Sharif Digital Repository

Service Identification is one of the most important phases in serviceoriented development methodologies. Although several service identification methods tried to identify services automatically or semi-automatically, various aspects of business domain are not taken into account simultaneously. To overcome this issue, three strategies from three different aspects of business domain are combined for semi-automated identification of services in this article. At first, the tasks interconnections within the business processes are considered. Then, based on the common supporting requirements, another tasks dependency has been determined and finally, regarding the significant impact of data in... 

Static malware detection approaches are time-consuming and cannot deal with code obfuscation techniques. Dynamic malware detection approaches, on the other hand, address these two challenges, however, suffer from behavioral ambiguity, such as the system calls obfuscation. In this paper, we introduce Markhor, a dynamic and behavior-based malware detection approach. Markhor uses system call data dependency and system call control dependency sequences to create a weighted list of malicious patterns. The list is then used to determine the malicious processes. Next, the similarity of a file system call sequences to a malicious pattern is extracted based on a fuzzy algorithm and the file nature is... 

Sophisticated and targeted malwares, which today are known as Advanced Persistent Threats (APTs), use multi-step, distributed, hybrid and low-level patterns to leak and exfiltrate information, manipulate data, or prevent progression of a program or mission. Since current intrusion detection systems (IDSs) and alert correlation systems do not correlate low-level operating system events with network events and use alert correlation instead of event correlation, the intruders use low and hybrid events in order to distribute the attack vector, hide malwares behaviors, and therefore make detection difficult for such detection systems. In this paper, a new approach for detecting hybrid and... 

Targeted cyber attacks, which today are known as Advanced Persistent Threats (APTs), use low and slow patterns to bypass intrusion detection and alert correlation systems. Since most of the attack detection approaches use a short time-window, the slow APTs abuse this weakness to escape from the detection systems. In these situations, the intruders increase the time of attacks and move as slowly as possible by some tricks such as using sleeper and wake up functions and make detection difficult for such detection systems. In addition, low APTs use trusted subjects or agents to conceal any footprint and abnormalities in the victim system by some tricks such as code injection and stealing... 

The variation of pose, illumination, and expression continues to make face recognition a challenging problem. As a pre-processing step in holistic approaches, faces are usually aligned by eyes. The proposed method tries to perform a pixel alignment rather than eye alignment by mapping the geometry of faces to a reference face while keeping their own textures. The proposed geometry alignment not only creates a meaningful correspondence among every pixel of all faces, but also removes expression and pose variations effectively. The geometry alignment is performed pixel-wise, i.e., every pixel of the face is corresponded to a pixel of the reference face. In the proposed method, the information... 

In Iranian Sign Language (ISL), alongside the movement of fingers/arms, the dynamic movement of lips is also essential to perform/recognize a sign completely and correctly. In a follow up of our previous studies in empowering the RASA social robot to interact with individuals with hearing problems via sign language, we have proposed two automated lip-reading systems based on DNN architectures, a CNN-LSTM and a 3D-CNN, on the robotic system to recognize OuluVS2 database words. In the first network, CNN was used to extract static features, and LSTM was used to model temporal dynamics. In the second one, a 3D-CNN network was used to extract appropriate visual and temporal features from the... 

Static malware detection approaches are time-consuming and cannot deal with code obfuscation techniques. Dynamic malware detection approaches, on the other hand, address these two challenges, however, suffer from behavioral ambiguity, such as the system calls obfuscation. In this paper, we introduce Markhor, a dynamic and behavior-based malware detection approach. Markhor uses system call data dependency and system call control dependency sequences to create a weighted list of malicious patterns. The list is then used to determine the malicious processes. Next, the similarity of a file system call sequences to a malicious pattern is extracted based on a fuzzy algorithm and the file nature is... 

Despite the numerous researches in Stress Corrosion Cracking (SCC) risk of austenitic stainless steels in aqueous chloride solution, no formulation or reliable method for prediction of time to failure as a result of SCC has yet been defined. In this paper, the capability of artificial neural network for estimation of the time to failure for SCC of 304 stainless steel in aqueous chloride solution together with sensitivity analysis has been expressed. The output results showed that artificial neural network can predict the time to failure for about 74% of the variance of SCC experimental data. Furthermore, the sensitivity analysis also demonstrated the effects of input parameters (Temperature,... 

Human action recognition from skeletal data is one of the most popular topics in computer vision which has been widely studied in the literature, occasionally with some very promising results. However, being supervised, most of the existing methods suffer from two major drawbacks; (1) too much reliance on massive labeled data and (2) high sensitivity to outliers, which in turn hinder their applications in such real-world scenarios as recognizing long-term and complex movements. In this paper, we propose a novel unsupervised 3D action recognition method called Sparseness Embedding in which the spatiotemporal representation of action sequences is nonlinearly projected into an unwarped feature... 

Despite many advances in optical character recognition in general, there are still serious challenges remaining in recognizing Farsi text. The main reason is the cursive nature of the letters in written Farsi, i.e., depending on the position of a letter within a word, it might join to its neighboring letters, which consequently changes the shape of the character. As a result, each letter can have up to four different character shapes. In addition to the problem of segmenting the characters, the increased number of characters makes the recognition task even more challenging. This paper introduces a complete framework for character recognition, including a method for segmenting the characters... 

In this case–control study, class І and ІІ human leukocyte antigen (HLA) alleles in Iranian patients with benign and severe cutaneous adverse drug reactions (CADRs) due to aromatic anticonvulsants and antibiotics were evaluated. Patients diagnosed with CADRs (based on clinical and laboratory findings) with a Naranjo score of ≥ 4 underwent blood sampling and HLA-DNA typing. The control group comprised 90 healthy Iranian adults. Alleles with a frequency of more than two were reported. Deviations from Hardy–Weinberg equilibrium were not observed. Eighty patients with CADRs including 54 females and 26 males with a mean age of 41.49 ± 16.08 years were enrolled in this study. The culprit drugs... 

In this study, optimized cephalexin-loaded niosomal formulations based on span 60 and tween 60 were prepared as a promising drug carrier system. The niosomal formulations were characterized using a series of techniques such as scanning electron microscopy, Fourier transformed infrared spectroscopy, dynamic light scattering, and zeta potential measurement. The size and drug encapsulation efficiency are determined by the type and composition of surfactant. The developed niosomal formulations showed great storage stability up to 30 days with low change in size and drug entrapment during the storage, making them potential candidates for real applications. Moreover, the prepared niosomes showed... 

Alzheimer’s disease (AD) is currently ranked as the sixth leading cause of death in the United States and recent estimates indicate that the disorder may rank third, just behind heart disease and cancer, as a cause of death for older people. Clearly, predicting this disease in the early stages and preventing it from progressing is of great importance. The diagnosis of Alzheimer’s disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. It can be difficult and exhausting to manually compare, visualize, and analyze this data due to the heterogeneous nature of medical tests, therefore, an efficient approach for accurate prediction of the... 

In this paper, we present a machine learning model to estimate the blood pressure (BP) of a person using only his photoplethysmogram (PPG) signal. We propose algorithms to better detect some critical points of the PPG signal, such as systolic and diastolic peaks, dicrotic notch and inflection point. These algorithms are applicable to different PPG signal morphologies and improve the precision of feature extraction. We show that the logarithm of dicrotic notch reflection index, the ratio of low-to high-frequency components of heart rate (HR) variability signal, and the product of HR multiplied by the modified Normalized Pulse Volume (mNPV) are the key features in accurately estimating the BP... 

In this article, we present a new photoplethysmogram (PPG)-based blood pressure (BP) estimation approach, in which the PPG recording site (fingertip) is not in a standstill position but swings up and down in the sagittal plane during the recording. The upward and downward movements of the recording site result in useful morphological changes in the PPG signal, which can be used to better estimate BP. To investigate the effect of the vertical hand movement on the shape of the PPG signal, we first devised a PPG recording hardware and used it to collect a dataset consisting of PPG signals recorded from 120 subjects. Then, we utilized machine-learning models to estimate BP using the extracted... 

Recently a few methods have been proposed in the literature for non-invasive cuff-less estimation of systolic and diastolic blood pressures. One of the most prominent methods is to use the Pulse Transit Time (PTT). Although it is proven that PTT has a strong correlation with the systolic and diastolic blood pressures, this relation is highly dependent to each individuals physiological properties. Therefore, it requires per person calibration for accurate and reliable blood pressure estimation from PTT, which is a big drawback. To alleviate this issue, in this paper, a novel method is proposed for accurate and reliable estimation of blood pressure that is calibration-free. This goal is... 

Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper...