Search results for: Early packet discard

Authors: Imen Sfaihi, Noureddine Hamdi

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In this paper, we investigate the study of techniques for scheduling users for resource allocation in the case of multiple input and multiple output (MIMO) packet transmission systems. In these systems, transmit antennas are assigned to one user or dynamically to different users using spatial multiplexing. The allocation of all transmit antennas to one user cannot take full advantages of multi-user diversity. Therefore, we developed the case when resources are allocated dynamically. At each time slot users have to feed back their channel information on an uplink feedback channel. Channel information considered available in the schedulers is the zero forcing (ZF) post detection signal to interference plus noise ratio. Our analysis study concerns the round robin and the opportunistic schemes. In this paper, we present an overview and a complete capacity analysis of these schemes. The main results in our study are to give an analytical form of system capacity using the ZF receiver at the user terminal. Simulations have been carried out to validate all proposed analytical solutions and to compare the performance of these schemes.

Keywords: MIMO, scheduling, ZF receiver, spatial multiplexing, round robin scheduling, opportunistic.

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: Cyber-security, Intrusion Detection Systems, Temporal Graph Network, Anomaly Detection.

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Authors: N. Muthukumaran, R. Ravi

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The Quad Tree Decomposition based performance analysis of compressed image data communication for lossy and lossless through wireless sensor network is presented. Images have considerably higher storage requirement than text. While transmitting a multimedia content there is chance of the packets being dropped due to noise and interference. At the receiver end the packets that carry valuable information might be damaged or lost due to noise, interference and congestion. In order to avoid the valuable information from being dropped various retransmission schemes have been proposed. In this proposed scheme QTD is used. QTD is an image segmentation method that divides the image into homogeneous areas. In this proposed scheme involves analysis of parameters such as compression ratio, peak signal to noise ratio, mean square error, bits per pixel in compressed image and analysis of difficulties during data packet communication in Wireless Sensor Networks. By considering the above, this paper is to use the QTD to improve the compression ratio as well as visual quality and the algorithm in MATLAB 7.1 and NS2 Simulator software tool.

Keywords: Image compression, Compression Ratio, Quad tree decomposition, Wireless sensor networks, NS2 simulator.

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

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Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: Cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma.

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Authors: Mohamed A. Azab

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Over the early years of the 21st century, cities throughout the Middle East, particularly in the Gulf region have expanded more rapidly than ever before. Given the presence of a large volume of high-rise buildings allover the region, the local authority aims to set a new standard for sustainable development; with an integrated approach to maintain a balance between economy, quality, environmental protection and safety of life. In the very near future, as mandatory requirements, sustainability will be the criteria that should be included in all building projects. It is well known in the building sustainability topics that structural design engineers do not have a key role in this matter. In addition, the LEED (Leadership in Energy and Environmental Design) has looked almost exclusively on the environmental components and materials specifications. The objective of this paper is to focus and establish groundwork for sustainability techniques and applications related to the RC high-rise buildings design, from the structural point of view. A set of recommendations related to local conditions, structural modeling and analysis is given, and some helpful suggestions for structural design team work are addressed. This paper attempts to help structural engineers in identifying the building sustainability design, in order to meet local needs and achieve alternative solutions at an early stage of project design.

Keywords: Building, Design, High-rise, Middle East, Structural, Sustainability.

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Authors: Simon B. N. Thompson

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Cortisol is essential to the regulation of the immune system and yawning is a pathological symptom of multiple sclerosis (MS). Electromyography activity (EMG) in the jaw muscles typically rises when the muscles are moved and with yawning is highly correlated with cortisol levels in healthy people. Saliva samples from 59 participants were collected at the start and after yawning, or at the end of the presentation of yawning-provoking stimuli, in the absence of a yawn, together with EMG data and questionnaire data: Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details. Exclusion criteria: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, stroke. Significant differences were found between the saliva cortisol samples for the yawners, t (23) = -4.263, p = 0.000, as compared with the non-yawners between rest and post-stimuli, which was nonsignificant. Significant evidence was found to support the Thompson Cortisol Hypothesis suggesting that rises in cortisol levels are associated with yawning. Further research is exploring the use of cortisol as an early diagnostic tool for MS. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein.

Keywords: Cortisol, Multiple Sclerosis, Yawning, Thompson’s Cortisol Hypothesis.

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Authors: O. Wright, N. Perkins, M. Donn, M. Halstead

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This research responded to anecdotal evidence that suggested inefficiencies within the Architect and Acoustician relationship may lead to ineffective acoustic design decisions.  The acoustician spoken to believed that he was approached too late in the design phase. The approached architect valued acoustical qualities, yet, struggled to interpret common measurement parameters. The preliminary investigation of these opinions indicated a gap in the current New Zealand Architectural discourse and currently informs the creation of a 2016 Master of Architecture (Prof) thesis research. Little meaningful information about acoustic intervention in the early design phase could be found from past literature. In the information that was sourced, authors focus on software as an incorporation tool without investigating why the flaws in the relationship originally exist. To further explore this relationship, a survey was designed. It underwent three phases to ensure its consistency, and was delivered to a group of 51 acousticians from one international Acoustics company. The results were then separated between New Zealand and off-shore to identify trends. The survey results suggest that 75% of acousticians meet the architect less than 5 times per project. Instead of regular contact, a mediated method is adopted though a mix of telecommunication and written reports. Acousticians tend to be introduced later into New Zealand building project than the corresponding off-shore building. This delay corresponds to an increase in remedial action for each of the building types in the survey except Auditoria and Office Buildings. 31 participants have had their specifications challenged by an architect. Furthermore, 71% of the acousticians believe that architects do not have the knowledge to understand why the acoustic specifications are in place. The issues raised in this investigation align to the colloquial evidence expressed by the two consultants. It identifies a larger gap in the industry were acoustics is remedially treated rather than identified as a possible design driver. Further research through design is suggested to understand the role of acoustics within architectural design and potential tools for its inclusion during, not after, the design process.

Keywords: Architectural acoustics, early-design, interdisciplinary communication, remedial response.

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Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: Clustering, heterogeneous, stability, scalability, throughput, IoT, WSN.

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Authors: Brandy Yee, Dianne Yee

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Through the exploration of the lived experiences, beliefs and values of instructional leaders, teachers and students in Finland, Germany and Canada, we investigated the factors which contribute to developmentally responsive, intellectually engaging middle-level learning environments for early adolescents. Student-centred leadership dimensions, effective instructional practices and student agency were examined through the lens of current policy and research on middle-level learning environments emerging from the Canadian province of Manitoba. Consideration of these three research perspectives in the context of early adolescent learning, placed against an international backdrop, provided a previously undocumented perspective on leading, teaching and learning in the middle years. Aligning with a social constructivist, qualitative research paradigm, the study incorporated collective case study methodology, along with constructivist grounded theory methods of data analysis. Data were collected through semi-structured individual and focus group interviews and document review, as well as direct and participant observation. Three case study narratives were developed to share the rich stories of study participants, who had been selected using maximum variation and intensity sampling techniques. Interview transcript data were coded using processes from constructivist grounded theory. A cross-case analysis yielded a conceptual framework highlighting key factors that were found to be significant in the establishment of developmentally responsive, intellectually engaging middle-level learning environments. Seven core categories emerged from the cross-case analysis as common to all three countries. Within the visual conceptual framework (which depicts the interconnected nature of leading, teaching and learning in middle-level learning environments), these seven core categories were grouped into Essential Factors (student agency, voice and choice), Contextual Factors (instructional practices; school culture; engaging families and the community), Synergistic Factors (instructional leadership) and Cornerstone Factors (education as a fundamental cultural value; preservice, in-service and ongoing teacher development). In addition, sub-factors emerged from recurring codes in the data and identified specific characteristics and actions found in developmentally responsive, intellectually engaging middle-level learning environments. Although this study focused on 12 schools in Finland, Germany and Canada, it informs the practice of educators working with early adolescent learners in middle-level learning environments internationally. The authentic voices of early adolescent learners are the most important resource educators have to gauge if they are creating effective learning environments for their students. Ongoing professional dialogue and learning is essential to ensure teachers are supported in their work and develop the pedagogical practices needed to meet the needs of early adolescent learners. It is critical to balance consistency, coherence and dependability in the school environment with the necessary flexibility in order to support the unique learning needs of early adolescents. Educators must intentionally create a school culture that unites teachers, students and their families in support of a common purpose, as well as nurture positive relationships between the school and its community. A large, urban school district in Canada has implemented a school cohort-based model to begin to bring developmentally responsive, intellectually engaging middle-level learning environments to scale.

Keywords: Developmentally responsive learning environments, early adolescents, middle-level learning, middle years, instructional leadership, instructional practices, intellectually engaging learning environments, leadership dimensions, student agency.

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Authors: Arundhati Devi Maibam, K. Ingocha Singh

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Cervical cancer is preventable if detected early. Determination of risk factors is essential to plan screening programmes to prevent the disease. To study the demographic risk factors of cervical cancer among Manipuri women, information on age, marital status, educational level, monthly family income and socioeconomic status were collected through a pre-tested interview schedule. In this study, 64 incident cases registered at the RT Dept, RIMS (Regional Institute of Medical Sciences), Imphal, Manipur, India during 2008-09 participated. Data were entered in Microsoft Excel and the results were expressed in percentages. Among the 64 patients with cervical cancer, 56 (88.9%) were in the age group of 40+ years. The majority of the patients were from rural areas (68.75%) and 31.25% were from urban areas. The majority of the patients were Hindus (73%), 55(85.9%) were of low educational level, 43(67.2%) were married, and 36 (56.25%) belonged to Class IV socioeconomic status. In conclusion, if detected early, cervical cancer is preventable and curable. The potential risk factors need to be identified and women in the risk group need to be motivated for screening. Affordable screening programmes and health care resources will help in lessening the burden of the disease.

Keywords: Cervical cancer, Manipuri women, RIIMS, Socio-demographic risk factors.

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Authors: Ali. Marjani, M. Farsi, M. Rahimizadeh

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Chickpea (Cicer arietinum L.) is one of the important grain legume crops in the world. However, drought stress is a serious threat to chickpea production, and development of drought-resistant varieties is a necessity. Field experiments were conducted to evaluate the response of 8 chickpea genotypes (MCC* 696, 537, 80, 283, 392, 361, 252, 397) and drought stress (S1: non-stress, S2: stress at vegetative growth stage, S3: stress at early bloom, S4: stress at early pod visible) at different growth stages. Experiment was arranged in split plot design with four replications. Difference among the drought stress time was found to be significant for investigated traits except biological yield. Differences were observed for genotypes in flowering time, pod information time, physiological maturation time and yield. Plant height reduced due to drought stress in vegetative growth stage. Stem dry weight reduced due to drought stress in pod visibly. Flowering time, maturation time, pod number, number of seed per plant and yield cause of drought stress in flowering was also reduced. The correlation between yield and number of seed per plant and biological yield was positive. The MCC283 and MCC696 were the high-tolerance genotypes. These results demonstrated that drought stress delayed phonological growth in chickpea and that flowering stage is sensitive.

Keywords: Chickpea, drought stress, growth stage, tolerance.

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Authors: S. Padmapriya

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Vehicular Adhoc Networks (VANETs), a subset of Mobile Adhoc Networks (MANETs), refers to a set of smart vehicles used for road safety. This vehicle provides communication services among one another or with the Road Side Unit (RSU). Security is one of the most critical issues related to VANET as the information transmitted is distributed in an open access environment. As each vehicle is not a source of all messages, most of the communication depends on the information received from other vehicles. To protect VANET from malicious action, each vehicle must be able to evaluate, decide and react locally on the information received from other vehicles. Therefore, message verification is more challenging in VANET because of the security and privacy concerns of the participating vehicles. To overcome security threats, we propose Monitoring Algorithm that detects malicious nodes based on the pre-selected threshold value. The threshold value is compared with the distrust value which is inherently tagged with each vehicle. The proposed Monitoring Algorithm not only detects malicious vehicles, but also isolates the malicious vehicles from the network. The proposed technique is simulated using Network Simulator2 (NS2) tool. The simulation result illustrated that the proposed Monitoring Algorithm outperforms the existing algorithms in terms of malicious node detection, network delay, packet delivery ratio and throughput, thereby uplifting the overall performance of the network.

Keywords: VANET, security, malicious vehicle detection, threshold value, distrust value.

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Authors: Qing Dai, Zhengkui Lin, Jiajia Zhang, Yi Qu

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Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving.

Keywords: Autonomous cars, bottleneck model, activity utility, user equilibrium.

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: Intelligent transportation systems, object detection, video processing, road traffic, vehicle counting, vehicle classification.

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Authors: Ki Ok Choi, Sung Ho Hong, Dong Suck Kim, Don Mook Choi

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Rack type warehouses are different from general buildings in the kinds, amount, and arrangement of stored goods, so the fire risk of rack type warehouses is different from those buildings. The fire pattern of rack type warehouses is different in combustion characteristic and storing condition of stored goods. The initial fire burning rate is different in the surface condition of materials, but the running time of fire is closely related with the kinds of stored materials and stored conditions. The stored goods of the warehouse are consisted of diverse combustibles, combustible liquid, and so on. Fire detection time may be delayed because the residents are less than office and commercial buildings. If fire detectors installed in rack type warehouses are inadaptable, the fire of the warehouse may be the great fire because of delaying of fire detection. In this paper, we studied what kinds of fire detectors are optimized in early detecting of rack type warehouse fire by real-scale fire tests. The fire detectors used in the tests are rate of rise type, fixed type, photo electric type, and aspirating type detectors. We considered optimum fire detecting method in rack type warehouses suggested by the response characteristic and comparative analysis of the fire detectors.

Keywords: Fire detector, rack, response characteristic, warehouse.

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Authors: Grace E. Santella, Shawn G. Gallaher, Joseph P. Smith

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In order to determine the importance of small-system riverine heat flux on regional landfast sea ice breakup, our study explores the annual spring freshet of the Sagavanirktok River from 2014-2019. Seasonal heat cycling ultimately serves as the driving mechanism behind the freshet; however, as an emerging area of study, the extent to which inland thermodynamics influence coastal tundra geomorphology and connected landfast sea ice has not been extensively investigated in relation to small-scale Arctic river systems. The Sagavanirktok River is a small-to-midsized river system that flows south-to-north on the Alaskan North Slope from the Brooks mountain range to the Beaufort Sea at Prudhoe Bay. Seasonal warming in the spring rapidly melts snow and ice in a northwards progression from the Brooks Range and transitional tundra highlands towards the coast and when coupled with seasonal precipitation, results in a pulsed freshet that propagates through the Sagavanirktok River. The concentrated presence of newly exposed vegetation in the transitional tundra region due to spring melting results in higher absorption of solar radiation due to a lower albedo relative to snow-covered tundra and/or landfast sea ice. This results in spring flood runoff that advances over impermeable early-season permafrost soils with elevated temperatures relative to landfast sea ice and sub-ice flow. We examine the extent to which interannual temporal variability influences the onset and magnitude of river discharge by analyzing field measurements from the United States Geological Survey (USGS) river and meteorological observation sites. Rapid influx of heat to the Arctic Ocean via riverine systems results in a noticeable decay of landfast sea ice independent of ice breakup seaward of the shear zone. Utilizing MODIS imagery from NASA’s Terra satellite, interannual variability of river discharge is visualized, allowing for optical validation that the discharge flow is interacting with landfast sea ice. Thermal erosion experienced by sediment fast ice at the arrival of warm overflow preconditions the ice regime for rapid thawing. We investigate the extent to which interannual heat flux from the Sagavanirktok River’s freshet significantly influences the onset of local landfast sea ice breakup. The early-season warming of atmospheric temperatures is evidenced by the presence of storms which introduce liquid, rather than frozen, precipitation into the system. The resultant decreased albedo of the transitional tundra supports the positive relationship between early-season precipitation events, inland thermodynamic cycling, and degradation of landfast sea ice. Early removal of landfast sea ice increases coastal erosion in these regions and has implications for coastline geomorphology which stress industrial, ecological, and humanitarian infrastructure.

Keywords: Albedo, freshet, landfast sea ice, riverine heat flux, seasonal heat cycling.

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Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

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Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: Detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter.

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, Fuzzy c means, Liver segmentation.

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Authors: Sirimanee Banjong

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This study aimed to 1) develop pre-service teachers’ leadership skills through camp-based learning, and 2) develop preservice teachers’ teamwork skills through camp-based learning. An applied research methodology was used. The target group was derived from a purposive selection. It involved 32 fourth-year students in Early Childhood Education Program enrolling a course entitled Seminar in Early Childhood Education provided during second semester of academic year 2013. The treatment was camp-based learning activities which applied a PDCA process including four stages: 1) plan, 2) do, 3) check, and 4) act. Research instruments were a learning camp program, a camp-based learning management plan, a 5-level assessment form for leadership skills and a 5-level assessment form for assessing teamwork skills. Data were analyzed using descriptive statistics. Results were: 1) pre-service teachers’ leadership skills yielded the before treatment average score at x= 3.4, S.D.=0.6 2and the after-treatment average score at x 4.29 , S.D.=0.66 pre-service teachers’ teamwork skills yielded the before-treatment average score at x=3.31, S.D.=0.60 and the after-treatment average score at x=4.42, S.D.=0.66 Both differences were statistically significant at the .05 level. Thus, the pre-service teachers’ leadership and teamwork skills were significantly improved through the camp-based learning approach.

Keywords: Learning camp, leadership skills, teamwork skills.

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Authors: Paria Soleimani, Arezoo Neshati

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Myocardial infarction is one of the leading causes of death in the world. Some of these deaths occur even before the patient reaches the hospital. Myocardial infarction occurs as a result of impaired blood supply. Because the most of these deaths are due to coronary artery disease, hence the awareness of the warning signs of a heart attack is essential. Some heart attacks are sudden and intense, but most of them start slowly, with mild pain or discomfort, then early detection and successful treatment of these symptoms is vital to save them. Therefore, importance and usefulness of a system designing to assist physicians in early diagnosis of the acute heart attacks is obvious. The main purpose of this study would be to enable patients to become better informed about their condition and to encourage them to seek professional care at an earlier stage in the appropriate situations. For this purpose, the data were collected on 711 heart patients in Iran hospitals. 28 attributes of clinical factors can be reported by patients; were studied. Three logistic regression models were made on the basis of the 28 features to predict the risk of heart attacks. The best logistic regression model in terms of performance had a C-index of 0.955 and with an accuracy of 94.9%. The variables, severe chest pain, back pain, cold sweats, shortness of breath, nausea and vomiting, were selected as the main features.

Keywords: Coronary heart disease, acute heart attacks, prediction, logistic regression.

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Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy

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Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.

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Authors: Karuppasamy Pandian. M, Krishna Raj. K, Sabarinath. K, Sandeep. G, Sanal Kumar. V.R.

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Numerical studies have been carried out using a two dimensional code to examine the influence of pressure / thrust transient of solid propellant rockets at liftoff. This code solves unsteady Reynolds-averaged thin-layer Navier–Stokes equations by an implicit LU-factorization time-integration method. The results from the parametric study indicate that when the port is narrow there is a possibility of increase in pressure / thrust-rise rate due to relatively high flame spread rate. Parametric studies further reveal that flame spread rate can be altered by altering the propellant properties, igniter jet characteristics and nozzle closure burst pressure without altering the grain configuration and/or the mission demanding thrust transient. We observed that when the igniter turbulent intensity is relatively low the vehicle could liftoff early due to the early flow choking of the rocket nozzle. We concluded that the high pressurization-rate has structural implications at liftoff in addition to transient burning effect. Therefore prudent selection of the port geometry and the igniter, for meeting the mission requirements, within the given envelop are meaningful objectives for any designer for the smooth liftoff of solid propellant rockets.

Keywords: Igniter Characteristics, Solid Propellant Rocket, SRM Liftoff, Starting Thrust Transient.

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Authors: Robin Lok-Wang

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The center/unit for industry engagement and collaboration, as well as Internship, plays a significant role at a university. In general, the Center serves as the official interface between industry and the school or department to cultivate students’ early exposure to professional experience. The missions of the Center are not limited to provide a communication channel and collaborative platform for the industries and the university but also to assist students to build their career paths early while still at the university. In recent years, a cooperative education experience (commonly known as a co-op) has been strongly advocated for students to make the school-to-work transition. The nature of the co-op program is not only consistent with the internships/final year design projects, but it is also more industrial-oriented with academic support from faculty at the university. The purpose of this paper is to describe an approach to how cooperative education experience can be integrated into the engineering curriculum. It provides a mutual understanding and exchange of ideas for the approach between the university and industry. A suggested format in terms of timeline, duration, selection of candidates, students, and companies’ expectations for the co-op program is described. Also, feedback from employers/industries shows that a longer-term co-op program is well suited for students compared with a short-term internship. To this end, it provides an insight into collaboration and/or partnership between the university and the industries to prepare professional work-ready graduates.

Keywords: Cooperative education, internship, industry collaboration, engineering curriculum.

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Authors: Chiang Tzu-Chiang, Chang Jia-Lin, Tsai Yue-Fu, Li Sha-Pai

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With the advantage of wireless network technology, there are a variety of mobile applications which make the issue of wireless sensor networks as a popular research area in recent years. As the wireless sensor network nodes move arbitrarily with the topology fast change feature, mobile nodes are often confronted with the void issue which will initiate packet losing, retransmitting, rerouting, additional transmission cost and power consumption. When transmitting packets, we would not predict void problem occurring in advance. Thus, how to improve geographic routing with void avoidance in wireless networks becomes an important issue. In this paper, we proposed a greedy geographical void routing algorithm to solve the void problem for wireless sensor networks. We use the information of source node and void area to draw two tangents to form a fan range of the existence void which can announce voidavoiding message. Then we use source and destination nodes to draw a line with an angle of the fan range to select the next forwarding neighbor node for routing. In a dynamic wireless sensor network environment, the proposed greedy void avoiding algorithm can be more time-saving and more efficient to forward packets, and improve current geographical void problem of wireless sensor networks.

Keywords: Wireless sensor network, internet routing, wireless network, greedy void avoiding algorithm, bypassing void.

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Authors: Wafa' S.Al-Sharafat, Reyadh Naoum

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Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportunity for malicious users to do their damage becomes very great and lucrative. The objective of this paper is to incorporate different techniques into classier system to detect and classify intrusion from normal network packet. Among several techniques, Steady State Genetic-based Machine Leaning Algorithm (SSGBML) will be used to detect intrusions. Where Steady State Genetic Algorithm (SSGA), Simple Genetic Algorithm (SGA), Modified Genetic Algorithm and Zeroth Level Classifier system are investigated in this research. SSGA is used as a discovery mechanism instead of SGA. SGA replaces all old rules with new produced rule preventing old good rules from participating in the next rule generation. Zeroth Level Classifier System is used to play the role of detector by matching incoming environment message with classifiers to determine whether the current message is normal or intrusion and receiving feedback from environment. Finally, in order to attain the best results, Modified SSGA will enhance our discovery engine by using Fuzzy Logic to optimize crossover and mutation probability. The experiments and evaluations of the proposed method were performed with the KDD 99 intrusion detection dataset.

Keywords: MSSGBML, Network Intrusion Detection, SGA, SSGA.

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Authors: Javed Parvez, Mushtaq Ahmad Peer

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Mobile Ad hoc networks (MANETs) are collections of wireless mobile nodes dynamically reconfiguring and collectively forming a temporary network. These types of networks assume existence of no fixed infrastructure and are often useful in battle-field tactical operations or emergency search-and-rescue type of operations where fixed infrastructure is neither feasible nor practical. They also find use in ad hoc conferences, campus networks and commercial recreational applications carrying multimedia traffic. All of the above applications of MANETs require guaranteed levels of performance as experienced by the end-user. This paper focuses on key challenges in provisioning predetermined levels of such Quality of Service (QoS). It also identifies functional areas where QoS models are currently defined and used. Evolving functional areas where performance and QoS provisioning may be applied are also identified and some suggestions are provided for further research in this area. Although each of the above functional areas have been discussed separately in recent research studies, since these QoS functional areas are highly correlated and interdependent, a comprehensive and comparative analysis of these areas and their interrelationships is desired. In this paper we have attempted to provide such an overview.

Keywords: Bandwidth Reservation, Congestion, DynamicNetwork Topology, End-to-End Delay, Flexible QoS Model forMANET(FQMM), Hidden Terminal, Mobile AdhocNetwork(MANET), Packet Jitter, Queuing, Quality-of-Service(QoS), Relative Bandwidth Service Differentiation(RBSD), Resource ReSerVation Protocol (RSVP).

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Authors: Mat Isa, C. M., Mohd Saman, H., Mohd Nasir, S. R., Jaapar, A.

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International market expansion involves a strategic process of market entry decision through which a firm expands its operation from domestic to the international domain. Hence, entry timing choices require the needs to balance the early entry risks and the problems in losing opportunities as a result of late entry into a new market. Questionnaire surveys administered to 115 Malaysian construction firms operating in 51 countries worldwide have resulted in 39.1 percent response rate. Factor analysis was used to determine the most significant factors affecting entry timing choices of the firms to penetrate the international market. A logistic regression analysis used to examine the firms’ entry timing choices, indicates that the model has correctly classified 89.5 per cent of cases as late movers. The findings reveal that the most significant factor influencing the construction firms’ choices as late movers was the firm factor related to the firm’s international experience, resources, competencies and financing capacity. The study also offers valuable information to construction firms with intention to internationalize their businesses.

Keywords: Factors, early movers, entry timing choices, late movers, Logistic Regression Model, Principal Axis Factorial Analysis, Malaysian construction firms.

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Authors: L. Vujičić, Ž. Ivković, Ž. Boneta

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There is a widespread belief in everyday discourse that science subjects (physics, chemistry and biology) are, along with math, the most difficult school subjects in the education of an individual. This assumption is usually justified by the following facts: low GPA in these subjects, the number of pupils who fail these subjects is high in comparison to other subjects, and the number of pupils interested in continuing their studies in the fields with a focus on science subjects is lower compared to non-science-oriented fields. From that perspective, the project: “Could it be different? How do children explore it?” becomes extremely interesting because it is focused on young children and on the introduction of new methods, with aim of arousing interest in scientific literacy development in 10 kindergartens by applying the methodology of an action research, with an ethnographic approach. We define scientific literacy as a process of encouraging and nurturing the research and explorative spirit in children, as well as their natural potential and abilities that represent an object of scientific research: to learn about exploration by conducting exploration. Upon project completion, an evaluation questionnaire was created for the parents of the children who had participated in the project, as well as for those whose children had not been involved in the project. The purpose of the first questionnaire was to examine the level of satisfaction with the project implementation and its outcomes among those parents whose children had been involved in the project (N=142), while the aim of the second questionnaire was to find out how much the parents of the children not involved (N=154) in this activity were interested in this topic.

Keywords: Documenting, early childhood education, evaluation questionnaire for parents, scientific literacy development.

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD, as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches, such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: Autism spectrum disorder, clustering, optimization, unsupervised machine learning.

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Authors: Kalangi Rodrigo, Kelum Manamendra-Arachchi

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Bones, teeth, and shells have been acknowledged over the last two centuries as evidence of chronology, Palaeo-environment, and human activity. Faunal traces are valid evidence of past situations because they have properties that have not changed over long periods. Sri Lanka has been known as an Island, which has a diverse variety of prehistoric occupation among ecological zones. Defining the Paleoecology of the past societies has been an archaeological thought developed in the 1960s. It is mainly concerned with the reconstruction from available geological and biological evidence of past biota, populations, communities, landscapes, environments, and ecosystems. This early and persistent human fossil, technical, and cultural florescence, as well as a collection of well-preserved tropical-forest rock shelters with associated 'on-site ' Palaeoenvironmental records, makes Sri Lanka a central and unusual case study to determine the extent and strength of early human tropical forest encounters. Excavations carried out in prehistoric caves in the low country wet zone has shown that in the last 50,000 years, the temperature in the lowland rainforests has not exceeded 5 degrees. Based on Semnopithecus Priam (Gray Langur) remains unearthed from wet zone prehistoric caves, it has been argued periods of momentous climate changes during the Last Glacial Maximum (LGM) and Terminal Pleistocene/Early Holocene boundary, with a recognizable preference for semi-open ‘Intermediate’ rainforest or edges. Continuous genus Acavus and Oligospira occupation along with uninterrupted horizontal pervasive of Canarium sp. (‘kekuna’ nut) have proven that temperatures in the lowland rain forests have not changed by at least 5 °C over the last 50,000 years. Site catchment or territorial analysis cannot be any longer defensible, due to time-distance based factors as well as optimal foraging theory failed as a consequence of prehistoric people were aware of the decrease in cost-benefit ratio and located sites, and generally played out a settlement strategy that minimized the ratio of energy expended to energy produced.

Keywords: Palaeo-environment, palaeo-ecology, palaeo-climate, prehistory, zooarchaeology.

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