A Hybrid System of Hidden Markov Models and Recurrent Neural Networks for Learning Deterministic Finite State Automata

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence/pattern recognition/classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Modelling of Designing a Conceptual Schema for Multimodal Freight Transportation Information System

Modelling of building processes of a multimodal freight transportation support information system is discussed based on modern CASE technologies. Functional efficiencies of ports in the eastern part of the Black Sea are analyzed taking into account their ecological, seasonal, resource usage parameters. By resources, we mean capacities of berths, cranes, automotive transport, as well as work crews and neighbouring airports. For the purpose of designing database of computer support system for Managerial (Logistics) function, using Object-Role Modeling (ORM) tool (NORMA–Natural ORM Architecture) is proposed, after which Entity Relationship Model (ERM) is generated in automated process. Software is developed based on Process-Oriented and Service-Oriented architecture, in Visual Studio.NET environment.

Influence of Thermal Damage on the Mechanical Strength of Trimmed CFRP

Carbon Fiber Reinforced Plastics (CFRPs) are widely used for advanced applications, in particular in aerospace, automotive and wind energy industries. Once cured to near net shape, CFRP parts need several finishing operations such as trimming, milling or drilling in order to accommodate fastening hardware and meeting the final dimensions. The present research aims to study the effect of the cutting temperature in trimming on the mechanical strength of high performance CFRP laminates used for aeronautics applications. The cutting temperature is of great importance when dealing with trimming of CFRP. Temperatures higher than the glass-transition temperature (Tg) of the resin matrix are highly undesirable: they cause degradation of the matrix in the trimmed edges area, which can severely affect the mechanical performance of the entire component. In this study, a 9.50mm diameter CVD diamond coated carbide tool with six flutes was used to trim 24-plies CFRP laminates. A 300m/min cutting speed and 1140mm/min feed rate were used in the experiments. The tool was heated prior to trimming using a blowtorch, for temperatures ranging from 20°C to 300°C. The temperature at the cutting edge was measured using embedded KType thermocouples. Samples trimmed for different cutting temperatures, below and above Tg, were mechanically tested using three-points bending short-beam loading configurations. New cutting tools as well as worn cutting tools were utilized for the experiments. The experiments with the new tools could not prove any correlation between the length of cut, the cutting temperature and the mechanical performance. Thus mechanical strength was constant, regardless of the cutting temperature. However, for worn tools, producing a cutting temperature rising up to 450°C, thermal damage of the resin was observed. The mechanical tests showed a reduced mean resistance in short beam configuration, while the resistance in three point bending decreases with increase of the cutting temperature.

NSBS: Design of a Network Storage Backup System

The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and the snapshot and hierarchical index are used in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Genetic Algorithm and Padé-Moment Matching for Model Order Reduction

A mixed method for model order reduction is presented in this paper. The denominator polynomial is derived by matching both Markov parameters and time moments, whereas numerator polynomial derivation and error minimization is done using Genetic Algorithm. The efficiency of the proposed method can be investigated in terms of closeness of the response of reduced order model with respect to that of higher order original model and a comparison of the integral square error as well.

Wicking and Evaporation of Liquids in Knitted Fabrics: Analytic Solution of Capillary Rise Restrained by Gravity and Evaporation

Wicking and evaporation of water in porous knitted fabrics is investigated by combining experimental and analytical approaches: The standard wicking model from Lucas and Washburn is enhanced to account for evaporation and gravity effects. The goal is to model the effect of gravity and evaporation on wicking using simple analytical expressions and investigate the influence of fabrics geometrical parameters, such as porosity and thickness on evaporation impact on maximum reachable height values. The results show that fabric properties have a significant influence on evaporation effect. In this paper, an experimental study of determining water kinetics from different knitted fabrics were gravimetrically investigated permitting the measure of the mass and the height of liquid rising in fabrics in various atmospheric conditions. From these measurements, characteristic pore parameters (capillary radius and permeability) can be determined.

Integrated Modeling Approach for Energy Planning and Climate Change Mitigation Assessment in the State of Florida

An integrated modeling approach was used in this study for energy planning and climate change mitigation assessment. The main objective of this study was to develop various green-house gas (GHG) mitigations scenarios in the energy demand and supply sectors for the state of Florida. The Long range energy alternative planning (LEAP) model was used in this study to examine the energy alternative and GHG emissions reduction scenarios for short and long term (2010-2050). One of the energy analysis and GHG mitigation scenarios was developed by taking into account the available renewable energy resources potential for power generation in the state of Florida. This will help to compare and analyze the GHG reduction measure against “Business As Usual” and ‘State of Florida Policy” scenarios. Two master scenarios: “Electrification” and “Energy efficiency and Lifestyle” were developed through combination of various mitigation scenarios: technological changes and energy efficiency and conservation. The results show a net reduction of the energy demand and GHG emissions by adopting these two energy scenarios compared to the business as usual.

Optimizing PID Parameters Using Harmony Search

Optimizing the parameters in the controller plays a vital role in the control theory and its applications. Optimizing the PID parameters is finding out the best value from the feasible solutions. Finding the optimal value is an optimization problem. Inverted Pendulum is a very good platform for control engineers to verify and apply different logics in the field of control theory. It is necessary to find an optimization technique for the controller to tune the values automatically in order to minimize the error within the given bounds. In this paper, the algorithmic concepts of Harmony search (HS) and Genetic Algorithm (GA) have been analyzed for the given range of values. The experimental results show that HS performs well than GA.

MHD Mixed Convection in a Vertical Porous Channel

This work deals with the problem of MHD mixed convection in a completely porous and differentially heated vertical channel. The model of Darcy-Brinkman-Forchheimer with the Boussinesq approximation is adopted and the governing equations are solved by the finite volume method. The effects of magnetic field and buoyancy force intensities are given by the Hartmann and Richardson numbers respectively, as well as the Joule heating represented by Eckert number on the velocity and temperature fields, are examined. The main results show an augmentation of heat transfer rate with the decrease of Darcy number and the increase of Ri and Ha when Joule heating is neglected.

The Effects of Wood Ash on Ignition Point of Wood

The effects of wood ash from five common tropical woods on the ignition point of four common tropical woods in Nigeria were investigated. The ash and moisture contents of the wood sawdust from Mahogany (Khaya ivorensis), Opepe (Sarcocephalus latifolius), Abura (Mitragyna ciliata), Rubber (Heavea brasilensis) and Poroporo (Sorghum bicolour) used, were determined using a furnace (Vecstar furnaces, model ECF2, serial no. f3077) and oven (Genlab laboratory oven, model MINO/040) respectively. The metal contents of the five wood sawdust ash samples were determined using a Perkin Elmer optima 3000 dv atomic absorption spectrometer while the ignition points were determined using Vecstar furnaces model ECF2. Poroporo had the highest ash content, 2.263g while rubber had the least, 0.710g. The results for the moisture content range from 2.971g to 0.903g. Magnesium metal had the highest concentration of all the metals, in all the wood ash samples; with mahogany ash having the highest concentration, 9.196ppm while rubber ash had the least concentration of magnesium metal, 2.196 ppm. The ignition point results showed that the wood ashes from mahogany and opepe increased the ignition points of the test wood samples, Danta (Nesogordonia papaverifera), Ekpaya, Akomu (Pycnanthus angolensis) and Oleku when coated on them while the ashes from poroporo, rubber and abura decreased the ignition points of the test wood samples when coated on them. However, Opepe saw dust ash decreased the ignition point in one of the test wood samples, suggesting that the metal content of the test wood sample was more than that of the Opepe saw dust ash. Therefore, Mahogany and Opepe saw dust ashes could be used in the surface treatment of wood to enhance their fire resistance or retardancy. However, the caution to be exercised in this application is that the metal content of the test wood samples should be evaluated as well.

Neural Networks-Based Acoustic Annoyance Model for Laptop Hard Disk Drive

Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and threedimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who are the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system, which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Theoretical Literature Review on Lack of Cardiorespiratory Fitness and Its Effects on Children

The purpose of this theoretical literature review is to study the relevant academic literature on lack of cardiorespiratory fitness and its effects on children. The total of thirty eight relevant documents were identified and considered for this review which nineteen of those were original research articles published in peer reviewed journals. The other nineteen articles were statistical documents. This literature review is structured to examine 5 effects in deficiency of cardiorespiratory fitness in school aged children (A) Relative Age Effect (RAE), (B) Obesity, (C) Inadequate fitness level (D) Unhealthy life style, and (E) Academics. The categories provide a theoretical framework for future studies where results are driven from the literature review. The study discusses that regular physical fitness assists children and adolescents to develop healthy physical activity behaviors which can be sustained throughout adult life. Conclusion suggests that advocacy for increasing physical activity and decreasing sedentary behaviors at school and home are necessary.

Experimental Investigation with Different Inclination Angles on Copper Oscillating Heat Pipes Performance Using Fe2O3/Kerosene under Magnetic Field

This paper presents the result of an experimental investigation regarding the use of Fe2O3 nanoparticles added to kerosene as a working fluid, under magnetic field for Copper Oscillating Heat pipe with inclination angle of 0°(horizontal), 15°, 30°,45°, 60°,75° and 90° (vertical). The following were examined; measure the temperature distribution and heat transfer rate on Oscillating Heat Pipe (OHP), with magnetic field under different angles. Results showed that the addition of Fe2O3 nanoparticles under magnetic field improved thermal performance of OHP especially in 75°.

Power Ultrasound Application on Convective Drying of Banana (Musa paradisiaca), Mango (Mangifera indica L.) and Guava (Psidium guajava L.)

High moisture content in fruits generates post-harvest problems such as mechanical, biochemical, microbial and physical losses. Dehydration, which is based on the reduction of water activity of the fruit, is a common option for overcoming such losses. However, regular hot air drying could affect negatively the quality properties of the fruit due to the long residence time at high temperature. Power ultrasound (US) application during the convective drying has been used as a novel method able to enhance drying rate and, consequently, to decrease drying time. In the present study, a new approach was tested to evaluate the effect of US on the drying time, the final antioxidant activity (AA) and the total polyphenol content (TPC) of banana slices (BS), mango slices (MS) and guava slices (GS). There were also studied the drying kinetics with nine different models from which water effective diffusivities (Deff) (with or without shrinkage corrections) were calculated. Compared with the corresponding control tests, US assisted drying for fruit slices showed reductions in drying time between 16.23 and 30.19%, 11.34 and 32.73%, and 19.25 and 47.51% for the MS, BS and GS respectively. Considering shrinkage effects, Deff calculated values ranged from 1.67*10-10 to 3.18*10-10 m2/s, 3.96*10-10 and 5.57*10-10 m2/s and 4.61*10-10 to 8.16*10-10 m2/s for the BS, MS and GS samples respectively. Reductions of TPC and AA (as DPPH) were observed compared with the original content in fresh fruit data in all kinds of drying assays.

An Improved Scheduling Strategy in Cloud Using Trust Based Mechanism

Cloud Computing refers to applications delivered as services over the internet, and the datacenters that provide those services with hardware and systems software. These were earlier referred to as Software as a Service (SaaS). Scheduling is justified by job components (called tasks), lack of information. In fact, in a large fraction of jobs from machine learning, bio-computing, and image processing domains, it is possible to estimate the maximum time required for a task in the job. This study focuses on Trust based scheduling to improve cloud security by modifying Heterogeneous Earliest Finish Time (HEFT) algorithm. It also proposes TR-HEFT (Trust Reputation HEFT) which is then compared to Dynamic Load Scheduling.

Transformation of Aluminum Unstable Oxyhydroxides in Ultrafine α-Al2O3 in Presence of Various Seeds

Ceramic obtained on the base of aluminum oxide has wide application range, because it has unique properties, for example, wear-resistance, dielectric characteristics, and exploitation ability at high temperatures and in corrosive atmosphere. Low temperature synthesis of α-Al2O3 is energo-economical process and it is topical for developing technologies of corundum ceramics fabrication. In the present work possibilities of low temperature transformation of oxyhydroxides in α-Al2O3, during the presence of small amount of rare–earth elements compounds (also Th, Re), have been discussed. Aluminum unstable oxyhydroxides have been obtained by hydrolysis of aluminium isopropoxide, nitrates, sulphate, and chloride in alkaline environment at 80-90ºC temperatures. β-Al(OH)3 has been received from aluminum powder by ultrasonic development. Drying of oxyhydroxide sol has been conducted with presence of various types seeds, which amount reaches 0,1-0,2% (mas). Neodymium, holmium, thorium, lanthanum, cerium, gadolinium, disprosium nitrates and rhenium carbonyls have been used as seeds and they have been added to the sol specimens in amount of 0.1-0.2% (mas) calculated on metals. Annealing of obtained gels is carried out at 70– 1100ºC for 2 hrs. The same specimen transforms in α-Al2O3 at 1100ºC. At this temperature in case of presence of lanthanum and gadolinium transformation takes place by 70-85%. In case of presence of thorium stabilization of γ-and θ-phases takes place. It is established, that thorium causes inhibition of α-phase generation at 1100ºC, and at the time when in all other doped specimens α-phase is generated at lower temperatures (1000-1050ºC). Synthesis of various type compounds and simultaneous consolidation has developed in the furnace of OXY-GON. Composite materials containing oxide and non-oxide components close to theoretical data have been obtained in this furnace respectively. During the work the following devices have been used: X-ray diffractometer DRON-3M (Cu-Kα, Ni filter, 2º/min), High temperature vacuum furnace OXY-GON, electronic scanning microscopes Nikon ECLIPSE LV 150, NMM-800TRF, planetary mill Pulverisette 7 premium line, SHIMADZU Dynamic Ultra Micro Hardness Tester, DUH-211S, Analysette 12 Dyna sizer.

Efficient and Timely Mutual Authentication Scheme for RFID Systems

The Radio Frequency Identification (RFID) technology has a diverse base of applications, but it is also prone to security threats. There are different types of security attacks which limit the range of the RFID applications. For example, deploying the RFID networks in insecure environments could make the RFID system vulnerable to many types of attacks such as spoofing attack, location traceability attack, physical attack and many more. Therefore, security is often an important requirement for RFID systems. In this paper, RFID mutual authentication protocol is implemented based on mobile agent technology and timestamp, which are used to provide strong authentication and integrity assurances to both the RFID readers and their corresponding RFID tags. The integration of mobile agent technology and timestamp provides promising results towards achieving this goal and towards reducing the security threats in RFID systems.

A Methodology for Automatic Diversification of Document Categories

Recently, numerous documents including large volumes of unstructured data and text have been created because of the rapid increase in the use of social media and the Internet. Usually, these documents are categorized for the convenience of users. Because the accuracy of manual categorization is not guaranteed, and such categorization requires a large amount of time and incurs huge costs. Many studies on automatic categorization have been conducted to help mitigate the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorize complex documents with multiple topics because they work on the assumption that individual documents can be categorized into single categories only. Therefore, to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, the learning process employed in these studies involves training using a multi-categorized document set. These methods therefore cannot be applied to the multi-categorization of most documents unless multi-categorized training sets using traditional multi-categorization algorithms are provided. To overcome this limitation, in this study, we review our novel methodology for extending the category of a single-categorized document to multiple categorizes, and then introduce a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Dry Relaxation Shrinkage Prediction of Bordeaux Fiber Using a Feed Forward Neural

The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes is included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

An Investigation into the Impact of Techno-Entrepreneurship Education on Self-Employment

Research has shown that techno-entrepreneurship is economically significant. Therefore, it is suggested that teaching techno-entrepreneurship may be important because such programmes would prepare current and future generations of learners to recognise and act on high-technology opportunities. Education in technoentrepreneurship may increase the knowledge of how to start one’s own enterprise and recognise the technological opportunities for commercialisation to improve decision-making about starting a new venture; also it influence decisions about capturing the business opportunities and turning them into successful ventures. Universities can play a main role in connecting and networking technoentrepreneurship students towards a cooperative attitude with real business practice and industry knowledge. To investigate and answer whether education for techno-entrepreneurs really helps, this paper choses a comparison of literature reviews as its method of research. After reviewing literature related to the impact of technoentrepreneurship education on self-employment 6 studies which had similar aim and objective to this paper were. These particular papers were selected based on a keywords search and as their aim, objectives, and gaps were close to the current research. In addition, they were all based on the influence of techno-entrepreneurship education in self-employment and intention of students to start new ventures. The findings showed that teaching techno-entrepreneurship education may have an influence on students’ intention and their future self-employment, but which courses should be covered and the duration of programmes, needs further investigation.