Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordination of V2G and distributed wind power using the storage-like aggregate PEV model

A plug-in electric vehicle (PEV) fleet utilizing vehicle-to-grid (V2G) technology, i.e., a V2G fleet, can behave as a storage system, e.g., promoting integration of distributed wind power resources. However, because the PEVs' behaviors are stochastic and a V2G fleet's population is large, three technical difficulties hinder the utilization of V2G: charging demand forecasting; ahead-of-time charge and discharge scheduling; real-time charge and discharge power dispatching. This paper utilizes a storage-like aggregate model (SLAM) of a V2G fleet that employs aggregated parameters to represent energy and power constraints of the entire PEV population, and therefore reduces the difficulty of forecasting. Then, a stochastic joint power scheduling strategy for a distributed wind generation and a V2G fleet based on the SLAM is proposed aiming to promote the integration of distributed wind power by V2G technology, which has low computational burden. A real-time heuristic strategy is designed to efficiently dispatch the power schedules to PEVs and guarantee the modeling accuracy of SLAM and effectiveness of the proposed power scheduling strategy.
Software caching and computation migration in Olden

The goal of the Olden project is to build a system that provides parallelism for general purpose C programs with minimal programmer annotations. We focus on programs using dynamic structures such as trees, lists, and DAGs. We demonstrate that providing both software caching and computation migration can improve the performance of these programs, and provide a compile-time heuristic that selects between them for each pointer dereference. We have implemented a prototype system on the Thinking Machines CM-5. We describe our implementation and report on experiments with ten benchmarks.
Process modelling of discontinuous long fibre carbon/polyether ether ketone composites: Defect prediction

A numerical model was developed to predict the defect formation during processing of compression moulded discontinuous long fibre carbon/polyether ether ketone composites. The model inputs are the material's temperature-dependant properties (through-thickness modulus and thermal shrinkage), the temperature distribution of the part during cooling and the applied moulding pressure. The material properties of carbon/polyether ether ketone prepreg were measured during cooling from melt using thermal analyses. The model was employed to identify regions on manufactured panels where pressure could be lost during cooling, which are prone to defect formation. Validation was performed by comparing the predicted defect areas against those found on flat panels moulded at pressures ranging from 10 to 110 bar. The model was then employed in a case study to show the importance of the cooling strategy in order to prevent defects on complex-shape components.
Unifying DVFS and offlining in mobile multicores

Energy efficiency is a primary design criterion of the modern smartphone due to limitations in battery capacity. Multi-core processors are now commonplace in these devices, which adds a new dimension, the number cores used, to energy management. In this paper we investigate how the mechanisms of frequency scaling and core offlining interact, and how to use them to reduce energy consumption. We find surprising differences in the characteristics of latest-generation smartphones, specifically in the importance of static power. This implies that policies that work well on one processor can lead to poor results on another. We propose a simple policy that integrates core offlining with frequency scaling and implement it in a Linux-based frequency governor called medusa. We show that, despite its simplicity, medusa obtains energy savings that are as good or better than governors presently shipping on the studied phones and approaches the static optimal setting.
A Telepresence-Robot Approach for Efficient Coordination of Swarms

In this paper we explore a novel perspective on surveillance robotics, which is based on a coordination principle of honeybees, and on the integration of an autonomous telepresence robot in such system. Coordination principles, based on biological systems such as ant, bee and termite colonies, show several properties which are essential to multi-robot surveillance, including low computation load, robustness, scalability and adaptability. In this paper we aim to improve on the efficiency of such a robotic swarm by taking a human in the loop by means of a telepresence robot. The human operator controlling the telepresence robot will aim to speed up the convergence of the swarm. The experiments, which evaluate the proposed multi- robot coordination system both in simulation and on real robots, show how the telepresence robot substantially increases the efficiency of the process.
An Algorithmic Approach for Learning Concept Identification and Relevant Resource Retrieval in Focused Subject Domains

Modern digital world has enormous amount of data on the Web easily accessible anywhere and anytime. This ease of access also creates new paradigms of education and learning. The modernday learners have access to lot many and in fact one of the best learning materials created in any part of the world. However, despite abundant availability of material, we still lack appropriate systems that can automatically identify learning needs of a user and present them with the most relevant (and best-quality) material to pursue. This paper presents our algorithmic design towards this goal. We propose a text processing-based system that works in three phases: (a) identifying learning needs of a learner; (b) retrieving relevant materials and ranking them; and (c) presenting material to learner and monitoring the learning process. We use know-how of text processing, information retrieval, recommender systems and educational psychology and presents useful and relevant learning material (including slides, videos, articles etc.) to a learner in a focused subject domain. Our initial experiments have produced promising results. We are working towards a Web-scale deployment of the system.
Adaptive Decision Feedback Equalization for Multi-Gbps Serial Links:Challenges and Opportunities

This editorial briefly examines challenges in design of adaptive decision feedback equalizers for multi-Gbps serial links. The state-of-the-art of serial links over wire channels is briefly reviewed. The impairment of wire channels at high frequencies and their effect on the performance of serial links are examined. It is followed with a close examination of channel equalization techniques to combat inter-symbol interference. Challenges and opportunities in design of adaptive feedback equalizers including timing constraints, power consumption, adaptive references for error generation and thresholds for logic state determination, data-DFE, eye-opening monitor DFE, and edge-DFE, floating tap DFE are examined.
Unusual variants of Alexander's disease

The purpose of this study was to describe unusual variants of Alexander's disease. We studied 10 patients who did not meet previously established magnetic resonance imaging (MRI) criteria for Alexander's disease, but for whom this diagnosis was considered because of Rosenthal fibers at histological examination or presence of some MRI features suggestive of Alexander's disease. Sequence analysis of the GFAP gene was performed. In eight patients, MRI results showed predominantly posterior fossa lesions, especially multiple tumor‐like brainstem lesions. One patient had asymmetrical frontal white matter abnormalities and basal ganglia abnormalities. One patient (Patient 10) developed degeneration of the frontal white matter. In nine patients, a mutation was found that was concluded to be pathogenic, because the mutation was de novo (five patients), a known mutation was found (two patients), or assembly of the glial fibrillary acidic protein was abnormal in cultured cells (two patients). In Patient 10, a DNA variation was found that was also present in the patient's clinically unaffected father and was concluded to be a polymorphism. In conclusion, DNA diagnostics is warranted in patients who display MRI features suggestive of Alexander's disease, even if they do not meet the full set of previously established MRI criteria. Ann Neurol 2005;57:327–338
Automatic Estimation of the LSA Dimension

Nowadays the size of collections of information achieved considerable sizes, making the finding and exploration of a particular subject hard to achieve. One way to solve this problem is through text classification, where a theme or category is assigned to a text based on the analysis of its content. However, existing approaches to text classification require some effort and a high level of knowledge on this subject by the users, making them inaccessible to the common user. Another problem of current approaches is that they are optimized for a specific problem and can not easily be adapted to another context. In particular, unsupervised methods based on the LSA algorithm require users to define the dimension to use in the algorithm. In this paper we describe an approach to make the use of text classification more accessible to common users, by providing a formula to estimate the dimension of the LSA based on the number of texts used during the bootstrapping process. Experimental results show that our formula for estimation of the LSA dimension allows us to create unsupervised solutions able to achieve results similar to supervised approaches.
Maximum-rate, Minimum-Decoding-Complexity STBCs from Clifford Algebras

It is well known that Space-Time Block Codes (STBCs) from orthogonal designs (ODs) are single-symbol decodable/symbol-by-symbol decodable (SSD) and are obtainable from unitary matrix representations of Clifford algebras. However, SSD codes are obtainable from designs that are not orthogonal also. Recently, two such classes of SSD codes have been studied: (i) Coordinate Interleaved Orthogonal Designs (CIODs) and (ii) Minimum-Decoding-Complexity (MDC) STBCs from Quasi-ODs (QODs). Codes from ODs, CIODs and MDC-QODs are mutually non-intersecting classes of codes. The class of CIODs have {\it non-unitary weight matrices} when written as a Linear Dispersion Code (LDC) proposed by Hassibi and Hochwald, whereas several known SSD codes including CODs have {\it unitary weight matrices}. In this paper, we obtain SSD codes with unitary weight matrices (that are not CODs) called Clifford Unitary Weight SSDs (CUW-SSDs) from matrix representations of Clifford algebras. A main result of this paper is the derivation of an achievable upper bound on the rate of any unitary weight SSD code as $\frac{a}{2^{a-1}}$ for $2^a$ antennas which is larger than that of the CODs which is $\frac{a+1}{2^a}$. It is shown that several known classes of SSD codes are CUW-SSD codes and CUW-SSD codes meet this upper bound. Also, for the codes of this paper conditions on the signal sets which ensure full-diversity and expressions for the coding gain are presented. A large class of SSD codes with non-unitary weight matrices are obtained which include CIODs as a proper subclass.
Estimation of diffuse and specular appearance

To account for the variability of object appearance due to differences in illumination, attention has recently been focused on representing the set of images for all possible lighting conditions. Approaches that address this problem have primarily focused on lighting differences for diffuse reflection using the Lambertian model; however specular reflections can additionally present considerable disparity in appearance. We present a method for representing illumination appearance for both diffuse and specular reflections for objects of uniform surface roughness using four photometric images. This approach uses separation of reflection components, extracts surface reflectances and roughness, and produces arbitrary lighting images without explicit computation of surface shape. Experimental results demonstrate the validity of the proposed method for constructing diffuse and specular appearances.
Cultivation and engineering of a software metrics program

Abstract. This paper reports from a case study of an organization that implements a software metrics program to measure the effects of its improvement efforts. The program measures key indicators of all completed projects and summarizes progress information in a quarterly management report. The implementation turns out to be long and complex, as the organization is confronted with dilemmas based on contradictory demands and value conflicts. The process is interpreted as a combination of a rational engineering process in which a metrics program is constructed and put into use, and an evolutionary cultivation process in which basic values of the software organization are confronted and transformed. The analysis exemplifies the difficulties and challenges that software organizations face when bringing known principles for software metrics programs into practical use. The article discusses the insights gained from the case in six lessons that may be used by Software Process Improvement managers in implementing a successful metrics program.
Characterization of RFID Strap Using Single-Ended Probe

Radio frequency identification (RFID) strap attachment modality is more reliable, low cost, and easy to assemble, and therefore, it becomes increasingly more popular in RFID tag designs. This paper presents a single-ended probe method with power transmission coefficient compensation for the characterization of RFID straps. Approximate identification of the read/write threshold power and impedance is based on the charge status of voltage multipliers and charge pumps instead of on the read/write-modulated commands. For comparison purposes, the conventional source-pull system is also briefly reviewed and applied to verify the measurement results of absorbing power and impedance of RFID straps using the presented method. An enhanced source-pull system, named RFID source-pull system, for an RFID strap that can accurately measure the threshold power and impedance for read/write-modulated commands is also constructed for verifying the presented method. Alien and Texas Instruments (TI) straps are used for measurement examples in this paper. It is found that the measurement results of both RFID straps obtained by the presented method agree well with those by the conventional source-pull system and the RFID source-pull system. The single-ended probe method can measure the approximate read/write threshold power and impedance of the RFID strap with minimum operating procedures; furthermore, the complicated radio frequency (RF) facilities are not required. Obtaining the read/write threshold power and impedance of RFID straps allows designers to estimate the maximum read range of the designed RFID tag in advance. Therefore, the implemented cost and design cycle times can substantially be reduced.
Data monitoring in high-performance clusters for computing applications

The shared memory in a LAN-like environment (SMiLE) project at Lehrstuhl fur Rechnertechnik und Rechnerorganisation, Technical University of Munich (LRR-TUM) investigates in high-performance cluster computing using system area networks. In the context of this project, a hardware monitor is being developed to observe the system area network (SAN) traffic. This hardware monitor is, therefore, capable of delivering detailed information about the run-time communication behavior of applications running on SMiLE clusters. The central part of this monitor consists of a content-addressable counter array managing a small working set of the most recently referenced memory regions.
Architecture and implementation of an associative memory using sparse clustered networks

Associative memories are alternatives to indexed memories that when implemented in hardware can benefit many applications such as data mining. The classical neural network based methodology is impractical to implement since in order to increase the size of the memory, the number of information bits stored per memory bit (efficiency) approaches zero. In addition, the length of a message to be stored and retrieved needs to be the same size as the number of nodes in the network causing the total number of messages the network is capable of storing (diversity) to be limited. Recently, a novel algorithm based on sparse clustered neural networks has been proposed that achieves nearly optimal efficiency and large diversity. In this paper, a proof-of-concept hardware implementation of these networks is presented. The limitations and possible future research areas are discussed.
Novel Molecular Imaging Approaches to Abdominal Aortic Aneurysm Risk Stratification

Selection of patients for abdominal aortic aneurysm repair is currently based on aneurysm size, growth rate, and symptoms. Molecular imaging of biological processes associated with aneurysm growth and rupture, for example, inflammation and matrix remodeling, could improve patient risk stratification and lead to a reduction in abdominal aortic aneurysm morbidity and mortality. 18F-fluorodeoxyglucose-positron emission tomography and ultrasmall superparamagnetic particles of iron oxide magnetic resonance imaging are 2 novel approaches to abdominal aortic aneurysm imaging evaluated in clinical trials. A variety of other tracers, including those that target inflammatory cells and proteolytic enzymes (eg, integrin &agr;v&bgr;3 and matrix metalloproteinases), have proven effective in preclinical models of abdominal aortic aneurysm and show great potential for clinical translation.
ICln159 Folds into a Pleckstrin Homology Domain-like Structure

ICln is a multifunctional protein involved in regulatory mechanisms as different as membrane ion transport and RNA splicing. The protein is water-soluble, and during regulatory volume decrease after cell swelling, it is able to migrate from the cytosol to the cell membrane. Purified, water-soluble ICln is able to insert into lipid bilayers to form ion channels. Here, we show that ICln159, a truncated ICln mutant, which is also able to form ion channels in lipid bilayers, belongs to the pleckstrin homology (PH) domain superfold family of proteins. The ICln PH domain shows unusual properties as it lacks the electrostatic surface polarization seen in classical PH domains. However, similar to many classical PH domain-containing proteins, ICln interacts with protein kinase C, and in addition, interacts with cAMP-dependent protein kinase and cGMP-dependent protein kinase type II but not cGMP-dependent protein kinase type Iβ. A major phosphorylation site for all three kinases is Ser-45 within the ICln PH domain. Furthermore, ICln159 interacts with LSm4, a protein involved in splicing and mRNA degradation, suggesting that the ICln159 PH domain may serve as a protein-protein interaction platform.
Expression of D-Amino Acid Oxidase (DAO/DAAO) and D-Amino Acid Oxidase Activator (DAOA/G72) during Development and Aging in the Human Post-mortem Brain

In the brain, D-amino acid oxidase (DAO/DAAO) mainly oxidizes D-serine, a co-agonist of the N-methyl-D-aspartate (NMDA) receptors. Thus, DAO can regulate the function of NMDA receptors via D-serine breakdown. Furthermore, DAO activator (DAOA)/G72 has been reported as both DAOA and repressor. The co-expression of DAO and DAOA genes and proteins in the human brain is not yet elucidated. The aim of this study was to understand the regional and age span distribution of DAO and DAOA (mRNA and protein) in a concomitant manner. We determined DAO and DAOA mRNA and protein expression across six brain regions in normal human post-mortem brain samples (16 weeks of gestation to 91 years) using quantitative real-time reverse transcription-polymerase chain reaction and enzyme-linked immunosorbent assay. We found higher expression of DAO mRNA in the cerebellum, whereas lower expression of DAO protein in the cerebellum compared to the other brain regions studied, which suggests post-transcriptional regulation. We detected DAOA protein but not DAOA mRNA in all brain regions studied, suggesting a tightly regulated expression. To understand this regulation at the transcriptional level, we analyzed DNA methylation levels at DAO and DAOA CpG sites in the cerebellum and frontal cortex of control human post-mortem brain obtained from Gene Expression Omnibus datasets. Indeed, DAO and DAOA CpG sites in the cerebellum were significantly more methylated than those in the frontal cortex. While investigating lifespan effects, we found that DAO mRNA levels were positively correlated with age <2 years in the cerebellum and amygdala. We also detected a significant positive correlation (controlled for age) between DAO and DAOA protein in all of the brain regions studied except for the frontal cortex. In summary, DAO and DAOA expression in the human brain are both age and brain region dependent.
Export Barriers and Competitiveness of Small and Medium-sized Enterprise in Developing Countries: Case study in Ethiopian Leather Footwear Manufacturing Firms

Export is one of the most important business activities that play a significant role for economic development of nations. Hence, this study aimed to investigate the export barriers and export competitiveness of the Ethiopian Leather Footwear manufacturing firms in particular and the industry in general. Purposively, 100 respondents were selected from 15 exporting firms in the leather industry. In addition, interview was held with some top managers and owners to collect more detail information. The survey data is analyzed using factor analysis and MDS techniques. Using factor analysis, 10 conceptually linked components were empirically identified. Both factor loadings and factor score coefficient results were used to interpretation the factor analysis result. With different perceived intensity, all the export barriers such as government policy, human resource, financial, product quality, marketing knowledge and information, competition barriers are important in impeding the export competitiveness of the industry. Going by the MDS, due to different perceived intensity of the barriers, four clusters of firms were constructed. Hence, based on the topmost barriers, the management of each exporting firms need to give focus to boost the competitiveness level. This implies that policy makers of the exporting firms, the industry and the government in general need to apply differentiated approaches.
A study on regression spline based local minima approach for gaussian noise reduction in images

The study proposes a novel image denoising algorithm based on the regression splines (RS) for the restoration of images corrupted with the Gaussian noise. In the proposed algorithm, overlapping window of dimension 5×5 have been considered to replace the central pixel value with the local minimum of both diagonal pixels and central row and column pixels of the processing window. Selection of minimum of approximate pixel value helps in reducing the noise diffusion to the neighboring pixels. The proposed algorithm has been found to function efficiently for the Gaussian noise removal while preserving the fine image details.