Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Associated with Utilization of Insecticide Treated Nets Among Residents of Kamwenge Town

Background: Malaria continues to be a leading cause of morbidity and mortality in sub-Saharan Africa. In Uganda, malaria remains the leading cause of morbidity, accounting for 30 to 50 percent of outpatient visits, 15 to 20 percent of admissions, and 9 to 14 percent of inpatient deaths. The first national-wide Insecticide Treated Nets (ITNs) coverage campaign was launched in 2010 targeted at households with pregnant women and children below 5yrs of age. Objective: To determine the factors associated with utilization of Insecticide Treated Nets (ITNs) among residents of Kamwenge Town Council, Kamwenge DistrictWestern Uganda. Methodology: The study design was cross-sectional in which data were collected using an interviewer administered structured questionnaire and analyzed using Stata version 13. Results: A total of 285 respondents were interviewed of which 39.7% were male. Ownership of ITNs was 60% whereas utilization in the night prior to the study was 54.4%. The factors associated with the ownership of the ITNs included: marital status: married respondents (p=0.05), level of education (p=0.001), knowledge of malaria cause (p=0.033), presence of children under 5 years (p=0.025). The factors associated with the utilization of ITNs included: marital status of the respondents: married respondents (p=0.018), education level (p=0.009), presence of children under five years (p=0.048), knowledge of cause of malaria (p=0.019), having faced challenges in using ITNs (p=0.001), and malaria episode in the last one month (p=0.011). Conclusion: The study concludes that the ownership and utilization of ITNs were low since they were all below the national target of universal coverage. The factors statistically associated with the ownership of the ITNs included: marital status, level of education, knowledge of malaria cause and the number of children under 5 years in a household. The factors statistically associated with the utilization of ITNs were marital status, education level of the respondents, and presence of children under five years of age in the household, having knowledge about malaria, having faced challenges in using ITNs in the past and malaria episode in the last one month.
HIGH QUALITY IMAGE SCALING USING INTERPOLATION TECHNIQUES WITH FILTERS

: The present paper dealing with Image scaling is the procedure of resizing a digital image, the digital image is converted from low to high resolution and low to high dimension without losing the natural content. It has many phrases in documentsuch as image bilinear interpolation, images resampling, digital resizing, image magnification. The proposed method is implementing two types of non-adaptive and adaptive interpolation algorithms two types. The proposed interpolating from low to high resolution as expected up scaling\up sampling and high to low resolution is down scaling\down sampling. The proposed method is non-adaptive image bilinear interpolation algorithm to scale images for any given scaling ratio with an improvement scheme to ensure a better image quality metric of the scaled image. The proposed method which has two reference images used one is higher resolution and another one is lower resolution from generated input image and image scaling process.
Molecular markers in development, diagnosis and progression of nonmuscle invasive bladder cancer

Objective | The potential risk of recurrence and progression in patients with non-muscle invasive bladder cancer necessitates follow-up by cystoscopy. The risk of progression to muscle invasive bladder cancer is estimated based on the European Organisation of Research and Treatment of Cancer score, a combination of several clinicopathological variables. However, pathological assessment is not objective and reproducibility is insufficient. The use of molecular markers could contribute to the estimation of tumor aggressiveness. We recently demonstrated that methylation of GATA2, TBX2, TBX3, and ZIC4 genes could predict progression in Ta tumors. In this study we aimed to validate the markers in a large patient set using DNA from formalin-fixed and paraffin embedded tissue. Material and methods | PALGA: the Dutch Pathology Registry was used for patient selection. We included 192 patients with pTaG1/2 bladder cancer of whom 77 experienced progression. Methylation analysis was performed and Log-rank analysis was used to calculate the predictive value of each methylation marker for developing progression over time. results | Log-rank analysis showed better progression-free survival in patients with low methylation rates compared to patients with high methylation rates for all markers (p<0.001) during a follow-up of ten-years. The combined predictive effect of the methylation markers was analyzed with the Cox-regression method. In this analysis, TBX2, TBX3 and ZIC4 were independent predictors of progression. Based on the methylation status of TBX2 and TBX3, patients were divided into three new molecular grade groups. Survival analysis showed that only 8% of patients in the low molecular grade group progressed within five years. This was 29% and 63% for the intermediate and high molecular grade groups. Conclusions | This new molecular grade based on the combination of TBX2 and TBX3 methylation is an excellent marker for predicting progression to muscle-invasive bladder cancer in patients with primary pTaG1/2 bladder cancer. pTa-specific progression markers 35
A Game-Changing Encounter?

onspecific common factors theory asserts, based on 75 years of randomized controlled trials of different types of psychotherapy, that specific processes and procedures cannot contribute powerfully to therapeutic change. This assertion derives from finding essentially the same rather modest level of efficacy for all of the many therapies studied using randomized controlled trials, or RCTs. Advocacy of nonspecific common factors theory has been especially strong in the last decade (e.g., Duncan, Miller, Wampold & Hubble, 2009). The fact that the efficacy measured by RCTs doesn’t change from therapy to therapy appears to imply that efficacy is due not to the specific methods and procedures used—which researchers call
Effect of Video and Image as Positive Feedback in Neurofeedback for Stressed Elderly

Slowing down of thought, memory and thinking is a normal part of aging. Mental exercise can help the brain to stay sharp. Neurofeedback training is a mental exercise which can improve the cortical activity. The neurofeedback process is a self-regulation training which allows the central nervous system to function better. Neurofeedback training is helpful with certain classes of problem such as attention, anxiety and depressions and also helps in improving the flexibility and resilience of brain. The training is given to elderly patients to treat age related cognitive decline such as stress.The brain wave frequencies are measured and analyzed in the course of training and the patients gradually learns to stay in the desired brain wave state by visualizing image and animated videos cues designed using LabVIEW software which are fed back to the subject via computer screen. 12 subjects were trained whose age range from 55-65. During the course of training beta wave is enhanced and theta wave is suppressed. As the training progresses, the threshold value is increased which is based on beta/theta ratio. After 3040 sessions, the efficacy is analyzed using the threshold and time
Social Disparities in Utilization of Preventive Health Services among Korean Women Aged 40-64

Social Disparities in Utilization of Preventive Health Services among Korean Women Aged 40-64 Hyun Hee Park, In Ae Chun, So Yeon Ryu, Jong Park, Mi Ah Han, Sung Woo Chio, Jun Ho Shin Department of Health Science, Graduate School of Chosun University, Gwangju; Department of Nutritional Service Team, Chosun University Hospital, Gwangju; Department of Preventive Medicine, Chosun University Medical School, Gwangju; Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Korea
Design and Analysis of CMOS Frequency to Voltage Converter using 0.35μm technology

This paper presents a 0. 35μm CMOS frequency to voltage converter for portable applications which is based on a operating principle comprises a differentiator, voltage to current converter, two RMS-DC converters, and a divider. Results show that the converter has a power consumption of 11.89mW operating at 3.3V supply voltage. This converter can accurately convert a sinusoidal signal frequency into an output voltage with no ripples. Moreover, its output response has input amplitude independent characteristic. The simulation results are in good accordance with the theoretical analyses.
A REVIEW OF BATTERY-SUPERCAPACITOR HYBRID ENERGY STORAGE SYSTEM SCHEMES FOR POWER SYSTEMS APPLICATIONS

The paper discusses typical hybrid energy storage applications in power systems, such as frequency and voltage regulation, demand management, load shaving and energy arbitrage. The review has provided the state of the art in the field of batterysupercapacitor hybrid energy storage topologies for power systems application. A comparison of advantages and disadvantages of the passive, the semi-active and the active dc and ac schemes has been made. The parallel active hybridization scheme has been chosen as the most appropriate solution for power system application. The review has proven relevancy of the research in the field. The steps for the future research have been identified.
A Deep Learning Model to Predict Vehicles Occupancy on Freeways for Traffic Management

Summary Prediction of traffic conditions plays a key role in the current era's intelligent transportation system. It not only enables commuters to choose appropriate routes to reach their destinations but also helps authorities in making effective traffic management plans. All needed for this purpose is to use a method that could handle abundant traffic data and by making wise use of this data, it could help authorities to get an estimate of traffic conditions on road networks and to make effective traffic management plans. Deep learning approaches are the most appropriate choice for these kinds of problems and have extensively been used for traffic forecast. In this work, we are using deep neural networks to predict the traffic condition on highways by considering the spatio-temporal correlation in traffic data attributes. For our deep model, we are using historical traffic data collected from Performance Measurement System (PeMS) for a period of three months on a selected patch of a highway in California. We are using vehicles occupancy values collected from the vehicle detector stations (VDSs) to predict the occupancy on the freeway. Prediction results compared with the actual occupancy values not only give very high accuracy but also enables us to make use of these predicted values in performing different traffic management tasks.
A FRAMEWORK FOR SENTIMENT ANALYSIS FROM TEXT IN ONLINE SOCIAL NETWORKS

: Online social networks are so popular nowadays that they are a major component of an individual’s social interaction. They are also emotionally rich environment where people share their emotions, feelings or sentiments and thoughts. Sentiments spread between people in direct contact, but it is unclear whether massive online social networks also contribute to this spread. Here, we elaborate a new framework for characterizing sentimental interactions in social networks. The goal is to extract the sentimental content of text in online networks. The framework includes a model for data collection, Database schema, Data processing and sentiment analysis. The informal language of online social network is main point to consider before performing any sentiment analysis techniques. This is the main reason framework includes the development of special lexicons. In general, we present a new perspective for studying sentiment analysis or expression in online social network where it deals with the nature of these sites and the nature of the language used.
Hybrid Technology With Battery Balancing

In this paper, hybrid (solar and wind power) technology with battery balancing function is proposed. All the inverters are connected to the battery bank individually. Number of batteries are connected to make the battery bank and it can be controlled according to battery voltages to implement the batterybalancing function, the design equation is derived. Experimental set of the battery-balancing discharge function is achieved practically. Finally, a prototype is designed and implemented to verify the feasibility and excellent performance. Index Terms A multilevel inverter, batterybalancing. MPPT, HarmonicReduction.
ICT Pedagogy for Effective Learning, Education and Quality Evaluation

The technology is moving rapidly in recent times than our ability so we need to adapt and adopt the new way of technology to improve to gather information in our daily affairs to save our money, energy and large amount of time. Nowadays, Information and Communication Technology (ICT) play a vital role to reduce mass illiteracy and help to overcome the educational problems faced during development of Digital India. IT is a discipline deals with Science, Technology, Engineering and Management in handling information, its applications associated with social, economic and cultural matters. Currently, 90% of the world’s population depends on internet technology and related gadgets to fulfill their basic needs of their routine life. This technological revolution is very important for all over human development in this smart world, especially in educational field. It makes the process of teaching-learning and evaluation more fascinating, easy to understanding and all involving with a smoother application. Even the government also promotes ICT based learning tools from primary level to degree level courses for practically sound knowledge and expanding expertise in their specific field. Students from any corner of the world can share their knowledge and solve their difficult experiments, problems with other researcher. In many fields of study, ICT based learning is useful to improve understanding of practical knowledge. There are so many applications based on ICTs. This paper focuses on methodologies of ICT in 21st Century’s, recent challenges of ICT in outcome based teaching and learning Pedagogy, Different Strategies for teachers to apply ICTs, various tools for different purpose like accessibility of distance learning, evaluation, scholastic performance
Gene Regulation under Hypoxia: HIF1 Mediated Adaptation

Mammalian cells require a certain level of oxygen in the environment in order to maintain homeostasis and to carry out aerobic respiration. However, in cancer and some other cardiovascular and pulmonary diseases, the cellular oxygen balance significantly changes in a way that pushes cells to survive under hypoxic conditions [1]. Survival under hypoxic conditions that arise from the insufficient delivery of oxygen via blood vessels to the rapidly growing tumor mass is a common feature of cancerous cells [2]. Cells that experience hypoxia develop adaptation to low-oxygen levels by activating cellular pathways related to cell survival, proliferation and metabolism. The ability of cancer cells to adapt to hypoxic conditions has been linked to tumor malignancy, resistance/unresponsiveness to treatment and poor prognosis [3].
Design of Optimal Reversible Arithmetic Logic Units (ALUs)

— Two unique, reversible Arithmetic Logic Units (ALU) have been designed in this paper. The number of functionalities of the ALU has been maximized and the cost metrics, minimized. Each functionality is realized using the least possible number of gates and incorporated together to get the optimal design. The ALU designs so obtained have AND, XOR, NOR, NOT and SUM functionalities with reduced optimized values of line costs, gate costs and transistor costs, which translates into lesser chip area for fabrication. The inability of the software to simulate complex V and V+ gates, increases the quantum cost marginally . However this tradeoff can be negated during actual fabrication. The platform used for the simulation of all reversible gates and reversible ALUs, is the ‘Revkit’ which is a package of iPython.
SECURITY IN NEAR FIELD COMMUNICATION(NFC) AND SECURE MOBILE HEALTHCARE SYSTEM

\ Abstract: Near field communication (NFC) is a set of standards for Smartphone and similar devices to establish radio communication with each other by touching them together or bringing them into proximity, usually no more than a few inches. Present and anticipated applications include contactless transactions, data exchange, and simplified setup of more complex communications such as Wi-Fi. Communication is also possible between an NFC device and an unpowered NFC chip, called a "tag". NFC is the descendant or an evolved form of Radio Frequency Identification (RFID). Although technically its working principal is based on RFID, it is more similar to Bluetooth in applications since it allows communication between active devices. Currently, it has applications mostly in the field of contactless electronic payment. One of the largest IT challenges in the health and medical fields is the ability to track large numbers of patients and materials. As mobile phone availability becomes ubiquitous around the world, the use of Near Field Communication (NFC) with mobile phones is emerging as a promising solution to this challenge. The decreasing price and increasing availability of mobile phones and NFC allows us to to apply these to developing countries in order to overcome patient identification and disease surveillance limitations, and permit improvements in data quality, patient referral and emergency response. Mobile phone based patient terminals require an easy-to use and versatile design to facilitate collecting of various kinds of data relevant for therapy optimization. To meet these requirements a user interface concept based on mobile phones and medical sensor devices enabled with Near Field Communication (NFC) technology was developed, linked to a web-based telemonitoring system and evaluated in clinical field trials with patients suffering from different chronic diseases like diabetes and heart failure. Simple touch of NFC enabled mobile devices can benefit both the patient as well as the medical doctors by providing a robust and secure health flow. It can also provide portability of devices and usability for health management in emergency situation, overpopulated hospitals and remote locations.
Identification of Shape-Signature of Moving Objects in Video Frames: A review

Detecting and tracking object is applied in diverse areas of computer vision,including video surveillance, person tracking, vehicle navigation, and robotics. Object detection and classification is essential prior to trackan object from a video sequence.The detectionprocess focuses on position, shape, and size of an object and can be achieved by using various approaches such asbackground subtraction, optical flow and spatio-temporal filtering. Once detected, the object can be categorizedusing shape-based, motion-based, and texture-based classification techniques. Over the past decades, there has been rapid development in the evaluation and analysis of object detection and tracking. This review highlights a comprehensive and up to date comparisons on available techniques, the underlying ideas, and their limitations.
Fast and Efficient Credit Card Fraud Detection on Real-Time Data Using Spark

:Fraud Detection is one of the mostly used techniques and is also the one requiring the most updates. An effective fraud detection system is the one that exhibits perfect detection rates with zero false positives. However, the requirement for such a system persists until now. This is due to the increase in the technology, that influences both the ends; the user and the fraudster. Hence it becomes mandatory that the users need to stay a step ahead in this scenario. This paper uses Hadoop architecture to provide a fraud detection technique based on the streaming nature of the data. Naïve Bayes is used as the detection technique and Spark framework is used for implementing the algorithm. Experiments show that the proposed framework exhibits excellent detection levels on the fast streaming data.
Synthesis of Lithium Copper Molybdate Nanoparticles and their Application for Photocatalytic Degradation of Malachite Green

In the present investigation, degradation of a non biodegradable azo dye, malachite green has been carried out using lithium copper molybdate (Li2CuMo2O8) as a photocatalyst. This catalyst was prepared by solid state reaction between Li2CO3, CuO and MoO3. The effect of various parameters such as pH, concentration of malachite green, amount of lithium copper molybdate and light intensity has also been studied. Water quality parameters like chemical oxygen demand (COD), conductance, pH, TDS, salinity and dissolved oxygen have been determined before and after treatment. The rate of photodegradation of malachite green dye followed pseudofirst order kinetics. A tentative mechanism involving OH radicals as an oxidant for degradation of dye has
Approximate Processing of Queries in P2P Networks

: Peer-to-peer (P2P) databases are mostly used on the Internet for distribution and sharing of documents, applications, and other data. Finding answers to large-scale ad hoc queries like aggregation queries on these databases gives rise to many new challenges. Finding the exact solutions can consume a large amount of time and is also difficult to implement since the P2P databases are distributed and dynamic. In this paper, an approach for approximately answering of ad hoc queries in such databases is presented. Generally, the data is distributed across many peers in a distributed environment, and most of the times, within each peer, the data is highly correlated. This fact is taken advantage of and an approach to process the queries in such an environment is proposed in this work.
Implementation of Effective Re-Ranking Approach Using Multimedia Search Engine

: Recently the detonating growth and comprehensive accessibility of association share media content on web have induce rise of research action in multimedia search. Generally while seeking result not actually coordinates with the search results. Hence the growing images on internet requires the best image retrieval technique that can enhance the image retrieval accuracy. Re-ranking is a viable technique to improve the search results of internet based multimedia search. This is generally adopted by business web crawlers, for example Google. The proposed Re-ranking approach is fit to work with all media types: video, picture, and audio. Techniques that apply text search methods for multimedia search have achieved limited success as they completely ignore visual content as a ranking. The crawler are generally base on content and compelled as the user look by keywards which results into vulnerability among multi media. Because of which loud or irrelevant images or video are available as results. The aim of multimedia search re-ranking is to reorder retrieved content to get optimal rank list. For that group of descriptors are utilized with weight and weight are assigned to it dynamically for acquire accurate multimedia files. Here we discuss various techniques for web multimedia re-ranking and propose new re-ranking technique to achieve the accurate query result and result demonstrates that it retrieves most significant files to the top. Here we utilize Optical Character Recognition ( OCR) and ASR i.e. combination of OCR and ASR(Hybrid Algorithm) to get text content from image and video.