Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Optimization Approach to Backup Network Design With Random Failures

This paper presents a scheme in which a dedicated backup network is designed to provide protection from random link failures. Upon a link failure in the primary network, traffic is rerouted through a preplanned path in the backup network. We introduce a novel approach for dealing with random link failures, in which probabilistic survivability guarantees are provided to limit capacity over provisioning. We show that the optimal backup routing strategy in this respect depends on the reliability of the primary network. Specifically, as primary links become less likely to fail, the optimal backup networks employ more resource sharing among backup paths. We apply results from the field of robust optimization to formulate an ILP for the design and capacity provisioning of these backup networks. We then propose a simulated annealing heuristic to solve this problem for large-scale networks and present simulation results that verify our analysis and approach.
Distributed Greedy Approximation to Maximum Weighted Independent Set for Scheduling With Fading Channels

It has been known that scheduling algorithms designed to achieve throughput optimality and good delay performance often require solving the Maximum Weighted Independent Set (MWIS) problem. However, under most realistic network settings, the MWIS problem is known to be NP-hard. In non-fading environments, low-complexity scheduling algorithms have been provided that converge either to the MWIS solution in time or to a solution that achieves at least a provable fraction of the achievable throughput. However, in more practical systems the channel conditions can vary at faster time-scales than convergence occurs in these lower-complexity algorithms. Hence, these algorithms cannot take advantage of opportunistic gains, and may no longer result in achieving good performance. In this paper, we propose a low-complexity scheduling scheme that performs provably well under fading channels and is amenable to implement in a distributed manner. To the best of our knowledge, this is the first scheduling scheme under fading environments that requires only local information, has a low complexity that grows logarithmically with the network size (provided that the conflict graph has bounded maximum vertex degree), and achieves provable performance guarantees (arbitrarily close to that of the well-known centralized Greedy Maximal Scheduler). We verify that the throughput and the delay of our proposed scheme are close to those of the optimal MaxWeight that solves MWIS at each time. Further, we implement our algorithm in a testbed by modifying the existing IEEE 802.11 DCF. The experiment results show that our implementation successfully accounts for wireless fading, attains the short-term opportunistic gains in practice, and hence substantially outperforms IEEE 802.11 DCF.
Trading Rules on Stock Markets Using Genetic Network Programming with Candle Chart

A new evolutionary method named "Genetic Network Programming, GNP" has been proposed. GNP represents its solutions as directed graph structures which have some useful features inherently. For example, GNP has the implicit memory function which memorizes the past action sequences of agents, and GNP can re-use nodes repeatedly in the network flow, so very compact graph structures can be made. In this paper, the stock trading model using GNP with Candle Chart is proposed and its effectiveness is comfirmed by trading simulations.
SLEEP-WAKE , ASPECTS OF MEMORY AND MELATONIN IN WILLIAMS-BEUREN SYNDROME : A

(1) Universidade Estadual Paulista-Unesp, Marília, São Paulo, Brasil. Source of help: Coordination of Improvement of Higher Education Personnel (CAPES) Conflict of interest: non-existent swelling periorbital, anteverted nostrils, long nose filter and thick lips. In addition, these individuals also have short stature, cardiovascular and connective tissue abnormalities 3. The behavioral phenotype presents personality and a cognitive profile unique in addition to different degrees of intellectual disability. A striking feature of this syndrome is the seemingly preservation of social and language functioning called Cocktail Party Speech ( CPS ) for his sociability, intention to interact, report of personal experiences to unknown people, speech fluent and intelligible using stereotyped phrases and cliches. This apparent social and communicative skills contrasts with the poor global and visuospatial cognitive performance of these individuals. In addition, more detailed studies showed problems in receptive, semantic and  INTRODUCTION
REPRESENTATIVE , EFFICACIOUS , AND REVOCABLE DATA ACCESS CONTROL FOR MULTI-AUTHORITY CLOUD STORAGE

Cloud Computing is one of the most prominent technology. It offers a service known as cloud storage which provides data outsourcing. Data access control is a way that ensures security in the cloud. However the cloud servers are un trusted which affects data access control. However, it is difficult to directly apply existing CP-ABE schemes to data access control for cloud storage systems because of the attribute revocation problem. In this paper, we design a Representative, Efficacious, and Revocable Data Access Control for Multi-Authority Cloud Storage, where there are multiple authorities co-exists and each authority is able to issue attributes independently. Ciphertext Policy Attribute-based Encryption (CP-ABE) scheme is used to propose revocable multi-authority method for access control. The attribute revocation method in this proposed work achieves both backward and forward security. Keywords— Cloud Computing, Cp-abe, Cloud Storage, Multi-authority, data access control
An automated approach to extract domain ontology for an e-learning system

The main aim of the proposed work is to design an automated approach to extract domain ontology from the e-learning resources. The domain ontology derived is embedded into the e-learning system so that the learners can be provided with more relevant and meaningful learning materials based on their knowledge levels. The advantage of the proposed approach is the concept map extraction that is effectively achieved through the use of association rule mining algorithm and fuzzy techniques. Experimentations were carried out to prove the efficiency in constructing the domain ontology and the performance is analysed with the previous approach. Simulation experiments were carried out to implement the automated domain ontology to the adaptive e-learning system.
Conditional Cash Transfers and Crime: Higher Income but also Better Loot

We quantify the effect of conditional cash transfer programs on crime. We find a positive correlation between welfare payments in cash significantly and criminal activities. We exploit the exogenous increase in the payment and the number of beneficiaries given by a major reformulation of the CCT program in Uruguay. The increase in crime is exclusively observed in property crime suggesting the impact is driven by economic reasons. Our findings suggest that an increase in cash available on the streets improves the loot from crime and thus increases the incentive for illegal activities.
Stability Analysis of a Wing in Ground Effect Craft

Analysis of dynamic stability is practically very important where the critical condition might occur during take-off of a Wing in Ground (WIG) craft. The change of hull resistance from the water to the air can make a sudden reduction in resistance. It is also strongly influenced by the pressure on the lower wing boundary layer which becomes greater due to air pressure reflections from the ground or water surface to the wings. The change of the pressure and resistance influenced the stability of the WIG significantly. In this research, dynamic stability of WIG craft during cruise and time domain analysis during take-off are conducted to study the WIG performance. A mathematical model was developed in time-domain (incorporating heave, pitch and surge motions) with varying parameters to analyze the WIG responses at the critical situation during take-off.
Real-World Evidence from the Integrative Medicine Primary Care Trial (IMPACT): Assessing Patient-Reported Outcomes at Baseline and 12-Month Follow-Up

Purpose The University of Arizona Integrative Health Center (UAIHC) was an innovative membership-supported integrative medicine (IM) adult primary care clinic in Phoenix, Arizona. UAIHC delivered healthcare using an integrative medicine model that combined conventional and complementary medical treatments, including nutrition, mind-body medicine, acupuncture, manual medicine, health coaching, educational classes, and groups. Results from pre-post evaluation of patient-reported outcomes on several standardized measures are presented here. Methods UAIHC patients completed surveys at baseline and after 12 months of continuous integrative primary care. Patients reported on perceived changes in health outcomes as measured by Short-Form Health Survey (SF-12 general, mental, and physical health), Perceived Stress Scale (PSS4), Work Productivity and Activity Impairment Questionnaire (WPAI), World Health Organization Well-Being Index (WHO-5), Pain Visual Analog Scale (VAS), Fatigue Severity Scale (VAS; FSS), Generalized Anxiety Disorder Scale (GAD2), Patient Health Questionnaire for depression (PHQ2), Pittsburgh Sleep Quality Index (PSQI) global rating of sleep quality, and the Behavioral Risk Factor Surveillance System (BRFSS; nutrition, exercise, and physical activity). Overall differences between time points were assessed for statistical significance. Patient demographics are also described. Results 177 patients completed baseline and follow-up outcome measures. Patients were predominantly white, female, college-educated, and employed. Baseline to one-year follow-up results indicate statistically significant improvements (p <.05) on all but perceived stress (PSS-4) and work absenteeism (WPAI). Clinical impact and/or practical effects are reported as percent change or standardized effect sizes whenever possible. Other demographic and descriptive information is summarized. Conclusions Following one year of IM primary care at UAIHC, patient-reported outcomes indicated positive impacts in several areas of patients' lives: mental, physical, and overall health; work productivity; sleep quality; pain; fatigue; overall well-being; and physical activity.
CONTINUITY OF DEVELOPER RANKING AND GROWTH CHANGE PREDICTION

Enormous amounts of raw content and information exist universally and large databases contain unordered, ungraded and unranked data. Ranking is most famous, ubiquitous and comprehensive techniques to build hierarchy of unordered group of items by calculating rank of every item based on one or several multiple attributes values. This technique allows analyzing and evaluating product performance with other products. Widespread usage of ranking technique represents relationship among several groups of well known items. In this analysis paper, We retrieve promising information from Git repository and demonstrate important fact of developers working individually or in a group and rank the developers based on core activities and contribution on several projects, bug resolving processes, source code commit and expertise in multiple languages by mining Git (a version control repository system). We discover key developers, influential software practitioner, projects and programming languages. We found developers grow over time in diverse areas. Our result shows developer ranking can assists project manager to take better quality decision to assign projects and gain help from expertise developer to support newly joined team members in the organization. Ranked developer can assists business to improve source code quality, timely delivery of projects, lower maintenance cost and better customer satisfaction. Keyword software practitioners, ranking, developers, Language-Language, commits ----------------------------------------------------------------------***--------------------------------------------------------------------
Safety Assurance for Operating Procedures – a formal methods approach

Automation is changing the way that many safety critical systems are operated, by changing the nature of the tasks operators perform. In such cases operating procedures need to be redesigned to find a balance between ensuring the operator performs the tasks that the machine requires, while allowing operators the flexibility they require. But how do system designers ensure that human errors are adequately mitigated? Safety standards dictate the degree of rigour that needs to be applied in assurance of software and hardware, but say little about design and verification of operating procedures. This paper proposes a rigorous qualitative approach to safety evaluation of operating procedures, illustrated on a new Air Traffic Management (ATM) function. Formal models of human-computer and human-human interaction were developed using Behavior Trees, and hazard analysis was performed using automated model checking. Because of the highly interleaved, concurrent nature of the operators’ tasks, it was necessary to develop a new way of categorising human error modes and system hazards. Model checking showed that the operating procedures prevented or mitigated errors in many cases, and revealed potential accident sequences in the other cases, thereby effectively validating informal hazard analysis results. The talk will also illustrate use of the safety assurance approach to derive requirements for a modification to the human-computer interface.
Towards efficient data analysis and management of semi-structured data

Over the last decade, there has been an enormous growth in both the amount and the complexity of online content that is collected and processed by humans and machines. Such a growth has spurred interest in flexible and fluid (semi-structured) data models that do not constrain the data to follow a fixed schema. Many applications ranging from bioinformatics to XML repositories, from software engineering to computational linguistics, are now generating and processing large amounts of semi-structured data. For these applications to reach their full potential, we need to build an effective set of tools to index, process, manage, and analyze such data. This dissertation focuses on a specific class of semi-structured data that is denoted using hierarchical tree objects. We specifically address the following questions pertaining to mining and managing tree-structured data: How can we provide quick access mechanisms to large semi-structured data stores? How can we discover hidden structural patterns from such data collections? How can we devise strategies to realize performance that is commensurate with modern computer architectures? In the context of managing tree-structured data, first, we develop an indexing mechanism that extracts discriminant features from the database and indexes them using a simple tunable inverted structure. Such an index is complemented with an efficient holistic query processing technique that retrieves the matches by operating entirely on space-efficient sequential representation of trees. Second, we propose a framework that enables the development of application-specific hash functions that convert variable-sized graph and tree structured data into fixed-sized hash values. We demonstrate the usability of this framework by developing a hash-based distributed data placement service for semi-structured data. We argue that this service is capable of supporting large scale data management and data mining algorithms. In the context of mining tree databases, first, we explore the role of succinct sequential data structures for efficiently discovering frequent tree patterns. Second, we propose a \memory-conscious design" wherein the algorithms trade memory for redundant computations to improve the memory system performance. Third, we consider the case of deploying data mining workloads on modern multicore systems. Here, we demonstrate that the bandwidth to main memory becomes a precious shared commodity as one increases the number of cores present in the system. We present mechanisms to alleviate the bandwidth pressure and show their effectiveness. Fourth, we explore an adaptive task and data parallel algorithm design that facilitates effective parallelization in the presence of data and workload skew. This algorithm is integrated into a general purpose scheduling service that supports the development of adaptive and moldable algorithms for database and mining tasks. Finally, we develop a hash-based distributed data placement service that can support the development of large scale distributed data mining and data management applications.
Synchronized GMTI radar collection management in a coalition environment

Surveillance of ground targets from airborne systems is increasingly of interest in tactical operations. Collection management synchronization can provide improved tactical data products for multi-platform operations. Synchronization of collection management is considered for coalition operations involving multiple airborne GMTI radar systems. An emerging synchronization collection management planning capability is evaluated for application to surveillance using GMTI radar systems. Several examples are provided which illustrate the capability and benefits of synchronized collection management.
Regional influence on the occurrence of road slipperiness during winter precipitation events

There is a severe risk of road icing and slipperiness when rain or sleet falls on a frozen road surface. Traffic can be severely affected, with a higher frequency of road accidents. These conditions usually occur during warm frontal passages when cold weather and low road surface temperatures are replaced by warmer air and precipitation. Two case studies from southern Sweden show the spatial and temporal distribution of rain or sleet on a frozen road surface. The influence of regional‐scale characteristics is demonstrated. Air temperature governs the spatial distribution when temperatures around −10°C precede the event. Weather stations in an open environment experience slippery conditions first. If temperatures are just below zero before the front arrives, road surface temperature becomes the crucial factor. Weather stations in locations screened by forest or road cuts are the first to register this event. The methodology presented in this paper can be used to increase knowledge of the spatial and temporal patterns of road slipperiness in an area. As a result, forecasts and maintenance activities can be improved and there is a better understanding of the relationship between synoptic events and road slipperiness. Copyright © 2001 Royal Meteorological Society
Identifying packet droppers in sensor networks via report analysis

vii CHAPTER 1. OVERVIEW . 1 1.1 Motivation and contribution . 1 1.2 Organization of this thesis . 2 CHAPTER 2. REVIEW OF LITERATURE . 3 CHAPTER 3. METHODS AND PROCEDURES . 5 3.1 Preliminaries . 5 3.1.1 Network model . 5 3.1.2 Security assumptions and attack model . 5 3.2 Proposed scheme . 6 3.2. 1 Information of tree topology . 7 3.2. 2 Packet encryption and decryption . 7 3.2. 3 Monitoring report transmission and analysis . 10 3.3 Catching packet droppers and modifiers in wireless sensor networks . 23 CHAPTER 4. RESULTS . 35 4.1 Impact of network density on failed-detection rate . 35 4.2 Impact of natural dropping rate and mis-overhearing on failed-detection rate . 35 4.3 Impact of percentage of droppers on failed-detection rate . 37 4.4 Impact of detection rounds on failed-detection rate . 37
Regulating Water Quality Impacts of Port and Harbor Stormwater Runoff1

The waters of ports and harbors are subject to a variety of potential pollutant sources including boat and ship antifoulants, boat hull cleaning, and other releases and discharges from boats, wastewater discharges from municipalities and industrial facilities, stormwater runoff from municipal, industrial (including shipyards) and agricultural activities, groundwater and the atmosphere. These sources of potential pollutants can degrade the water quality-beneficial uses of the waters through causing aquatic life toxicity and excessive food web bioaccumulation, as well as causing other impairments of the waterbody’s beneficial uses. For some ports and harbors municipal stormwater runoff is one of the most important, if not the most important, sources of a variety of potential pollutants in the water column and waterbody sediments. There is considerable confusion and unreliability in regulating stormwater runoff water quality impacts. Typical US EPA water quality criteria and state water quality standards tend to overregulate stormwater runoff-associated constituents for which there are water quality criteria/standards. There is underregulation of potential pollutants for which there are no criteria/standards. The regulation of potential pollutants that accumulate in sediments is even more unreliable since there is no relationship between the total concentration of a constituent in sediments and water quality impacts. This paper discusses the problems in current regulatory approaches for urban stormwater runoff water quality impacts and recommends regulatory approaches that will provide for technically valid, cost-effective regulation of stormwater runoff-associated pollutants. These include the development of “wet weather” water quality standards for regulating water column impacts. For sediments a non-numeric Best Professional Judgment Weight of Evidence Triad approach implemented through an expert panel in a public peer review process should be used. The triad is to be based on aquatic life toxicity, sources of chemicals that bioaccumulate to excessive levels in the higher trophic food web, benthic organism assemblages, and appropriate chemical evaluation of the cause of toxicity (TIEs).
THE NATURE OF THE GAP BETWEEN THE INTENDED AND THE IMPLEMENTED ORDINARY LEVEL MATHEMATICS CURRICULUM: A CASE STUDY OF MASHONALAND CENTRAL DISTRICT

An information- and technology based society requires individuals who are able to think critically about complex issues, analyze and adapt to new situations, solve problems of various kinds and communicate their thinking effectively. To learn mathematics in a way that is beneficial to students in their lives, there is need to have classroom experiences that help them develop mathematical understanding, develop skills, procedures and habits, develop the ability to apply mathematics and acquire a positive attitude towards mathematics. The study sought to establish the nature of the gap between the intended and the implemented mathematics at ordinary level in Zimbabwean Secondary Schools. As is typical of ethnography, the focus of the study was mainly on teaching methods, the “O” level intended mathematics curriculum interpretation as well as issues surrounding assessment and classroom discourse in the teaching and learning of “O” level mathematics. A sample of fifteen qualified teachers purposively and randomly selected from sixty qualified mathematics teachers in Mashonaland province was used. A mixed research paradigm was employed and data was collected through document analysis, focus group discussionsand lesson observations. However, the curriculum expectations of the “O” level mathematics curriculum do not seem to be reflected in practice in a classroom situation. Measures cited for the successful implementation of the curriculum is through in service training programs, workshops and launching a resource centre.