Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithm for ﬁnding optimal paths in a public transit network with real-time data

Recently, transit agencies have been opening up their route conﬁguration and schedule data to the public, as well as providing online APIs (Application Programming Interfaces) to real-time bus positions and arrival estimates. Based on this infrastructure of providing transit data over the internet, we developed an algorithm to calculate the travel times of K-shortest paths in a public transportation network where all wait and travel times are only known at real-time. Although there is a large body of work in routing algorithms in transit networks, we take cues from an algorithm to ﬁnd shortest paths in road networks, called Transit Node routing. Our approach is based on a simple observation intuitively used by humans: when you take transit, you will look for a particular set of transfer points that connect transit routes that lead from the origin and destination. We precompute a lookup table of feasible paths between the origin stop of every bus route to the terminus of every other bus route using the transfer points. This precomputation of paths signiﬁcantly reduces the computation time and number of real-time arrival requests to transit agency servers, the bottleneck in computing this problem. The computational complexity of the algorithm is linear in real-time and implementation results show that queries from a webserver are returned in 3 seconds in the worst-case.
An Application of Simulated Annealing to Maze Routing

The simulated annealing optimisation technique is used to provide a framework for controlling ripup and rerouting transformations within an implementation of Lee‘s routing algorithm. The performance of the optimised router is compared with a more traditional implementation of Lee’s algorithm. The results show a significant improvement in completion rate obtained by the optimised router. In addition, the versatility of the optimised router is confirmed by the diverse nature of the experimental data.
Cmsc 858k — Advanced Topics in Cryptography Lecture 27

In a previous lecture, we defined the Byzantine agreement/broadcast problems and showed that there is no protocol solving these problems when the fraction of corrupted players is 1/3 or larger. Today, we prove the converse by showing a protocol for broadcast (and hence Byzantine agreement; cf. the previous lecture) when the fraction of corrupted players is less than 1/3. The protocol we will show is called the Exponential Information Gathering (EIG) protocol, and was essentially the first known protocol for this task (see [2, 4, 1, 3]). We stress at the outset that the protocol is not very efficient — as the name suggests, its complexity is exponential in the number of players — but it forms an important feasibility result. Since the protocol was introduced, much work has focused on improving various parameters of the protocol, and fully polynomial Byzantine agreement/broadcast protocols with optimal resilience are now known.
Maximum Likelihood of Evolutionary Trees is Hard ∗

Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees (Felsenstein, 1981). Finding optimal ML trees appears to be a very hard computational task, but for tractable cases, ML is the method of choice. In particular, algorithms and heuristics for ML take longer to run than algorithms and heuristics for the second major character based criterion, maximum parsimony (MP). However, while MP has been known to be NP-complete for over 20 years (Day, Johnson and Sankoff, 1986), reduction from vertex cover), such a hardness result for ML has so far eluded researchers in the field. An important work by Tuffley and Steel (1997) proves quantitative relations between the parsimony values of given sequences and the corresponding log likelihood values. However, a direct application of it would only give an exponential time reduction from MP to ML. Another step in this direction has recently been made by Addario-Berry et al. (2004), who proved that ancestral maximum likelihood (AML) is NP-complete. AML “lies in between” the two problems, having some properties of MP and some properties of ML. Still, the AML proof is not directly applicable to the ML problem. We resolve the question, showing that “regular” ML on phylogenetic trees is indeed intractable. Our reduction follows those for MP and AML, but its starting point is an approximation version of vertex cover, known as gap vc. The crux of our work is not the reduction, but its correctness proof. The proof goes through a series of tree modifications, while controlling the likelihood losses at each step, using the bounds of Tuffley and Steel. The proof can be viewed as correlating the value of any ML solution to an arbitrarily close approximation to vertex cover.
Food Detection Using Histogram of Oriented Gradient (HOG) as Feature Extraction and K-Nearest Neighbors (K-NN) as Classifier

Food Recognition was an interesting thing to do in computer visualization research . Food had different shapes and colors to be recognized by the senses from human’s eye. The computer recognized the image with analog values were converted it to digital value in matrix form. The research conducted aims to create non-manual payment machines. Thus creating an automatic cash register that calculated the price and name of food from an image of food ordered on a tray. The method was used a Histogram of Oriented Gradient (HOG) could be used to find valued feature extraction from an image. HOG method combined with K-Nearest Neighbors (K-NN) classificationed for designing food detection systems. That the dataset used for testing was an image taken from a webcam. An image containing food in one tray was there three types of food placed on a plate. If food was taken, the system issued the name of food on the picture. The best HOG parameter obtained was bin = 8, Pixel peer Cell = 2x2, Cell per Block = 2x2. The optimal one the k value used was 3. The simulation result has accuracy 82%.
Web Semantics : Science , Services and Agents on the World Wide Web

Simple Knowledge Organization System (SKOS) provides a data model and vocabulary for expressing Knowledge Organization Systems (KOSs) such as thesauri and classification schemes in Semantic Web applications. This paper presents the main components of SKOS and their formal expression in Web Ontology Language (OWL), providing an extensive account of the design decisions taken by the Semantic WebDeployment (SWD)WorkingGroup of theWorldWideWebConsortium (W3C),which between2006 and 2009 brought SKOS to the status of W3C Recommendation. The paper explains key design principles such as ‘‘minimal ontological commitment’’ and systematically cites the requirements and issues that influenced the design of SKOS components. By reconstructing the discussion around alternative features and design options and presenting the rationale for design decisions, the paper aims at providing insight into how SKOS turned out as it did, and why. Assuming that SKOS, like any other successful technology, may eventually be subject to revision and improvement, the critical account offered here may help future editors approach such a task with deeper understanding. © 2013 The Authors. Published by Elsevier B.V. All rights reserved.
Short-term load forecasting based on big data technologies

With the construction of smart grid, lots of renewable energy resources such as wind and solar are deployed in power system. It might make the power system load varied complex than before which will bring difficulties in short-term load forecasting area. To overcome this issue, this paper proposes a new short-term load forecasting framework based on big data technologies. First, a cluster analysis is performed to classify daily load patterns for individual loads using smart meter data. Next, an association analysis is used to determine critical influential factors. This is followed by the application of a decision tree to establish classification rules. Then, appropriate forecasting models are chosen for different load patterns. Finally, the forecasted total system load is obtained through an aggregation of an individual load’s forecasting results. Case studies using real load data show that the proposed new framework can guarantee the accuracy of short-term load forecasting within required limits.
A Real Time Driver Drowsiness Detection System

Driving with drowsiness is one of the main causes of traffic accidents. Driver fatigue is a significant factor in a large number of vehicle accidents. The development of technologies for detecting or preventing drowsiness at the wheel is a major challenge in the field of accident avoidance systems. Due to the hazard that drowsiness presents on the road, methods need to be developed for counteracting its affects. This paper describes a real-time non-intrusive method for detecting drowsiness of driver. It uses webcam to acquire video images of the driver. Visual features like mouth & eyes which are typically characterizing the drowsiness of the driver are extracted with the help of image processing techniques to detect drowsiness. A study about the performance of this proposal & some results are presented.
Verifying Determinism in Sequential Programs

A nondeterministic program is difficult to test and debug. Nondeterminism occurs even in sequential programs: for example, iterating over the elements of a hash table can result in diverging test results. We have created a type system that can express whether a computation is deterministic, nondeterministic, or ordernondeterministic (like a set). While state-of-the-art nondeterminism detection tools unsoundly rely on observing run-time output, our approach soundly verifies determinism at compile time. Our implementation found previously-unknown nondeterminism errors in a 24,000 line program that had been heavily vetted by its developers.
Stereo matching using neighboring system constructed with MST

Stereo matching is a hot topic in computer vision, while stereo matching in large textureless regions and slanted planes are still challenging problems. We propose a novel stereo matching algorithm to handle the problems. We novelly utilizes minimum spanning tree (MST) to construct a new superpixel-based neighboring system. The neighboring system is used to improve the matching performance in textureless regions. Then we apply the new neighboring system to the stereo matching problem, which uses the superpixel as the matching primitive. The use of the new neighboring system is efficient and effective. We compare our method with 4 popular methods. Experiments on Middlebury dataset show that our method can achieve good matching results. Especially, our method obtains more accurate disparity in textureless regions while maintaining a comparable performance of matching in slanted planes.
A Data Mining Approach to Validating Drill Hole Logging Data in Pilbara Iron Ore Exploration

Logging of exploration drillholes is a routine practice and its accuracy is essential for resource evaluation and planning in the minerals industry. Logged compositions record a set of material types with standardized mineralogy and texture characteristics. The material types logged may vary due to diversities in mineralization and geology, but also due to subjective biases and human error, leading to significant challenges for the industry. Thus, there is a need to validate the field logging whereby the material types and their percentages are adjusted to reconcile with laboratory assay values, while retaining the physical characteristics and geological context. We introduce the Auto-Validation Assistant (AVA) algorithm that applies data mining methods to geologists’ validation patterns recorded in a training process over hundreds of intervals of iron ore exploration drillholes. The AVA modifies the material types selected in the logged composition and their percentages according to geological rules learned in the training process, and proposes to the geologist a number of validated compositions with optimized geochemistry and mineralogical hardness, while also considering visible properties such as chip shape and color. Using the confidence value provided with each validated composition, the geologist can make informed validation decisions and remains in control of the validation process, while harnessing computational power. Experiments were conducted to evaluate the auto-validated compositions generated by AVA: one to analyze the acceptance rate of the AVA generated compositions by geologists for 1,996 intervals in drillholes from different sites; and the other to compare manual and AVA-validated compositions using 14,600 drillholes from one entire deposit. The results showed the acceptance rate of AVA-validated compositions (without further change) of 74.3%, leading to significant time savings over tedious manual validation, while demonstrating that AVA provides comparable but more consistent results. The algorithm is fast and repeatable and can be adapted to different material types and training datasets, with potential applications beyond iron ore exploration.
Gross Domes � c Product Government Spending Investment Consump � on Export Consumer Price Index Unemployment Rate Price Level

We present a framework for constructing a specific type of knowledge graph, a concept map from textbooks. Using Wikipedia, we derive prerequisite relations among these concepts. A traditional approach for concept map extraction consists of two sub-problems: key concept extraction and concept relationship identification. Previous work for the most part had considered these two sub-problems independently. We propose a framework that jointly optimizes these sub-problems and investigates methods that identify concept relationships. Experiments on concept maps that are manually extracted in six educational areas (computer networks, macroeconomics, precalculus, databases, physics, and geometry) show that our model outperforms supervised learning baselines that solve the two sub-problems separately. Moreover, we observe that incorporating textbook information helps with concept map extraction.
The African Journal of Information Systems The

This paper presents one of the first comprehensive analyses of Nigeria’s future readiness and attractiveness as a potential destination for IT-enabled services offshoring. The paper examines existing literature on IT services offshoring to Africa, and presents results from in-depth evaluation of seven important location selection criteria. The study indicates that while Nigeria appears to be making progress in many areas, the country is neither yet ready nor attractive as an offshoring destination. Nevertheless, the analysis suggests that Nigeria might already be on the path to attaining readiness in the future. However, significant hurdles will need to be surmounted if Nigeria is to become fully attractive for offshoring. The study further reinforces beliefs that Nigeria has the potential to take its own share of the global offshoring market, and concludes that bringing IT services to Nigeria is all about seeking opportunities while muddling through manageable risks.
A Distributed Maximal Link Scheduler for Multi Tx/Rx Wireless Mesh Networks

The capacity of Wireless Mesh Networks (WMNs) has significantly increased with the recent addition of multiple transmit (Tx) and receive (Rx) (MTR) capability or smart antennas. This increase however is predicated on an effective link scheduler. The aim of any scheduler is to derive a superframe comprising the smallest number of slots that affords each link one or more transmission opportunities. In particular, the scheduler is required to solve an instance of the NP-complete, MAX-CUT problem, in each time slot. To this end, there are a number of centralized schedulers, but only a handful of distributed schedulers. However, each of these distributed schedulers has its own drawbacks; either they do not guarantee maximal activated links or do not guarantee all links are activated. Henceforth, in this paper, we add to the state-of-the-art by proposing a novel distributed scheduler, called Algo-d, which approximates the MAX-CUT problem in a distributed manner using only local information. In fact, this is the first distributed solution for MAX-CUT problem. Through theoretical analysis and simulation, we show that Algo-d achieves the following performance: 1) Algo-d schedules on average 12% fewer and 46.5% more links in each time slot than two centralized algorithms, and 2) Algo-d schedules 28% more links than ROMA and 270% more links than JazzyMAC; both state-of-the-art distributed schedulers for MTR WMNs.
Computer-Based Cognitive Retraining for Individuals with Chronic Acquired Brain Injury : A Pilot Study

Objective: The purpose of this study was to evaluate the effectiveness of a computerbased cognitive retraining program, the Parrot Software, on improving cognitive deficits in memory and attention in individuals with a chronic acquired brain injury (ABI). Research Design: This study utilized a quantitative quasi-experimental one-group pretest-posttest design. Participants: Eleven adults over 18 years of age who sustained a chronic ABI two or more years prior to participation in the study and demonstrated deficits in memory and attention were included. Only individuals with ABI due to traumatic brain injury, hemorrhagic cerebrovascular accident, or ischemic cerebrovascular accident were included. Method and Procedures: The study was conducted over a period of five months, during which participants completed a total of eight 60-minute sessions using the Parrot Software. The participants completed eight sub-programs in memory and attention. Pretest and posttest data were collected using the paper version of the Cognistat Assessment (2009). In order to control for bias and create inter-rater reliability, each researcher was trained in administering the standardized Cognistat Assessment (2009) and the Parrot software, and participated in the process of data collection and analysis. Results: A significant improvement was found in both memory and attention scores postintervention. No significant correlations were found between memory or attention changes and age, years since injury, and education level. Conclusion: Computer-based cognitive retraining programs, such as the Parrot Software, may be effective in improving cognitive deficits in memory and attention in individuals
Rapid Changes in Land‐Sea Thermal Contrast Across China's Coastal Zone in a Warming Climate

Coastal areas are important sites of environmental and socioeconomic activities and are significantly influenced by climate change. Here we analyzed the current and future responses of spatiotemporal characteristics of land‐sea thermal contrast (LSTC) along China's coastal zone to global warming. Using the European Centre for Medium‐Range Weather Forecasts Re‐Analysis (ERA)‐Interim and 18 Coupled Model Intercomparison Project 5 models, we find that the rate of global warming significantly influenced the LSTC in summer. The LSTC first decreased and then increased during the warming and hiatus periods, respectively. In winter, the LSTC decreased in the Bohai Sea coastal zone, Yellow Sea‐East China Sea coastal zone, and South China Sea coastal zone at rates of 0.46 (p < 0.01), 0.18 (p < 0.01), and 0.19 °C/decade, respectively. Spatially, the LSTC decreased in summer and winter with the decrease in latitude and increased in summer and winter with the decrease in longitude. These changes were caused by urbanization, land use changes, and topography. The spatial distribution was more strongly controlled by land than by sea. Meanwhile, the land/sea warming ratio was concentrated within the range of 0–1 and 1–2, and land/sea temperature variation trends commonly followed the same direction. Overall, land/sea surface temperature variations had similar amplitudes. Under three Representative Concentration Pathways (RCPs), the warming rate difference between land and sea in summer is small, but the land warms faster than the sea in winter, resulting in the LSTC decreasing fast in winter. Under RCP4.5 and RCP8.5, the linear trends in LSTC in Bohai Sea coastal zone, Yellow Sea‐East China Sea coastal zone, and South China Sea coastal zone ranged from 0.05 to 0.08 (p < 0.01) and 0.13 to 0.15 °C/decade (p < 0.01), respectively.
Investigation of the impact of land use management scenarios on diffuse source nutrients in the River Axe catchment

I ACKNOWLEDGEMENTS . II TABLE OF CONTENTS . III LIST OF TABLES.V LIST OF FIGURES.VIII LIST OF APPENDICES . XII LIST OF SYMBOLS . XIV ABBREVIATIONS AND ACRONYMS . XVIII
Stabilisation, modification, delivery and treatment of phospholipid based vesicles for applications in advanced wound management

This project focuses on the stabilisation, modification, delivery and treatment of phospholipid based vesicles for applications in advanced wound care, with a focus on paediatric burns. Vesicles, commonly referred to as liposomes or nanocapsules, are attractive drug delivery composites, due to their biocompatible properties. They have the ability to entrap active compounds within their core, which can be released at the point of use, (in vivo or ex vivo) either through passive diffusion, or in response to local environmental stimulus.
Shallow techniques for argument mining

Argument BLOCKINmining BLOCKINhas BLOCKINrecently BLOCKINemerged BLOCKINas BLOCKINa BLOCKINpromising BLOCKINfield BLOCKINat the frontiers of the argumentation and text mining communities. However, most techniques developed within that BLOCKINfield BLOCKINdo BLOCKINnot BLOCKINscale BLOCKINto BLOCKINlarger BLOCKINamounts BLOCKINof BLOCKINdata, BLOCKINdepriving BLOCKINus for example of valuable insights in large-scale discussion forums. On two social media datasets, we study different lightweight scalable text mining techniques used within the sentiment analysis community and their applicability to the argument BLOCKINmining BLOCKINproblem.
A Fine-grained Event-based Modem Power Model for Enabling In-depth Modem Energy Drain Analysis

Cellular modems enable ubiquitous Internet connectivities to modern smartphones, but in doing so they become a major contributor to the smartphone energy drain. Understanding modem energy drain requires a detailed power model. The prior art, an RRC-state based power model, was developed primarily to model the modem energy drain of application data transfer. As such, it serves well its original purpose, but is insufficient to study detailed modem behavior, e.g., activities in the control plane. In this paper, we propose a new methodology of modeling modem power draw behavior at the event-granularity, and develop to our knowledge the first fine-grained modem power model that captures the power draw of all LTE modem radio-on events in different RRC modes. Second, we quantitatively demonstrate the advantages of the new model over the state-based power model under a wide variety of context via controlled experiments. Finally, using our fine-grained modem power model, we perform the first detailed modem energy drain in-the-wild study involving 12 Nexus 6 phones under normal usage by 12 volunteers spanning a total of 348 days. Our study provides the first quantitative analysis of energy drain due to modem control activities in the wild and exposes their correlation with context such as location and user mobility.