IAENG Transactions on Engineering Sciences

The following sections are included:

• PREFACE
• CONTENTS

A finite element analysis of a double layered shell with a circular hole is carried out using a commercial finite element software. The model proposed has been used to perform a stress analysis on three pipes with different sized hole. Moreover, thermal expansion has been implemented in the testing. For the purpose of the research, the elastic properties of the materials have been considered and the results compared with the authors’ previous publication. The outcome of the investigation will benefit towards the design of optimal and sustainable pipes with circular cut outs.

We investigate the processes of quasistatic deformation of aging viscoelastic spherical solids gradually formed by accretion in the centrally symmetric force field of self-gravitation. Neglecting inertial effects and assuming the strains being small, we study the evolution of the stress-strain state of an accreted ball before its growing, at stages of its continuous growth, in pauses between them, and after eventual cease of the growth. Using the earlier constructed mathematical theory of growing bodies, we state corresponding initial-boundary value problems that describe the deformation process of the objects in question in all above indicated time periods. We construct the closed form analytical solution of these problems. We perform numerical computations of the stress-strain state evolution of a growing spherical body for various modes of its growth. We reveal essentially new mechanical effects typical only of growing bodies. One of the primary applications of the presented work results is the problem of estimating the distributions of gravitational stresses within the Earth.

The operating temperature of the tires is an important parameter for both performance and degradation phenomena of the tire compound. The TRT model, able to reproduce accurately the tire thermal dynamics in all the vehicle working conditions, has to be thermally characterized. An appropriate experimental non-destructive procedure, allowing to obtain thermal diffusivity parameters of the different tire layers, is described. A laser is employed in the form of heat supplier on the tire tread surface, while two thermal cameras acquire temperatures reached on both the outer and the inner layers. By means of the above instrumentation layout able to acquire the tire radial and circumferential temperature gradients and a specifically developed physical-mathematical TRTLab model based on the use of Fourier’s equation of diffusion applied to a three-dimensional domain, it is possible to estimate the tire thermal diffusivity. A sensitivity analysis of thermal parameters of the main tire layers is provided, underlining the effects of variation of specific heat and conductivity values upon the thermal dynamics of the entire tire thickness in both transient and steady-state warming conditions.

Afifia popularly called and known as grass were human laborious as it is cut by hand using scythes of sickles, lawn mower is a machine utilizing one or more revolving blades to cut the afifia (grass) surface to an even height. This research work is an extensions of the previous work. The goal remains the same: to efficiently and intelligently mow grass is an environment typically, the lawn mowing the machine uses laming techniques to accomplish its task. Technology has become more affordable and penetrate every aspect of daily life, even in developing country like Nigeria. However many of the users in developing countries are still finding difficulty in using then technologies due to lack of experience as they undergo a technology leap. The aim of this research work explores the approach on designing, development of a motorized Afifia (grass) mowing machine. This research was considered because of the unhygienic environmental conservation and its menace. An estimate of 20N was adopted as the required force to cut lawns. The result found from the design force of the Machine is 85% efficient based on the area mowed per hour which is 390.6m²

Recently, human resource, which is crucial to ensure productivity improvement, became one of the most important competition tools. Employing the labor force in an effective way will provide to benefit from the advantages of productivity improvement. In this aspect, determination and evaluation of the factors affecting labor productivity will ease the right employment of labor force. In the literature, there are numerous researches related with the factors affecting labor productivity. However, in most of these studies motivation theories were neglected and critical factors were not correlated with motivation schemes. The aim of this study is to correlate the factors affecting labor productivity in Turkey with motivation schemes. For this purpose a three-step study was conducted. In the first step, factors affecting labor productivity were categorized under 4 different factors groups named as organizational, economical, socio-physiological and physical, respectively and a questionnaire was administered to craft workers. In the second step, factors affecting labor productivity were categorized under Maslow’s needs named as self-actualization, esteem needs, affiliation-social needs, safety-security needs and physiological needs, respectively. Finally, in the third step factors were investigated by using Herzberg’s Motivation-Hygiene theory which was developed by Herzberg is one of the broadly accepted one.

This work investigated the use of laboratory batch anaerobic digester to derive kinetics parameters for anaerobic co-digestion of sewage sludge and food waste. Laboratory experiment data from 500 ml batch anaerobic digester operating at ambient mesophilic temperature of 37°C and pH of 6.9 was used to derive parameters for Modified Gompertz model. The carbon/nitrogen (C/N) ratio of sewage sludge was found to be 30.77 and food waste to be 15.57. Through co-digestion in ratio of 1:1, the C/N ratio settled at 20.31. The actual biogas yield was found to be 766.6 Nml Biogas/gVS. In the model of biogas production prediction, the kinetics constants of A (Nml Biogas/gVS), μ (Nml Biogas/gVS), λ (day) was 825.73, 75.65, 0.40 respectively with coefficient of determination (R²) of 0.98. Modified Gompertz plot showed better correlation of cumulative biogas production and these results show biogas production can be enhanced from co-digestion of substrates.

To select an optimal solution from the Pareto frontier based on decision-maker preference or responses priority may not be the best practice and may lead to unexpected results in practice due to the variability that is inherent to some optimal solutions. The assessment of optimal solutions reproducibility has been ignored so far, though this information is critical for the decision-maker in the optimal solution selection process. This chapter explores the Quality of Prediction metric usefulness to help him/her in selecting a solution for multiresponse problems. Results from two case studies show that quality of prediction value cannot be ignored.

Time, cost and risk are the main elements that effect the operating margin of the oil and gas companies due to Turnaround Maintenance (TAM). Turnaround Maintenance (TAM) is a methodology for the total shutdown of plant facilities during a pre-defined period to execute inspection actions, replacement and repairs according to Scope of Work (SoW). This paper presents a new methodology for improving TAM scheduling of oil and gas plants. The methodology includes four stages: removing Non-critical Equipment (NE) from reactive maintenance to proactive maintenance, risk-based inspection of Critical Static Equipment (CSE), risk-based failure of Critical Rotating Equipment (CRE), and application of failure distributions. The results from improving TAM scheduling is associated with decreasing duration and increasing interval between TAM leading to improved availability, reliability, operation and maintenance costs and safety risks. The paper presents findings from the TAM model application. The methodology is fairly generic in its approach and can also be adapted for implementation in other oil and gas industries that operate under similar harsh conditions.

Optimum grinding conditions have always been important in producing the best surface finished workpiece. Liquid coolant is absolutely essential for obtaining an excellent surface finish. Unfortunately, large quantities of liquid waste are produced, and in recent times it has become imperative that companies implement appropriate waste disposal measures. This has increased the cost of the grinding process, which has given rise to companies looking for alternative cooling methods. To date, there has only been limited success using other methods which do not rely on copious amounts of liquid coolant. Alternative strategies still require substantial research to produce a ground workpiece with similar surface finish as produced by using traditional coolant. The goal of this research is to discover the best method to reduce the reliance on liquid coolant, while still producing a suitable standard workpiece.

Documenting process flows in a manufacturing environment provides a guide to understanding how processes are interconnected and how materials are handled, thus forming the basis for modelling and optimization in order to simplify the otherwise complex systems particularly in multi-product manufacturing. Research was carried out at a furniture manufacturing company specializing in the production of a wide range of furniture from hardwood. Owing to the multiplicity of processes and the movement of materials in manufacturing environments, the factors affecting such setups increasingly become complex, equally requiring complex techniques to analyze and optimize them. A work study carried out at the company established inherent problems that affected production and were used as the basis for modelling and optimizing the processes, focusing on grouping of workstations depending on functions, predicting performance using simulation and machine distance matrices for a reorganized plant layout. Results obtained after modelling and optimizing the plant layout were useful for production planning and control as well as enhancing the company’s productivity and efficiency.

The aims of this paper are to determine the composition of municipal solid waste (MSW) at the Robinson Deep landfill site (LS) and estimate the economics of setting up a recycling facility. The waste composition study was conducted during the summer period of 2015 at the LS. This was done to determine the quantity of organic wastes that are generated daily as a basis for the waste to energy (WtE) proposition and the quantities of the entire wastes generated for the recycling facilities plan in the City of Johannesburg (CoJ). The samples were classified into nine broad categories. The categories include; paper, organics, plastics, metals, glasses, textiles, construction and demolition (C&D), special care and other wastes. The results of the analysis were classified into two services. The services are Dailies refuse (DR) non-compacted and Round collected refuse (RCR) compacted wastes. The results obtained showed organic wastes to be 14% for the DR and 34% for the RCR. The 14% organic waste generated from the DR was attributed to the consumption patterns of people mostly at work. People in offices tend to buy more packaged food items and a smaller amount of organics are disposed of since wastages are less. The 34% organic wastes from the RCR was attributed to the fact that the majority of the people tend to prepare every of their basic meal from their homes and surplus are made; hence, when the surplus could not be consumed, it is disposed of, as a result, more organics are generated. The economic valuation of the recycling facility was also carried out and this was done on all the waste components to estimate the total cost of setting up a facility to divert all the entire MSWs generated. Based on the results obtained, the total capital investment (TCI) was R 35,643,262.73.

Mathematical model was developed to compare to the Neural Network techniques for predicting ion-exchange process using clinoptilolite. Numerous applications of NNs have been successfully conducted to solve environmental problems. Since it is reliable and robust in capturing the non-linear relationships existing between variables (input/output) in complex systems. Feed Forward Neural Network successfully tracked the non-linear behavior of the ion-exchange process. The predictability of the network was statistically assessed with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that Feed Forward Neural Network modelling techniques could effectively predict and simulate the highly complex system and non-linear process such as the ion-exchange using clinoptilolite.

Membrane reactors offer a promising approach towards achieving green and sustainable gas recovery, separation and conversion with minimal fouling, and minimal energy consumption. In this work, the use of a composite alumina/zeolite membrane for the separation of C₃H₈, N₂, O₂, and CO₂ from CH₄ has been studied. The physical properties of the membrane were investigated by scanning electron microscopy (SEM). The SEM micrographs confirm that the zeolite is distributed homogeneously in the alumina support matrix. Single gas permeation tests were carried out in the pressure range of 0.01 to 0.1 MPa. The Fickian model was applied for evaluating the separation of propane and methane from nitrogen, oxygen, and carbon dioxide. The Fickian approach assumes that the transport diffusivity of gases through the zeolite membrane is dependent on the operating temperature. Therefore, the flux of CO₂, N₂, CH₄, C₃H₈, and O₂ was determined at 372, 473, and 573 K, and the activation energy of these gases was also determined. Experimental results indicated that the temperature indeed affects the flux of gases in the zeolite membrane, and therefore, the Fick’s model can be used to analyse the transport of gases through the zeolite layer.

Increasing climatic changes, exhaustion of natural resources from mining and similar activities, and the insistent growth in population have caused various human and environmental problems. Acid mine drainage (AMD) from mining operations in South Africa and around the world has been known to contribute a number of severe environmental challenges presently in need of dire attention. Pollution and/or contamination from AMD presents a serious risk requiring prevention and mitigation approaches for arresting consequential impacts on environmental and human health. The persistent human and environmental challenges based on AMD problems, created the impetus for the study to investigate the breakthrough curves and percolation parameters of two soils- Kaolinite, Halloysite and Illite/Vermiculite mixed layer (Soil A) and Kaolinite (Soil H) subtropical clayey soils interacted with AMD towards establishing their mineral buffering efficacy for use as natural contaminant barriers in areas under AMD attack. Successive prolonged percolation up to 24 pore volume passage of AMD through the respective soil media were carried out. The results of the study showed that after approximately 2.4 pore volumes of 0.01N CaSO₄, baseline hydraulic conductivities of 1.3 × 10⁻¹¹ m/s and 2.6 × 10⁻¹¹ m/s were obtained for both soils respectively. After AMD infusion, their respective values were found to be within the accepted criterion of 1 × 10⁻⁹ m/s specified for clay/clayey liner construction in South Africa.

This research work was carried out in order to develop an improved motorized nmanu akuoyibo (coconut oil) extracting machine with an ability to grind, break, split akuoyibo/coconut meat. The machine can be used for other oil-bearing seeds such as ground nut and palm kernel. The machine is made up of a plunger, ram dics, expression chamber, electric heater and bearings. The extractor can process 10kg nmanu akuoyibo/coconut oil per hour. An efficiency of 15% was obtained from the akuoyibo/coconut cake of 2.9kg (wet basis) while for dry basis 40% of oil was obtained from the akuoyibo /coconut cake of 2.5kg. The machine is portable, unique in design and can be use for domestic and industrial purposes for commercialization. The machine will create job opportunities for self employment in Nigeria.

In this study, we investigated the design model selection and dimensioning of anaerobic digester for the digestion of sewage sludge from the wastewater treatment plant. The sludge quantification and characterization exercise was undertaken at the point of generation, so as to ascertain the sludge composition. Via the application of the analytical hierarchy process (AHP) technique of multiple-criteria decision analysis (MCDA) on decision matrix approach (DMA) or weighted sum method (WSM) as a decision support tool base on cost, scalability, temperature regulation, ease of construction, operation and maintenance. The most preferred model option for bioenergy design technology was selected from a list of potential alternatives available in the market. Continuous stirred tank reactor (digester) CSTR scored the highest with 79% and was selected for the design in sludge to biogas production. The geometry of the biodigester parameters was comparable with the anaerobic digestion (AD) process.

This research paper reports the effect of laser power on the degree of porosity of the deposited tracks and characterized the specific porous structures of the deposits. The samples were characterized through the microstructure and the porosity analysis. The results revealed that as the laser power was increased, the degree of porosity was however reduced. Prior the characterization process, titanium alloy and boron carbide (Ti6Al4V-B₄C) composites powder were deposited on Ti6Al4V substrate using laser metal deposition (LMD) process through the application of Ytterbium fibre laser system. The laser power was varied between 800 W and 2400 W at interval of 200 W while all other process parameters were kept constant. The maximum capacity of this laser system is 3.0 KW which provides beam size of 4 mm for the control characterization of the deposited samples. The porosity behaviour of various samples at different laser power were observed in which the degree of their porosities varies as the laser power increases. At a laser power of 2200 W, there was no porosity observed in the composite which revealed that there were no unmelted powder presented in the melt pool after solidification for this particular sample. Percentage porosity was significantly reduced from 0.45% to 0.03%.

The influence of laser power on the microstructure and corrosion behavior of Ti6Al4V/W composites in 3.5wt% NaCl solution was investigated. The energy flow rates were varied while every single other parameter was kept steady. The evolving microstructure and the hardness of the composites were studied and reported in this study. The laser power directly influenced the hardness and the microstructure. SEM was utilised to characterise the microstructure of the composite layer formed on the surface of the Ti6Al4V substrate. The microstructure of all the composite layers delivered by the LMD process has upgraded properties compared to the properties of the Ti64l4V substrate. The addition of W particles in the Ti6Al4V composites has improved the potentiodynamic polarisation curve as well as the surface modification.

Industrie 4.0 is increasingly entering the industrial landscape of German Small and Medium- sized Enterprises (SME). However, the right introduction to the subject for the affected enterprises proves to be difficult. For this reason, a holistic approach for introducing the strategic initiative Industrie 4.0 is represented as a “Generic Procedure Model to introduce Industrie 4.0 in Small and Medium-sized Enterprises” (GPMI4.0) [1]. The purpose of this approach is to give SMEs a guidance on how to address Industrie 4.0 in order to identify enterprise-specific technology solutions, to optimize existing processes, to advance existing business models and to exploit new business models.

The Flow Shop Scheduling Problem (FSSP) is a problem that is commonly found by master production scheduling planners in Flexible Manufacturing Systems (FMS). The planner should find the optimal scheduling to carry out a set of jobs in order to satisfy the predefined objective (e.g., makespan). All the jobs are processed in a production line composed of a set of shared machines. Furthermore, the jobs are processed in the same sequence. In order to be able to analyze this problem in a better way, this problem needs to be represented adequately for understanding the relationship among the operations that are carried out. Thus, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation. In this work, we propose a new way to calculate the makespan of FSSP based on timed place PNs.

The increase of renewable energy exploitation is a current topic in the energy field. One of the main obstacles to the use of renewable energy in the global energetic mix is represented by the fluctuating nature of renewable power sources, since power fluctuations are cause of stress for the electric grid. A possibility to widely exploit renewable sources is the implementation of a “smart grid”, consisting in an interconnection of several smart-nodes. To reduce the stochastic effect of the renewable energy source it is possible to equip the nodes an energy storage managed in order to smooth the power peaks. In this regard, a dynamic analysis was carried out in order to integrate the renewable sources with the electric grid. This work presents a simulation model of a smart node consisting in a user power profile, a photovoltaic panel and a battery. Tests were worked out in different node configurations, in order to evaluate the incidence on the energy flows and on the grid distortion factor. Simulations were repeated by implementing the system with an algorithm for home automation in order to exploit intelligently the energy from the renewable source. This algorithm allows to synchronizethe operation of certain loads to the sun irradiation power.

In recent years, micro grid system has received more and more attention internationally. As the most effective form of distributed generations, micro grid system has found wide applications in many areas. Micro grids are low voltage (LV) distribution networks comprising various distributed generators (DGs), storage devices, and controllable loads that can operate either interconnected or isolated from the main distribution grid as a controlled entity. This paper describes the operation of a central controller for micro grids. Different control methods of micro grid system and their advantages and shortcomings are carried out and analyzed. The controller aims to optimize the operation of the micro grid during interconnected operation, that is, maximize its value by optimizing the production of the local DGs and power exchanges with the main distribution grid. Two market policies are assumed including demand side bidding options for controllable loads. The developed optimization of a typical LV case study network operating under various market policies and assuming realistic spot market prices and DG bids reflecting realistic operational costs. A laboratory scale micro grid system is proposed as an example to verify the micro grid control strategy. The operation experimental results show that the laboratory scale micro grid system can operate in gridconnected or islanded mode, with a seamless transfer from one mode to the other, and hence increase the reliability of energy supplies.

3D printing is already well established for printing macro dimension objects. 3D printing is now planned for manufacturing water quality measurement nano-sensors. For this positioning up to the nanometer range is necessary. The motors enabling 3D printing are explored, namely stepper motors. Conventional stepper motors are studied, and their drawbacks mentioned. Motors based on the piezoelectric motor are also introduced and studied. Their high resolution, good force and vacuum operation are their advantages. Piezo-walk motor is selected at present as it is the most suitable. Before proceeding with actual building, computer simulation is done on simplified model of piezo-walk motor to observe nano-motion and resulting effects. Controlled motion of the order of few tens of nanometers are obtained in the software model, under different situations.

The connection of inverters for distributed generation photovoltaic systems to the distribution network creates situations of risk to the loads that are connected to the point of common coupling (PCC) and personals who maintain the power grid. A risk that should be avoided is the supply of electricity, by one or more inverters, to the distribution network after disconnecting the main power grid. The isolation of distributed generation systems that continue to supply the power required by the load at the PCC is known in the literature as islanding. The unintentional islanding can be avoided by using islanding detection techniques. This paper presents a review of chopping factor related to active islanding detection. The main focuses are the study, implementation and analysis of the Active Frequency drift and Active Frequency Drift with Positive Feedback method based on the IEEE 929-2000 standard so as to verify the reliability of anti island methods that implement the chopping factor concept.

The subject of the paper, and at the same time, its purpose is to conduct research in the context of analysis, development of mathematical models and simulation of selected onboard components of the autonomous power system ASE (Autonomous Power System), both in the field of the electric power system EPS (Electric Power System) and in the field of power electronics power supply system PES (Power Electronics System). Sample studies were based on a synchronous electric machine, based on permanent magnets PMSM (Permanent Magnet Synchronous Machine) in the form of an engine or generator, in the field of EPS system and on the basis of the selected multi- pulse rectifier, which is a key element of the PES rectifier system. Based on the above, exemplary simulations of selected components (PMSM, multi- pulse rectifiers) of power supply systems (EPS, PES), selected from the group of civil aircraft companies Airbus (A-380, A-350XWB) and Boeing (B-787) compatible with the concept of more electric aircraft MEA (More- Electric Aircraft) were conducted. Because of the dominant role of civil aviation of major aircraft companies (Boeing, Airbus) in the field of more electric technology MET (More Electric Technology), a key (fully justified) role in this paper has been attributed to civil aviation. The final part of the paper presents the main conclusions resulting from the analysis in the light of the literature of the subject, the development of mathematical models and the simulations of selected components of the on- board power supply system ASE (EPS, PES) compatible with the MEA concept.

Tackling routing misbehavior due to insider attacks in Delay Tolerant Networks becomes very crucial as Delay Tolerant Networks (DTNs) are deployed in battlefield environments and emergency situations to provide critical services. The effect of insider attacks cannot be tackled with traditional approaches as DTN characteristics are different from ad hoc and other wireless networks, wherein connectivity among mobile nodes is not always guaranteed. A novel technique to tackle Black Hole(BH) attacks in DTNs by segregating the simple information like sent and received packets to and from multiple nodes is presented in this paper. Our approach has been evaluated using OMNeT++ simulator with Random Way Point model and the results show that our approach can mitigate black hole attacks efficiently with high detection rate.

The increasing importance of wireless communications, involving electronic devices, has been worldly recognized. Performance is a crucial issue, leading to more reliable and efficient communications. Security is also critically important. New laboratory experiments were performed about several performance aspects of Wi-Fi IEEE 802.11n Open 5 GHz links. Our study contributes to the performance evaluation of this technology, using available equipments (HP V-M200 access points and Linksys WPC600N adapters). New detailed results are presented and discussed, namely at OSI level 4, from TCP and UDP measurements. TCP throughput is measured versus TCP packet length. Jitter and percentage datagram loss are measured versus UDP datagram size. Data comparisons are made for point-to-point, point-to-multipoint and four-node point-to-multipoint links. Conclusions are drawn about performance of the links.

This chapter provides an overview of the Vehicular Ad-hoc Network (VANET) architecture and its Quality of Service (QoS). VANET has attracted a great deal of attention during the last decade because its communication protocols offer good potential for increasing safety and driver assistance. VANET as a foundation for Intelligent Transportation System (ITS) promises many improvements in terms of safety, traffic management, and infotainment. Among these three main categories, safety applications are the most important because they are designed to enhance safety and save lives. As such, safety applications are classified as real-time applications, which must react to events, e.g. accidents, within a certain period of time; otherwise, their implementation will be worthless. To achieve QoS, different layers of the VANET protocol stack have been targeted. This chapter focuses on two important groups of routing protocols, Ad-hoc On-demand Distance Vector (AODV) and Destination-Sequenced Distance Vector (DSDV) at the network layer. These routing protocols are investigated with respect to three QoS parameters: end-to-end delay, packet loss, and packet overhead.

In Wireless Sensor Networks (WSNs), clustering is one of the most power efficient techniques which minimize the transmission ranges of sensor nodes. Instead of sending packets directly to the BS with high power levels, sensor nodes in the sensing filed can be organized in groups (i.e. clusters), where Cluster Heads (CHs) manage the transmission by aggregating the whole group of packets and retransmit them to the Base Station (BS). Therefore, the clustering technique solve the problem that nodes close to the BS consume a large amount of power due to the need to be active most of the time to retransmit packets to the BS (i.e. sink hole problem). In this paper, we propose a novel Raining Energy Cluster Head Selection (RECHS) protocol which is based on a simple Statistical Discrimination (SD) metric which detects collided packets before decoding as well as the Multi-Dimensional Slotted ALOHA (MDSA) MAC protocol which organizes the access to the communication channel. Hence, both reception and transmission power consumption will be minimized remarkably. In addition, in RECHS protocol, a simple Cluster Head (CH) selection algorithm is proposed which is based on the ratio between the remaining energy of every member (node) in a cluster and the initial (start-up) energy as well as the minimum distance between the CH and the sink node. In this paper, we will show how the proposed CH selection mechanism in RECHS protocol along with the SD technique and the MDSA MAC protocol overcomes some well-known protocols such as LEACH where a CH is selected in a distributed (i.e. random) fashion and the MAC protocol is TDMA. In particular, we will show how the performance of RECHS protocol overcomes LEACH protocol in terms of the percentage of alive nodes, the average number of successfully arrived packets to the BS (i.e. the throughput), and the average residual energy of the network per simulation round.

Prolonging lifetime of wireless sensor network becomes very essential for mission critical applications where network nodes are required to monitor and report for a longer period of time rather than becoming dead over a very short period or resulting in network partitioning due to energy depletion. In this paper, we present our model based on swarm Intelligence based efficient routing which associates every node with a threshold energy parameter to control the energy conservation and balancing in wireless sensor network. This threshold parameter plays an important role in ensuring that all the nodes in the neighborhood of a node of concern to participate in packet forwarding periodically resulting in optimal energy balancing and excellent energy conservation among all the participating nodes, thereby extending the lifetime of the network. The performance evaluation of our proposed approach for variation of threshold energy of nodes in the network reflecting different types of load or traffic patterns was carried out using NS-2 Simulator. Our simulation results demonstrate that optimal energy balancing and excellent energy conservation among nodes can be achieved by judiciously controlling the threshold energy associated with the nodes to extend the network lifetime.

This study evaluated the convenience of post-disaster recovery housing complexes constructed in Japan’s Iwate Prefecture following the 2011 Tohoku Earthquake. We expected that five years on from the disaster, the evacuees would find life there more convenient. The study was targeted at three major cities in the southern coastal area of Iwate Prefecture that were most heavily struck by the earthquake-triggered tsunami: Kamaishi, Ofunato, and Rikuzentakata. Using geographical information system software, we conducted a network analysis of the coordinate data on the location of crucial infrastructure. Housing complexes within the defined service area of each infrastructure facility were assigned a score of 10, while those within two and three times the defined service area were assigned scores of 5.0 and 3.3, respectively. The convenience of the housing complexes was evaluated using these scores. In Ofunato City, the post-disaster recovery housing complexes were shown to have better access to key infrastructure than the temporary housing complexes, and in Rikuzentakata City, the two types of complexes were shown to have comparable access. In Kamaishi City, however, the post-disaster recovery housing complexes were shown to have poorer access to key infrastructure than the temporary housing complexes. These results suggest that the daily life of evacuees has not greatly improved in Rikuzentakata and Kamaishi. These results were not in line with our prior expectations.

Network protocols have vulnerabilities, and one way to reduce these vulnerabilities is to reduce the protocols in use to a small set of well-tested standard protocols. This reduces the attack surface and provides high confidence in selected communications. Screening of acceptable ports and protocols can be done by network appliances known as firewalls. Communications on the approved list are permitted, and others blocked. Many appliances now have port and protocol filters, and the server or service itself may have a host-based security system that can apply this functionality. This paper covers enterprise considerations for use and screening of ports and protocols.

Testing is one of the most important phases in the software development process, often requiring considerable effort and resources. We propose a novel approach for generating test cases, based on requirements specification. We make use of scenarios used in the requirements specification phase, taking into consideration the various relationships that can exist between them. These relationships are represented as dependency diagrams and they play an important role both in requirements specifications and in test case generation. Using our approach we can ensure that a larger proportion of requirements are actually tested.

Access control of electronic records involves establishing a common set of access requirements, binding those access requirements to the electronic records, and computing whether or not the criteria are met for allowing access. An electronic record can be an email, a document, a spreadsheet, or a series of sensor readings. Records that need to be controlled are stored in an encrypted file, which is decrypted when access criteria are verified. The number of controlled electronic records is rising dramatically. Current methods of key management often group and segment objects by type to reduce the number of keys and the associated management overhead. This approach compromises a large number of content files and uses PKI managed wrapped keys to extract cryptographic keys. The proposed process uses a hybrid symmetric/asymmetric keying approach that provides a unique key for each electronic record while minimizing the key management requirements. This method reduces losses to individual electronic records when keys are compromised, but with a greatly reduced key management process that leverages PKI processes.

This work investigated the ability of hyperspectral imagery for identifying Agathosma (A) Betulina and Agathosma (A) Crenulata plants. The plants have been used as traditional medicines to heal diseases such as urinary tract infections, stomach complaints, for washing and cleaning wounds, kidney diseases, and symptomatic relief of rheumatism. The species are normally identified on the basis of their shapes. A. Betulina has round-leaves while A. Crenulata has oval-leaves. The recognition based on morphology is no longer adequate because of extensive cultivation. New hybrids of the leaves now exist which are not easily separable. The study proposed implementation of Local Polynomial Approximation (LPA) algorithm and Principal Component Analysis (PCA) for the data processing. The data generated from the two methods are subjected to classification procedures for the plants identification. Various classifiers were used for the data separations. The results obtained reveal that most of the classifiers performed better on LPA processed data as compared to PCA.

Sequential Pattern Mining techniques have been employed in a variety of domains to analyze the available enormous data to identify frequent sequential patterns in order to implement efficient recommendation systems. Considering the variety of datasets pertaining to various application domains the judicious selection of sequential pattern mining approaches becomes a challenging task. As a major step in this direction, this paper presents the domain specific performance evaluation of the most commonly used sequential pattern mining approaches to analyze the behavior of these algorithms on the real-life datasets which represent characteristics of truly real-life situations rather than the synthetic ones and to select the one which best suits the given application domain characteristics. This study further aims at building a recommendation system for judicious selection of algorithm(s) and minimum support thresholds for application domains considering the nature of the application(s) and characteristics of the involved data Sets.

As a reliable and portable object-oriented programming language, Java has been used in a variety of practical systems including enterprise servers, smart phones, and embedded systems. Correspondingly, numerous educational institutes have offered Java programming courses to foster Java engineers. In order to assist Java programming educations, we have proposed a Web-based Java Programming Learning Assistant System (JPLAS). JPLAS provides four types of problems to cover the different learning levels of students: 1) element fill-in-blank problem, 2) value trace problem, 3) statement fill-in-blank problem, and 4) code writing problem. To encourage continuous self-studies of the students using JPLAS, the answers will be automatically marked in the server by comparing with the stored correct answers in 1) and 2), and by testing them on JUnit that is a single test framework in 3) and 4), where we have adopted the test-driven development (TDD) method. In this chapter, we introduce the outline of JPLAS and its application results to the Java programming course in Okayama University.

An increasingly important topic in education is the use of video lectures. It is known that it has many advantages, for example, improving the accessibility of the education and in some aspects the interactivity of the learning process. Still, the accessibility is limited to those who have the right devices and internet access. In this paper we discuss the accessibility at developing countries such as Brazil. It was given a survey to 440 freshmen of the biggest brazilian engineering school in terms of number of students, the Escola Politecnica da Universidade de Sao Paulo. We worked on the results as a case study in order to try to expand the results, for example, to the case of a general developing country. Some of the results of the survey were that almost one third of the students watches video lectures once a week, more than 80% of the students watch it to have a better understanding of the subject and the biggest part of the students are watching through Youtube. Finally, this study suggests that in order to improve the accessibility it is important to invest in services related to smartphones and Youtube. We noticed that it is important to make similar studies at other universities because of the socioeconomic bias found at the case studied.

Nowadays educational mobile apps represent a fundamental tool for the developmental learning of children with Down Syndrome (DS). However, these tools haven’t been formally integrated into the learning process due to cognitive growth that hasn’t been verified by the educator. In this work the results of the development of a mobile educational platform (m-learning) are presented. These count with many learning modules with technological innovative tendencies throughout the use of recognized tendencies towards the treatment of children with DS that allow the educator to have control over the cognitive development of the students.

In this work, we will introduce a two phases compression algorithm based on the binary representation of DNA sequences. In the first phase, we will use an implemented version of the Hoffman coding to efficiently compress and convert the DNA sequence into binary representation. Thereafter, we will compress the resulting DNA using the Extended-ASCII encoding through which one character can represent 16 bytes. The remarkable compression ratio and the easy way to implement our algorithm makes its use interesting.

One of the major orthodontic problems of the adult patient is the periodontal disease and its inerrant loss of bone support. The intensity of the forces needed to be applied during an orthodontic treatment must be adapted to obtain the same movement as in a tooth with a healthy periodontal support. Excessive force in case of advanced periodontal bone loss may traumatize the periodontium, which may affect the orthodontic tooth movement. For the clinical practitioner it is an important to use the optimal force which produces the maximum tooth movement without causing detrimental effects on the periodontium. The stress generated in the periodontal ligament (PDL) during orthodontic loading is important factor to be evaluated because these stresses are transmitted to the surrounding alveolar bone resulting in tooth movement. Finite element method (FEM) is one of the best in vivo available methods in evaluating the stress pattern and distribution. The stress distribution in PDL, in the case of periodontal disease, is rarely studied, even though this tooth movement is routinely used in the day to day practice.

The large amount of DNA sequences stored on online databases has led scientists to implement compression algorithms for DNA sequences. These algorithms attempt to remove the redundant and unuseful data before storing it in databases. In this paper, we will present a two phases compression algorithm based on the binary representation of DNA sequences. In the first phase, we will use a modified version of DNABIT compression algorithm to compress and convert the DNA sequence into binary representation. Thereafter, we will compress the resulting DNA using the Extended-ASCII encoding through which one character can represent four nucleotides or more. The remarkable compression ratio of our algorithm makes its use interesting.