Graph invariants for unique localizability in cooperative localization of wireless sensor networks: rigidity index and redundancy index

Rigidity theory enables us to specify the conditions of unique localizability in the cooperative localization problem of wireless sensor networks. This paper presents a combinatorial rigidity approach to measure (i) generic rigidity and (ii) generalized redundant rigidity properties of graph structures through graph invariants for the localization problem in wireless sensor networks. We define the rigidity index as a graph invariant based on independent set of edges in the rigidity matroid. It has a value between 0 and 1, and it indicates how close we are to rigidity. Redundant rigidity is required for global rigidity, which is associated with unique realization of graphs. Moreover, redundant rigidity also provides rigidity robustness in networked systems against structural changes, such as link losses. Here, we give a broader definition of redundant edge that we call the "generalized redundant edge." This definition of redundancy is valid for both rigid and non-rigid graphs. Next, we define the redundancy index as a graph invariant based on generalized redundant edges in the rigidity matroid. It also has a value between 0 and 1, and it indicates the percentage of redundancy in a graph. These two indices allow us to explore the transition from non-rigidity to rigidity and the transition from rigidity to redundant rigidity. Examples on graphs are provided to demonstrate this approach. From a sensor network point of view, these two indices enable us to evaluate the effects of sensing radii of sensors on the rigidity properties of networks, which in turn, allow us to examine the localizability of sensor networks. We evaluate the required changes in sensing radii for localizability by means of the rigidity index and the redundancy index using random geometric graphs in simulations.Comment: 13 pages, 7 figures, to be submitted for possible journal publicatio

A Theoretical Analysis of the Conditions for Unambiguous Node Localization in Sensor Networks

In this paper we provide a theoretical foundation for the problem of network localization in which some nodes know their locations and other nodes determine their locations by measuring distances or bearings to their neighbors. Distance information is the separation between two nodes connected by a sensing/communication link. Bearing is the angle between a sensing/communication link and the x-axis of a node's local coordinate system. We construct grounded graphs to model network localization and apply graph rigidity theory and parallel drawings to test the conditions for unique localizability and to construct uniquely localizable networks. We further investigate partially localizable networks

A Theoretical Analysis of the Conditions for Unambiguous Node Localization in Sensor Networks

In this paper we provide a theoretical foundation for the problem of network localization in which some nodes know their locations and other nodes determine their locations by measuring distances or bearings to their neighbors. Distance information is the separation between two nodes connected by a sensing/communication link. Bearing is the angle between a sensing/communication link and the x-axis of a node's local coordinate system. We construct grounded graphs to model network localization and apply graph rigidity theory and parallel drawings to test the conditions for unique localizability and to construct uniquely localizable networks. We further investigate partially localizable networks

Scene creation and exploration in outdoor augmented reality

This thesis investigates Outdoor Augmented Reality (AR) especially for scene creation and exploration aspects.We decompose a scene into several components: a) Device, b) Target Object(s), c) Task, and discuss their interrelations. Based on those relations we outline use-cases and workflows. The main contribution of this thesis is providing AR oriented workflows for selected professional fields specifically for scene creation and exploration purposes, through case studies as well as analyzing the relations between AR scene components. Our contributions inlude, but not limited to: i) analysis of scene components and factoring inherintly available errors, to create a transitional hybrid tracking scheme for multiple targets, ii) a novel image-based approach that uses building block analogy for modelling and introduces volumetric and temporal labeling for annotations, iii) an evaluation of the state of the art X-Ray visualization methods as well as our proposed multi-view method. AR technology and capabilities tend to change rapidly, however we believe the relation between scene components and the practical advantages their analysis provide are valuable. Moreover, we have chosen case studies as diverse as possible in order to cover a wide range of professional field studies. We believe our research is extendible to a variety of field studies for disciplines including but not limited to: Archaeology, architecture, cultural heritage, tourism, stratigraphy, civil engineering, and urban maintenance

Investigation of Deep Learning Approaches for Identification of Important Wheat Pests in Central Anatolia

Artificial intelligence-based systems play a crucial role in Integrated Pest Management studies. It is important to develop and support such systems for controlling wheat pests, which cause significant losses in wheat production which is strategic importance, particularly in Turkey. This study employed various pre-trained deep learning approaches to identify key wheat pests in the Central Anatolia Region, namely Aelia spp., Anisoplia spp., Eurygaster spp., Pachytychius hordei, and Zabrus spp. The models' classification success was determined using open and original datasets. Among the models, the ResNet-18 model outperformed others, achieving a classification success rate of 99%. Furthermore, each model was tested with original images collected during field studies to assess their effectiveness. The results demonstrate that pre-trained deep learning models can be utilized for the identification of important wheat pests in Central Anatolia as part of Integrated Pest Management

Exercise-Induced Right Ventricular Outflow Tract Tachycardia in a Patient with Isolated Left Ventricular Noncompaction

Isolated left ventricular noncompaction is a hereditary cardiomyopathy in which a variety of supraventricular and ventricular arrhythmias could be observed. We report a patient with exercise-induced ventricular tachycardia with left bundle branch block morphology that had characteristics of an idiopathic ventricular tachycardia who was subsequently diagnosed as left ventricular noncompaction. Successful remission of arrhythmia was ensured after the introduction of oral beta-blocker therapy

Reconstruction of the temporal signaling network in Salmonella-infected human cells

Salmonella enterica is a bacterial pathogen that usually infects its host through food sources. Translocation of the pathogen proteins into the host cells leads to changes in the signaling mechanism either by activating or inhibiting the host proteins. Using high-throughput ‘omic’ technologies, changes in the signaling components can be quantified at different levels; however, experimental hits are usually incomplete to represent the whole signaling system as some driver proteins stay hidden within the experimental data. Given that the bacterial infection modifies the response network of the host, more coherent view of the underlying biological processes and the signaling networks can be obtained by using a network modeling approach based on the reverse engineering principles in which a confident region from the protein interactome is found by inferring hits from the omic experiments. In this work, we have used a published temporal phosphoproteomic dataset of Salmonella-infected human cells and reconstructed the temporal signaling network of the human host by integrating the interactome and the phosphoproteomic datasets. We have combined two well-established network modeling frameworks, the Prize-collecting Steiner Forest (PCSF) approach and the Integer Linear Programming (ILP) based edge inference approach. The resulting network conserves the information on temporality, direction of interactions, while revealing hidden entities in the signaling, such as the SNARE binding, mTOR signaling, immune response, cytoskeleton organization, and apoptosis pathways. Targets of the Salmonella effectors in the host cells such as CDC42, RHOA, 14-3-3δ, Syntaxin family, Oxysterol-binding proteins were included in the reconstructed signaling network although they were not present in the initial phosphoproteomic data. We believe that integrated approaches have a high potential for the identification of clinical targets in infectious diseases, especially in the Salmonella infections

Integrating meaning into quality evaluation of machine translation

Machine translation (MT) quality is evaluated through comparisons between MT outputs and the human translations (HT). Traditionally, this evaluation relies on form related features (e.g. lexicon and syntax) and ignores the transfer of meaning reflected in HT outputs. Instead, we evaluate the quality of MT outputs through meaning related features (e.g. polarity, subjectivity) with two experiments. In the first experiment, the meaning related features are compared to human rankings individually. In the second experiment, combinations of meaning related features and other quality metrics are utilized to predict the same human rankings. The results of our experiments confirm the benefit of these features in predicting human evaluation of translation quality in addition to traditional metrics which focus mainly on form

Information Structures to Secure Control of Rigid Formations with Leader-Follower Structure

This paper is concerned with rigid formations of mobile autonomous agents using a leader-follower structure. A formation is a group of agents moving in real 2- or 3- dimensional space. A formation is called rigid if the distance between each pair of agents does not change over time under ideal conditions. Sensing/communication links between agents are used to maintain a rigid formation. Two agents connected by a sensing/communication link are called neighbors. There are two types of neighbor relations in rigid formations. In the first type, the neighbor relation is symmetric. In the second type, the neighbor relation is asymmetric. Rigid formations with a leader-follower structure have the asymmetric neighbor relation. A framework to analyze rigid formations with symmetric neighbor relations is given in our previous work. This paper suggests an approach to analyze rigid formations that have a leader-follower structure

Yeni doğan dudak damak yarıklı bebeklerin alçı modellerinin değerlendirilmesi

Amaç: Dudak ve damak yarıkları baş-boyun bölgesinin sık görülen konjenital malformasyonları arasındadır. Bu çalışmada Gaziantep Üniversitesi Diş Hekimliği Fakültesi Ortodonti Anabilim Dalı’nda tedavi edilen dudak damak yarıklı hastalarının cinsiyet, yaş, yarık tipi, anterior yarık genişliği, midpalatal ve posterior palatal genişliklerine göre değerlendirilmesi amaçlanmıştır.Gereç ve Yöntemler: Çalışmada kliniğimize gelen 39 dudak damak yarıklı hastanın kayıtları kullanıldı ve yaş, cinsiyet, yarık tipleri değerlendirildi. Analiz için alçı modeller üzerinde ölçümler yapıldı. Kullanılan referans noktaları; c, c’ noktaları (kaninler bölgesi), t, t’ noktaları (tüber noktaları), g, g’ noktaları (c ve t noktaları arası mesafenin orta noktası) olarak belirlendi.Bulgular: Çalışmaya dâhil edilen bireylerin %24ü (n=9) çift taraflı dudak damak yarıklı, %20si (n=8) izole damak yarıklı, %56sı (n=22) tek taraflı dudak damak yarıklı idi. Çift taraflı dudak damak yarıklı bireylerin yaş ortalaması 24.33±24.69 gün, izole damak yarıklı bireylerin yaş ortalaması 68.37±58.04 gün, tek taraflı dudak damak yarıklı bireylerin yaş ortalaması ise 31±30.11 gündü. Çift taraflı dudak damak yarıklı bireylerin %66.7si (n=6) erkekti. Grubun anterior yarık genişliği ortalama olarak 13.23±3.06, midpalatal genişliği 32.67±3.58, postpalatal genişliği 29.25±2.78 mm idi. İzole damak yarıklı bireylerin %37.5’i (3kişi) erkekti. Grubun anterior yarık genişliği bulunmamaktaydı. Midpalatal yarık genişliği 30.71±2.11, postpalatal genişliği 27.17±2.42 mm idi. Unilateral yarıklı bireylerin %54.5i (12kişi) erkekti. Grubun anterior yarık genişliği 10.14±3.12, midpalatal genişlik 35.74±3.05, postpalatal genişlik ise 31.35±3.22 mm idi.Sonuç: Tek ve çift taraflı dudak damak yarıkları erkeklerde, izole damak yarıkları ise kızlarda daha çok görüldü. Anterior yarık genişliği miktarı çift taraflı dudak damak yarıklı grupta tek taraflı dudak damak yarıklı gruptan daha fazla olduğu görüldü. Ancak midpalatal genişliğin ve posterior palatal genişliğin tek taraflı dudak damak yarıklı bireylerde daha fazla olduğu görüldü. Kliniğimize en erken başvuran grubun çift taraflı dudak damak yarıklı bireyler, en geç başvuran grubun ise izole damak yarıklı bireyler olduğu tespit edildi. Kliniğimize başvuran, gerek Hotz plağı gerek nazal molding aygıtlarıyla tedavilerine başlanan hastaların uzun dönem takiplerinin yapılarak başlangıç değerleriyle karşılaştırılması düşünüldü