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This New Articles Channel contents the latest articles published in Inderscience's distinguished academic, scientific and professional journals.


Thornthwaite-Holzman model for a wide range of daily evaporation rates
This study employs meteorological data from a weather station located in a coastal desert area in Kuwait, with a wide range of temperature, relative humidity, wind speed and evaporation measurements. The data have been used to test the well-known theoretical aerodynamic model of Thornthwaite-Holzman. The results show that the performance of this model is satisfactory for evaporation rates up to 10 mm/day, but there is an obvious systematic shift in accuracy beyond that from 10 to 40 mm/day. It is noted that the specific humidity difference proposed in the original model was assumed to have a linear correlation with evaporation rates. The study suggests modifying this assumption to become rather of a power form. The modification produced acceptable results based on subjective statistical criteria. This modification will help in extending our ability for analysing hydrological problems in different environments of high or low evaporation rates.

A groundwater ecosystem classification - the next steps
To manage the diverse range of groundwater dependent ecosystems (or GDEs), they must first be grouped appropriately in a logical and meaningful manner. An ecohydrogeological classification system for GDEs is presented. This classification was developed to protect high value water dependent ecosystems including groundwater dependent ecosystems. The need for a new classification system for this specialised group of ecosystems became apparent when the existing classifications could not adequately encompass, characterise, order, or prioritise the large number of known GDEs. In this paper, we review the previous classification systems that have included groundwater ecosystems worldwide and discuss the attributes and ecological drivers used. This paper focuses particularly on GDEs occurring in Australia. A new, more comprehensive classification scheme for aquifers is also presented based on structure, lithology and degree of confinement.

Application of artificial neural networks to predict peak flow of Surma River in Sylhet Zone of Bangladesh
River flow analysis and prediction is an important task in water resources planning, particularly for a disaster-prone agricultural country like Bangladesh. The present study used two ANN models namely radial basis function (RBF) and multi-layer perceptron (MLP) to analyse Surma River flow and estimate its peak flow concentration based on five input parameters. The performances of selected models were measured using the correlation coefficient (R), mean absolute error (MAE) and model efficiency (EFF%). However, RBF network model performed better than MLP network model with high model efficiency (99.55%), low mean squared errors (38.60) and high correlation coefficient (0.996), where the optimum number of neurons was 18 for RBF and 22 for MPL network. Moreover, the proposed ANN models could be used successfully in estimating the peak-flow of the Surma River, which would facilitate water resources management policy of this region.

Intricacies, challenges and implications: the governance of Tadlac Lake, Baños, Laguna, Philippines
Grounded on the lacuna in literature - the scarcity of scholarly works on lake governance and small lakes in the country, and the notable transformation of Tadlac Lake - from a threatened and poorly regulated lake to a potential model for governance and ecotourism development, this article documents the small lake and examines its governance specifics, challenges and implications. It argues that the governance of Tadlac Lake can be characterised as intricate, watershed-based, hierarchical, participatory and centralised. It also contends that the lake's development - its transformation from an aquaculture-based lake into an ecotourism-oriented lake - illustrates a key lesson for developing small lakes in the country. To close, the article hopes to instigate more governance studies on lakes, particularly small lakes, owing to their number (in the country and globally) and the fact that in the country, many are surrounded by impoverished communities.

Variation in rainfall trend at upstream - a threat towards filling schedule of Hirakud Reservoir, India
This study is focusing on the possibility of trend in monthly rainfall of upstream districts of the Hirakud reservoir of Mahanadi basin of Odisha applying Mann-Kendall test. Out of the other monsoon months, almost 19 districts show falling rainfall trend in September at 5% significance level. However, the inflow to reservoir shown declining trend during month of August and no trend in rest monsoon months. As the month of September is sensitive towards filling of reservoir as well as for flood control, the falling trends of rainfall will definitely put an alarm for the planner. The effect of climate change as well as changes in land use and storing/releases of upstream reservoir are suspected for the irregularities found in the pattern. The integrated basin management is also the call of the time for smooth operations of all the reservoirs.

Recognition of benzene structure from handwritten chemical expression with radial basis function neural network and rule-based approach
The chemical symbols and structures are basic building blocks of chemical expressions and reactions. Benzene symbol is widely used in aromatic chemical reactions. In this paper, we attempt to build a system which can recognise a benzene symbol from the handwritten chemical expressions, reactions or statements (HCERS). In this work a classifier has been developed. It identifies the parts of an image, which can possibly represent a benzene symbol from HCERS. On the next stage, i.e., recognition, the correct benzene structure is recognised from the identified parts of images. Two approaches, first rule based and second radial basis function neural network (RBFNN) based, have been proposed for the classifier. The scanned image of the handwritten chemical reaction, expressions or statements is input to our system. The output shows the presence of valid benzene ring structure or otherwise in the scanned image.

A novel mobile application for circuit component identification and recognition through machine learning and image processing techniques
Building an electronic product is complex and needs many steps, guidelines to be followed. From initial phase, till testing the product complexities are numerous. Most of the time in building a product is spent towards simulating the design to check if the proposed design is successful. People with expertise in using simulators only are deployed for this purpose. Although simulation and coding skills are secondary which may not contribute to the core value in the product, it is forced that everyone should learn them. To avoid this, we have come up with an innovative solution through an application in mobile phone that involves machine learning and image processing. Our proposed application enables the user to draw the circuit which he wishes to, once drawn with freehand, the circuit would be recognised and segregation happens where wires and components are split appropriately. Then, each component will be identified through the machine learning algorithms and netlist will be generated, all in seconds with high accuracy.

A novel Arabic font recognition system based on texture feature and dynamic training
Recognising an Arabic text with OCR is a complex task caused by the cursive nature of Arabic script for printed and handwritten text. The Arabic letters change forms according to not only their position in the word, but also their font. In fact, developing a font recognition system as a pre-recognition step may help to increase the OCR performances. In this paper, we present an Arabic font recognition system using curvelet transform for feature extraction. Moreover, we expose a new classification strategy based on a back-propagation artificial neural network (BpANN) called a dynamics multi-BpANN-1Class classifier. To validate our proposed system, we first focused our research on a comparative study of five texture analysis techniques. Second, we compared our classifier to a classical BpANN. And finally, we validate the dynamic training for the classification phase.

A novel similarity measure: Voronoi audio similarity for genre classification
One of the major challenges in genre classification, recommender systems is to find similarity between the query song and songs in a database. In this paper, we propose a novel similarity measure called Voronoi audio similarity (VAS). We extracted the Content-based features from the audio signal of the song split in frames over a particular time period and we represented each song as a point in 2D space. The proposed system is a two-level classification process, where songs are first clustered by K-means clustering and then a Voronoi diagram is created using centroids from the resulting K-means, which is called the template Voronoi diagram (TVD). This approach learns the decision boundary used for genre classification. The genre of the song could thus be predicted as the genre with the maximum normalised area overlap. Empirical results performed with 10 cross-fold validations on million song subsets of 500 songs showed 78% accuracy.

A fuzzy-based approach for bug report categorisation
Various studies conducted on bug repositories utilise issue reports labelled as 'bug'. Research conducted on a number of bug repositories have shown that not all issue reports labelled as 'bug' are actually bugs but can also be a request for additional feature, improvement or documentation. This not only threatens the validity of studies that have used mislabelled data but may also give wrong prediction results in future. This has necessitated need for correct labelling of issue reports. The proposed work using fuzzy logic classifier suggests improvement and also reduces the complexity. Validation of this work is done using five open source projects. Experimental results have shown that our approach gives better F-measure scores. The study also elaborated on use of issue reports from other similar projects for training a model; the impact of frequent terms from the training data and applicability of our approach to fine grained categorisation of issues.

Time synchronisation attacks and defences in IEEE802.15.4e networks
Time synchronisation is very crucial in many wireless sensor network applications especially in industrial wireless networks. The current industrial wireless standards all use TDMA-based channel-sharing protocols on the medium access control (MAC) layer. If an adversary launches time synchronisation attacks to the industrial wireless networks, the whole networks communication will be paralysed. However, the time synchronisation is insufficient to be protected in the current industrial wireless standards which based on IEEE802.15.4e standard. So it is important to study in depth the time synchronisation method of attack and defense in IEEE802.15.4e networks. In this paper we give a survey of time synchronisation in IEEE802.15.4e networks and point out the possible attacks. They include ASN attack, message manipulation attack, node identity attack and pulse-delay attack. Then we propose some countermeasures against these attacks. Finally, we perform a series of experiments to evaluate the effectiveness of corresponding defences for the attacks. The experiment results show that the proposed mechanisms can successfully defend against these attacks. And the energy consumption of these defense methods are very low.

A new construction of fuzzy operator-attribute-based signcryption on VCC
Recently, vehicular computer clouds (VCC) have taken an important role in intelligent transportation systems (ITS). VCC meets lots of security challenges, it is important to build secure VCC access. In this paper, a fuzzy operator-attribute-based signcryption (FOABS) is presented, which is a novel security mechanism that makes relations between the vehicle operator's right and these operations. FOABS leverages fuzzy attribute-based encryption to enable data encryption, access control, and signature for vehicular control, and signature for vehicular control information in VCC. FOABS, which combines digital signatures and encryption, provides confidentiality, authenticity, undeniability, and collusion resistance. Through the prototype system, we analyse its security level.

Expressive ciphertext-policy attribute-based encryption with direct user revocation
Attribute-based encryption enables fine-grained access control on sensitive data with a specific user set. However, traditional ABE schemes cannot satisfy practical requirements of data sharing applications where users may leave or join a system frequently. In this paper, a ciphertext-policy ABE scheme with direct user revocation (DUR-CP-ABE) is proposed. In DUR-CP-ABE, both the private key and the ciphertext contain partial components associated with a user identity and a revocation list, respectively. A user can decrypt a ciphertext if and only if he/she is not in the revocation list and his/her attribute set satisfies the access policy, simultaneously. In addition, whenever revocation events occur, only ciphertext components associated with the revocation list need to be updated. Finally, the DUR-CP-ABE scheme is proved selectively secure under the decisional q-bilinear Diffie-Hellman exponent assumption in the standard model. Compared with the existing revocation-related schemes, the new scheme can achieve high efficiency and ensure the expression ability of access structure.

Context-driven composition for mobile applications: a metamodelling approach
Nowadays, the numbers of mobile applications (apps) is undeniably explosive. This phenomenon is likely to encourage the user to expect more or less the same app to be available on just about any kind of platforms, even when there are differences in the apps that run on such platforms. In order to better fulfil user's expectations, understanding such differences - or heterogeneities - then becomes critical, as does resolving them, but is quite challenging. In this paper, we propose a technique for developing mobile device apps, through composition of existing homogeneous or heterogeneous software entities that are context-aware. As a key novelty, this technique uses a metamodelling approach in understanding and representing the differences, as well as commonalities, between reused software entities. In order to see the applicability and the effectiveness of this technique, a tool has been implemented to date, together with an application to a shop review app.

Energy efficient real-time scheduling algorithm for mixed task set on multi-core processors
Energy optimisation is gaining greater significance in a wide range of systems from mobile devices to datacentres. Specifically, in battery powered real-time embedded systems where tasks are executed under hard timing constraints, energy optimisation poses a big challenge. This paper focuses on dynamic energy optimisation using a well-established technique namely dynamic voltage and frequency scaling (DVFS). This work presents a real-time scheduling algorithm that uses DVFS on mixed task system containing periodic as well as aperiodic tasks on homogeneous multi-core processor. The proposed algorithm guarantees periodic task deadlines and offers minimum aperiodic task response times. Simulation analysis shows that the proposed scheme saves more energy as compared to cycle conserving, static FVS and non-DVFS scheduling algorithms. Further, it does not result in any response time degradation of aperiodic tasks as compared to other algorithms.

Proxy re-designated verifier signature and its applications
With the development of cloud computing, vast amounts of data are stored in a cloud. Some stored contents may be shared with other people. For a content consumer, it is crucial to identify the owners of some contents. However, for a content owner, it is usually better not to leave evidences on sharing some contents. Considering this requirement, we propose a new cryptographic primitive based on designated verifier signatures (DVSs) to enable efficient sharing of sensitive contents in a cloud. With the primitive, a content owner can store a sharable content in a cloud. On request of a content consumer, the content owner can produce a re-signing key for a cloud server with which the cloud server produces a customised DVS of the content for the content consumer. The customised DVS can be verified by the consumer, and cannot be transferred to any third party for a proof of source. When the content owner is under investigation, they can always deny their sharing of sensitive contents facing evidences collected from a receiver.

L4eRTL: a robust and secure real-time architecture with L4 microkernel and para-virtualised PSE51 partitions
Different classes of applications exhibit different demands on today's heterogeneous computing systems whose complexity will incur further challenges in ensuring system safety and application security for certain required functionality of these systems. This paper proposes a component-based robust and secure real-time architecture, L4eRTL, which decomposes complex systems into sub-modules and distributes them to POSIX-enabled partitions through para-virtualisation. L4eRTL is designed and implemented based on low-level L4 microkernel and several essential para-virtualised components by IRQ virtualisation, time virtualisation, clock virtualisation, and memory virtualisation. Micro-benchmark programs and sample applications have been conducted to demonstrate the effectiveness of L4eRTL in supporting multiple isolated PSE51 environments for system safety and application security.

Multi-core model checking and maximum satisfiability applied to hardware-software partitioning
Bounded model checking (BMC) based on satisfiability modulo theories (SMT) is well-known by its capability to verify software. However, its use as optimisation tool, to solve hardware and software (HW-SW) partitioning problems, is something new. In particular, its integration with the maximum satisfiability solver vZ tool, which provides a portfolio of approaches for solving linear optimisation problems over SMT formulas, is unprecedented. We present new alternative approaches to solve the HW-SW partitioning problem. First, we use SMT-based BMC in conjunction with a multi-core support using open multi-processing to create four variants to solve the partitioning problem. The multi-core SMT-based BMC approaches allow initialising many verification instances based on the number of available processing cores, where each instance checks a different optimum value until the optimisation problem is satisfied. Additionally, we integrate the vZ into the BMC, making it a specialised solution for optimisation in a single-core environment. We implement all five approaches on top of the efficient SMT-based context-bounded model checker (ESBMC) and compare them to a state-of-the-art optimisation tool. Experimental results show that there is no single optimisation tool to solve all HW-SW partitioning benchmarks, but based on medium-size benchmarks, ESBMC-vZ had better performance.

MSD's in industry - a careful examination of the predictors using MANOVA
Among computer operators, risk factors associated with work-related musculo-skeletal disorders, include the integration of biomechanical factors, work environment and issues related to the working organisation, as well as those associated with the psychosocial aspects of work. With more and more jobs available in software industry today, it is all the more important to be aware of the problems and follow necessary preventive steps to check the progression of computer related health problems. Musculoskeletal disorders (MSD) such as neck and low back pain have been widely reported as being of significant health and economic concern due to increased globalisation and industrial advancements. The debilitating effects of MSD are widely acknowledged by researchers in the medical field as well as in the engineering field. This research has provided empirical result to establish the curative along with preventive effects of physiotherapy in combating MSD present in today's Indian software industry.

Drivers of product visibility in Indian automobile sector: an interpretive structural modelling-based approach
The automobile business in India is highly competitive, dynamic and technology driven. Achieving competitive advantage is of utmost importance for existing automobile players and ensuring enhanced product visibility is the key to gain required competitiveness in cutthroat market. The emergence of modern technology has changed the way organisations in automobile sector are reaching out to their prospective customers. It has also equipped marketers with most recent means of improving product visibility to ascertain a deeper market penetration and better coverage in Indian business scenario. Present research work is an attempt to identify the drivers of product visibility in context of automobile sector in India. A total of 32 initial dimensions which drive the visibility of a product are refined through a structured Delphi method and interrelationships among these drivers are established using an interpretive structural modelling technique. The insights gained through present work have several practical implications for academia and practicing managers of Indian automobile industry.

Outsourcing strategies in the security sector
The purpose of this paper is to examine how security-related outsourcing strategies and the negotiating power of the public sector, the military and the relevant logistics service providers influence indirect logistics costs. Survey data was gathered from 149 respondents and the model was tested using structural equation modelling. The findings indicate that negotiating power and logistics strategy do not correlate. However, together they do affect direct costs and perceived service quality to reduce indirect logistics costs. Furthermore, it seems that service quality may have a strong mediating role in the relationship between negotiation power and indirect costs. Hence, the buyers of logistics services could learn from the public sector and the military on how to use negotiating power and strategy to obtain better service and short-term cost reductions and potentially improve the service performance of their supply chain. The paper will therefore be of value to both practitioners and scholars.

Logistics service providers perceptions on halal logistics certification
The purpose of this research is to examine the attributes of halal certification from the logistics managers' perspective. Specifically, the research seeks to measure the Malaysian logistics service providers' (LSP) perception on halal logistics certification. A survey was designed and gathered from logistics managers at 65 LSPs registered in Malaysia. Data were then analysed using descriptive and factor analysis methods. Results indicate that logistics managers in Malaysia have positive perceptions towards halal logistics certification, claiming that it is an essential tool to achieve greater performance and a way to increase the number of customers. Factor analysis identified logistics operation, productivity, industry acceptance, certification process, and knowledge as factors associated with halal logistics certification. The findings derived from this research further accentuate the significance of halal certification for the service industry, specifically logistics services. Additionally, this research supports the notion that halal certification is a critical success factor to halal logistics.

Complex vehicle transport problems: taxonomy, new variants, challenges and solution methodology
Due to appeared of several and new alternatives of vehicle routing problems (VRPs) in the last years, the contributions focus on design of traffic flow and transportation systems, vehicle routing, and other important aspects of supply chain management such as dynamic routing, multi commodity problems, inventory management, lot sizing, and lot scheduling. In this paper, we are going to present an extensive review of the general vehicle routing problem then we are going to focus on the problematic approaches in this field. For each one of these problematic, a positioning compared to this state of the art will be developed. In the first part a synthesis of literature review devoted to the complex and logistic transport problems in general and a transport problem with limited fleet and common carrier in particular with stochastic and dynamic vehicle routing problem. In the second part, a description of the vehicle routing problem with mathematical formulations will be presented. The different variants of this problem will be approached.

Radioprotective potential of some medicines used in Tabuk, Saudi Arabia, to minimise the effects of the ionising radiations
With increasing use of ionising radiations (in particular the gamma rays and X-rays) in medicine, many dangerous diseases may occur. Hence, it is necessary to restrict and control exposure of human beings to these radiations. In this study we have investigated the radioprotective effectiveness of some medications sold at community pharmacies in Tabuk, Saudi Arabia. The data were collected and recorded for 20 drugs commonly used for different medical purposes. In order to investigate the effectiveness of these radioprotectives in terms of absorption of low and high energy photons, the effective atomic number (Zeff) of ten drugs for total photon interaction in the energy range of 1 keV to 15 MeV using WinXCom were calculated. In addition, by Geometric-Progression (G-P) method, the energy absorption (EABF) and exposure build-up factors (EBF) for incident photon energy 0.015 MeV to 15 MeV up to penetration depths of 40 mean free paths (mfp) were calculated for the ten drugs. Among the selected compounds, Captopril and Cefixime have the maximum value of Zeff, while the minimum EBF and EABF were found for Mesna, Cramastine, Thiotepa and Busflan; therefore, they are appealing as radioprotective compounds.

The role of the breakup channel on the fusion reaction of light and weakly bound nuclei
The effect of the breakup channel on fusion reactions of weakly bound systems by means of semi-classical and full quantum mechanical approaches has been discussed. The total fusion reaction cross-section σfus and the fusion barrier distribution Dfus for the systems 4He+64Zn, 6Li+208Pb and 7Li+24Mg have been calculated. The inclusion of the breakup channel enhances the calculations of the fusion cross-section markedly below the Coulomb barrier and hindrance above the Coulomb barrier in comparison to the experimental data. The semi-classical calculations agree reasonably with the full quantum mechanical treatment and they were able to reproduce the experimental data in details for the total fusion reaction cross-section σfus and the fusion barrier distribution Dfus.

CFD analysis of thermal-hydraulic behaviour of the high performance light water reactor fuel assembly
The High-Performance Light Water Reactor (HPLWR) is the European Supercritical Water-cooled Reactor design. In this paper, a thermal-hydraulic study of the HPLWR fuel assembly using CFD codes was carried out. The capability of the Reynolds Stress model of Speziale (SSG) and the k-ω Shear Stress Transport model (SST) for predicting the supercritical water heat transfer was evaluated. The axial temperature distributions of the fuel, cladding, coolant and moderator in the fuel assembly were obtained. Numerical results of the fuel temperature profiles were compared with that obtained by Waata (2006) and a good agreement was achieved. The cladding surface temperature profiles calculated with SSG and SST turbulence models are below the prescribed limits; however, hot spots in one sub-channel were found. The difference in the average thermal-hydraulic properties of the supercritical water calculated with SSG and SST was negligible. The fuel and cladding surface temperatures are higher when using the SST model.

Electromagnetic flow meter with non-insulation pipe wall for liquid sodium in nuclear reactors
An electromagnetic flow meter (EMFM) with non-insulation pipe wall that may be used in the Fast Reactor Test Facility (FARET) has been designed and partially tested. The internal pipe wall of EMFMs must be non-conductive to prevent generated electromotive force from short circuiting. Usually the inside of metallic pipes is lined with insulating material. The lining limits the applicable temperature range of measured fluid and also its reliability. A new structure is proposed, in which the insulating liner is eliminated and metallic pipe instead of non-insulation material. Also a servo system is applied. Therefore, the output signal is exactly the same as that of conventional EMFMs. In this paper, an analytical method based on conducting wall boundary conditions and experimental results is described.

Understanding kinetic behaviour of TRIGA reactor core
The kinetic parameters govern the transient behaviour of a nuclear reactor. Estimation of these parameters has great importance for the safe design and operation of a nuclear reactor. In order to understand the kinetic behaviour of TRIGA core, the influence of graphite dummy elements, absorber materials and beam ports on kinetic parameters has been studied. To do so, the effective delayed neutron fraction (βeff), prompt removal lifetime (ℓ) and mean neutron generation time (Λ) have been calculated for an infinite system of LEU fuel cells. The investigation has been extended to four different cases of TRIGA reactor core. Monte Carlo simulation has been carried out to compute the kinetic parameters by Monte Carlo code MCNP5. The βeff value remains unchanged but the ℓ and Λ values are found to be sensitive to the local perturbations of core components.

Influence of Prandtl number on heat transfer of a flat vertical plate
Liquid metals, such as sodium (Na), lead (Pb), and lead-bismuth (Pb-Bi) eutectic (e), are considered as potential coolants for the fast spectrum nuclear reactors of the next generation. So the main objective of this paper is to study the heat transfer and fluid flow characteristics of liquid metal coolants flowing over a nuclear fuel element having uniform volumetric energy generation. Stream function vorticity formulation method was used to solve the full Navier Stokes equations governing the flow. The energy equation was solved using central finite difference method. For the two-dimensional steady state heat conduction and stream-function equation, the discretisation was done in the form suitable to solve using 'line-by-line Gauss-Seidel' solution technique whereas the discretisation of vorticity transport and energy equations was done using Alternating Direction Implicit (ADI) scheme. After discretisation the systems of algebraic equations were solved using 'Thomas algorithm'. The complete work was done by writing a well-validated indigenous computer code using C-language. The parameters considered for the study were: aspect ratio of fuel element, Ar, conduction-convection parameter Ncc, total energy generation parameter Qt, and flow Reynolds number ReH. The results obtained can be used to minimise the maximum temperature in the fuel element (hot spots) and prevent its melting.

Ownership structure and dividend policy: application of Lintner's dividend model in Sri Lanka
This paper investigates the effect of ownership structure on the dividend policy of 77 Sri Lankan firms listed in the Colombo Stock Exchange over the period 2006-2014. The Lintner's full adjustment model and the partial adjustment model are used to examine the potential relationship between ownership structure and the dividend policy. We find that the ownership identity matters in determining the dividends according to Lintner's dividend model in Sri Lanka. Compared to the full adjustment model, the partial adjustment model is superior in explaining the variation in dividends with variables associated in different ownership structures. There is a negative association between institutional, managerial ownership structures and the dividend policy and a significant positive association between concentrated ownership structure and the dividend policy. In addition, the dividend in the preceding year is highly significant in explaining the succeeding year's dividend, thus confirming the stability of the dividend policy.

Value relevance of the voluntary disclosure of advertising expenditure: evidence from Canada
This paper investigates whether the voluntary disclosure of advertising expenditure by Canadian firms is value relevant. The analysis is based on a matched sample of 876 firms listed on the Canadian Toronto Stock Exchange over the period 2007-2014. There were 438 firms that disclosed their advertising expenditures, which we refer to as disclosers and 438 firms that did not disclose, which we refer to as non-disclosers. The findings suggest that advertising expenditure is positively related to firm value, a firm size effect exists and that only for certain sectors is this expenditure value relevant. We also found a positive relationship between market value and advertising expenditure for discloser firms. The results are stable across several econometric models that control for endogeneity. The implications for disclosure strategies of firms are discussed.

Investigating capital structure through IAS 1: variations in disclosure and measurement
This study examines how a set of Canadian and German firms apply the quantitative capital disclosure requirements contained in IAS 1. We find significant inter-country differences in both the propensity to disclose a capital structure and in the form of the disclosure. Further, we find variation both within and between countries in the balance sheet elements used to construct the numerators and denominators of the capital structures. When we compare the ratios constructed from the various combinations of balance sheet elements, we find significant measurement differences, in some cases exceeding 10 percentage points. When we use the ratio constructions to generate cost of capital we also find significant differences, in more than half the cases exceeding a full percentage point. Overall, our results suggest that the significant variations in capital structure disclosures and measurements we identify are potentially value relevant information for users.

Quality management in the public sector accounting department - (un)avoidable quality costs and unlikely financial impacts
This paper investigates the nature of quality costs and the likelihood of their having financial impacts in the public sector. An illustrative quality development case project in an accounting department of a Finnish city administration is presented. The empirical data includes answers to a qualitative project question sheet, workshop material and participative observation. Quality problems are classified according to their quality cost category and the extent to which they are avoidable. Some of the quality costs proved unavoidable and some are likely to lack financial impact, exhibiting sticky cost behaviour. The study indicates that certain prevention and appraisal costs in the public sector might not deliver the desired outcomes because of such sticky behaviour of costs. Traditional quality thinking holds that increased prevention and appraisal investments decrease failure costs. However, the extent to which these costs are avoidable has not been analysed in previous studies.

Service-dominant logic and service logic - contradictory and/or complementary?
In the contemporary marketing theoretical discussion there has been a widely established effort to revitalise the concept of service. In this endeavour, conceptual friction between two well-established marketing theoretical logics, namely service-dominant logic (S-D logic) and service logic has emerged. Although these perspectives have been widely debated, there have not been systematic efforts to analyse their conceptual differences. Analysing these differences will aid the further development toward more consistent marketing theory. Thus, this study identifies areas of contradiction and complementarity between S-D logic and service logic.

Machine learning methods with feature selection approach to estimate software services development effort
Estimate of the effort required for software services development has been a most important topic in the field of service in recent years. Exact estimate of effort is a key factor for project's successful management and control. Over and underestimation waste system resources endanger the position of the related company. The development effort estimation is done with the help of expert judgement, algorithmic and machine learning methods. Recently, several methods of machine learning have been used to estimation software services effort and look much better than the other two groups. This paper presents an experimental evaluation of the effectiveness of these methods with feature selection approach and done a thorough comparison of their accuracy. Evaluation and comparison have been made onto two famous datasets NASA and ISBSG and results are well demonstrated position of each one of these methods.

The effects of consumer and brand personality on mobile services purchase
The advent of telecommunication technology saw a growth of mobile service providers, particularly in the Malaysian market. Each service provider tends to offer competitive packages in their quest to attract customers. Nevertheless, the purchase of mobile services indirectly is influenced by the customers and brand personality. Hence, brand personality management is a critical part of a company's marketing program in today's global market. Despite the importance of brand personality in academia and practice, very limited empirical research has examined the determinant roles of brand personality on actual consumer brand purchase, particularly mobile services. Given its great potential usability for marketers and brand managers, this study conceptualises and examines the impact of consumer personality on brand personality and its subsequent effect on the Malaysian consumers brand purchase, focusing specifically on mobile services purchase. The empirical evidence from the study suggests that the consumer personality's dimensions have significant relationship with the mobile services brand personality. However, the results of this study indicate no differentiation of impact for mobile services brand personality on the actual mobile services purchase.

Process capability and performance in business services offshoring
Service providers continually seek ways to improve their offshore delivery performance. In this study, we analyse detailed performance data from a large service provider that implemented a framework to enhance its process capability for services offshoring. We evaluate the extent to which process capability influences service delivery performance, and how the effect of process capability differs based on task complexity, process synergies, and length of experience with the new processes. Our results indicate that for non-complex tasks, service delivery performance improves significantly over time after new processes are introduced, particularly when process synergies are present. In contrast, for complex tasks there is an initial decline in performance after new processes are adopted. However, over time, performance on complex tasks increases at a faster rate than performance on non-complex tasks. Task complexity also reduces the effect of process synergies on performance, but this reduction attenuates over time.

Customer satisfaction on Indian domestic gas delivery
LP gas is extremely versatile and portable. It can be transported using sea, rail or road transport. LP gas is available in a wide variety of packaging and storage options and is available in even the remotest of areas. LP gas is used throughout the home, as a gas to cook with, a source of fuel for central heating and hot water. LP gas is also commonly used in the agricultural sector and as a lower emission automotive transportation fuel Indian households are fully dependent on LPG cylinders. Therefore, attention needs to be diverted towards customers' perception on quality of supply of LPG gases and its related services so that distributors can focus on specific areas of concern to improve customer satisfaction. In this paper, attempt is made for concrete and measurable improvements in the service through an extensive study on customer's perception and various extents of the LPG gas supply. Some suggestions are provided for the improvement in service quality in Indian context.

Time to retire: indicators for aircraft fleets
It is well known that aircraft fleets are aging alongside rising operations and support costs. Logisticians and fleet managers who better understand the milestones and timeline of an aging fleet can recognise potential savings. This paper outlines generalised milestones germane to military aircraft fleets and then discusses the causes that lead to retirement motivations. Then this paper develops a utility per cost metric for aging aircraft fleet comparison as a means for determining when to retire a fleet. It is shown that utility per cost is a pragmatic metric for gauging the desirability of an existing fleet because of naturally occurring zones. Historical data from the US Air Force's fleet are used to validate the existence of these zones. Lastly, this work highlights the need for increased vigilance during the waning years of a fleet's lifecycle and discusses the intricacies of asset divestment planning.

Strategy and competitive rivalry in the original equipment manufacturer single aisle market
The development of new jet aircraft has become the focal point of competition within the commercial aviation industry, pushing product development and positioning strategies to the core of the competitive game. This paper explores the competitive forces of the single aisle aircraft manufacturing market and how the rivalry between competitors affects their respective strategies. A survey was distributed to industry executives, along with interviews with key senior managers, to uncover and critique strategies the respective airframe original equipment manufacturers (OEMs) adopted. It was found that movements in the engine OEM industry were a key determinant in the competitive positioning of airframe OEMs during the period of this study ranging from 2004-2013. The focus OEMs established different strategies, considering the competitive actions of their rivals, to succeed in the single-aisle segment. Bombardier followed a niche strategy, differentiating itself in that niche by developing a clean sheet design aircraft. Airbus and Boeing use their competencies to create a broad cost and differentiation strategy, respectively. Embraer competes with its counterparts by adopting a niche strategy coupled with cost leadership in that niche.

Employment motivation of airline pilots in the USA
The airline industry is currently experiencing a high volume of airline pilot retirements. As a result, there is a large demand for new airline pilots. Many regional airlines are reporting that there is a pilot shortage in the airline industry since they are having difficulty hiring enough qualified pilots to meet their demand. Conversely, research has shown that there is a sufficient number of qualified pilots in the USA to meet the current and future demand. The purpose of this descriptive study was to quantify the motivations of the entire ATP/commercial pilot population and to specifically identify the reasons why two-thirds of the ATP/commercial pilot population have decided not to seek airline employment. The results suggest that insufficient pay is the primary reason that pilots choose non-aviation careers and that an increase in starting salary would motivate many qualified pilots to seek employment at regional airlines.

IATA's new distribution capability and its impact on traditional forms of cooperation in the airline industry
Intensified competition, stagnating ticket sales and increasing operational costs cause airlines to seek for new sources of revenue. Ancillary services and complementing offers are therefore becoming crucial in the airline industry. Particularly in indirect distribution channels, the presentation of products and services, generating extra revenue, depends on the capabilities of the GDS. 'new distribution capability' (NDC) is a technology which will fundamentally change traditional GDS-based distribution processes used for decades. The quintessence of the NDC concept is to position the airline in the centre of an interactive offer-generation process. This impacts commercial cooperations with partner airlines. Nevertheless established forms of cooperations (Interlining/Code Sharing) will basically be maintained. Dynamic interaction between the partners enables more flexible collaboration which will significantly influence forms of cooperation. This affects cooperations within the framework of 'Global Airline Alliances'. Specific consequences and actual implications of NDC cannot yet be defined in detail.

Analysis of the legacy of conflict among international tourists in Vietnam
Since the late 1980s, the Vietnamese Communist Party (VCP) has made extensive political and economic reforms while rapidly expanding tourism. Known as Doi Moi, the reforms opened up new areas of Vietnam unconnected with the country's wartime past while lessening the VCPs antagonistic stance towards former adversaries. Reforms have also helped broaden Vietnam's identity among younger generations of international tourists who no longer solely associate the country with war. Although the war will always be a part of the country's history, other factors such as Vietnam's food, beaches, and shopping opportunities are larger draws for its fast-growing tourism industry.

Ethnography on tourist spaces
Tourism-related research, despite the great number of books and studies, seems to face one of its worst epistemological crises. At some extent, scholars have serious difficulties to define what tourism means. Though anthropology was the discipline more prone to tourism, as it is, a rite of passage, the current state of indiscipline claimed by Tribe, de Escalona and Korstanje as well as the autonomy of an international academy is more oriented to marketing than to science, are some of the problems tourism research faces today (Tribe, 1997, 2010; Korstanje, 2010; de Escalona, 2015). In this difficult context, Nogues Pedregal provides readers with a masterful ethnography which serves to interpret, understand and decipher the shifts over territory once tourism is adapted as a main activity. Though a lot has been written on the effects of tourism, this seminal book describes with accuracy how these transformations are gradually happening.

Identification and removal of different categories of noises from magnetic resonance image using hybrid partial differential equation-based filter
This paper identifies various types of noise present into the MRI and filters them by choosing an appropriate filter. The different categories of noises during the acquisition of MR image may be generally corrupted due to external or internal causes. The external causes lead to an additive noise pattern which follows a Gaussian distribution (pdf). Causes of internal noise in MR image are basically the intrinsic noise that is generated during the acquisition process. Normally intrinsic noise in MR image follows the Rician distribution (pdf). The proposed filter gets adapted for the removal of specific types of noise based on SNR values of image data. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of PSNR, MSE, SSIM and CP. From the simulation results, it is observed that the proposed framework with CD-based prior is performing better in comparison to other priors.

Shaping the future design and manufacturing of a composite rotor blade for multi-megawatt wind turbines
Given that wind energy is a key solution in fighting against global warming emissions arising from human activities, the interest for developing more powerful wind turbines has become nowadays a challenging area to research and innovation for the wind-turbine industry worldwide. As the electric power supplied by the wind turbine is directly related to the size of its blades: the larger the size of blades the more energy is captured, new design and manufacturing strategies of these critical components, using advanced fibre-reinforced composites such as carbon nanotubes (CNTs) and resin transfer moulding (RTM) process, have become a major focus for manufacturers and competitors of wind turbines. In this perspective, the outcomes presented in this paper can be exploited by the modern wind turbine industry with the aim of developing reliable, efficient and cost-effective rotor blades that are capable to withstand, without adverse effects, severe static and/or dynamic loading to which they may be exposed during their lifetime. As part of long-term strategic plans, CNTs offer the required criteria to help researchers design and manufacture 200 m rotor blades for 50 MW turbines.

Development of monitoring algorithm for controlling a biped robot: norm bounded uncertainties system-based
It is well known that the biped walking gait is represented as a steady periodic gait. Investigation of such passive natural motion leads to different strategies of control; these strategies require a sharp mathematical model of the walking dynamics. One of the most used models is the Kajita's one. In this paper, we present an algorithm of controller's design used for the stabilisation of biped robot's gait. Using the Kajita's model as a reference, we include a Norm bounded uncertainties to ensure a more realistic numerical model. The modified model allows us to include constraints on both inputs, outputs and states. The synthesis of the dynamic controller relies on the use of predictive control theory (MPC) and the resolution of a convex optimisation problem with linear matrix inequalities (LMIs) at every sampling period. The generated control law allows a real-time walking robot even in rough ground or unknown environment.

Robust DC-motor speed control using a fractional adaptive PIα regulator
Conventional adaptive PI controller is one of the most widely used controllers in industry, but the recent advancement in fractional calculus has introduced applications of fractional order calculus in control theory. One of the prime applications of fractional calculus is fractional adaptive PI controller and it has received a considerable attention in academic studies and in industrial applications. Fractional order adaptive PI controller is an advancement of classical integer order adaptive PI controller. In many a cases fractional order adaptive PI controller has outperformed classical integer order adaptive PI controller. Particularly for the problem of controlling the speed of DC-motors, it is very important use a suitable and efficient controller as any small change can lead to instability of the closed loop system. This research paper, studies the control aspect of fractional order controller in speed control of DC motor. A comparative study of classical adaptive PI controller and fractional order adaptive PI controller has been performed to illustrate the effectiveness and robustness of the proposed fractional adaptive control solution.

Policy iteration and coupled Riccati solutions for dynamic graphical games
A novel online adaptive learning technique is developed to solve the dynamic graphical games in real-time. The players or agents exchange the information on a communication graph. Hamiltonian mechanics are used to derive the constrained minimum conditions for the graphical game. Novel coupled Riccati equations are developed for this type of games. Convergence of the adaptive learning technique is studied given the graph topology. Nash equilibrium solution for the graphical game is found by solving the underlying Hamilton-Jacobi-Bellman equations. Actor-Critic neural network structures are used to implement the adaptive learning solution using local information available to the players.

A state space I/O map to transform nonlinear systems into an observable form
This paper deals with the problematic of state-space realisation of input-output (i/o) nonlinear systems. For that, we propose a general method that can be used to verify the realisability of i/o models and provides the equivalent state-space model when it is possible. The main advantage of the proposed approach is the use of graphic map to design the state space model without analytic analysis. The resulted state-space model is identified using a special class of modular feed-forward neural networks that embeds the state vector of the model. New results are also proposed using a realisable non-recurrent i/o subclass that is adapted to Matlab identification procedure. This approach is applied on some examples and proved its efficiency.