Miracle-dz/UniFAR-FTUs huggingface dataset:
THE ISLAMIC UNIVERSITY FACULTY OF INFORMATION TECHNOLOGY DEPARTMENT OF COMPUTER SCIENCE GAZA - PALESTINE

In large datasets, identifying exception or rare case/cases with respect to a group of similar cases is to be considered very significant problem. The traditional problem (Outlier Mining) is to find exception or rare cases in a dataset irrespective of the class label of these cases, they are considered rare event with respect to the whole dataset. In this research, we discuss the problem that is Class Outliers Mining and a method to find out those outliers. The general framework of this problem is “given a set of observations with class labels, find those that arouse suspicions, taking into account the class labels”. We introduce a novel definition of Class Outlier, and propose the Class Outlier Factor (COF) which measures the degree of being a Class Outlier of a data object. Out work includes a proposal of a new efficient algorithm towards mining of the Class Outliers, presenting experimental results applied on various domains of real world datasets and finally a comparison study with other related methods is performed. Class Outliers Mining: Distance-Based Approach. 3 TO The Memory of My Father:
Modulation analysis for outdoors applications of optical wireless communications

For optical wireless communication systems, the most frequently used system is intensity modulated direct detection (IM/DD). We analyze the modulation schemes that could be used in an outdoor environment. We keep our concern on the direct detection method. We discuss uncoded on-off keying (OOK) (proposed for its simplicity), pulse position modulation (PPM) (proposed for its power efficiency) and digital pulse interval modulation (DPIM). We compare OOK with the PPM and DPIM schemes for power and bandwidth efficiency. DPIM offers higher transmission capacity compared to OOK/PPM, and that can be employed to improve either the bandwidth efficiency or power efficiency of the system. It is very suitable for outdoors applications.
O. Dmitriev et al. Development of Ways of Increasing the Reliability of the Integrated Complex of Satellite and Inneration Navigation Systems

Purpose: is an analysis of methods and models for ensuring the functions of controlling the integrity of the GNSS and functional diagnostics of the INS in flight conditions, as well as developing an algorithm for monitoring the integrity of the GNSS and controlling the correct functioning of it. Methods: methods of the theory of optimal estimation, the theory of probability and the theory of random processes.Results: The analysis of factors influencing the quality of autonomous monitoring of the integrity of the satellite radionavigation system and analysis of possible ways to increase reliability and integrity were carried out. An algorithm for monitoring the integrity of the GNSS and controlling the correct functioning of the INS has been developed.Discussion: Based on the results of the study it is proposed to develop mathematical complex, which allows to conduct a complete cycle of simulation of the algorithm at a given stage of flight of the aircraft using existing groupings of spacecraft, as well as experimental navigation data of the GNSS and the INS, registered during the flights.
CS 7140 : Advanced Machine Learning Lecture 11 : Latent Dirichlet Allocation

Latent Dirichlet Allocation (LDA) is a probabilistic model for characterizing discrete data. It was initially developed in a paper by David Blei, et. al. (2003) [1] as a method of performing latent topic analysis on text corpora. The goal of latent topic analysis is to discover groups of documents that exist in a collection of discrete data that share certain latent characteristics. In the context of text characterization, these groups represent textual topics, e.g. sports, statistics, politics, etc. There are several variants of principal components analysis (PCA) that have been applied to the problem (categorical PCA, exponential PCA, multinomial PCA). Additionally, there are a number of methods for this analysis represented in the information retrieval literature, and one such method, called Latent Semantic Indexing (LSI), and a probabilistic extension (probabilistic LSI) are the logical predecessors of LDA [2] [3]. The key difference between LDA and its predecessor, pLSI, is that LDA adds Dirichlet priors to the model. In the following, we will describe this model in detail and derive methods for inferring the model parameters.
N A ] 7 J an 2 01 5 Multigrid Methods for Space Fractional Partial Differential Equations ∗

We propose some multigrid methods for solving the algebraic systems resulting from finite element approximations of space fractional partial differential equations (SFPDEs). It is shown that our multigrid methods are optimal, which means the convergence rates of the methods are independent of the mesh size and mesh level. Moreover, our theoretical analysis and convergence results do not require regularity assumptions of the model problems. Numerical results are given to support our theoretical findings.
SECURE DATA SHARING USING VISUAL CRYPTOGRAPHY

The Secure Data Sharing Using Visual Cryptography Scheme is a kind of secret sharing scheme that fixates on sharing secret data. The fundamental conception of the visual cryptography scheme is to split a secret data into number of desultory shares which discretely reveals no information about the secret data other than the size of the secret data. The AES algorithm used for secret key . The secret data can be reconstructed by stacking the portions. In the multimedia steganocryptic system, the message will first be encrypted utilizing public key encryption algorithm, and then this encrypted data will be obnubilated into an image file thus accomplishing both data encoding and obnubilating. The multimedia data will be acclimated to provide the cover for the information. Visual steganography is one of the most secure forms of steganography available today. It is most commonly implemented in image files. In this application concept of visual cryptography is the legal distribution of multimedia contents with copyright protection whilst preserving the privacy of user, whose identities are only revealed in case of illegal re-distribution. This application to apply sharing of single secrete data and multiple secrete data on ebony and white as well as on colour images but withal a comparative analysis on visual cryptography schemes is with all performed.
Research and practice of dynamic network security architecture for IaaS platforms

Network security requirements based on virtual network technologies in IaaS platforms and corresponding solutions were reviewed. A dynamic network security architecture was proposed, which was built on the technologies of software defined networking, Virtual Machine (VM) traffic redirection, network policy unified management, software defined isolation networks, vulnerability scanning, and software updates. The proposed architecture was able to obtain the capacity for detection and access control for VM traffic by redirecting it to configurable security appliances, and ensured the effectiveness of network policies in the total life cycle of the VM by configuring the policies to the right place at the appropriate time, according to the impacts of VM state transitions. The virtual isolation domains for tenants' VMs could be built flexibly based on VLAN policies or Netfilter/Iptables firewall appliances, and vulnerability scanning as a service and software update as a service were both provided as security supports. Through cooperation with IDS appliances and automatic alarm mechanisms, the proposed architecture could dynamically mitigate a wide range of network-based attacks. The experimental results demonstrate the effectiveness of the proposed architecture.
Chapter 4 Imaging of Hypoxia in Retinal Vascular Disease

Retinal tissue hypoxia is a key mediator in the pathogenesis of many leading causes of irreversible vision loss, including diabetic retinopathy. Retinal hypoxia in diabetic retinopathy has been shown to drive the production of pro-inflammatory cytokines and pro-angiogenic growth factors. Together, these factors contribute to disease progression by causing unregulated growth of new blood vessels, increased vascular permeability and cell death within the retina. Studies have shown that retinal hypoxia precedes many of the pathologic events that occur during the progression of diabetic retinopathy such as angiopathy, microaneurysms, and capillary dropout. Therefore, early detection of hypoxia in the retinas of diabetic patients could help clinicians identify problems in patients before irreversible damage has occurred. Currently, oxygen sensitive electrodes remain the gold standard for direct measurement of oxygen tension within the retinal tissue; however the procedure is highly invasive and is therefore limited in its applicability towards preclinical models. Less invasive techniques such as retinal oximetry, phosphorescence-lifetime imaging, and hypoxia-sensitive fluorescent probes have shown promising diagnostic value in facilitating detection of oxygen imbalance correlated with neurovascular dysfunction in DR patients. This review highlights the current progress and potential of these minimally invasive hypoxia-imaging techniques in diabetic retinopathy.
2 . 2 People-Space-Technology : An Ethnographic Approach

CyberParks aims at advancing knowledge on the relationship between information and communication technologies and the socially sustainable production and usage of public open spaces. Such research necessitates a solid methodological base. Urban ethnography brings together a number of perspectives and approaches to deal with cultural and social aspects of urban life, and as such it is able to provide an integrated methodological framework for the study of technology-public space relationship. The ethnographic approach means, by definition, an in-depth, micro-scale look at the phenomena under concern. However, the technological dimension makes the relationship between people and space more complex. This is not simply because an additional layer of analysis is added; it comes as a result of the emergence of multiple connections between the real and the virtual. From an ethnographic perspective, this requires the researcher to capture, explore and understand the cyber-social phenomena and dynamics in a multifaceted, hybrid, triangulated and crossreferenced way. This makes ethnographic research much more complicated but more interesting as well. The current chapter attempts to outline such an analytical framework to guide empirical research on the issues. This framework draws on the public space literature and adds the technological dimension brought in by the CyberParks project. We argue that this enriches the ethnographic approach providing a more integrated framework for the analysis of the relationship between people, space and technology.
Analogical Integration of Semantic Roles with Vector Symbolic Architectures

Semantic roles describe “who did what to whom” and as such are central to analogy processing and other cognitive processes. For analogy processing, roles are usually specific to each predicate: for loves there is a LOVER and a BELOVED, for eats an EATER and an EATEN, etc. Language modeling, on the other hand, requires more general roles like AGENT and PATIENT in order to relate form to meaning in a parsimonious way. This paper presents a new model of semantic roles that addresses this dichotomy. The model uses a distributed representation scheme called Vector Symbolic Architectures (VSA) for representing roles and their fillers. Starting with specific roles, the model learns to generalize roles through exposure to language data, through a process that is itself analogical. The learning mechanism is simple and efficient, and its scaling properties are well-understood. The model is able to learn and exploit new representations without losing the information from existing ones. The contribution of the model to the study of analogy is thus twofold: it shows how representations needed for analogy processing can be accommodated within a more general theory of semantic roles, and suggests how important analogy may be to language learning. We present experimental data illustrating these principles, and conclude by discussing some implications for the relation between analogical processing and language.
Fickle Consumers versus Random Technology : Explaining Domestic and International Comovements

Viewing technology shocks as the primary source of business cycles has resulted in many \puzzles" or counter-factual predictions of general equilibrium theory with respect to international movements of output, consumption, investment, employment, and net exports (Backus, Kehoe and Kydland, JPE 1992). There are few puzzles, however, when aggregate demand rather than aggregate supply is the source of uncertainty. In particular, the stylized openeconomy business cycle regularities are what standard general equilibrium theory predicts once the usual suspect ̄ckle consumers is held responsible for the business cycle. The ̄nding that preference shocks explain both domestic and international business cycles suggests the possibility of a uni ̄ed explanation of the business cycle and the seasonal cycle, as both types of °uctuations share a common source: recurrent shifts in preferences. ¤This paper is a substantially revised version of my working paper entitled \Demand-Driven Business Cycles: Explaining Domestic and International Comovements. " (Cornell University, 2001). I am grateful to Assaf Razin and an anonymous referee for helpful comments and to Tarek Coury for research assistance.
Statistical Errors

Reproduced with permission from Orbit and Constellation Design and Management [Wertz, 2009], Appendix C. This appendix is an analytic introduction to error analysis. The flow of topics is summarized in Fig. Gweb-1. Section 6.3 provides an introduction to error analysis and a general recipe for adding errors in an error budget. The process of creating an error budget is introduced and discussed in detail with tables of error sources in Sec. 6.3. Chapter 8 provides an introduction to spacecraft position and attitude measurements. Specifically, Sec. 7.2 in OCDM by Wertz [2009] provides a detailed assessment of the evaluation of measurement uncertainty on the celestial sphere and Sec. 7.6 in OCDM describes good and bad measurement sets (in terms of uncertainty) and a set of practical tests to determine them.
Reconstructing Obfuscated Human Faces

This paper examines the usage of convolutional neural networks to reconstructed obfuscated images of human faces. Prior work has been done in the field of superresolution, but this paper will explore the gap using highly obfuscated faces. The input to our algorithm is an obfuscated image of a person’s face. We use a convolutional neural network to output a reconstructed image of the person’s face. This is be applied to the Labeled Faces in the Wild data set using two types of obfuscation techniques on faces: pixelation and Gaussian blurs. Results will be measured using the PSNR and SSIM metrics. We explore the effect of loss functions of the model by examining pixel loss and perceptual loss functions and showing how perceptual loss is preferable to pixel loss. We also explore the capability of the model to reconstruct faces from highly obfuscated images. Our experiments show that this model can produce recognizable faces from seemingly unrecognizable inputs.
A Framework for Privacy-Preserving Access Control Mechanism in Relational Data

Access control Mechanisms are security features that control how users and systems communicate and interact with other systems and resources. Access control mechanisms give organization the ability to control, restrict, monitor, and protect resource availability, integrity and confidentiality. Privacy Protection Mechanism (PPM) uses suppression and generalization of relational data to anonymize and satisfy privacy needs. The access control policies define selection predicates available to roles while the privacy requirement is to satisfy the k-anonymity or l-diversity. Imprecision bound constraint is assigned for each selection predicate. Essentially analysis within the data processing or information mining with sub space of information security is loosely classified into access management analysis and data privacy analysis. Each plays vital role in information security thence we've integrated these methodologies to boost our security on relative information. Mistreatment privacy protective mechanism we will generalize and suppress our relative information to anonymize and satisfy privacy needs against identity and attribute speech act. In this paper we implement a Privacy Protection Mechanism for protecting sensitive information from unauthorized users.
Chapters ILR Collection 1999 Engineering Bureaucracy : The Genesis of Formal Policies , Positions , and Structures in High-Technology Firms

Excerpt] This article examines the impact of organizational founding conditions on several facets of bureaucratization—managerial intensity, the proliferation of specialized managerial and administrative roles, and formalization of employment relations. Analyzing information on a sample of technology start-ups in California's Silicon Valley, we characterize the organizational models or blueprints espoused by founders in creating new enterprises. We find that those models and the social composition of the labor force at the time of founding had enduring effects on growth in managerial intensity (i.e., reliance on managerial and administrative specialists) over time. Our analyses thus provide compelling evidence of path dependence in the evolution of bureaucracy—even in a context in which firms face intense selection pressures—and underscore the importance of the "logics of organizing" that founders bring to new enterprises. We find less evidence that founding models exert persistent effects on the formalization of employment relations or on the proliferation of specialized senior management titles. Rather, consistent with neo-institutional perspectives on organizations, those superficial facets of bureaucracy appear to be shaped by the need to satisfy external gatekeepers (venture capitalists and the constituents of public corporations), as well as by exigencies of organizational scale, growth, and aging. We discuss some implications of these results for efforts to understand the varieties, determinants, and consequences of bureaucracy.
Measuring Cost Avoidance Through Software Reuse A model to measure costs avoided through software reuse and guidelines to increase profits through software reuse

Context. Software Reuse is considered as silver-bullet for software development. However, measuring benefits of software reuse is difficult and cumbersome task because of varying number of factors involved in it. Different reuse cost models already exist in literature which measure various different attributes of software reuse. Mainly these models are used for calculating return over investment or cost-benefit analysis. Objectives.We have investigated that very few cost economic models have been proposed for measuring costs avoidance,degree of empirical validation, assumptions, types of artifacts they can measure and whether they provide guidelines on collection of metrics for measuring reuse benefits. Methods.In this research, a systematic review was conducted. Based on the results of systematic review, a model was proposed which can measure cost avoided by reuse of every kind of artifact. In a systematic all major article sources were used. Studies were selected after reading titles and abstracts. Three cost avoidance models were found and an analysis of these models was performed. Based on the analysis, a new model was proposed to fill the gap left by these studies. Results. New model measures every kind of reuse artifact and provides guidelines on how and what to measure in order to calculate reuse benefits. This model was then validated in the industry and technology was transferred to the industry for future usage. Guidelines for improved savings were developed. Conclusions. We conclude that many models are related to each other and use similar techniques to measure the cost avoidance however they can not measure all kinds of reuse artifacts. New model performed well in industry. However, we found that the new model should accommodate maintenance costs since these are major savings by software reuse. Moreover, we conclude that there is a need for further validation of guidelines and model in industry.
Generating New Space-Filling Test Instances for Continuous Black-Box Optimization

This article presents a method to generate diverse and challenging new test instances for continuous black-box optimization. Each instance is represented as a feature vector of exploratory landscape analysis measures. By projecting the features into a two-dimensional instance space, the location of existing test instances can be visualized, and their similarities and differences revealed. New instances are generated through genetic programming which evolves functions with controllable characteristics. Convergence to selected target points in the instance space is used to drive the evolutionary process, such that the new instances span the entire space more comprehensively. We demonstrate the method by generating two-dimensional functions to visualize its success, and ten-dimensional functions to test its scalability. We show that the method can recreate existing test functions when target points are co-located with existing functions, and can generate new functions with entirely different characteristics when target points are located in empty regions of the instance space. Moreover, we test the effectiveness of three state-of-the-art algorithms on the new set of instances. The results demonstrate that the new set is not only more diverse than a well-known benchmark set, but also more challenging for the tested algorithms. Hence, the method opens up a new avenue for developing test instances with controllable characteristics, necessary to expose the strengths and weaknesses of algorithms, and drive algorithm development.
DNA Sequence Variations Contribute to Variability in Fitness and Trainability.

Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA IO N S Genetic differences contribute to human variability in exercise-related traits. In this commentary, the focus is on endurance exercise performance and cardiorespiratory fitness (CRF). The evidence pertaining to other relevant traits (e.g., muscle strength) will not be considered. Three main topics are addressed to provide a brief summary of our current knowledge base.
Imaging and analysis of genetically encoded calcium indicators linking neural circuits and behaviors

Confirming the direct link between neural circuit activity and animal behavior has been a principal aim of neuroscience. The genetically encoded calcium indicator (GECI), which binds to calcium ions and emits fluorescence visualizing intracellular calcium concentration, enables detection of in vivo neuronal firing activity. Various GECIs have been developed and can be chosen for diverse purposes. These GECI-based signals can be acquired by several tools including two-photon microscopy and microendoscopy for precise or wide imaging at cellular to synaptic levels. In addition, the images from GECI signals can be analyzed with open source codes including constrained non-negative matrix factorization for endoscopy data (CNMF_E) and miniscope 1-photon-based calcium imaging signal extraction pipeline (MIN1PIPE), and considering parameters of the imaged brain regions (e.g., diameter or shape of soma or the resolution of recorded images), the real-time activity of each cell can be acquired and linked with animal behaviors. As a result, GECI signal analysis can be a powerful tool for revealing the functions of neuronal circuits related to specific behaviors.