Antimicrobial Effect of Essential oil of Plant Trigonella focnum greacum on some Bacteria Pathogens

The plant world is the source of many medicines. Recently, researchers have estimated that there are approximately 400,000 plant species worldwide, of which about a quarter or a third have been used by societies for medicinal purposes. The human uses of plants for thousands of years to treat various ailments, in many developing countries, much of the population trust in traditional doctors and their collections of medicinal plants to treat them. Essential oils have many therapeutic properties. In herbal medicine, they are used for their antiseptic properties against infectious diseases of fungal origin, against dermatophytes, those of bacterial origin. The aim of our study is to determine the antimicrobial effect of essential oils of the plant Trigonella focnum greacum on some pathogenic bacteria, it is a medicinal plant used in traditional therapy. The test adopted is based on the diffusion method on solid medium (Antibiogram), this method determines the sensitivity or resistance of a microorganism vis-à-vis the extract studied. Our study reveals that the essential oil of the plant Trigonella focnum greacum has a different effect on the resistance of germs. For staphiloccocus Pseudomonnas aeroginosa and Krebsilla, are moderately sensitive strains, also Escherichia coli and Candida albicans represents a high sensitivity. By against Proteus is a strain that represents a weak sensitivity.

Multidimensional Performance Management

In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.

A Pilot Study for the Optimization of Routes for Waste Collection Vehicles for the Göçmenköy District of Lefkoşa

A pilot project was carried out in 2007 by the senior students of Cyprus International University, aiming to minimize the total cost of waste collection in Northern Cyprus. Many developed and developing countries have cut their transportation costs – which lies between 30-40% – down at a rate of 40% percent, by implementing network models for their route assignments. Accordingly, a network model was implemented at Göçmenköy district, to optimize and standardize waste collection works. The work environment of the employees were also redesigned to provide maximum ergonomy and to increase productivity, efficiency and safety. Following the collection of the required data including waste densities, lengths of roads and population, a model was constructed to allocate the optimal route assignment for the waste collection trucks at Göçmenköy district.

Tourism-Impact on Environment-Observations from North Coastal Districts of A.P, India

This paper deals with the status of solid waste pollution in touristic spots of North coastal Andhra Pradesh. Case studies of Eco tourism, cultural tourism and pilgrim tourism are elaborately discussed and the study is based on both primary and secondary data. Data collection includes field collection of solid waste, semi structured interviews and observation of tourists. Results indicate generation of 72% Non biodegradable material in Eco touristic places like RK beach Visakhapatnam, Araku Valley. Pydithalli Jathra is a famous cultural touristic attraction and more than one lakh people converge here. The solid waste at this spot includes 20% coconut shells, 50% plastic bottles and covers, 20% Banana peelings and remaining are food materials. Radhasapthami is the most important festival celebrated at famous sun temple Arasavalli of Srikakulam. Here solid waste includes 50% water bottles, plastic covers, 10% papers, 10% hair, 30% left out food material and Banana peelings.

Induced Acyclic Graphoidal Covers in a Graph

An induced acyclic graphoidal cover of a graph G is a collection ψ of open paths in G such that every path in ψ has atleast two vertices, every vertex of G is an internal vertex of at most one path in ψ, every edge of G is in exactly one path in ψ and every member of ψ is an induced path. The minimum cardinality of an induced acyclic graphoidal cover of G is called the induced acyclic graphoidal covering number of G and is denoted by ηia(G) or ηia. Here we find induced acyclic graphoidal cover for some classes of graphs.

Applications of Cascade Correlation Neural Networks for Cipher System Identification

Crypto System Identification is one of the challenging tasks in Crypt analysis. The paper discusses the possibility of employing Neural Networks for identification of Cipher Systems from cipher texts. Cascade Correlation Neural Network and Back Propagation Network have been employed for identification of Cipher Systems. Very large collection of cipher texts were generated using a Block Cipher (Enhanced RC6) and a Stream Cipher (SEAL). Promising results were obtained in terms of accuracy using both the Neural Network models but it was observed that the Cascade Correlation Neural Network Model performed better compared to Back Propagation Network.

Off-Shore Port Management on the Environmental Issue - Case Study of Sichang Harbor

The research is to minimize environmental damage pertinent to maritime activities about the operation of lighter boat anchorage and its tugboat. The guidance on upgrading current harbor service and infrastructure has been provided to Kho Sichang Municpality. This will involve a study of the maritime logistics of the water area under jurisdiction of the Sichang island Municipality and possible recommendations may involve charging taxes, regulations and fees. With implementing these recommendations will help in protection of the marine environment and in increasing operator functionality. Additionally, our recommendation is to generate a consistent revenue stream to the municipality. The action items contained in this research are feasible and effective, the success of these initiatives are heavily dependent upon successful promotion and enforcement. Promoting new rules and regulations effectively and peacefully can be done through theories and techniques used in the psychology of persuasion. In order to assure compliance with the regulations, the municipality must maintain stringent patrols and fines for violators. In order to become success, the Municipality must preserve a consistent, transparent and significant enforcement system. Considering potential opportunities outside of the current state of the municipality, the authors recommend that Koh Sichang be given additional jurisdiction to capture value from the master vessels, as well as to confront the more significant environmental challenges these vessels pose. Finally, the authors recommend that the Port of Koh Sichang Island obtain a free port status in order to increase economic viability and overall sustainability.

Improving the Quality of e-learning Courses in Higher Education through Student Satisfaction

Thepurpose of the research is to characterize the levels of satisfaction of the students in e-learning post-graduate courses, taking into account specific dimensions of the course which were considered as benchmarks for the quality of this type of online learning initiative, as well as the levels of satisfaction towards each specific indicator identified in each dimension. It was also an aim of this study to understand how thesedimensions relate to one another. Using a quantitative research approach in the collection and analysis of the data, the study involves the participation of the students who attended on e-learning course in 2010/2011. The conclusions of this study suggest that online students present relatively high levels of satisfaction, which points towards a positive experience during the course. It is possible to note that there is a correlation between the different dimensions studied, consequently leading to different improvement strategies. Ultimately, this investigation aims to contribute to the promotion of quality and the success of e-learning initiatives in Higher Education.

A Video-based Algorithm for Moving Objects Detection at Signalized Intersection

Mixed-traffic (e.g., pedestrians, bicycles, and vehicles) data at an intersection is one of the essential factors for intersection design and traffic control. However, some data such as pedestrian volume cannot be directly collected by common detectors (e.g. inductive loop, sonar and microwave sensors). In this paper, a video based detection algorithm is proposed for mixed-traffic data collection at intersections using surveillance cameras. The algorithm is derived from Gaussian Mixture Model (GMM), and uses a mergence time adjustment scheme to improve the traditional algorithm. Real-world video data were selected to test the algorithm. The results show that the proposed algorithm has the faster processing speed and more accuracy than the traditional algorithm. This indicates that the improved algorithm can be applied to detect mixed-traffic at signalized intersection, even when conflicts occur.

Correction of Frequent English Writing Errors by Using Coded Indirect Corrective Feedback and Error Treatment

The purposes of this study are 1) to study the frequent English writing errors of students registering the course: Reading and Writing English for Academic Purposes II, and 2) to find out the results of writing error correction by using coded indirect corrective feedback and writing error treatments. Samples include 28 2nd year English Major students, Faculty of Education, Suan Sunandha Rajabhat University. Tool for experimental study includes the lesson plan of the course; Reading and Writing English for Academic Purposes II, and tool for data collection includes 4 writing tests of short texts. The research findings disclose that frequent English writing errors found in this course comprise 7 types of grammatical errors, namely Fragment sentence, Subject-verb agreement, Wrong form of verb tense, Singular or plural noun endings, Run-ons sentence, Wrong form of verb pattern and Lack of parallel structure. Moreover, it is found that the results of writing error correction by using coded indirect corrective feedback and error treatment reveal the overall reduction of the frequent English writing errors and the increase of students’ achievement in the writing of short texts with the significance at .05.

Bullies and Their Mothers: Who Influence Whom?

Even though most researchers would agree that in symbiotic relationships, like the one between parent and child, influences become reciprocal over time, empirical evidence supporting this claim is limited. The aim of the current study was to develop and test a model describing the reciprocal influence between characteristics of the parent-child relationship, such as closeness and conflict, and the child-s bullying and victimization experiences at school. The study used data from the longitudinal Study of Early Child-Care, conducted by the National Institute of Child Health and Human Development. The participants were dyads of early adolescents (5th and 6th graders during the two data collection waves) and their mothers (N=1364). Supporting our hypothesis, the findings suggested a reciprocal association between bullying and positive parenting, although this association was only significant for boys. Victimization and positive parenting were not significantly interrelated.

Analysis of Long-Term File System Activities on Cluster Systems

I/O workload is a critical and important factor to analyze I/O pattern and to maximize file system performance. However to measure I/O workload on running distributed parallel file system is non-trivial due to collection overhead and large volume of data. In this paper, we measured and analyzed file system activities on two large-scale cluster systems which had TFlops level high performance computation resources. By comparing file system activities of 2009 with those of 2006, we analyzed the change of I/O workloads by the development of system performance and high-speed network technology.

A Modified Fuzzy C-Means Algorithm for Natural Data Exploration

In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algorithms in dealing with the challenges posed by large collections of vague and uncertain natural data. This paper reviews concept of fuzzy logic and fuzzy clustering. The classical fuzzy c-means algorithm is presented and its limitations are highlighted. Based on the study of the fuzzy c-means algorithm and its extensions, we propose a modification to the cmeans algorithm to overcome the limitations of it in calculating the new cluster centers and in finding the membership values with natural data. The efficiency of the new modified method is demonstrated on real data collected for Bhutan-s Gross National Happiness (GNH) program.

Predicting Protein-Protein Interactions from Protein Sequences Using Phylogenetic Profiles

In this study, a high accuracy protein-protein interaction prediction method is developed. The importance of the proposed method is that it only uses sequence information of proteins while predicting interaction. The method extracts phylogenetic profiles of proteins by using their sequence information. Combining the phylogenetic profiles of two proteins by checking existence of homologs in different species and fitting this combined profile into a statistical model, it is possible to make predictions about the interaction status of two proteins. For this purpose, we apply a collection of pattern recognition techniques on the dataset of combined phylogenetic profiles of protein pairs. Support Vector Machines, Feature Extraction using ReliefF, Naive Bayes Classification, K-Nearest Neighborhood Classification, Decision Trees, and Random Forest Classification are the methods we applied for finding the classification method that best predicts the interaction status of protein pairs. Random Forest Classification outperformed all other methods with a prediction accuracy of 76.93%

Student Satisfaction Data for Work Based Learners

This paper aims to describe how student satisfaction is measured for work-based learners as these are non-traditional learners, conducting academic learning in the workplace, typically their curricula have a high degree of negotiation, and whose motivations are directly related to their employers- needs, as well as their own career ambitions. We argue that while increasing WBL participation, and use of SSD are both accepted as being of strategic importance to the HE agenda, the use of WBL SSD is rarely examined, and lessons can be learned from the comparison of SSD from a range of WBL programmes, and increased visibility of this type of data will provide insight into ways to improve and develop this type of delivery. The key themes that emerged from the analysis of the interview data were: learners profiles and needs, employers drivers, academic staff drivers, organizational approach, tools for collecting data and visibility of findings. The paper concludes with observations on best practice in the collection, analysis and use of WBL SSD, thus offering recommendations for both academic managers and practitioners.

Dew and Rain Water Collection in South Croatia

Dew harvesting needs only weak investment and exploits a free, clean and inexhaustible energy. This study aims to measure the relative contributions of dew and rain water in the Mediterranean Dalmatian coast and islands of Croatia and determine whether dew water is potable. Two sites were chosen, an open site on the coast favourable to dew formation (Zadar) and a less favourable site in a circus of mountains in Komiža (Vis Island). Between July 1st, 2003 and October 31st, 2006, dew hasbeen daily collected on a 1 m2 tilted (30°) test dew condenser together with ordinary meteorological data (air temperature and relative humidity, cloud coverage, windspeed and direction). The mean yearly cumulative dew yields were found to be 20 mm (Zadar) and 9.3 mm (Komiža ). During the dry season (May to October), monthly cumulative dew water yield can represent up to 38% of water collected by rain fall. In July 2003 and 2006, dew water represented about 120% of the monthly cumulative rain water. Dew and rain water were analyzed in Zadar. The corresponding parameters were measured: pH, electrical conductivity, major anions (HCO3 -, Cl-, SO4 2- , NO3 - , ,) and major cations (NH4 +, Na+, K+, Ca2+, Mg2+. Both dew and rain water are in conformity with the WHO directives for potability except Mg2+. Using existing roofs and refurbishing the abandoned impluviums to permit dew collection could then provide a useful supplementary amount of water, especially during the dry season.

Exploring the Effects of Top Managements Commitment on Knowledge Management Success in Academia: A Case Study

In this paper the effects of top management commitment on knowledge management activities has been analyzed. This research has been conducted as a case study in an academic environment. The data collection was carried out in the form of semi-structured interview with an interview guide. This study shows the effects of knowledge management strategic plan developing in academia strategic plan on knowledge management success. This paper shows the importance top management commitment factors including strategic plan, communication, and training on knowledge management success in academia. In particular the most important role of Strategic planning in knowledge management success is clarified. This study explores one of the necessary organizational infrastructures of successful implementation of knowledge management. The idea of this research could be applied in the other context especially in the industrial organizations.

Proteins Length and their Phenotypic Potential

Mendelian Disease Genes represent a collection of single points of failure for the various systems they constitute. Such genes have been shown, on average, to encode longer proteins than 'non-disease' proteins. Existing models suggest that this results from the increased likeli-hood of longer genes undergoing mutations. Here, we show that in saturated mutagenesis experiments performed on model organisms, where the likelihood of each gene mutating is one, a similar relationship between length and the probability of a gene being lethal was observed. We thus suggest an extended model demonstrating that the likelihood of a mutated gene to produce a severe phenotype is length-dependent. Using the occurrence of conserved domains, we bring evidence that this dependency results from a correlation between protein length and the number of functions it performs. We propose that protein length thus serves as a proxy for protein cardinality in different networks required for the organism's survival and well-being. We use this example to argue that the collection of Mendelian Disease Genes can, and should, be used to study the rules governing systems vulnerability in living organisms.

Fusing Local Binary Patterns with Wavelet Features for Ethnicity Identification

Ethnicity identification of face images is of interest in many areas of application, but existing methods are few and limited. This paper presents a fusion scheme that uses block-based uniform local binary patterns and Haar wavelet transform to combine local and global features. In particular, the LL subband coefficients of the whole face are fused with the histograms of uniform local binary patterns from block partitions of the face. We applied the principal component analysis on the fused features and managed to reduce the dimensionality of the feature space from 536 down to around 15 without sacrificing too much accuracy. We have conducted a number of preliminary experiments using a collection of 746 subject face images. The test results show good accuracy and demonstrate the potential of fusing global and local features. The fusion approach is robust, making it easy to further improve the identification at both feature and score levels.

The Design and Development of Multimedia Pronunciation Learning Management System

The proposed Multimedia Pronunciation Learning Management System (MPLMS) in this study is a technology with profound potential for inducing improvement in pronunciation learning. The MPLMS optimizes the digitised phonetic symbols with the integration of text, sound and mouth movement video. The components are designed and developed in an online management system which turns the web to a dynamic user-centric collection of consistent and timely information for quality sustainable learning. The aim of this study is to design and develop the MPLMS which serves as an innovative tool to improve English pronunciation. This paper discusses the iterative methodology and the three-phase Alessi and Trollip model in the development of MPLMS. To align with the flexibility of the development of educational software, the iterative approach comprises plan, design, develop, evaluate and implement is followed. To ensure the instructional appropriateness of MPLMS, the instructional system design (ISD) model of Alessi and Trollip serves as a platform to guide the important instructional factors and process. It is expected that the results of future empirical research will support the efficacy of MPLMS and its place as the premier pronunciation learning system.