Miracle-dz/UniFAR-FTUs huggingface dataset:
CLERECO INSTITUTIONAL REPOSITORY

With the advent of solid-state storage systems, NAND ﬂash memories are becoming a key storage technology. However, they suffer from serious reliability and endurance issues during the operating lifetime that can be handled by the use of appropriate error correction codes (ECC) in order to reconstruct the information when needed. Adaptable ECCs may provide the ﬂexibility to avoid worst-case reliability design thus leading to improved performance. However, a way to control such adaptable ECCs strength is required. This paper proposes FLARES, an algorithm able to adapt the ECC correction capability of each page of a ﬂash based on a ﬂash RBER prediction model and on a measurement of the number of errors detected in a given time window. FLARES has been fully implemented within the YAFFS 2 ﬁlesystem under the Linux operating system. This allowed us to perform an extensive set of simulations on a set of standard benchmarks that highlighted the beneﬁt of FLARES on the overall storage subsystem performances.
STDP as Presynaptic Activity Times Rate of Change of Postsynaptic Activity Approximates Backpropagation

We show that Langevin Monte Carlo Markov chain inference in an energy-based model with latent variables has the property that the early steps of inference, starting from a stationary point, correspond to propagating error gradients into internal layers, similar to backpropagation. The backpropagated error is with respect to output units that have received an outside driving force pushing them away from the stationary point. Backpropagated error gradients correspond to temporal derivatives with respect to the activation of hidden units. These lead to a weight update proportional to the product of the presynaptic firing rate and the temporal rate of change of the postsynaptic firing rate. Simulations and a theoretical argument suggest that this rate-based update rule is consistent with those associated with spike-timing-dependent plasticity. The ideas presented in this article could be an element of a theory for explaining how brains perform credit assignment in deep hierarchies as efficiently as backpropagation does, with neural computation corresponding to both approximate inference in continuous-valued latent variables and error backpropagation, at the same time.
Evolutionary Training of Hybrid Systems of Recurrent Neural Networks and Hidden Markov Models

networks (RNNs) inspired by hidden Markov models (HMMs). We train the hybrid architecture using genetic algorithms to learn and represent dynamical systems. We train the hybrid architecture on a set of deterministic finite-state automata strings and observe the generalization performance of the hybrid architecture when presented with a new set of strings which were not present in the training data set. In this way, we show that the hybrid system of HMM and RNN can learn and represent deterministic finite-state automata. We ran experiments with different sets of population sizes in the genetic algorithm; we also ran experiments to find out which weight initializations were best for training the hybrid architecture. The results show that the hybrid architecture of recurrent neural networks inspired by hidden Markov models can train and represent dynamical systems. The best training and generalization performance is achieved when the hybrid architecture is initialized with random real weight values of range-15 to 15.
Chapter 2 Isotope-Aided Methods for Biological NMR Spectroscopy : Past , Present , and Future

This chapter starts by providing a historical background of our research endeavors over the past half-century to develop various isotope-aided methods in biological NMR spectroscopy, since innovations bloom only on the rich ground cultivated by previous investigators. We then focused on the stereo-array isotope-labeling (SAIL) method, one of our recent accomplishments, which culminates the isotope-aided NMR technologies for structural studies of proteins from various aspects: accurate structural determinations of large proteins, elaboration for automated structural determination, highly efficient and versatile residue-selective methyl labeling with newly developed auxotrophic E. coli strains, large-amplitude slow-breathing motion (LASBM) as revealed by the aromatic ring flipping of the residues in ligand-binding interfaces, and applications of the deuterium-induced C-NMR isotope shift to investigate the hydrogen exchange phenomena of side-chain polar groups. Meanwhile, the expected role of NMR spectroscopy has been rapidly shifting from structure determinations to dynamics studies of biologically interesting targets, such as membrane proteins and larger protein complexes. The dynamic aspects of protein–protein and protein–ligand interactions are closely related to their biological functions and can be efficiently studied by using proteins residue selectively labeled with amino acids bearing optimized labeling M. Kainosho (&) Graduate School of Science and Engineering, Tokyo Metropolitan University, 1-1 Minami-ohsawa, Hachioji 192-0397, Tokyo, Japan e-mail: kainosho@tmu.ac. jp M. Kainosho Y. Miyanoiri Structural Biology Research Center, Graduate School of Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8602, Japan e-mail: y-miyanoiri@protein.osaka-u.ac. jp Y. Miyanoiri Research Center for State-of-the-Art Functional Protein Analysis, Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita 565-0871, Osaka, Japan M. Takeda Department of Structural BioImaging, Faculty of Life Sciences, Kumamoto University, 5-1, Oe-honmachi, Chuo-ku, Kumamoto 862-0973, Japan e-mail: takeda@structbiol.com © Springer Nature Singapore Pte Ltd. 2018 The Nuclear Magnetic Resonance Society of Japan, Experimental Approaches of NMR Spectroscopy, https://doi.org/10.1007/978-981-10-5966-7_2 37 patterns, prepared by cellular expression. We are absolutely confident that biological NMR spectroscopy will continually develop with further innovations of isotope-labeling technologies in the coming era, featuring ultrahigh field spectrometers beyond 1 GHz.
AIS Electronic Library (AISeL)

The process of digital transformation entails changes in both the processes, practices and routines of organizations. This flux of changes, brings to question the conventional notion of documented business processes and highlights the importance for agility and flexibility in the configuration of organizational processes during digital transformation. Prior research provides a thorough view on the value of meticulous and preplanned business processes as well as capabilities for identifying and capitalizing on new opportunities. However, these studies typically focus on organizations operating in regular business conditions, while studies examining these concepts in periods of digital transformation process are still relatively few. In this study, we focus on the digital transformation processes in a manufacturing technology company that seeks to expand its business to providing data based services for its customers. Our study draws from an empirical base of 60 interviews, supported with company documents, participation in strategy workshops, and several meetings for over 16 months. The paper describes changes that the company is implementing, both in its organizational structure, technology infrastructure, as well as in its business processes. Our observations highlight the difficulty of relaxing the control of business processes and technology infrastructures, required for flexibility, and creation of new processes. The paper advances four principles of agility during digital transformation - mind-fulness, light touch routines, flexible infrastructure and ambidextrous organization.
On becoming a supervisee: Preparation for learning in a supervisory relationship.

Trainees' experiences in supervision are crucial to the development of psychotherapy skills. However, they usually enter the supervisory situation with little understanding of the process. This paper proposes a more structured form of presupervisory preparation than generally exists in graduate training programs. Guidelines for incorporating such instruction are provided. Topics for discussion, including salient issues and perspectives in the supervision literature as well as research findings, are outlined. Potential pitfalls and strategies for trainees to deal with dissatisfactions are identified.
Hierarchical asset tracking system using IEEE 802.15.4a radio in container terminals

Due to the increase in the volume of international trading, throughput of logistics terminals has emerged as an important issue. It is important to ship and unload container cargo rapidly to improve throughput. The real-time location tracking of various vehicle assets is a major factor for efficient port terminal processing. In this paper, we will describe a system that we designed for asset tracking using IEEE 802.15. 4a-based wireless communications for the efficient management of vehicles in the logistics terminals, and we will provide data from performance evaluations obtained from a real terminal environment. We applied a hierarchical-based tracking technique to overcome a non-line of sight (NLOS) problem. We improved the tracking estimation accuracy of yard tractors between container stacks by measuring a transfer crane's precise location using communication between the light tower's readers and crane's mobile readers. We improved the tracking estimation accuracy of yard tractors between container stacks using a transfer crane's precision location. For measuring the crane's precision location, a mobile reader was attached to the crane. The mobile reader communicates with readers attached to light towers so that line of sight (LOS) is guaranteed. The proposed tracking system was installed at Gwangyang International Terminal, where we carried out an asset tracking performance evaluation. The results of the evaluation in a real logistics terminal confirmed that the tracking system has an estimated tracking error of approximately 6.53 m.
Modelling And Simulation Of Photovoltaic Array Fed Induction Motor Based On Field Oriented Control And Single Stage MPPT Inverter For Water Pumping System

This paper presents a photovoltaic (PV) system for water pumping. The water pumping system consists of PV array, a voltage source inverter (VSI) and 3 phase induction motor that drives the centrifugal pump. For the purpose of improving the efficiency of overall system, the incremental conductance method algorithm based Maximum Power Point Tracker (MPPT) and field oriented control scheme is applied to control the single stage of VSI fed the three phase induction motor. An incremental conductance method is used for extraction of maximum power and the vector control is used to drive motor which provides smooth startup and reducing of starting current. The proposed system could be employed in agricultural irrigation under any operating condition of varying natures of solar irradiances and temperatures. Simulation results using MATLAB/SIMULINK show that the performance of the PV pumping system in transient as well as in steady state is quite satisfactory. Keywords; Photovoltaic array, MPPT, field oriented control, Centrifugal water pump.
Chapter 15 Fault-Tolerance & Paxos

How do you create a fault-tolerant distributed system? In this chapter we start out with simple questions, and, step by step, improve our solutions until we arrive at a system that works even under adverse circumstances, Paxos. Definition 15.1 (node). We call a single actor in the system node. In a computer network the computers are the nodes, in the classical client-server model both the server and the client are nodes, and so on. If not stated otherwise, the total number of nodes in the system is n. Model 15.2 (message passing). In the message passing model we study distributed systems that consist of a set of nodes. Each node can perform local computations, and can send messages to every other node. Remarks: • We start with two nodes, the smallest number of nodes in a distributed system. We have a client node that wants to " manipulate " data (e.g., store, update,. . .) on a remote server node. 1: Client sends commands one at a time to server Model 15.4 (message loss). In the message passing model with message loss, for any specific message, it is not guaranteed that it will arrive safely at the receiver. Remarks: • A related problem is message corruption, i.e., a message is received but the content of the message is corrupted. In practice, in contrast to message loss, message corruption can be handled quite well, e.g. by including additional information in the message, such as a checksum.
WRITTEN TESTIMONY OF DAVID WAGNER, PH.D. COMPUTER SCIENCE DIVISION UNIVERSITY OF CALIFORNIA, BERKELEY BEFORE THE COMMITTEE ON OVERSIGHT AND GOVERNMENT REFORM, SUBCOMMITTEE ON INFORMATION POLICY, CENSUS, AND NATIONAL ARCHIVES

Chairman Clay, Ranking Member Turner, committee members, thank you for the opportunity to testify today. My name is David Wagner. I am an associate professor of computer science at U.C. Berkeley. My area of expertise is in computer security and the security of electronic voting. I have an A.B. (1995, Mathematics) from Princeton University and a Ph.D. (2000, Computer Science) from U.C. Berkeley. I have published two books and over 90 peer-reviewed scientiﬁc papers. In past work, I have analyzed the security of cellphones, web browsers, wireless networks, and other kinds of widely used information technology. I am a member of the ACCURATE center, a multi-institution, interdisciplinary academic research project funded by the National Science Foundation 1 to conduct novel scientiﬁc research on improving election technology. I am a member of the California Secretary of State’s Voting Systems Technology Assessment Advisory Board and of the Election Assistance Commission’s Technical Guidelines Development Committee (TGDC) 2 . I have served as a poll worker in my county
Cytology Image Analysis Techniques Towards Automation: Systematically Revisited

Cytology is the branch of pathology which deals with the microscopic examination of cells for diagnosis of carcinoma or inflammatory conditions. Automation in cytology started in the early 1950s with the aim to reduce manual efforts in diagnosis of cancer. The inflush of intelligent technological units with high computational power and improved specimen collection techniques helped to achieve its technological heights. In the present survey, we focus on such image processing techniques which put steps forward towards the automation of cytology. We take a short tour to 17 types of cytology and explore various segmentation and/or classification techniques which evolved during last three decades boosting the concept of automation in cytology. It is observed, that most of the works are aligned towards three types of cytology: Cervical, Breast and Lung, which are discussed elaborately in this paper. The user-end systems developed during that period are summarized to comprehend the overall growth in the respective domains. To be precise, we discuss the diversity of the state-of-the-art methodologies, their challenges to provide prolific and competent future research directions inbringing the cytology-based commercial systems into the mainstream.
Research of semantic caching for LDQ in mobile network

Location-dependent query is becoming very popular in mobile environments. To improve system performance, many semantic cache models are proposed. In this paper, we first define a new structure of semantic segments index. Then we analyze the detailed query processing and FAR algorithm. For overcoming the shortage of predicting future location in FAR, we propose a new improved algorithm (RBF-FAR) as replacement policy, which use RBFNN to predicate next location instead of velocity in FAR. Using this new replacement policy, we propose a new model for LDQ semantic cache. The experiment results show that new model, on the basis of RBF-FAR, is more flexible and effective at reducing average response time network-load used in LDQ than FAR model
Refined mapping of loss of heterozygosity in Chinese sporadic gastric carcinoma

The aim of this study is to explore precise deleted regions where the candidate tumor suppressor genes might be located in Chinese sporadic gastric carcinoma. By searching in Genothon, NCBI and GDB databases, 145 polymorphic microsatellite markers were chosen, at a mean density of approximately one marker every 2 - 4 cM, covering 15 chromosomes. These polymorphic microsatellite markers in gastric carcinoma and adjacent tissue were analyzed via PCR. PCR products were submitted to electrophoresis on an ABI 3730 DNA sequencer. Genemapper3.2 software was used for LOH (Loss of Heterozygosity) scanning and analysis. Comparison between LOH frequency and clinicopathological factors was performed by Fisher’s exact test. 26 refined regions were mapped as candidate regions for TSGs (Tumor suppression genes) in Chinese sporadic gastric cancer. Associations between LOH and clinical information indicated that 6 loci was associated with pTNM stage, 5 with Lauren's type, 4 with lymph nodes metastasis and another 2 with distant metastasis. Through refined deletion mapping, 26 candidate regions, where TSGs may be located, were found and 17 loci were proposed to be used as clinical markers in Chinese sporadic gastric cancer. Keywords: Gastric carcinoma, refined mapping, loss of heterozygosity (LOH), tumor suppressor genes (TSGs), tumor markers African Journal of Biotechnology Vol. 9(35), pp. 5754-5761, 30 August, 2010
Rabi Waves in Carbon Nanotubes

QED-model for the multichain qubit system with interactions of qubits and chains between themselves on the example of the system of $\sigma$-polarons in carbon zigzag nanotubes, interacting with quantized EM-field, is considered analytically. The possibility of experimental detection of Rabi waves in conventional stationary optical experiments for any quasi-1D system with strong electron-photon interaction is predicted.
VizBin-an application for reference-independent visualization and human-augmented binning of metagenomic data Microbiome Sample

Cedric C Laczny (cedric.laczny@uni.lu) Tomasz Sternal (sternal.tomasz@gmail.com) Valentin Plugaru (valentin.plugaru@gmail.com) Piotr Gawron (piotr.gawron@uni.lu) Arash Atashpendar (arash.atashpendar.001@student.uni.lu) Houry Hera Margossian (houry.margossian.001@student.uni.lu) Sergio Coronado (sergio.coronado@ext.uni.lu) Laurens van der Maaten (lvdmaaten@gmail.com) Nikos Vlassis (nikos.vlassis@gmail.com) Paul Wilmes (paul.wilmes@uni.lu)
Genetic Programming Approach to Hierarchical Production Rule Discovery

— Automated discovery of hierarchical structures in large data sets has been an active research area in the recent past. This paper focuses on the issue of mining generalized rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses flat rules as initial individuals of GP and discovers hierarchical structure. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy. Experimental results are presented to demonstrate the performance of the proposed algorithm.
The Information Systems Identity Crisis: Focusing on High-Visibility and High-Impact Research

This paper presents an alternative view of the Information Systems identity crisis described recently by Benbasat and Zmud (2003). We agree with many of their observations, but we are con cerned with their prescription for IS research. We critique their discussion of errors of inclusion and exclusion in IS research and highlight the potential misinterpretations that are possible from a literal 1Ron Weber was the accepting senior editor for this paper. Iris Vessey and Rudy Hirschheim served as reviewers. reading of their comments. Our conclusion is that following Benbasat and Zmud's nomological net will result in a micro focus for IS research. The results of such a focus are potentially dangerous for the field. They could result in the elimination of IS from many academic programs. We present an alternative set of heuristics that can be used to assess what lies within the domain of IS scholar ship. We argue that the IS community has a powerful story to tell about the transformational impact of information technology. We believe that a significant portion of our research should be macro studies of the impact of IT. It is important for academic colleagues, deans, and managers to understand the transformational power of the technology. As IS researchers with deep knowl edge of the underlying artifact, we are best positioned to do such research.
The Economic Effects of a Marathon as a Sport Tourism Event

Marathons are sport tourism events taking place in many cities around the globe. Economic impacts studies have shown that there exist positive economic effects for the host city but the economics literature has questioned the applied methodology. Costbenefit analyses and general equilibrium approaches have shown that the economic effects may not be positive. This study reviews this literature using an eclectic approach. It emphasizes the long term impacts of promoting exports and attracting foreign direct investment. The Athens marathon is used as a case study.
Learning from Imperfect Demonstrations through Dynamics Evaluation

—Standard imitation learning usually assumes that demonstrations are drawn from an optimal policy distribution. However, in real-world scenarios, every human demonstration may exhibit nearly random behavior and collecting high-quality human datasets can be quite costly. This requires imitation learning can learn from imperfect demonstrations to obtain robotic policies that align human intent. Prior work uses confidence scores to extract useful information from imperfect demonstrations, which relies on access to ground truth rewards or active human supervision. In this paper, we propose a dynamics-based method to evaluate the data confidence scores without above efforts. We develop a generalized confidence-based imitation learning framework called Confidence-based Inverse soft-Q Learning (CIQL), which can employ different optimal policy matching methods by simply changing object functions. Experimental results show that our confidence evaluation method can increase the success rate by 40 . 3% over the original algorithm and 13 . 5% over the simple noise filtering
Optimizing Company Finances Using Business Intelligence in Accounting

Business intelligence is the process of collecting, analyzing, and interpreting business data to help companies make informed decisions and improve business performance. In accounting, business intelligence is used to understand financial data and monitor overall business performance. This study aims to link the relationship between business intelligence in accounting. Novelty in this research is the methodology in developing business intelligence research in accounting, as it is relatively new to be applied in accounting and business. An approach that combines quantitative and qualitative analysis is very important in achieving the optimization of company finances. Companies must ensure that they have the right strategies and techniques in place to collect, analyze and utilize this information to achieve their financial goals.