Miracle-dz/UniFAR-FTUs huggingface dataset:
TB Detection in Chest Radiograph Using Deep Learning Architecture

Tuberculosis (TB) is a malignant infectious disease and is a major health threat in most of the regions in the world. Most of the diagnostic methods were developed in the last century which are still in use and are time consuming and generally unreliable. Chest radiography is used as the most common method for screening of large population. The successfulness of this method depends on the experience and the interpretation skill of the radiologists. Computer-aided diagnostic (CAD) system can be used to overcome this issue and can accelerate the process of active case finding. There is a considerable growth in recent years, in the field of deep learning, which allows the classification of extremely heterogeneous images. Convolutional neural networks (CNN), a deep learning technique has gained popularity due to its ability to learn mid and high level image representations. In this work various CNN models are used which classifies the chest radiographs into TB positive and TB negative classes. The performance of the system is measured on two publicly available datasets: Shenzhen chest X-ray set and Montgomery County chest X-ray set (MC). The proposed computer-aided diagnostic system for TB screening, achieves accuracy more than 80%, which is comparable to the performance of radiologists.
The Odyssey of Integration: Is Management its Achilles’ Heel?

Introduction: The importance of management to the implementation of integrated care is recognised in evidence and practice. Despite this recognition, there is a lack of clarity about what ‘good’ management of integrated care looks like, if the competences are different to management for ‘traditional’ care, and how such competences can be acquired. Theory and methods: This exploratory study is based on qualitative interviews with participants with extensive experience of implementing integrated care in senior professional, research, administrative and/or policy roles. It conceptualises management as working at ‘strategic’ and ‘operational’ levels. Results: Management of integrated care was seen to require an ability to create networks across professions and organisations, to be comfortable with distributing responsibilities, and to thoroughly understand the wider system. Competences to support these new ways of working included an understanding of how to implement people-centredness, to have courage to challenge the status quo, and to demonstrate humility to learn from others. Structured development opportunities for managers were lacking, but seen as vital for the sustainability of change. Discussion and conclusion: Management for integrated care remains an underdeveloped concept and practice. A first formulation of the competences necessary was achieved, but more work is urgently required to understand how to better prepare and support managers to achieve necessary changes in practice and culture.
Performance Analysis of Wireless Link Operating in α-µ Fading Channel

— The α-µ distribution is a generalized fading distribution which explores nonlinearities of the wireless propagation medium. This distribution includes the other distributions such as Gamma, Nakagami, exponential, Gaussian, Rayleigh etc. This makes α-µ distribution very interesting. In this paper probability density function and performance metrics such as outage and bit error rate of α-µ distribution is discussed with Monte-Carlo simulation results.
Design and Performance of the 3GPP Long Term Evolution Transceiver Physical Layer in SUI Channels

— Third Generation Partnership Project Long Term Evolution (3GPP LTE), emerged with an aim of providing voice, data, video and multimedia services on mobile phones at high speeds and cheap rates. Long Term Evolution (LTE) is one of the 4th generation wireless communications. The major aim of this paper is to analyze the LTE radio frame. We designed and simulated the OFDM system with cyclic prefix. Its Bit Error Rate (BER) is verified by changing the Signal to Noise Ratio (SNR) value. We designed, simulated the QAM digital modulation in SUI channels its BER vs. SNR are verified using simulations on MATLAB.
DYNAMIC PACKET SCHEDULING SCHEME FOR WIRELESS SENSOR NETWORK

- Wireless sensor networks (WSNs) have a wide variety of military and civil applications. The sensor nodes are powered by batteries with limited energy. Hostile or hazardous environments where the sensor nodes are deployed or the sheer number of the sensors prevents replacement or recharge of the batteries. Therefore in WSNs, scheduling of different types of packets is of vital importance to reduce sensors’ energy consumptions and end-to-end data transmission delays. Most of the existing packet-scheduling mechanisms of WSN use First Come First Served (FCFS), non-preemptive priority and preemptive priority scheduling algorithms. These algorithms incur a high processing overhead and long end-to-end data transmission delay due to the FCFS concept, starvation of high priority real-time data packets due to the transmission of a large data packet in non-preemptive priority scheduling, starvation of non-real-time data packets due to the probable continuous arrival of real-time data in preemptive priority scheduling, and improper allocation of data packets to queues in multilevel queue scheduling algorithms. Moreover, these algorithms are not dynamic to the changing requirements of WSN applications since their scheduling policies are predetermined. In this paper, we propose a Dynamic Multilevel Priority (DMP) packet scheduling scheme. In the proposed scheme, each node, except those at the last level of the virtual hierarchy in the zone-based topology of WSN, has three levels of priority queues. Real-time packets are placed into the highest-priority queue and can preempt data packets in other queues. Non-real-time packets are placed into two other queues based on a certain threshold of their estimated processing time. Leaf nodes have two queues for real-time and non-real-time data packets since they do not receive data from other nodes and thus, reduce end-to-end delay.
BER Mitigation in LDPC-COFDM System with Different Modulation Schemes over Generalized Gamma Fading Channel

—Orthogonal Frequency Division Multiplexing (OFDM) is a very promising technique to achieve the high-data-rate transmission required for wireless communications. To minimize the error rate performance of OFDM, forward error correction coding is essential. Forward Error correction (FEC) coding like LDPC coding is generally used to Improve BER performance . Recently, low-density parity-check code (LDPC) which can achieve the near Shannon limit performance, have attracted much attention. We explore the LDPC coded OFDM (LDPC-COFDM) systems to improve the error rate performance of OFDM.LDPC provides large minimum distance and also the power efficiency of the LDPC code increases significantly with the code length. Further this system is implemented with generalized gamma fading channel. It is a versatile wireless channel model, which can generalize the commonly used models for multipath fading and shadowing. Finally using a long Irregular LDPC code, it is shown that LDPC coded OFDM provides very low bit error rate compared to OFDM without coding case with a gain in transmitter power and thus making the link power efficient.
Smart Home Automation Based on IOT and Android Technology

: Accessibility of rapid portable systems like Gand Long Term Evolution (LTE) combined with less expensive and open advanced cells, versatile industry has seen a gigantic development as far as giving different administrations and applications at the fingertips to the natives. Internet of Things (IOT) is one of the promising innovations which can be utilized for interfacing, controlling and overseeing insightful articles which are associated with Internet through an IP address. Applications extending from keen administration, savvy training, brilliant horticulture, shrewd human services, savvy homes and so forth can utilize IOT to viable conveyance 0f administrations without manual intercession in a more powerful way. This paper examines about IOT and how it can be utilized for acknowledging brilliant home mechanization utilizing a small scale controller based Arduino board and Android portable application. In this paper, two models to be specific home mechanization utilizing Bluetooth in an indoor situation and home computerization utilizing IOT in an open air condition are introduced.
Cymbidium sinense cultivars

Cymbidium sinense cultivars exhibit an incredible range of diversity in the foliar morphology as well as the range of flower colors and shapes, which make them more popular among horticultural plants with great economic value. Understanding the genetic diversity and population structure in target populations will be of great importance for germplasm collection, breeding improvement and conversation of this species. In this study, Inter-simple sequence repeat (ISSR) markers were used to assess the genetic diversity and population structure of 151 C. sinense cultivars collected from China and Japan. C. sinense cultivars exhibited moderate levels of genetic diversity (H = 0.24, I = 0.38, Ppl = 100%) and genetic differentiation (Gst = 0.17) with gene flow estimate Nm of 2.4 among six geographical groups. With neighbor joining (NJ) analysis, 151 cultivars were clustered into seven main groups, and approximately related to their geographical distribution. Population structure analysis revealed six subpopulations, generally consistent with NJ-clustering. The results in our study suggest that different provenance collection and in situ conversation are important for C. sinense conservation and genetic improvement.
Review helpfulness as a function of Linguistic Indicators

Online reviews are playing an important role in customer’s decision making procedure for buying any product online. As buying products online is becoming customer’s first choice while shopping. It is very helpful to make purchase decision for any product by reading online reviews related to that particular product. However, such a large volume of online reviews that is being generated can be considered as a big data challenge for both entities i.e. e-commerce websites and customers. These online reviews are usually ranked on the basis of helpful votes. This article examined the important factors that contribute to the helpfulness of online reviews and built a helpfulness predictive model for online reviews. Five novel linguistic characteristics are proposed and popular machine learning algorithms are applied to construct an effective predictive model for review helpfulness. LCM and visibility features are also used as baseline. We have performed experimental analysis on two popular Amazon review datasets and results reveals that hybrid set of features deliver the best predictive performance. We also found that the proposed Linguistic features are better predictors for review helpfulness as a standalone model. The findings of our study can provide new wisdom to e-commerce vendors for effective ranking of online reviews on the basis of their helpfulness. This research would also help customers in making better decisions before purchasing any product.
Secured Outsourcing of Image Reconstruction Service In Cloud Using Attribute Based Encryption

: With the increase in image data sets there exists a problem with secured image storage as well as secured image sharing. In order to overcome these problems we can outsource the image management system to the cloud [1][10]. But the cloud is an open environment operated by external third parties so the security becomes a major concern. Since the image data sets are intended to be shared only to particular group of users the accountability of the image data is a high priority issue. To address the challenges with the accountability we propose an object-centered approach that enables enclosing our logging mechanism together with user’s data and policies. Attribute-Based Access Control (ABAC) [11] uses attributes as building blocks which defines access control rules and describes access requests performed by the user. Attributes are sets of labels or properties that can be used to describe all the entities that must be considered for authorization purposes. And for the Integrity and Recoverability of image data we utilize the Cipher Text policy Attribute Based Encryption (CPABE) techniques along with HMAC with SHA which is an efficient and effective way for the outsourcing of image reconstruction service in cloud.
Inter-generic relatedness of pheasants (Aves: Galliformes: Phasianidae) based on RAPD using non-invasive samples

Molecular tools play an important role in conservation genetics. RAPD, the simplest among all PCR techniques, has been used in the present study to reveal the inter-generic relatedness among pheasants such as Indian Peafowl (Pavo cristatus), Silver pheasant (Lophura nycthemera), Domesticated Turkey (Meleagris gallopavo) and Domesticated fowl (Gallus gallus). Among 38 bands amplified by three primers, 34 (89.4%) were highly polymorphic. The bands produced were checked for reproducibility and further statistical analyses were made with Jaccard’s and UPGMA method for genetic distance and developing dendrogram. The results clearly revealed the clade divergence of Pavo cristatus and Gallus gallus with that of Lophura nycthemera and Meleagris gallopavo.
Antimicrobial effects of the stem extracts of Apium graveolens Mill

Apium graveolens Mill. is a vegetable that is abundantly found and consumed in the markets of Aydýn province. The aim of this study was to test the antimicrobial activity of A. graveolens stem. Plant stems were dried and extracted with methanol, n-propanol, ethanol, acetone, nhexane, and ethyl acetate. Antimicrobial activity of the extracts was determined by the disc diffusion method. Test microorganisms were 18 bacteria and 4 yeasts. Also standard antibiotic discs were used for comparison of inhibition zones. Results showed that n-propanol and acetone extracts of A. glaveolens stem were most effective against used microorganisms. n-propanol extract of A. glaveolens stem inhibited the growth of twenty microorganisms and the inhibition zones ranged between 9-16 mm. The acetone extract of A. glaveolens stem inhibited the growth of eighteen microorganisms and the inhibition zones ranged between 8-15 mm. The ethanol extract of A. glaveolens stem inhibited the growth of ten microorganisms and the inhibition zones ranged between 9-13 mm. However, methanol, hexane and ethyl acetate extracts did not show any antimicrobial effects against used microorganisms. The inhibition zones of standard antibiotics used as positive control (chloramphenicol, gentamycin, tetracycline, erythromycin and ampicillin) were between 11-30 mm. against bacteria while the inhibition zones of standard antibiotic (nystatin) were between 20-22 mm. against yeasts.
A Study of Web Design for Customer Billing Telephony System Using User Experience (UX) Approach

Telecommunications industry has gone through series of development efforts to make services available to consumers and to provide quality services. The hardest challenge in telecommunications industry is to meet the customer satisfaction in billing system such as the accurate billing, easy to understand and resolving billing issue, the billing problem resolution speed, the service cost performance, rate discount degree, and rate communication. Hence, the improvement of these issues can enhance the customer satisfaction. User Experience (UX) is an approach that takes in consideration on user’s preference, emotions, physical and psychological responses, perceptions, behavior that occur before, during and after using the system in designing the user interfaces. Obviously, this creates innumerable design and experience opportunities which represent the holistic view with of the pragmatic aspect and hedonic aspect. Nowadays, UX is becoming an important issue in developing web based system and it has been discussed by many researchers. This research is focus on a study of customer billing telephony system in order to decrease the challenges in telecommunications industry. A survey conducted to collect data from the customers of telecommunication industry. The result shows that the improvement of billing system is needed to improve the efficiency and correctness in billing process. It is expected that by implementing the UX approach, it will improve the customer billing telephony system. In addition, it gives the positive perceptions and experiences of a service in order to increase the customer satisfaction.
Comparative Performance Analysis of Single-Server and Multiple-Server Markovian Models

This research paper compares M/M/1 and M/M/N Markovian models to determine a more suitable queuing model for the enhancement of a wireless system’s performance. Data traffic was collected from the wireless MikroTik router connecting the overhead satellite to the university Wireless Campus Area Network (WCAN) using “Winbox” software monitoring tool for a period of 11 months from 31th January 2011 to 30 th December 2012. The computation of this data traffic gave the average arrival rate of 176.5 kilobits per second, and the average service rate of 746 kilobits per second. By using these values in the analyses, M/M/1 was found to be better than M/M/2 and even far better than M/M/3. The results shows that the higher the number of servers in a queuing model, the more the number of unserviced entities in the system, and in the queue waiting for service, and also the system has slower response time and longer waiting time in the queue.
SIMILARITY MEASURE FOR TEXT CLASSIFICATION

Text processing plays very important role in information retrieval, data mining and web search. Text classification can efficiently enhance the text processing capability by automatically sorting out them according to defined collection of categories. Measuring the similarity between documents is an important operation in the text processing field. In this work, a similarity measure is proposed to compute the similarity between two documents with respect to a feature. The proposed measure takes the following three cases into account: The feature appears in both documents, the feature appears in only one document, and the feature appears in none of the documents. For the first case, the similarity increases as the difference between the two involved feature values decreases. Furthermore, the contribution of the difference is normally scaled. For the second case, a fixed value is contributed to the similarity. For the last case, the feature has no contribution to the similarity. The proposed measure will be extended to gauge the similarity between two sets of documents. The effectiveness of this measure will be evaluated on several real-world data sets for text classification problems.
A REVIEW ON APPLICATIONS OF BIOSURFACTANTS PRODUCED FROM UNCONVENTIONAL INEXPENSIVE WASTES IN FOOD AND AGRICULTURE INDUSTRY

Biosurfactants can serve as green alternative in different areas due to their ecological acceptance as they are biodegradable and nontoxic. Nowadays biosurfactants are predominantly used in pharmaceutical, oil industry, and for the bioremediation of pollutants. Apart from these, biosurfactants also show potential applications in many sectors of food industry and agriculture. Allied with emulsion forming and breaking, antiadhesive, functional ingredient, are some properties that can be exploited in agro-food biotechnology. Potential role of biosurfactants in food and agricultural sectors as well as present concern of lowering the production cost of biosurfactants by using the unconventional wastes as substrate is discussed in this article.
Coartemether in Dietary Oil Induces Oxidative Stress and Hepatotoxicity in Albino Rat

Lipid rich diet enhances the bioavailability and therapeutic potency of coartemether (artemetherlumefantrine), an ACT antimalarial drug. However, its impact on the coartemether cytotoxicity has stimulated this investigation. Thus, this study evaluated the in vivo effect of coartemether in the presence of oil on the antioxidant and hepatotoxic biomarkers in albino rats for 3 days. Twenty (20) rats were randomly divided into four groups of five rats per group. Group I (control) received normal placebo saline (0.9% NaCl), group II (C) was treated with coartemether (4 mg artemether: 24 mg lumefantrine), group III (O) received sunflower oil (1.0 ml) and group IV (CO) was co-administered coartemether (4 mg artemether: 24 mg lumefantrine) and (1.0 ml sunflower oil). Result showed no significant difference (P>0.05) in SOD and GSH levels in all treated groups compared to control while there was a significant (P<0.05) elevated catalase activity in the liver and heart of C-O and coartemether treated animals compared to other treatment groups. The C-O treated animals had significantly (P<0.05) high kidney and heart GST activity compared with other groups. Coartemether treated animals had an elevated plasma malondialdehyde content which was reversed in C-O group. Furthermore, coartemether and C-O treated groups had elevated alkaline phosphatase, alanine aminotransferase and aspartate aminotransferase levels compared with the control animals. However, bilirubin levels were high and low in coartemether and C-O treated groups respectively. Therefore, investigation from this study shows that coartemether in an oil medium could induce oxidative stress and hepatotoxic biomarkers. [Anyasor God’swill Nduka, Odunsanya Olutayo Tolulope. Coartemether in Dietary Oil Induces Oxidative Stress and Hepatotoxicity in Albino Rat. Researcher. 2011;3(7):35-41]. (ISSN: 1553-9865). http://www.sciencepub. net.
Survey Paper for Enhancement of Apriori Algorithm

As with the advancement of the IT technologies, the amount of accumulated data is also increasing. It has resulted in large amount of data stored in databases, warehouses and other repositories. Thus the Data mining comes into picture to explore and analyze the databases to extract the interesting and previously unknown patterns and rules known as association rule mining. In data mining, Association rule mining becomes one of the important tasks of descriptive technique which can be defined as discovering meaningful patterns from large collection of data. Mining frequent item set is very fundamental part of association rule mining . As in retailer industry many transactional databases contain same set of transactions many times, to apply this thought, in this thesis present an improved Apriori algorithm that guarantee the better performance than classical Apriori algorithm .
Clinical multimodal multiphoton tomography of pigmented skin lesions with an ultracompact femtosecond fiber laser

Multiphoton tomography (MPT) has become a high-resolution label-free clinical imaging tool to obtain optical skin biopsies for rapid in vivo histology. Here, we report on the novel multimodal multiphoton tomograph MPT compact based on a chiller-free ultracompact 80 MHz femtosecond fiber laser operating at 780 nm. The 360°-measurement head contains the laser head and multiple photon detectors for (i) autofluorescence (AF) imaging, (ii) fluorescence lifetime imaging (FLIM) for optical metabolic imaging (OMI) and melanin detection, (iii) second harmonic imaging (SHG) of collagen, (iv) confocal reflection microscopy (CRM), and (v) white-light imaging (dermoscopy). Preliminary results of an ongoing multicenter clinical study in patients with suspicious pigmented lesions in two hospitals are presented.