Miracle-dz/UniFAR-FTUs huggingface dataset:
The Bare Necessities for Doing Undergraduate Multivariable Calculus

Students in two mathematics streams at Concordia University start their programs on similar footing in terms of pre-requisite courses; their paths soon split in the two directions set by the Pure and Applied Mathematics (MATH) courses and the Major in Mathematics and Statistics (MAST) courses. In particular, likely during their first year of studies, the students set out to take a two-term arrangement of Multivariable Calculus in the form of MAST 218 – 219 and MATH 264 – 265, respectively. There is an ongoing discussion about the distinction between the MAST and MATH courses, and how it is justified. This thesis seeks to address the matter by identifying the mathematics that is essential for students to learn in order to succeed in each of these courses. We apply the Anthropological Theory of the Didactic (ATD) in order to model the knowledge to be taught and to be learned in MAST 218 and MATH 264, as decreed by the curricular documents and course assessments. The ATD describes units of mathematical knowledge in terms of a practical block (tasks to be done and techniques to accomplish them) and a theoretical block that frames and justifies the practical block. We use these notions to model the knowledge to be taught and learned in each course and reflect on the implications of the inclusion and exclusion of certain units of knowledge in the minimal core of what students need to learn. Based on these models, we infer that the learning of Multivariable Calculus in both courses follows in a tradition observed in single-variable calculus courses, whereby students develop compartmentalized units of knowledge. That is, we find that it is necessary for students in MAST 218 and MATH 264 to specialize in techniques that apply to certain routine tasks, and to this end, it suffices to learn bits and pieces of theoretical knowledge that are not unified in a mathematically-informed way. We briefly consider potential implications of such learning in the wider context of the MATH and MAST programs.
Forwarding and Routing Stateless Multi-Hop Protocol for Wireless Sensor Networks

—Energy conservation can be achieved by the use of clustering routing protocols in Wireless Sensor Networks (WSN). They have a great impact on the system lifetime. In these WSNs, the concepts of communication between Cluster Head (CH) nodes and Base Station (BS), data aggregation and round can be approached in a different way. This paper studies a cluster-based multi-hop routing protocol. The proposed approach introduces a progressive data aggregation, and a sequential data request during a round. Simulation results show that the new Forwarding and Routing Stateless Multi-Hop (FRSM) protocol extends network lifetime (improved by 50%) and lowers energy consumption. The comparison with an existing cluster-based protocol shows better performances.
Framework for Traffic Congestion Prediction

Traffic Congestion is a complex dilemma facing most major cities. It has undergone a lot of research since the early 80s in an attempt to predict traffic in the short-term. Recently, Intelligent Transportation Systems (ITS) became an integral part of traffic research which helped in modeling and forecasting traffic conditions. In this paper, two frameworks for traffic congestion prediction are proposed. The first framework is based on NeuroFuzzy model which is well surveyed in traffic literature. The second framework is based on Hidden Markov Models (HMM) which is rarely used in traffic prediction. The methods are used to define traffic congestion during morning rush hours. The results of the two methods are compared.
PAPER Special Section on Cryptography and Information Security Evaluation of the Security of RC6 against the χ 2 -Attack ∗∗

SUMMARY Knudsen and Meier applied the χ 2-attack to RC6. The χ 2-attack recovers a key by using high correlations measured by χ 2-value. Up to the present, the success probability of any χ 2-attack has not been evaluated theoretically without using experimental results. In this paper, we discuss the success probability of χ 2-attack and give the theorem that evaluates the success probability without using any experimental result, for the first time. We make sure the accuracy of our theorem by demonstrating it on both 4-round RC6 without post-whitening and 4-round RC6-8. We also evaluate the security of RC6 theoretically and show that a variant of the χ 2-attack is faster than an exhaustive key search for the 192-bit-key and 256-bit-key RC6 with up to 16 rounds. As a result, we succeed in answering such an open question that a variant of the χ 2-attack can be used to attack RC6 with 16 or more rounds.
Formants of Speech for Biometric Identification System

In hands free security system, speech is the widely used bio-feature. Extracted formant frequencies of human speech are utilized for the identification of a person. In this study, a prototype system was developed and tested. The advantage of the system is that it can be used without the knowledge of the end users. The system was developed in four modules. In the first module the speech samples are recorded. The formant frequencies are extracted from the the speech samples and recorded in a knowledge base in the second module. The autoregressive (AR) models are built in the third module. The testing is carried out in the fourth module. The influence of the envelop threshold and orders of AR model is examined to identify the optimum performance of the system.
A Complete Automatic Test Set Generator for Embedded Reactive Systems: From AUTSEG V1 to AUTSEG V2

One of the biggest challenges in hardware and software design is to ensure that a system is error-free. Small defects in reactive embedded systems can have disastrous and costly consequences for a project. Preventing such errors by identifying the most probable cases of erratic system behavior is quite challenging. Indeed, tests performed in industry are non-exhaustive, while state space analysis using formal verification in scientific research is inappropriate for large complex systems. We present in this context a new approach for generating exhaustive test sets that combines the underlying principles of the industrial testing technique with the academic-based formal verification. Our method consists in building a generic model of the system under test according to the synchronous approach. The goal is to identify the optimal preconditions for restricting the state space of the model such that test generation can take place on significant subspaces only. So, all the possible test sets are generated from the extracted subspace preconditions. Our approach exhibits a simpler and efficient quasi-flattening algorithm compared with existing techniques, and a useful compiled internal description to check security properties while minimizing the state space combinatorial explosion problem. It also provides a symbolic processing technique for numeric data that provides an expressive and concrete test of the system, while improving system verification (Determinism, Death sequences) and identifying all possible test cases. We have implemented our approach on a tool called AUTSEG V2. This testing tool is an extension of the first version AUTSEG V1 to integrate data manipulations. We present in this paper a complete description of our automatic testing approach including all features presented in AUTSEG V1 and AUTSEG V2.
A User-Centric CPU-GPU Governing Framework for 3-D Mobile Games

Graphics-intensive mobile games place different and varying levels of demand on the associated central processing units (CPUs) and graphics processing units (GPUs). In contrast to the workload variability that characterizes games, the current design of the energy governor employed by mobile systems appears to be outdated. In this paper, we review the energy-saving mechanism implemented in an Android system coupled with graphics-intensive gaming workloads from three perspectives: 1) user perception; 2) application status; and 3) the interplay between the CPU and GPU. We observe that there are information gaps in the current system, which may result in unnecessary energy wastage. To resolve the problem, we propose an online user-centric CPU-GPU governing framework. To bridge the identified information gaps, we classify rendered game frames into redundant/changing frames to satisfy user demand, categorize an application into GPU sensitive/insensitive phases to understand the application’s demand, and determine the frequency scaling intents of the CPU and GPU to capture processor demand. In response to the measured demand, we employ a required workload estimator, a unified policy selector, and a frequency-scaling intent communicator in the framework to save energy. The proposed framework was implemented on an LG Nexus 5X smartphone, and extensive experiments with real-world 3-D gaming applications were conducted. According to the experiment results, for an application which is low interactive and infrequent phase changing, the proposed framework can, respectively, reduce energy consumption by 25.3% and 39% compared with our previous work and Android governors while maintaining user experience.
ADAPTIVE 4D PSI-BASED CHANGE DETECTION

Abstract. In a previous work, we proposed a PSI-based 4D change detection to detect disappearing and emerging PS points (3D) along with their occurrence dates (1D). Such change points are usually caused by anthropic events, e.g., building constructions in cities. This method first divides an entire SAR image stack into several subsets by a set of break dates. The PS points, which are selected based on their temporal coherences before or after a break date, are regarded as change candidates. Change points are then extracted from these candidates according to their change indices, which are modelled from their temporal coherences of divided image subsets. Finally, we check the evolution of the change indices for each change point to detect the break date that this change occurred. The experiment validated both feasibility and applicability of our method. However, two questions still remain. First, selection of temporal coherence threshold associates with a trade-off between quality and quantity of PS points. This selection is also crucial for the amount of change points in a more complex way. Second, heuristic selection of change index thresholds brings vulnerability and causes loss of change points. In this study, we adapt our approach to identify change points based on statistical characteristics of change indices rather than thresholding. The experiment validates this adaptive approach and shows increase of change points compared with the old version. In addition, we also explore and discuss optimal selection of temporal coherence threshold.
Linked Information Visualization for Linked Open Government Data. A Visual Synthetics Approach to Governmental Data and Knowledge Collections

Open government data initiatives provide citizens with access to the information that governments have about their countries (such as data about people, resources, infrastructure, or services) upon which they act. Information visualizations can help to make sense of these complex data and knowledge collections, but are mostly used to shed light on subselections of data only, without coordinated efforts to connect them to bigger pictures up to now. In analogy to linked data initiatives, this article discusses methods and strategies to link information visualizations in the government data realm and thereby to connect widely available local pictures and insights into more coherent global mental models. We expect related developments to provide benefits for communication professions like civic education and political journalism, and to open up enhanced methods for cross-domain exploration and reasoning for (linked) open government data. Thus linked information visualizations aim for supporting students, readers, and citizens to meet a widening range of macro-cognitive challenges, which complex societies are facing in increasing amounts.
Computer Programs for Investigation of Intercellular Communication using Double Whole Cell Voltage Clamp

The set of programs (Microsoft Windows and DOS applications) for investigation of electrical intercellular communication using Double Whole Cell Voltage Clamp method consists of programs for experiment flow control and specialized signal analysis. Various data export possibilities via Windows Clipboard are the new features of programs. Signal data or measurement results' export to popular universal data processing programs (Ex. Microsoft Excel, Sigma Plot, etc.) allow to use all conventional data analysis methods and to realize the new analysis ideas rising in everyday's work. Export of signal pictures in various graphical formats allows to use popular graphic design programs (Microsoft Power Point, Corel Draw, etc.) for presentation of investigation results. Experiment flow control program allows to substitute an oscilloscope and pulse generator by computer and make an automatic experiment flow control. Additional utility programs allow to do a comfortable data management and documentation.
Balancing Efficiency and Equality in Vehicle Licenses Allocation

Due to traffic and air quality concerns in urban cities, many big cities have begun to adopt the vehicle licenses quantitative control policies. In these cities, a limited number of vehicle licenses are allocated among a very large number of potential car buyers every one or two months. The current allocation mechanisms differ from city to city. Several mechanisms have been developed and implemented in reality, such as auction, lottery, lottery with reserved price, and the simultaneous auction and lottery. In this work, we target to design the optimal mechanism to balance efficiency and equality in practice. We first propose a unified two-group mechanism framework that either includes or outperforms all the existing mechanisms. Besides, the unified framework also leads to easy implementation in reality due to its truthfulness and simple structure. Under this framework, assuming the players' private values are drawn independently from a common distribution, we prove the optimal mechanism is always sequential auction and lottery. Besides, the optimal allocation rule depends only on the total number of players and the total number of licenses for all commonly used distributions. We then extend the two-group framework to a general multi-group framework. The experimental results show us the optimal two-group mechanism is the best choice in practice. Thus, our work provides an effective tool for social planner to design truthful mechanisms to maximize the social efficiency under any equality level. We also discuss possible applications of our result to resource allocation in other settings.
THE EFFECT OF CONSTRAINT BASED MULTI-MODAL VIRTUAL ASSEMBLY ON STUDENT’S LEARNING

In this article we propose Virtual Reality Training System (VRTS), a computer generated environment for assembly. VRTS provides training to students to assemble a three phase step down transformer on one hand and renders multimodal information about objects that enhances students’ theoretical knowledge on the other hand. The system is cost effective, does not need complex set up and its implementation in real educational environments is easy. Low cost ARToolkit markers are utilized to have real time interaction. The analysis reveals that mean learning of students who got training in VRTS students is 81.5% as compared to 35.75% of those who did not get training in VRTS. Similarly experimental results show that students who used VRTS are more confident in performing the same task in real world as compared to students who did not received training through VRTS.
DNASynth: a software application to optimization of artificial gene synthesis

DNASynth is a client-server software application in which the client runs in a web browser. The aim of this program is to support and optimize process of artificial gene synthesizing using Ligase Chain Reaction. Thanks to LCR it is possible to obtain DNA strand coding defined by user peptide. The DNA sequence is calculated by optimization algorithm that consider optimal codon usage, minimal energy of secondary structures and minimal number of required LCR. Additionally absence of sequences characteristic for defined by user set of restriction enzymes is guaranteed. The presented software was tested on synthetic and real data.
An assessment of middle grades preservice teachers' mathematics knowledge for teaching

An Assessment of Middle Grades Preservice Teachers’ Mathematics Knowledge for Teaching. (August 2006) Margaret Joan Mohr, B.S.Ed., Pittsburg State University; M.S., Pittsburg State University Chair of Advisory Committee: Dr. Gerald O. Kulm The overall purpose of this concurrent mixed methods study was to develop an online performance assessment using content questions taken from a reputable seventh and eighth grade standardized assessment that effectively evaluated and allowed preservice middle grades mathematics teachers to demonstrate their mathematics knowledge for teaching in the four main content strands of algebra, probability and statistics, geometry, and number and operations. In addition, this study examined differences in mathematics knowledge for teaching in enrollment characteristics, in courses taken and currently taking, and in three different cohorts, each at different stages in the program, of 122 preservice middle grades mathematics teachers at a large public university in central Texas. Constant comparative analysis and descriptive statistics revealed average scores on the seventh and eighth grade content questions. The middle grades preservice teachers’ content understanding and pedagogical understanding responses indicated several misunderstandings and misinterpretations in the middle grades mathematics they were tested on. Content knowledge, content understanding, and pedagogical understanding together made up a preservice teacher’s mathematics knowledge for teaching. The study
A Bayesian framework for inverse problems for quantitative biology

In this thesis, we present a Bayesian framework to solve inverse problems in the context of quantitative biology. We present a novel combination of the Bayesian approach to inverse problems, suitable for infinite-dimensional problems, with a parallel, scalable Markov Chain Monte Carlo algorithm to approximate the posterior distribution. Both the Bayesian framework and the parallelised MCMC were already known but they were not used in this context in the past. Our approach puts together existing results in order to provide a tool to easily solve inverse problems. We focus on models given by partial differential equations. Our methodology differs from previous results in its approach: it aims to be as transparent and independent of the model as possible, in order to make it flexible and applicable to a wide range of problems emerging from experimental and physical sciences. We illustrate our methodology with three of such applications in the areas of theoretical biology and cell biology. The first application deals with parameter and function identification within a Turing pattern formation model. To the best of our knowledge, our results are the first attempt to use Bayesian techniques to study the inverse problem for Turing patterns. In this example, we show how our implementation can deal with both finite- and infinite-dimensional parameters in the context of inverse problems for partial differential equations. The second example studies the spatio-temporal dynamics in cell biology. The study provides an example that seeks to best-fit a mathematical model to experimental data finding in the process optimal parameters and credible regimes and regions. We present a new derivation of the model, that corrects the short-comings of previous approaches. We provide all the details from techniques for data acquisition to the parameter identification, and we show in particular how the mathematical model can be used as a proxy to estimate parameters that are difficult to measure in the experiments, providing an novel alternative to more indirect estimates that also require more complex experiments. Finally, our third example illustrates the flexibility of our implementation of the methodology by using it to study traction force microscopy (TFM) data with a solver implemented independent of the Bayesian approach for parameter identification. We limit ourselves to the classical TFM setting, that we model as a two-dimensional linear elasticity problem. The results and methods generalise to more complex settings where quantitative modelling driven by biological observations is a requirement.
On the Static Accuracy of Charge-Discharge Units Intended for Electrical Tests of High Capacity Li-ion Batteries

Performing of the cycle testing according to the principles of Dynamic Stress Test can significantly reduce the overall time of development and production of batteries, which in turn allows reducing the cost of designing and testing of the spacecraft power systems. Performing of Dynamic Stress Test require special charge-discharge units that allows to perform a full cycle of electrical tests of batteries, including cyclic testing. Providing the required accuracy of measurement and stabilization of certain attributes of Li-ion battery operating modes is one of the problems that arise during thedevelopment of such charge-discharge units. The following attributes are of particular interest: charge and discharge currents, discharge powers, battery voltages. Analysis of the charge-discharge unit as a control system allows evaluating the steady-state stabilization error of the required attributes of the developed device. Moreover, using a digital integrator in the control system of the charge-discharge unit allows providing specified values of steady-state stabilization error of required attributes in different test modes.
Recommendation with Implicit Trust Relationship Based on Users’ Similarity

Recommendation algorithms based on trust relationship have been shown with a great influence. Many existing algorithms only consider the trust relationship. But in the real world, most users have few trustworthy person can be added to the trust list, they do not know or unacquainted each other. So, the implicit trust relationship is valuable by inferring more trust relationships. This paper proposes a new method to mine the implicit trust relationship based on the users’ similarity. The proposed methods combine the trust-based recommendation algorithms and show the effectiveness in the FilmTrust data set.
Automated system for fingerprint authentication using pores and ridge structure

A novel technique for automated fingerprint authentication is presented which utilizes pore information extracted from live scanned images. The position of the pores on the fingerprint ridges is known to provide information that is unique to an individual and is sufficient for use in identification. By combining the use of ridge and pore features, we have developed a unique multilevel verification/identification technique that possesses advantages over systems employing ridge information only. An optical/electronic sensor capable of providing a high resolution fingerprint image is required for extraction of pertinent pore information, which makes it unlikely that electronically scanned inked fingerprints would contain adequate pore data that is sufficient, or consistent enough, for use in authentication. The feasibility of this technique has been demonstrated by a working system that was designed to provide secure access to a computer. Low false reject and zero false accept error rates have been observed based on initial testing of the prototype verification system.