A Network Traffic Prediction Algorithm Based On Data Mining Technique

This paper is a description approach to predict incoming and outgoing data rate in network system by using association rule discover, which is one of the data mining techniques. Information of incoming and outgoing data in each times and network bandwidth are network performance parameters, which needed to solve in the traffic problem. Since congestion and data loss are important network problems. The result of this technique can predicted future network traffic. In addition, this research is useful for network routing selection and network performance improvement.

Promising Immobilization of Cadmium and Lead inside Ca-rich Glass-ceramics

Considering toxicity of heavy metals and their accumulation in domestic wastes, immobilization of lead and cadmium is envisaged inside glass-ceramics. We particularly focused this work on calcium-rich phases embedded in a glassy matrix. Glass-ceramics were synthesized from glasses doped with 12 wt% and 16 wt% of PbO or CdO. They were observed and analyzed by Electron MicroProbe Analysis (EMPA) and Analytical Scanning Electron Microscopy (ASEM). Structural characterization of the samples was performed by powder XRay Diffraction. Diopside crystals of CaMgSi2O6 composition are shown to incorporate significant amounts of cadmium (up to 9 wt% of CdO). Two new crystalline phases are observed with very high Cd or Pb contents: about 40 wt% CdO for the cadmiumrich phase and near 60 wt% PbO for the lead-rich phase. We present complete chemical and structural characterization of these phases. They represent a promising way for the immobilization of toxic elements like Cd or Pb since glass ceramics are known to propose a “double barrier" protection (metal-rich crystals embedded in a glass matrix) against metal release in the environment.

Architecture Integrating Wireless Body Area Networks with Web Services for Ubiquitous Healthcare Service Provisioning

Recent advancements in sensor technologies and Wireless Body Area Networks (WBANs) have led to the development of cost-effective healthcare devices which can be used to monitor and analyse a person-s physiological parameters from remote locations. These advancements provides a unique opportunity to overcome current healthcare challenges of low quality service provisioning, lack of easy accessibility to service varieties, high costs of services and increasing population of the elderly experienced globally. This paper reports on a prototype implementation of an architecture that seamlessly integrates Wireless Body Area Network (WBAN) with Web services (WS) to proactively collect physiological data of remote patients to recommend diagnostic services. Technologies based upon WBAN and WS can provide ubiquitous accessibility to a variety of services by allowing distributed healthcare resources to be massively reused to provide cost-effective services without individuals physically moving to the locations of those resources. In addition, these technologies can reduce costs of healthcare services by allowing individuals to access services to support their healthcare. The prototype uses WBAN body sensors implemented on arduino fio platforms to be worn by the patient and an android smart phone as a personal server. The physiological data are collected and uploaded through GPRS/internet to the Medical Health Server (MHS) to be analysed. The prototype monitors the activities, location and physiological parameters such as SpO2 and Heart Rate of the elderly and patients in rehabilitation. Medical practitioners would have real time access to the uploaded information through a web application.

A Digital Media e-Learning Training Strategy for Healthcare Employees: Cost effective Distance Learning by Collaborative offline / online Engagement and Assessment

Within the healthcare system, training and continued professional development although essential, can be effected by cost and logistical restraints due to the nature of healthcare provision e.g employee shift patterns, access to expertise, cost factors in releasing staff to attend training etc. The use of multimedia technology for the development of e-learning applications is also a major cost consideration for healthcare management staff, and this type of media whether optical or on line requires careful planning in order to remain inclusive of all staff with potentially varied access to multimedia computing. This paper discusses a project in which the use of DVD authoring technology has been successfully implemented to meet the needs of distance learning and user considerations, and is based on film production techniques and reduced product turnaround deadlines.

Effect of Heat-Moisture Treatment on the Formation and Properties of Resistant Starches From Mung Bean (Phaseolus radiatus) Starches

Mung bean starches were subjected to heat-moisture treatment (HMT) by different moisture contents (15%, 20%, 25%, 30% and 35%) at 120Ôäâ for 12h. The impact on the yields of resistant starch (RS), microstructure, physicochemical and functional properties was investigated. Compared to native starch, the RS content of heat-moisture treated starches increased significantly. The RS level of HMT-20 was the highest of all the starches. Birefringence was displayed clear at the center of native starch. For HMT starches, pronounced birefringence was exhibited on the periphery of starch granules; however, birefringence disappeared at the centre of some starch granules. The shape of HMT starches hadn-t been changed and the integrity of starch granules was preserved for all the conditions. Concavity could be observed on HMT starches under scanning electronic microscopy. After HMT, apparent amylose contents were increased and starch macromolecule was degraded in comparison with those of native starch. There was a reduction in swelling power on HMT starches, but the solubility of HMT starches was higher than that of native starch. Both of native and HMT starches showed A-type X-ray diffraction pattern. Furthermore, there is a higher intensity at the peak of 15.0 and 22.9 Å than those of native starch.

In Silico Analysis of Pax6 Interacting Proteins Indicates Missing Molecular Links in Development of Brain and Associated Disease

The PAX6, a transcription factor, is essential for the morphogenesis of the eyes, brain, pituitary and pancreatic islets. In rodents, the loss of Pax6 function leads to central nervous system defects, anophthalmia, and nasal hypoplasia. The haplo-insufficiency of Pax6 causes microphthalmia, aggression and other behavioral abnormalities. It is also required in brain patterning and neuronal plasticity. In human, heterozygous mutation of Pax6 causes loss of iris [aniridia], mental retardation and glucose intolerance. The 3- deletion in Pax6 leads to autism and aniridia. The phenotypes are variable in peneterance and expressivity. However, mechanism of function and interaction of PAX6 with other proteins during development and associated disease are not clear. It is intended to explore interactors of PAX6 to elucidated biology of PAX6 function in the tissues where it is expressed and also in the central regulatory pathway. This report describes In-silico approaches to explore interacting proteins of PAX6. The models show several possible proteins interacting with PAX6 like MITF, SIX3, SOX2, SOX3, IPO13, TRIM, and OGT. Since the Pax6 is a critical transcriptional regulator and master control gene of eye and brain development it might be interacting with other protein involved in morphogenesis [TGIF, TGF, Ras etc]. It is also presumed that matricelluar proteins [SPARC, thrombospondin-1 and osteonectin etc] are likely to interact during transport and processing of PAX6 and are somewhere its cascade. The proteins involved in cell survival and cell proliferation can also not be ignored.

Comparison of Different Gas Turbine Inlet Air Cooling Methods

Gas turbine air inlet cooling is a useful method for increasing output for regions where significant power demand and highest electricity prices occur during the warm months. Inlet air cooling increases the power output by taking advantage of the gas turbine-s feature of higher mass flow rate when the compressor inlet temperature decreases. Different methods are available for reducing gas turbine inlet temperature. There are two basic systems currently available for inlet cooling. The first and most cost-effective system is evaporative cooling. Evaporative coolers make use of the evaporation of water to reduce the gas turbine-s inlet air temperature. The second system employs various ways to chill the inlet air. In this method, the cooling medium flows through a heat exchanger located in the inlet duct to remove heat from the inlet air. However, the evaporative cooling is limited by wet-bulb temperature while the chilling can cool the inlet air to temperatures that are lower than the wet bulb temperature. In the present work, a thermodynamic model of a gas turbine is built to calculate heat rate, power output and thermal efficiency at different inlet air temperature conditions. Computational results are compared with ISO conditions herein called "base-case". Therefore, the two cooling methods are implemented and solved for different inlet conditions (inlet temperature and relative humidity). Evaporative cooler and absorption chiller systems results show that when the ambient temperature is extremely high with low relative humidity (requiring a large temperature reduction) the chiller is the more suitable cooling solution. The net increment in the power output as a function of the temperature decrease for each cooling method is also obtained.

Static and Dynamic Complexity Analysis of Software Metrics

Software complexity metrics are used to predict critical information about reliability and maintainability of software systems. Object oriented software development requires a different approach to software complexity metrics. Object Oriented Software Metrics can be broadly classified into static and dynamic metrics. Static Metrics give information at the code level whereas dynamic metrics provide information on the actual runtime. In this paper we will discuss the various complexity metrics, and the comparison between static and dynamic complexity.

Designing a Rescue System for Earthquake-Stricken Area with the Aim of Facilitation and Accelerating Accessibilities (Case Study: City of Tehran)

Natural disasters, including earthquake, kill many people around the world every year. Society rescue actions, which start after the earthquake and are called LAST in abbreviation, include locating, access, stabilization and transportation. In the present article, we have studied the process of local accessibility to the injured and transporting them to health care centers. With regard the heavy traffic load due to earthquake, the destruction of connecting roads and bridges and the heavy debris in alleys and street, which put the lives of the injured and the people buried under the debris in danger, accelerating the rescue actions and facilitating the accessibilities are of great importance, obviously. Tehran, the capital of Iran, is among the crowded cities in the world and is the center of extensive economic, political, cultural and social activities. Tehran has a population of about 9.5 millions and because of the immigration of people from the surrounding cities. Furthermore, considering the fact that Tehran is located on two important and large faults, a 6 Richter magnitude earthquake in this city could lead to the greatest catastrophe during the entire human history. The present study is a kind of review and a major part of the required information for it, has been obtained from libraries all of the rescue vehicles around the world, including rescue helicopters, ambulances, fire fighting vehicles and rescue boats, and their applied technology, and also the robots specifically designed for the rescue system and the advantages and disadvantages of them, have been investigated. The studies show that there is a significant relationship between the rescue team-s arrival time at the incident zone and the number of saved people; so that, if the duration of burial under debris 30 minutes, the probability of survival is %99.3, after a day is %81, after 2days is %19 and after 5days is %7.4. The exiting transport systems all have some defects. If these defects are removed, more people could be saved each hour and the preparedness against natural disasters is increased. In this study, transport system has been designed for the rescue team and the injured; which could carry the rescue team to the incident zone and the injured to the health care centers. In addition, this system is able to fly in the air and move on the earth as well; so that the destruction of roads and the heavy traffic load could not prevent the rescue team from arriving early at the incident zone. The system also has the equipment required firebird for debris removing, optimum transport of the injured and first aid.

Polarization Modulation by free-Standing Asymmetric Hole Arrays

We theoretically demonstrate modulation of light polarization by a crossed rectangular hole array with asymmetric arm lengths. There are two waveguide modes that can modulate the x- and y- polarized incident waves independently. A specific structure is proposed to convert a left-hand incident wave to a right-hand outgoing wave by transmission.

Combined Simulated Annealing and Genetic Algorithm to Solve Optimization Problems

Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative states. However, there are also significant differences between them. The GA mechanism is parallel on a set of solutions and exchanges information using the crossover operation. SA works on a single solution at a time. In this work SA and GA are combined using new technique in order to overcome the disadvantages' of both algorithms.

A New Iterative Method for Solving Nonlinear Equations

In this study, a new root-finding method for solving nonlinear equations is proposed. This method requires two starting values that do not necessarily bracketing a root. However, when the starting values are selected to be close to a root, the proposed method converges to the root quicker than the secant method. Another advantage over all iterative methods is that; the proposed method usually converges to two distinct roots when the given function has more than one root, that is, the odd iterations of this new technique converge to a root and the even iterations converge to another root. Some numerical examples, including a sine-polynomial equation, are solved by using the proposed method and compared with results obtained by the secant method; perfect agreements are found.

Hybrid Feature and Adaptive Particle Filter for Robust Object Tracking

A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera. The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental results show the good performance of the proposed method.

SAF: A Substitution and Alignment Free Similarity Measure for Protein Sequences

The literature reports a large number of approaches for measuring the similarity between protein sequences. Most of these approaches estimate this similarity using alignment-based techniques that do not necessarily yield biologically plausible results, for two reasons. First, for the case of non-alignable (i.e., not yet definitively aligned and biologically approved) sequences such as multi-domain, circular permutation and tandem repeat protein sequences, alignment-based approaches do not succeed in producing biologically plausible results. This is due to the nature of the alignment, which is based on the matching of subsequences in equivalent positions, while non-alignable proteins often have similar and conserved domains in non-equivalent positions. Second, the alignment-based approaches lead to similarity measures that depend heavily on the parameters set by the user for the alignment (e.g., gap penalties and substitution matrices). For easily alignable protein sequences, it's possible to supply a suitable combination of input parameters that allows such an approach to yield biologically plausible results. However, for difficult-to-align protein sequences, supplying different combinations of input parameters yields different results. Such variable results create ambiguities and complicate the similarity measurement task. To overcome these drawbacks, this paper describes a novel and effective approach for measuring the similarity between protein sequences, called SAF for Substitution and Alignment Free. Without resorting either to the alignment of protein sequences or to substitution relations between amino acids, SAF is able to efficiently detect the significant subsequences that best represent the intrinsic properties of protein sequences, those underlying the chronological dependencies of structural features and biochemical activities of protein sequences. Moreover, by using a new efficient subsequence matching scheme, SAF more efficiently handles protein sequences that contain similar structural features with significant meaning in chronologically non-equivalent positions. To show the effectiveness of SAF, extensive experiments were performed on protein datasets from different databases, and the results were compared with those obtained by several mainstream algorithms.

A Weighted Sum Technique for the Joint Optimization of Performance and Power Consumption in Data Centers

With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Compared to traditional methodologies for multi-objective optimization problems, the proposed self-adaptive weighted sum technique does not rely on a systematical change of weights during the optimization procedure. The proposed technique is compared with the greedy and LR heuristics for large-scale problems, and the optimal solution for small-scale problems implemented in LINDO. the experimental results revealed that the proposed selfadaptive weighted sum technique outperforms both of the heuristics and projects a competitive performance compared to the optimal solution.

Mining Genes Relations in Microarray Data Combined with Ontology in Colon Cancer Automated Diagnosis System

MATCH project [1] entitle the development of an automatic diagnosis system that aims to support treatment of colon cancer diseases by discovering mutations that occurs to tumour suppressor genes (TSGs) and contributes to the development of cancerous tumours. The constitution of the system is based on a) colon cancer clinical data and b) biological information that will be derived by data mining techniques from genomic and proteomic sources The core mining module will consist of the popular, well tested hybrid feature extraction methods, and new combined algorithms, designed especially for the project. Elements of rough sets, evolutionary computing, cluster analysis, self-organization maps and association rules will be used to discover the annotations between genes, and their influence on tumours [2]-[11]. The methods used to process the data have to address their high complexity, potential inconsistency and problems of dealing with the missing values. They must integrate all the useful information necessary to solve the expert's question. For this purpose, the system has to learn from data, or be able to interactively specify by a domain specialist, the part of the knowledge structure it needs to answer a given query. The program should also take into account the importance/rank of the particular parts of data it analyses, and adjusts the used algorithms accordingly.

Technical Trading Rules in Emerging Stock Markets

Literature reveals that many investors rely on technical trading rules when making investment decisions. If stock markets are efficient, one cannot achieve superior results by using these trading rules. However, if market inefficiencies are present, profitable opportunities may arise. The aim of this study is to investigate the effectiveness of technical trading rules in 34 emerging stock markets. The performance of the rules is evaluated by utilizing White-s Reality Check and the Superior Predictive Ability test of Hansen, along with an adjustment for transaction costs. These tests are able to evaluate whether the best model performs better than a buy-and-hold benchmark. Further, they provide an answer to data snooping problems, which is essential to obtain unbiased outcomes. Based on our results we conclude that technical trading rules are not able to outperform a naïve buy-and-hold benchmark on a consistent basis. However, we do find significant trading rule profits in 4 of the 34 investigated markets. We also present evidence that technical analysis is more profitable in crisis situations. Nevertheless, this result is relatively weak.

Palmprint based Cancelable Biometric Authentication System

A cancelable palmprint authentication system proposed in this paper is specifically designed to overcome the limitations of the contemporary biometric authentication system. In this proposed system, Geometric and pseudo Zernike moments are employed as feature extractors to transform palmprint image into a lower dimensional compact feature representation. Before moment computation, wavelet transform is adopted to decompose palmprint image into lower resolution and dimensional frequency subbands. This reduces the computational load of moment calculation drastically. The generated wavelet-moment based feature representation is used to generate cancelable verification key with a set of random data. This private binary key can be canceled and replaced. Besides that, this key also possesses high data capture offset tolerance, with highly correlated bit strings for intra-class population. This property allows a clear separation of the genuine and imposter populations, as well as zero Equal Error Rate achievement, which is hardly gained in the conventional biometric based authentication system.

Database Development and Discrimination Algorithms for Membrane Protein Functions

We have developed a database for membrane protein functions, which has more than 3000 experimental data on functionally important amino acid residues in membrane proteins along with sequence, structure and literature information. Further, we have proposed different methods for identifying membrane proteins based on their functions: (i) discrimination of membrane transport proteins from other globular and membrane proteins and classifying them into channels/pores, electrochemical and active transporters, and (ii) β-signal for the insertion of mitochondrial β-barrel outer membrane proteins and potential targets. Our method showed an accuracy of 82% in discriminating transport proteins and 68% to classify them into three different transporters. In addition, we have identified a motif for targeting β-signal and potential candidates for mitochondrial β-barrel membrane proteins. Our methods can be used as effective tools for genome-wide annotations.

Account Management Method with Blind Signature Scheme

Reducing the risk of information leaks is one of the most important functions of identity management systems. To achieve this purpose, Dey et al. have already proposed an account management method for a federated login system using a blind signature scheme. In order to ensure account anonymity for the authentication provider, referred to as an IDP (identity provider), a blind signature scheme is utilized to generate an authentication token on an authentication service and the token is sent to an IDP. However, there is a problem with the proposed system. Malicious users can establish multiple accounts on an IDP by requesting such accounts. As a measure to solve this problem, in this paper, the authors propose an account checking method that is performed before account generation.