Identifying the Evolutionary Conditions for the Emergence of Alternative Reproductive Tactics in Simulated Robot Colonies

Alternative reproductive tactics (ARTs), phenomena in which individuals within one sex adopt different tactics for accessing mates or raising offspring, are commonly observed in all major taxa. In order to study the ecological conditions for the emergence of ARTs, we developed an embodied evolution framework incorporating ecological features, such as body size and energy maintenance, where male and female robotic agents naturally face both intersexual and intrasexual interactions for survival and reproduction. Each agent has a decision neural network with extrinsic and intrinsic sensory inputs to choose one of four basic behaviors: mating, foraging, approaching and waiting. The reproductive success depends on the body size and the energy level of both male and female upon mating and it is assumed that only female carries the reproduction cost, as in nature the cost of male’s sperm production is negligible relative to that of female’s eggs. We performed simulation experiments in environments with different conditions (food density, reproductive cost, and male-female ratio) and found ARTs emerged both in males and females. Males evolved three kinds of alternative tactics - fixed genetically distinct ARTs (dominant and sneaker males that differ in body size and the tactic for getting access to female), conditionally flexible ARTs (individuals change tactics according to body size), and mixed ARTs (combination of genetically fixed and conditionally flexible ARTs). Females evolved to have two genetically distinct ARTs (quality oriented female, QoF, and number oriented female, NoF), where they increase fitness either by offspring quality or quantity. Analysis of the results confirms the experimental notions that male genetically fixed ARTs are strongly affected by intensity of sexual selection, male conditionally flexible ARTs are significantly affected by competition level, and female ARTs are mainly affected by food density. Analysis of ESS shows male ARTs are evolutionary stable with negative frequency dependent selection and female ARTs are evolutionary stable with both frequency and density dependent selection. To our knowledge, this study is the first to show the emergence of ARTs in both male and female from initially continuous characteristics in a simulated embodied evolution framework. The evolved ARTs are quite similar to the ARTs found in nature and provide insights about how interactions between the sexes are affected by and affect the evolution of ARTs within each sex. This framework is flexible enough to further analyze species of different sexual mechanisms (hermaphrodite, androdioecious, gynodioecious, etc.) and can be used as an important tool to understand the ecology of social interaction.Okinawa Institute of Science and Technology Graduate Universit

Ensuring Application Specific Security, Privacy and Performance Goals in RFID Systems

Radio Frequency IDentification (RFID) is an automatic identification technology that uses radio frequency to identify objects. Securing RFID systems and providing privacy in RFID applications has been the focus of much academic work lately. To ensure universal acceptance of RFID technology, security and privacy issued must be addressed into the design of any RFID application. Due to the constraints on memory, power, storage capacity, and amount of logic on RFID devices, traditional public key based strong security mechanisms are unsuitable for them. Usually, low cost general authentication protocols are used to secure RFID systems. However, the generic authentication protocols provide relatively low performance for different types of RFID applications. We identified that each RFID application has unique research challenges and different performance bottlenecks based on the characteristics of the system. One strategy is to devise security protocols such that application specific goals are met and system specific performance requirements are maximized. This dissertation aims to address the problem of devising application specific security protocols for current and next generation RFID systems so that in each application area maximum performance can be achieved and system specific goals are met. In this dissertation, we propose four different authentication techniques for RFID technologies, providing solutions to the following research issues: 1) detecting counterfeit as well as ensuring low response time in large scale RFID systems, 2) preserving privacy and maintaining scalability in RFID based healthcare systems, 3) ensuring security and survivability of Computational RFID (CRFID) networks, and 4) detecting missing WISP tags efficiently to ensure reliability of CRFID based system\u27s decision. The techniques presented in this dissertation achieve good levels of privacy, provide security, scale to large systems, and can be implemented on resource-constrained RFID devices

Towards Secure and Scalable Tag Search approaches for Current and Next Generation RFID Systems

The technology behind Radio Frequency Identification (RFID) has been around for a while, but dropping tag prices and standardization efforts are finally facilitating the expansion of RFID systems. The massive adoption of this technology is taking us closer to the well known ubiquitous computing scenarios. However, the widespread deployment of RFID technology also gives rise to significant user security issues. One possible solution to these challenges is the use of secure authentication protocols to protect RFID communications. A natural extension of RFID authentication is RFID tag searching, where a reader needs to search for a particular RFID tag out of a large collection of tags. As the number of tags of the system increases, the ability to search for the tags is invaluable when the reader requires data from a few tags rather than all the tags of the system. Authenticating each tag one at a time until the desired tag is found is a time consuming process. Surprisingly, RFID search has not been widely addressed in the literature despite the availability of search capabilities in typical RFID tags. In this thesis, we examine the challenges of extending security and scalability issues to RFID tag search and suggest several solutions. This thesis aims to design RFID tag search protocols that ensure security and scalability using lightweight cryptographic primitives. We identify the security and performance requirements for RFID systems. We also point out and explain the major attacks that are typically launched against an RFID system. This thesis makes four main contributions. First, we propose a serverless (without a central server) and untraceable search protocol that is secure against major attacks we identified earlier. The unique feature of this protocol is that it provides security protection and searching capacity same as an RFID system with a central server. In addition, this approach is no more vulnerable to a single point-of-failure. Second, we propose a scalable tag search protocol that provides most of the identified security and performance features. The highly scalable feature of this protocol allows it to be deployed in large scale RFID systems. Third, we propose a hexagonal cell based distributed architecture for efficient RFID tag searching in an emergency evacuation system. Finally, we introduce tag monitoring as a new dimension of tag searching and propose a Slotted Aloha based scalable tag monitoring protocol for next generation WISP (Wireless Identification and Sensing Platform) tags

低温における温帯性シダのヒ素除去能力の検討とそのヒ素含有浸出水浄化への応用

Tohoku University井上千弘課

Ensuring Victims’ Participation in the Criminal Justice of Bangladesh

It is seen that if the main actors in a criminal justice framework are to be identified, the most commonly identified would be the alleged, his legal representative, the prosecutor and the judge. In our current legal system, the victim appears to be one of the overlooked and disregarded parties, when in reality they should be considered a vital stakeholder in the criminal justice process to secure justice. Due to adversarial legal system in Bangladesh the burden of proof lies upon the prosecution or victim in a criminal proceeding. There is hence no comprehensive law securing rights and participation of victims in criminal justice system though few supports exist for them. In accessing the justice system, victims face numerous challenges and the plight of crime victims continues to go from bad to worse. In this background, the research relies on qualitative methods to explore their status, participation and challenges in the justice system and lastly recommends how to make the justice system victim oriented

AnonPri: A Secure Anonymous Private Authentication Protocol for RFID Systems

Privacy preservation in RFID systems is a very important issue in modern day world. Privacy activists have been worried about the invasion of user privacy while using various RFID systems and services. Hence, significant efforts have been made to design RFID systems that preserve users\u27 privacy. Majority of the privacy preserving protocols for RFID systems require the reader to search all tags in the system in order to identify a single RFID tag which not efficient for large scale systems. In order to achieve high-speed authentication in large-scale RFID systems, researchers propose tree-based approaches, in which any pair of tags share a number of key components. Another technique is to perform group-based authentication that improves the tradeoff between scalability and privacy by dividing the tags into a number of groups. This novel authentication scheme ensures privacy of the tags. However, the level of privacy provided by the scheme decreases as more and more tags are compromised. To address this issue, in this paper, we propose a group based anonymous private authentication protocol (AnonPri) that provides higher level of privacy than the above mentioned group based scheme and achieves better efficiency (in terms of providing privacy) than the approaches that prompt the reader to perform an exhaustive search. Our protocol guarantees that the adversary cannot link the tag responses even if she can learn the identifier of the tags. Our evaluation results demonstrates that the level of privacy provided by AnonPri is higher than that of the group based authentication technique

Focus on Domestic Violence in Bangladesh: A Study from Criminological Perspectives

Bangladesh is a patriarchal society where powerlessness and vulnerability are associated with women’s lives, as they are often found in positions where they are dominated and subjugated by men. Women are often controlled by their father, husband and son at different phases of their lives, and due to this reason a woman commonly has risk of experiencing domestic violence within her family. Though Bangladesh is experiencing a relatively high level of gender equality for South Asia, it is still not very surprising that a husband is more likely to assault and/or batter his educated/financially solvent wife if she fails to meet his demands or to perform household work. Domestic violence often takes place in form of physical aggression or threats, sexual and emotional abuse, stalking, passive/covert abuse, and economic deprivations. There have been many studies investigating the social and cultural reasoning of such heinous behaviour and crimes in Bangladesh. This paper focuses on criminological perspectives (e.g. individual personalities, socialisation, moral upbringings, and drug addiction of male partner) in addition to the feminist theory of domestic violence. These variables work together to conceptualise domestic violence. Theory integration has been used to amalgamate a number of relevant theories to gain a more eclectic and broad understanding of this phenomenon. Hence, in this study, all the relevant factors and aspects of criminological theories of domestic violence have been analysed and put in context to Bangladesh. The methodology includes a wide literature review on the issue of domestic violence and a survey with victims and perpetrators. The study reveals the continuing persistence of misogynistic gender roles in the society and the dominance of men over women in an abusive and subjugated manner that ultimately results in domestic violence. Additionally, results suggest that for households where abuse occurs and children are present, the children grow up having this violence ingrained and normalized due to the modelling of family members

A Privacy Preserving Framework for RFID Based Healthcare Systems

RFID (Radio Frequency IDentification) is anticipated to be a core technology that will be used in many practical applications of our life in near future. It has received considerable attention within the healthcare for almost a decade now. The technology’s promise to efficiently track hospital supplies, medical equipment, medications and patients is an attractive proposition to the healthcare industry. However, the prospect of wide spread use of RFID tags in the healthcare area has also triggered discussions regarding privacy, particularly because RFID data in transit may easily be intercepted and can be send to track its user (owner). In a nutshell, this technology has not really seen its true potential in healthcare industry since privacy concerns raised by the tag bearers are not properly addressed by existing identification techniques. There are two major types of privacy preservation techniques that are required in an RFID based healthcare system—(1) a privacy preserving authentication protocol is required while sensing RFID tags for different identification and monitoring purposes, and (2) a privacy preserving access control mechanism is required to restrict unauthorized access of private information while providing healthcare services using the tag ID. In this paper, we propose a framework (PriSens-HSAC) that makes an effort to address the above mentioned two privacy issues. To the best of our knowledge, it is the first framework to provide increased privacy in RFID based healthcare systems, using RFID authentication along with access control technique

ECEF Position Accuracy and Reliability: Inertial Navigation with GNSS Precise Point Positioning (PPP)

This report presents experimental results for a moving platform using GPS PPP data for state estimation. Results from two PPP GPS state estimation approaches are presented: point-wise least squares (LS) and aided inertial navigation (INS). The point-wise LS results provide information about the accuracy and reliability of PPP GPS information at each measurement epoch, independent of other epochs. The INS results show the performance that can be achieved by combining information across measurement epochs. INS results are included for two different grades of IMU: navigation grade and consumer grade.The report cites publications that contain more detailed expla- nations of the GNSS error sources, computation of PPP wide area correction, and the LS and aided INS estimation algorithms

A convolutional neural network (CNN) for defect detection of additively manufactured parts

“Additive manufacturing (AM) is a layer-by-layer deposition process to fabricate parts with complex geometries. The formation of defects within AM components is a major concern for critical structural and cyclic loading applications. Understanding the mechanisms of defect formation and identifying the defects play an important role in improving the product lifecycle. The convolutional neural network (CNN) has been demonstrated to be an effective deep learning tool for automated detection of defects for both conventional and AM processes. A network with optimized parameters including proper data processing and sampling can improve the performance of the architecture. In this study, for the detection of good deposition quality and defects such as lack of fusion, gas porosity, and cracks in a fusion-based AM process, a CNN architecture is presented comparing the classification report and evaluation of different architectural settings and obtaining the optimized result from them. Since data set preparation, visualization, and balancing are very important aspects in deep learning to improve the performance and accuracy of neural network architectures, exploratory data analysis was performed for data visualization and the up-sampling method was implemented to balance the data set for each class. By comparing the results for different architectures, the optimal CNN network was chosen for further investigation. To tune the hyperparameters and to achieve an optimized parameter set, a design of experiments was implemented to improve the performance of the network. The performance of the network with optimized parameters was compared with the results from the previous study. The overall accuracy ( \u3e 97%) for both training and testing the CNN network presented in this work transcends the current state of the art (92%) for AM defect detection”--Abstract, page iv