Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced linguistic explanations of classifier decisions for users' annotation support

We propose several new concepts for providing enhanced explanations of classifier decisions in linguistic (human readable) form. These are intended to help operators to better understand the decision process and support them during sample annotation to improve their certainty and consistency in successive labeling cycles. This is expected to lead to better, more consistent data sets (streams) for use in training and updating classifiers. The enhanced explanations are composed of 1) grounded reasons for classification decisions, represented as linguistically readable fuzzy rules, 2) a classifier's level of uncertainty in relation to its decisions and possible alternative suggestions, 3) the degree of novelty of current samples and 4) the levels of impact of the input features on the current classification response. The last of these are also used to reduce the lengths of the rules to a maximum of 3 to 4 antecedent parts to ensure readability for operators and users. The proposed techniques were embedded within an annotation GUI and applied to a real-world application scenario from the field of visual inspection. The usefulness of the proposed linguistic explanations was evaluated based on experiments conducted with six operators. The results indicate that there is approximately an 80% chance that operator/ user labeling behavior improves significantly when enhanced linguistic explanations are provided, whereas this chance drops to 10% when only the classifier responses are shown.
Functions in databases

We discuss the objectives of including functional dependencies in the definition of a relational database. We find two distinct objectives. The appearance of a dependency in the definition of a database indicates that the states of the database are to encode a function. A method based on the chase of calculating the function encoded by a particular state is given and compared to methods utilizing derivations of the dependency. A test for deciding whether the states of a schema may encode a nonempty function is presented as is a characterization of the class of schemas which are capable of encoding nonempty functions for all the dependencies in the definition. This class is the class of dependency preserving schemas as defined by Beeri et al. and is strictly larger than the class presented by Bernstein. The second objective of including a functional dependency in the definition of a database is that the dependency be capable of constraining the states of the database; that is, capable of uncovering input errors made by the users. We show that this capability is weaker than the first objective; thus, even dependencies whose functions are everywhere empty may still act as constraints. Bounds on the requirements for a dependency to act as a constraint are derived. These results are founded on the notion of a weak instance for a database state, which replaces the universal relation instance assumption and is both intuitively and computationally more nearly acceptable.
High-speed laser diode driver with low sensitivity to process variation and improvement on overshoot performance

In this paper, we proposed a high speed and large current laser diode driving circuit with low sensitivity to process variation. It is commonly applied in the DVD player. In a large current and high speed output LDD circuit, topics such as overshoot, undershoot, rising time, falling time and slew-rate are necessary to be considered. Therefore, to improve the signal integrity of Combination Switch Mode (CSM) LDD Architecture in [5], modification is made. The simulation results show that the output current turned slightly slower in speed, whereas the performance in overshoot and undershoot are significantly improved. Finally, we proposed the Source Degeneration Type with Improve Overshoot Performance (CSM) LDD Architecture. The circuit has been implemented in 0.35-μ m 5V CMOS process and simulated by HSPICE.
Undesired relatives: protection mechanisms against the evil twin attack in IEEE 802.11

Commonly used identifiers for IEEE 802.11 access points (APs), such as network name (SSID), MAC (BSSID), or IP address can be trivially spoofed. Impersonating existing APs with faked ones to attract their traffic is referred to in the literature as the \emph{evil twin attack}. It allows an attacker with little effort and expenditure to fake a genuine AP and intercept, collect, or alter (potentially even encrypted) data. Due to its severity, the topic has gained remarkable research interest in the past decade. In this paper, we introduce a differentiated attacker model to express the attack in all its facets. We propose a taxonomy for classifying and structuring countermeasures and apply it to existing approaches. We are the first to conduct a comprehensive survey in this domain to reveal the potential and the limits of state-of-the-art solutions. Our study discloses an important attack scenario which has not been addressed so far, i.e., the usage of specialized software to mount the attack. We propose and experimentally validate a novel method to detect evil twin APs operated by software within a few seconds.
Scheduling to Minimize Average Completion Time: Off-Line and On-Line Approximation Algorithms

In this paper we introduce two general techniques for the design and analysis of approximation algorithms for NP-hard scheduling problems in which the objective is to minimize the weighted sum of the job completion times. For a variety of scheduling models, these techniques yield the first algorithms that are guaranteed to find schedules that have objective function value within a constant factor of the optimum. In the first approach, we use an optimal solution to a linear programming relaxation in order to guide a simple list-scheduling rule. Consequently, we also obtain results about the strength of the relaxation. Our second approach yields on-line algorithms for these problems: in this setting, we are scheduling jobs that continually arrive to be processed and, for each time t, we must construct the schedule until time t without any knowledge of the jobs that will arrive afterwards. Our on-line technique yields constant performance guarantees for a variety of scheduling environments, and in some cases essentially matches the performance of our off-line LP-based algorithms.
Optical Multiple-Particle Manipulation With a Rectangular-Shaped VCSEL

Optical manipulation of cells and particles is an efficient non-destructive technique for isolation and sorting in the field of biophotonics. For several years, vertical-cavity surfaceemitting lasers (VCSELs) have been investigated as light sources for particle manipulation inside microfluidic channels, where their small dimension and low power consumption enable direct integration with the channels. In such an integrated module, however, the simultaneous manipulation of multiple particles requires the use of densely packed VCSEL arrays with very small device pitch, making the fabrication process more expensive and complicated. We show efficient single as well as multiple polystyrene particle trapping and sorting inside polydimethylsiloxane (PDMS) microfluidic channels using one rectangularshaped top-emitting AlGaAs–GaAs VCSEL with an active aperture area of about 100 × 14μm. The VCSEL emission wavelength is around 850 nm, which is suitable for usage in biophotonics, as biological materials present little absorption in the near-infrared spectral range. Furthermore, the oblong-shaped VCSELs can potentially be integrated with PDMS microfluidic channels to form miniaturized optofluidic chips for ultra-compact particle handling and manipulation.
Semi-Automatic 2D to 3D Video Conversion Based on Relative Velocity Estimation

we propose a semi-automatic method for requiring low computation resources and precisely generating depth map using on 2D to 3D conversion. Firstly, the user-defined points in the first frame background scene of 2D video sequence are used to extract vanishing line. Then, the background depth map is determined by vanishing line tracking and the moving objects are assigned with depth values according to their position in the background. Finally, the motion based depth map and the geometry based map are integrated into one depth map by a depth fusion algorithm. With the depth map and original 2D video, a 3D video is constructed.
Battery monitoring and analysis for android based system

Testing of Embedded system have always faced numerous problems with complex architecture of software and hardware combinations. Rapidly growing energy and battery consumption demands of mobile phones are not accomplished with advances in battery technology. Energy consumption is an important issue in android devices for mobile devices having advanced operating system. The lifetime of the battery is more and more important issue for users, for example if Wi-Fi or other applications are used continuously in the mobile, the battery of mobile discharges before its specified time. This paper presents a battery monitoring system which is capable of sensing and monitoring capability of battery of mobile phone, which is used to indicate the battery conditions in any numbers of standby powers. The battery capability is to monitor any number of cells utilizing a frequency-shift-keyed signal to sequentially interrogate each individual cell. This modulated tone responses are used to transmit the data back to the monitoring module. This paper introduces the background service name as Mainactivity. This service provides Power saver for automated power model construction method that uses built-in battery voltage sensors and knowledge of battery discharge behavior to monitor power consumption. To save android applications energy, it is critical to monitor the energy consumption of each application. As a solution to this, process acts as a background process and used to monitor battery power for each application and overall system. It also helps to inform users about the battery usage information and restricting the application which uses excess power.
Experimental Investigation for Improving Shrinkage Cracking Resistance of BFS Blended Cement Concrete Exposed to Hot Environment

It was reported that shrinkage cracking resistance of BFS cement concrete tended to be significantly lower than that of the normal concrete at hot environment due to higher autogenous shrinkage and smaller creep. This study investigates effects of concrete constituents on improving shrinkage cracking resistance via restraint shrinkage cracking experiments. Experimental parameters are: fineness in BFS powder, anti-shrinkage admixtures like expansive agents and shrinkage reducing agents. As a result, a shrinkage reducing agent, which has been newly developed as improving water retaining ability, most significantly affect to strengthen shrinkage cracking resistance in BFS concrete in hot environment.
Salmonella enterica Infections in the United States and Assessment of Coefficients of Variation: A Novel Approach to Identify Epidemiologic Characteristics of Individual Serotypes, 1996–2011

Background Despite control efforts, salmonellosis continues to cause an estimated 1.2 million infections in the United States (US) annually. We describe the incidence of salmonellosis in the US and introduce a novel approach to examine the epidemiologic similarities and differences of individual serotypes. Methods Cases of salmonellosis in humans reported to the laboratory-based National Salmonella Surveillance System during 1996–2011 from US states were included. Coefficients of variation were used to describe distribution of incidence rates of common Salmonella serotypes by geographic region, age group and sex of patient, and month of sample isolation. Results During 1996–2011, more than 600,000 Salmonella isolates from humans were reported, with an average annual incidence of 13.1 cases/100,000 persons. The annual reported rate of Salmonella infections did not decrease during the study period. The top five most commonly reported serotypes, Typhimurium, Enteritidis, Newport, Heidelberg, and Javiana, accounted for 62% of fully serotyped isolates. Coefficients of variation showed the most geographically concentrated serotypes were often clustered in Gulf Coast states and were also more frequently found to be increasing in incidence. Serotypes clustered in particular months, age groups, and sex were also identified and described. Conclusions Although overall incidence rates of Salmonella did not change over time, trends and epidemiological factors differed remarkably by serotype. A better understanding of Salmonella, facilitated by this comprehensive description of overall trends and unique characteristics of individual serotypes, will assist in responding to this disease and in planning and implementing prevention activities.
Current Concepts on Gastric Carcinoid Tumors

Gastric carcinoid tumors (GCs) are rare lesions representing less than 10% of carcinoid tumors and less than 1% of all stomach neoplasms. There are three distinct types of gastric carcinoids; type I includes the vast majority (70–85%) of these neoplasms that are closely linked to chronic atrophic gastritis. Type II which accounts for 5–10 %, is associated with Zollinger-Ellison syndrome and often occurs in the context of multiple endocrine neoplasia type 1. Type III, finally, represents 15–25% of gastric carcinoids and is characterized by a far more aggressive course. The optimal clinical approach to GCs remains to be elucidated, depending upon type, size, and number of carcinoids. While there is universal agreement about the surgical treatment of type III GCs, current options for type I and II include simple surveillance, endoscopic polypectomy, surgical excision associated with or without surgical antrectomy, or total gastrectomy. Moreover, the introduction of somatostatin analogues could represent another therapeutic option.
Designing an ELearning Portal for Developing Countries: An Action Design Approach

This paper presents the first phase of a study on using course design, including current eLearning and social trends, to overcome challenges in eLearning within developing countries, particularly for vocational/non-mainstream training. The paper outlines the research and development of an ICT artefact using the Action Design Research method. The artefact will later be deployed and evaluated. The paper discusses the previous research that has categorised challenges in eLearning in developing countries and explores how these can be overcome through course and element design. Course design includes training development, platform selection and platform hosting, particularly in the context of developing countries. Element design looks at the creation of content that should be available, practical and viable to both the user and developer through the exploitation of current eLearning and social trends. The paper concludes with the concept of the ICT artefact that has been designed for phase two of the study.
NoC-MPU: A secure architecture for flexible co-hosting on shared memory MPSoCs

For many embedded systems, data protection is becoming a major issue. On those systems, processors are often heterogeneous and prevent from deploying a common, trusted hypervisor on all of them. Multiple native software stacks are thus bound to share the resources without protection between them. NoC-MPU is a Memory Protection Unit allowing to support the secure and flexible co-hosting of multiple native software stacks running in multiple protection domains, on any shared memory MP-SoC using a NoC. This paper presents a complete hardware architecture of this NoC-MPU mechanism, along with a software trusted model organization.
Imaging capabilities of resist in deep ultraviolet liquid immersion interferometric lithography

Liquid immersion lithography (LIL) extends the resolution of optical lithography to meet industry demands into the next decade. Through the use of exposure media such as purified water (n of 1.44 at 193nm), it is possible to reduce minimum pitches compared with traditional air/vacuum exposures media by a factor of as much as 44%—a full technology node. Beyond this simple observation, there is a good deal of work necessary to fully understand the impact of LIL immersion lithography on a lithography processes. This article addresses the impact of water immersion on the imaging capabilities of different resist formulations. All resists were evaluated by imaging dense line-space structures at a 65-nm half-pitch both in air and with water immersion. Studies of dense 65-nm lines made by immersion imaging in HPLC grade water with controlled variations in resist components were performed. Significant differences were observed and will be discussed.
Prediction of kinase-specific phosphorylation sites using conditional random fields

Motivation: Phosphorylation is a crucial post-translational protein modification mechanism with important regulatory functions in biological systems. It is catalyzed by a group of enzymes called kinases, each of which recognizes certain target sites in its substrate proteins. Several authors have built computational models trained from sets of experimentally validated phosphorylation sites to predict these target sites for each given kinase. All of these models suffer from certain limitations, such as the fact that they do not take into account the dependencies between amino acid motifs within protein sequences in a global fashion. Results: We propose a novel approach to predict phosphorylation sites from the protein sequence. The method uses a positive dataset to train a conditional random field (CRF) model. The negative training dataset is used to specify the decision threshold corresponding to a desired false positive rate. Application of the method on experimentally verified benchmark phosphorylation data (Phospho.ELM) shows that it performs well compared to existing methods for most kinases. This is to our knowledge that the first report of the use of CRFs to predict post-translational modification sites in protein sequences. Availability: The source code of the implementation, called CRPhos, is available from http://www.ptools. ua.ac. be/CRPhos/ Contact: kris.laukens@ua.ac. be Suplementary Information: Supplementary data are available at http://www.ptools. ua.ac. be/CRPhos/
The Regulation of Corticofugal Fiber Targeting by Retinal Inputs

Corticothalamic projection systems arise from 2 main cortical layers. Layer V neurons project exclusively to higher-order thalamic nuclei, while layer VIa fibers project to both first-order and higher-order thalamic nuclei. During early postnatal development, layer VIa and VIb fibers accumulate at the borders of the dorsal lateral geniculate nucleus (dLGN) before they innervate it. After neonatal monocular enucleation or silencing of the early retinal activity, there is premature entry of layer VIa and VIb fibers into the dLGN contralateral to the manipulation. Layer V fibers do not innervate the superficial gray layer of the superior colliculus during the first postnatal week, but also demonstrate premature entry to the contralateral superficial gray layer following neonatal enucleation. Normally, layer V driver projections to the thalamus only innervate higher-order nuclei. Our results demonstrate that removal of retinal input from the dLGN induces cortical layer V projections to aberrantly enter, arborize, and synapse within the first-order dLGN. These results suggest that there is cross-hierarchical corticothalamic plasticity after monocular enucleation. Cross-hierarchical rewiring has been previously demonstrated in the thalamocortical system (Pouchelon et al. 2014), and now we provide evidence for cross-hierarchical corticothalamic rewiring after loss of the peripheral sensory input.
A sitting posture recognition system based on 3 axis accelerometer

According to a recent study poor sitting posture of the spine has been shown to lead to a variety of spinal disorders. For this reason, it is important to measure the sitting posture. In this study, we proposed a system that sitting posture classify using 3-axis accelerometer. We retrieved acceleration data from single tri-axial accelerometer attached on the back of the subject's neck in 5-types of sitting posture. 6 subjects without any spinal disorder were participated in this experiment. Acceleration data were transformed to the feature vectors of principle component analysis. Support vector machine (SVM) and K-means clustering were used to classify sitting posture with the transformed feature vectors. To evaluate performance, we calculated the correct rate for each classification strategy. Although the correct rate of SVM in sitting back arch was lower than that of K-means clustering by 1.9%, SVM's correct rate was higher by 0.8%, 4.7%, 15.5%, 6.9% in a normal posture, sitting front arch, sitting cross-legged, sitting leaning right, respectively. In conclusion, the overall correction rates were 95.33% and 89.35% in SVM and K-means clustering respectively, which means that SVM have more advantage than K-means method for classification of sitting posture.
AN INTELLIGENT LOCATION MANAGEMENT ALGORITHM FOR C E L L U L A R SYSTEMS

With the explosive growth in the number of cellular subscribers in the past decade, cellular systems are faced with the challenge of increasing the efficiency of the usage of the limited frequency spectrum. The service providers are forced to use increasingly smaller cells to increase system capacity; however, smaller cell sizes result in higher signalling loads generated by location management procedures. The intelligent location management algorithm which utilizes the user profile of individual users is proposed. The user profile contains a history of the user's cell-to-cell transitions and the total time spent in a cell. Using this information, the intelligent algorithm generates location areas dynamically around the user in such a way that the mean location updating traffic is reduced, and pages within the location area in multiple steps such that the mean paging traffic is reduced by paging the most probable cells first. A user mobility model is proposed for the purpose of quantifying the performance results of location management algorithms. The proposed model, activity-based mobility model with directional random walk, simulates mobility behaviour patterns of users of different classes. Such a model which captures an individual user's daily movement pattern is important in properly evaluating location management algorithms that utilize user mobility history. Performance in terms of radio signalling is evaluated and compared with other location management algorithms such as the G S M and dynamic location management algorithms. The intelligent algorithm produces less radio signalling at the cost of increased memory storage and processing capabilities at the mobile station and network.
Differentially Private Location Protection for Worker Datasets in Spatial Crowdsourcing

Spatial Crowdsourcing (SC) is a transformative platform that engages individuals in collecting and analyzing environmental, social, and other spatio-temporal information. SC outsources spatio-temporal tasks to a set of workers, i.e., individuals with mobile devices that perform the tasks by physically traveling to specified locations. However, current solutions require the workers to disclose their locations to untrusted parties. In this paper, we introduce a framework for protecting location privacy of workers participating in SC tasks. We propose a mechanism based on differential privacy and geocasting that achieves effective SC services while offering privacy guarantees to workers. We address scenarios with both static and dynamic (i.e., moving) datasets of workers. Experimental results on real-world data show that the proposed technique protects location privacy without incurring significant performance overhead.