Miracle-dz/UniFAR-FTUs huggingface dataset:
Pathogens involved in Respiratory Tract Infections ( RTIs ) in Abeokuta , Nigeria

Various Bacteria have being implicated as etiological agents of respiratory tract infections, often times these same bacteria colonize the nostrils mouth and throat, acting as normal flora, before adverse events make them become pathogenic. Our objective is to review bacteria agents isolated from various respiratory tract infections and their antibiotic susceptibility profile in Abeokuta, Nigeria. 130 cases of various respiratory conditions were retrospectively reviewed from May 2010 to December 2010, for culture and susceptibility profile. All samples were processed following standard Microbiological protocols and susceptibility was tested by Kirby-Bauer method for disk diffusion. An isolation rate of (29.0%) was recorded for pathogens (71.0%) for commensal (Normal flora). Distribution of pathogenic bacteria isolates by gram reaction showed that Gram negative bacilli (GNB) had a higher value with 22(58.0%) and Gram positive cocci (GPC) 16(42.0%). Female subjects recorded a higher isolation rate than males, 62.2% vs 37.8%, (P-value 1.98, Chi square test X). Klebsiella pneumonia recorded the highest occurrence rate with 15(40.5%), followed by Streptococcus pneumonia with 8(21.6%), the lowest rate was recorded by Proteus spp with 1(2.7%). Age range distribution was highest in 45-60(39.0%), 15-30 (37.5%) the lowest rate was recorded by 0-15 (21.0%). The antibiograms revealed that majority of the pathogens showed multi-drug resistant (MDR) pattern to most of the antibiotics used. Augumentin was the most broadly active antibiotic with 75.0% sensitivity to Streptococcus pnuemoniae, 100.0% sensitivity to Streptococcus viridians, and 100.0% sensitivity to Staphylococcus aureus, followed by Gentamycin, Ofloxacin also displayed good sensitivity with a rate of 73.3% to Klebsiella pneumonia, 75.0% sensitivity to Pseudomonas aeruginosa. The Cephalosporins performed poorly, and there was absolute resistance to Amplicillin and Tetracycline, while Amoxiclillin recorded very poor sensitivity against all isolates tested. The high β-lactamase resistance observed in all our isolates, particularly in GNB isolates even to the cephalosporin is in an indication of acquisition and dissemination of ESBL genes. The study showed the presence of multi-drug resistant (MDR) pathogens among the subjects with RTIs attending out-patient clinic in a tertiary hospital in Abeokuta, Nigeria and this calls for particular public health attention. We hereby advocate better surveillance and infection control programs in our health institutions for early detection and intervention of multi-resistant bacteria. [Motayo BO, Ogiogwa JI, Aboderin BW, Okerentugba PO, Innocent-Adiele HC, Nwanze JC, Onoh CC, Okonko IO. Bacteriological Review of Multi-Drug Resistance (MDR) Pathogens involved in Respiratory Tract Infections (RTIs) in Abeokuta, Nigeria. Researcher 2012;4(5):49-55]. (ISSN: 1553-9865). http://www.sciencepub. net/researcher. 10
A NEW ERA OF FIFTH GENERATION COMMUNICATION TECHNOLOGY

5G simply stands for fifth generation and refers to the upcoming and latest mobile wireless standard based on the IEEE 802.11ac standard of broadband technology. This paper throws light on the Architecture of fifth generation technology. 5G is the proposed next telecommunications standards beyond the current 4G/IMT-Advanced standards, rather than faster peak Internet connection speeds. 5G planning aims at higher capacity than current 4G. This paper mainly focuses on all preceding generations of mobile communication along with fifth generation technology. Fifth generation network provide affordable broadband wireless connectivity (very high speed). The new 5th generation, 5G technology for cellular systems will probably start to come to fruition around 2020.
Intelligent Heart Disease Diagnosis System Using Distance Based Outlier Detection With Gradient Tree Boosting Algorithm

— Generally, outlier detection techniques recognize the abnormal data instances which deviates from most of the data in the dataset. In this paper, we present a new distance based outlier detection (DOD) model from the given patient’s care particularly heart disease, where every patient-management action are mainly based on the condition of the patient. This method intends to recognize the patient-management actions for a provided patient data which is highly abnormal with respect to previous patients with condition(s) which are identical to the ones that the provided patient suffers from. When a variation is identified, it might be employed to classify the patient data to identify heart disease. For classification purposes, gradient boosting tree (GBT) classifier is employed. To ensure the correctness of the presented DOD-GBT model, a set of two benchmark dataset namely Heart-Statlog and Cleveland heart disease dataset under several performance measures. The presented DOD-GBT classifier achieves a maximum of 96.70% accuracy whereas the GBT classifier without outlier identification attains a maximum of only 95.19% accuracy.
Adaptive Kernels for Skeleton Based Action Recognition using Geometric Feature Score Fusion

: This paper presents a novel adaptive kernel based method for classifying the human actions from the skeletal data. Three types of geometric features: joint positions, joint relative distances and joint relative angles were used for action recognition using the information sensed by Microsoft Kinect sensors. Recently, kernel-based methods mostly focused on the action recognition on spatio-temporal data. In this work, the obtained scores from the individual adaptive kernels which are inputted three different geometric feature namely joint positions, joint relative distances and joint relative angles features were fused to detect the action by using simple kernel matching technique which evaluates the similarity between the features. This method is used to rank the actions from the database according to the highest ranked query action. The experimental results conducted over three publicly available datasets, i.e., NTU RGB-D, G3D and UTD-MHAD. The proposed technique has been tested and compared with other state-of-the-art methods on above datasets. The proposed method performed well on all datasets and good recognition rates were recorded.
Optimizing Operational Lifetime in Manet by Network Topology Control Mechanism

-Recent developments in mobile networks have much importance because of their improved edibility costs. In addition to device portability MANET does not require pre-established network arrangement and hence can install in conditions like emergency rescue and disaster management but there are someproblemswhich MANET such as hidden and exposed terminal problem in this kind of network is much more challenging conventional network because of their limited processing power and restricted hardware important the Nodes in MANET are mostly operated by battery and the batteries are limited in capacity midcult to replacer re-charge the battery and this reduces the network lifetime. To enhance the operational lifetime of network the nodes in the network should use the minimal power during communication and some beneficial must be applied at the hardware level as well as protocol level. In this paper, we have focused our concern on energy conservation technique and proposed a topology control mechanism to enhance the operational life time in MANET our method will consume considerably least possible power while transmitting the packet from source to destination.
International Journal of Emerging Trends in Engineering and Development Issue 4, Vol.4 (June-July 2014) Available online on http://www.rspublication.com/ijeted/ijeted_index.htm ISSN 2249-6149

Patterns which repeat over a period of time are known as periodic patterns. This Periodic pattern detection is an important data mining task, which discovers in the time series all patterns that exhibit temporal regularities. Periodic pattern mining has a large number of applications in real life as well; it helps understanding the regular trend of the data along time, and enables the forecast and prediction of future events. An interesting related problem that has not received enough attention is to find out outlier periodic patterns in a time series . Outlier patterns are defined as those which are different from the rest of the patterns; outliers are different from noise. While noise does not belong to the data and it is mostly eliminated by pre-processing, while outliers are actual instances in the data but have exceptional characteristics compared with the majority of the other instances. Outliers are unusual patterns that rarely occur, and, thus, have lesser support (frequency of appearance) in the data. Outlier patterns may hint toward discrepancy in the data such as fraudulent transactions, network intrusion, change in customer behavior, epidemic and disease biomarkers, severe weather conditions, recession in the economy, etc. so here the argument is that detecting the periodicity of outlier patterns might be more important in many sequences than the periodicity of regular, more frequent patterns. In this paper, a suffix tree-based algorithm capable of detecting the periodicity of outlier patterns in a time series using MAD (Median Absolute Deviation) is presented. An existing algorithm makes use of mean values, which is inefficient. Use of MAD increases the output of these algorithms and gives more accurate information. Several experiments have been conducted using real data; all aspects of the proposed approach are compared with the existing algorithm which makes use of the mean value; the reported results demonstrate the effectiveness and applicability of the proposed approach.
Dynamic Test Case Design Scenario and analysis of Module Testing Using Manual vs. Automated Technique

Software can be tested either manually or automatically. The two approaches are complementary: automated testing can perform a huge number of tests in short time or period, whereas manual testing uses the knowledge of the testing engineer to target testing to the parts of the system that are assumed to be more error-prone. Despite this contemporary, tools for manual and automatic testing are usually different, leading to decreased productivity and reliability of the testing process. AutoTest is a testing tool that provides a “best of both worlds” strategy: it integrates developers’ test cases into an automated process of systematic contractdriven testing. This allows it to combine the benefits of both approaches while keeping a simple interface, and to treat the two types of tests in a unified fashion: evaluation of results is the same, coverage measures are added up, and both types of tests can be saved in the same format. The objective of this paper is to discuss the Importance of Automation tool with associate to software testing techniques in software engineering. In this paper we provide introduction of software testing and describe the CASE tools. The solution of this problem leads to the new approach of software development known as software testing in the IT world. Software Test Automation is the process of automating the steps of manual test cases using an automation tool or utility to shorten the testing life cycle with respect to time.
A CASE REPORT: ICTAL BRADYCARDIA IN A PATIENT WITH SYNCOPAL ATTACKS

Aims: Ictal bradycardia is characterized as the presence of bradycardia during the ictal discharge and mostly seen in left temporal zone originated seizures. It could lead to conditions such as syncope, asystole and severe injuries. With this case report, it is aimed to emphasize the importance of applying 24-hour video electroencephalographyelectrocardiography monitoring in patients with unexplained loss of consciousness
Biogenic synthesis of zinc nanoparticles from Thevetia peruviana and influence on soil exo-enzyme activity and growth of peanut plants

Zinc nanoparticles were synthesized using Thevetia peruviana leaves extract and characterized using different spectroscopic (Ultraviolet-Visible and Fourier Transform Infrared Spectroscopy) and microscopic (Particle size analyzer, Xray diffraction, Scanning and Transmission electron microscopy) techniques. Absorption spectrum of zinc nanoparticles showed broad absorption peaks at 327 nm and 254 nm. Average particle size and zeta potential were recorded as 53 nm and 82 mV respectively. Microscopy techniques revealed triangular shaped and poly-dispersed zinc nanoparticles. The synthesized zinc nanoparticles were applied to the pot-culture of peanut and studied soil micro-biota and soil exo-enzyme activities and estimated the physiological traits of peanut plants in 2 regular time intervals of 30 days and 60 days of sowing period. Zinc nanoparticles applied to the peanut pot-culture exhibited good soil microbial and enzyme activities by showing significant variations compared to the control and enhanced the physiological growth parameters of peanut plants.
Smart System for Garbage Management

In a smart city, maintaining hygienic conditions is crucial; hence a garbage management system is introduced. The objective is to determine the garbage level in dustbin with sensors and notify the controlling authority through wireless communication module. Garbage level is supervised with GUI built in Android application. Location of garbage bin is traced with the GPS system employed. This system introduced will considerably reduce the overall operational time required for regularly monitoring the bins.
Medical Image Compression and Decompression Maintaining Location Privacy and QoS

—The Internet of Things (IoT) is a network of physical devices, vehicles, buildings and various other items-embedded with electronics, sensors, actuators etc. that enable these things to collect and exchange data. If one thing can prevent the IoT from transforming the way we live and work, it will be a breakdown in Security. Traditional security mechanisms like Configuring Firewall, Intrusion Detection and Prevention Systems are deployed at the Internet edge. These mechanisms are used to protect the network from external attacks. Such mechanisms are no longer enough to secure the next generation internet. The borderless architecture of the IoT raises additional concerns over the network access control and software verification. In order to maintain the integrity of thedata sent and the confidentiality of the data collected, security must be built into the design of the devices and systems to create trust in both the hardware and the integrity of the data. Considering the rapid growth of the IoT, the project proposes an improvised framework for the future development of security and privacy standards in the Internet of Things.
Carcass Yield and Organ Characteristics of West African Centre Dwarf Rams Fed Ensiled Guinea Grass and Cassava Tops with Different Additives

Twenty five individually housed West African Dwarf (WAD) rams were used to study the effect of ensiled guinea grass and cassava tops mixture with different additives on the performance and carcass characteristics of WAD rams. The guinea grass and cassava tops mixture with different additives were ensiled in ratio 6:3:1 in five treatments designated Treatment 1: 60% Guinea grass +30% cassava tops + 10% cassava chips; Treatment 2: 60% Guinea grass +30% cassava tops + 10% sorghum grain; Treatment 3: 60% Guinea grass +30% cassava tops + 10% millet grain; Treatment 4: 60% Guinea grass +30% cassava tops + 10% sugar and Treatment 5: 60% Guinea grass + 40% cassava tops + 0% additives. The 25 WAD rams were divided into five groups of five animals each. Each group was assigned to the treatments in a completely randomized design (CRD). Each animal in a group represented a replicate. The experiment lasted for 135 days. Data on Weight gain, dressing percentage and carcass quality was collected.Results revealed that the different silages fed to the rams significantly influenced dressing percentage (P<0.05), with values ranging between 50.89% and 53.77 %. Meat cut values showed that leg and shoulder were not significantly different (P<0.05) but the Rack, Neck, Brest and Flank were significantly (P<0.05) affected the legs gave the highest percentage (34.32 – 36.82%). This was followed by shoulder (23.05 – 24.44%), rack (18.58 – 22.54%) and loin (12.00 – 14.85%) in that order. There were no significant differences (P<0.05) among treatment means for all the non-meat parts (head,, feet, full gut) except for the skin. It can be concluded that ram fed treatment 3 performed better in terms of dressing percentage and carcass characteristics.
International Journal of Innovative Technology and Exploring Engineering (IJITEE)

3394 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: A3903119119/2019©BEIESP DOI: 10.35940/ijitee.A3903. 119119  Abstract: This paper studies about various job scheduling methodologies used in big data systems. Map reduce is a highly efficient distributed job processing strategy for big data systems. Job scheduling is a critical task of any big data system as the volume of jobs need to be processed is tremendous. This study will go over the map reduce process in detail. It also reviews various job scheduling methodologies and tries to perform an efficient comparison among these methodologies.
Face Recognition using Principle Component Analysis Face Recognition using Principle Component Analysis Face Recognition using Principle Component Analysis Face Recognition using Principle Component Analysis with with with with DDDDifferent ifferent ifferent ifferent DDDDistance istance istance ista

Summary Face recognition has received substantial attention from researchers in biometrics, pattern recognition field and computer vision communities. Face recognition can be applied in Security measure at Air ports, Passport verification, Criminals list verification in police department, Visa processing, Verification of Electoral identification and Card Security measure at ATM’s. Principal Component Analysis (PCA)is a technique among the most common feature extraction techniques used in Face Recognition. In this paper, a face recognition system for personal identification and verification using Principal Component Analysis with different distance classifiers is proposed. The test results in the ORL face database produces interesting results from the point of view of recognition success, rate, and robustness of the face recognition algorithm. Different classifiers were used to match the image of a person to a class (a subject) obtained from the training data. These classifiers are: the City-Block Distance Classifier, the Euclidian distance classifier, the Squared Euclidian Distance Classifier, and the Squared Chebyshev distance Classifier. The Euclidian Distance Classifier produces a recognition rate higher than the City-Block Distance Classifier which gives a recognition rate higher than the Squared Chebyshev Distance Classifier. Also, the Euclidian Distance Classifier gives a recognition rate similar to the squared Euclidian Distance Classifier.
A IMPLEMENTATION OF HIGH SPEED ON-CHIP MONITORING CIRCUIT BY USING SAR BASED COMPARATOR DESIGN

1Research Scholar, Trinity Institute of Technology & Research, Bhopal, India 2Faculty Electronics’ & Communication Dept., Trinity Institute of Technology & Research, Bhopal, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract An 10-bit pipelined analog-to digital converter (COMPARATOR) is designed in this thesis. The pipelined architecture realizes the high-speed and high-resolution. To reduce some complexities of flash COMPARATOR pipeline COMPARATOR is used. The calibration schemes of pipelined COMPARATOR limit absolute and relative accuracy. Deviations in residue amplifier gain results due to low intrinsic gain of transistors, and mismatching between all the capacitors of capacitance 1pF result in both deviations in residue amplifier gain and DAC nonlinearity in a pipelined COMPARATOR. To image the world, a low-power CMOS image sensor array is required in the vision processor. The image sensor array is typically formed through photo diodes and analog to digital converter (COMPARATOR). To achieve low power acquisition, a low-power mid-resolution COMPARATOR is necessary. Digital correction allows also to use very low power dynamic comparators. The multiplying D/A converters (MDACs) utilize a modified folded dynamic amplifier . In this enables to the use of dynamic amplifiers in a pipeline COMPARATOR. In addition, the dynamic amplifier offers both clock scalability and highspeed operation even with a scaled supply voltage. Using the above techniques, a 16 bit prototype COMPARATOR achieves a conversion rate of 160 MS/s with a supply voltage of 0.55 V. Therefore, the combination of interpolated pipeline architecture and dynamic residue amplifiers demonstrates the feasibility of ultra-low voltage high-speed analog circuit design. To implement the whole system a low-power and small size capacitance value sensing readout circuit is required. Also, it has to be integrated together with the back-end low-power current-mode COMPARATOR on the same chip. The low-power current-mode COMPARATOR has been designed and fabricated with TSMC 0.18um CMOS technology. In the simulation result, the power consumption for 6-bit COMPARATOR was 6 W, with a power supply of 0.65 V.
Design and Implementation of Power Efficient Turbo Decoder

: Turbo decoding is viewed as superior alternate decoding technique in communication system, the circuit complexity and power consumption of turbo decoder implementation can often be prohibitive for power constrained system. To address these issues a power efficient turbo decoder based on soft out viterbi algorithm is designed. SOVA based turbo decoder can be implemented with high throughput and less complexity, This project work is towards Design and ASIC implementation of turbo decoder Using TSMC 65nm library, RTL model for Decoder is developed using HDL and synthesized, targeting ASIC implementation, clock gating technique has been adopted to meet low power requirement.
Hormone receptor (ER, PR) status in breast carcinoma – correlation with clinicopathological prognostic parameters

Background: Breast is one of the most common cause of death in women. Earlier diagnosis and treatment with appropriate therapy based on hormonal status leads to a reduction in mortality rate. Aim of this study is to assess the hormone receptor status in breast carcinomas and to compare them with other clinical and pathological parameters. Materials and Methods: This retrospective study was conducted in Department of Pathology, Vishwabharti Medical College, Kurnool, A.P. for a period of 2 years. A total of 52 cases were studied and IHC were done. ER, PR status of patients were studied and compared with other parameters. Results: Majority of cases were in postmenopausal women. Clinical stage 2 and histological grade 2 cases were more in number. There was significant correlation between clinical staging and NPI sore and between tumor grade and ER, PR status. Conclusion: ER, PR status has significant correlation with histological grading but does not have significant correlation with clinical staging. So, irrespective staging and other clinical parameters hormonal studies should be conducted in all cases to reduce mortality and recurrences.