This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially their utility in allocating a problem to a specific developer. An analysis was conducted on two key areas: first, the development of a model to represent developer prioritizing within the bug repository, and second, the use of hybrid machine learning techniques to select bug reports. Moreover, we use our model to facilitate developer assignment responsibilities. Moreover, we considered the developers’ backgrounds and drew upon their established knowledge and experience when formulating the pertinent objectives. An examination of two individuals’ experiences with software defects and how their actions impacted their rankings as developers in a software project is presented in this study. Researchers are implementing developer categorization techniques, assessing severity, and reopening bugs. A suitable number of bug reports is used to examine the model’s output. A developer’s bug assignment employee has been established, enabling the program to successfully address software maintenance issues with the highest accuracy of 78.38%. Best engine performance was achieved by optimizing and cleansing data, using relevant attributes, and processing it using deep learning.
The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences
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The curriculum is amodern science which reflects the social philosophy and
what it needs . It searches for amothod that limits the knowledge that the
indiridual gets in the society and the sorts of the culture that suits the enrironment
in which they live. It also clears for them their history and their great in heritance.
It has a great in flunce in their mental growth ,and it teacher the students new
roles in the thin king ,and training then on what they have learned . According to
there points the problem concentrats on the mostimpotant difficulties which facer
thestudents in studing Arabic langnage text-books
In spite of the great care that the text taker but it is full of subjects and studies
w
مفهوم معامل الارتباط كمقياس يربط بين متغيرين هذا يجلب انتباهنا إلى موضوع الإحصاء في كل المستويات. أكثر من ذلك هناك ثلاث نقاط خاصة هي اعتيادياً نشدد عليها كما يأتي:-
(1 معامل الارتباط هو الدليل المعياري والذي قيمته لا تعتمد على قياسات
المتغيرات الأصلية.
(2قيمته تقع في المدى] 1,1-[ .
&nb
... Show MoreAbstract
In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min
... Show MoreThis study investigates the results of electrocoagulation (EC) using aluminum (Al) electrodes as anode and stainless steel (grade 316) as a cathode for removing silica, calcium, and magnesium ions from simulated cooling tower blowdown waters. The simulated water contains (50 mg/l silica, 508 mg/l calcium, and 292 mg/l magnesium). The influence of different experimental parameters, such as current density (0.5, 1, and 2 mA/cm2), initial pH(5,7, and 10), the temperature of the simulated solution(250C and 35 0C), and electrolysis time was studied. The highest removal efficiency of 80.183%, 99.21%, and 98.06% for calcium, silica, and magnesium ions, respectively, were obtained at a current de
... Show Moreبحث لمعرفة رواة السنن والمسانيد للحافظ ابن نقطة
Electrocoagulation is an electrochemical process of treating polluted water where sacrificial anode corrodes to produce active coagulant (usually aluminum or iron cations) into solution. Accompanying electrolytic reactions evolve gas (usually as hydrogen bubbles). The present study investigates the removal of phenol from water by this method. A glass tank with 1 liter volume and two electrodes were used to perform the experiments. The electrode connected to a D.C. power supply. The effect of various factors on the removal of phenol (initial phenol concentration, electrode size, electrodes gab, current density, pH and treatment time) were studied. The results indicated that the removal efficiency decreased as initial phenol concentration
... Show MoreDoses for most drugs are determined from population-level information, resulting in a standard ?one-size-fits-all’ dose range for all individuals. This review explores how doses can be personalised through the use of the individuals’ pharmacokinetic (PK)-pharmacodynamic (PD) profile, its particular application in children, and therapy areas where such approaches have made inroads.
The Bayesian forecasting approach, based on population PK/PD models that account for variability in exposure and response, is a potent method for personalising drug therapy. Its potential utility is eve
Childhood is characterized by ahigh privacy in the life of the child overall educational institutions in the world. Based on this specificity, modern education begins with a holistic vision of the child through all developmental aspects (moral, religious, emotional, social, linguistic, physical, health, and mental). This integration could be achieved through taking into consideration the needs and rights of children and developing curricula that consider these needs and capacities to provide opportunities for developing and supporting the developmental aspects of the child. The contemporary technological developments in the field of computer and the Internet have brought with it new forms, ideas, and problems for children in recent years
... Show MorePrediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one