Miracle-dz/UniFAR-FTUs huggingface dataset:
A natural user interface for e-learning learners: Focused on the automatic speed control of multimedia materials

There are few previous empirical studies on an automatic speed control of multimedia materials based on a natural user interface (NUI) that distinguish note taking from watching to a lecture through nodding. This study conducted two experiments and an interview. First, in experiment 1, we found that there is significant relevancy between the participants’ action of lowering their head and note taking. Second, we determined that nodding that lasts less than two seconds has no relationship to note taking. In experiment 2, we determined that the e-learning system with the automatic speed control of multimedia materials reported less learner manual control, clicking pause and rewind buttons, than the regular e-learning system. For the interview, the analysis shows that “The automatic speed control of multimedia materials” and “Note taking” influence “Participant’s satisfaction” positively.
A bandwidth efficient pilot symbol technique for coherent detection of turbo codes over fading channels

A method is proposed to implement coherent detection of turbo coded binary phase shift keying (BPSK) signals transmitted over frequency-flat Rayleigh fading channels. After turbo encoding, a subset of the parity symbols is punctured and replaced with known pilot symbols. Because the pilot symbols replace existing parity symbols, no bandwidth expansion is required. However, there is a restriction on the set of possible pilot symbol spacings and interleaver sizes. At the receiver, estimates of the complex channel gain and variance of the additive noise are first computed by filtering observations of the pilot symbols. As the turbo decoder performs its iterations, the channel estimates are refined by using information produced by the decoder. The performance of the proposed technique is assessed by computer simulation, and compared for two normalized fade rates with both perfect coherent detection (corresponding to perfect knowledge of the fading process and noise variance) and differential detection of differentially-encoded binary phase shift keying (DPSK).
Large-Scale Hierarchical Classification via Stochastic Perceptron

Hierarchical classification (HC) plays an significant role in machine learning and data mining. However, most of the state-of-the-art HC algorithms suffer from high computational costs. To improve the performance of solving, we propose a stochastic perceptron (SP) algorithm in the large margin framework. In particular, a stochastic choice procedure is devised to decide the direction of next iteration. We prove that after finite iterations the SP algorithm yields a sub-optimal solution with high probability if the input instances are separable. For large-scale and high-dimensional data sets, we reform SP to the kernel version (KSP), which dramatically reduces the memory space needed. The KSP algorithm has the merit of low space complexity as well as low time complexity. The experimental results show that our KSP approach achieves almost the same accuracy as the contemporary algorithms on the real-world data sets, but with much less CPU running time.
Providing motor impaired users with access to standard Graphical User Interface (GUI) software via eye-based interaction

We have designed an on-screen keyboard, operated by eye-gaze, for use by motor-impaired users. It enables interaction with unmodified standard Graphic User Interface (GUI) software written for ablebodied users, and it is not solely designed around the need to enter text. The keyboard will adapt automatically to the application context by, for example, loading a specific set of keys designed for use with particular menus whenever a menu is displayed in the target application. Results of initial evaluation trials are presented and the implications for improvements in design are discussed.
Titanium Salan Complexes Displays Strong Antitumor Properties In Vitro and In Vivo in Mice

The anticancer activity of titanium complexes has been known since the groundbreaking studies of Köpf and Köpf-Maier on titanocen dichloride. Unfortunately, possibly due to their fast hydrolysis, derivatives of titanocen dichloride failed in clinical studies. Recently, the new family of titanium salan complexes containing tetradentate ONNO ligands with anti-cancer properties has been discovered. These salan complexes are much more stabile in aqueous media. In this study we describe the biological activity of two titanium salan complexes in a mouse model of cervical cancer. High efficiency of this promising complex family was demonstrated for the first time in vivo. From these data we conclude that titanium salan complexes display very strong antitumor properties exhibiting only minor side effects. Our results may influence the chemotherapy with metallo therapeutics in the future.
Event typicality and memory: Investigating how prior knowledge and novelty modulate memory for complex events

A complex set of processes and brain regions work together in healthy adults, allowing them to create and recall memories of daily events. Additionally, the perception and recall of these events is shaped by factors such as novelty and congruence with prior knowledge (typicality). Despite a long history of research, studies on the neural underpinnings of the mnemonic effects of novelty and typicality rarely examine complex naturalistic event memories. Moreover, it is uncertain how these effects evolve over time, as memories are stabilized and transformed from acquisition to retention and retrieval. In this thesis I use naturalistic film clip stimuli, behavioural measures, and functional magnetic resonance imaging (fMRI) to explore the effects of both novelty and typicality on the neural substrates mediating memory, and examine how these effects evolve through encoding and retrieval over the course of a week. Behaviourally, I find that both typicality and novelty enhance memory for events, but that atypical events are recalled with more errors over time. With respect to the neural bases of memory, I demonstrate that the greatest differences based on event typicality are seen during encoding when typicality is correlated with greater medial prefrontal cortex (mPFC) and parietal activation, while novelty is correlated with greater activation in the medial temporal lobes (MTLs) and posterior sensory cortices. During retrieval, however, such differences based on typicality are subtler, with iii retrieval supported by the MTLs, irrespective of event typicality, at all time points. Notwithstanding these overall neural similarities in the retrieval of all events, typical clips are associated with attenuated MTL activation during remote retrieval, indicating that recall dynamics may be influenced by event typicality over time. Furthermore, I provide evidence for differential functional connectivity of both the mPFC and MTLs during encoding and retrieval, based on event typicality. These results, which demonstrate how the neural substrates mediating narrative episodic memories are modulated by event typicality, are consistent with two complementary theories Trace Transformation Theory and Schema Theory. Furthermore, they suggest, through mPFC and MTL functional connectivity, potential mechanisms by which typical and novel events may be differentially encoded and retrieved.
Maximizing User Satisfaction By Improving Coding Efficiency Of Multiple Descriptions Coded Video

: Due to the emerging technologies for video compression and broadband Internet, video streaming services are made available. Live video streaming without delay is a reality now. However, the available bandwidth has to be allocated optimally when video streaming takes place over a multicast network. This is because users have different requirement with respect to bandwidth. Moreover, the users may need streaming to their mobile devices, PCs or high – definition TV. In order to allocate bandwidth based on user requirement, the users can be grouped into various categories. This will facilitate to manage bandwidth allocation easily. This is achieved using MDC (Multiple Description Coding) in which video source is associated with various descriptions and the receivers are associated with one of the descriptions. This will automate the process of allocating different bandwidth to different users while the same video is being streamed. However allocating optimal bandwidth is a challenging task that needs research. In this Paper we consider this as an optimization problem. The aim is to maximize user bandwidth experience and satisfaction by improving coding efficiency pertaining to MDC. We developed an algorithm to achieve this. The simulation results of our algorithm reveal that it improves user satisfaction significantly.
VLEPpO: a Visual Language for Problem Representation

AI planning constitutes a field of interest as its techniques can be applied to many areas. Contemporary systems that are being developed deal with certain aspects of planning and focus mainly on dealing with advanced features such as resources, time and numerical expressions. This paper presents VLEPpO, a Visual Language for Enhanced Planning problem Orchestration. VLEPpO is a visual programming environment that allows the user to easily define planning domains and problems, acquire their PDDL representations, as well as receive solutions, utilizing web services infrastructure.
Information flow modeling based on diffusion rate for prediction and ranking

Information flows in a network where individuals influence each other. The diffusion rate captures how efficiently the information can diffuse among the users in the network. We propose an information flow model that leverages diffusion rates for: (1) prediction . identify where information should flow to, and (2) ranking . identify who will most quickly receive the information. For prediction, we measure how likely information will propagate from a specific sender to a specific receiver during a certain time period. Accordingly a rate-based recommendation algorithm is proposed that predicts who will most likely receive the information during a limited time period. For ranking, we estimate the expected time for information diffusion to reach a specific user in a network. Subsequently, a DiffusionRank algorithm is proposed that ranks users based on how quickly information will flow to them. Experiments on two datasets demonstrate the effectiveness of the proposed algorithms to both improve the recommendation performance and rank users by the efficiency of information flow.
From work to word: How do software developers describe their work?

Developers take notes about their work sessions, either to remember the work status and share it with collaborators, or because employers explicitly require this for project management matters. We report on an exploratory study which aims at understanding how software developers describe their work. We analyzed more than 750,000 work descriptions of about 2,000 professionals taken over 8 years in three settings. We observed several similarities in the content and time meta-data of work descriptions. Most frequent terms, such as top-30 performed activities, are used consistently. Particular templates such as “ACTION concerning ARTIFACT because of CAUSE” occur frequently. Developers described sessions that last 30–120 min. 4–16 times a day. Maintaining diaries seems to consume between 3–6% of the total work time, and in 10% of the sessions, developers did not describe their work in sufficient detail. We argue that our results make the first step towards automatically generating work diaries for software developers.
Consequences of Comorbidity of Elevated Stress and/or Depressive Symptoms and Incident Cardiovascular Outcomes in Diabetes: Results From the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study

OBJECTIVE To evaluate the impact of comorbid depressive symptoms and/or stress on adverse cardiovascular (CV) outcomes in individuals with diabetes compared with those without diabetes. RESEARCH DESIGN AND METHODS Investigators examined the relationship between baseline depressive symptoms and/or stress in adults with and without diabetes and physician-adjudicated incident CV outcomes including stroke, myocardial infarction/acute coronary heart disease, and CV death over a median follow-up of 5.95 years in the national REGARDS cohort study. RESULTS Subjects included 22,003 adults (4,090 with diabetes) (mean age 64 years, 58% female, 42% black, and 56% living in the southeastern “Stroke Belt”). Elevated stress and/or depressive symptoms were more common in subjects with diabetes (36.8% vs. 29.5%; P < 0.001). In fully adjusted models, reporting either elevated stress or depressive symptoms was associated with a significantly increased incidence of stroke (HR 1.57 [95% CI 1.05, 2.33] vs. 1.01 [0.79, 1.30]) and CV death (1.53 [1.08, 2.17] vs. 1.12 [0.90, 1.38]) in subjects with diabetes but not in those without diabetes. The combination of both elevated stress and depressive symptoms in subjects with diabetes was associated with a higher incidence of CV death (2.15 [1.33, 3.47]) than either behavioral comorbidity alone (1.53 [1.08, 2.17]) and higher than in those with both elevated stress and depressive symptoms but without diabetes (1.27 [0.86, 1.88]). CONCLUSIONS Comorbid stress and/or depressive symptoms are common in individuals with diabetes and together are associated with progressively increased risks for adverse CV outcomes.
On Graphs with Characteristic Bounded-Width Functions

Graphs can be represented symbolically by the Ordered Binary Decision Diagram (OBDD) of their characteristic Boolean function. The latter is said to have bounded width b if its minimal-size complete OBDD has bounded width b. Bounded-width functions have small OBDDs and allow efficient functional operations. Therefore, they are of interest in the analysis of symbolic graph algorithms. In this paper, a variety of graph sequences is proved to have characteristic functions of bounded-width. It is shown that this property is closed under important graph composition operations. Finally, an unpleasant property of a naive symbolic all-pairs shortest-paths algorithm in the context of bounded-width functions is presented.
A behavioral architecture for strategy execution in the RoboFlag game

Strategy definition for teams of multiple mobile robots with fewer human operators than robots is a continuing area of research. Before strategies can be defined, the medium upon which they are implemented must be understood. This paper describes the development of a hybrid multi-agent behavioral control architecture used to implement the strategies for game play in the RoboFlag environment. Additionally, the graphical-based human-robotic interface is described. A framework has been built upon which systematic evaluation of strategy definition components can be performed.
Protein Intake and Muscle Health in Old Age: From Biological Plausibility to Clinical Evidence

The provision of sufficient amounts of dietary proteins is central to muscle health as it ensures the supply of essential amino acids and stimulates protein synthesis. Older persons, in particular, are at high risk of insufficient protein ingestion. Furthermore, the current recommended dietary allowance for protein (0.8 g/kg/day) might be inadequate for maintaining muscle health in older adults, probably as a consequence of “anabolic resistance” in aged muscle. Older individuals therefore need to ingest a greater quantity of protein to maintain muscle function. The quality of protein ingested is also essential to promoting muscle health. Given the role of leucine as the master dietary regulator of muscle protein turnover, the ingestion of protein sources enriched with this essential amino acid, or its metabolite β-hydroxy β-methylbutyrate, is thought to offer the greatest benefit in terms of preservation of muscle mass and function in old age.
A Compilation Manager for Standard ML of New Jersey

The design and implementation of a compilation manager (CM) for Standard ML of New Jersey (SML/NJ) is described. Truly independent compilation is difficult to implement correctly and efficiently for SML because one compilation unit may depend not only on the interface of another, but also on its implementation. In this paper we present an integrated compilation system based on the “visible compiler” primitives provided by SML/NJ that supports selective recompilation to minimize system build time in most situations. Large systems are presented as hierarchical source groups. An automatic dependency analyzer determines constraints on the order in which sources must be considered. By abstracting away from the specifics of the SML/NJ compiler, the CM readily generalizes to arbitrary “compilation tools” such as parser generators and embedded languages.
Design and Implementation of Long-Digit Karatsuba ’ s Multiplication Algorithm Using Tensor Product Formulation ∗

Karatsuba’s multiplication algorithm uses three singledigit multiplications to perform one two-digit multiplication. If we apply Karatsuba’s multiplier recursively, it takes only 3 single-digit multiplications to multiply a pair of 2-digit numbers. This is a significant improvement compared to 4 single-digit multiplications using grade-school multiplier. In this paper, we will use tensor production formulation to express Karatsuba’s multiplication algorithm in both recursive and iterative form. Usually, Karatsuba’s algorithm is implemented as recursive program. With the iterative tensor product formula of Karatsuba’s algorithm, we can derive an iterative (for loop) program to perform multiplication of long-digit numbers. Furthermore, the 3 single-digit multiplications can be fully parallelized. Keyword: tensor product, block recursive algorithm, programming methodology, Karatsuba’s multiplication algorithm.
Steady-State analysis of a split-connection scheme for Internet access through a wireless terminal

TCP does not perform well in a connection that includes a lossy wireless link. Techniques intended to improve the performance of TCP for such connections can be grouped into three categories: end-to-end, link layer and split-connection approaches. Some simulations and experimental results indicate that split-connection protocols yield better performance than the other two approaches. Although analytical modeling of the end-to-end and link-layer approaches has been presented, no comparable performance analysis for split-connection protocols has been reported previously. In this paper, a stochastic model is developed and used to analyze the performance of a class of split-connection protocols which deploy TCP on the wire-line network and a light-weight transport protocol on the wireless final hop. The final hop is provided by a digital TDMA cellular system. The condition of heavy source traffic to the wireless terminal is considered. The model relates the throughput and some useful auxiliary performance measures to key system parameters such as propagation delays, the base-station buffer size, the ARQ protocol and channel-error process of the wireless link. The usefulness of the analysis is illustrated by its application to the problem of sizing the TCP receiving buffer in a base station.
Protection of regional object and camera tampering

Protection of regional object and camera tampering is very important in video surveillance and security applications. This paper presents a novel technique for protection of regional object and camera tampering detection. The monitoring regions are set artificially in the surveillance background scenes for protecting regional object, and cameras positions are also selected for camera tampering. According to the motion segmentation results based on background substraction model, alarm is triggered in comparison with the monitoring regions. The multiple original background images are sent into buffer and stored for protecting camera tampering. In order to recognize the slight shake of the camera, the normalized histogram distribution is utilized to detect the camera tampering. Experimental results show that the proposed algorithms can efficiently detect the abnormal events for protection of regional object and camera tampering.
Blind Extraction of Dominant Target Sources Using ICA and Time-Frequency Masking

This paper presents a method for enhancing target sources of interest and suppressing other interference sources. The target sources are assumed to be close to sensors, to have dominant powers at these sensors, and to have non-Gaussianity. The enhancement is performed blindly, i.e., without knowing the position and active time of each source. We consider a general case where the total number of sources is larger than the number of sensors, and neither the number of target sources nor the total number of sources is known. The method is based on a two-stage process where independent component analysis (ICA) is first employed in each frequency bin and then time-frequency masking is used to improve the performance further. We propose a new sophisticated method for deciding the number of target sources and then selecting their frequency components. We also propose a new criterion for specifying time-frequency masks. Experimental results for simulated cocktail party situations in a room, whose reverberation time was 130 ms, are presented to show the effectiveness and characteristics of the proposed method
Bilingual terminology extraction : an approach based on a multilingual thesaurus applicable to comparable corpora

This paper presents several methods for exploiting multiple resources in bilingual lexicon extraction, either from parallel or comparable corpora. First, a special attention is given to the use of multilingual thesauri, and different search strategies based on such thesauri are investigated. Then, a method to optimally combine the different resources for bilingual lexicon extraction is presented. Our results show that the combination of the resources significantly improves results, and that the use of the hierarchical information contained in our thesaurus, UMLS/MeSH, is of primary importance. Lastly, methods for bilingual terminology extraction and thesaurus enrichment
ELEMENTS OF STATISTICAL DECISION MAKING

Measurements are the key to rational decision making. Measurement information generates value, when it is applied in the decision making. Normative decision making considers all decision tasks as optimization problems, typically with multiple objectives and uncertainties. Therefore in normative decision making the decision task must first be formulated mathematically and then the resulting optimization problem is solved. This paper considers the elements of decision making under uncertainty based on statistical decision theory.
Using and enhancing the current MPEG-7 standard for a music content processing tool

The aim of this document is to discuss possible ways of describing some music constructs in a dual context. First, that of the current standard for multimedia content description: MPEG-7. Second, that of a specific software application, the Sound Palette (a tool for content-based management, content edition and transformation of simple audio phrases). We discuss some MPEG-7 limitations regarding different musical layers: melodic (present but underdeveloped), rhythmic (practically absent) and instrumental (present though using an exclusive procedure). Some proposals for overcoming them are presented in the context of our application.