Playing Doom with Anticipator-A3C Based Agents Using Deep Reinforcement Learning and the ViZDoom Game-AI Research Platform

The built-in game agents act according to the pre-written scripts and make decisions, take actions like they have been stated. They acquire and take advantage of unfair information, instead of acting flexibly like human players, who make decisions only based on game screens. This chapter focuses on studying the application of Deep Learning and Reinforcement Learning in games agents and the improvement of the related algorithms. The goal is to develop a game agent that makes decisions in human’s way and gets rid of relying on unfair information. A game agent (CNN) is implemented by augmenting the A3C algorithm. This agent takes the original real-time game screen as the input of the network, and then output the matching policy. The agent interacts with ViZDoom and reads the real-time game screen to make decisions for controlling the character to act. This chapter improved the A3C algorithm by adding an anticipator network to the original model structure. The goal of doing this is to make the agent act more like human players. It will generate anticipation before making decisions, then combine the real-time game screen with anticipation images together as a whole input of the network defined by the A3C algorithm. It can use the combination of the data to make decisions and output the discrete actions. Because the method only changes the structure of data for the input of the network, so it is a model-free method and can be easily transplanted to other algorithms. The performance of A3C is compared with variants proposed in this chapter, analyzed the differences between them and gathered the experimental data from the latest articles as a comparison which studies the same problem. The result shows, that the A3C algorithm with Anticipation performs better than the A3C algorithm

SPATA: Strong Pseudonym based AuthenTicAtion in Intelligent Transport System

Intelligent Transport System (ITS) is generally deployed to improve road safety, comfort, security, and traffic efficiency. A robust mechanism of authentication and secure communication is required to protect privacy and conditional resolution of pseudonyms to revoke malicious vehicles. In a typical ITS framework, a station can be a vehicle, Road Side Unit (RSU), or a server that can participate in communication. During authentication, the real identity of an Intelligent Transport System-Station (ITSS), referred to as a vehiclečň should not be revealed in order to preserve its privacy. In this paper, we propose a Strong Pseudonym based AutenTicAtion (SPATA) framework for preserving the real identity of vehicles. The distributed architecture of SPATA allows vehicles to generate pseudonyms in a very private and secure way. In the absence of a distributed architecture, the privacy cannot be preserved by storing information regarding vehicles in a single location. Therefore, the concept of linkability of certificates based on single authority is eliminated. This is done by keeping the real identity to pseudonym mappings distributed. Furthermore, the size of the Certificate Revocation List (CRL) is kept small, as only the most recent revoked communication pseudonyms are kept in the CRL. The privacy of the vehicle is preserved during the revocation and resolution phase through the distributed mechanism. Empirical results show that SPATA is a lightweight framework with low computational overhead, average latency, overhead ratio, and stable delivery ratio, in both sparse and dense network scenarios

Emergence of fluoroquinolone resistance among drug resistant tuberculosis patients at a tertiary care facility in Karachi, Pakistan

Background: Pakistan is classified as one of the high multi-drug resistant tuberculosis (MDR-TB) burden countries. A poorly regulated private sector, over-prescription of antibiotics and self-medication has led to augmented rates of drug-resistance in the country. Pakistan\u27s first national anti-tuberculosis drug resistance survey identified high prevalence of fluoroquinolone resistance among MDR-TB patients. Further institutional evidence of fluoroquinolone drug-resistance can support re-evaluation of treatment regimens as well as invigorate efforts to control antibiotic resistance in the country.Findings: In this study, data for drug-susceptibility testing (DST) was retrospectively analyzed for a total of 133 patients receiving MDR-TB treatment at the Chest Department of Jinnah Postgraduate Medical Center, Karachi, Pakistan. Frequency analyses for resistance patterns was carried out and association of fluoroquinolone (ofloxacin) resistance with demographics and past TB treatment category were assessed. Within first-line drugs, resistance to isoniazid was detected in 97.7% of cases, followed by rifampicin (96.9%), pyrazinamide (86.4%), ethambutol (69.2%) and streptomycin (64.6%). Within second-line drugs, ofloxacin resistance was detected in 34.6% of cases. Resistance to ethionamide and amikacin was 2.3% and 1.6%, respectively. Combined resistance of oflaxacin and isoniazid was detected in 33.9% of cases. Age, gender and past TB treatment category were not significantly associated with resistance to ofloxacin.Conclusion: Fluoroquinolone resistance was observed in an alarmingly high proportion of MDR-TB cases. Our results suggest caution in their use for empirical management of MDR-TB cases and recommended treatment regimens for MDR-TB may require re-evaluation. Greater engagement of private providers and stringent pharmacy regulations are urgently required

Knowledge, attitudes, and practices among nurses in Pakistan towards diabetic foot

Introduction: Diabetic foot ulcers are a pressing complication of diabetes mellitus. Wound care requires a significant proportion of healthcare resources. It is imperative, therefore, for healthcare professionals to possess sound knowledge of the disease along with a positive attitude to ensure better clinical practice. Our literature search revealed a scarcity of data pertaining to diabetic foot ulcers. Therefore, this study aims to evaluate the knowledge and attitudes of nurses regarding diabetic foot care. Methods: A cross-sectional study design was employed, a pre-validated and pre-tested questionnaire was used to collect data from a sample size of 250 nurses working at two tertiary care hospitals in Karachi, Pakistan. The study was conducted over a period of three months (January to March 2018) and included all nurses who possessed at least one year of clinical experience in diabetic ulcer care. The statistical software employed was SPSS version 19 (IBM Corp., Armonk, NY, US). Non-parametric tests and descriptive statistics were used for data analysis and statistical significance was assumed at a p-value of less than 0.5. Results: Only 54% of the nurses in our study possessed adequate knowledge of diabetic foot ulcers. The mean score of knowledge was 74.9 (±9.5). Macdonald’s standard criteria for learning outcomes was used to gauge the knowledge levels of our study population. Nurses performed best in the domain of ulcer care with 65.3% of the participants possessing good knowledge of the topic. The overall attitude of nurses towards patients with diabetic ulcers was positive. Conclusion: This study highlights important gaps in nurses’ knowledge and sheds light on the lack of evidence-based practice. Poor knowledge can compromise healthcare standards, even with the presence of positive attitudes. Hence, a comprehensive revision of nursing curricula across local tertiary hospitals for allowing nurses to update their knowledge is warrante

Issues, Challenges, and Research Opportunities in Intelligent Transport System for Security and Privacy

Intelligent transport system (ITS), owing to their potential to enhance road safety and improve traffic management, have attracted attention from automotive industries and academia in recent years. The underlying technology—i.e., vehicular ad-hoc networks (VANETs)—provide a means for vehicles to intelligently exchange messages regarding road and traffic conditions to enhance safety. The open nature of ITS as wireless communication technology leads to many security and privacy challenges. These challenges pertain to confidentiality, authentication, integrity, non-repudiation, location privacy, identity privacy, anonymity, certificate revocation, and certificate resolution. This article aims to propose a novel taxonomy of security and privacy issues and solutions in ITS. Furthermore, categorization of security and privacy schemes in ITS and their limitations are discussed with various parameters—scalability, privacy, computational cost, communication overhead, latency—and various types of security attacks has been analyzed. This article leverages new researchers for challenges and opportunities related to security and privacy in ITS

Reversible data hiding techniques with high message embedding capacity in images.

Reversible Data Hiding (RDH) techniques have gained popularity over the last two decades, where data is embedded in an image in such a way that the original image can be restored. Earlier works on RDH was based on the Image Histogram Modification that uses the peak point to embed data in the image. More recent works focus on the Difference Image Histogram Modification that exploits the fact that the neighbouring pixels of an image are highly correlated and therefore the difference of image makes more space to embed large amount of data. In this paper we propose a framework to increase the embedding capacity of reversible data hiding techniques that use a difference of image to embed data. The main idea is that, instead of taking the difference of the neighboring pixels, we rearrange the columns (or rows) of the image in a way that enhances the smooth regions of an image. Any difference based technique to embed data can then be used in the transformed image. The proposed method is applied on different types of images including textures, patterns and publicly available images. Experimental results demonstrate that the proposed method not only increases the message embedding capacity of a given image by more than 50% but also the visual quality of the marked image containing the message is more than the visual quality obtained by existing state-of-the-art reversible data hiding technique. The proposed technique is also verified by Pixel Difference Histogram (PDH) Stegoanalysis and results demonstrate that marked images generated by proposed method is undetectable by PDH analysis

Efficient Processing of Image Processing Applications on CPU/GPU

Heterogeneous systems have gained popularity due to the rapid growth in data and the need for processing this big data to extract useful information. In recent years, many healthcare applications have been developed which use machine learning algorithms to perform tasks such as image classification, object detection, image segmentation, and instance segmentation. The increasing amount of big visual data requires images to be processed efficiently. It is common that we use heterogeneous systems for such type of applications, as processing a huge number of images on a single PC may take months of computation. In heterogeneous systems, data are distributed on different nodes in the system. However, heterogeneous systems do not distribute images based on the computing capabilities of different types of processors in the node; therefore, a slow processor may take much longer to process an image compared to a faster processor. This imbalanced workload distribution observed in heterogeneous systems for image processing applications is the main cause of inefficient execution. In this paper, an efficient workload distribution mechanism for image processing applications is introduced. The proposed approach consists of two phases. In the first phase, image data are divided into an ideal split size and distributed amongst nodes, and in the second phase, image data are further distributed between CPU and GPU according to their computation speeds. Java bindings for OpenCL are used to configure both the CPU and GPU to execute the program. The results have demonstrated that the proposed workload distribution policy efficiently distributes the images in a heterogeneous system for image processing applications and achieves 50% improvements compared to the current state-of-the-art programming frameworks

Development of amplified fragment length polymorphism (AFLP) markers for the identification of Cholistani cattle

<p>The identification issue of livestock can be resolved by using molecular identification tools that are acceptable to preserve and maintain pure breeds worldwide. The application of a molecular identification methodology is more important for developing nations, e.g., Pakistan, where uncontrolled crossbreeding has become a common practice and the import of exotic animals and germplasm is ever increasing. This presents a risk to local breeds as also stated by the FAO. Therefore, the current study was designed to develop standard molecular markers for Cholistani cattle to ascertain their purity for breeding purpose. In this study 50 and 48 unrelated males were sampled for Cholistani and each crossbred cattle, respectively. Candidate molecular markers present in Cholistani but absent in crossbred cattle and vice versa were detected using the amplified fragment length polymorphism (AFLP) method. Eleven markers were developed and were converted to single nucleotide polymorphism (SNP) markers for genotyping. The allele frequencies in both breeds were determined for discrimination ability using polymerase-chain-reaction–restriction-fragment-polymorphism (PCR-AFLP). The probability of identifying the Cholistani breed was 0.905 and the probability of misjudgment was 0.073 using a panel of markers. The identified markers can ascertain the breed purity and are likely to extend the facility for breed purity testing before entering into a genetic improvement program in the country.</p&gt

Development of amplified fragment length polymorphism (AFLP) markers for the identification of Cholistani cattle

<p>The identification issue of livestock can be resolved by using molecular identification tools that are acceptable to preserve and maintain pure breeds worldwide. The application of a molecular identification methodology is more important for developing nations, e.g., Pakistan, where uncontrolled crossbreeding has become a common practice and the import of exotic animals and germplasm is ever increasing. This presents a risk to local breeds as also stated by the FAO. Therefore, the current study was designed to develop standard molecular markers for Cholistani cattle to ascertain their purity for breeding purpose. In this study 50 and 48 unrelated males were sampled for Cholistani and each crossbred cattle, respectively. Candidate molecular markers present in Cholistani but absent in crossbred cattle and vice versa were detected using the amplified fragment length polymorphism (AFLP) method. Eleven markers were developed and were converted to single nucleotide polymorphism (SNP) markers for genotyping. The allele frequencies in both breeds were determined for discrimination ability using polymerase-chain-reaction–restriction-fragment-polymorphism (PCR-AFLP). The probability of identifying the Cholistani breed was 0.905 and the probability of misjudgment was 0.073 using a panel of markers. The identified markers can ascertain the breed purity and are likely to extend the facility for breed purity testing before entering into a genetic improvement program in the country.</p&gt