Quantum Hall Effect on Dirac electrons in modulated graphene

Theoretical investigation of Dirac electrons in electrically modulated graphene under perpendicular magnetic field B is presented. We have carried out a detailed study of modulation effect on Dirac electrons, which determine its electrical transport properties. The periodic potential broadens the Landau levels (LL), which oscillate with magnetic field B and a comparison made with two-dimensional electron gas system (2DEGS). We have found the effect of Hall conductivity on electronic conduction in this system. In addition, we find that Hall conductivity exhibits Weiss oscillations and Shubnikov de Haas (SdH) oscillations. The effect of temperature and the period of periodic potential on these oscillations are studied in this work. Furthermore, an integral quantum Hall effect in graphene is also discussed

Leveraging intelligence from network CDR data for interference aware energy consumption minimization

Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo

To Study the Effect of Boundary Conditions and Disorder in Spin Chain Systems Using Quantum Computers

Condensed matter physics plays a crucial role in modern scientific research and technological advancements, providing insights into the behavior of materials and their fundamental properties. Understanding complex phenomena and systems in condensed matter physics poses significant challenges due to their inherent intricacies. Over the years, computational approaches have been pivotal in unraveling the mysteries of condensed matter physics, but they face limitations when dealing with large-scale systems and simulating quantum effects accurately. Quantum simulation and quantum computation techniques have emerged as promising tools for addressing these limitations, offering the potential to revolutionize our understanding of condensed matter physics. In this paper, we focus on the simulation of Anderson localization in the Heisenberg spin chain systems and explore the effects of disorder on closed and open chain systems using quantum computers

Energy efficiency in heterogeneous wireless access networks

In this article, we bring forward the important aspect of energy savings in wireless access networks. We specifically focus on the energy saving opportunities in the recently evolving heterogeneous networks (HetNets), both Single- RAT and Multi-RAT. Issues such as sleep/wakeup cycles and interference management are discussed for co-channel Single-RAT HetNets. In addition to that, a simulation based study for LTE macro-femto HetNets is presented, indicating the need for dynamic energy efficient resource management schemes. Multi-RAT HetNets also come with challenges such as network integration, combined resource management and network selection. Along with a discussion on these challenges, we also investigate the performance of the conventional WLAN-first network selection mechanism in terms of energy efficiency (EE) and suggest that EE can be improved by the application of intelligent call admission control policies

A SON Solution for Sleeping Cell Detection Using Low-Dimensional Embedding of MDT Measurements

Automatic detection of cells which are in outage has been identified as one of the key use cases for Self Organizing Networks (SON) for emerging and future generations of cellular systems. A special case of cell outage, referred to as Sleeping Cell (SC) remains particularly challenging to detect in state of the art SON because in this case cell goes into outage or may perform poorly without triggering an alarm for Operation and Maintenance (O&M) entity. Consequently, no SON compensation function can be launched unless SC situation is detected via drive tests or through complaints registered by the affected customers. In this paper, we present a novel solution to address this problem that makes use of minimization of drive test (MDT) measurements recently standardized by 3GPP and NGMN. To overcome the processing complexity challenge, the MDT measurements are projected to a low-dimensional space using multidimensional scaling method. Then we apply state of the art k-nearest neighbor and local outlier factor based anomaly detection models together with pre-processed MDT measurements to profile the network behaviour and to detect SC. Our numerical results show that our proposed solution can automate the SC detection process with 93 accuracy

Control and data channel resource allocation in OFDMA heterogeneous networks

This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macro cells and small cells sharing the same frequency band. Dense deployment of small cells overlaid by a macro layer is considered to be one of the most promising solutions for providing hotspot coverage in future 5G networks. The focus is to devise an optimised policy for small cells’ access to the shared spectrum, in terms of their transmissions, in order to keep small cell served users sum data rate at high levels while ensuring that certain level of quality of service (QoS) for the macro cell users in the vicinity of small cells is provided. Both data and control channel constraints are considered, to ensure that not only the macro cell users’ data rate demands are met, but also a certain level of Bit Error Rate (BER) is ensured for the control channel information. Control channel reliability is especially important as it holds key information to successfully decode the data channel. The problem is addressed by our proposed linear binary integer programming heuristic algorithm which maximises the small cells utility while ensuring the macro users imposed constraints. To further reduce the computational complexity, we propose a progressive interference aware low complexity heuristic solution. Discussion is also presented for the implementation possibility of our proposed algorithms in a practical network. The performance of both the proposed algorithms is compared with the conventional Reuse-1 scheme under different fading conditions and small cell loads. Results show a negligible drop in small cell performance for our proposed schemes, as a trade-off for ensuring all macro users data rate demands, while Reuse-1 scheme can even lead up to 40 % outage when control region of the small cells in heavily loaded

A Study of Performance of Regulated Market and Its Benefits

The main objective of regulating the market is protecting the interest of producer, sellers increase the standards of the local Markets where the first exchange of the commodities take its place. In order to attain and reach the object of each regulated markets hence the establishment of Market committees are executed which is consisting of the representatives of the cultivators, dealers, locals’ bodies, co-operative, shops, sellers, and the selected state government candidates. Producers are mostly considered in these committees. The committee of market, would consist of (12) to (18) members, subjected to the size of the market. Regulated Markets have many advantages and benefits such as the growers are encouraged to bring their produce straight to the markets, Growers are protected from the manipulation of market functionaries, Market costs are definite and obligatory, Growers are ensured with better prices, Obtainability of the staffs for the disbursement of disputes, Facilities like platforms for the sale transactions, parking storage facilities, rest houses, and etc. are made available, Growers have accessibility to up-to-date, market information and Marketing costs are lowered and the producer share in consumer will increase. The regulated market functions are to deliver marketing facilitates, marketing of notified crops regulation, as well as to create a yards of the required infrastructural facilities

Relationship between risk factors and in-hospital mortality due to myocardial infarction by educational level: a national prospective study in Iran

Introduction: Since no hospital-based, nationwide study has been yet conducted on the association between risk factors and in-hospital mortality due to myocardial infarction (MI) by educational level in Iran, the present study was conducted to investigate relationship between risk factors and in-hospital mortality due to MI by educational level. Methods: In this nationwide hospital-based, prospective analysis, follow-up duration was from definite diagnosis of MI to death. The cohort of the patients was defined in view of the date at diagnosis, hospitalization and the date at discharge (recovery or in-hospital death due to MI). 20750 patients hospitalized for newly diagnosed MI between April, 2012 and March, 2013 comprised sample size. Totally, 2511 deaths due to MI were obtained. The data on education level (four-level) were collected based on years of schooling. To determine in-hospital mortality rate and the associated factors with mortality, seven statistical models were developed using Cox proportional hazards models. Results: Of the studied patients, 9611 (6.1%) had no education. in-hospital mortality rate was 8.36 (95% CI: 7.81-8.9) in women and 6.12 (95% CI: 5.83-6.43) in men per 100 person-years. This rate was 5.56 in under 65-year-old patients and 8.37 in over 65-year-old patients. This rate in the patients with no, primary, high school, and academic education was respectively 8.11, 6.11, 4.85 and 5.81 per 100 person-years. Being woman, chest pain prior to arriving in hospital, lack of thrombolytic therapy, right bundle branch block, ventricular tachycardia, smoking and ST-segment elevation myocardial infarction were significantly associated with increased hazard ratio (HR) of death. The adjusted HR of mortality was 1.27 (95% CI: 1.06-1.52), 0.93 (95% CI: 0.77-1.13), 0.72 (95% CI: 0.57-0.91) and 0.82 (95% CI: 0.66-1.01) in the patients with respectively illiterate, primary, secondary and high school education compared to academic education. Conclusion: A disparity was noted in post-MI mortality incidence in different educational levels in Iran. HR of death was higher in illiterate patients than in the patients with academic education. Identifying disparities per educational level could contribute to detecting the individuals at high risk, health promotion and care improvement by relevant planning and interventions in clinics and communities