Cluster-based cooperative subcarrier sensing using antenna diversity-based weighted data fusion

Cooperative spectrum sensing (CSS) is used in cognitive radio (CR) networks to improve the spectrum sensing performance in shadow fading environments. Moreover, clustering in CR networks is used to reduce reporting time and bandwidth overhead during CSS. Thus, cluster-based cooperative spectrum sensing (CBCSS) has manifested satisfactory spectrum sensing results in harsh environments under processing constraints. On the other hand, the antenna diversity of multiple input multiple output CR systems can be exploited to further improve the spectrum sensing performance. This paper presents the CBCSS performance in a CR network which is comprised of single- as well as multiple-antenna CR systems. We give theoretical analysis of CBCSS for orthogonal frequency division multiplexing signal sensing and propose a novel fusion scheme at the fusion center which takes into account the receiver antenna diversity of the CRs present in the network. We introduce the concept of weighted data fusion in which the sensing results of different CRs are weighted proportional to the number of receiving antennas they are equipped with. Thus, the receiver diversity is used to the advantage of improving spectrum sensing performance in a CR cluster. Simulation results show that the proposed scheme outperforms the conventional CBCSS scheme

Cooperative subcarrier sensing using antenna diversity based weighted virtual sub clustering

The idea of cooperation and the clustering amongst cognitive radios (CRs) has recently been focus of attention of research community, owing to its potential to improve performance of spectrum sensing (SS) schemes. This focus has led to the paradigm of cluster based cooperative spectrum sensing (CBCSS). In perspective of high date rate 4th generation wireless systems, which are characterized by orthogonal frequency division multiplexing (OFDM) and spatial diversity, there is a need to devise effective SS strategies. A novel CBCSS scheme is proposed for OFDM subcarrier detection in order to enable the non-contiguous OFDM (NC-OFDM) at the physical layer of CRs for efficient utilization of spectrum holes. Proposed scheme is based on the energy detection in MIMO CR network, using equal gain combiner as diversity combining technique, hard combining (AND, OR and Majority) rule as data fusion technique and antenna diversity based weighted clustering as virtual sub clustering algorithm. Results of proposed CBCSS are compared with conventional CBCSS scheme for AND, OR and Majority data fusion rules. Moreover the effects of antenna diversity, cooperation and cooperating clusters are also discussed

Personal and sociocultural factors as barriers to exercise among female university students. A cross-sectional study

It is a well-known fact that the illness rate is increasing day by day in the world and physical inactivity is a major factor of it. According to studies physical inactivity is the 4th most leading cause of mortality worldwide, accounting for 6% of all casualties. Objective: This cross-sectional study aims to explore the personal and sociocultural factors that act as barriers to exercise among female university students. By examining these factors, the study seeks to provide valuable insights for researchers, policymakers, and health professionals to develop targeted strategies that address the identified barriers and promote physical activity among this demographic. Material and Method: This was a cross-sectional study conducted in different universities of Faisalabad. The sample size of 800 female university students of age 17-27 was included in the study through a simple random sampling method. Females with recent injury, pregnant, mentally retarded female were excluded. Data was collected by self-generated questionnaire and the collected data was analyzed through SPSS version 16 Results: The finding of the study showed that females had many personal and sociocultural factors which acted as an obstacle in their exercise and made them inactive. Most prominent obstacle for females related to sociocultural factors was the lack of sidewalks in parks which provide enjoyable and safe strolling and a smaller number of gyms specifically for females. And another prominent personal barrier in exercise was time shortage and the parent’s preference of academic activities over exercise. Conclusion: This study sheds light on the personal and sociocultural factors that hinder exercise participation among female university students. The findings underscore the importance of developing targeted interventions to address these barriers. Strategies focused on enhancing self-efficacy, promoting positive body image, and time management skills can help alleviate personal barriers

Efficient channel allocation schemes for multi-band relay networks

As next generation wireless and mobile networks continue to evolve, the scarcity of frequency spectrum and bandwidth are on the rise. While ultra-dense small-scale networks aim to satisfy the demand for ultra-high data rate needs, they offer limited coverage to mobile users. While relay-based network coverage expansion emerges as an appealing solution, it typically contributes to the additional transmission delay between a source node (SN) and a destination node (DN). To support high data rate communication and reduce the transmission delay, the heterogeneous frequency bands could be adaptively/simultaneously used to transmit the data packets over the relay node/s (RN/s). In this thesis, the exploitation of heterogeneous frequency bands in this manner is referred to as the multi-band communication. In this thesis, the advantages and shortcomings of relay-based transmission with multiband communication are studied in a systematic manner. By first formulating the theoretical problem, it is then investigated that how to develop efficient approaches and algorithms to effectively reduce the packet relay latency. In particular, the primary concern is the added delay due to relaying data packets from SN till DN via one or more RNs and any additional coordination among nodes might end up in additional computational overhead. Therefore, there emerges a trade-off between optimal (i.e., best) and fast decisions. To address the trade-off between the quality and speed of the required solution, both centralized and distributed methods are analyzed and proposed, so as to reduce the packet latency from SN to DN. In centralized optimization approach, as the number of RNs increase, an optimal solution is difficult to determine because of non-deterministic computation time. [...

Addictive brain-network identification by spatial attention recurrent network with feature selection

Abstract Addiction in the brain is associated with adaptive changes that reshape addiction-related brain regions and lead to functional abnormalities that cause a range of behavioral changes, and functional magnetic resonance imaging (fMRI) studies can reveal complex dynamic patterns of brain functional change. However, it is still a challenge to identify functional brain networks and discover region-level biomarkers between nicotine addiction (NA) and healthy control (HC) groups. To tackle it, we transform the fMRI of the rat brain into a network with biological attributes and propose a novel feature-selected framework to extract and select the features of addictive brain regions and identify these graph-level networks. In this framework, spatial attention recurrent network (SARN) is designed to capture the features with spatial and time-sequential information. And the Bayesian feature selection(BFS) strategy is adopted to optimize the model and improve classification tasks by restricting features. Our experiments on the addiction brain imaging dataset obtain superior identification performance and interpretable biomarkers associated with addiction-relevant brain regions

Removal of pectoral muscle based on topographic map and shape-shifting silhouette

Abstract Background In digital mammography, finding accurate breast profile segmentation of women’s mammogram is considered a challenging task. The existence of the pectoral muscle may mislead the diagnosis of cancer due to its high-level similarity to breast body. In addition, some other challenges due to manifestation of the breast body pectoral muscle in the mammogram data include inaccurate estimation of the density level and assessment of the cancer cell. The discrete differentiation operator has been proven to eliminate the pectoral muscle before the analysis processing. Methods We propose a novel approach to remove the pectoral muscle in terms of the mediolateral-oblique observation of a mammogram using a discrete differentiation operator. This is used to detect the edges boundaries and to approximate the gradient value of the intensity function. Further refinement is achieved using a convex hull technique. This method is implemented on dataset provided by MIAS and 20 contrast enhanced digital mammographic images. Results To assess the performance of the proposed method, visual inspections by radiologist as well as calculation based on well-known metrics are observed. For calculation of performance metrics, the given pixels in pectoral muscle region of the input scans are calculated as ground truth. Conclusions Our approach tolerates an extensive variety of the pectoral muscle geometries with minimum risk of bias in breast profile than existing techniques

Does working women’s causes innovation: an untouched reality?

Working women play a vital role in all fields of lifestyle and are the pillars of society. Women’s workforce is the key to economic boom, innovation, research and development, growth and prosperity in modern societies. Globally, governments spend billions of dollars to promote the workforce, to enhance their country’s economy and innovation. This research aims to contribute to the knowledge on innovation by working women globally and to investigate how working women affect the process of innovation, using the number of patents and trademarks as innovation indicators. The empirical study adopted a two-stage least squares (2SLS) estimation and generalized method of moments (GMM) with and without robust standard errors. Panel data of 136 countries for the period 1996–2016 was used. The results of this study show that working women positively and statistically significantly explained the patent and trademark, which is a proxy for innovation with other control variables (per capita income, education, research and development, technology, article, industry, and foreign direct investment). Overall, the findings show that working women have a positive effect on innovation – they exert a positive and significant effect on patents and trademarks. The regression results based on GMM and system GMM (SGMM) show how working women influence trademarks and patents. Specifically, the GMM reveals that the regression coefficients of patent and trademark positively affect innovation, with all variables being positive at the 1% level, indicating that the current level of patent and trademark is positive. This implies that working women have favourable economic participation in innovation. This study contributes to the cross-over of knowledge on innovation and working women and reduces the existing scarcity of information on the subject

Differential expression of micro RNA-29 family in non-diabetic adults of diabetic and non-diabetic parents.

OBJECTIVE: MicroRNAs are known to regulate 60% of genes at post translational level. MicroRNAs including Micro RNA-29 family play a vital role in cellular activities and have validate role in numerous metabolic disorders inclusive of diabetes mellitus and its complications. While micro RNA profile changes years before the occurrence of disease. This cross-sectional study was conducted in non-diabetic adults of diabetic and non-diabetic parents to explore the early changes in expression of micro RNA-29 family as it can be served as early biomarker of type 2 diabetes in non-diabetic adults. This study was conducted from January 2019 to January 2021. Micro RNA was extracted from plasma of 50 participants and expression was compared through qPCR. While data was analyzed through SPSS version 21.0. RESULTS: 29a and 29b had lower expression in participants with family history of DM compared to those having no family history of DM (P \u3c 0.0001). While micro RNA 29c was found to be significantly higher in participants with positive family history of type 2 diabetes as compared to those without family history of diabetes (P = 0.001)