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ntroduction: Stapler Haemorrhoidopexy is a relatively recent technique used in surgical management of haemorrhoids. The traditional haemorhhoidectomy procedure (Milligan Morgan Technique) is known to be associated with more post operative complications which may include bleeding, pain , fever etc. The aim of this study was to compare the two procedures in terms of post operative complications in the immediate period following surgery. Aim : To analyse open haemorrhoidectomy and stapler haemorrhoidopexy in the management of grade III/IV haemorrhoids based on immediate post operative period. Objective: To study the incidence of post operative complications in the 2 techniques of surgical management of haemorrhoids. Materials and Methods : A prospective and retrospective clinical study done in Department of general surgery of Dr. Sampurnanand Medical College, Jodhpur, Rajasthan. In our study 116 patients with grade ¾ haemorrhoids were included and were equally divided in 2 groups that underwent either procedure. Results: Among all patients, the ones who underwent stapler haemorrhoidopexy had signicantly fewer complications as compared to patients in open haemorrhoidectomy group. Conclusion: stapled haemorrhoidopexy is a safe and effective procedure in grade 3 & 4 haemorrhoids and can be safely considered an alternative to open haemorrhoidectomy

Denial of Service (DoS) attacks have evolved from volumetric attacks to target specific applications and can cripple different services with very limited effort. Hypertext Transfer Protocol (HTTP) is vulnerable to a slow rate DoS attack generated through prolonged connections which deliberately send incomplete requests to server. Simple detection methods which use $x$ number of such connections in $y$ time can be easily evaded. In this paper, we present SlowTrack which can detect slow rate DoS attacks against HTTP using a set of behavioral parameters. SlowTrack uses eight behavioral parameters which are validated to be useful in identifying the attack. We correlate these parameters to understand how their values change when attack is launched and subsequently use these observations to propose detection methods. \texttt{SlowTrack} is composed of three detection algorithms which make use of these observations for detecting attacks. We evaluate the detection performance of \texttt{SlowTarck} using experiments done in a testbed and also in a live network to show that these algorithms can detect the slow rate attacks effectively.

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