Miracle-dz/UniFAR-FTUs huggingface dataset:
Call Blocking Performance of New Reservation based Channel Assignment Scheme in Cellular Networks

Cellular operators are facing difficulties in supporting a huge increment in the subscribers due to spectrum and equipment restrictions. Substantial amount of investigation has been reported in the area of increasing call carrying capacity such as Reuse Partitioning and Directed Retry. However, such action increases the size of the network and results to higher installation, maintenance and optimization costs for the cellular operator. In this paper, a cost effective new channel reservation scheme based on subscribers’ average call duration has been reported. A
Text Summarization Approach for Unstructured Customer Reviews in the field of E-commerce A Comparative Analysis

— Due to the large amounts of text data being generated and organizations increased rapidly with the availability of Big Data platforms, there is no enough time to read and understand each document and make decisions based on document contents. Hence, there is a great demand for summarizing text documents to provide a representative substitute for the original documents. Text summarization is the task of reducing a text document with help of a computer program in order to create a summary that keeps the most important points of the original document. It is not easy task for people to manually summarize large documents of text data. There are two methods to summarize a text data 1) extractive summarization and 2) abstractive summarization. An extractive summarization method selects important sentence, content etc. from the original text data and combined them into shorter form. An abstractive summarization method understand the original text data and re-telling it in fewer words to generate summary. Popularity and growth of E-commerce has led to the creation of several websites that market and sell products as well as allow customer to post reviews and that reviews about a product grows rapidly. The number of reviews can be more than hundreds or thousands for a particular product. So it is difficult for a potential customer to take decision about products by reading all reviews manually and if he reads only a few of those reviews, then he may get a biased and confused view about the product. Product reviews are written by persons is not in structured form, natural language text; the process of summarizing them is one challenge and has a great commercial importance. With a feature-based summary, a current customer can easily see what other customer feels about product and can take decision. For a maker of a product, it is possible to combine summaries from multiple web sources to produce a single report for each product. In this paper, we present a survey and Comparative Analysis of Text Summarization Approach for Unstructured Customer Reviews in the field of E-commerce
Isolation of an Antifungal Compound from Anaphalis sinica Hance

The present investigation was in order to isolate antifungal constituents from Anaphalis sinica Hance, using activity against several phytopathogenic fungi as a lead. Bioactivity guided fractionation of the petroleum ether extract has led to the isolation of a tremetone derivative (compound 1 ), whose structure had been elucidated as 4,6-dihydroxy-14,14-dimethyltremeton based on extensive 1D and 2D NMR and HR-ESI-MS spectral data. Compound 1 had exhibited excellent antifungal activity against Valsa mali , Elsinoe ampelina and Gibberella saubinetii and the values of their EC 50 reached 2.27, 7.18 and 12.30 µg/mL respectively, that was comparable to the commercial fungicide carbendazim, whose EC 50 values were 1.60, 33.54 and 6.60 µg/mL respectively.
Real Time Speech Recognition Using DSK TMS320C6713

— Speech recognition is an important field of digital signal processing. Automatic Speaker Recognition (ASR) objective is to extract features, characterize and recognize speaker. Mel Frequency Cepstral Coefficients (MFCC) is most widely used feature vector for ASR. MFCC is used for designing a text dependent speaker identification system. In this paper the DSP processor TMS320C6713 with Code Composer Studio (CCS) has been used for real time speech recognition. For analyzing the performance of speech recognition, we have considered here four speaker’s 20 number of spoken words as numbers and commands of length 2 sec in time.
The Effect of Thymoquinone Extract of Black Seeds Toward Socket New Blood Vessels Formation Process After Extraction in Diabetic-Induced Rats

Background: Hyperglycemia elevates the advanced glycation end product (AGEs) formation which induced complication after tooth extraction, such as endothelial dysfunction. Thymoquinone (TQ), the active compoud of black seeds (Nigella sativa L.), has been known to stimulates new blood vessels activity also for its anti-diabetic properties. Objective: To determine the effect of Thymoquinone towards socket new blood vessels formation process (angiogenesis) after extraction on diabetic rats model. Methods: 27 male rats were injected STZ intravenously and rats with blood glucose level ≥250 mg/dl were divided into three groups (K, P1, P2). Rats were given aquadest (K), Thymoquinone (P1) and Metformin (P1). On 7th day after treatment, its lower first left molar teeth was extracted. 3 samples from each group were euthanasized on 3rd, 7th, and 10th day after axtraction. HE and Immunostaining VEGF was used to observe the new blood vessels formation (angiogenesis). Results and Conclusion: We found the lowest blood glucose in P1 group on 10th day after extraction. The new blood vessels formation in P1 showed the progressive formation compared to P2 and K group. We conclude that Thymoquinone treatment may improve the socket new blood vessels formation process and prevent the complication.
A Review on Methods of Image Dehazing

Literature survey is an important for understanding and gaining much more knowledge about the specific area of a subject. The outdoor images captured in inclement weather are degraded due to the presence of haze, fog, rain and so on. Images of scenes captured in bad weather have poor contrasts and colors. This may cause difficulty in detecting the objects in the captured hazy images. Due to haze there is a trouble to many computer vision applications as it diminishes the visibility of the scene. This paper presents a study about different image dehazing methods to remove the haze from the hazy images captured in real world weather conditions to recover a fast and improved quality of haze free images. There is a improvement in terms of contrast, visible range and color fidelity. All these techniques are widely used in many applications such as outdoor Surveillance, object detection, underwater images, etc. General Terms Bad weather conditions, Haze, Airlight, Direct attenuation, contrast, color fidelity, Haze model.
MODIFIED DOHERTY POWER AMPLIFIER FOR WIDER BAND

Wireless communication system are developing rapidly, due to which new standards like WIMAX and 4G Long Term Evaluating(LTE) with a purpose of achieving high data rate result in high end applications such as high speed internet, video conferences and broadband width. These applications require mobile base stations at the transmitter as well as at receiver (T/R) to support features like multiple bands, multiple modes, higher BW and less power consumption. The design and implementation of multi-standard transceivers for wireless mobile system is very complex task. In this paper we discuss the design of a wider band Doherty Amplifier, which operational frequency of 3 GHz to 3.75 GHz. The development of proposed DPA is based on techniques of inserting wider band compensators along with second and third harmonic tuning at the output of the GaN HEMT main and peak amplifier. In this work, the basic constraints in the basic DPA is  /4 impendence transformer has been eliminated with the help of Branch Line Coupler (BLC). The designed amplifier gives the drain efficiency 70% - 75% at about 46-43 dBm output power and gain around 12 dB in the desired band.
RoCA: A Humanoid Robotic Assistive Technology for Children with Autism

Current research suggests that autistic children are drawn to robots and are likely to benefit from robot mediated interventions. However, many autistic children from resource constrained environments have not benefited from robot enhanced therapy due to the high costs associated with the development and deployment of social robots. This paper presents the implementation of a novel low cost robotic assistive technology for children with autism to aid caregivers in their classroom activities. RoCA is a medium sized humanoid robot which has been equipped with motion, speech and interaction capabilities to encourage the children to learn through play.
Antibacterial activity of Zinc oxide nanoparticles on Staphylococcus aureus

Introduction: One of the main healthproblemsis increasing resistance of bacteria to antimicrobial agents world-wide. Nanoparticles can be useful for preventing the distribution of resistant bacteria in the hospital and community. This study was carried out to determine the antimicrobial activity ofzinc oxide (ZnO) nanoparticle against isolated Staphylococcus aureus. Method of study:This study was conducted on 268 Staphylococcus aureuswhichwas isolated from healthy carriers, patients and food materials in Golestan province, innorth –east Iran.Antimicrobial activity of ZnOnanoparticles (10-30 nmdiameters) against Staphylococcus aureus was carried out by Agar dilution method and subsequently by Microdilution method for thedetermination of its minimum inhibitory concentration (MIC). Distribution of MIC were evaluated and statistically analyzed on the basis of source, antibacterialresistance, the ability of biofilm formation and virulence factors. Results: The minimum concentration of ZnO nanoparticles that could prevent the growth of isolated Staphylococcus aureus was 625μg/ml.MIC50 and MIC90 were 1250 and 5000 μg/ml, respectively. The Mean MIC ofZnO nanoparticle on S.aureuswhich wasisolated from food material (2108.6μ/ml) was more than two other groups; patients: 1614. 2μg/ml,and Healthy Carriers: 1503. 9μg/ml.This difference was statistically significant (P = 0.02). There was not any statistically difference in the mean ofMIC amongS.aureus which was isolated from thepatients, but the MIC value was lower in the strains which were isolated from blood cultures. The mean MICvalueof ZnO in S.aureus resistant and sensitive to Gentamicin were 1564.25 and 2343.7, respectively (p = 0.04) and in resistant and sensitive to Erythromycin were 1530.59 and 2103.4, respectively (p = 0.06). There were not any significant differences among the strains according to antibiotic resistance profiles , the ability to produce biofilm, and ager typing groups. Conclusion: In addition to size of nanoparticles and the concentration of bacteria, we found that the efficacy of ZnO nanoparticles dependent mainly on the source of Staphylococcus aureus isolation and its resistance to GentamicinandErythromycin.
Investigation into Standard Image Restoration Methods and their Comparison with Proposed Technique for Deblurring Images

The restoration of digital image is very important process in the image processing. Image restoration attempts to restore images t hat have degraded because of camera shake, movement of object or both . The degradation mainly involves blurring and noise . By combining information extracted from both blurred and noisy images we show in this paper how to produce a high quality image that cannot be obtained by simply denoising the noisy image, or deblurring the blurred image alone. To remove blurring, we need to (i) know and analyse how the image is blurred (ii) restore a natural looking image through deconvolution formulas . In deconvulation the main thing is blur kernel or Point Spread Function . Estimating Blur kernel is really very challenging because the algorithm needs to distinguish between correct image pairs and Incorrect ones . Difficulty also arises as the because the algorithm needs to restore high frequency image contents attenuated by blur. In this paper , we shall deal with a few of these challenges. We will introduce an technique that shows blur kernel can be estimated by analyzing blurred edges i-e we shall analyze blurred edges to calculate Radon Transform and then recover the blur kernel using the inverse of Radon transform. This method is effective and is well suited to images with many edges. We introduce a method to integrate this data into a maximum-a-posteriori kernel estimation framework and show its pros and cons . In this paper we compare Restored Blurred Images by using four types of techniques of deblurring images such as Wiener filter,Regularised filter ,Lucy Richardson deconvlution algorithm and our proposed algorithm on the basis of Well-known image quality accessment parameters like mean squared error (MSE) and peak signal-to-noise ratio (PSNR).
Isolation , Identification and Enterotoxin Detection of Escherichia Coli Isolated from Calf Diarrhea and their Virulence Characteristics

A total of 260 E. coli isolates out of 342 bacterial isolates were obtained from faecal samples collected from 300 diarrhoeic calves from different localities in Khartoum State. The isolates were confirmed using API 20E and VITEK2 identification systems. Ninety isolates were confirmed by API 20E strips and twenty isolates scored high probability percentages by using VITEK2. Then 150 E. coli isolates were subjected to sensitivity test to ten antimicrobial agents used for treatment of calf diarrhea in Sudan. They exhibited high susceptibility to Gentamycin, Ampicillin, Ciprofloxacin, Sulphamethoxazole-trimethoprim, Cephalothin, Kanamycin, Chloramphenicol and Tetracycline but they demonstrated less sensitivity to Erythromycin and high resistance to Procaine Penicillin. Fifty E. coli isolates were examined for enterotoxins production using suckling mouse test for heat stable (STa) production and reversed passive latex agglutination test for heat labile (LT) production. Forty five isolates were positive for STa and ten isolates were positive for LT production. Also 110 of E. coli isolates were tested for specific fimbrial antigens possession. The agglutination reactions of fimbrial adhesions showed different percentages for K99(F5), K88(F4) and 987p(F6) which was detected in two isolates. Taken together the study showed that E. coli is the predominant bacterial spp isolated from diarrhoeic calves and the incidence rate of calf diarrhea in Khartoum State is 60%. Index terms — Calf diarrhea, E. coli, Enterotoxins, Khartoum State, Virulence
Characterisation of Cellulose produced by Pseudomonas sp. and Actinomycetes sp.

The demand for cellulose in paper making process is accelerating at an alarming rate. Alternate sources of cellulose has to be traced in order to meet this demand. In this study, Pseudomonas sp. and Actinomycetes sp. , isolated from the forest soil was tested for their potential to produce cellulose. Characterisation of cellulose produced by Pseudomonas sp. and Actinomycetes sp. , by FTIR and SEM indicate that Pseudomonas sp. and Actinomycetes sp. , produce cellulose. Furthermore, culture conditions has to be optimized for enhancing the production of bacterial cellulose.
ANALYSIS OF VARIABLE FREQUENCY PWM TECHNIQUES FOR UNEQUAL VOLTAGE SOURCE MULTILEVEL INVERTER

ABSTRACT This paper represents a new topology of asymmetrical variable frequency multilevel inverters using trapezoidal reference. Seven level output are achieved by the Binary DC sources. The asymmetric inverter is triggered by Variable Frequency Unipolar Pulse Width Modulation (VFUPWM) methods using Phase Disposition (PD) strategy, Alternate Phase Opposition Disposition (APOD) strategy, and Carrier Overlapping (CO) strategy. The Performances measure like Total Harmonic Distortion (THD), Fundamental VRMS, Crest Factor (CF), Distortion Factor (DF) and Form Factor (FF) are estimated for different modulation indices. Simulation is performed by using MATLAB-SIMUINK. It is observed that VFUPDPWM method provides lower THD, VFUCOPWM method provides higher fundamental VRMS output voltage and Form Factor, and VFUAPODPWM method provides lower Distortion Factor
A Relative Study on Task Schedulers in Hadoop MapReduce

— Hadoop is a framework for BigData processing in distributed applications. Hadoop cluster is built for running data intensive distributed applications. Hadoop distributed file system is the primary storage area for BigData. MapReduce is a model to aggregate tasks of a job. Task assignment is possible by schedulers. Schedulers guarantee the fair allocation of resources among users. When a user submits a job, it will move to a job queue. From the job queue, job will be divided into tasks and distributed to different nodes. By the proper assignment of tasks, job completion time will reduce. This can ensure better performance of the job. In this paper we study different default and extended task schedulers in Hadoop MapReduce.
Improved Search Results Of Keyword Query Using Data Imputation Approach

- Keyword queries over databases offer simple access to data, but this frequently suffer from low quality of ranking. It would be beneficial to categorize queries that are likely to have the low ranking quality to improve the user satisfaction. For example, the system may recommend to the user alternate queries for such hard queries. In this report, the characteristics of hard queries are analyzed and a novel framework to compute the degree of difficulty for a keyword query above a database are proposed by considering both the structure and the content of the database and the query results. Additionally, Imputation is the process of supplanting missing information with the substituted values. Numerous current modern and exploration data sets contain missing values. Issues connected with missing values are loss of productivity, entanglements in taking care of and investigating the information and inclination coming about because of differences between missing and complete data. The most existing imputation methods to string attribute values are inferring-based approaches with low imputation recall by just inferring missing values from the complete a portion of the data set. Recently, some retrieving-based methods are proposed to retrieve missing values from outer resources such as the World Wide Web but fails to respond to large number of search queries. So the approach is built called interactive Retrieving-Inferring data imPutation approach (TRIP), which is the interaction between the inferring-based methods and the retrieving-based methods. It performs retrieving and inferring alternately in filling in missing attribute values in a data set.
Imroving Performance of WSN using Low Latency SINR Based Data Gathering

— Data gathering is an essential operation in wireless sensor network (WSN) where all nodes senses information and forwards that data to base station (sink node) by multihop wireless communication. Typically data in WSN relayed over a tree type of topology to sink for their effective data gathering. In scenarios of real-time data collection in long-term deployed Wireless Sensor Networks (WSNs), low-latency data collection and long network lifetime become key issue.We propose Low Latency SINR based data gathering scheme in wireless sensor networks. The objective of the proposed scheme is to minimize delays in the data collection processes of wireless sensor networks . In the first phase of our proposed scheme, Data gathering tree is constructed iteratively based on reliability model. In the second phase, active links are scheduled on the tree for data transmission and transmitting power is assigned to each active link accordingly. Since the reliability of a link is highly related to its signal to interference plus noise ratio (SINR), the SINR of all the currently used links on the data gathering tree should be greater than a threshold to guarantee high reliability. Simulation results show that, when comparing with other common network structures in wireless sensor networks, the proposed scheme is able to shorten the delays in the data collection process significantly
Study of morphological features of breast carcinoma in relation to ER/PR status

Introduction: Breast carcinoma is the most common cancer among women in the urban Indian population and second only to cervical cancer in the rural population. Prognosis is related to a variety of clinical, pathologic and molecular features. Immunohistochemical evaluation of estrogen receptor (ER) and progesterone receptor (PR) status of breast carcinoma has become a routine investigation to predict the response to endocrine therapy. Aims and Objectives: To study patient and tumor characteristics in relation to estrogen and progesterone receptor (ER & PR) status of the tumor. Materials and Methods: This is a retrospective and prospective study of 100 cases of breast carcinoma diagnosed during January 2007 to September 2011 in the department of Pathology, NRI Medical College, and Chinakakani. Clinical details were archived from the files. Routine histological examination and Immunohistochemical analysis of all the cases were done. Results: Tumors were separated into four categories: ER+PR+ (33%), ER+PR− (15%), ER−PR+ (7%) and ER−PR− (45%). ER and PR immunoreactivity increased with advancing age. 52% of cases were in the right breast. Invasive lobular carcinoma, and papillary carcinoma were more frequently ER+PR+. High-grade infiltrating ductal carcinomas, pure comedo ductal carcinoma in situ, mucinous carcinoma and medullary carcinoma were predominantly ER−PR−. ER & PR immunoreactivity decreased with increasing tumor grade, lymph nodal metastasis, presence of tumor necrosis, desmoplasia and lymphovascular emboli. Conclusion: Histological grading together with receptor status offers an excellent method of predicting the prognosis and response to hormonal therapy which lightens up a prospect of various treatment modalities.
Computer and

: Document Recommendation system is the technique which provides necessary document to user in the context of his interest, in spite of having the search on search engine. This Dissertation work proposed a real time document recommendation system that depends on keyword extraction. The system is designed basically for a chat conversion . It can be deployed on local network wherein new documents are recommended based on conversation. Also the data can be analyzed to improve the domain knowledge and relevancy of documents retrieved. This dissertation work going to improve an answering system so that user can handle multiple requests effectively and accurately. This technique uses real time database which is provided by admin to the system. Effective Techniques for keyword extraction and clustering will make the system to provide more relevant recommendations.
Research of the Post Evaluation model for the Productivity Construction Project of Oilfield Based on the AHP

Summary In order to improve the investment efficiency, decision-making and management level of the productive capacity construction project of oilfield, on the basis of analysis of work processes and work content in detail, for uncertainty, high risk, investment and other characteristics, proposed a design scheme on computer technical supporting of auxiliary systems of the post evaluation for the productive capacity construction project of oilfield based on the AHP. First, determined the evaluation weights reasonably with the AHP; then got the composite score; finally, researched and developed the intelligent systems of satisfying engineering and technical personnel and the decision-making needs of project management according to the actual needs. The system is used in the work of the productive capacity construction project of oilfield, evaluate efficiently and objectively and the decision-making scientifically.