Miracle-dz/UniFAR-FTUs huggingface dataset:
Attitudes Toward Risk and Coping Responses: The Case of Food Crop Farmers at Agona Duakwa in Agona East District of Ghana

The effect of fermentation duration of raw Bambara groundnut ( Voandzeia subterranean (L) on the growth performance, carcass quality and feed cost of finisher broilers were investigated. Two hundred 21 day old female Arbor acre broiler chicks were randomly divided into five treatment groups of forty birds each. The experimental design was a Completely Randomized Design with each treatment replicated five times with eight birds per replicated. Five test diets were formulated to contain no Bambara groundnut (C0) control or 15% of Bambara groundnut (BGN) either socked in water for 12 hours (F0) or socked and fermented for 12 hours, (F12), 24 hours (F24) and 36 hours (F36). Results showed that total feed consumption was significantly (P<0.05) higher with birds fed diet F0 compared with birds fed diet F12. The final body weight and total body weight gain were significantly (P<0.05) higher for the control diet (C0) compared to the rest of the treatments. Birds fed the control diet (C0) had improved fed conversion ratio (P<0.05) compared with the other treatments. Bigger liver and heart (P<0.05) were obtained with birds fed diet containing BGN (F0, F24 and F36) compared with the control (C0) and F12 group. The cost per kg weight gain ($1 USA = CFA 480 Francs) was significantly (P<0.05) lower with birds fed diet F0 compared with birds fed diet F12, F24 and F36 but comparable with the control (Co) diet. The result of the present study showed that fermentation duration had no significant effect on body live weight, weight gain and feed consumption ratio.
A Lossless Compression Scheme for Bayer Color Filter Array Images Using Genetic Algorithm

: A portable device such as a digital camera with a single sensor and Bayer color filter array (CFA) requires demosaicing to reconstruct a full color image. In most digital cameras, Bayer CFA images are captured and demosaicing is generally carried out before compression. Recently, it was found that compression-first schemes outperform the conventional demosaicing-first schemes in terms of output image quality. A Genetic Algorithm based lossless compression scheme for Bayer CFA images is proposed in this Project. Simulation results show that the proposed compression scheme can achieve a better compression performance than conventional lossless CFA image coding schemes
Analysis of User Access Probability and Collision in Device-to-Device Communication for 5G Cellular Network

: In the near future, i.e., beyond 4G, to fulfil the increasing demands for higher capacity, improved data rate, decreased latency and better quality of service, the wireless based networks of today will have to advance in various ways. In next generation of wireless networks, Device-to-Device (D2D) communication is considered as an innovative mobile network technology for improving communication performance and network capacity of fifth generation (5G) cellular system. It is introduced to offload the increasing traffic to the user equipment. To achieve better efficiency and improved traffic transmission rate in communication, it is highly important to reduce collision. In this paper, our goal is to design a scheme to minimize collision probability for D2D communication. We first provide performance analysis based on the Markov process model using numerical calculations on Matlab. In addition, we present the relationship between user access probability and collision probability. The results demonstrate the viability of the proposed scheme.
Optimal Financial Leverage Determinants For Smes Capital Structure Decision Making: Empirical Evidence From Indonesia

s: The purpose of conducting this research is to determine the effect of company characteristics and the characteristics of SMEs owners on the targeted leverage. This research is a quantitative study in nature with a sample of research is SMEs located in Banyumas Regency, Central Java, Indonesia. This study employed multiple linear regression analysis with e-views (econometric views) program on panel data as a statistical approach. The results showed that the variable of growth rate, company size, liquidity, and asset structure significantly influence the leverage of SMEs. Further, profitability has a negative effect but not significant on SMEs leverage. While the variable characteristics of SME owners also have an impact on SMEs leverage. Results of statistical analysis also show that variables such as knowledge, experience, and risk propensity have a significant effect on SMEs leverage. Finally, gender differences statistically have no significant effect on the SMEs leverage The results of this study are expected to provide information for SME owners about factors that influence corporate leverage decisions in terms of company characteristics and characteristics of SME owners/managers. Index-Term : Company Characteristics, Characteristics of SME Owners/Managers, SME, and Leverage ——————————  ——————————
Adaptive Back stepping Approach for Longitudinal Control of Aircraft Unmanned Aerial Vehicles

Autonomous unmanned aerial vehicles provide the possibility of performing tasks and missions that are currently hazardous or can cost lives. Here a nonlinear model of the unmanned aerial vehicle is used in order to describe the longitudinal dynamics which is highly complicated in itself. Therefore an adaptive back stepping controller is employed, the underlying feature of which is a dynamic parameter adaptation law. The control input is derived based on the Lyapunov stability theorems, that guarantees asymptotic stability design phase itself. The control law along with the parameter adaptation law gives a better regulation when compared with other linear control techniques. Software implementation is carried our using MATHLAB Simulink. Simulation results validate the fact that the controller works satisfactory.
Achieving Optical Fiber Communication Experiments by OptiSystem

-Recently, optical fiber communication technology have made great progress, where has been constantly exploring new technologies has greatly enhanced communications capabilities in the traditional sense, this makes the optical fiber communication technology in a broader context has been applied. Deployment of optical communication systems is costly and reconfiguration is in some cases impossible or uneconomical, therefore the experiments and simulation of systems are has become necessity to predict and optimize system performance. This paper highlights on the implement of these technologies by use optisystem program which will increase the proper understanding of mechanism action of each optical communication component and provides more freedom to explore design parameters than analytic calculations and physical experiments thus allows students to develop an intuitive understanding of optics in a rapid way.
Protection of Sensitive Data for Multi-Level Trust Privacy Preserving Data Mining

: The study of perturbation based privacy preserving data mining (PPDM) approaches introduces random perturbation that is number of changes made in the original data. The limitation of previous solution is single level trust on data miners but new work is perturbation based PPDM to multilevel trust. When data owner sends number of perturbed copy to the trusted third party that time adversary cannot find the original copy from the perturbed copy means the adversary diverse from original Copy this is known as the diversity attack. To prevent diversity attack is main goal of MLT-PPDM services. The malicious data miner has different perturbed copy by applying different MLT-PPDM algorithms to add the noise into original data.
Supporting Church of England clergy through the provision of Reflective Practice Groups

This document is a pdf of the finalised, published verson of the article 'Supporting Church of England clergy through the provision of reflective practice groups'. It first appeared in the winter 2015 issue of the journal Thresholds, which is published by the British Association for Counselling and Psychotherapy©. This pdf may not be adapted and is supplied for non-commercial use only.
A Pathological Voices Assessment Using Classification

The diagnosing of pathological voice may be a tedious topic and it receives abundant attention. There are several diseases that adversely have an effect on our human speech (voice). The doctor will use only the equipments for detection of pathological voice. However, it is invasive and needs a skilled analysis of diverse human speech signal parameters. Automatic voice analysis for pathological speech has its own blessings, like 1)its quantitative and non-invasive nature. 2) permitting the identification and observance of vocal system diseases . Within the pathological voice classification techniques gathered by the voice of a patient, the goal is to discriminate whether the given voice is normal or pathological. From the speech Mel- Frequency Cepstral Coefficients (MFCC) has been extracted from the voice information and classified into two categories. However, the accuracy of the earlier classification methodology may need additional improvement. In my project work, Support Vector Machine (SVM) classifier is used for pathological voice classification with non-invasive nature to diagnose and analyze the voice of the patient.
The classification scheme for the heart disease prediction

With the enormous enhancement of diseases in medical and the other communities of healthcare, it is extremely important to have an analysis of the heart diseases at the early stages. Since, nowadays it is very important to detect the diseases and lessen the death of patients at early stages. Every person has different values of cholesterol, blood pressure and many more that are linked with heart disease prediction. But it has scientifically proven that the normal person blood pressure is counted to be 120/90 along with this the pulse rate and the cholesterol value is 72. In this paper, the various “machine learning algorithms” are explained that include Support Vector Machine, Decision tree, neural network and many more are explained so that complete description can be provided. Along with this, the entire description of the heart disease has been provided that depicts about the need for the topic to be selected. There are some of the issues present in the Data Mining algorithm that are also described in the paper. The ultimate aim is to improve efficiency in different parameters by describing the classification approach for detecting heart disease. The parameters on which the prediction can be done are the age, serum cholesterol, gender, blood pressure, pulse rate. The accuracy and the efficiency in the prediction can be increased only if the number of attributes is more. For the classification of heart disease, the most efficient algorithm is the Support Vector Machine algorithm since it will not only reduce the prediction time but will also improve the efficiency of the algorithm.
Antioxidant and enzyme inhibitory activities of Cissampelos pareira L. leaf extracts

Mir Zahoor Gul, Sambamurthy Chandrasekaran*, Mohd Yasin Bhat, Radheshyam Maurya*, Insaf Ahmed Qureshi** and Irfan Ahmad Ghazi Department of Plant Sciences, School of Life Sciences, University of Hyderabad, Gachibowli, Hyderabad 500 046, Telangana State, India *Department of Animal Biology, School of Life Sciences, University of Hyderabad,Gachibowli, Hyderabad 500 046, Telangana State, India **Department of Biotechnology, School of Life Sciences, University of Hyderabad, Gachibowli, Hyderabad 500 046, Telangana State, India
Designing Procedure for Micro-Class Remote Controlled Fixed Wing VTOL

The current economy is not just concerned about efficient production, but also fast and safe transportation of the produce, UAVs (unmanned aerial vehicle) are playing a crucial role in speedy delivery of perishable or, lifesaving supplies to remote and inaccessible regions of the world during medical emergencies or natural calamities. Conventional multirotor UAVs have good maneuverability and take less space to land and take-off but are slow and inefficient. Whereas, RC (remote controlled) planes are fast and efficient but have less maneuverability and require space for take-off and landing. Fixed wing VTOLs (vertical take-off and landing) combine the advantages of both these forms of UAVs. The following is a simple design procedure for the conventional structural components of a fixed wing micro-class RC VTOL. The optimum ranges of all the parameters required for designing were found out through literature survey and practical manufacturing of various UAVs for diverse applications.
Investigation into Reliable & Efficient Biometrics Techniques

: Biometrics allows to check human subjects by analyzing & comparing physical traits. Human body of characteristics might be prints of finger, eye retinas, voice of patterns & irises, facial patterns & hand measurements. Biometric systems consist of application that requires biometric technologies. They would allow automatic identification. It would allow authentication or verification of natural person. Many researches are done on biometrics. But there are several limitations in such technologies such as slow comparison speed, biometric data requires more space & error rate during comparison is too much. Our research would eliminate all above limitation by integrating edge detection mechanism with biometric. Only useful part of biometric data would be saved so that space would be saved & comparison time would be reduced as there would be small data to make comparison. If useless data is eliminated then probability of error rate during comparison also gets reduced. We have discussed several edge detection mechanisms also & we have chosen best from them.
IoT based Real Time ECG Monitoring System using Cypress WICED

: Smart and cost effective healthcare has been in increasing demand to meet the needs of growing human population and medical expenses. It is a known fact that country like India has become heart disease capital of the world. There is a urgent need to develop an effective health monitoring system, that can detect abnormalities of health conditions in time and make diagnoses according to the gleaned data. ECG monitoring is a widely studied and applied approach to diagnose heart diseases. However, existing portable wireless ECG monitoring systems cannot work without a mobile application, which is responsible for data collection and passing on the messages to doctors. Recent advances in mobile technology and cloud computing have inspired numerous designs of cloud-based health care services and devices. Within the cloud system, medical data can be collected and transmitted automatically to medical professionals from anywhere and feedback can be returned to patients through the network. In this paper, we propose a new method for ECG monitoring based on Cypress Wireless Internet Connectivity for Embedded Devices (WICED) Internet of Things (IoT) platform. ECG data are gathered using a wearable monitoring node and are transmitted directly to the IoT cloud using Wi-Fi. Internet of Things utilizes open source protocols like CoAP/HTTP, MQTT, TLS/TCP, DTLS/UDP and OMALWM2M for data communication and device management.
DISTANCE BASED CLUSTER HEAD ELECTING TECHNIQUE FOR ENERGY CONSTRAINT APPLICATIONS

: Wireless Sensor Networks (WSN) is made of substantial amount of energy, and also it has computationaland communication constraints, WSN applications spread over fields like military, habitat monitoring, in these applications replacing or recharging the batteries is impossible scenario. Once they are placedin threatening situations. Consequently, to keep the system alive as long as possible, communication between the WSN nodes must be finished with balanced parameters (energy vs. amount of data transfer). The paper will address above issue. In this paper, a routing algorithm is proposed by making necessary modifications in higher connectivity algorithm which considers the distance as a factor for electing the clusterhead. The modified algorithm is also implemented for multicasting. Factors like mobility have also been considered.
Real-Time Twitter Sentiment Classification Using Unsupervised Reviews

--Sentiment analysis, also known as opinion mining, is an area that analyzes people’s opinions, sentiments, evaluations, towards entities such as products, services, individuals made in blog posts, comments, reviews or tweets. In the real world, businesses and organizations always want to consider consumer or public opinion about their products and services. So sentiment classification is an important task in everyday life. All the web page contains reviews that are given by users expressing different polarity i.e. positive or negative. Sentiment is expressed differently in different domains. The data trained on one domain cannot be applied to the data trained on another domain and it is costly too. The cross domain sentiment classification overcomes these problems by creating thesaurus for labeled data on the target domain and unlabeled data from source and target domains. The proposed method the reviews are analyzed by unsupervised method and sentiment can be analyzed for each sentence.
Identifying Text,Visual Objects of Traffic Panels using Text Detection Algorithm

— Traffic Panel detection and recognition has been studied from long time. Traffic panel detection and recognition still remains a challenge in computer vision because of different types of information depicted in them. In this context, not only a good visibility of panels is important for a safe use by road users, but also the suitability of the information contained in the traffic panel. In this system we studied a method which detects traffic panels and to recognize the information contained. The main purpose of development of system is to make an automatic inventory of traffic panel. The system is used to help for road support and traffic panel maintenance and assist drivers. In our propose system, images are represented as a “bag of visual words”. For text detection where a traffic panel has been detected Optical Character Recognition (OCR) algorithm is used, in order to automatically read and save the information contained in panel. Efficiency of algorithm is proved by the experimental results on real images taken from Google Street View.
Molecular detection of methicillin resistant staphylococcus aureus isolated from burns infection in Al-nasiriyah city

The present study aimed to investigate the prevalence of Methicillin-Resistant Staphylococcus aureus (MRSA) in the burn unit at Al-Hussein teaching hospital during the period from September, 2013 to January, 2014 in Thi-Qar province, Iraq. From a total of two hundred burn swab samples, there were 90 isolates recorded a 90 positive MRSA culture with a percentage of (45%). Identification was done depending on morphological , cultural , microscopical characterization and biochemical tests. Depending on the area of collection, the swabs were collected from 7 sites. Hands showed the highest Staph. aureus infections with 25 isolates (27.77%), followed by feet and necks with 20 (22.22%) and 16 (17.77%), respectively. axilla and back sites showed the lowest infections with one Staph. aureus isolate with a percentage of for both (1.11%). A total of 90 isolates of Staph. aureus were further examined using polymerase chain reaction (PCR) for detection of mecA gene,16s rRNA and PVL. The results revealed that of MRSA isolates yield amplification products of mecA gene 68(75.5%) , 16S rRNA found in all isolates and Eighty six isolates were PVL negative (95.5%) and the remaining 4.4% (4 isolates) were PVL positive.
International Journal of Current Research in

A simple, non-toxic and eco-friendly technique was adopted for synthesizing silver nanoparticles (Ag NPs) by using aqueous leaf extracts of Eichhornia crassipes. In the present study, silver nanoparticles were synthesized using silver nitrate. The visual appearance of colour was noted and characterized further by UV, IR, SEM and XRD analysis. By using this green technique, silver nanoparticles can be effectively synthesized in a very short time which can be helpful in controlling its population. Accepted: 20 February 2016 Available Online: 06 March 2016
The genetic structure and adaptation of Andean highlanders and Amazonian dwellers is influenced by the interplay between geography and culture

Western South America was one of the worldwide cradles of civilization. The well known Inca Empire was the tip of the iceberg of a cultural and biological evolutionary process that started 14-11 thousand years ago. Genetic data from 18 Peruvian populations reveal that: (1) The between-population homogenization of the central-southern Andes and its differentiation with respect to Amazonian populations of similar latitudes do not extend northward. Instead, longitudinal gene flow between the northern coast of Peru, Andes and Amazonia accompanied cultural and socioeconomic interactions revealed by archeological studies. This pattern recapitulates the environmental and cultural differentiation between the fertile north, where altitudes are lower; and the arid south, where the Andes are higher, acting as a genetic barrier between the sharply different environments of the Andes and Amazonia (2). The genetic homogenization between the populations of the arid Andes is not only due to migration during the Inca Empire or the subsequent colonial period. It started at least during the earlier expansion of the pre-Inca Wari Empire (600-1000 YBP) (3) This demographic history allowed for cases of positive natural selection in the high and arid Andes vs. the low Amazon tropical forest: in the Andes, HAND2-AS1 (heart and neural crest derivatives expressed 2 antisense RNA1, related with cardiovascular function) and DUOX2 (dual oxidase 2, related to thyroid function and innate immunity) genes; in the Amazon, the gene encoding for the CD45 protein, essential for antigen recognition by T/B lymphocytes in viral-host interaction, consistent with the host-virus arms race hypothesis.
Pilot based Channel Estimation of OFDM aided with KGMO Algorithm

: Now a days there is a huge demand for wireless communications. To accommodate huge number of users new methods are required. Orthogonal Frequency Division Multiplexing (OFDM) is one of the promising technology for modern wireless communications. In this paper OFDM system performance is investigated by estimating the channel with the help of Kinetic Gas Molecule Optimization (KGMO) algorithm. Comb type pilot arrangement is used for estimating the channel with Least Square (LS) estimation method. Results are simulated with Matlab and shown at the end of the paper.
A Teacher-Guided Automated Essay Grading Tool using Gradient Descent Algorithm and Reflective Random Indexing

— The emergence of automated essay scoring (AES) tools is an effect of the problems of teachers in tediously checking essays of students. The AES tools proved to be useful for this task. However, current tools disables the ability of the teacher to select the criteria to be used in checking these essays. Thus, these tools are discouraged by teachers. This study made use of the gradient descent algorithm for multiple variables to automate the checking of the essay responses with teacher-guided scoring preferences. The extracted features are the word count, the keyword count, the spelling error value, the grammar error value and the content similarity value. Reflective random indexing is used to extract the content similarity value of a student essay response to the essay response provided by the teacher. The model shows an 89.78% accuracy based on the quadratic weighted kappa error (QWKE) metric. This shows that the proposed model is able to correctly grade student essays. The model was then implemented in a batch-processed essay quiz creation and scoring web application for full usage on any educational institution.