The traditional Yemeni window and natural lighting

The traditional Yemeni window is considered to be one of the most important elements that characterize the yemeni architecture. The beauty of the traditional Yemeni window comes from its four main components which combined the functions of view, lighting, ventilation, protection, and privacy. These functions can be controlled by the occupants according to their social and environmental needs. The four main components are the lower part (Taqah), the fanlight (Qamariyah), the wooden external overhang (Konnah), and the small vent (Shaquos). Since fanlights provide natural lighting during day-time, the area of the lower part can be reduced and its exterior shutters can be closed without the need for artificial lighting. The internal natural lighting that is provided by the upper and lower parts of the window was investigated to see its quality. In this investigation, there were two main goals. The first is the contribution and quality of the internal light provided by the Qamariyah when shutters are closed. The second is the effect of the internal simple white cloth curtains, in the lower part, in the internal light quality. Visual measurements were taken in a typical room of a traditional house of the Old City of Sana'a, Yemen. From the findings, it was found that the fanlights (Qamariyat) provide low and soft homogeneous internal lighting which was as low as 22 lux average. However, the occupants have the ability to increase level of lighting to as high as 600 or 700 lux. This can be done simply by deciding which shutter to open and how many of them to be opened. In this paper, the methodology and findings will be presented and discussed.     

KINETICS FOR LOW TEMPERATURE PYROLYSIS OF BLACK LIQUOR

A kinetic study of pyrolysis of dried black liquor was performed using a Netzsch 429 Thermogravimetric Analyzer. It was found that as conversion increases from 10 to 45% the apparent pyrolysis activation energy for black liquor increases from 77.20 to 112.74 KJ/mol. For black liquor the order of reaction was found to be first-order. The reaction rate constant was found to be 2.12×10⁹ min. These results are in agreement with the data reported by other investigators on biomass pyrolysis.     

Functional and sensory properties of chicken meat from spent-hen carcasses deboned manually or mechanically in Jordan

Samples of chicken meat from spent laying hens were obtained by four different methods: (1) manual deboning of whole carcasses; (2) manual deboning of skinned carcasses; (3) mechanical deboning of whole carcasses; and (4) mechanical deboning of skinned carcasses. The meat was packaged, frozen and stored at ?18 °C for up to 3 months. Functional properties studied were pH, emulsifying capacity (EC) and water‐holding capacity (WHC) and, in addition, pigment concentration was investigated. Sensory properties included aroma, colour, texture and overall acceptability, as judged by a trained panel using a nine‐point hedonic scale. Removal of the skin prior to deboning by either method gave significantly higher values (P < 0.05) for EC, while WHC values were not significantly different among the experimental treatments, despite higher pH values for mechanically‐deboned meat, with and without skin. Pigment concentrations were highest in meat from Treatment 4 and lowest for Treatment 1, but values for both methods of deboning were affected by the presence of skin. There were no significant differences between treatments for any of the sensory properties studied. Changes occurring in the meat during frozen storage are described.     

Bandwidth Adaptive Cache Coherence Optimizations for Chip Multiprocessors

Chip Multiprocessors (CMPs) have different technological parameters and physical constraints than earlier multi-processor systems, which should be taken into consideration when designing cache coherence protocols. Also, contemporary cache coherence protocols use invalidate schemes that are known to generate a high number of coherence misses. This is especially true under producer-consumer sharing patterns that can become a performance bottleneck as the number of cores increases. This paper presents two mechanisms to design efficient and scalable cache coherence protocols for CMPs. First, we propose an adaptive hybrid protocol to reduce coherence misses observed in write-invalidate based protocols. The proposed protocol is based on a write-invalidate scheme. However, adaptively, it can push updates to potential consumers based on observed producer-consumer sharing patterns. Secondly, we extend this adaptive protocol with an interconnection resource aware mechanism. Experimental evaluations, conducted on a tiled-CMP via full-system simulation, were used to assess the performance from our proposed dynamic hybrid protocols. Performance analysis is presented on a set of scientific applications from the SPLASH-2 and NAS parallel benchmark suites. Results showed that the proposed mechanisms reduce cache-to-cache sharing misses up to 48 % and speed up application performance up to 34 %. In addition, the proposed interconnection resource aware mechanism is proven to perform well under varying interconnection utilizations.     

Improved phase performance for rotman lens

Rotman lenses are used to obtain multiple beams from a single array. Although the beams produced by the feed antennas at focal points have no path length errors, the beams produced by feed antennas at off focal points may have large path length errors. These path length errors cause deterioration in the multiple beams. In this article, two novel methods are introduced to obtain feed curves which reduce the path length errors of off focal feed points significantly, compared with the commonly used circular and elliptical feed curves. The first method obtains feed curve points based on having zero path length error at three chosen points of the radiating array for each beam direction. The second method uses the particle swarm optimization method for obtaining optimum feed points for each beam direction. The results show that there is a very significant drop in the level of the maximum path length errors (in the order of about 1:4). © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE 23: 634–638, 2013.     

Medical image segmentation with transform and moment based features and incremental supervised neural network

In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment the tissues in medical images. Two-dimensional (2D) continuous wavelet transform (CWT) and the moments of the gray-level histogram (MGH) are computed in order to form the feature vectors of ultrasound (US) bladder and phantom images, X-ray computerized tomography (CT) and magnetic resonance (MR) head images. In the 2D-CWT method, feature vectors are formed by the intensity of one pixel of each wavelet-plane of different energy bands. The MGH represents the tissues within the sub-windows by using the spatial variation of image intensities. In this study, the ISNN and Grow and Learn (GAL) network are employed for the segmentation task. It is observed that the ISNN has significantly eliminated the disadvantages of the GAL network in the segmentation of the medical images.     

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.     

High-performance MEMS shutter display with metal-oxide thin-film transistors and optimized MEMS element

Active matrix prestressed microelectromechanical shutter displays enable outstanding optical properties as well as robust operating performance. The microelectromechanical systems (MEMS) shutter elements have been optimized for higher light outcoupling efficiency with lower operation voltage and higher pixel density. The MEMS elements have been co-fabricated with self-aligned metal-oxide thin-film transistors (TFTs). Several optimizations were required to integrate MEMS process without hampering the performance of both elements. The optimized display process requires only seven photolithographic masks with ensuring proper compatibility between MEMS shutter and metal-oxide TFT process.