This is the template for question paper of Department of CSE of Stamford University Bangladesh.
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\title{Exam Title}
\author{Faculty Name}
\date{Month YYYY}
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\begin{document}
% Details about the oraganizing institute and the exam
% \header{Instituition name}{Department}{Exam Level}{Exam Name}{Course Teacher}{Date and Time}
\hdr{STAMFORD UNIVERSITY BANGLADESH}{Department of Computer Science and Engineering}{Term X Examination, Spr./Sum//Fall YYYY Semester}{Course Code: Course Title}{CT: Faculty Name}{Date and Time: dd/MM/YYYY, HH:MM - HH:MM}
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\subhdr{CSE-S-XX-X}{Siddeswari}{2 hours}{30 marks}
% Provide general exam instructions here
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\vspace{-1em}
\geninstructions{
\textit{(There are \textbf{FOUR} questions. \textbf{Answering all of them is mandatory}. Figures in the right margin indicate CLOs and marks. Writing anything on the question paper is strictly prohibited.)}
}
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% Begin question sections here
% \question{Question no.}{Question Statement}{Sub Question number}{Sub Question Statement}{Marks}
\question{1}{
\lipsum[1-1]\\~\\
Now, take a look at a figure.
\img{0.8}{0.6}{Images/fig1}{A basic OP-Amp circuit}{op_amp}\\
\lipsum[1-1]
And now look at the two sub-figures.
\imgtwo{0.95}{0.75}{Images/titanic_EDA_1}{A boxplot}{0.95}{0.75}{Images/titanic_EDA_2}{A histogram}{EDA from the titanic dataset}\\
As a potential data scientist, try to find out the following:}
{a}{
\begin{itemize}
\item [i.] Sub task 1.
\item [ii.] Sub task 2.
\end{itemize}
}
{(3)}
\subquestion{b}
{\lipsum[1-1]
Consider the following equation:
\equ{\textnormal{net}_j = \sum_{i}{W_{ij}x_{ij} = W_{0j}x_{0j} + W_{1j}x_{1j}+ \dots +W_{Ij}x_{Ij}}}
Do the following tasks:
\begin{itemize}
\item [i.] Sub task 1.
\item [ii.] Sub task 2.
\end{itemize}
}
{(3)}{}
\subquestion{c}
{Task description}
{(4)}{}
\question{2}{
\lipsum[2-3]:
\img{0.8}{0.4}{Images/fig2}{Architecture of the neural network}{neural_architecture}\\
The weights of the neural network are randomly set as follows:
The weights of the neural network are randomly set as follows: \\
\begin{table}[htp]
\fontsize{12}{12}
\centering
\caption{Weights of the neural network}
\begin{tabular}{|c|c|c|c|c|c|}
\hline
$x_{0} = 1$ & $W_{0e} = 0.5$ & $W_{0f} = 0.5$ & $W_{0g} = 0.5$ & & $W_{0h} = 0.25$ \\
\hline
$x_a = 0.8$ & $W_{ae} = 0.5$ & $W_{be} = 0.9$ & $W_{ce} = 0.6$ & $W_{de} = 0.6$ & $W_{eh} = 0.9$ \\
\hline
$x_b = 0.3$ & $W_{af} = 0.5$ & $W_{bf} = 0.9$ & $W_{cf} = 0.6$ & $W_{df} = 0.8$ & $W_{fh} = 0.9$ \\
\hline
$x_c = 0.6$ & $W_{ag} = 0.4$ & $W_{bg} = 0.8$ & $W_{cg} = 0.6$ & $W_{dg} = 0.6$ & $W_{gh} = 0.8$ \\
\hline
$x_d = 0.6$ & & & & & \\
\hline
\end{tabular}
\label{tab:neural_weights}
\end{table}
}
{a}{
Now perform the following task
\begin{itemize}
\item [i.] Calculate the value of $(1+\frac{1}{\exp^{-x}})$.
\item [ii.] Task 2.
\end{itemize}
}
{(6)}{}
\subquestion{b}
{
Take a look at the given Figure \ref{op_amp} and do task 1.
}
{(4)}{}
\question{3}{}
{}{\lipsum[4-4] }
{(10)}
\begin{center}
====== Best of Luck ======
\end{center}
\pagebreak
\section*{Appendix}
\begin{table}[!htp]
\begin{center}
\caption{T-table of Confidence interval estimate}
\begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|c|}
\multicolumn{12}{c}{$t$ PERCENTAGE POINTS} \\
\hline
$\nu$&60.0\%&66.7\%&75.0\%&80.0\%&87.5\%&90.0\%&95.0\%&97.5\%&99.0\%&99.5\%
&99.9\% \\
\hline
\hline
1&0.325&0.577&1.000&1.376&2.414&3.078&6.314&12.706&31.821&63.657&318.31 \\
\hline
2&0.289&0.500&0.816&1.061&1.604&1.886&2.920&4.303&6.965&9.925&22.327 \\
\hline
3&0.277&0.476&0.765&0.978&1.423&1.638&2.353&3.182&4.541&5.841&10.215 \\
\hline
4&0.271&0.464&0.741&0.941&1.344&1.533&2.132&2.776&3.747&4.604&7.173 \\
\hline
5&0.267&0.457&0.727&0.920&1.301&1.476&2.015&2.571&3.365&4.032&5.893 \\
\hline
6&0.265&0.453&0.718&0.906&1.273&1.440&1.943&2.447&3.143&3.707&5.208 \\
\hline
7&0.263&0.449&0.711&0.896&1.254&1.415&1.895&2.365&2.998&3.499&4.785 \\
\hline
8&0.262&0.447&0.706&0.889&1.240&1.397&1.860&2.306&2.896&3.355&4.501 \\
\hline
9&0.261&0.445&0.703&0.883&1.230&1.383&1.833&2.262&2.821&3.250&4.297 \\
\hline
10&0.260&0.444&0.700&0.879&1.221&1.372&1.812&2.228&2.764&3.169&4.144 \\
\hline
11&0.260&0.443&0.697&0.876&1.214&1.363&1.796&2.201&2.718&3.106&4.025 \\
\hline
12&0.259&0.442&0.695&0.873&1.209&1.356&1.782&2.179&2.681&3.055&3.930 \\
\hline
13&0.259&0.441&0.694&0.870&1.204&1.350&1.771&2.160&2.650&3.012&3.852 \\
\hline
14&0.258&0.440&0.692&0.868&1.200&1.345&1.761&2.145&2.624&2.977&3.787 \\
\hline
15&0.258&0.439&0.691&0.866&1.197&1.341&1.753&2.131&2.602&2.947&3.733 \\
\hline
16&0.258&0.439&0.690&0.865&1.194&1.337&1.746&2.120&2.583&2.921&3.686 \\
\hline
17&0.257&0.438&0.689&0.863&1.191&1.333&1.740&2.110&2.567&2.898&3.646 \\
\hline
18&0.257&0.438&0.688&0.862&1.189&1.330&1.734&2.101&2.552&2.878&3.610 \\
\hline
19&0.257&0.438&0.688&0.861&1.187&1.328&1.729&2.093&2.539&2.861&3.579 \\
\hline
20&0.257&0.437&0.687&0.860&1.185&1.325&1.725&2.086&2.528&2.845&3.552 \\
\hline
21&0.257&0.437&0.686&0.859&1.183&1.323&1.721&2.080&2.518&2.831&3.527 \\
\hline
22&0.256&0.437&0.686&0.858&1.182&1.321&1.717&2.074&2.508&2.819&3.505 \\
\hline
23&0.256&0.436&0.685&0.858&1.180&1.319&1.714&2.069&2.500&2.807&3.485 \\
\hline
24&0.256&0.436&0.685&0.857&1.179&1.318&1.711&2.064&2.492&2.797&3.467 \\
\hline
25&0.256&0.436&0.684&0.856&1.178&1.316&1.708&2.060&2.485&2.787&3.450 \\
\hline
26&0.256&0.436&0.684&0.856&1.177&1.315&1.706&2.056&2.479&2.779&3.435 \\
\hline
27&0.256&0.435&0.684&0.855&1.176&1.314&1.703&2.052&2.473&2.771&3.421 \\
\hline
28&0.256&0.435&0.683&0.855&1.175&1.313&1.701&2.048&2.467&2.763&3.408 \\
\hline
29&0.256&0.435&0.683&0.854&1.174&1.311&1.699&2.045&2.462&2.756&3.396 \\
\hline
30&0.256&0.435&0.683&0.854&1.173&1.310&1.697&2.042&2.457&2.750&3.385 \\
\hline
35&0.255&0.434&0.682&0.852&1.170&1.306&1.690&2.030&2.438&2.724&3.340 \\
\hline
40&0.255&0.434&0.681&0.851&1.167&1.303&1.684&2.021&2.423&2.704&3.307 \\
\hline
45&0.255&0.434&0.680&0.850&1.165&1.301&1.679&2.014&2.412&2.690&3.281 \\
\hline
50&0.255&0.433&0.679&0.849&1.164&1.299&1.676&2.009&2.403&2.678&3.261 \\
\hline
55&0.255&0.433&0.679&0.848&1.163&1.297&1.673&2.004&2.396&2.668&3.245 \\
\hline
60&0.254&0.433&0.679&0.848&1.162&1.296&1.671&2.000&2.390&2.660&3.232 \\
\hline
$\infty$
&0.253&0.431&0.674&0.842&1.150&1.282&1.645&1.960&2.326&2.576&3.090 \\
\hline
\hline
$\nu$&60.0\%&66.7\%&75.0\%&80.0\%&87.5\%&90.0\%&95.0\%&97.5\%&99.0\%&99.5\%
&99.9\% \\
\hline
\end{tabular}
\label{tab:t-table}
\end{center}
\end{table}
\end{document}