Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of Acceptance and Commitment Therapy (ACT) on Anxiety, Depression, and Flexibility of Patients with Asthma

Asthma is one of the rapidly spreading diseases. The present study aims to investigate the effectiveness of acceptance and commitment therapy (ACT) on anxiety, depression, and flexibility of patients with asthma. This research is an empirical field study whose population consists of all patients with asthma in Kashan-Iran in First Semester 2014, from which 40 people were selected using the sampling method and randomly divided into two control and experimental groups. Subjects in the experimental group received the intervention; then, both groups were post-tested. Pre-test and post-test data were collected using the depression inventory developed by Beck [10], the anxiety inventory developed by Beck et al [10] and the AAQ-II questionnaire (for assessing the flexibility) developed by Hayes et al. (2004). The face validity of questionnaires was confirmed by a number of patients with asthma in a pilot study. The reliability of depression and AAQ-II questionnaires were determined equal to 0.76 and 0.61, respectively using the Cronbach’s alpha coefficient. Also, the reliability of anxiety inventory was determined equal to 0.60 using both the Cronbach’s alpha and the split-half method. The research data were analyzed using the covariance analysis test. The results of this study showed that this therapy has a significant effect on anxiety, depression, and flexibility of patients with asthma, so that it reduced the anxiety and depression of patients and increased their mental flexibility. Also, follow-up after one month showed that the impact was significant. The results also indicated that this method can be considered as a desired therapeutic option in comparison to other treatments and can provide a significant improvement through its processes.
Cluster based Energy balanced Routing Protocol for Wireless Sensor Network : A Review

The lifetime of a wireless sensor network is constrained by the limited energy and processing capabilities of its nodes. To extend the life time of the sensor networks it is very important to have high energy efficiency at all the processing nodes and to distribute the energy dissipated throughout the wireless sensor network. So it is essential to design effective and energy aware protocols in order to enhance the network lifetime. Various protocols for sensor network have been developed for which energy efficiency is primary goal. The traditional routing approaches for WSN may not be optimal in terms of energy consumption. So we propose a cluster-based approach for WSN. The clustering algorithm is a kind of key technique used to reduce energy consumption. Many clustering, power management, and data dissemination protocols have been specifically designed for wireless sensor network (WSN) where energy awareness is an essential design issue. This paper reviews some energy efficient clustering based protocols and approach of these protocols is to maximize the lifetime of wireless sensor network. Here Energy consumption and network life time has been considered as the major issues.
IDENTIFICATION OF ISCHEMIC HEART DISEASE DIAGNOSIS USING POLYNOMIAL SIGMOID SUPPORT VECTOR MACHINE

Medical diagnosis has been considered as an art despite all efforts to standardize, which has been mainly owing to the fact that medical diagnosis requires a proficiency in dealing with uncertainty merely not present in the present day's computing machinery. The researchers have been motivated through the development in computer technology as well as machine learning techniques to enhance software so as to aid doctors in taking resolution without demanding the straight discussion with the experts. In the present manuscript, application of artificial intelligence in usual heart disease diagnosis is being examined. The suggested approaches are pre-processing, bilateral filter as well as DWT for characteristic extraction. These suggested techniques provides an enhanced end result for heart disease recognition with certain phases such as pre-processing phases which suppresses the image quality for the enhancement in affected region. DWT has been a frequently utilized image processing technique that carries out the application of transferring images from the spatial domain into the frequency domain. In the present manuscript, the researchers have introduced a new kernel function known as polynomial sigmoid (PS) which can enhance the classification precision of support vector machines (SVMs). The suggested kernel function merges both Sigmoid (S) and Polynomial (POLY) a kernel as well has been represented in general form. It has been displayed that the suggested kernel meets quicker when compared the Sigmoid and Polynomial kernels. The precision of the suggested algorithm has been compared to algorithms depending on both Sigmoid and Polynomial kernels by application to varied non-separable sets with large number of attributes. The researchers recognized that the suggested kernel provides better classification accuracy in most of the data sets, particularly which are of higher dimensions.
ICBA Treatment of Chronic Un-healing Lesion in a Femoral DVT Patient-A Hypothesis of the Mechanism of Action

Introduction: DVT is a major, preventable cause of death worldwide. Ultrasound (US) is universally accepted as the first-line imaging procedure for DVT diagnosis. Case presentation: Three years ago, a 59-years-old patient detected a painless lesion above the right lateral malleolus. After starting to feel strong, right femoral pain, the patient sought treatment at a community health medical organization (HMO) and was urgently referred to a hospitalization. During a 5-day hospitalization, the patient was diagnosed to suffer from right femoral DVT, according to the venous Doppler US results. The patient was treated with clot-dissolving drugs. Upon discharge from the hospital, the patient was instructed to continue a clot-dissolving drug and to followed-up in an HMO. The patient was instructed to wear an elastic compression stocking on his right leg, and prescribed analgesic and oral antibiotics and. Non-healing of lesion and pain continued for about three years after initial treatment. Since the lesion failed to heal and the pain did not dissipate, the patient decided to attempt acupuncture treatment. Methods: The patient was treated with 12 sessions I Ching Balance Acupuncture (ICBA) and followed up for the next six months. Results: Lesion healing setup began during the 1st ICBA session. Following the 3rd session, the patient stopped consuming the analgesic. Complete lesion healing occurred after 12 ICBA sessions and persisted throughout the follow-up period. Conclusion: ICBA treatment successfully affected the setup of the healing process of an unhealing lesion. Additional large-scale studies are necessary to validate the efficacy of ICBA in thrombosis.
Intrusion Detection System using Fuzzy Genetic Approach

: Network security is of primary concerned now days for large organizations. The intrusion detection systems (IDS) are becoming indispensable for effective protection against attacks that are constantly changing in magnitude and complexity. With data integrity, confidentiality and availability, they must be reliable, easy to manage and with low maintenance cost. Various modifications are being applied to IDS regularly to detect new attacks and handle them. This paper proposes a fuzzy genetic algorithm (FGA) for intrusion detection. The FGA system is a fuzzy classifier, whose knowledge base is modeled as a fuzzy rule such as "if-then" and improved by a genetic algorithm. The method is tested on the benchmark KDD'99 intrusion dataset and compared with other existing techniques available in the literature. The results are encouraging and demonstrate the benefits of the proposed approach.
An assessment of the effects of seed ageing, application of phytohormone and KNO3 on aged corn seeds

Seed ageing is a main problem of seed storage. Unsuitable storage conditions with high moisture and temperature increases seed ageing. In fact, seed ageing results in the decrease of seed quality. Seed priming is known as a seed enhancement treatment which could improve seed germination and germination synchrony in many of crops. In this experiment we investigated effects of seed ageing, application of phytohormone and KNO3 on aged corn seeds. In order to improve germination characteristics in aged seeds phytohormone treatment using different gibberlline concentration (50, 100, 200, 400 and 800 ppm) and KNO3 (0.5, 1, 2.5 and 4%) were used. Results of study showed significant difference in aged seeds. It was also observed that with higher ageing duration, more germination characteristics decreased. Gibberlline at 400 ppm increased germination characteristics in aged seeds and had a positive effect on seed germination of aged corn seeds. KNO3 also had positive effects on seed germination of aged seed. This was higher in application of 0.5% KNO3 for 8 h and 2.5% for 24 h. Based on our results, it was suggested that seed ageing for higher duration could significantly decrease seed quality. Using seed enhancement treatments like seed priming or application of phytohormone could improve aged and non-aged seed performance especially for high aged seeds.
Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia

Pneumonia is among the major killer diseases in under-five children in the world. In developing countries 3 million children die each year due to pneumonia. Ethiopia is one of the 15 pneumonia high burden countries. The aim of this study was to examine the risk factors of the survival time of under-five pneumonia patients using Bayesian approach analysis. Total of 281 under-five pneumonia patients included in this study. The parametric survival models such as Weibull, Lognormal and Log-logistic baseline distributions were used to fit the datasets by introducing prior distributions. The DIC value was used to compare the baseline distributions, and based on the DIC value the Weibull baseline distribution was selected as good model to fit under-five pneumonia dataset well. The results obtained from the Weibull survival model showed that patients from urban residence and patients who were admitted during patient nurse ratio (PNR) was small; were prolong timing death of under-five pneumonia patients, while patients who admitted during Spring and summer season, patients who suffer comorbidity and severe acute malnutrition (SAM) were shorten timing of death of under-five pneumonia patients. Factors such as sex, residence, Season of Diagnosis, Comorbidity, Severe Acute Malnutrition (SAM), Patient refer status and Patient to Nurse Ratio (PNR) were associated with the survival time of under-five pneumonia in this study. The concerned body should give attention for the factors identified in these study to prevent the mortality of under-five children due to pneumonia.
A Review on Fuzzy Fingerprints Based Privacy Preserving Approach

— Now-a-days there are many data-leaks. The Statistics from security firms, research institutions and government organizations shows many data-leaks. Human mistakes are one of the main causes of data loss in various data-leak cases. There exist many solutions detecting unintentional, sensitive data leaks caused by human mistakes and to provide alerts against them to the organization. Here privacy preserving data-leak detection (DLD) solution is used to detect the data loss. Two techniques are used Rabin fingerprint and sliding window. The advantage of proposed method is that, it enables the data owner how to protect the data from being leaked. DLD is offered to the customers with some Internet service providers that can offer service with strong privacy guarantees. Thus evaluation results show that this method can support accurate detection of leaks in various data-leak cases with very small number of false alarms.
A REVIEW ON RELIABLE IMAGE DEHAZING TECHNIQUES

— This paper presents a survey on the different haze removal techniques. Haze is a trouble to many computer vision/graphics applications as it reduces the visibility of the scene in the images. Haze is formed due to the two fundamental phenomena such as attenuation and the air light. Attenuation decreases the contrast and air light increases the whiteness in the scene. Haze removal techniques will retain the color and brightness of the scene . These techniques are widely used in many applications such as underwater photography, satellite images etc. Haze removal is very difficult task because fog depends on the scenes depth information which are unknown. Fog effect is the function of distance between camera and object. There for the removal of fog requires the estimation of air light lamp the overall objective of this paper is to describe the various methods for efficiently removing the haze from remote sensing images . It also gives description of some filters used for dehazing.
A Qualitative Review on Image Processing Algorithms to Detect Early Stage Lung Cancer

 Abstract: Nowa days, the image processing algorithms are being usedwidely in medical systems for detection of lung cancer. It is observed that the life span rate of lung cancer patients increases from 15 to 50% if they were detected at early stages. Detection of cancer cells is the most important issue for medical researchers as it becomes more complex in the treatment process. The detection steps of presence of cancerous cells include image pre-processing, segmentation, feature extraction and classification. In this paper, algorithms for enhancement, segmentation and feature extractionto detect the cancerous tumors which are small and large in size from the lung CT scan images are reviewed. Finally thealgorithms are compared with one another using three parameters called accuracy, sensitivity and specificity.
Assessment of the Outcome of Transarterial Chemoembolization and Sorafenib in the Treatment of Advanced Stage of Hepatocellular Carcinoma: An Observational Study

Aim: This study aims to assess the outcome of transarterial chemoembolization (TACE) and sorafenib in the treatment of advanced stage of hepatocellular carcinoma (HCC). Materials and Methods: The longitudinal analysis of the data was approved by the institutional ethical committee and proper informed consent was taken from the study population. Advanced-stage HCC was defined according to Barcelona clinic liver cancer staging classification (Child-Pugh Class A or B, Eastern Cooperative Oncology Group performance status of 1–2, and/ or macrovascular invasion or extrahepatic metastasis). A total number of 22 patients of advanced-stage HCC were treated with TACE (n = 11) and sorafenib (n = 11) between the period of July 2017 and September 2018. Modified response evaluation criteria in solid tumors (mRECIST) were used to evaluate the outcome in all patients. Results: There was no significant difference between the tumor characteristics (size and number of the lesion, portal vein invasion, and metastases) in the study groups. Both sorafenib and TACE would result in stable response in majority of the patients using mRECIST with no significant difference in the overall survival period between these two treatment modalities. Conclusion: TACE is similar to sorafenib in terms of outcome in advanced-stage HCC using mRECIST. Thus, TACE can be considered as an effective treatment modality in advanced-stage HCC; however, further studies are required to firmly establish this clause.
Studying of the Biosynthesis of 2 H-Labeled Inosine by a Gram-positive Chemoheterotrophic Bacterium Bacillus Subtilis B-3157 on Heavy Water ( 2 H 2 O ) Medium

We studied the biosynthesis of 2 H-labeled purine ribonucleoside inosine (output, 3.9 g/l of liquid microbial culture (LC)) using a strain of the Gram-positive chemoheterotrophic bacterium Bacillus subtilis B-3157, adapted to deuterium. The strain was grown on heavy water (HW) medium with high degree of isotopic purity (99.9 atom% 2 H) containing 2% (v/v) hydrolysate of deuterated biomass of the methylotrophic bacterium Brevibacterium methylicum B-5662 as a source of 2 H-labeled growth substrates, obtained in minimal M9 growth medium with 98% (v/v) 2 H2O and 2% (v/v) [ 2 H]methanol. Inosine was isolated from LC by adsorption/desorption on activated carbon with following extraction by 0.3 M ammonium–formate buffer (pH = 8.9), subsequent crystallization in 80% (v/v) ethanol, and ion exchange chromatography (IEC) on a column with AG50WX 4 cation exchange resin equilibrated with 0.3 M ammonium–formate buffer and 0.045 M NH4Cl. The evaluation of the level of deuterium enrichment performed by fast atom bombardment (FAB) mass spectrometry demonstrated incorporation of 5 deuterium atoms into the inosine molecule (the total level of deuterium enrichment – 65.5 atom% 2 H); 3 deuterium atoms were included into the ribose and 2 deuterium atoms – into the hypoxanthine residue of the molecule.
Cloud Computing-A Study of Infrastructure as a Service

— Cloud computing is a promising technology of the present and the future which uses the grid computing as its backbone. Cloud computing is the hottest topic of information and communication technology (ICT) for implementing it for individual, communities and business. It provides services such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). It provides many benefits like scalability and pay per use etc. Different deployment models are also available to fulfill the needs of the business and industry.
Effects of Oxygen Diffusion on Physicochemical Characteristics of Petroleum Contaminated Sandy Loam Soil

Soil pollution by petroleum and its products in Niger Delta region of Nigeria are predominant due to oil exploration, exploitation and transportation.The aim of this study was to examine the effects of oxygen diffusion onthe physicochemical characteristics of petroleum contaminated sandy loam soils at 100cm depth when there is sufficient availability of indigenous microorganism in the polluted soils. The soil samples were analysis after pollution with Bonny light crude oil. The purpose of the pollution of the soil samples were to simulate conditions of major crude oil spill. Oxygen was diffused through the impacted soils in reactor C. Physicochemical properties of the sandy loam soils considered for analysis were pH, Electrical conductivity, Total organic carbon, Total Nitrogen, Moisture content, Phosphorous and Total petroleum hydrocarbon at two weeks’ interval for six weeks using standard methods. Theanalysis indicated that bioremediation was faster in the soils at the depth of 100cm with oxygen diffusion. The study showed75% reduction in TPH concentration, pH decreased from 6.47to 6.34, Electrical conductivity increased from 92.1 to169. 9μş, Moisture content decreased from 13to 8%, Total organic carbon reduced from 2.301 to 1.716%, Total Nitrogen decreased from 0.199 to 0.032% and Phosphorous reduced from 0.08 to 0.003mg/kg at the end of the study. Physicochemical properties of the treated soils showed similar soil characteristics as compared with the initial conditions of the soil before contamination with Bonny light crude oil. Therefore, this confirmed that oxygen diffusion through petroleum contaminated sandy loam soil was an effective method and a good approach for treatment of petroleum contaminated Sandy loam soil at the depth of 100cm and below.
Phytochemical Screening of Justicia Gendrussa

Justicia gendarussa belongs to family Acanthaceae is commonly known as Nili-Nirgundi. It is traditionally used to treat various diseases such as the wound healing, antioxidant, anti-proliferative etc. The aim of the present study was to investigate the qualitative and quantitative estimation of phytoconstituents of aerial parts of alcoholic extract of Justicia gendarussa. Physiochemical constant, preliminary phytochemical analysis for carbohydrates, glycosides, alkaloids, flavonoid, phenols, tannins and saponin and quantitative analysis for total flavonoid and total alkaloid content were carried out by standard procedures. The physiochemical constituents like total ash and acid insoluble ash, water soluble ash were found to be 14.25%w/w, 05%w/w, 7.30%w/w respectively. The results confirmed the presence of carbohydrates, glycosides, alkaloids, flavonoid, phenols, tannins and saponin and the plant extracts shows higher yield of total phenolic content and also flavonoid content.
Introduction to Machine Prediction of Personality from Facebook Profiles

—Social networks have become widely-used for information dissemination as well as facilitators of social interactions. People express themselves to other people in the community by sharing their experiences, ideas, activities, and memories. As a means, people mostly prefer to use social media such as Facebook, Twitter, Instagram. Early studies exist on the sharing of speciﬁc types of information (photos, posts, etc.), one area that has been less explored is how Facebook proﬁles can identify personality information and in a machine-readable fashion. In this study, we apply data mining and classifications in machine learning techniques which refers to the process of categorizing given input data pieces into certain given groups to predict users’ personality traits using the Big Five personality model. Text-based attributes are extracted from Facebook proﬁles. Then using these predictions we rank individuals in terms of the ﬁve traits. A similarity among individual’s personality traits and linguistic information is explored for analytics .
SUPERVISED LEARNING APPROACH FOR SINGER IDENTIFICATION IN SRI LANKAN MUSIC

: This paper describes a method of modeling the characteristics of a singing voice from polyphonic audio signals, in the context of Sri Lankan Music. The main problem in modeling the characteristics of a singing voice is the negative influences caused by accompaniment sounds. Hence the proposed method consists of a procedure to reduce the effect of accompaniment sound. It extracts the predominant melody frequencies of the music file and then resynthesize it. Melody is extracted only on the vocal-parts of the music file to achieve better accuracy. Features vectors are then extracted from the predominant melody frequencies, which are then subjected to supervised leaning approaches with different classifier, using Principal Component Analysis as feature selection algorithms. The models trained with 10-fold cross validation and different combinations of experiments are done to critically analyze the performance of the proposed method for Singer Identification.
SIMULATION AND ANALYSIS OF MULTILEVEL INVERTER WITH REDUCED NUMBER OF SWITCHES

As compared to conventional two level inverters, multilevel inverters have been widely accepted for high-power and high-voltage applications due to their added advantages of low switching stress and lower total harmonic distortion (THD), hence reducing the size and bulk of the passive filters. In this paper a new five level inverter topology is presented with reduced number of switches as compared to conventional cascaded H-bridge multilevel inverter, and can be extended to any number of levels. The performance of the new topology and its controller are validated with simulation results using the MATLAB/SIMULINK software.
A CAUSE-EFFECT GRAPH SOFTWARE TESTING TOOL

: This paper explains analysis and implementation of a cause-effect graph software testing tool. The cause-effect graph software testing method and its application are described. The method of generating test cases from software specification is discussed. In addition, a new cause-effect graph testing tool is developed, and processes in the cause-effect graph software testing is explained with an example. Moreover, the coverage analysis of effect nodes is described.