Miracle-dz/UniFAR-FTUs huggingface dataset:
the Lumped Elements Using Differential Evolution Algorithm

L-shaped patch antenna (LPA) is formed by combining two monopole patch radiators. Proper modelling of a LPA using lumped elements is crucial in antenna design and analysis. In this study, a novel equivalent circuit (EC) modeling of an LPA using differential evolution (DE) optimization algorithm is presented. Two parallel branches each represents the monopole patch radiator compose the EC topology. In each branch, a serial resistance and inductance pair stands for patch conductor, a parallel resistance and capacitance pair symbolizes the dielectric substrate. The expressions of these eight lumped elements enclosing the antenna’s physical and electrical parameters accompanying with optimization variables are constituted considering the element definitions of micro strip transmission line (MTL). Return loss equation is derived through input impedance equation of the EC model. The variables are then optimally found by fitting the calculated return loss to the simulated results by DE algorithm. The proposed EC model is then verified through results of simulated and measured LPA. Moreover, real and imaginary parts of the EC input impedance are comparatively calculated. These results show that the proposed EC model gives almost the same results in terms of important antenna parameters.
PHOTOACOUSTIC TOMOGRAPHY BASED ON THE APPLICATION OF VIRTUAL DETECTORS

Photoacoustic tomography (PAT) based on the filtered back projection (FBP) algorithm needs full-scanned photoacoustic data of the sample to reconstruct good quality images. Unfortunately, the number of ultrasonic sensor locations and the sampling angles are subject to the restriction of hardware conditions and spatial size in the practical application. The consequence is that the quality of reconstructed images becomes poor. Proposed the concept of virtual detectors using interpolation and compressed sensing method to preprocess the photoacoustic data in order to solve these problems. Results of numerical simulation with Matlab demonstrate that the peak signal-to-noise ratio (PSNR) of the images has been significantly improved.
FM0/Manchester Encoding for DSRC Applications using Sols Technique

The dedicated short-range communication (DSRC) is an emerging technique to push the intelligent transportation system into our daily life. The DSRC standards generally adopt FM0 and Manchester codes to reach dc-balance, enhancing the signal reliability. Nevertheless, the coding-diversity between the FM0 and Manchester codes seriously limits the potential to design a fully reused VLSI architecture for both. In this paper, the similarity-oriented logic simplification (SOLS) technique is proposed to overcome this limitation. The SOLS technique improves the hardware utilization rate from 57.14% to 100% for both FM0 and Manchester encodings. The performance of this paper is evaluated on the postlayout simulation in Taiwan Semiconductor Manufacturing Company (TSMC) 0.18-µm 1P6M CMOS technology. The maximum operation frequency is 2 GHz and 900 MHz for Manchester and FM0 encodings, respectively. The power consumption is 1.58 mW at 2 GHz for Manchester encoding and 1.14 mW at 900 MHz for FM0 encoding. The core circuit area is 65.98×30.43 µm2. The encoding capability of this paper can fully support the DSRC standards of America, Europe, and Japan. This paper not only develops a fully reused VLSI architecture, but also exhibits an efficient performance compared with the existing works.
Comparison of the accuracy of clinical methods for estimation of fetal weight

Estimation of fetal weight (EFW) is one of the esse ntial measures for labor and delivery. While the us e of ultrasonography for EFW is costly, may not work in some centers. So, to make a nonultrasound method for EFW is important. This study aimed to compare the accuracy of various clinical methods for EFW with the actua l birth weight at term pregnancy. A cross-sectional study c onducted on 98 pregnant women who were admitted for elivery with gestational age of 37-42 weeks, singleton preg nancy and cephalic presentation in Imam Khomeini ho spital, Ahvaz. The fetal weight was anticipated by a midwif e through abdominal palpation (using Leopold's mane uvers), measurements of symphysis-fundal height and abdomin al girth, and also three formulas. The results were analyzed using the software SPSS version 20 and SATA11. The actual average birth weight was3242.85±43.37 gr. A significant positive correlation was observed betwe en actual birth weight and clinically estimated wei ght. Kappa coefficient was > 0.8 when all studied methods we re compared with the actual weight. This agreement was greater on abdominal palpation and Risanto’s formula, respe ctiv ly. In the present study, abdominal palpation a d Risanto's formula are more accurate for predicting fetal weight. Since these methods are quick, simple and costeffective for EFW so, they can be a useful alternat ive instead of routine ultrasonography.
Modified Technique for Speaker Recognition using ANN

Speaker recognition consists of three phases: pre-processing, feature extraction and classification. During the first phase, the computer records the voice pattern of the speaker and analyse it. By the end of the second phase, the main features of the voice pattern are extracted. In the third phase, many classification techniques are exist such as artificial neural network (ANN) , hidden Markov model (HMM) and vector quantization (VQ). Classifiers based on ANN are used in both text dependent and text independent speaker identification and speaker verification systems. Furthermore, it is extremely efficient at learning complex mappings between input and outputs. Unfortunately, ANN technique is complex and time consuming. In this paper, we use two different feature extraction techniques. These techniques are MFCC and PNCC. In addition, we use principle component analysis (PCA) as a feature reduction technique to enhance the classifier performance and speed. We apply ANN for both techniques with different training algorithms. The best results are achieved using PNCC as a feature extraction, the ANN as a classifier with sequential weight/bias training algorithm. Our proposed technique decreases the number of neurons that lead to have best performance and processing time.
ATTENTION DEFICIT HYPERACTIVITY DISORDER SYMPTOMS IN PRIMARY CHILDREN WITH POOR SCHOOL PERFORMANCE IN FCT

A sound education is essential to a good life. Being successful in their academic pursuits is the goal of every educational venture. Therefore persistent poor academic outcome should be considered a symptom of a larger problem and investigated. Children with poor school performance would be seen by healthcare providers. It is then important that the awareness of the burden of ADHD as a medical cause of school failure be created. This study aims to describe the symptoms of ADHD prevalent in symptoms in primary school children in the Gwagwalada Area Council who are failing in school. Materials and Methods: This study was carried out among primary school children with poor school performance who were assessed to have symptoms of ADHD using the DSM-IV school version adapted by Du-Paul. Results: Fifty (50) children were assessed to have ADHD. Thirty –one (62%) children were assessed to have inattentive subtype (IA) of ADHD, 16 (32%) had the combined subtype while only 3(6%) had the hyperactivity-impulsivity subtype (HA) of ADHD. The prevalence of symptoms was higher in the inattentive subset. Discussion: This study highlights the high prevalence of inattentive symptoms of ADHD in primary school children in the Gwagwalada area council who have poor academic performance; a finding which is in keeping with other studies. Conclusion: it does appear that there is a need for a larger study which will also incorporate the diagnosis of comorbid conditions which have been shown to exist with ADHD.
Cell Structure and Power Analysis Using Dynamic Ram

: The scaling of channels attains the current leakage at transistors, which shows the power lenience. In order to decrease the power and also to increase the speed of the structure, the size of the transistor is assumed to be low. Then it can also be changed. In this paper the dynamic RAM has been implemented for reducing the power. By analyzing the structure with 6T, N-CRAM in its features, a decreased power is reached, which is compared with the system in its active mode. The performance are analyzed in 1.8v which reduces the 90 percent of power than 6T, and 18 percent of power is reduced than in 8T cell, and 30 percent of current leakage is reduced in 6T cell. Thus it is compared to the existing SRAM, that leads to the cell with less power and storage of data is fine without distortion. So the constancy of the structure is increased when related to other cell. The result waveform gives that the cell contains improved stability and reduction in leakage using the cadence virtuoso of 180 nm technology.
Real Time Implementation of Model Reference Adaptive Controller for a Conical Tank

Nonlinear process control is a difficult task in process industries. Conical tank level control is one among them. Real processes often exhibits nonlinear behavior, time variance and delays between inputs and outputs. This paper aims at implementing an adaptive control algorithm for a conical tank system. System identification of the non-linear process is done using black box modelling and found to be first order plus dead time (FOPDT) model. Here Proportional integral (PI) controller based on Ziegler Nichols (ZN) method is designed initially and the results are compared with model reference adaptive controller (MRAC). The real time implementation of process is done in LabVIEW using NI DAQ (BNC 2120). Better controller performance and error can be minimized by using MRAC than that of the ZN tuned PI controller.
A New Approach of Semi-Supervised Clustering With Abbreviation Detection and Domain Prediction Using Online Dictionaries

: The data mining is a technique that offers the computer algorithms to compute useful patterns from the huge data. The nature of data may be found in two popular categories structured and unstructured data. The structured data is available in form of relational manner and the unstructured data is not organized in a given relativity, but if the data is well defined then that can be utilized with the supervised learning algorithms. Text mining is a branch of data mining which deals with unstructured data. Text mining is a technique, which extracts information from the large amount of textual contents. Proposed work uses the text data to perform analysis of clustering algorithms performance. The clustering of chat data uses the unsupervised learning, therefore the entire input data samples require to cluster with predefined domain knowledge, therefore dynamic knowledgebase that helps to improve clustering algorithm uses a domain classifier. The proposed work introduces the semi-supervised clustering technique with dynamic knowledge of abbreviation and domain of the text. Proposed work enhances the text clustering performance by previous knowledge of classes. Agglomerative clustering and their improved variant is utilized for making analysis and performing the clustering task, before clustering of text data that is needed to improve the quality of data therefore the raw text data is first pre-processed then tagged according to the domain names. The clustering algorithm trains and makes use to cluster the text according to their semantics after tagging on the original text data.
Optimizing Feed Withdrawal in Broiler Effect of Feed Withdrawal Timing on Broiler Carcass Yield in Tropics

Food and for that matter poultry meat contamination has become a major concern to poultry producers, processors and consumers. The objectives of this study was to determine the optimum feed withdrawal time on broiler yield and provide basis formajor welfare problems in broiler destined for slaughter and processing. Two experiments were conducted. Experiment 1 was an on-farm data collection system based on typical feed withdrawal time practicedby a commercial farm on carcass yield. In experiment 2, Hubbard commercial day old chicks (n=200)were weighed and reared under anad-libitumfeeding and water condition for 56 days. At 56 days, broilers were randomly allocated to 5 feed withdrawal treatments (0, 4, 8, 12 and 16 hours) prior to slaughter.Parameters measured were the average feed intake and initial body weight, final live body weight, intestinal and crop weight, dressed weight and feed conversion ratio. All data were analyzed using the Generalized Linear Model ofSAS (Proc. GLM procedure)and lsmeans separated by SNK at P< 0.05. In experiment 1, a fixed 16 hour feed withdrawal period resulted in 267.5g live weight loss between before and after feed withdrawal. In experiment 2, the initial body weight and the feed intake was the same for all birds reared.The final live body weight, intestines and crop weight reduced significantly as the feed withdrawal time increased. The dressed weight of the 8, 12 and 16 hours was significantly (P<0.0001) lower than 0 and 4 hour withdrawal time. There was increased intestinal sloughing in 12 and 16 hours withdrawal treatment, indicating increasing poor welfare implications on the birds. Increasing length of feed withdrawal increased feed conversion ratio which was due heavily to live weight reduction as withdrawal time increased. While feed withdrawal has it benefits, the physical reduction in body weight, dressed weight and intestinal integrity pose a welfare danger to the birds in longer hours.
COMPARATIVE ASSESSMENT OF ICA METHODS FOR BLIND SOURCE SEPARATION OF INSTANTANEOUS MIXTURES

-The paper presents a comparative assessment of Blind Source Separation (BSS) methods for instantaneous mixtures based on namely generalized eigen-value decomposition, geometrical concepts, differential of mutual information and Kalman filtering applied to Nonlinear Principal Component Analysis (Nonlinear PCA). The methods highlight the independence concept underlying Independent Component Analysis (ICA). The methods have been tested on instantaneous mixtures of synthetic periodic signals, monotonous noise from electromechanical systems and speech signals. A comparison among the methods has been made on the basis of separation ability, processing time and accuracy. The quality of output, complexity of algorithms and simplicity (implementation) of the methods are some of the performance measures which have been highlighted with respect to the above signals
THE MODERATING EFFECT OF COMPETITIVE INTENSITY ON THE RELATIONSHIP BETWEEN MARKET ORIENTATION AND PERFORMANCE OF PRIVATE SECURITY FIRMS IN KENYA

The objective of this study was to establish the moderating effect of competitive intensity on the relationship between market orientation on the performance of private security firms in Kenya. Data was collected from key informants in the private security firms and they were either the marketing managers or the Chief Executive Officer of the firms. The theoretical perspective to the study was Market based View. The study targeted 39 firms that were members of the Kenya Security Industry Association (KSIA) in a census study that was cross-sectional in nature and 37 firms participated in the study. Data was collected using a semi-structured questionnaire. Results of the regression analysis indicated that market orientation had a positive and significant effect on both non-financial and financial performance of the private security firms in Kenya. The results also indicated that competitive intensity moderated the relationship between market orientation and non-financial performance but not with financial performance. The study recommended that managers of private security firms and firms in other industries should view market orientation as a resource that can enhance the firms’ ability to achieve sustainable competitive advantage. It also recommended that management of firms should invest their time in developing a market orientation culture among all departments of their firms. The study also recommended that managers should evaluate performance implications of their internal firm resources and use them to develop and implement strategies that will help the firm to counter competitor actions through exploration or exploitation of market opportunities. A longitudinal study was suggested since the industry competition will be significantly affected by the strong government regulation through the Private Security Regulatory Authority. KEY WORDS: Market Orientation, Competitive Intensity, Private Security Firms, Kenya CITATION: Onditi, E. O. , Kibera, N. F. , Aranga, M. J., & Iraki, X. N. (2020). The moderating effect of competitive intensity on the relationship between market orientation and performance of private security firms in Kenya. The Strategic Journal of Business & Change Management, 7(1), 47 – 65.
An estimation of economic, recreational and aesthetic value of Margoon Waterfall-Iran "A comparison of Logit and artificial neural networks"

In the present study, the efficiency of neural network model and a Logit regression model are compared to predict willingness to pay to preserve Margoon Waterfall. To do so, first, a logit regression model was estimated and then using the same set of regressors (input variables) an artificial neural network model was designed and estimated. For this purpose, 329 questionnaires were collected through simple random sampling method, of which about 90% of data (289 data) were used to design and train neural network and the remaining 10 percents were used to examine the predictive power of the models. Error percentages of the two models for predicting the tendency to pay were compared. The results of the study indicate that neural network model is more efficient in predicting the willingness to pay (with fewer errors) than the Logit regression model.
Performance Analysis of Sensing Time Parameter in Cooperative Sensing Cognitive Radio

— Spectrum scarcity problem is well addressed by cognitive radio. The main role of spectrum sensing is to discover the empty band correctly . This is done with the help of energy detector. The sensing time is a very crucial parameter which regulates the detection probability. In this paper the impact of sensing time has been investigated. The rigorous simulations are done on sensing time parameter with varying snr and keeping probability of false alarm constant and vice versa. The simulations are done for cooperative sensing with AND and OR rule and it shows that AND rule outperforms in terms of detecting the band. Results also show that Sensing efficiency is declined with increasing sensing time.
Example Based Machine Translation Using Various Soft-Computing Techniques Review

— This paper focus on the various techniques involved in machine translation (MT). The various techniques involved in machine ignore many aspects when they generate natural language processing (NLP). An optimization technique was one of the major tools for many years in the formulation and solution of computational problems arising in speech and language processing. One of the methods, phrase-based SMT consists of three steps: segmentation of source sentences into a sequence of phrases, translation of each source phrase to a target phrase; and reordering of target phrases into target sentences. Further a Fuzzy Inference system model is used selecting the optimal features from speech vectors. The most fundamental problems in the field of machine learning are Feature selection. Fuzzy logic plays the major role in approximate reasoning. It has the ability to deal with different types of uncertainty, the implementation of the theory to real life problems. A linguistic variable, as its name suggests, is a variable whose values are not numbers but words or sentences in a natural language. Convex optimization problems are formulated and solved, with analytical formulas derived for training the ensemble-learning parameters. The result shows that above mentioned techniques were effective to certain limit which have not yield the proper translation in case of NLP. Thus this paper proposes an idea for under the heading “example based translation using soft-computing tool” like fuzzy logic implementation to yield successful NLP.
Knowledge Discovery in Higher Education using Association Rule Mining

— Since last few years, so many statistical tools have been used to analyze students’ performance from different points of view. This paper presents data mining in education environment that identifies students’ failure patterns using association rule mining technique. The identified patterns are analyzed to offer a helpful and productive recommendations to the academic planners in higher institutions of learning to improve their decision making process. This will also aid in the curriculum structure and modification in order to improve students’ academic performance and reduce failure rate
Speaker Detection of Encrypted Speech Communication Using Talk Patterns

— In this paper, we propose a new class of traffic analysis attacks to encrypted speech communications with the goal of detecting speakers of encrypted speech communications. These attacks are based on packet timing information only and the attacks can detect speakers of speech communications made with different codec’s. The detection can be made with the talk patterns. These talk patterns are observed from the encrypted speech packets and this can be analyzed for speaker detection.
Real Time HCI using Eye Blink Detection

— This project aims to design an effective and efficient HCI both in terms of performance and cost. It also designs a Hands-free interface which helps to interact with the computer by using the facial features. To select a robust facial feature, we use the pattern recognition paradigm of treating features. We are using an off-the-shelf webcam that affords a moderate resolution and frame rate as the capturing device. It compensates people who have hand disabilities that prevent them from using the mouse by designing an application that uses facial features to interact with the computer.
Cocaína durante la gestación y conducta materna postparto en ratones

Maternal cocaine abuse during pregnancy is associated to neglect, abuse, and mother-child bond disruption, which directly affects infant development; therefore, various neurobehavioral problems of children of drug-dependent parents could be attributed to inadequate maternal behavior or prenatal exposure to drugs. Thus, the aim of this research was to analyze the effects of chronic cocaine administration during pregnancy on postpartum maternal behavior. To do this, 21 CD1 pregnant female mice were randomly assigned for administration of saline solution and cocaine (25 mg/kg/day and 50 mg/kg/day), from day 8 to 21 of gestation. After delivery, for 15 minutes a day, during 20 days, the frequency of occurrence of 16 behavioral patterns of maternal behavior was individually recorded, using an ethogram. Cocaine slightly affected maternal behavior frequency, although it may have affected other parameters, such as latency, duration, and sequence of this behavior.
Multiband Patch Antenna for Wireless Devices

In this paper, a novel microstrip antenna is designed, fabricated and experimentally verified for operation in various bands like GPS, WI MAX and WLAN bands. This microstrip patch antenna is based on a DSP antenna design with U-shaped slots and resonant strip to achieve the wideband operation required to meet the specifications. The effect of variation of dimensions and locations of the Uslots and resonant stripe are studied thoroughly to get an appropriate design. It can sever most of wireless communication applications that operate between 1 GHz to 12GHz and require wide band characteristics. The antenna is planner and will be printed on both the sides of FR4 substrate which adds compactness to it, so as to easily embed it in any portable appliances. Keywords—Microstrip antennas; Wi MAX; mobile antennas; WLAN; GSM; Bluetooth; wideband antennas. __________________________________________________*****_________________________________________________