Archives-j 

In this paper, Bayesian estimators of the population proportion of a sensitive attribute were developed when real life data were gathered through the administration of survey questionnaires on an induced abortion on 300 matured women in some selected hospitals in the metropolis. Using both the Kumaraswamy (KUMA) and the Generalised (GLS) beta distributions as alternative beta priors, efficiency of the proposed Bayesian estimators was established for a wide interval of the values of the population proportion. We observed that for small, medium as well as large sample sizes, the proposed Bayesian estimators were better than the conventional Bayesian estimator proposed by Hussain and Shabbir [10] when a simple beta prior was used.

The simple 4D- hyperchaotic dynamics of an autonomous oscillator circuit was studied by measuring its responsible in the form of phase-portrait, power spectrum and hyperchaotic time series. The circuit consists of just four linear elements (two capacitors and two inductors), one linear negative conductance and two ideal diodes. The power spectrums are presented to confirm the strong hyperchaotic nature of the oscillations of the circuit. The performance of the circuit is investigated by means of experimental and numerical confirmation of the appropriate differential equations. The features of the obtained results are respected for various engineering system such as chaos based secure communication systems with robustness against various interferences.

This study investigated some cross-linguistic properties of poetic and prosaic genre through the compilation and application of a parallel corpus. To this end, 16 stories from Sa'di's Gulistan (Rose Garden) and three translations of the book by Gladwin, Ross and Rehatsek were compared. Regarding the general contentions in terms of explicit hypotheses about the translations, four hypotheses were formulated to test two translation universals, i.e., simplification and explicitation. The analysis of the data demonstrated significant cross-linguistic differences in the original Persian text and its translations as pertinent to the intended properties.

Although the Solanaceae family leaves (tomato, eggplant, potato,…etc.) is a main host plant for the larvae of tomato leafminer, Tuta absoluta; field bindweed, Convolvulus arvensis is recorded as a new host plant to tomato leafminer, T. absoluta as a first time in Egypt. The larvae of T. absoluta were attacked the leaves of C. arvensis completely. This finding confirmed that the tomato leafminer is a polyphagous insect. This allows it to survive in many habitats in the absence of Solanaceae family crops. This result recommended that removing of field bindweed plants from tomato field may be reducing the tomato leafworm population.

Brushless Direct Current (BLDC) motors are one of the motor types rapidly gaining popularity. BLDC motors are used in industries such as Appliances, Automotive, Aerospace, Consumer, Medical, Industrial Automation Equipment and Instrumentation. As the name implies, BLDC motors do not use brushes for commutation; Instead, they are electronically commutated. This paper is focused on the various methods of testing and various tests both during construction and after construction is done on BLDC motors. These tests include: measurement of coil resistance, measurement of air gap, vibration testing, magnetic saturation, temperature experiments and etc. For a large number of experiments, The proposed method has been described for the size and various types of BLDC motors that in different conditions the motor is encountered.

Web 2.0 has become principle tool for accessing information. With Photo sharing websites like Flickr, Picassa, Zoomr images uploaded by user and their tags are available. But Missing tags and Noise problems among image and tag make it difficult to retrieve relevant image based on user’s preference. This requires tags refinement. We propose a model that utilizes Ranking based multicorrelation tensor factorization model for enriching tags pool. This model does it by constructing ternary relation between User, Image and Tag. RMTF does qualitative analysis on available tag set and find positive example and negative example by finding user, image tag interrelations. Tags are compared based on context relevance and semantic relevance. The proposed model finds better result than previous solutions. Given module is tested for multiple word query and shown attractive results.

ABSTRACT Suitability of growing media or substrates is essential for production of quality seedlings for transplant. It directly affects the development and later maintenance of the extensive functional system. A good growing medium would provide sufficient anchorage of support to plant, serves a reservoir for nutrient and water, allow oxygen diffusion to the root and permit gaseous exchange between the root and atmosphere outside the root substrate. In the present of study different growth media were used to germinate the seed of white yam (Dioscorea rotundata) under a controlled growth chamber to identify which among the tried media is best for yam seed. The growth media tested were Cocopeat, Peat pellet, Carbonized rice husk, Top soil, Cocopeat + Top soil and Carbonized rice husk + Top soil. Each treatment was measured into a nursery seedling basket, arranged in randomized complete block design, and replicated four times. Daily minimum and maximum Temperature and Relative humidity records were recorded throughout the experiment. At 60 and 90 days after seed sowing, growth response parameters were recorded and were subjected to analysis of variance and treatment means were separated using least significant difference at 5% probability level. Highest germination of 71.65 and 88.65% at 60 and 90 days after sowing respectively were recorded from yam seed planted in Cocopeat and the same trend was observed in respect of growth response parameters observed. Top soil had the least influence as growth medium, which was not significantly different from response from its mixture with other growth media.

CHROMagar Candida is a new differential culture medium that allows the isolation and presumptive identification of species of yeast of clinical importance. During the past two decades, there has been a significant increase in the prevalence of fungal infections caused by Candida species. The aim of the study was to isolate and identify Candida species from the oral cavity with CHROMagar Candida. This study was carried out in 30 patients with infections aged 21 to 90 years. Swabs samples were taken from oral cavity and were cultured directly on Sabouraud dextrose agar medium. In this study shows that CHROMagar Candida can easily identify four species of Candida on the basis of colonial color and morphology, and accurately differentiate between them i.e. Candida albicans, Candida glabrata, Candida tropicalis and Candida krusei. Results showed the prevalence of C.albicans (n = 21, 70%), C. glabrata (n = 5, 16.6%), C. krusei (n = 2, 6.7%), and C. tropicalis (n =2, 6.7%). In this investigation, CHROMagar produced light green colonies and were considered as Candida albicans, Pink with a darker mauve center colonies were identified as Candida glabrata, pink with pale borders colonies were identified as Candida krusei, and dark blue, purple diffusion colonies were identified as Candida tropicalis. CHROMagar is extremely useful in making a rapid presumptive identification of common yeast species. This capability plus the ability to detect mixed cultures of Candida species promises to improve and streamline the work flow in the mycology and clinical microbiology laboratory.

This paper describes a hybrid design for intrusion detection that combines anomaly detection with misuse detection. The proposed method includes an ensemble feature selecting classifier and a data mining classifier. The former consists of four classifiers using different sets of features and each of them employs a machine learning algorithm named fuzzy belief k-NN classification algorithm. The latter applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The outputs of ensemble feature selecting classifier and data mining classifier are then fused together to get the final decision. The experimental results indicate that hybrid approach effectively generates a more accurate intrusion detection model on detecting both normal usages and malicious activities.

Table of contents for the month of August 2011