Miracle-dz/UniFAR-FTUs huggingface dataset:
KINEMATICS MODELING AND WORKSPACE ANALYSIS OF A CABLE-BASED PARALLEL MANIPULATOR FOR SHOULDER REHABILITATION

The science of rehabilitation showed, in most cases, that repeated movements of human members can to help the patient regain the functions of the member injury. Robots for these tasks can be more efficient in performing these exercises than humans. Robotic systems for rehabilitation can be generally used to record information like position, trajectory, force and velocity exploiting the motor performance during active movements, and to guide the movement of a patient limb attached to the device. The cable-based parallel manipulator consists of a moving platform, which can carry an end-effector, and a base. These two elements are connected by multiple cables that can extend or retract. These structures have characteristics that make them suitable for rehabilitation purposes like large workspace which may be adapted to different patient and different training, the mechanical structure is easy to assembly and disassembly and can be reconfigurated in order to perform different therapies, can be easy to transportation and have low cost and simple maintenance which are relevant characteristics for possible commercial system to be used by patients at home. This paper presents a cable-based parallel structure for rehabilitation of the movements of the human shoulder named CaMaReS (Cable Manipulator for Rehabilitation of Shoulder). The robotics structure consists of four cables that allow the shoulder movements with different limits of movement and speed. After kinematics modeling, the kinds of workspace are defined then a statically reachable combined workspace for different geometric structures of fixed and moving platform is obtained. This workspace is defined as the situations of reference point of the moving platform, center of mass, which under external forces the moving platform should be in static equilibrium under conditions that length of all cables must not be exceeded from the maximum value and all of cables must be at tension. The development of this robotic device is justified by the large number of people with shoulder problems like stroke, polio, arthritis and disaster recovery.
Spatial Multiple Criteria Fuzzy Clustering for Image Segmentation

In this paper, we propose a spatial fuzzy clustering method based on multiple criteria optimization method. Our fuzzy clustering method is an enhanced version of fuzzy c-means (FCM) with consideration of multiple criteria. We initiate our multiple criteria optimization approach with two criteria in term of the features of an image: spatial information and intensity. Our spatial clustering attempts to overcome the limitation of conventional FCM. We have tested the proposed method on synthetic and coins images with added Gaussian and Salt and Pepper noises. Besides, we also experiment on real medical images (Magnetic Resonance Images (MRI)) for brain and osteosarcoma (bone tumour). The result reported was encouraging.
A Novel Design of Reversible Multiplier Circuit (TECHNICAL NOTE)

Adders and multipliers are two main units of the computer arithmetic processors and play an important role in reversible computations. The binary multiplier consists of two main parts, the partial products generation circuit (PPGC) and the reversible parallel adders (RPA). This paper introduces a novel reversible 4×4 multiplier circuit that is based on an advanced PPGC with Peres gates only. Again, an optimized Peres full adder reversible gate is used in RPA part with accompaniment with the carry save adder technique. The comparison of the proposed design with previous ones shows that the proposed reversible multiplier improves the quantum parameters. The proposed design shows lower quantum cost, depth and total cost with the help of a novel design in partial product generator. Moreover, the number of gates, garbage input and output has no change regarding to the best compared design. The proposed multiplier can be generalized as an n×n bit multiplication.
Zero-sum repeated games: counterexamples to the existence of the asymptotic value and the conjecture maxmin=lim v(n)

We provide an example of a two-player zero-sum repeated game with public signals and perfect observation of the actions, where neither the value of the lambda-discounted game nor the value of the n-stage game converges, when respectively lambda goes to 0 and n goes to infinity. It is a counterexample to two long-standing conjectures, formulated by Mertens: first, in any zero-sum repeated game, the asymptotic value exists, and secondly, when Player 1 is more informed than Player 2, Player 1 is able to guarantee the limit value of the n-stage game in the long run. The aforementioned example involves seven states, two actions and two signals for each player. Remarkably, players observe the payoffs, and play in turn (at each step the action of one player only has an effect on the payoff and the transition). Moreover, it can be adapted to fit in the class of standard stochastic games where the state is not observed.
Blind separation of dependent sources using the "time-frequency ratio of mixtures" approach

In this paper, we first briefly recall the principles of the "time-frequency ratio of mixtures" (TIFROM) approach that we recently proposed. We then show that, unlike independent component analysis (ICA) methods, our approach can separate dependent signals, provided there exist some areas in the time-frequency plane where only one source occurs. We achieve this attractive property because, whereas ICA methods aim at creating independent output signals, we use another concept, i.e. we directly estimate the mixing matrix by using the time-frequency information contained in the observations. Detailed results concerning mixtures of voice and music signals are presented and show that this approach yields very good performance for signals, which cannot be separated with traditional ICA methods.
Representation of Case Law as an Argumentation Framework

Since their introduction by Dung, Argumentation Frameworks have pro- vided a fruitful basis for studying reasoning in defeasible contexts, including law. As yet, however, no realistic body of case law has been represented as an Argumenta- tion Framework. In this paper we develop an Argumentation Framework of a much discussed body of case law, and draw attention to a number of questions concern- ing approaches to reasoning with cases in AI and Law that can be informed by this exercise.
Application-Specific Architecture Exploration Based on Processor-Agnostic Performance Estimation

Early design decisions such as architectural class and instruction set selection largely determine the performance and energy consumption of application specific processors (ASIPs). However, making decisions that effectively reflect in high performance require that a careful analysis of the target application is done by an experienced designer. Such process is extremely time consuming, and a confirmation that the processor meets the application requirements can only be extracted after costly architectural implementation, synthesis and simulation. To shorten design times, this work couples High-Level Synthesis (HLS) with pre-architectural performance estimation. We do so with the aim of providing designers with an initial architectural seed together with quantitative feedback about its performance. This enables to perform a light-weight refinement process based on the obtained feedback, such that time-consuming microarchitectural implementation is done only once at the end of the refinement steps. We employed our flow to generate four potential ASIPs for a 1024-point FFT. Estimates validation and gain evaluation is performed on actual ASIP implementations, which achieve performance gains of up to 8.42x and energy gains up to 1.32x over an existing VLIW processor.
Detecting malicious executable file via graph comparison using support vector machine

In every day, Anti-virus Corporations receive large number of potentially harmful executables. Many of the malicious samples among these executables are variations of their early versions that created by their authors to evade the detection. Consequently, robust detection approaches are required, capable of recognizing similar samples automatically. In this paper, malware detection through call graph was studied, the call graph functions of a binary executable are represented as vertices, and the calls between those functions as edges. By representing malware samples as call graphs, it is possible to derive and detect structural similarities between multiple samples. The present paper provides a new malware detection algorithm based on the analysis of graphs introduced from instructions of the executable objects, the graph is constructed through the graph extractor, and the maximum common sub-graph similarity measures is approximated, then the graphs are sent to support vector machine to perfectly approximate the similarity value.
Individual Differences in the Sense of Presence

There is a lack in the literature of studies that investigate the human factors involved in the engagement of presence. The present study is addressed to investigate the influence of five user’s characteristics (spatial intelligence, personality, cognitive style, computer experience and test anxiety) on the sense of presence. This study is the first one to investigate the relationship between spatial intelligence and presence, and it’s also pioneer in investigating the influence of personality characteristics on the sense of presence in an immersive virtual reality system. Results suggest that spatial intelligence, introversion, and anxiety influence the sense of presence experienced by the user.
Golden-run alignment for analysis of robustness testing results: dealing with diagnostics issues

For the analysis of robustness testing results, comparison with a golden run is commonly used to determine whether robustness failures occurred or not. One limitation of this approach is that traditional comparison techniques require the system to have a repeatable behavior under the same workload, whether or not in presence of faults. This limits the applicability of this technique, since most systems have indeterminist behavior due to concurrency, for example. Moreover, tools that use golden-run comparison hardly ever give information about what are the common patterns of behavior between the golden-run and a faulty trace and where there are deviations due to action of fault-tolerance mechanisms, for example. In this paper, we show how the use of sequence alignment algorithms, from computational biology, can be of help. Besides allowing the determination of regions of similarities between two sequences that are not exactly equal, these algorithms present results in a visual form, highlighting the different zones where there are common patterns between the two sequences. We also point out other ways in which alignment algorithms can be useful as well.
Multiple Antenna Systems: Capacities, Transmit Diversity and Turbo Processing

Gerhard Bauch and Joachim Hagenauer Institute for Communications Engineering (LNT) Munich University of Technology (TUM) Abstra t | We give an introduction to wireless systems with multiple transmit and receive antennas. Using multiple antenna systems is motivated by results on the capacity of multiple-input-multipleoutput (MIMO) channels. We describe different approaches to exploit these capacities like Bell Labs Layered Space-Time Architecture (BLAST), which we append by FEC coding and turbo processing, and transmit antenna diversity using space-time codes. The focus of the paper is on space-time codes. We describe the diversity effect of space-time trellis codes and space-time block codes using equivalent channel models and discuss if the MIMO channel capacity can be fully exploited using those techniques.
Problems remaining NP-complette for sparse or dense graphs

For each flxed pair fi;c > 0 let INDEPENDENT SET (mcn fi ) and INDEPENDENT SET (m ‚ i n ¢ i cn fi ) be the problem INDE- PENDENT SET restricted to graphs on n vertices with mcn fi or m ‚ i n ¢ i cn fi edges, respectively. Analogously, HAMILTONIAN CIRCUIT (mn + cn fi ) and HAMILTONIAN PATH (mn + cn fi ) are the problems HAMILTONIAN CIRCUIT and HAMILTONIAN PATH restricted to graphs with mn+cn fi edges. For each † > 0 let HAMILTONIAN CIRCUIT (m ‚ (1i†) i n ¢ ) and HAMILTONIAN PATH (m ‚ (1 i †) i n ¢ ) be the problems HAMILTONIAN CIRCUIT and HAMILTONIAN PATH restricted to graphs with m ‚ (1i†) i n ¢ edges. We prove that these six restricted problems remain NP{complete. Finally, we consider su-cient conditions for a graph to have a Hamil- tonian circuit. These conditions are based on degree sums and neigh- borhood unions of independent vertices, respectively. Lowering the required bounds the problem HAMILTONIAN CIRCUIT jumps from 'easy' to 'NP{complete'.
Accumulation of Heavy Metals in Crayfish and Fish from Selected Czech Reservoirs

To evaluate the accumulation of aluminium, cadmium, chromium, copper, lead, mercury, nickel, and zinc in crayfish and fish organ tissues, specimens from three drinking water reservoirs (Boskovice, Landštejn, and Nová Říše) and one contaminated site (Darkovské moře) in the Czech Republic were examined. Crayfish hepatopancreas was confirmed to be the primary accumulating site for the majority of metals (Cu > Zn > Ni > Cd > Cr), while Hg and Cr were concentrated in abdominal muscle, and Al and Pb were concentrated in gill. Metals found in Nová Říše specimens included Cu > Zn > Ni and those found in Boskovice included Zn > Hg > Cr. Cd concentrations were observed only in Landštejn specimens, while contaminated Darkovské moře specimens showed the highest levels of accumulation (Cu > Al > Zn > Pb). The majority of evaluated metals were found in higher concentrations in crayfish: Cu > Al > Zn > Ni > Cr > Cd > Pb, with Hg being the only metal accumulating higher in fish. Due to accumulation similarities of Al in crayfish and fish gill, differences of Hg in muscle, and features noted for the remaining metals in examined tissues, biomonitoring should incorporate both crayfish and fish to produce more relevant water quality surveys.
The Economic Geography of Talent

The distribution of talent, or human capital, is an important factor in economic geography. This article examines the economic geography of talent, exploring the factors that attract talent and its effects on high-technology industry and regional incomes. Talent is defined as individuals with high levels of human capital, measured as the percentage of the population with a bachelor's degree and above. This article advances the hypothesis that talent is attracted by diversity, or what are referred to as low barriers to entry for human capital. To get at this, it introduces a new measure of diversity, referred to as the diversity index, measured as the proportion of gay households in a region. It also introduces a new measure of cultural and nightlife amenities, the coolness index, as well as employing conventional measures of amenities, high-technology industry, and regional income. Statistical research supported by the findings of interviews and focus groups is used to probe these issues. The findings confirm the hypothesis and shed light on both the factors associated with the economic geography of talent and its effects on regional development. The economic geography of talent is highly concentrated. Talent is associated with the diversity index. Furthermore, the economic geography of talent is strongly associated with high-technology industry location. Talent and high-technology industry work independently and together to generate higher regional incomes. In short, talent is a key intermediate variable in attracting high-technology industries and generating higher regional incomes.
Implementation of packet classification algorithm in NetworkProcessor based router to enhance multimedia applications

The objective of this paper is to implement the Tuple Pruning Search(TPS) based packet classification algorithm in two different mappings namely Parallel mapping and Pipelined mapping for Network Processor(NP) based router to support multimedia applications. The performance is evaluated using Intel IXP2400 NP Simulator. The results demonstrate that, TPS has better classification rate and lesser memory occupancy than Tuple Space Search algorithm. Parallel mapping of TPS based algorithm achieves better performance than the Pipelined mapping and is well suited to achieve high speed packet classification to support multimedia applications.
Regional anesthesia in children: indications and limitations

The goal of regional anesthesia in infants and children is perioperative and postoperative pain relief. The use of regional anesthesia and analgesia provide improvement in patient outcomes, and may be helpful in special situations, such as premature babies, patients with neuromuscular disorders or non-fasting children presenting for urgent surgery. Application of ilioinguinal and rectus sheath blocks, transverses abdominal plane blocks and wound infiltra tion with local anesthetics is commonly performed in combination with general anesthesia. Continuous central and perineural infusion of local anesthetics remains the technique of choice for prolonged major surgery or intense postoperative pain. Caudal block still remains the most important and safe technique. Introduction of nerve stimulators and lastly ultrasound guided regional anesthesia techniques reduced the risks and increase the benefits of this kind of anesthesia. The safety profile of regional anesthesia presented in surveys is superior with the very low incidence of serious complications. The aim is to find the safest technique for realizing the anesthesia and analgesia in children where a benefit overcomes the risk.
Metabolic Surgery for Type 2 Diabetes Mellitus: Experience from Asia

Type 2 diabetes mellitus (T2DM) is a current global health priority and Asia is the epicenter of this epidemic disease. Unlike in the west, where older population is most affected, the burden of diabetes in Asian countries is disproportionately high in young to middle-age adults. The incidence of diabetic nephropathy is alarmingly high in patients with early onset T2DM, especially in those with poor glycemic control. How to control this chronic and debilitating disease is currently a very important health issue in Asia. Bariatric surgery has proven successful in treating not just obesity but also T2DM in morbid obese patients (body mass index [BMI] >35 kg/m2). Gastrointestinal metabolic surgery recently has been proposed as a new treatment modality for obesity related T2DM for patients with BMI <35 kg/m2. Many studies from Asia reported promising results of metabolic surgery to treat obese patients with T2DM which is not well controlled. It has been demonstrated that changes in gastrointestinal hormone secretion after gastrointestinal surgery would favor an early improvement of T2DM in Asians. New procedures have also been designed and proposed specifically for the treatment of diabetes in Asia. This article examines clinical trial data and accepted algorithms with a view toward elucidating the application of metabolic surgery for the treatment of T2DM in the Asia. We propose a systematic approach to surgical treatment, addressing current evidences, patient selection, procedure of choice, and timing and guideline for new procedures.
Primal-Dual Interior-Point Methods for Linear Optimization Based on a New Class of Kernel Functions

In this paper we present a new class of kernel functions for primal-dual interior point methods (IPMs) in linear optimization. The proposed functions have a finite value at the boundary of the feasible region. They are not exponentially convex and also not strongly convex like the usual barrier functions. In spite of this, the iteration bound of large-update interior-point methods based on these functions and analyzed in this paper, are shown to be O ‡ n 1 1+p lognlog n † · ; where p is a parameter, p 2 [0;1]. For small-update interior point methods the iteration bound is O ip nlog n ¢ ; which is currently the best-known bound for primal-dual IPMs.
Intron-exon structure of ubiquitin c-terminal hydrolase-L1.

Parkinson's disease (PD) is a common neurodegenerative movement disorder characterized by tremor, bradykinesia, postural instability and muscular rigidity. Neuropathologically, it is defined by cell loss in the substantia nigra associated with the presence of intraneuronal inclusions called Lewy bodies (LB) and processes engorged with proteinaceous material, the Lewy neurites. The recent identification of mutations in the a-synuclein gene in some familial forms of PD 3 ' 6 and the demonstration of accumulation of the protein in Lewy bodies and Lewy neurites 7 suggest that abnormal protein aggregation may cause the disease. In addition to asynuclein, LBs contain ubiquitin, proteasomal subunits 2 and ubiquitin C-terminal hydrolase-Ll, 5 pointing to a potential participation of the ubiquitin-proteasome degradation pathway in the onset of the disease. We confirmed this hypothesis by identifying a missense mutation in the ubiquitin C-terminal hydrolase LI (UCH-L1) gene in a German family with an autosomal dominant form of PD. 4 UCH-L1 is highly specific for neurons and cells of the diffuse neuroendocrine system, and represents 1% to 5% of the total brain protein extract. 8 Northern blot analysis reveals a 1.3-kb brain-specific transcript broadly represented in all areas of the brain tested, particularly in the substantia nigra (Fig. 1). Enzymes belonging to the ubiquitin C-terminal hydrolases family can remove small amides and esters at the carboxyl terminus of ubiquitin and have been shown to hydrolyze peptides and small proteins similarly (reviewed in 9). They contribute to the pool of free monomeric ubiquitin molecules by hydrolysing the ubiquitin polymeric proprotein or ubiquitin-ribosomal fusion proteins during the maturation of the ribosome. 9 The Ile93Met mutation observed in 2 PD patients 4 causes a partial loss of catalytic activity of the UCH-L1 enzyme which could induce aberrations in the degradation pathway and lead to aggregation of proteins. To permit the rapid screening for mutations and assess the UCH-L1 role in PD, we have established specific amplification assays for all of its coding exons.
The UT Austin Villa 2003 Four-Legged Team

The UT Austin Villa RoboCup 2003 Four-Legged Team was a new entry in the ongoing series of RoboCup legged league competitions. The team development began in mid-January of 2003, at which time none of the team members had any familiarity with the Aibos. Without using any RoboCup-related code from other teams, we entered a team in the American Open competition at the end of April, and met with some success at the annual RoboCup competition that took place in Padova, Italy at the beginning of July. In this paper, we describe aspects of (i) our development process and (ii) the technical details of its end result, the UT Austin Villa team. Complete details in both regards are available in our team technical report [1].
Towards a mobile social data commons

This paper discusses how born-digital cultural material can be opened up for research. We focus in particular on the grey area between private mobile phone data and its publication and use for research and beyond. We report on the results of the `Empowering Data Citizens' (EDC) project, which is a collaboration between King's College London and the Open Data Institute. The work builds on the project Our Data Ourselves (http://big-social-data.net/), which studies the content we generate on our mobile devices, what we call big social data (BSD), and explores the possibilities of its ethical storage.