A Framework for Analyzing Neighbor Discovery Protocols under Non-Ideal Conditions

Neighbor Discovery (ND) protocols are crucial to achieving the paradigm of interconnecting thousands of small nodes (sensors or things) to the Internet, also known as the IoT. These protocols usually assume that nodes operate with few energy resources. Therefore, they cannot be fully active all the time. The vast majority of these protocols focus on increasing the probability that two nodes become active simultaneously, thus enabling mutual discovery. In addition, these protocols assume that successful discovery is guaranteed once two nodes are simultaneously active, with very few exceptions. However, many problems can disrupt the discovery, such as channel errors, collisions, synchronization mismatches, energy availability, and so forth. Most ND protocols did not consider these factors, making them vulnerable to severe performance degradation when transmission errors occur. This paper proposes a new framework to evaluate the performance of deterministic neighbor discovery protocols when transmission errors are present. The proposed framework facilitates obtaining an analytical CDF of the discovery time of such protocols with transmissions errors without having to implement the protocol in a simulator, since is time-consuming and prone to implementation errors. We applied the framework to analyze the effect of transmission errors on the discovery time in four of the most representative ND protocols in the literature. Finally, we validate the framework accuracy for the selected protocols using extensive simulations. The results show that the CDF of discovery times provided by the framework closely matches the performance results obtained through simulating these protocols. In general, neighbor discovery protocols are deeply affected as a result of transmission errors.

PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE DISCOVERY TIME TOKEN PADA MATA PELAJARAN IPS EKONOMI SMP NEGERI 4 WATAMPONE

Penelitian ini adalah penelitian tindakan kelas (classroom action recearch) yang bertujuan untuk mengetahui hasil belajar IPS Ekonomi siswa melalui model pembelajaran Discovery Time Token dan mengatasi masalah pada siswa mengenai model pembelajaran dan manfaatnya. Subjek penelitian ini adalah siswa kelas VII B SMP Negeri 4 Watampone Kabupaten Bone dengan jumlah siswa 23 orang. Siklus I dilaksanakan selama empat kali pertemuan dan siklus II dilaksanakan selama empat kali pertemuan. Pengambilan data dilakukan dengan menggunakan tes hasil belajar dan observasi. Hasil penelitian menunjukkan bahwa 23 siswa kelas menggunakan model pembelajaran Discovery Time Token, bahwa hasil penelitian pada siklus I menunjukkan nilai rata-rata adalah 73,73 berada pada kategori sedang. Hasil belajar pada siklus II adalah 80,00 berada pada kategori tinggi. Siklus I skor yang dapat dicapai siswa adalah pada rentang nilai antara 55 – 74 sedang dengan jumlah siswa 11 orang atau 78,26%. Siklus II berada pada rentang nilai antara 75 – 89 kategori tinggi yaitu 12 orang. Kesimpulan bahwa siklus I ke siklus II mengalami peningkatan yang berarti, maka selesailah siklus itu karena peningkatannya 6,27%.

Leg or antenna injury in Cataglyphis ants impairs survival but does not hinder searching for food

Injury is common in nature resulting, for example, from fighting, partial predation, or the wear of body parts. Injury is costly, expressed in impaired performance, failure in competition, and a shorter life span. A survey of the literature revealed the frequent occurrence of injury in ants and its various causes. We examined whether leg or antenna injury impacts food-discovery time and reduces the likelihood of reaching food in workers of the desert ant Cataglyphis niger. We examined the search-related consequences of injury in groups of either 4 or 8 workers searching for food in a short arena, a long arena, and a maze. We conducted a small field survey to evaluate the prevalence of injury in the studied population. Finally, we compared the survival rates of injured versus uninjured workers in the laboratory. Injury was common in the field, with almost 9% of the workers collected out of the nest, found to be injured. Injured workers survived shorter than uninjured ones and there was a positive link between injury severity and survival. However, we could not detect an effect of injury on any of the searching-related response variables, neither in the arenas nor in the mazes tested. We suggest that workers that survive such injury are only moderately affected by it.

Knowledgebase Approximation Using Association Rules Aggregation

This paper introduces knowledgebase approximation and fusion using association rules aggregation as a means to facilitate accelerated insight induction from high-dimensional and disparate knowledgebases. There are two typical observations that make approximating knowledgebases of interest: (1) it is quite often that insights can be derived based from a partial set of the samples, and not necessarily from all of them; and (2) generally speaking, it is rare that the knowledge of interest is contained in one knowledgebase, but rather distributed among a disparate set of unidentical knowledgebases. As a matter of fact, the insights derivable from knowledgebases tend to be uncertain, even if they were to be derived from a wholistic analysis of the knowledgebase. Thus, optimal knowledgebase approximation may yield the computational efficiency benefit without necessarily compromising insight accuracy. This paper presents a novel method to approximate a set of knowledgebases based on association rule aggregation using the disjunctive pooling rule. We show that this method can reduce insight discovery time while maintaining approximation accuracy within a desirable level.

An asynchronous neighbor discovery protocol based on double tokens in directional ad hoc networks

Aiming at the problem of slow neighbor discovery speed of sector antenna neighbor discovery (SAND) protocol based single token, an asynchronous sector antenna neighbor discovery protocol based double tokens (D-SAND) is proposed. The double tokens include one master token and one slave token. The master token holder (MTH) starts its neighbor nodes discovery process by sending hone-in message through beam scanning, and ends this process when each neighbor node is discovered. Then, MTH passes the master token to the next hop master token holder (nMTH). At the same time, MTH sends the location information of the nMTH node to its parent master token holder (MTP) from which it obtains its token. MTP determines whether to generate a slave token according to that if there exists a neighbor node with a distance greater than 2R from nMTH, where R represents the communication distance. If there exists one such neighbor, MTP generates a slave token and passes it to that neighbor node, who can begin the neighbor discovering process. The time conditions are theoretically derived when these two tokens begin their neighbor discovering process respectively and without interference to each other. Simulation results show that compared to Q-SAND(quick-SAND), the proposed D-SAND protocol reduces the network-wide neighbor discovery time about by 10%.

The Economics of Optimal Foraging by the Red Imported Fire Ant

For social organisms, foraging is often a complicated behavior where tasks are divided among numerous individuals. Here, we ask how one species, the red imported fire ant (Solenopsis invicta Buren) (Hymenoptera: Formicidae), collectively manages this behavior. We tested the Diminishing Returns Hypothesis, which posits that for social insects 1) foraging investment levels increase until diminishing gains result in a decelerating slope of return and 2) the level of investment is a function of the size of the collective group. We compared how different metrics of foraging (e.g., number of foragers, mass of foragers, and body size of foragers) are correlated and how these metrics change over time. We then tested the prediction that as fire ant colonies increase in size, both discovery time and the inflection point (i.e., the time point where colonial investment toward resources slows) should decrease while a colony’s maximum foraging mass should increase. In congruence with our predictions, we found that fire ants recruited en masse toward baits, allocating 486 workers and 148 mg of biomass, on average, after 60 min: amounts that were not different 30 min prior. There was incredible variation across colonies with discovery time, the inflection point, and the maximum biomass of foragers all being significantly correlated with colony size. We suggest that biomass is a solid indicator of how social taxa invest their workforce toward resources and hypothesize ways that invasive fire ants are able to leverage their enormous workforce to dominate novel ecosystems by comparing their foraging and colony mass with co-occurring native species.

A Novel for Construct Knowledge Structure using Marker Watershed Algorithm

Lung tumor is by all accounts the basic reason for death among individuals all through the world. Survival from lung tumor is straightforwardly identified with its development at its discovery time. The prior the identification is, the higher the odds of fruitful treatment.. To upgrade malignancy location the radiologists, utilizes CT check pictures for reviewing the insides of the body.Image handling methods give a decent quality apparatus to enhancing the manual examination. Henceforth, a lung malignancy recognition framework utilizing picture handling is utilized to arrange the present of lung disease in a CT-pictures. A programmed growth discovery framework is proposed to recognize malignant tumor from the CT check pictures. The tumor discovery conspire comprises of four phases. They are preprocessing, division, include extraction and characterization. These four levels are utilized as a part of picture handling to upgrade the tumor recognizable proof exactness. The ultimate result of this paper is to discover malignancy identification

Cancer Recognition in Medical Image Processing using Watershed Algorithm

Lung tumor is by all accounts the basic reason for death among individuals all through the world. Survival from lung tumor is straightforwardly identified with its development at its discovery time. The prior the identification is, the higher the odds of fruitful treatment.. To upgrade malignancy location the radiologists, utilizes CT check pictures for reviewing the insides of the body.Image handling methods give a decent quality apparatus to enhancing the manual examination. Henceforth, a lung malignancy recognition framework utilizing picture handling is utilized to arrange the present of lung disease in a CT-pictures. A programmed growth discovery framework is proposed to recognize malignant tumor from the CT check pictures. The tumor discovery conspire comprises of four phases. They are preprocessing, division, include extraction and characterization. These four levels are utilized as a part of picture handling to upgrade the tumor recognizable proof exactness. The ultimate result of this paper is to discover malignancy identification.

Sociodemographic and clinical characterization of patients with chronic hepatitis C

Objetivo: Describir la caracterización sociodemográfica y clínica de los pacientes portadores de hepatitis C crónica acompañados en el ambulatorio de un hospital de referencia en infectología. Método: Estudio transversal, descriptivo, cuantitativo, con usuarios portadores de hepatitis C crónica asistidos en el ambulatorio de un hospital de referencia durante noviembre de 2015 a abril de 2016 con una muestra de 47 usuarios. Resultados: Los participantes son de sexo masculino (76,6%) con rango de edad superior a 57 años (57,5%), pardo (38,3%), casado (55,3%), con grado de escolaridad (31,9%), y residente en la capital (61,7%), con tiempo de descubrimiento de hasta 6 años (68,1%), desconociendo la forma de contaminación (57,5%), inmunizado contra la hepatitis B (65,9%), realizando tratamiento medicamentoso (85,1%) con Ribavirina (55,6%); Y el 70,2% presentó efectos adversos. Conclusión: La caracterización sociodemográfica y clínica auxilian en la práctica clínica del equipo multiprofesional con los portadores de hepatitis C crónica. Objective: To describe the sociodemographic and clinical characterization of patients with chronic hepatitis C followed at the outpatient clinic of a reference hospital in infectology.Method: A cross-sectional, descriptive, quantitative study with chronic hepatitis C patients attended at a referral hospital during November 2015 to April 2016 with a sample of 47 users. Results: The participants were male (76.6%), 57 years old (57.5%), brown (38.3%), married (55.3%), (61.7%), with a discovery time of up to 6 years (68.1%), not knowing the form of contamination (57.5%), immunized against hepatitis B (65.9%), undergoing drug therapy (85.1%) with Ribavirin (55.6%); And 70.2% had adverse effects. Conclusion: Sociodemographic and clinical characterization assist the clinical practice of the multiprofessional team with patients with chronic hepatitis C Objetivo: Descrever a caracterização sociodemográfica e clínica dos pacientes portadores de hepatite C crônica acompanhados no ambulatório de um hospital referência em infectologia. Método: Estudo transversal, descritivo, quantitativo, com usuários portadores de hepatite C crônica assistidos no ambulatório de um hospital referência durante Novembro 2015 a Abril de 2016 com uma amostra de 47 usuários. Resultados: Os participantes encontram-se no sexo masculino (76,6%) com faixa etária acima de 57 anos (57,5%), pardo (38,3%), casado (55,3%), com grau de escolaridade fundamental incompleto (31,9%), e residente na capital (61,7%), com tempo de descoberta de até 6 anos (68,1%), desconhecendo a forma de contaminação (57,5%), realizando tratamento medicamentoso (85,1%) com Ribavirina (55,6%); e 70,2% apresentaram efeitos adversos. Conclusões: A caracterização sociodemográfica e clínica auxiliam na prática clínica da equipe multiprofissional com os portadores de hepatite C crônica.