Miracle-dz/UniFAR-FTUs huggingface dataset:
Contextual Distance for Data Perception

Structural perception of data plays a fundamental role in pattern analysis and machine learning. In this paper, we develop a new structural perception of data based on local contexts. We first identify the contextual set of a point by finding its nearest neighbors. Then the contextual distance between the point and one of its neighbors is defined by the difference between their contribution to the integrity of the geometric structure of the contextual set, which is depicted by a structural descriptor. The centroid and the coding length are introduced as the examples of descriptors of the contextual set. Furthermore, a directed graph (digraph) is built to model the asymmetry of perception. The edges of the digraph are weighted based on the contextual distances. Thus direction is brought to the undirected data. And the structural perception of data can be performed by mining the properties of the digraph. We also present the method for deriving the global digraph Laplacian from the alignment of the local digraph Laplacians. Experimental results on clustering and ranking of toy problems and real data show the superiority of asymmetric perception.
Improving Packet Caching Scalability Through the Concept of an Explicit End of Data Marker

Over the past few years, the Web has witnessed an explosion of dynamic content generation to provide Web users with an interactive and personalized experience. While traditional Web caching techniques work well when redundancy occurs on an object-level basis (page, image, etc.), the use of dynamic content presents unique challenges. Although past work has addressed mechanisms for detecting redundancy despite dynamic content, the scalability of such techniques is limited. In this paper, we present a technique for explicit packet boundary delineation to enable scalable and highly efficient packet caching in the network. Our approach, explicit end of data (EEOD), does not require client-side modification and requires only minimal server-side modifications. We demonstrate through experimental studies on an Apache Web server 25% and 30% relative improvements in terms of bandwidth efficiency and retrieval time over current approaches in the literature
Efficient design of Local Binary Pattern for image retrieval

A novel image description method named Half-LBP has been proposed in this paper for image retrieval applications. Half-LBP transforms the relationship among the intensity levels of image local pixel blocks into a binary pattern in such a way that reduces the dimension of the descriptor significantly while keeping the retrieval accuracy comparable with the state of art methods. The basic operation is quite similar to the texture operator named Local Binary Pattern (LBP). However, the dimension of the LBP method and its variants are too high and take substantial amount of time to retrieve the images. To address this issue, Half-LBP image descriptor has been proposed which takes comparatively less time to find out the matched images from the database.
Helping students keep up with real-time captions by pausing and highlighting

We explore methods for improving the readability of real- time captions by allowing users to more easily switch their gaze between multiple visual information sources. Real-time captioning provides deaf and hard of hearing (DHH) users with access to spoken content during live events, and the web has allowed these services to be provided via remotely- located captioning services, and for web content itself. However, despite caption benefits, spoken language reading rates often result in DHH users falling behind spoken content, especially when the audio is paired with visual references. This is particularly true in classroom settings, where multi-modal content is the norm, and captions are often poorly positioned in the room, relative to speakers. Additionally, this accommodation can benefit other students who face temporary or "situational" disabilities such as listening to unfamiliar speech accents, or if a student is in a location with poor acoustics. In this paper, we explore pausing and highlighting as a means of helping DHH students keep up with live classroom content by helping them track their place when reading text involving visual references. Our experiments show that by providing users with a tool to more easily track their place in a transcript while viewing live video, it is possible for them to follow visual content that might otherwise have been missed. Both pausing and highlighting have a positive impact on students' scores on comprehension tests, but highlighting is preferred to pausing, and yields nearly twice as large of an improvement. We then discuss several issues with captioning that we observed during our design process and user study, and then suggest future work that builds on these insights.
Privacy in Mediated and Nonmediated Interpersonal Communication: How Subjective Concepts and Situational Perceptions Influence Behaviors

New communication media such as social networking sites (SNSs) and instant messengers (IMs) challenge users’ privacy perceptions. Technical infrastructures and the flow of digital information lead to novel privacy risks that individuals are often not acquainted with. Users’ subjective perceptions of privacy may thus be flawed and lead to irrational behavior. In this work, we investigated a concept that has been addressed only implicitly in academic research on privacy: the user’s subjective perception of a given level of privacy. We examined the literature on how privacy perceptions have been conceptualized in traditional theories of privacy and how these conceptualizations are challenged in social media communication. We first qualitatively explored laypeople’s privacy concepts and investigated their subjective perceptions of privacy levels and subsequent private disclosures in different mediated and nonmediated communication settings. Interviews with N = 33 Germans revealed that, similar to academic privacy theories, they tend to conceptualize privacy as control over social, physical, and psychological boundaries. However, trust and other-dependent privacy emerged as important novel aspects for understanding privacy regulation in online communication. We further found that individuals consistently perceived a high level of privacy in face-to-face situations and a low level of privacy in public communication on SNSs. With regard to IMs, however, their answers were mixed: Uncertainty regarding digital communication properties and audiences as well as limited control over the communication setting prevented a reliable and shared perception of the privacy level. With regard to privacy behavior and private disclosures, we found that people tend to adapt their sharing of private information to the perceived level of privacy.
InetVis : a Graphical aid for the Detection and Visualisation of Network Scans

This paper presents an investigative analysis of network scans and scan detection algorithms. Visualisation is employed to review network telescope traffic and identify incidents of scan activity. Some of the identified phenomena appear to be novel forms of host discovery. The scan detection algorithms of Snort and Bro are critiqued by comparing the visualised scans with alert output. Where human assessment disagrees with the alert output, explanations are sought after by analysing the detection algorithms. The algorithms of the Snort and Bro intrusion detection systems are based on counting unique connection attempts to destination addresses and ports. For Snort, notable false positive and false negative cases result due to a grossly oversimplified method of counting unique destination addresses and ports.
Direct Serum Assay for Cell-Free Bmi-1 mRNA and Its Potential Diagnostic and Prognostic Value for Colorectal Cancer

Purpose: Cell-free Bmi-1 mRNA is stably detectable in the serum/plasma and is associated with the development and progression of some tumors. Previous methods detecting extracellular Bmi-1 mRNA with RNA extraction are inefficient. This study developed a novel reverse transcription quantitative PCR (RT-qPCR) approach directly applied in serum (RT-qPCR-D) to quantify Bmi-1 mRNA, and assessed its diagnostic and prognostic potential in colorectal cancer. Experimental Design: The feasibility of the RT-qPCR-D method was first analyzed in 50 serum samples. Then, using the RT-qPCR-D method, Bmi-1 mRNA expression was validated in serum from an independent cohort of patients with 87 normal colonoscopy, 76 hyperplastic polyp, 82 inflammatory bowel disease, 68 adenoma, and 158 colorectal cancer. Receiver operating characteristic (ROC) curves and Cox analyses were used to evaluate its diagnosis and prognosis value, respectively. Results: In a pilot study, levels of Bmi-1 mRNA were increased in colorectal cancer serum samples detected by RT-qPCR-D and significantly associated with results obtained by RT-qPCR. In a validation cohort, serum Bmi-1 mRNA levels were significantly elevated in the colorectal cancer group and the adenoma group when compared with other groups. The area under ROC curve distinguishing colorectal cancer from benign colorectal diseases was 0.888, with 72.2% sensitivity and 94.9% specificity, which was superior to carcinoembryogenic antigen. Bmi-1 mRNA levels were significantly associated with survival. Cox analysis indicated Bmi-1 mRNA was an independent prognostic factor for overall survival. Conclusions: Detection of cell-free Bmi-1 mRNA in serum by RT-qPCR-D is a simple and noninvasive approach and may be used for colorectal cancer diagnosis and prognosis. Clin Cancer Res; 21(5); 1225–33. ©2014 AACR.
Software Escalation Prediction with Data Mining

One of the most severe manifestations of poor quality of software products occurs when a customer “escalates” a defect: an escalation is triggered when a defect significantly impacts a customer's operations. Escalated defects are then quickly resolved, at a high cost, outside of the general product release engineering cycle. While the software vendor and its customers often detect and report defects before they are escalated it is not always possible to quickly and accurately prioritize reported defects for resolution. As a result, even previously known defects, in addition to newly discovered defects, are often escalated by customers. Labor cost of escalations from known defects to a software vendor can amount to millions of dollars per year. The total costs to the vendor are even greater, including loss of reputation, satisfaction, loyalty, and repeat revenue. The objective of Escalation Prediction (EP) is to avoid escalations from known product defects by predicting and proactively resolving those known defects that have the highest escalation risk. This short paper outlines the business case for EP, an analysis of the business problem, the solution architecture, and some preliminary validation results on the effectiveness of EP.
Development of Unmanned Aerial Vehicle for Intelligent Transportation

An unmanned aerial vehicle (UAV) has many applications including implementation in intelligent transportation. The UAVs can be used in detection and tracking of a specific road which play an important role in transportation including traffic monitoring, and ground–vehicle tracking. It can also be implemented in constructing road networks for modeling and simulation. Various algorithms can be used for detection of the road networks. In this paper, two main approaches have been proposed including, graph-cut–based road detection during the initialization stage and a homography-based road-tracking scheme is developed to automatically track road areas. The proposed system works more efficiently as the road detection is performed only when it is necessary. Thus implementation of UAVs in intelligent transportation provides a more efficient of tracking and detection of road conditions and traffic situations.
Finite Size Formula in the XYZ Spin Chain

The XYZ spin chain with boundaries is studied. We construct the vacuum state by the vertex operators in the level one modules of the elliptic algebra, and compact it through a geometric symmetry of the model called the turning symmetry. From this simplified expression the ``finite size formula'' for magnetizations in the bounded and in the half-infinite chains is deduced. Applying this formula we calculate the spontaneous magnetization in the bounded XYZ model.
Sub-Nyquist processing with the modulated wideband converter

Sub-Nyquist systems capture the signal information in a different fashion than uniform high-rate samples. Consequently, digital processing, which is the prime reason for leaving the analog domain, becomes challenging. We propose a digital algorithm that translates samples obtained by the modulated wideband converter, a recent sub-Nyquist system, to the standard format of existing software packages. Our algorithm works in baseband, that is without the need to interpolate the samples to the Nyquist grid. Related methods such as nonuniform sampling or the random demodulator are shown to lack the baseband processing option.
A Social Identity Threat To Merit: The Effects Of Similar Experience On Empathic Concern

Past research indicates that having a similar life experience as another person leads to greater empathic concern towards that person. Two studies empirically investigated if similar experiences of race-based social identity threat can increase the empathic concern of White Americans toward African Americans. Study 1 revealed that White Americans randomly assigned to think about White privilege and then randomly assigned to read a passage about an African American whose accomplishments are attributed to Affirmative Action policies (versus an African American whose accomplishments are attributed to his hard work and merit) felt greater empathic concern toward the African American described in the passage. This effect was significantly mediated by stereotype threat feelings and moderated by group identity. Study 2 revealed that White Americans randomly assigned to think about how others think they have benefited from White privilege and then randomly assigned to read a passage about an African American whose accomplishments are attributed to Affirmative Action policies (versus an African American whose accomplishments are attributed to his hard work and merit) felt greater empathic concern toward the African American described in the passage only when mediated by stereotype threat feelings or stereotype threat cognitions. This mediated effect was moderated by merit identity. This suggests that White American participants do not see the literal similarities between the scenarios of race based social identity threat to merit but can see the similarities in internal feelings and cognitions that both experiences create. Collectively, these studies suggest a novel consideration of social identity and understanding of intergroup processes.
Some strains of Plasmodium falciparum, a human malaria parasite, evade the complement-like system of Anopheles gambiae mosquitoes

Plasmodium falciparum lines differ in their ability to infect mosquitoes. The Anopheles gambiae L3-5 refractory (R) line melanizes most Plasmodium species, including the Brazilian P. falciparum 7G8 line, but it is highly susceptible to some African P. falciparum strains such as 3D7, NF54, and GB4. We investigated whether these lines differ in their ability to evade the mosquito immune system. Silencing key components of the mosquito complement-like system [thioester-containing protein 1 (TEP1), leucine-rich repeat protein 1, and Anopheles Plasmodium-responsive leucine-rich repeat protein 1] prevented melanization of 7G8 parasites, reverting the refractory phenotype. In contrast, it had no effect on the intensity of infection with NF54, suggesting that this line is able to evade TEP1-mediated lysis. When R females were coinfected with a line that is melanized (7G8) and a line that survives (3D7), the coinfection resulted in mixed infections with both live and encapsulated parasites on individual midguts. This finding shows that survival of individual parasites is parasite-specific and not systemic in nature, because parasites can evade TEP1-mediated lysis even when other parasites are melanized in the same midgut. When females from an extensive genetic cross between R and susceptible A. gambiae (G3) mosquitoes were infected with P. berghei, encapsulation was strongly correlated with the TEP1-R1 allele. However, P. falciparum 7G8 parasites were no longer encapsulated by females from this cross, indicating that the TEP1-R1 allele is not sufficient to melanize this line. Evasion of the A. gambiae immune system by P. falciparum may be the result of parasite adaptation to sympatric mosquito vectors and may be an important factor driving malaria transmission.
ClouDedup: Secure Deduplication with Encrypted Data for Cloud Storage

With the continuous and exponential increase of the number of users and the size of their data, data deduplication becomes more and more a necessity for cloud storage providers. By storing a unique copy of duplicate data, cloud providers greatly reduce their storage and data transfer costs. The advantages of deduplication unfortunately come with a high cost in terms of new security and privacy challenges. We propose ClouDedup, a secure and efficient storage service which assures block-level deduplication and data confidentiality at the same time. Although based on convergent encryption, ClouDedup remains secure thanks to the definition of a component that implements an additional encryption operation and an access control mechanism. Furthermore, as the requirement for deduplication at block-level raises an issue with respect to key management, we suggest to include a new component in order to implement the key management for each block together with the actual deduplication operation. We show that the overhead introduced by these new components is minimal and does not impact the overall storage and computational costs.
Facial Recognition using Modified Local Binary Pattern and Random Forest

This paper presents an efficient algorithm for face recognition using the local binary pattern (LBP) and random forest (RF). The novelty of this research effort is that a modified local binary pattern (MLBP), which combines both the sign and magnitude features for the improvement of facial texture classification performance, is applied. Furthermore, RF is used to select the most important features from the extracted feature sequence. The performance of the proposed scheme is validated using a complex dataset, namely Craniofacial Longitudinal Morphological Face (MORPH) Album 1 dataset.
Level Set Based Hippocampus Segmentation in MR Images with Improved Initialization Using Region Growing

The hippocampus has been known as one of the most important structures referred to as Alzheimer's disease and other neurological disorders. However, segmentation of the hippocampus from MR images is still a challenging task due to its small size, complex shape, low contrast, and discontinuous boundaries. For the accurate and efficient detection of the hippocampus, a new image segmentation method based on adaptive region growing and level set algorithm is proposed. Firstly, adaptive region growing and morphological operations are performed in the target regions and its output is used for the initial contour of level set evolution method. Then, an improved edge-based level set method utilizing global Gaussian distributions with different means and variances is developed to implement the accurate segmentation. Finally, gradient descent method is adopted to get the minimization of the energy equation. As proved by experiment results, the proposed method can ideally extract the contours of the hippocampus that are very close to manual segmentation drawn by specialists.
Continuous User Verification Using Mouse Dynamics

This paper provides overview of the current methods of identifying users based on their interactions with a computer keyboard, mouse or a touchscreen and argues that in their current state of development none of them are capable of establishing the users identity within the time it takes for a user to input a password. The paper proposes the application of behavioral biometrics as a supplement to regular password based user authentication as a safeguard against unauthorized users gaining access to a computer that is already running an authenticated session e.g. unattended computers in offices.
Exploring the Patterns of Acupuncture on Mild Cognitive Impairment Patients Using Regional Homogeneity

Purpose To investigate the different responses to acupuncture in MCI patients and age-matched healthy subjects reflected by the Regional Homogeneity (ReHo) indices. Methods The experiment was performed at the acupoint KI3 in 12 MCI patients and 12 healthy controls, respectively. A novel non-repeated event-related (NRER) fMRI design paradigm was applied to separately detect neural activities related to different stages of acupuncture (pre-acupuncture resting state, needling manipulation and post-acupuncture resting state). ReHo values were calculated for MCI patients and healthy controls in pre- and post-acupuncture resting state. Then, a two-way ANCOVA with repeated measures with post-hoc two sample t-tests was performed to explore the different responses to acupuncture in the two groups. Results The ANCOVA revealed a significant main effect of group, but no significant main effect of acupuncture and interactions between group and acupuncture. During the pre-acupuncture resting state, ReHo values increased in the precentral gyrus (PCG), superior frontal gyrus (SFG), and insula (INS) and decreased mainly in middle temporal gyrus (MTG), parahippocampal (PHIP) and cingulate cortex in MCI patients compared with healthy controls. Furthermore, we found that the regions including precuneus (PCUN), and cingulate cortex showed increased ReHo values for MCI patients following acupuncture. For healthy controls, the medial frontal gyrus, PCG, anterior cingulate cortex (ACC) and INS showed enhanced ReHo values following acupuncture. During the post-acupuncture resting state, MCI patients showed increased ReHo values mainly in the MTG, superior parietal lobule (SPL), middle frontal gyrus (MFG), supramarginal (SMG), and PCG, and decreased ReHo values mainly in the frontal regions, PHIP, and posterior cingulated cortex (PCC) compared to healthy controls. Conclusion Though we found some ReHo changes between MCI patients and healthy controls, the two-way ANCOVA results showed no significant effects after multiple corrections. Further study is needed to reveal the real acupuncture effects on MCI patients.
The Art of Designing Socially Intelligent Agents: Science, Fiction, and the Human in the Loop

In this article, socially intelligent agents (SIAs) are understood to be agents that do not only from an observer point of view behave socially but that are able to recognize and identify other agents and establish and maintain relationships to other agents. The process of building SI As is influenced by what the human as the designer considers “social,” and conversely, agent tools that are behaving socially can influence human conceptions of sociality. A cognitive technology (CT) approach toward designing SIAs affords an opportunity to study the process of(1) how new forms of interactions and functionalities and use of technology can emerge at the human-tool interface, (2) how social agents can constrain their cognitive and social potential, and (3) how social agent technology and human (social) cognition can co-evolve and co-adapt and result in new forms of sociality. Agent-human interaction requires a cognitive fit between SI A technology and the human-in-the-loop as designer of, user of and participan.