Burst on Hurst Algorithm for Detecting Activity Patterns in Networks of Cortical Neurons

Electrophysiological signals were recorded from primary cultures of dissociated rat cortical neurons coupled to Micro-Electrode Arrays (MEAs). The neuronal discharge patterns may change under varying physiological and pathological conditions. For this reason, we developed a new burst detection method able to identify bursts with peculiar features in different experimental conditions (i.e. spontaneous activity and under the effect of specific drugs). The main feature of our algorithm (i.e. Burst On Hurst), based on the auto-similarity or fractal property of the recorded signal, is the independence from the chosen spike detection method since it works directly on the raw data.

Development of a Support Tool for Cost and Schedule Integration Managment at Program Level

There has been gradual progress of late in construction projects, particularly in big-scale megaprojects. Due to the long-term construction period, however, with large-scale budget investment, lack of construction management technologies, and increase in the incomplete elements of project schedule management, a plan to conduct efficient operations and to ensure business safety is required. In particular, as the project management information system (PMIS) is meant for managing a single project centering on the construction phase, there is a limitation in the management of program-scale businesses like megaprojects. Thus, a program management information system (PgMIS) that includes program-level management technologies is needed to manage multiple projects. In this study, a support tool was developed for managing the cost and schedule information occurring in the construction phase, at the program level. In addition, a case study on the developed support tool was conducted to verify the usability of the system. With the use of the developed support tool program, construction managers can monitor the progress of the entire project and of the individual subprojects in real time.

The Emotional Language and Temperamental Traits

The aim of this study is to describe the associations between the temperamental traits and the narrative emotional expression. The Temperament Questionnaire was used: The FCB-TI of Zawadzki & Strelau. A sample of 85 persons described three emotional situations: love. hate, and anxiety. This study analyzes the verbal form of expression by means of a written account of emotions. The relationship between the narratives of love, hate and anxiety and temperament characteristics were studied. Results indicate that vigorousness (VI), perseverance (PE), sensory sensitivity (SS), emotional reactivity (ER), endurance (EN) and activeness (AC) have a significant impact on the emotional expression in narratives. The temperamental traits are linked to the form of emotional language. It means that temperament has an impact on cognitive representations of emotions.

A New Approach to Image Segmentation via Fuzzification of Rènyi Entropy of Generalized Distributions

In this paper, we propose a novel approach for image segmentation via fuzzification of Rènyi Entropy of Generalized Distributions (REGD). The fuzzy REGD is used to precisely measure the structural information of image and to locate the optimal threshold desired by segmentation. The proposed approach draws upon the postulation that the optimal threshold concurs with maximum information content of the distribution. The contributions in the paper are as follow: Initially, the fuzzy REGD as a measure of the spatial structure of image is introduced. Then, we propose an efficient entropic segmentation approach using fuzzy REGD. However the proposed approach belongs to entropic segmentation approaches (i.e. these approaches are commonly applied to grayscale images), it is adapted to be viable for segmenting color images. Lastly, diverse experiments on real images that show the superior performance of the proposed method are carried out.

Increase Success by Decreasing Admission for Maths– Fairytale or Reality?

South Africa is facing a crisis with not being able to produce enough graduates in the scarce skills areas to sustain economic growth. The crisis is fuelled by a school system that does not produce enough potential students with Mathematics, Accounting and Science. Since the introduction of the new school curriculum in 2008, there is no longer an option to take pure maths on a standard grade level. Instead, only two mathematical subjects are offered: pure maths (which is on par with higher grade maths) and mathematical literacy. It is compulsory to take one or the other. As a result, lees student finishes Grade 12 with pure mathematics every year. This national problem needs urgent attention if South Africa is to make any headway in critical skills development as mathematics is a gateway to scarce skills professions. Higher education institutions initiated several initiatives in an attempt to address the above, including preparatory courses, bridging programmes and extended curricula with foundation provisions. In view of the above, and government policy directives to broaden access in the scarce skills areas to increase student throughput, foundation provision was introduced for Commerce and Information Technology programmes at the Vaal Triangle Campus (VTC) of North-West University (NWU) in 2010. Students enrolling for extended programmes do not comply with the minimum prerequisites for the normal programmes. The question then arises as to whether these programmes have the intended impact? This paper reports the results of a two year longitudinal study, tracking the first year academic achievement of the two cohorts of enrolments since 2010. The results provide valuable insight into the structuring of an extended programme and its potential impact.

A Decision Boundary based Discretization Technique using Resampling

Many supervised induction algorithms require discrete data, even while real data often comes in a discrete and continuous formats. Quality discretization of continuous attributes is an important problem that has effects on speed, accuracy and understandability of the induction models. Usually, discretization and other types of statistical processes are applied to subsets of the population as the entire population is practically inaccessible. For this reason we argue that the discretization performed on a sample of the population is only an estimate of the entire population. Most of the existing discretization methods, partition the attribute range into two or several intervals using a single or a set of cut points. In this paper, we introduce a technique by using resampling (such as bootstrap) to generate a set of candidate discretization points and thus, improving the discretization quality by providing a better estimation towards the entire population. Thus, the goal of this paper is to observe whether the resampling technique can lead to better discretization points, which opens up a new paradigm to construction of soft decision trees.

Methods for Data Selection in Medical Databases: The Binary Logistic Regression -Relations with the Calculated Risks

The medical studies often require different methods for parameters selection, as a second step of processing, after the database-s designing and filling with information. One common task is the selection of fields that act as risk factors using wellknown methods, in order to find the most relevant risk factors and to establish a possible hierarchy between them. Different methods are available in this purpose, one of the most known being the binary logistic regression. We will present the mathematical principles of this method and a practical example of using it in the analysis of the influence of 10 different psychiatric diagnostics over 4 different types of offences (in a database made from 289 psychiatric patients involved in different types of offences). Finally, we will make some observations about the relation between the risk factors hierarchy established through binary logistic regression and the individual risks, as well as the results of Chi-squared test. We will show that the hierarchy built using the binary logistic regression doesn-t agree with the direct order of risk factors, even if it was naturally to assume this hypothesis as being always true.

How the Kinematic Swimming of European Eel Anguilla Anguilla Changes from Axial to Non-axial Velocity Flow

The aim of this study is to investigate the kinematics of undulatory elongated fish swimming against a velocity flow. We perform the experiments on European eel Anguilla Anguilla swimming in a hydrodynamic re-circulating tank with the velocity flow fixed at 0.2 m/s. We find that the undulating shape of overall eel body changes when it swims slantwise from the flow direction, by comparison to axial undulation shape. We examine this kinematics and we propose a general equation describing the lateral position of undulation body taking into account the direction of the eel-s swimming.

A Design-Based Cohesion Metric for Object-Oriented Classes

Class cohesion is an important object-oriented software quality attribute. It indicates how much the members in a class are related. Assessing the class cohesion and improving the class quality accordingly during the object-oriented design phase allows for cheaper management of the later phases. In this paper, the notion of distance between pairs of methods and pairs of attribute types in a class is introduced and used as a basis for introducing a novel class cohesion metric. The metric considers the methodmethod, attribute-attribute, and attribute-method direct interactions. It is shown that the metric gives more sensitive values than other well-known design-based class cohesion metrics.

Why Do Pakistani Customers Patronize Islamic Banks- An Empirical Analysis

Throughout the world, the Islamic way of banking and financing is increasing. The same trend is also visible in Pakistan, where the Islamic banking sector is increasing in size and volume each year. The question immediately arises as why the Pakistanis patronize the Islamic banking system? This study was carried out to find whether following the Islamic rules in finance is the main factor for such selection or whether other factors such as customer service, location, banking hour, physical facilities of the bank etc also have importance. The study was carried by distributing questionnaire and 200 responses were collected from the clients of Islamic banks. The result showed that the service quality and other factors are as important as following the Islamic rules for finance to retain old ustomers and catch new customers. The result is important and Islamic banks can take actions accordingly to look after both the factors

Simulating Discrete Time Model Reference Adaptive Control System with Great Initial Error

This article is based on the technique which is called Discrete Parameter Tracking (DPT). First introduced by A. A. Azab [8] which is applicable for less order reference model. The order of the reference model is (n-l) and n is the number of the adjustable parameters in the physical plant. The technique utilizes a modified gradient method [9] where the knowledge of the exact order of the nonadaptive system is not required, so, as to eliminate the identification problem. The applicability of the mentioned technique (DPT) was examined through the solution of several problems. This article introduces the solution of a third order system with three adjustable parameters, controlled according to second order reference model. The adjustable parameters have great initial error which represent condition. Computer simulations for the solution and analysis are provided to demonstrate the simplicity and feasibility of the technique.

H-ARQ Techniques for Wireless Systems with Punctured Non-Binary LDPC as FEC Code

This paper presents the H-ARQ techniques comparison for OFDM systems with a new family of non-binary LDPC codes which has been developed within the EU FP7 DAVINCI project. The punctured NB-LDPC codes have been used in a simulated model of the transmission system. The link level performance has been evaluated in terms of spectral efficiency, codeword error rate and average number of retransmissions. The NB-LDPC codes can be easily and effective implemented with different methods of the retransmission needed if correct decoding of a codeword failed. Here the Optimal Symbol Selection method is proposed as a Chase Combining technique.

Semantic Web Agent Communication Capable of Reasoning with Ontology and Agent Locations

Multi-agent communication of Semantic Web information cannot be realized without the need to reason with ontology and agent locations. This is because for an agent to be able to reason with an external semantic web ontology, it must know where and how to access to that ontology. Similarly, for an agent to be able to communicate with another agent, it must know where and how to send a message to that agent. In this paper we propose a framework of an agent which can reason with ontology and agent locations in order to perform reasoning with multiple distributed ontologies and perform communication with other agents on the semantic web. The agent framework and its communication mechanism are formulated entirely in meta-logic.

A Review of Coverage and Routing for Wireless Sensor Networks

The special constraints of sensor networks impose a number of technical challenges for employing them. In this review, we study the issues and existing protocols in three areas: coverage and routing. We present two types of coverage problems: to determine the minimum number of sensor nodes that need to perform active sensing in order to monitor a certain area; and to decide the quality of service that can be provided by a given sensor network. While most routing protocols in sensor networks are data-centric, there are other types of routing protocols as well, such as hierarchical, location-based, and QoS-aware. We describe and compare several protocols in each group. We present several multipath routing protocols and single-path with local repair routing protocols, which are proposed for recovering from sensor node crashes. We also discuss some transport layer schemes for reliable data transmission in lossy wireless channels.

Coordination between SC and SVC for Voltage Stability Improvement

At any point of time, a power system operating condition should be stable, meeting various operational criteria and it should also be secure in the event of any credible contingency. Present day power systems are being operated closer to their stability limits due to economic and environmental constraints. Maintaining a stable and secure operation of a power system is therefore a very important and challenging issue. Voltage instability has been given much attention by power system researchers and planners in recent years, and is being regarded as one of the major sources of power system insecurity. Voltage instability phenomena are the ones in which the receiving end voltage decreases well below its normal value and does not come back even after setting restoring mechanisms such as VAR compensators, or continues to oscillate for lack of damping against the disturbances. Reactive power limit of power system is one of the major causes of voltage instability. This paper investigates the effects of coordinated series capacitors (SC) with static VAR compensators (SVC) on steady-state voltage stability of a power system. Also, the influence of the presence of series capacitor on static VAR compensator controller parameters and ratings required to stabilize load voltages at certain values are highlighted.

Discrete Time Optimal Solution for the Connection Admission Control Problem

The Connection Admission Control (CAC) problem is formulated in this paper as a discrete time optimal control problem. The control variables account for the acceptance/ rejection of new connections and forced dropping of in-progress connections. These variables are constrained to meet suitable conditions which account for the QoS requirements (Link Availability, Blocking Probability, Dropping Probability). The performance index evaluates the total throughput. At each discrete time, the problem is solved as an integer-valued linear programming one. The proposed procedure was successfully tested against suitably simulated data.

Developing Pedotransfer Functions for Estimating Some Soil Properties using Artificial Neural Network and Multivariate Regression Approaches

Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.

Flight Control of a Trirotor Mini-UAV for Enhanced Situational Awareness

This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for an unmanned aerial vehicle (UAV). Autonomous vertical flight is a challenging but important task for tactical UAVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a two stage flight control procedure using two autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial nonlinear trirotor mini-UAV model. This control strategy for chosen mini-UAV model has been verified by simulation of hovering maneuvers using software package Simulink and demonstrated good performance for fast SA in realtime search-and-rescue operations.

A Study on Dogme 95 in the Korean Films

Many new experimental films which were free from conventional movie forms have appeared since Nubellbak Movement in the late 1950s. Forty years after the movement started, on March 13th, 1995, on the 100th anniversary of the birth of film, the declaration called Dogme 95, was issued in Copenhagen, Denmark. It aimed to create a new style of avant-garde film, and showed a tendency toward being anti-Hollywood and anti-genre, which were against the highly popular Hollywood trend of movies based on large-scale investment. The main idea of Dogme 95 is the opposition to 'the writer's doctrine' that a film should be the artist's individual work and to 'the overuse of technology' in film. The key figures declared ten principles called 'Vow of Chastity', by which new movie forms were to be produced. Interview (2000), directed by Byunhyuk, was made in 2000, five years after Dogme 95 was declared. This movie was dedicated as the first Asian Dogme. This study will survey the relationship between Korean film and the Vow of Chastity through the Korean films released in theaters from a viewpoint of technology and content. It also will call attention to its effects on and significance to Korean film in modern society.

Application of Genetic Algorithms to Feature Subset Selection in a Farsi OCR

Dealing with hundreds of features in character recognition systems is not unusual. This large number of features leads to the increase of computational workload of recognition process. There have been many methods which try to remove unnecessary or redundant features and reduce feature dimensionality. Besides because of the characteristics of Farsi scripts, it-s not possible to apply other languages algorithms to Farsi directly. In this paper some methods for feature subset selection using genetic algorithms are applied on a Farsi optical character recognition (OCR) system. Experimental results show that application of genetic algorithms (GA) to feature subset selection in a Farsi OCR results in lower computational complexity and enhanced recognition rate.