Knowledge Representation and Inconsistency Reasoning of Class Diagram Maintenance in Big Data

Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.

Anti-Social Media: Implications of Social Media in the Form of Stressors on Our Daily Lives

This research aims to investigate the role of social media (Snapchat, Facebook, Twitter, etc.) in our daily lives and its implication on our everyday routine in the form of stressors. The study has been validated by a social media survey with 150 social media users belonging to various age groups. The study explores how social media can make an individual anti-social in his or her life offline. To explain the phenomenon, we have proposed and evaluated a model based on social media usage and stressors including burnout and social overload. Results, through correlation and regression tests, have revealed that with increase in social media usage, social overload and burnout also increases. Evidence for the fact that excessive social media usage causes social overload and burnout has been provided in the study.

Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction

A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Role-Governed Categorization and Category Learning as a Result from Structural Alignment: The RoleMap Model

The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Large Strain Compression-Tension Behavior of AZ31B Rolled Sheet in the Rolling Direction

Being made with the lightest commercially available industrial metal, Magnesium (Mg) alloys are of interest for light-weighting. Expanding their application to different material processing methods requires Mg properties at large strains. Several room-temperature processes such as shot and laser peening and hole cold expansion need compressive large strain data. Two methods have been proposed in the literature to obtain the stress-strain curve at high strains: 1) anti-buckling guides and 2) small cubic samples. In this paper, an anti-buckling fixture is used with the help of digital image correlation (DIC) to obtain the compression-tension (C-T) of AZ31B-H24 rolled sheet at large strain values of up to 10.5%. The effect of the anti-bucking fixture on stress-strain curves is evaluated experimentally by comparing the results with those of the compression tests of cubic samples. For testing cubic samples, a new fixture has been designed to increase the accuracy of testing cubic samples with DIC strain measurements. Results show a negligible effect of anti-buckling on stress-strain curves, specifically at high strain values.

X-Ray Fluorescence Molecular Imaging with Improved Sensitivity for Biomedical Applications

X-ray Fluorescence Molecular Imaging (XFMI) holds great promise as a low-cost molecular imaging modality for biomedical applications with high chemical sensitivity. However, for in vivo biomedical applications, a key technical bottleneck is the relatively low chemical sensitivity of XFMI, especially at a reasonably low radiation dose. In laboratory x-ray source based XFMI, one of the main factors that limits the chemical sensitivity of XFMI is the scattered x-rays. We will present our latest findings on improving the chemical sensitivity of XFMI using excitation beam spectrum optimization. XFMI imaging experiments on two mouse-sized phantoms were conducted at three different excitation beam spectra. Our results show that the minimum detectable concentration (MDC) of iodine can be readily increased by five times via excitation spectrum optimization. Findings from this investigation could find use for in vivo pre-clinical small-animal XFMI in the future.

Evaluating the Effectiveness of the Use of Scharmer’s Theory-U Model in Action-Learning-Based Leadership Development Program

We constructed a training program for top-talents of a Bank with Scharmer Theory-U as the model. In this training program, we implemented the action learning perspective, as it is claimed to be the most effective one currently available. In the process, participants were encouraged to be more involved, especially compared to traditional lecturing. The goal of this study is to assess the effectiveness of this particular training. The program consists of six days non-residential workshop within two months. Between each workshop, the participants were involved in the works of action learning group. They were challenged by dealing with the real problem related to their tasks at work. The participants of the program were 30 best talents who were chosen according to their yearly performance. Using paired difference statistical test in the behavioral assessment, we found that the training was not effective to increase participants’ leadership competencies. For the future development program, we suggested to modify the goals of the program toward the next stage of development.

Microscopic Simulation of Toll Plaza Safety and Operations

The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.

An Analysis of Digital Forensic Laboratory Development among Malaysia’s Law Enforcement Agencies

Cybercrime is on the rise, and yet many Law Enforcement Agencies (LEAs) in Malaysia have no Digital Forensics Laboratory (DFL) to assist them in the attrition and analysis of digital evidence. From the estimated number of 30 LEAs in Malaysia, sadly, only eight of them owned a DFL. All of the DFLs are concentrated in the capital of Malaysia and none at the state level. LEAs are still depending on the national DFL (CyberSecurity Malaysia) even for simple and straightforward cases. A survey was conducted among LEAs in Malaysia owning a DFL to understand their history of establishing the DFL, the challenges that they faced and the significance of the DFL to their case investigation. The results showed that the while some LEAs faced no challenge in establishing a DFL, some of them took seven to 10 years to do so. The reason was due to the difficulty in convincing their management because of the high costs involved. The results also revealed that with the establishment of a DFL, LEAs were better able to get faster forensic result and to meet agency’s timeline expectation. It is also found that LEAs were also able to get more meaningful forensic results on cases that require niche expertise, compared to sending off cases to the national DFL. Other than that, cases are getting more complex, and hence, a continuous stream of budget for equipment and training is inevitable. The result derived from the study is hoped to be used by other LEAs in justifying to their management the benefits of establishing an in-house DFL.

CRYPTO COPYCAT: A Fashion Centric Blockchain Framework for Eliminating Fashion Infringement

The fashion industry represents a significant portion of the global gross domestic product, however, it is plagued by cheap imitators that infringe on the trademarks which destroys the fashion industry's hard work and investment. While eventually the copycats would be found and stopped, the damage has already been done, sales are missed and direct and indirect jobs are lost. The infringer thrives on two main facts: the time it takes to discover them and the lack of tracking technologies that can help the consumer distinguish them. Blockchain technology is a new emerging technology that provides a distributed encrypted immutable and fault resistant ledger. Blockchain presents a ripe technology to resolve the infringement epidemic facing the fashion industry. The significance of the study is that a new approach leveraging the state of the art blockchain technology coupled with artificial intelligence is used to create a framework addressing the fashion infringement problem. It transforms the current focus on legal enforcement, which is difficult at best, to consumer awareness that is far more effective. The framework, Crypto CopyCat, creates an immutable digital asset representing the actual product to empower the customer with a near real time query system. This combination emphasizes the consumer's awareness and appreciation of the product's authenticity, while provides real time feedback to the producer regarding the fake replicas. The main findings of this study are that implementing this approach can delay the fake product penetration of the original product market, thus allowing the original product the time to take advantage of the market. The shift in the fake adoption results in reduced returns, which impedes the copycat market and moves the emphasis to the original product innovation.

A Hybrid Artificial Intelligence and Two Dimensional Depth Averaged Numerical Model for Solving Shallow Water and Exner Equations Simultaneously

Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Ear Protectors and Their Action in Protecting Hearing System of Workers against Occupational Noise

For many years, the ear protectors have been used to preventing the audio and non-audio effects of received noise from occupation environments. Despite performing hearing protection programs, there are many people which still suffer from noise-induced hearing loss. This study was conducted with the aim of determination of human hearing system response to received noise and the effectiveness of ear protectors on preventing of noise-induced hearing loss. Sound pressure microphones were placed in a simulated ear canal. The severity of noise measured inside and outside of ear canal. The noise reduction values due to installing ear protectors were calculated in the octave band frequencies and LabVIEW programmer. The results of noise measurement inside and outside of ear canal showed a different in received sound levels by ear canal. The effectiveness of ear protectors has been considerably reduced for the low frequency limits. A change in resonance frequency also was observed after using ear protectors. The study indicated the ear canal structure may affect the received noise and it may lead a difference between the received sound from the measured sound by a sound level meter, and hearing system. It means the human hearing system may probably respond different from a sound level meter. Hearing protectors’ efficiency declines by increasing the noise levels, and thus, they are not suitable to protect workers against industrial noise particularly low frequency noise. Hearing protectors may be solely a reason to damaging of hearing system in a special frequency via changing of human hearing system acoustical structure. We need developing the subjective method of hearing protectors testing, because their evaluation is not designed based on industrial noise or in the field.

Improving Health Care and Patient Safety at the ICU by Using Innovative Medical Devices and ICT Tools: Examples from Bangladesh

Innovative medical technologies offer more effective medical care, with less risk to patient and healthcare personnel. Medical technology and devices when properly used provide better data, precise monitoring and less invasive treatments and can be more targeted and often less costly. The Intensive Care Unit (ICU) equipped with patient monitoring, respiratory and cardiac support, pain management, emergency resuscitation and life support devices is particularly prone to medical errors for various reasons. Many people in the developing countries now wonder whether their visit to hospital might harm rather than help them. This is because; clinicians in the developing countries are required to maintain an increasing workload with limited resources and absence of well-functioning safety system. A team of experts from the medical, biomedical and clinical engineering in Sweden and Bangladesh have worked together to study the incidents, adverse events at the ICU in Bangladesh. The study included both public and private hospitals to provide a better understanding for physical structure, organization and practice in operating processes of care, and the occurrence of adverse outcomes the errors, risks and accidents related to medical devices at the ICU, and to develop a ICT based support system in order to reduce hazards and errors and thus improve the quality of performance, care and cost effectiveness at the ICU. Concrete recommendations and guidelines have been made for preparing appropriate ICT related tools and methods for improving the routine for use of medical devices, reporting and analyzing of the incidents at the ICU in order to reduce the number of undetected and unsolved incidents and thus improve the patient safety.

Specification Requirements for a Combined Dehumidifier/Cooling Panel: A Global Scale Analysis

The use of a radiant cooling solution would enable to lower cooling needs which is of great interest when the demand is initially high (hot climate). But, radiant systems are not naturally compatibles with humid climates since a low-temperature surface leads to condensation risks as soon as the surface temperature is close to or lower than the dew point temperature. A radiant cooling system combined to a dehumidification system would enable to remove humidity for the space, thereby lowering the dew point temperature. The humidity removal needs to be especially effective near the cooled surface. This requirement could be fulfilled by a system using a single desiccant fluid for the removal of both excessive heat and moisture. This task aims at providing an estimation of the specification requirements of such system in terms of cooling power and dehumidification rate required to fulfill comfort issues and to prevent any condensation risk on the cool panel surface. The present paper develops a preliminary study on the specification requirements, performances and behavior of a combined dehumidifier/cooling ceiling panel for different operating conditions. This study has been carried using the TRNSYS software which allows nodal calculations of thermal systems. It consists of the dynamic modeling of heat and vapor balances of a 5m x 3m x 2.7m office space. In a first design estimation, this room is equipped with an ideal heating, cooling, humidification and dehumidification system so that the room temperature is always maintained in between 21◦C and 25◦C with a relative humidity in between 40% and 60%. The room is also equipped with a ventilation system that includes a heat recovery heat exchanger and another heat exchanger connected to a heat sink. Main results show that the system should be designed to meet a cooling power of 42W.m−2 and a desiccant rate of 45 gH2O.h−1. In a second time, a parametric study of comfort issues and system performances has been achieved on a more realistic system (that includes a chilled ceiling) under different operating conditions. It enables an estimation of an acceptable range of operating conditions. This preliminary study is intended to provide useful information for the system design.

Meta-Learning for Hierarchical Classification and Applications in Bioinformatics

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Modeling and Simulation of Ship Structures Using Finite Element Method

The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Free Vibration of Axially Functionally Graded Simply Supported Beams Using Differential Transformation Method

Free vibration analysis of homogenous and axially functionally graded simply supported beams within the context of Euler-Bernoulli beam theory is presented in this paper. The material properties of the beams are assumed to obey the linear law distribution. The effective elastic modulus of the composite was predicted by using the rule of mixture. Here, the complexities which appear in solving differential equation of transverse vibration of composite beams which limit the analytical solution to some special cases are overcome using a relatively new approach called the Differential Transformation Method. This technique is applied for solving differential equation of transverse vibration of axially functionally graded beams. Natural frequencies and corresponding normalized mode shapes are calculated for different Young’s modulus ratios. MATLAB code is designed to solve the transformed differential equation of the beam. Comparison of the present results with the exact solutions proves the effectiveness, the accuracy, the simplicity, and computational stability of the differential transformation method. The effect of the Young’s modulus ratio on the normalized natural frequencies and mode shapes is found to be very important.

Green Function and Eshelby Tensor Based on Mindlin’s 2nd Gradient Model: An Explicit Study of Spherical Inclusion Case

Using Fourier transform and based on the Mindlin's 2nd gradient model that involves two length scale parameters, the Green's function, the Eshelby tensor, and the Eshelby-like tensor for a spherical inclusion are derived. It is proved that the Eshelby tensor consists of two parts; the classical Eshelby tensor and a gradient part including the length scale parameters which enable the interpretation of the size effect. When the strain gradient is not taken into account, the obtained Green's function and Eshelby tensor reduce to its analogue based on the classical elasticity. The Eshelby tensor in and outside the inclusion, the volume average of the gradient part and the Eshelby-like tensor are explicitly obtained. Unlike the classical Eshelby tensor, the results show that the components of the new Eshelby tensor vary with the position and the inclusion dimensions. It is demonstrated that the contribution of the gradient part should not be neglected.

Development of Numerical Model to Compute Water Hammer Transients in Pipe Flow

Water hammer is a hydraulic transient problem which is commonly encountered in the penstocks of hydropower plants. The numerical model was developed to estimate the transient behavior of pressure waves in pipe systems. The computational algorithm was proposed to model the water hammer phenomenon in a pipe system with pump shutdown at midstream and sudden valve closure at downstream. To predict the pressure head and flow velocity as a function of time as a result of rapidly closing a valve and pump shutdown, two boundary conditions at the ends considering pump operation and valve control can be implemented as specified equations of the pressure head and flow velocity based on the characteristics method. It was shown that the effects of transient flow make it determine the needs for protection devices, such as surge tanks, surge relief valves, or air valves, at various points in the system against overpressure and low pressure. It produced reasonably good performance with the results of the proposed transient model for pipeline systems. The proposed numerical model can be used as an efficient tool for the safety assessment of hydropower plants due to water hammer.

Outbound Tourism in Developed Countries: Analysis of the Trends, Behavior and the Transformation of the Moroccan Demand for International Travels

Outbound tourism in Morocco, as in the majority of developing countries, reveals some of the aspects of inequality between the north and the south. Considered by some researchers as one of the facets of the development crisis, access to tourism and especially international tourism is a chance for a small minority with financial means, while the vast portions of the population dream rather of immigrating to a developed country for the sake of improving their standard of living. The right to travel is also limited by visa requirements, procedures in host countries, security and technical measures and creates discrimination in the practice of tourism. These conditions do not seem to be favorable to the democratization of the practice of international tourism for the populations of the southern countries. This paper is a contribution to the reading of the trends of outbound tourism in developing countries through the example of Morocco. It highlights the different aspects of Moroccan outbound tourism, destinations and the behavior of tourists through an analysis of the offer of a sample of 50 travel agencies. In the same vein, it offers a reading grid of the possibilities offered for the development of outbound tourism and the various existing obstacles to the democratization of international outbound tourism in the southern countries. This reading reveals the transformation in the behavior of Moroccan international tourists as well as the profound changes in Moroccan society, through a model of statistical analysis.