Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximizing the Utility in Location-Based Mobile Advertising

Nowadays, the locations and contexts of users are easily accessed by mobile advertising brokers, and the brokers can send customers related location-based advertisement. In this paper, we consider a location-based advertising problem, namely maximum utility advertisement assignment (MUAA) problem, with the estimation of the interests of customers and the contexts of the vendors, we want to maximize the overall utility of ads by determining the ads sent to each customer subject to the constraints of the capacities of customers, the distance ranges and the budgets of vendors. We prove that the MUAA problem is NP-hard and intractable. Thus, we propose one offline approach, namely the reconciliation approach, which has an approximation ratio of (1-ε)⋅θ, where θ = min(a_1\n^c_1, a_2 n^c_2,., a_m n^c_m), and n^c_i is the larger value between the number of valid vendors and the capacity a_i of customer u_i. Experiments on real data sets confirm the efficiency and effectiveness of our proposed approach.
Intelligent Big Data Summarization for Rare Anomaly Detection

Identifying interesting patterns from a huge amount of data is a challenging task across a wide range of application domain. Especially, for cyber security being able to identify rare types of network activities or anomalies from network traffic data (a.k.a. Big Data! ) is an important but time-consuming data analysis task having moderate computing resources. Existing research has shown that it is possible to detect rare anomalies from the summarized version of big data. Therefore, summarization is an effective preprocessing function before applying anomaly detection techniques. This aim of this paper is to improve and quantify the scalability and accuracy of the anomaly detection techniques by using summarization. Hence, we propose a sampling-based summarization technique (SUCh: Summarization Using Chernoff-Bound) which is computationally effective than the existing techniques and also performs better in identifying rare anomalies from twelve benchmark network traffic datasets. The experimental results show that, instead of using original dataset, a summary of the data yields better performance in terms of true positive and false positive rates, when used for anomaly detection with less time required.
Minimizing Maximum Delay of Task Assignment in Spatial Crowdsourcing

Spatial crowdsourcing services, such as Uber and Grabhub, become popular recently. Task assignment plays an important role in offering high-quality services. However, most of the existing solutions for task assignment only focus on the entire performance of the platform and do not optimize the maximum assignment delay. As a result, they cannot handle some real world scenarios which require minimizing the maximum delay in task assignment. In this paper, we study the minimizing maximum delay spatial crowdsourcing (MMD-SC) problem and propose solutions aiming at achieving a worst case controlled task assignment. The MMD-SC problem assumes that both workers and requesters come dynamically and considers not only the workers' travel costs but also the buffering time of tasks, thus it is very challenging due to two-sided online setting. To address these challenges, in this work, we propose a space embedding based online random algorithm with a competitive ratio of O(log n) and two efficient heuristic algorithms, namely the threshold based greedy approach and the batch-based approach. In addition, we demonstrate the effectiveness and efficiency of our methods via extensive experiments on both synthetic and real datasets.
Extracting BTI-induced Degradation without Temporal Factors by Using BTI-Sensitive and BTI-Insensitive ring Oscillators

Measuring bias temperature instability (BTI) by ring oscillators (ROs) is frequently used. However, the performance of a semiconductor chip is fluctuated dynamically due to bias, temperature and etc. BTI-sensitive and -insensitive ROs are implemented in order to extract BTI-induced degradation without temporal fluctuation factors. A test chip including those ROs was fabricated in a 65 nm process. BTI-induced degradation without temporal fluctuation was successfully measured by subtracting results of BTI-insensitive ROs from those of BTI-sensitive ones. Performance degradation of NMOS and PMOS transistors mainly due to BTI increases along logarithmic and exponential functions, respectively.
Alternative Measurement Instrument to Evaluate Executive Functions in Children of All Scholar Range

Problems related to executive functions can be characterized as weaknesses in a set of mental skills that are key during the learning process. Child neuropsychologists are often asked to determine whether a child experiencing dificulties in the academic setting has a specific learning disability attentional deficit, memory impairment, or some combination of these problems. Typically, the diagnosis is carried out by using a set of standardized questionnaires, which are not friendly and put a lot of stress over the evaluated child. In this work is propose a measurement instrument using computational tools to evaluate the principal dimensions of the executive functions: viso-spatial work memory, phonological work memory, processing speed, inhibition control, planning and organization, and cognitive flexibility, in children of all scholar range (6 to 16 years old). Conclusive results have not be obtained yet, as this is the initial stage of development.
Native Storage Techniques for Data Management

In the present tutorial we perform a cross-cut analysis of database storage management from the perspective of modern storage technologies. We argue that neither the design of modern DBMS, nor the architecture of modern storage technologies are aligned with each other. Moreover, the majority of the systems rely on a complex multi-layer and compatibility-oriented storage stack. The result is needlessly suboptimal DBMS performance, inefficient utilization, or significant write amplification due to outdated abstractions and interfaces. In the present tutorial we focus on the concept of native storage, which is storage operated without intermediate abstraction layers over an open native storage interface and is directly controlled by the DBMS. We cover the following aspects of native storage: (i) architectural approaches and techniques; (ii) interfaces; (iii) storage abstractions; (iv) DBMS/system integration; (v) in-storage processing.
MPR — A Partitioning-Replication Framework for Multi-Processing kNN Search on Road Networks

We study the problem of executing road-network k-nearest-neighbor (\knn) search on multi-core machines. State-of-the-art kNN algorithms on road networks often involve elaborate index structures and complex computational logic. Moreover, most kNN algorithms are inherently sequential. These make the traditional approach of parallel programming very costly, laborious, and ineffective when they are applied to kNN algorithms. We propose the MPR (Multi-layer Partitioning-Replication) mechanism that orchestrates CPU cores and schedules kNN query and index update processes to run on the cores. The MPR mechanism performs workload analysis to determine the best arrangement of the cores with the objective of optimizing quality-of-service (QoS) measures, such as system throughput and query response time. We demonstrate the effectiveness of MPR by applying it to a number of state-of-the-art kNN indexing methods running on a multi-core machine. Our experiments show that multi-processing using our MPR approach requires minimal programming effort. It also leads to significant improvements in query response time and system throughput compared with other baseline parallelization methods.
Tracking Control and Differential Flatness of Quadrotor with Cable-suspended Load

A new approach to tracking control of a quadrotor with a cable-suspended load is presented in this paper. The highly coupled nonlinear dynamics of 8 degrees of freedom quadrotor-load system is decoupled into 2 subsystem: a quadrotor attitude control subsystem and a double points link subsystem. Based on Lagrange equation, dynamical model is obtained. This system is proved to be differentially flat with the load position and the quadrotor yaw serving as the flat outputs. According to the relationship between flatness and feedback linearization, the system is transformed into a linear closed-loop system by an endogenous dynamic feedback. Then, trajectory tracking is carried out in closed loop based on Hurwitz stability criterion. Simulation results demonstrate the effectiveness of the controller.
Estimating User Contexts from Mobile Application Usage Histories

While context information of a smartphone user such as his/her current location, the number of companions, mental conditions, and health conditions can be fundamental information towards smarter services, it is not easy to estimate these information with built in smartphone sensors. This paper develops a user context estimation model based on mobile application usage histories. As user application history and context are assumed to be time series data that change over time, a recurrent neural network was employed to learn temporal relationship between the history and context. The experimental results confirmed that the proposed model was effectively able to estimate user context from application usage history.
Optimal coordinated voltage control for power system voltage stability

An optimal coordinated voltage controller (OCVC) is developed based on the spirit of model predictive control (MPC) method. The OCVC consists of three components, namely a predictor, a control candidate pool, and a selector. It has been used in secondary voltage control (SVC) to coordinate dissimilar control actions at different geographical locations in order to maintain desired voltage profiles in a global sense in emergencies. A single-stage Euler state predictor (SESP) is utilized, based on the system model, to predict voltage performance under selected control actions; the selection of the optimum control action from the pool is a complex optimization problem that is achieved by a pseudogradient evolutionary programming (PGEP) technique. Simulation results on a six-bus benchmark system and the New England 10-generator-39-bus system are given to show the potential of this method for online usage.
Preliminary Questionnaire-Based Study on Using Behaviour Change to Increase Tourism to Toyama

Progress of information technology has enabled people to have more opportunities to diversify their interests and also led to an increase of tourists to various new locations. In this research, we study the possibility of using Persuasive Technology to increase the number of tourists with a focus on Toyama prefecture. We conducted a preliminary questionnaire for Japanese tourists, to explore their barriers for those who visit or would like to visit the area, the advantages of the location, and studied the possibilities of using behaviour change techniques derived from our initial analysis. Our focus was on Toyama prefecture, but we can extrapolate some suggestions to other regions as well. The analysis suggested that Toyama should appeal more to its often unknown attractive offerings, like hot springs and its unique features, while giving this information contextualized to users and routing the visitors to the destination based on the their home location. We also discuss with examples, the implications of using the persuasive system design (PSD) model, which has several system qualities we can take advantage of, such as primary task and dialogue support to create more persuasive features. Lastly, we present the limitations in our study.
Does Aging Change Foraging Behavior of Black-Tailed Gulls?

How do wild animals behave as they get older? We investigated the foraging behavior of black-tailed gulls (Larus crassirostris) of known age using GPS and acceleration loggers. We found that the older gulls reduced their mean flight speed and tended to feed on prey on land rather than on prey at sea. However, breeding performance of gulls did not change with age. Therefore, older gulls might experience senescence, but optimize their foraging behavior in relation to their age to maintain breeding performance.
Poster: Aiding Java Developers with Interactive Fault Localization in Eclipse IDE

Spectrum-Based ones are a popular class of Fault Localization (FL) methods among researchers due to their relative simplicity. However, recent studies highlighted some barriers to the wider adoption of the technique in practical settings. One possibility to increase the practical usefulness of related tools is to involve interactivity between the user and the core FL algorithm. In this setting, the developer interacts with the fault localization algorithm by giving feedback on the elements proposed by the algorithm. This way, the proposed elements can be influenced in the hope to reach the faulty element earlier (we call the proposed approach Interactive Fault Localization, or iFL). With this work, we present our recent achievements in this topic. In particular, we overview the basic approach, our preliminary experimentation with user simulation, and the supporting tool for the actual usage of the method, iFL for Eclipse. Our aim is to provide a basis for the investigation of the feasibility and effectiveness of the technique, before moving on to more comprehensive experiments with actual human subjects. We invite researchers for further discussion on the topic, and for that, the method and tool will be made accessible.
Reliability based PMU placement in a power system

PMUs are widely used to monitored the grid quantities over few decades all over the world. Grid information in the form of voltage magnitude, voltage angle, currents and frequency are collected by PMUs and send to control center for data record and its analysis. Many network components such as CTs, PTs, PMUs, PDCs, LAN, WAN, CPU etc plays an important role in database applications. Hence consideration of reliability of such components at planning stage needs to be acknowledge. This facilitate the scope of further research in the developing area of optimal PMU placement in power system. In this paper, author present PMUs placement model incorporating the reliability of concerned network components and derived probability of network observability coverage in a power system. Proposed model is verified on IEEE 14 bus and IEEE 30 bus test system.
Effect of Logic Depth ad Switching Speed on Random Telegraph Noise Induced Delay Fluctuation

We present measurement results of the effect of switching speed and logic depth on random telegraph noise (RTN) induced delay fluctuation using a test chip fabricated in a 65-nm Silicon-On- Thin-Buried-Oxide process. Measurement results reveal that the expected value of delay fluctuation decreases rapidly with the increase of logic depth. However, the delay fluctuation above 99th percentile is not strongly affected by logic depth. RTN-induced delay fluctuations are found to be not affected by the switching speed of logic gates. The measurement results provide useful insights into developing a statistical static timing analysis (SSTA) framework to asses the worst-case delay under the presence of RTN.
A survey on mobile edge platform with blockchain

As the Internet of Things (IoT), 5G and embedded artificial cloud computing develop, cloud computing is encountering growing challenges such as stringent latency requirements, network bandwidth constraints, etc. Edge computing proposes to bring computing and storage closer to user ends (UEs). Furthermore, mobile edge computing (MEC) aims to combine edge computing and cloud computing to offer better latency and user experience. However, cloud computing exists some inherent weakness, such as data loss and leakage, threats to data privacy, etc. We propose a blockchain-based MEC platform, called BlockMEC, that consists of unknown devices to distribute computing, control, storage, and networking functions to the edge of network without involving any central controllers. The survey paper also summarizes typical MEC concepts and makes comparisons between them and BlockMEC.
ECOQUG: An Effective Ensemble Community Scoring Function

A reasonable and effective community scoring function is of great significance since it can measure the community quality of groups we found more properly and help us discover more valuable communities. In this paper, we propose a new community scoring function, ECOQUG. Different from the existing community scoring functions, ECOQUG is designed based on the experimental study and theoretical analysis of groups with different community qualities. ECOQUG is more convincing. In addition, we design a series of experiments to examine the effectiveness and accuracy of ECOQUG and 13 other classic community scoring functions comprehensively. The extensive experimental results show that ECOQUG is effective and better than other community scoring functions.
Weighted Combinatorial Sequence Testing for the TLS Protocol

In this paper, we apply the notion of weighted t-way sequences to derive sequence test cases for testing implementations of the TLS protocol version 1.2. The used weights have been derived from an analysis of a security bug database of GnuTLS and we tested four implementations of the TLS protocol against them comparing their behavior. Our results indicate discrepancies in the behavior of different TLS implementations.
Behavioral Models and Scenario Selection for Testing IoT Trickle-Based Lossy Multicast Networks

The Trickle algorithm is widely used to manage information dissemination in Wireless Sensor Networks (WSN) and it continues to be studied, in order to evaluate its performance or to derive variants or use in higher-level protocols. In this paper, we propose behavioural test models for the Trickle-based Multicast Protocol for Low Power and Lossy Networks (MPL). MPL proposes to use Trickle not only to schedule on-demand retransmissions but also to discover new information that has not yet been received, eventually due to non-deterministic packets loss. Testing such a protocol is challenging as it is used in particular to update sensors functionalities by disseminating prioritized large-scale firmware upgrades in the network. As part of our contribution, we have implemented reachability-based techniques which allow the selection of distributed test objectives in the form of timed scenarios with high-coverage of critical multicast communications achieving an up-to-date state of the sensors network.
Android software vulnerability mining framework based on dynamic taint analysis technology

Security vulnerability mining is at the core of Android system security research. How to effectively exploit Android system security vulnerabilities has become an important technical means to enhance the security of smartphones and protect user security and privacy. An Android software vulnerability mining framework based on dynamic taint analysis technology is designed in this paper. Firstly, it analyzes the shortcomings of existing vulnerability mining technology, then gives the detailed design of the framework, and then discusses in detail the taint propagation analysis under Java context. Complete the switching between Java context and native context taint analysis environment at runtime, instruction preprocessing and other key techniques of Android vulnerability mining based on dynamic taint analysis theory. Finally, summarizes the whole paper and puts forward the problem worthy of further study.
Constant-rate Space-Time Code Selection Design Using Particle Swarm Optimization

In this paper, a constant-rate space-time code selection technique for multiple input-single output systems has been designed using the particle swarm optimization algorithm, finding channels threshold levels used by this technique. An analytical expression is proposed to be used as objective function, to address the problem of minimizing the bit-error rate. Results show that considerable energy-to-noise gains were obtained when using optimized threshold levels.
Road Surface Condition Inspection Using a Laser Scanner Mounted on an Autonomous Driving Car

Inspection and repair of road infrastructures are important for safety. While highways and motorways are periodically inspected with specialized vehicles, the roads which are maintained by local governments are not inspected because of lack of budget and workforce. In the future, however, a large number of autonomous driving cars will run everywhere. They are equipped with laser scanners to recognize the surroundings. If we utilize these sensors to inspect the road surface condition automatically, the cost of inspection will be reduced dramatically. In this paper, we extract transverse profiles of a road using point clouds which are recorded by a laser scanner mounted on an autonomous driving car. Point clouds are converted to the same format of special vehicle. We compared the data recorded by a specialized vehicle and a car with a laser scanner in Ichinomiya, Aichi prefecture, Japan and found that proposed method can be used as a preliminary survey to find where needs the detailed inspection.
Design of A Compact Staircase Shaped Ultra Wideband Antenna For Wireless Applications

A compact ultra wide-band antenna is presented in this work. The proposed antenna has a staircase shaped radiating structure. Band notching is obtained by creating notches at its ends and two narrow slots from the ground plane. FR4 with dielectric constant of 4.4 is used as substrate. The size of antenna is 26x18x1.6 mm3. A narrow slot is introduced in the proposed structure & simulated results were compared with the structure with L cut. The proposed antenna with narrow slots gives good performance and coverage when compared to the antenna with L cut. The antenna exhibits an average gain of 3 dB and directivity of about 4 dB with good coverage. ADS (2009) is used to perform the simulation of the proposed antenna structure.
Answering Why-Not Group Spatial Keyword Queries (Extended Abstract)

With the proliferation of geo-textual objects on the web, extensive efforts have been devoted to improving the efficiency of top-k spatial keyword queries in different settings. However, comparatively much less work has been reported on enhancing the quality and usability of such queries. In this context, we propose means of enhancing the usability of a top-k group spatial keyword query, where a group of users aim to find k objects that contain given query keywords and are nearest to the users. Specifically, when users receive the result of such a query, they may find that one or more objects that they expect to be in the result are in fact missing, and they may wonder why. To address this situation, we develop a so-called why-not query that is able to minimally modify the original query into a query that returns the expected, but missing, objects, in addition to other objects. Specifically, we formalize the why-not query in relation to the top-k group spatial keyword query, called the Why-not Group Spatial Keyword Query (WGSK) that is able to provide a group of users with a more satisfactory query result. We propose a three-phase framework for efficiently computing he WGSK. Extensive experiments with real and synthetic data offer evidence that the proposed solution excels over baselines with respect to both effectiveness and efficiency.