Effect of neighbouring village conditions and infrastructure interdependency on economic opportunity: A case study of the Yogyakarta region,Indonesia

To determine whether the inclusion of conditions in neighbouring villages and infrastructure interdependency are able to improve the performance of infrastructure–economy interaction models, we compare three related and progressive concepts. The first concept defines economic opportunity in a village as a function of available infrastructure within that village. The second concept includes the effect of economic opportunity in neighbouring villages in addition to available infrastructure within the village. In the third concept, we include the interdependency of infrastructures as another factor affecting the potential level of economic development in the village. We use Ordinary Least Squares (OLS) and a Geographic Information System (GIS) to model the first concept, and we add a spatial-lag model for the second. The third model expands on the second by introducing a Sugeno Fuzzy Inference System (FIS) and a rule-based OLS to capture the nature of infrastructure interdependency. The result of the three models is validated by a known spatial distribution of poverty levels and subjective well-being that serve as proxies for economic opportunity in the Yogyakarta region in Indonesia. The results demonstrate that the third model provides a more accurate prediction of the real conditions and performs consistently better than the other two models. We therefore conclude that conditions in neighbouring villages and infrastructure interdependency influence the economic opportunity of a village and should be considered in policy making regarding resource allocation in infrastructure development.     

Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4 × 10³⁸ unique IP addresses of devices in the network. IPv6 has introduced new features like Neighbour Discovery Protocol (NDP) and Address Auto-configuration Scheme. IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol (ICMPv6). IPv6 is vulnerable to numerous attacks like Denial of Service (DoS) and Distributed Denial of Service (DDoS) which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications. Therefore, an Intrusion Detection System (IDS) is a monitoring system of the security of a network that detects suspicious activities and deals with a massive amount of data comprised of repetitive and inappropriate features which affect the detection rate. A feature selection (FS) technique helps to reduce the computation time and complexity by selecting the optimum subset of features. This paper proposes a method for detecting DDoS flooding attacks (FA) based on ICMPv6 messages using a Binary Flower Pollination Algorithm (BFPA-FA). The proposed method (BFPA-FA) employs FS technology with a support vector machine (SVM) to identify the most relevant, influential features. Moreover, The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios. The results show that the proposed method BFPA-FA achieved the best accuracy rate (97.96%) for the ICMPv6 DDoS detection with a reduced number of features (9) to half the total (19) features. The proven proposed method BFPA-FA is effective in the ICMPv6 DDoS attacks via IDS.     

Efficient solution of a stochastic SI epidemic system

One of the side-effects of the climate changes that are upon us is that infectious diseases are adapting, evolving and spreading to new geographic regions. It is, therefore, imperious to develop epidemic models that shed light on the interplay between the dynamics of the spread of infectious diseases and the combined effects of various vaccination and prevention regimens. With this in mind, in this work we propose a epidemic model operating on a large population; we restrict our attention to strains of infectious diseases that resist treatment. The time-dependent epidemic accounts, among others, for the effects of improved sanitation, education and vaccination. Our first main contribution is to derive the time-dependent probability mass function of the number of infected individuals in such a system. Our derivation does not use probability generating functions and partial differential equations. Instead, we develop an iterative solution that is conceptually simple and easy to implement. Somewhat surprisingly, the epidemic model also provides insight into various stochastic phenomena noticed in sociology, macroeconomics, marketing, transportation and computer science. Our second main contribution is to show, by extensive simulations, that suitably instantiated, our epidemic model be used to model phenomena describing the adoption of durable consumer goods, the spread of AIDS and the dissemination of mobile worm spread.     

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.     

Monte Carlo simulation of extrusion die life

Due to the high cost of metal forming tools (especially in hot extrusion), one of the major goals in tool design is a longer service life. Estimation and prediction of tool life thus becomes critically important for performance evaluation of the tools. The two most dominant failure mechanisms for extrusion dies (solid, hollow, and semi-hollow dies all taken together) are fracture and wear. In the first part of the paper, a fracture mechanics based fatigue life prediction model is described. A similar treatment is then presented for wear-related failures. Fracture and wear usually coexist as failure modes, and final die breakdown occurs due to the mechanism that becomes dominant. Therefore, a competing fracture–wear model has been later developed to represent the complete die failure situation. Attempt has been made to correlate the stochastic nature of various fatigue and wear related die parameters to die life. Monte Carlo simulation has been used to predict the life distribution of a die for a given set of manufacturing conditions and mechanical properties. In comparison with actual life data from the industry, the simulated life yields very realistic predictions.     

A review of gas engine driven heat pumps (GEHPs) for residential and industrial applications

This study reviews gas engine-driven heat pump (GEHP) systems for residential and industrial applications in terms of energetic and exergetic aspects for the first time to the best of the authors’ knowledge. These systems are novel heat pump systems (one of today's promising new technologies). Although the first investigations had been performed at late 1970s, the first merchandized GEHP was produced and introduced in the market in 1985. Gradually, it has become widespread all over the world for various purposes. Main application of GEHPs are for space and water heating/cooling purposes. However, they can be integrated to industrial applications, especially to drying processes.In this study, historical development of GEHP systems was briefly given first. Next, the operation of these systems was described, while studies conducted on them were reviewed and presented in tabulated forms. GEHPs were then modeled for performance evaluation purposes by using energy and exergy analysis methods. Finally, an illustrative example was given, while the results obtained were discussed. In addition, a new project on integration of GEHP systems to food drying processes in Turkey initiated by the authors was introduced. It is expected that this comprehensive study will be very beneficial to everyone involved or interested in the energetic and exergetic design, simulation, analysis and performance of assessment of GEHP systems.     

Determination of photoinitiated polymerization of multifunctional acrylates with acetic acid derivatives of thioxanthone by RT-FTIR

Photopolymerization of multifunctional acrylates with 2-thioxanthone-thioacetic acid (TXSCH₂COOH) and 2-(carboxymethoxy) thioxanthone (TXOCH₂COOH) as the one-component photoinitiator has been investigated by real-time Fourier transform infrared (RT-FTIR) spectroscopy. The photobleaching of these one-component nature initiators was performed in air. The irradiation time for total bleaching was 240 s for TXSCH₂COOH and 540 s for TXOCH₂COOH.