The necessity of data allocation: A plea for a private law (property law) perspective

Clarifying the legal status of data is one of the major issues and challenges the European legislator has to deal and cope with while establishing a legal frame for a European data economy. Albeit at the beginning of the policy-making process the idea of creating a data right (on non-personal data) was on the agenda of the European Commission, this idea now seems to be have been abandoned. Instead, the focus actually lies on the creation of access and management regimes (e.g. Open Data Directive, Proposal for a European Data Governance Act). This approach seems, from a private law perspective, questionable, since the access right is inherently connected to – or more precisely, flowing from – an allocative right (in its most classical form: ownership). This article is a plea for a private law, or more precisely, property law perspective, namely for the creation of an allocative data right. It explores why the access approach from a private law perspective appears to be inconsistent and outlines the contours of such allocative right. In this context, contemporary property law theories are also assessed, since it is primarily property law which shall serve as the doctrinal background and framework for the envisaged allocative data right.

Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning

Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides a significant gain (almost 40%) with 10.7% compared to the linear model with the lowest RMSE (Root Mean Squared Error) 17.01%. The solution can be adopted as a part of the data allocation algorithm implemented in the telemetry devices equipped with the 4G radio interface, or, after the adjustment, the NB-IoT (Narrowband Internet of Things), to maximize the reliability of the services in harsh indoor or urban environments. Presented results also prove the existence of the inverse proportional dependence between the number of hidden layers and the number of historical samples in terms of the obtained RMSE. The increase of the historical data memory allows using models with fewer hidden layers while maintaining a comparable RMSE value for each scenario, which reduces the total computational cost.

Data Optimization in IoT-Assisted Sensor Networks on Cloud Platform

This article presents a new scheme for data optimization in IoT assister sensor networks. The various components of IoT assisted cloud platform are discussed. In addition, a new architecture for IoT assisted sensor networks is presented. Further, a model for data optimization in IoT assisted sensor networks is proposed. A novel Membership inducing Dynamic Data Optimization (MIDDO) algorithm for IoT assisted sensor network is proposed in this research. The proposed algorithm considers every node data and utilized membership function for the optimized data allocation. The proposed framework is compared with two stage optimization, dynamic stochastic optimization and sparsity inducing optimization and evaluated in terms of performance ratio, reliability ratio, coverage ratio and sensing error. It was inferred that the proposed MIDDO algorithm achieves an average performance ratio of 76.55%, reliability ratio of 94.74%, coverage ratio of 85.75% and sensing error of 0.154.

Life Cycle Assessment of Network Traffic: A Review of Challenges and Possible Solutions

The environmental impact of Industry 4.0 and related technologies remains relatively unknown, with little research devoted to investigating the impact on sustainability aspects, resulting in a greater need for climate reporting. However, impacts of data transmission have historically been the least studied part of the information and communication technology sector, and there is currently no consensus on how to correctly assess it. In an attempt to guide process development within the area in the hopes that future life cycle assessments will be created, this study sought to identify, examine, and address potential challenges that might occur when assessing the environmental impact of network traffic during its life cycle. Through a combination of a literature review and semi-systematic research interviews with identified experts within the field of research, several areas in the form of knowledge gaps, unsolved methodological issues, and areas in need of further development were identified and assessed. The results show that eight key challenges exist in the areas of system boundaries, data collection methods, energy intensity metrics, transparency and data availability, age of data, allocation procedures, assumptions, and limited coverage of impact categories. Several approaches to address said challenges are presented, as well as areas in need of further investigation. It is furthermore suggested that the sector should strive to agree upon several parameters of significance to enable future harmonized life cycle studies of network traffic.

Optimization of data allocation in hierarchical memory for blocked shortest paths algorithms

This paper is devoted to the reduction of data transfer between the main memory and direct mapped cache for blocked shortest paths algorithms (BSPA), which represent data by a D[M×M] matrix of blocks. For large graphs, the cache size S = δ×M2, δ < 1 is smaller than the matrix size. The cache assigns a group of main memory blocks to a single cache block. BSPA performs multiple recalculations of a block over one or two other blocks and may access up to three blocks simultaneously. If the blocks are assigned to the same cache block, conflicts occur among the blocks, which imply active transfer of data between memory levels. The distribution of blocks on groups and the block conflict count strongly depends on the allocation and ordering of the matrix blocks in main memory. To solve the problem of optimal block allocation, the paper introduces a block conflict weighted graph and recognizes two cases of block mapping: non-conflict and minimum-conflict. In first case, it formulates an equitable color-class-size constrained coloring problem on the conflict graph and solves it by developing deterministic and random algorithms. In second case, the paper formulates a problem of weighted defective color-count constrained coloring of the conflict graph and solves it by developing a random algorithm. Experimental results show that the equitable random algorithm provides an upper bound of the cache size that is very close to the lower bound estimated over the size of a complete subgraph, and show that a non-conflict matrix allocation is possible at δ = 0.5 for M = 4 and at δ = 0.1 for M = 20. For a low cache size, the weighted defective algorithm gives the number of remaining conflicts that is up to 8.8 times less than the original BSPA gives. The proposed model and algorithms are applicable to set-associative cache as well.

Efficacy of Home Anticonvulsant Administration for Second-Line Status Epilepticus Treatment

Objective:To investigate whether receiving a second-line anticonvulsant medication that is part of a patient’s home regimen influences outcomes in benzodiazepine-refractory convulsive status epilepticus.Methods:Using the Established Status Epilepticus Treatment Trial (ESETT) data, allocation to a study drug included in the patient’s home anticonvulsant medication regimen was compared to receipt of an alternative second-line study medication. The primary outcome was cessation of clinical seizures with improved consciousness by 60 minutes after study drug initiation. Secondary outcomes were seizure cessation adjudicated from medical records and adverse events. We performed inverse probability of treatment-weighted [IPTW] logistic regressions.Results:Of 462 patients, 232 (50%) were taking 1-2 of the 3 study medications at home. The primary outcome was observed in 39/89 (44%) patients allocated to their home medication versus 76/143 (53%) allocated to a non-home medication (IPTW odds ratio [OR] 0.66, 95% confidence interval [CI] 0.39-1.14). The adjudicated outcome occurred in 37/89 (42%) patients versus 82/143 (57%) respectively (IPTW OR 0.52, 95% CI 0.30-0.89). There was no interaction between study levetiracetam and home levetiracetam and there were no differences in adverse events.Conclusion:There was no difference in the primary outcome for patients who received a home medication versus non-home medication. However, the retrospective evaluation suggested an association between receiving a non-home medication and seizure cessation.Classification of Evidence:This study provides Class II evidence that for patients with refractory convulsive status epilepticus, use of a home second-line anticonvulsant compared to a non-home anticonvulsant did not significantly affect the probability of stopping seizures.

Characteristics of the Urinary Proteome in Women with Overactive Bladder Syndrome: A Case-Control Study

Despite an estimated prevalence of 13% in women, the exact etiology of non-neurogenic overactive bladder syndrome is unclear. The aim of our study was to gain a better understanding of the pathophysiology of female overactive bladder syndrome by mapping the urinary proteomic profile. We collected urine samples of 20 patients with overactive bladder syndrome and of 20 controls. We used mass spectrometric analysis for label-free quantitation, Swissprot human database for data search, Scaffold for data allocation and the Reactome Knowledgebase for final pathway enrichment analysis. We identified 1897 proteins at a false discovery rate of 1% and significance level p < 0.001. Thirty-seven significant proteins of the case group and 53 of the control group met the criteria for further pathway analysis (p < 0.0003 and Log2 (fold change) >2). Significant proteins of the overactive bladder group were, according to the 25 most relevant pathways, mainly involved in cellular response to stress and apoptosis. In the control group, significant pathways mainly concerned immunological, microbial-protective processes and tissue- elasticity processes. These findings may suggest a loss of protective factors as well as increased cellular response to stress and apoptosis in overactive bladder syndrome.