the relative rank of different dimensions of service quality is very important in that it can help managers to find out which service dimensions have a greater effect on customers- overall satisfaction. Such an insight will consequently lead to more effective resource allocation which will finally end in higher levels of customer satisfaction. This issue –despite its criticality- has not received enough attention so far. Therefore, using a sample of 240 bank customers in Iran, an artificial neural network is developed to address this gap in the literature. As customers- evaluation of service quality is a subjective process, artificial neural networks –as a brain metaphor- may appear to have a potentiality to model such a complicated process. Proposing a neural network which is able to predict the customers- overall satisfaction of service quality with a promising level of accuracy is the first contribution of this study. In addition, prioritizing the service quality dimensions in affecting customers- overall satisfaction –by using sensitivity analysis of neural network- is the second important finding of this paper.

Keywords: service quality, customer satisfaction, relativeimportance, artificial neural network.

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