An improvement and a fast DSP implementation of the bit flipping algorithms for low density parity check decoder

<span lang="EN-US">For low density parity check (LDPC) decoding, hard-decision algorithms are sometimes more suitable than the soft-decision ones. Particularly in the high throughput and high speed applications. However, there exists a considerable gap in performances between these two classes of algorithms in favor of soft-decision algorithms. In order to reduce this gap, in this work we introduce two new improved versions of the hard-decision algorithms, the adaptative gradient descent bit-flipping (AGDBF) and adaptative reliability ratio weighted GDBF (ARRWGDBF). An adaptative weighting and correction factor is introduced in each case to improve the performances of the two algorithms allowing an important gain of bit error rate. As a second contribution of this work a real time implementation of the proposed solutions on a digital signal processors (DSP) is performed in order to optimize and improve the performance of these new approchs. The results of numerical simulations and DSP implementation reveal a faster convergence with a low processing time and a reduction in consumed memory resources when compared to soft-decision algorithms. For the irregular LDPC code, our approachs achieves gains of 0.25 and 0.15 dB respectively for the AGDBF and ARRWGDBF algorithms.</span>

Complexity Assessments for Decidable Fragments of Set Theory. I: A Taxonomy for the Boolean Case*

We report on an investigation aimed at identifying small fragments of set theory (typically, sublanguages of Multi-Level Syllogistic) endowed with polynomial-time satisfiability decision tests, potentially useful for automated proof verification. Leaving out of consideration the membership relator ∈ for the time being, in this paper we provide a complete taxonomy of the polynomial and the NP-complete fragments involving, besides variables intended to range over the von Neumann set-universe, the Boolean operators ∪ ∩ \, the Boolean relators ⊆, ⊈,=, ≠, and the predicates ‘• = Ø’ and ‘Disj(•, •)’, meaning ‘the argument set is empty’ and ‘the arguments are disjoint sets’, along with their opposites ‘• ≠ Ø and ‘¬Disj(•, •)’. We also examine in detail how to test for satisfiability the formulae of six sample fragments: three sample problems are shown to be NP-complete, two to admit quadratic-time decision algorithms, and one to be solvable in linear time.

Developing practical digital e-learning tools in times of Covid-19: The experience of our Pathology department (Preprint)

BACKGROUND E-learning is the use of Internet technologies to enhance knowledge and performance. Due to the education disruption caused by the spread of the Coronavirus disease 2019 (COVID 19), our aim was developing digital tools representing practical educational documents answering the questions asked by pathologists in training in front of important and complicated situations faced in the daily practice, thus enabling particularly pathologists in training, medical students and doctors in general, to better understand the diagnostic process by developing simplified decision algorithms while ensuring the management of small and precious samples, and therefore the relevance of treatment options and patient management. OBJECTIVE In our Pathology department, we have started utilizing this didactic method of learning way before COVID-19 pandemic, by developing digital tools, allowing medical students and residents in training to learn at their own pace. We believe a hybrid model of education has significant benefits, as traditional offline learning and e-learning are complementary. METHODS Self- training kits were designed to provide practical educational tools that offer a clear and rational approach for residents in training to face challenges in their daily practice, by using numorous diagnosis algorithms, this enables them to better understand the diagnostic process. The project was planned in multiple phases; it has two main components, a medical component that comprises the scientific content and the informatic one that allows the user to access the final version. RESULTS The digital tools contain definitions and general recent information on the subject selected, clinical, biological and radiological study to help managing pathological cases in a multidisciplinary approach, and most importantly, a detailed histopathological chapter, rich in simplified decision algorithms, tables and illustrative practical clinical cases. A final chapter is dedicated to the evaluation which aims to identify the specific needs of each user. Once inserted, users browse the kit’s content and clicks on the file "index.html" to find the different sections on the horizontal menu bar. CONCLUSIONS Self-training kits help controlling the pace and sequence of instruction and make personally meaningful choices which should help residents in training to understand and orient towards a pertinent diagnosis in order to improve the management of small and precious samples, and therefore the relevance of treatment options and patient management.

Risk Analysis of the Power System Protection Delayed Triggers in Power Network Integrating Renewable Energy Sources in Fault Dynamic States

In the development of power systems it is indicated very often, that transformation of power systems should be carried out in accordance with the idea of energy democracy. This will develop energy communities, that are trying to meet energy needs by using local renewable generation sources. This may result with a temporary low load on the MV lines connecting the community grid and the power system. Such state may cause incorrect operation of power protection systems. This can cause an extended protection operation time, due to decision algorithms inactivity at low values of measurement currents. Therefore, the detailed MV lines overcurrent digital protection model and a dynamic model of the power network were developed. The simulation results are showing that the settings of the parameters activating the protection decision algorithms affect their operation time in dynamic conditions. The conclusion is that the development of the power protection automatics must be carried out in the same time (preferably in advance) with the change of the power system operation model. This is very important for future power systems with high penetration energy communities and renewable generation sources.

Using LTE-Sim in New Hanover Decision Algorithm for 2-Tier Macrocell-Femtocell LTE Network

Deployment of mini macrocell base stations can also be referred to as femtocells improve quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with in-depth focus on the most important aspect of mobility management - handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research, are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength based handover decision algorithm.