ABSTRACT:
In this paper, we focus on an energy efficient position-based three dimensional (3D) routing algorithm using distance information, which affects transmission power consumption between nodes as a metric. In wireless sensor networks, energy efficiency is one of the primary objectives of research. In addition, recent interest in sensor networks is extended to the need to understand how to design networks in a 3D space. Generally, most wireless sensor networks are based on two dimensional (2D) designs. However, in reality, such networks operate in a 3D space. Since 2D designs are simpler and easier to implement than 3D designs for routing algorithms in wireless sensor networks, the 2D assumption is somewhat justified and usually does not lead to major inaccuracies. However, in some applications such as an airborne to terrestrial sensor networks or sensor networks, which are deployed in mountains, taking 3D designs into consideration is reasonable. In this paper, we propose the Minimum Sum of Square distance (MSoS) algorithm as an energy efficient position-based three dimensional routing algorithm. In addition, we evaluate and compare the performance of the proposed routing algorithm with other algorithms through simulation. Finally, the results of the simulation show that the proposed routing algorithm is more energy efficient than other algorithms in a 3D space.

ABSTRACT:
In this work we report experimental results at loading points and compare them with hydrodinamic and mass transfer model predictions in order to determine the adjusted parameters and to know the relationship between a two-phase countercurrent flow and the geometry of the bed of the packing column. The bed of the packing is essential for the design of rectification and absorption columns. A study of hydrodynamic processes was carried out in an absorption column of 0.252 metre diameter with stainless steel gauze corrugated sheet packing by means of air-water and SO2-water systems. The experiment results include capacity, liquid hold-up and composition. The absorption test produced a total of 48 data points. The average deviation between the measured values of liquid hold-up to the predicted values is 3 time higher than the experimental data.

ABSTRACT:
Knowledge generation can be naturalized by adopting computational model of cognition and evolutionary approach. In this framework knowledge is seen as a result of the structuring of input data (data ? information ? knowledge) by an interactive computational process going on in the agent during the adaptive interplay with the environment, which clearly presents developmental advantage by increasing agent’s ability to cope with the situation dynamics. This paper addresses the mechanism of knowledge generation, a process that may be modeled as natural computation in order to be better understood and improved.

ABSTRACT:
An M&A due diligence is the process in which one of the parties to the transaction undertakes to investigate the other in order to judge whether to go forward with the transaction on the terms proposed. It encompasses the missions in three phases: searching and preliminary screening potential candidates, evaluating the candidates and deciding the target, and assisting the after-transaction integration. This work suggests using a Fuzzy Multiple Criteria Decision Making approach (Fuzzy MCDM) and develops detailed algorithms to carry out the second-phase task. The approach of MCDM is able to facilitate the analysis and integration of information from different aspects and criteria. The theory of Fuzzy Sets can include qualitative information in addition to quantitative information. In the developed algorithms the evaluators’ subjective judgments are expressed in linguistic terms which can better reflect human intuitive thought than the quantitative scores. These linguistic judgments are transformed into fuzzy numbers and made subsequent synthesis with quantitative financial figures. The order of candidates can be ranked after a defuzzification. Then the acquiring firm can work out a more specific study, including pricing and costing, on the priority candidates so as to decide the target.

ABSTRACT:
In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than “a priori” assumption of the global target function shape (e.g., linear or quadratic). In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.

ABSTRACT:
Rhinoplasty and facial plastic surgery are among the most frequently performed surgical procedures in the world. Although the underlying anatomical features of nose and face are very well known, performing a successful facial surgery requires not only surgical skills but also aesthetical talent from surgeon. Sculpting facial features surgically in correct proportions to end up with an aesthetically pleasing result is highly difficult. To further complicate the matter, some patients may have some anatomical features which affect rhinoplasty operation outcome negatively. If goes undetected, these anatomical variants jeopardize the surgery causing unexpected rhinoplasty outcomes. In this study, a model is developed with the aid of artificial intelligence tools, which analyses facial features of the patient from photograph, and generates an index of “appropriateness” of the facial features and an index of existence of anatomical variants that effect rhinoplasty negatively. The software tool developed is intended to detect the variants and warn the surgeon before the surgery. Another purpose of the tool is to generate an objective score to assess the outcome of the surgery.

ABSTRACT:
Presently, most computers authenticate user ID and password before users can login these systems. However, danger soon comes if the two items are known to hackers. In this paper, we propose a system, named Intrusion Detection and Identification System (IDIS), which builds a profile for each user in an intranet to keep track his/her usage habits as forensic features with which IDIS can identify who the underlying user in the intranet is. Our experimental results show that the recognition accuracy of students of computer science department is up to 98.99%.

ABSTRACT:
This paper aims at analyzing the development of guidelines on Intellectual Capital Statement, providing a comparison of them and presenting their importance within the knowledge management process of the today’s companies. We entered the Knowledge Era in which the basic economic resources are no longer financial capital, physical resources, or labor, but knowledge, called also intellectual capital (IC). Many analysts and investors demand for more information and they highlight the gap that exists between the information found in companies’ annual reports and the financial information regarding intangible part of the company requested by the market. Knowledge of the company should be measured and the effects should be communicated, as measurement without any further action has no sense. Intellectual capital statement seems an appropriate tool for that and becomes an integral part of the knowledge management of the modern enterprise. This kind of statement emphasizes the role of IC in relation to the value creation and communicates how knowledge resources are managed in the firms within a strategic objectives. This paper compares different approaches to IC statement preparation: underlines similarities and differences concerning the scope, methodology and terminology used and ensuing consequences. It raises significant implications for managers of the companies, researches and policy makers.

ABSTRACT:
In this paper we describe a preliminary, work-in-progress Spoken Language Understanding Software (SLUS) with tailored feedback options, which uses interactive spoken language interface to teach Iraqi Arabic and culture to second language learners. The SLUS analyzes input speech by the second language learner and grades for correct pronunciation in terms of supra-segmental and rudimentary segmental errors such as missing consonants. We evaluated this software on training data with the help of two native speakers, and found that the software recorded an accuracy of around 70% in law and order domain. For future work, we plan to develop similar systems for multiple languages.

ABSTRACT:
Material discriminated X-ray CT system has been constructed by using conventional X-ray tube (white X-ray source) and photon-counting X-ray imager as an application with energy band detection. We have already reported material identify X-ray CT using K-shell edge method elsewhere. In this report the principle of material discrimination was adapted the separation of electron-density and atomic number from attenuation coefficient mapping in X-ray CT reconstructed image in two wavelength X-ray CT method using white X-ray source and energy discriminated X-ray imager by using two monochrome X-ray source method. The measurement phantom was prepared as four kinds material rods (Carbon(C), Iron(Fe), Copper(Cu), Titanium(Ti) rods of 3mm-diameter) inside an aluminum(Al) rod of 20mm-diameter. We could observed material discriminated X-ray CT reconstructed image, however, the discrimination properties were not good than two monochrome X-ray CT method. This results was could be explained because X-ray scattering, beam-hardening and so on based on white X-ray source, which could not observe in two monochrome X-ray CT method. However, since our developed CdTe imager can be detect five energy-bands at the same time, we can use multi-band analysis to decrease the least square error margin. We will be able to obtain more high separation in atomic number mapping in X-ray CT reconstructed image by using this system.

ABSTRACT:
Modern technology has opened up many new possibilities in learning. Unfortunately, technology's uncritical use can also be damaging. In promoting productive and comprehensive IT learning the essential issue lies within the capability of the teacher and IT material to use computer to promote the basic cognitive aspects of learning and not only to manipulate the learner to remain motivated. Motivation is productive only if used with a focus towards knowledge and understanding. Especially in mathematics the concepts, we try to teach, are simple and logical, but often abstract. Smart use of computers can motivate this abstract concepts through intuitive simulations and animations as well as provide a sophisticated but simple insight into the causality of mathematical thinking. Thus, we argue that preparation of good e-Learning materials requires an almost contemplative focus on what we want to communicate in order not to overwhelm the student with too many effects that the technology offers. The concept and the vision of E-um project has been based on the above premises with a comprehensive system of simple technical, mathematical and didactical guidelines, together with a dynamic and creative system of permanent self evaluation and control. To support those premises new software package based on the Exe open source system has been developed. In order to provide an adequate technical framework for our conceptual ideas new emerging technologies with an emphasis on writing mathematical texts had been used.

ABSTRACT:
We analyzed the heartbeat interval by the detrended fluctuation analysis (DFA) in models and humans. In models, the myocardium of the healthy heart contracted regularly. The deteriorated heart model, however, showed alternating beats so-called “alternans.” The DFA revealed that if the heart is having “alternans” exhibited there is a declined scaling exponent (~0.5). In humans, the heart that had “alternans” also showed a low scaling exponent (~0.6). We consider that the coexistence of “alternans” and a low scaling exponent can be a risk marker in predictive and preventative diagnosis, supporting the idea that “alternans” can be a harbinger of sudden death.

ABSTRACT:
The European Environment Agency has started the implementation of a programme of land use and ecosystem accounts, following the System of Environmental and Economic Accounts (SEEA) guidelines of the United Nations. The purpose is to integrate information across the various ecosystem components and to support further assessments and modeling of these components and their interactions with economic and social developments. This programme reflects the increasing demand for environmental policy integration in Europe, both vertically through thematic policies as well as horizontally across policies in those sectors that contribute most to environmental impacts. The construction of land and ecosystem accounts is now feasible due to continuous improvements in monitoring, collecting and processing data and progress with the development of statistical methods that facilitate data assimilation and integration. The accounts are based on explicit spatial patterns provided by comprehensive land cover accounts that can be upscaled and downscaled using a 1km² grid to any type of administrative region or ecosystem zone (e.g., river basin catchments, coastal zones or bio- geographic areas). Land cover accounts have been produced for 24 countries in Europe and published in EEA Report in 2006.

ABSTRACT:
In recent years, we have seen several catastrophic & cascading failures of power systems throughout the world. Power system breakup and blackouts are rare events. However, when they occur, the effects on utilities & general population can be quite severe. To prevent or reduce cascading sequences of events caused by the various reasons, KEPRI is researching ways to revolutionize innovative strategies that will significantly reduce the vulnerability of the power system and will ensure successful restoration of service to customers. This paper describes a restoration guidelines / recommendations for the KEPS simulator, which allows power system operator and planner to simulate and plan restoration events in an interactive mode. The KEPS simulator provides a list of restoration events according to the priority based on some restoration rules and list of priority loads. Further, the paper will draw on research using information from a Jeju case study.

ABSTRACT:
Survey data collection projects strive to collect high quality data from survey respondents. The quality of the data collected is greatly dependent upon the effectiveness of field interviewers (FIs) to conduct inperson screenings and interviews. Training FIs and subsequently assessing their knowledge of project protocol, methods and interviewing techniques is critical to the overall success of any data collection effort. For large surveys, as the number of FIs increase, the cost of inperson training can become prohibitively large. As a cost effective solution to increase the quality of the field data, we developed a suite of web and media based training and assessment tools called iLearning and eHomeStudy for training field staff. Besides saving the project costs associated with inperson training, we are also able to provide refresher trainings throughout the year. This application also enables FIs to view standardized training courses at their convenience and at their own pace. This paper describes the technical details, key features and benefits of this application suite, and also it includes some details on user satisfaction and future directions.

ABSTRACT:
New technologies are needed to put on the market ever accelerated schedule in order to design and fabricate devices that fulfill consumers’ expectations. An industry-academy collaborative working mode is very efficient way to accelerate and diversify progression of novel technological solutions, educate new multidisciplinary professionals, and to act the function of new business incubation. This type of long-term research activity strengthens the position of research groups from small countries in an international competition.

ABSTRACT:
This paper introduces a novel method for human face recognition based on a simplified approach for the Pulse Coupled Neural Network (PCNN) Algorithm. The face image is introduced to the Intersecting Cortical Model (ICM) to be iterated 200 times, and then the time signals for the faces are compared to make a decision. Experimental results for human face recognition confirm that the proposed method lends itself to higher classification accuracy relative to existing techniques.