Miracle-dz/UniFAR-FTUs huggingface dataset:
Discussion on risk assessment of energy internet

Energy Internet is a deep fusion concept consisting of electric power system, electrification transportation system and natural gas system linked by information and communication technology (ICT). It is a new focus in academia and industry. Facing its fast development stage, it is also exposed to greater potential risk. The paper introduces the recent research development status of Energy Internet, and then establishes a new Energy Internet safety risk assessment framework. The framework evaluates the risks of electric power system, electrification transportation system, natural gas system as well as the system cyber security by three-dimensional risk assessment method. It assesses the risk from three dimensions such as adequacy evaluation dimension, probability risk dimension, and the risk source dimension. Since it is still the initial stage of Energy Internet, there remains a lot of basic research to be further developed.
Acoustic emotion recognition: A benchmark comparison of performances

In the light of the first challenge on emotion recognition from speech we provide the largest-to-date benchmark comparison under equal conditions on nine standard corpora in the field using the two pre-dominant paradigms: modeling on a frame-level by means of hidden Markov models and supra-segmental modeling by systematic feature brute-forcing. Investigated corpora are the ABC, AVIC, DES, EMO-DB, eNTERFACE, SAL, SmartKom, SUSAS, and VAM databases. To provide better comparability among sets, we additionally cluster each database's emotions into binary valence and arousal discrimination tasks. In the result large differences are found among corpora that mostly stem from naturalistic emotions and spontaneous speech vs. more prototypical events. Further, supra-segmental modeling proves significantly beneficial on average when several classes are addressed at a time.
Scalable Semantic Version Control for Linked Data Management

Linked Data is the Semantic Web’s established standard for publishing and interlinking data. When authors collaborate on a data set, distribution and tracking of changes are crucial aspects. Several approaches for version control were presented in this area each focusing on different aspects and bounded to different limitations. In this paper we present an approach for semantic version control for dynamic Linked Data based on a delta-based storage strategy and on-demand reconstruction of historic versions. The approach is intended for large data sets and supports targeted and cross-version queries. The approach was implemented prototypically on top of a scalable triple store and tested with a generated data set based on parts of DBpedia with several million triples and thousands of versions.
SmartOrch: an adaptive orchestration system for human-machine collectives

Web-based collaborative systems, where most computation is performed by human collectives, have distinctly different requirements from traditional workflow orchestration systems, as humans have to be mobilised to perform computations and the system has to adapt to their collective behaviour at runtime. In this paper, we present a social orchestration system called SmartOrch, which has been designed specifically for collective adaptive systems in which human participation is at the core of the overall distributed computation. SmartOrch provides a flexible and customisable workflow composition framework that has multi-level optimisation capabilities. These features allow us to manage the uncertainty that collective adaptive systems need to deal with in a principled way. We demonstrate the benefits of SmartOrch with simulation experiments in a ridesharing domain. Our experiments show that SmartOrch is able to respond flexibly to variation in collective human behaviour, and to adapt to observed behaviour at different levels. This is accomplished by learning how to propose and route human-based tasks, how to allocate computational resources when managing these tasks, and how to adapt the overall interaction model of the platform based on past performance. By proposing novel, solid engineering principles for these kinds of systems, SmartOrch addresses shortcomings of previous work that mostly focused on application-specific, non-adaptive solutions.
2D and 3D high-resolution imaging to reconstruct the microstructure of clay media

Clayrock formations are under consideration to serve as host formation and geological barriers for radioactive waste repositories due to their favorable properties (low permeability, low diffusion coefficient, high retention capacity for radionuclides…). The currently on-going European CATCLAY project (EURATOM FP7) (www.catclay.org) is focused on understanding the fundamental processes governing the diffusion-driven transport of cationic species in natural clayrocks. The project combines modeling with experimental studies of migration of three cations (Sr +2 , Zn +2 and Eu +3 ) in a monophasic compacted clay (illite) system, considered to be an analogy for the clay matrix constituting clay-rocks, and three different clayrocks (Callovo-Oxfordian argilites (FR), Opalinus Clay (CH), Boom Clay (BE)). Part of the experimental studies are focused on the small scale structural (µm to nm) properties of the different materials in order to determine how the spatial distribution of mineral and pores at small scales can influence diffusion driven transport of cations. The present study focuses on compacted illite properties in hopes of extending this study to the natural clayrocks. Clayrocks are more complex and include other mineral phases such carbonates or quartz. Our approach is mainly based on imaging the small scale structural organization of compacted illite material and analyzing the resulting images in order to extract information on pore space geometry/morphology and mineral spatial distribution, in order to use them as input data for transport modelling. Small-scale investigations were performed using two high-resolution imaging techniques:
OPN06-1: A WDM Optical Packet Switch based on Wavelength Converter Blocks with Heterogeneous Conversion Capability

The wavelength-division-multiplexing (WDM) optical packet switches (OPSes) using wavelength converters (WCs) have been focused to improve the optical network performance significantly. Among them, a shared-per-node (SPN) switch architecture has been considered as a way to utilize WCs efficiently. In this paper, we propose a new switch control algorithm for the architecture, which reduces the total number of wavelength conversion degree (WCD) of a wavelength converter block (WCB). The algorithm also reduces the number of WCs with higher WCD while minimizing the packet loss by wavelength contention at outbound links. Based on this algorithm, we then design a flexible WDM OPS architecture. The proposed algorithm, different from the previous works, focuses on using the heterogeneous wavelength converter blocks (HeWCBs), where a HeWCB consists of WCs with different WCD. The proposed HeWCBs are motivated by the observation that the conventional WDM OPS architecture seldom uses long-range convertible WCs. The architecture shows the same packet loss probability as that of the homogeneous WCBs (HoWCBs) consisting of WCs with the same WCD. Through analysis and simulation, it is shown that the WDM OPS architecture using a combination of WCs of WCD less than or equal to d achieves the same performance as using HoWCBs with WCs of WCD d.
Modeling 802.11e for data traffic parameter design

This paper introduces a finite load multi-class 802.11e EDCF model that is simple enough to be explicitly solvable. The model is nevertheless flexible enough to model the impact of 802.11e parameters on the prioritization of realistic traffic. We emphasize that a modeling framework which allows nonsaturated sources is essential in the study of realistic traffic. We apply the model to a situation of practical interest: competing TCP flows in an infrastructure network. The model allows us to make a principled selection of 802.11e parameters to resolve problems highlighted in this scenario. Model predictions and parameter selections are validated against simulation and experiment. The model is shown to be accurate and the parameters effective.
Assessing the Value of a Societal-Level Sustainability Index for Macromarketing Research

As the Internet makes secondary data increasingly more accessible and less costly to obtain, the need for methods to evaluate the reliability and validity of such data has grown accordingly. In efforts to harness the surge of data at the country level, researchers have created indexes to more efficiently track the performance of societies on a variety of dimensions. Large-scale global indexes like the Sustainable Society Index (SSI), published biannually since 2006 by the Sustainable Society Foundation, have the potential to provide valuable insights into important issues related to macromarketing, sustainability, and quality of life. The primary purpose of this article is to assess the value of a societal-level index for macromarketing research. By evaluating the reliability, internal validity and external validity of a societal-level index, such as the SSI, researchers will be better informed about the importance of such an index, but will also understand how the protocol used in this study can be applied to other indexes. In order to gauge the external validity of the SSI, the study also evaluates and utilizes three other established secondary data sources in conjunction with the SSI. These include: (1) the Legatum Prosperity Index; (2) Transparency International’s Corruption Perceptions Index; and (3) the Euromoney Country Risk Index.
Hemodynamic and Biochemical Alterations in Dogs with Lymphoma after Induction of Chemotherapy

Background Doxorubicin is a common antineoplastic agent with dose‐dependent cardiotoxic adverse effects, and pre‐existing myocardial dysfunction is a contraindication to its use. Objectives To systematically define the hemodynamic and biochemical alterations in dogs undergoing chemotherapy for newly diagnosed lymphoma and assess the reversibility of these alterations with fluid administration. Animals Twenty‐one client‐owned dogs with newly diagnosed lymphoma were evaluated 1 week after induction of chemotherapy. Underlying degenerative valve disease was exclusionary. Eighteen healthy age‐ and weight‐matched dogs were used as controls. Methods Physical examination, blood pressure by Doppler, echocardiography, and biochemical evaluation (routine serum biochemistry, plasma renin activity and aldosterone concentrations, plasma and urine osmolalities, and urine electrolyte concentrations) were measured in dogs with lymphoma and compared to controls. Dogs with lymphoma received crystalloids IV at 6 mL/kg/h for 24 hours. All variables were reassessed at 4 and 24 hours. Deuterium oxide dilution and bromide dilution were used to determine total body water and extracellular water space, respectively. Results Baseline echocardiograms showed significantly smaller chamber dimensions in dogs with lymphoma compared to controls. These changes were reversed by fluid administration. Systolic blood pressure and urine sodium concentration were significantly increased, and bromide dilution space, PCV, urine specific gravity, and urine potassium concentration were significantly decreased compared to controls. Conclusion and Clinical Importance Echocardiographic and biochemical abnormalities in dogs with lymphoma appear consistent with volume depletion, and may be the result of systemic hypertension and subsequent pressure natriuresis.
An Ambiguity Aversion Framework of Security Games under Ambiguities

Security is a critical concern around the world. Since resources for security are always limited, lots of interest have arisen in using game theory to handle security resource allocation problems. However, most of the existing work does not address adequately how a defender chooses his optimal strategy in a game with absent, inaccurate, uncertain, and even ambiguous strategy profiles' payoffs. To address this issue, we propose a general framework of security games under ambiguities based on Dempster-Shafer theory and the ambiguity aversion principle of minimax regret. Then, we reveal some properties of this framework. Also, we present two methods to reduce the influence of complete ignorance. Our investigation shows that this new framework is better in handling security resource allocation problems under ambiguities.
Robust Matrix Completion via Alternating Projection

Matrix completion aims to find the missing entries from incomplete observations using the low-rank property. Conventional convex optimization based techniques for matrix completion minimize the nuclear norm subject to a constraint on the Frobenius norm of the residual. However, they are not robust to outliers and have a high computational complexity. Different from the existing schemes based on solving a minimization problem, we formulate matrix completion as a feasibility problem. An alternating projection algorithm (APA) is devised to find a feasible point in the intersection of the low-rank constraint set and fidelity constraint set. To achieve resistance to outliers, the fidelity constraint set is modeled as an $\ell _p$ -ball, where the ball center corresponds to the observed data. Furthermore, there is no stepsize within the framework of APA. Convergence of the APA is analyzed and the local linear convergence rate is established. Simulation results demonstrate the efficiency, accuracy, and outlier robustness of the APA.
The assertive profile of the Bulgarian students in computer science and computer engineering

Different points of view on the nature and content of the assertiveness are followed in this paper. The main purpose is to study the assertive profile of Bulgarian students in computer science and computer engineering by analyzing the components of assertiveness. Research was performed using testing methods. It was found that the level of expressivity of this personal quality among subjects were above-average level.
Rett syndrome management with Snoezelen or controlled multi-sensory stimulation. A review

Rett syndrome is a neurological disorder resulting from an X-linked dominant mutation. It is characterized by a variety of physical and perceptual disabilities, resulting in a need for constant therapy programs to be administered on a regular basis throughout life. Resistance to physical activity has driven the authors in a search for new intervention techniques which might improve the ability to cope while reducing difficulty in handling an external physical facilitator. Snoezelen, or multi-sensory environment, can provide a soothing environment appealing to the child or adolescent with Rett syndrome while at the same time improving physical abilities. The article reviews Rett syndrome typical phenotype and suggests suitable activities that might take place in the multi-sensory environment.
4D Kelly-Lochbaum junction-based digital filter

This paper introduces a four-dimension (4D) Kelly-Lochbaum junction-based digital filter, whose classical one-dimension (1D) configuration has been extensively used in speech signal processing. The proposed 4D circuit realization uses a minimum number of delay elements. As a result, the dimension of the state-vector, of the derived 4D state-space model, is minimal and its 4D transfer function has the all-pass property which is evident from a provided first-order example.
Layered Coding with Block Turbo Code for Broadcasting and Multicasting Services

This paper presents an efficient layered coding scheme using block turbo codes for multimedia broadcasting and multicasting services (MBMS). Because of unidirectional nature of MBMS, we cannot use adaptive coding and modulation schemes using channel quality information from a return link. The layered coding scheme consists of more than two codes that are concatenated and can be separated, and thus the receiver selects a suitable demodulation and decoding scheme for the channel condition. In this paper we demonstrate an example of layered coding scheme using 2D/3D block turbo codes combined with M-ary modulation.
The delivery of therapeutic oligonucleotides

The oligonucleotide therapeutics field has seen remarkable progress over the last few years with the approval of the first antisense drug and with promising developments in late stage clinical trials using siRNA or splice switching oligonucleotides. However, effective delivery of oligonucleotides to their intracellular sites of action remains a major issue. This review will describe the biological basis of oligonucleotide delivery including the nature of various tissue barriers and the mechanisms of cellular uptake and intracellular trafficking of oligonucleotides. It will then examine a variety of current approaches for enhancing the delivery of oligonucleotides. This includes molecular scale targeted ligand-oligonucleotide conjugates, lipid- and polymer-based nanoparticles, antibody conjugates and small molecules that improve oligonucleotide delivery. The merits and liabilities of these approaches will be discussed in the context of the underlying basic biology.
Crowdsourcing computing resources for shortest-path computation

Crowdsourcing road network data, i.e., involving users to collect data including the detection and assessment of changes to the road network graph, poses a challenge to shortest-path algorithms that rely on preprocessing. Hence, current research challenges lie with improving performance by adequately balancing preprocessing with respect to fast-changing road networks. In this work, we take the crowdsourcing approach further in that we solicit the help of users not only for data collection, but also to provide us their computing resources. A promising approach is parallelization, which splits the graph into chunks of data that may be processed separately. This work extends this approach in that small-enough chunks allow us to use browser-based computing to solve the pre-computation problem. Essentially, we aim for a Web-based navigation service that whenever users request a route, the service uses their browsers for partially preprocessing a large, but changing road network. The paper gives performance studies that highlight the potential of the browser as a computing platform and showcases a scalable approach, which almost eliminates the computing load on the server.
A method of identifying and locating encoded artificial points automatically in close range digital photogrammetry

Using coding artificial point can match the homonymy points during multiple images automatically in the photogrammetry. A method of identifying and locating 8 bits encoded points automatically has been presented in this paper. The experimental results show that the accuracy of center coordinate of encoding point reaches sub-pixel level. And decoding method is simple. The robust of decoding and recognition rate is high. So it can meet the requirements of close range photogrammetry fully.
Building a phylogenetic tree

Several artificial organisms are shown on the cards. These drawings have been prepared so that it is easy to find differences and to distinguish between the characteristics of each organism. No numerical data are needed to distinguish between characteristics such as long and short birds’ tails. In contrast, with real organisms a researcher must usually collect numerical data and subjectively decide how to group characteristics or, alternatively, use advanced mathematical tools. Such problems do not exist when analysing molecular data. Phylogenetic trees for even distantly-related organisms may be prepared using amino acid or nucleotide sequence data. The differences between the sequences in different organisms indicate evolutionary distances. Wojciech Grajkowski
The Application of DEA/AHP Method to Supplier Selection

The selection of suppliers is an important part of enterprise strategy, so it is very important to evaluate suppliers using proper methods. This paper firstly constructs comparison matrix using DEA, then assesses the alternatives using AHP. In this method the known data is fully used and the influence of personal factor is avoided. Finally an example is used to prove the method effective.
Key Decisions in Strategic New Product Development for Small Software Product Businesses

Small companies in the software product business risk rework and market failure due to shortcomings in integrating a strategic perspective into management of product development. Because little guidance exists for helping such companies link business strategy with product development, we propose that improvement should begin with helping the key persons maintain the ‘big picture’ in their everyday bustle of multiple, sometimes even contradictory roles and responsibilities. We present a framework of key decisions to address in order to reconcile the perspectives of business strategy and product development, based on strategic management, new product development and software engineering literature. The framework was tested and refined as part of a study aiming to improve the NPD management practices in three companies. Our findings indicate that using the framework helped raise the companies’ awareness of the importance of long-term planning in product development and yielded relevant improvement suggestions regarding daily product development activities.
Perceived Effectiveness of Conflict Management Strategies in Dating Relationships.

2 LIST OF TABLES . 7 Chapter
Sub-Nyquist 1 bit sampling system for sparse multiband signals

Efficient sampling of wideband analog signals is a hard problem because their Nyquist rates may exceed the specifications of the analog-to-digital converters by magnitude. Modulated Wideband Converter (MWC) is a known method to sample sparse multiband signals below the Nyquist rate and the precision recovery relies on high precision quantization of samples which may take a great bit-budget. This paper proposes an alternative system that optimizes space utilization by applying comparator in sub-Nyquist sampling system. The system first multiplies the signal by a bank of periodic waveforms, and then it performs lowpass filtering, sampling and quantization through the comparator which just keeps the sign information. And we introduce a corresponding algorithm for perfect recovery. The primary design goals are efficient hardware implementation and low bit-budget. We compare our system with MWC to prove its advantages in condition of fixed bit-budget, particularly in low levels of input signal to noise ratio.