Landscape Visual Classification Using Land use and Contour Data for Tourism and Planning Decision Making in Cameron Highlands District

Cameron Highlands is known for upland tourism area with vast natural wealth, mountainous landscape endowed with rich diverse species as well as people traditions and cultures. With these various resources, CH possesses an interesting visual and panorama that can be offered to the tourist. However this benefit may not be utilized without obtaining the understanding of existing landscape structure and visual. Given a limited data, this paper attempts to classify landscape visual of Cameron Highlands using land use and contour data. Visual points of view were determined from the given tourist attraction points in the CH Local Plan 2003-2015. The result shows landscape visual and structure categories offered in the study area. The result can be used for further analysis to determine the best alternative tourist trails for tourism planning and decision making using readily available data.

Hybridizing Genetic Algorithm with Biased Chance Local Search

This paper explores university course timetabling problem. There are several characteristics that make scheduling and timetabling problems particularly difficult to solve: they have huge search spaces, they are often highly constrained, they require sophisticated solution representation schemes, and they usually require very time-consuming fitness evaluation routines. Thus standard evolutionary algorithms lack of efficiency to deal with them. In this paper we have proposed a memetic algorithm that incorporates the problem specific knowledge such that most of chromosomes generated are decoded into feasible solutions. Generating vast amount of feasible chromosomes makes the progress of search process possible in a time efficient manner. Experimental results exhibit the advantages of the developed Hybrid Genetic Algorithm than the standard Genetic Algorithm.

AGV Guidance System: An Application of Simple Active Contour for Visual Tracking

In this paper, a simple active contour based visual tracking algorithm is presented for outdoor AGV application which is currently under development at the USM robotic research group (URRG) lab. The presented algorithm is computationally low cost and able to track road boundaries in an image sequence and can easily be implemented on available low cost hardware. The proposed algorithm used an active shape modeling using the B-spline deformable template and recursive curve fitting method to track the current orientation of the road.

Probabilistic Method of Wind Generation Placement for Congestion Management

Wind farms (WFs) with high level of penetration are being established in power systems worldwide more rapidly than other renewable resources. The Independent System Operator (ISO), as a policy maker, should propose appropriate places for WF installation in order to maximize the benefits for the investors. There is also a possibility of congestion relief using the new installation of WFs which should be taken into account by the ISO when proposing the locations for WF installation. In this context, efficient wind farm (WF) placement method is proposed in order to reduce burdens on congested lines. Since the wind speed is a random variable and load forecasts also contain uncertainties, probabilistic approaches are used for this type of study. AC probabilistic optimal power flow (P-OPF) is formulated and solved using Monte Carlo Simulations (MCS). In order to reduce computation time, point estimate methods (PEM) are introduced as efficient alternative for time-demanding MCS. Subsequently, WF optimal placement is determined using generation shift distribution factors (GSDF) considering a new parameter entitled, wind availability factor (WAF). In order to obtain more realistic results, N-1 contingency analysis is employed to find the optimal size of WF, by means of line outage distribution factors (LODF). The IEEE 30-bus test system is used to show and compare the accuracy of proposed methodology.

A Cascaded Fuzzy Inference System for Dynamic Online Portals Customization

In our modern world, more physical transactions are being substituted by electronic transactions (i.e. banking, shopping, and payments), many businesses and companies are performing most of their operations through the internet. Instead of having a physical commerce, internet visitors are now adapting to electronic commerce (e-Commerce). The ability of web users to reach products worldwide can be greatly benefited by creating friendly and personalized online business portals. Internet visitors will return to a particular website when they can find the information they need or want easily. Dealing with this human conceptualization brings the incorporation of Artificial/Computational Intelligence techniques in the creation of customized portals. From these techniques, Fuzzy-Set technologies can make many useful contributions to the development of such a human-centered endeavor as e-Commerce. The main objective of this paper is the implementation of a Paradigm for the Intelligent Design and Operation of Human-Computer interfaces. In particular, the paradigm is quite appropriate for the intelligent design and operation of software modules that display information (such Web Pages, graphic user interfaces GUIs, Multimedia modules) on a computer screen. The human conceptualization of the user personal information is analyzed throughout a Cascaded Fuzzy Inference (decision-making) System to generate the User Ascribe Qualities, which identify the user and that can be used to customize portals with proper Web links.

Data Mining Techniques in Computer-Aided Diagnosis: Non-Invasive Cancer Detection

Diagnosis can be achieved by building a model of a certain organ under surveillance and comparing it with the real time physiological measurements taken from the patient. This paper deals with the presentation of the benefits of using Data Mining techniques in the computer-aided diagnosis (CAD), focusing on the cancer detection, in order to help doctors to make optimal decisions quickly and accurately. In the field of the noninvasive diagnosis techniques, the endoscopic ultrasound elastography (EUSE) is a recent elasticity imaging technique, allowing characterizing the difference between malignant and benign tumors. Digitalizing and summarizing the main EUSE sample movies features in a vector form concern with the use of the exploratory data analysis (EDA). Neural networks are then trained on the corresponding EUSE sample movies vector input in such a way that these intelligent systems are able to offer a very precise and objective diagnosis, discriminating between benign and malignant tumors. A concrete application of these Data Mining techniques illustrates the suitability and the reliability of this methodology in CAD.

Challenges and Opportunities for Biodiversity Conservation and Sustainable Development of Ecotourism in Lalzi Bay, Durres County, Albania - Today's Science for Tomorrow's Management. A Methodology Guide with a Concrete Example by Lalzi Bay, Durres County, Albania

Tourism and coastal lines are the business sectors since centuries especially in the European Nations and Albania is one such spots. However, in recent decades tourism is experienced as vulnerability of the surrounding ecological conditions of air, soil, water, land and the communities that are dependant and sharing the ecosystem among flora and fauna. Experts opine that apart from the maintenance of near-originality of ecological biodiversity the tourism rather known as ecotourism an indigenous socio-cultural maintenance of indigenous/traditional knowledge of the local people must be well cared in order to sustain on sustainable grounds. As a general tendency, growth of tourism has been affected by the deterioration in the economic conditions on one aspect and unsustainable ecological areas affected since human interventions earlier to this has negative impact on futuristic tourist spots. However, tourism in Albania as of now is 11% of GDP and coastal regions accounting to 2-4%. An amicable Mediterranean climate with 300 sunny days similar parameters of Greece and Spain throws up sustainable ecotourism in future decades provided public services namely, transportation, road safety, lodging, food availability, recreational regiments, banking accessibility are as per the World Tourism Organizations- protocols. Thus as of Albanian situation, classification of ecotourism activities to safe-guard the localities with its maintenance of ecological land, water and climate has become a paramount importance with a wanting and satisfactory options through harnessing human energy for profit and fitness of ecological flora and fauna. A check on anthropogenic wastes and their safer utilizations inclusive of agricultural and industrial operations in line with Lalzi Bay Coastal Line are of utmost importance for the reason that the Adriatic Sea Coast is the one long stretch of Albanian Lifeline. The present work is based on the methodology of the sustainable management of the same issue.

Municipal Solid Waste Management Problems in Nigeria: Evolving Knowledge Management Solution

The paper attempts a synthesis of problems relating to municipal waste management in Nigeria and proposes a conceptual knowledge management approach for tackling municipal waste problems in cities across Nigeria. The application of knowledge management approach and strategy is crucial for inculcating a change of attitude towards improving the management of waste. The paper is a review of existing literatures, information, policies and data on municipal waste management in Nigeria. The inefficient management of waste by individuals, households, consumers and waste management companies can be attributed to inadequate information on waste management benefits, lack of producers- involvement in waste management as well as poor implementation of government policies. The paper presents an alternative approach providing solutions promoting efficient municipal waste management.

A Comparison between Heuristic and Meta-Heuristic Methods for Solving the Multiple Traveling Salesman Problem

The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.

Economic Load Dispatch with Daily Load Patterns and Generator Constraints by Particle Swarm Optimization

This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction

Linguistic, Pragmatic and Evolutionary Factors in Wason Selection Task

In two studies we tested the hypothesis that the appropriate linguistic formulation of a deontic rule – i.e. the formulation which clarifies the monadic nature of deontic operators - should produce more correct responses than the conditional formulation in Wason selection task. We tested this assumption by presenting a prescription rule and a prohibition rule in conditional vs. proper deontic formulation. We contrasted this hypothesis with two other hypotheses derived from social contract theory and relevance theory. According to the first theory, a deontic rule expressed in terms of cost-benefit should elicit a cheater detection module, sensible to mental states attributions and thus able to discriminate intentional rule violations from accidental rule violations. We tested this prevision by distinguishing the two types of violations. According to relevance theory, performance in selection task should improve by increasing cognitive effect and decreasing cognitive effort. We tested this prevision by focusing experimental instructions on the rule vs. the action covered by the rule. In study 1, in which 480 undergraduates participated, we tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x rule formulation x type of violation x experimental instructions) between-subjects design. In study 2 – carried out by means of a 2 x 2 (rule formulation x type of violation) between-subjects design - we retested the hypothesis of rule formulation vs. the cheaterdetection hypothesis through a new version of selection task in which intentional vs. accidental rule violations were better discriminated. 240 undergraduates participated in this study. Results corroborate our hypothesis and challenge the contrasting assumptions. However, they show that the conditional formulation of deontic rules produces a lower performance than what is reported in literature.

A Novel Stator Resistance Estimation Method and Control Design of Speed-Sensorless Induction Motor Drives

Speed sensorless systems are intensively studied during recent years; this is mainly due to their economical benefit and fragility of mechanical sensors and also the difficulty of installing this type of sensor in many applications. These systems suffer from instability problems and sensitivity to parameter mismatch at low speed operation. In this paper an analysis of adaptive observer stability with stator resistance estimation is given.

Seismic Behavior and Capacity/Demand Analyses of a Simply-Supported Multi-Span Precast Bridge

This paper presents the results of an analytical study on the seismic response of a Multi-Span-Simply-Supported precast bridge in Washington State. The bridge was built in the early 1960's along Interstate 5 and was widened the first time in 1979 and the second time in 2001. The primary objective of this research project is to determine the seismic vulnerability of the bridge in order to develop the required retrofit measure. The seismic vulnerability of the bridge is evaluated using two seismic evaluation methods presented in the FHWA Seismic Retrofitting Manual for Highway Bridges, Method C and Method D2. The results of the seismic analyses demonstrate that Method C and Method D2 vary markedly in terms of the information they provide to the bridge designer regarding the vulnerability of the bridge columns.

Migration among Multicities

This paper proposes a simple model of economic geography within the Dixit-Stiglitz-Iceberg framework that may be used to analyze migration patterns among three cities. The cost–benefit tradeoffs affecting incentives for three types of migration, including echelon migration, are discussed. This paper develops a tractable, heterogeneous-agent, general equilibrium model, where agents share constant human capital, and explores the relationship between the benefits of echelon migration and gross human capital. Using Chinese numerical solutions, we study the manifestation of echelon migration and how it responds to changes in transportation cost and elasticity of substitution. Numerical results demonstrate that (i) there are positive relationships between a migration-s benefit-and-wage ratio, (ii) there are positive relationships between gross human capital ratios and wage ratios as to origin and destination, and (iii) we identify 13 varieties of human capital convergence among cities. In particular, this model predicts population shock resulting from the processes of migration choice and echelon migration.

Design, Implementation and Testing of Mobile Agent Protection Mechanism for MANETS

In the current research, we present an operation framework and protection mechanism to facilitate secure environment to protect mobile agents against tampering. The system depends on the presence of an authentication authority. The advantage of the proposed system is that security measures is an integral part of the design, thus common security retrofitting problems do not arise. This is due to the presence of AlGamal encryption mechanism to protect its confidential content and any collected data by the agent from the visited host . So that eavesdropping on information from the agent is no longer possible to reveal any confidential information. Also the inherent security constraints within the framework allow the system to operate as an intrusion detection system for any mobile agent environment. The mechanism is tested for most of the well known severe attacks against agents and networked systems. The scheme proved a promising performance that makes it very much recommended for the types of transactions that needs highly secure environments, e. g., business to business.

Constructing an Attitude Scale: Attitudes toward Violence on Televisions

The process of constructing a scale measuring the attitudes of youth toward violence on televisions is reported. A 30-item draft attitude scale was applied to a working group of 232 students attending the Faculty of Educational Sciences at Ankara University between the years 2005-2006. To introduce the construct validity and dimensionality of the scale, exploratory and confirmatory factor analysis was applied to the data. Results of the exploratory factor analysis showed that the scale had three factors that accounted for 58,44% (22,46% for the first, 22,15% for the second and 13,83% for the third factor) of the common variance. It is determined that the first factor considered issues related individual effects of violence on televisions, the second factor concerned issues related social effects of violence on televisions and the third factor concerned issues related violence on television programs. Results of the confirmatory factor analysis showed that all the items under each factor are fitting the concerning factors structure. An alpha reliability of 0,90 was estimated for the whole scale. It is concluded that the scale is valid and reliable.

Corporate Knowledge Communication and Knowledge Communication Difficulties

Communication is an important factor and a prop in directing corporate activities efficiently, in ensuring the flow of knowledge which is necessary for the continuity of the institution, in creating a common language in the institution, in transferring corporate culture and ultimately in corporate success. The idea of transmitting the knowledge among the workers in a healthy manner has revived knowledge communication. Knowledge communication can be defined as the act of mutual creation and communication of intuitions, assessments, experiences and capabilities, as long as maintained effectively, can provide advantages such as corporate continuity, access to corporate objectives and making true administrative decisions. Although the benefits of the knowledge communication to corporations are known, and the necessary worth and care is given, some hardships may arise which makes it difficult or even block it. In this article, difficulties that prevent knowledge communication will be discussed and solutions will be proposed.

Generalized Method for Estimating Best-Fit Vertical Alignments for Profile Data

When the profile information of an existing road is missing or not up-to-date and the parameters of the vertical alignment are needed for engineering analysis, the engineer has to recreate the geometric design features of the road alignment using collected profile data. The profile data may be collected using traditional surveying methods, global positioning systems, or digital imagery. This paper develops a method that estimates the parameters of the geometric features that best characterize the existing vertical alignments in terms of tangents and the expressions of the curve, that may be symmetrical, asymmetrical, reverse, and complex vertical curves. The method is implemented using an Excel-based optimization method that minimizes the differences between the observed profile and the profiles estimated from the equations of the vertical curve. The method uses a 'wireframe' representation of the profile that makes the proposed method applicable to all types of vertical curves. A secondary contribution of this paper is to introduce the properties of the equal-arc asymmetrical curve that has been recently developed in the highway geometric design field.

View-Point Insensitive Human Pose Recognition using Neural Network

This paper proposes view-point insensitive human pose recognition system using neural network. Recognition system consists of silhouette image capturing module, data driven database, and neural network. The advantages of our system are first, it is possible to capture multiple view-point silhouette images of 3D human model automatically. This automatic capture module is helpful to reduce time consuming task of database construction. Second, we develop huge feature database to offer view-point insensitivity at pose recognition. Third, we use neural network to recognize human pose from multiple-view because every pose from each model have similar feature patterns, even though each model has different appearance and view-point. To construct database, we need to create 3D human model using 3D manipulate tools. Contour shape is used to convert silhouette image to feature vector of 12 degree. This extraction task is processed semi-automatically, which benefits in that capturing images and converting to silhouette images from the real capturing environment is needless. We demonstrate the effectiveness of our approach with experiments on virtual environment.

The Para-Universe of Collaborative Group Work in Today-s University Classrooms: Strategies to Help Ensure Success

Group work, projects and discussions are important components of teacher education courses whether they are face-toface, blended or exclusively online formats. This paper examines the varieties of tasks and challenges with this learning format in a face to face class teacher education class providing specific examples of both failure and success from both the student and instructor perspective. The discussion begins with a brief history of collaborative and cooperative learning, moves to an exploration of the promised benefits and then takes a look at some of the challenges which can arise specifically from the use of new technologies. The discussion concludes with guidelines and specific suggestions.