A cross layer multi hop network architecture for wireless Ad Hoc networks

In this paper, a novel decentralized cross-layer multi-hop cooperative network architecture is presented. Our architecture involves the design of a simple yet efficient cooperative flooding scheme,two decentralized opportunistic cooperative forwarding mechanisms as well as the design of Routing Enabled Cooperative Medium Access Control (RECOMAC) protocol that spans and incorporates the physical, medium access control (MAC) and routing layers for improving the performance of multihop communication. The proposed architecture exploits randomized coding at the physical layer to realize cooperative diversity. Randomized coding alleviates relay selection and actuation mechanisms,and therefore reduces the coordination among the relays. The coded packets are forwarded via opportunistically formed cooperative sets within a region, without communication among the relays and without establishing a prior route. In our architecture, routing layer functionality is submerged into the MAC layer to provide seamless cooperative communication while the messaging overhead to set up routes, select and actuate relays is minimized. RECOMAC is shown to provide dramatic performance improvements, such as eight times higher throughput and ten times lower end-to-end delay as well as reduced overhead, as compared to networks based on well-known IEEE 802.11 and Ad hoc On Demand Distance Vector (AODV) protocols

RECOMAC: a cross-layer cooperative network protocol for wireless ad hoc networks

A novel decentralized cross-layer multi-hop cooperative protocol, namely, Routing Enabled Cooperative Medium Access Control (RECOMAC) is proposed for wireless ad hoc networks. The protocol architecture makes use of cooperative forwarding methods, in which coded packets are forwarded via opportunistically formed cooperative sets within a region, as RECOMAC spans the physical, medium access control (MAC) and routing layers. Randomized coding is exploited at the physical layer to realize cooperative transmissions, and cooperative forwarding is implemented for routing functionality, which is submerged into the MAC layer, while the overhead for MAC and route set up is minimized. RECOMAC is shown to provide dramatic performance improvements of eight times higher throughput and one tenth of end-to-end delay than that of the conventional architecture in practical wireless mesh networks

Throughput analysis of ALOHA with cooperative diversity

Cooperative transmissions emulate multi-antenna systems and can improve the quality of signal reception. In this paper, we propose and analyze a cross layer random access scheme, C-ALOHA, that enables cooperative transmissions in the context of ALOHA system. Our analysis shows that over a fading channel C-ALOHA can improve the throughput by 30%, as compared to standard ALOHA protocol

Energy distribution control in wireless sensor networks through range optimization

A major objective in wireless sensor networks is to find optimum routing strategies for energy efficient use of nodes. Routing decision and transmission power selection are intrinsically connected since the transmission power of a node is adjusted depending on the location of the next hop. In this paper, we propose a location-based routing framework to control the energy distribution in a network where transmission ranges, hence powers, of nodes are determined based on their locations. We show that the proposed framework is sufficiently general to investigate the minimum-energy and maximum-lifetime routing problems. It is shown that via the location based strategy the network lifetime can be improved by 70% and the total energy consumption can be decreased to three-fourths to one-third of the constant transmission range strategy depending on the propagation medium and the size of the network

Exploring the Relationship Between Personality Traits, eMail Overload and Productivity in the Workplace

As email use becomes more ubiquitous in organisations, negative effects that stem from its use are becoming more prevalent. This study classifies Email Overload as a negative product of email use. It investigates the link between the personality traits Self Esteem and Locus of Control and Email Overload. Furthermore it proposes a link between the level of perceived Email Overload and individual productivity in the work place. A sample of 239 respondents from an engineering organisation was collected for this study. Using Partial Least Squares (PLS) results suggest a strong negative relationship between Email Overload and productivity, indicating that as perceived Email Overload increases, a person’s productivity decreases. Weaker links were formed with Self Esteem and Locus of Control to Email Overload

The Family of Carabidae (Coleoptera) in Artvin Hatila National Park of Turkey

The faunistical studies on the family Carabidae (Coleoptera) species in Artvin Hatila National Park in Turkey. In this study, totally 32 species belonging to Pterostichinae, Brachininae, Carabinae, Platyninae, Lebiinae, Nebriinae and Harpalinae subfamilies of Carabidae were collected from Artvin province during 2011-2014. Among these, Amara lucida Duftschmid, Amara aulica Panzer, Brachinus elegans Chaudoir, Brachinus crepitans Linné, Carabus scabrosus Olivier, Anisodactylus binotatus Fabricius, Carabus coriaceus Linnaeus, Carabus mulsantianus Paykull, Carabus graecus Dejean, Harpalus affinis Schrank, Harpalus caspius Panzer, Ophonus cribricollis Dejean, Ophonus azureus Fabricius, Ophonus subquadratus Dejean, Pterostichus anthracinum Illiger are the first records from Artvin

Assessment of the Ethical Orientations of Turkish Teachers

Students’ development in terms of values, moral education and character is crucial for the culture of any society. Considering that these are gained through family and school, school principals and teachers can be the key players.  Even if teachers do not deliberately act as models or ethic agents, or their main purpose is not merely ethical education, they still affect the students directly and indirectly. Therefore, exploration of their ethical decisions and what orientations guide them in making those ethical decisions is highly important. In this regard, teachers’ ethical orientation is worth measuring. In this study, Ethical Position Questionnaire [1], which has so far been commonly used to explore ethical orientations of a variety of professionals and cultural groups was translated into Turkish; and validity and reliability study was applied on teachers. Research group consisted of 251 primary school teachers working in state schools located in Kocaeli province, Turkey. To identify the construct validity of Ethical Position Questionnaire (EPQ), factor analysis was conducted. The analysis revealed that EPQ is two factor-structured and these factors explain 45% of the variance. Cronbach’s Alpha internal consistency reliability assessed for the total items of Turkish version of EPQ was .81 and for the first subscale –idealism-, for the second scale –relativism- was found .84 and .86 respectively. In conclusion, The Turkish version of Ethical Position Questionnaire was identified as a valid and reliable research tool to assess ethical positions of primary school teachers

My Face My Choice: Privacy Enhancing Deepfakes for Social Media Anonymization

Recently, productization of face recognition and identification algorithms have become the most controversial topic about ethical AI. As new policies around digital identities are formed, we introduce three face access models in a hypothetical social network, where the user has the power to only appear in photos they approve. Our approach eclipses current tagging systems and replaces unapproved faces with quantitatively dissimilar deepfakes. In addition, we propose new metrics specific for this task, where the deepfake is generated at random with a guaranteed dissimilarity. We explain access models based on strictness of the data flow, and discuss impact of each model on privacy, usability, and performance. We evaluate our system on Facial Descriptor Dataset as the real dataset, and two synthetic datasets with random and equal class distributions. Running seven SOTA face recognizers on our results, MFMC reduces the average accuracy by 61%. Lastly, we extensively analyze similarity metrics, deepfake generators, and datasets in structural, visual, and generative spaces; supporting the design choices and verifying the quality.Comment: 2023 IEEE Winter Conference on Applications of Computer Vision (WACV