Search results for: neighbor joining

Authors: Habibi Said Mustafa, Hiroko Ono

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Since 2006, Afghanistan is dealing with one of the most dramatic trend of urban movement in its history, cities and towns are expanding in size and number. Kabul is the capital of Afghanistan and as well as the fast-growing city in the Asia. The influx of the returnees from neighbor countries and other provinces of Afghanistan caused high rate of artificial growth which slums increased. As an unwanted consequence of this growth, today informal settlements have covered a vast portion of the city. Land Readjustment (LR) has proved to be an important tool for developing informal settlements and reorganizing urban areas but its implementation always varies from country to country and region to region within the countries. Consequently, to successfully develop the informal settlements in Kabul, we need to define an Afghan model of LR specifically for Afghanistan which needs to incorporate all those factors related to the socio-economic condition of the country. For this purpose, a part of the old city of Kabul has selected as a study area which is located near the Central Business District (CBD). After the further analysis and incorporating all needed factors, the result shows a positive potential for the implementation of an adaptable Land Readjustment model for Kabul city which is more sustainable and socio-economically friendly. It will enhance quality of life and provide better urban services for the residents. Moreover, it will set a vision and criteria by which sustainable developments shall proceed in other similar informal settlements of Kabul.

Keywords: Adaptation, informal settlements, Kabul, land readjustment, preservation.

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Authors: Saimir Heta, Ilma Robo, Vera Ostreni, Glorja Demika, Sonila Kapaj

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Suturing, as a procedure of joining the lips of the lembo or wound, is important at the beginning of the healing process. This procedure helps to pass the healing process from the procedure per secundam to the stages of healing per primam, thus logically reducing the healing time of the wound. The purpose of this article is to publish some data on the clinical characteristics of periodontal suturing, presenting the advantages and disadvantages of different types of suture threads. The article is a mini-review type of articles selected from the application of keywords on the PubMed page. The number of articles extracted from this article publication page is in accordance with the 10-year publication time limit. The element that remains in the individual selection of the dentist applying the suture is the selection of the suture material. At a moment when some types of sutures are offered for use, some elements should be considered in the selection of the suture depending on the constituent material, the cross-section of the suture elements, and whether it collects bacteria in the "pits" created by the material. The presence of bacteria is a source of infection and possible delay in the healing of the sutured wound. The marketing of suture types offers a variety of materials, from which the selection of the most suitable suture type for specific application cases is a personal indication of the dental surgeon based on professional experiences and knowledge in this field.

Keywords: Suture, suture material, types of sutures, clinical application.

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Authors: Frank Emmert-Streib, Matthias Dehmer, Jing Liu, Max Muhlhauser

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The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, generalized trees, graph alignment, DNA microarray data, cervical cancer.

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Authors: Saliha Gachi, Mouloud Aissani, Fouad Boubenider

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Friction Stir Welding (FSW) is a solid-state welding technique that can join material without melting the plates to be welded. In this work, we are interested to demonstrate the potentiality of FSW for joining the heat-treatable aluminum alloy 2024-T3 which is reputed as difficult to be welded by fusion techniques. Thereafter, the FSW joint is compared with another one obtained from a conventional fusion process Tungsten Inert Gas (TIG). FSW welds are made up using an FSW tool mounted on a milling machine. Single pass welding was applied to fabricated TIG joint. The comparison between the two processes has been made on the temperature evolution, mechanical and microstructure behavior. The microstructural examination revealed that FSW weld is composed of four zones: Base metal (BM), Heat affected zone (HAZ), Thermo-mechanical affected zone (THAZ) and the nugget zone (NZ). The NZ exhibits a recrystallized equiaxed refined grains that induce better mechanical properties and good ductility compared to TIG joint where the grains have a larger size in the welded region compared with the BM due to the elevated heat input. The microhardness results show that, in FSW weld, the THAZ contains the lowest microhardness values and increase in the NZ; however, in TIG process, the lowest values are localized on the NZ.

Keywords: Friction stir welding, tungsten inert gaz, aluminum, microstructure.

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: Artificial neural networks, fuel consumption, machine learning, regression, statistical tests.

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Authors: E. Ghabouli

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Intermediate cities which also called medium size cities have an important role in the process of globalization. It is argued that, in some cases this type of cities may be depopulated or in otherwise may be transformed as the periphery of metropolitans, so that the personal identity of the city and its local cultural heritage could suffer from its neighbor metropolitan. Over the last decades, the role of tourism in the development process and the cultural heritage has increased. The impact of tourism on socioeconomic growth makes motivation for the study of tourism development in regional and urban planning process. There are evidences that tourism has a positive impact in local development and makes economic motivations for cultural heritage protection. In this study, by considering the role of tourism in local development, especially by its economic and socio-cultural impacts, it is tried to introduce a strategy for tourism development through a method of urban planning for intermediate cities called as Base plan. Damavand is an intermediate city located in Tehran province, Iran with a high potential in tourism by its local specific characteristic like social structure, antiquities and natural attractions. It’s selected as a suitable case study for intended strategy which is a combination of urban planning and tourism development methods. Focusing on recognition of the historical and cultural heritage of Damavand, in this paper through “base plan methodology” a strategy of urban planning toward tourism development is prepared in order to make tourism development as a support for cultural heritage of this city.

Keywords: Urban planning, tourism, cultural heritage, intermediate cities.

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Authors: Sima Ziaee, Khosro Jafarpur

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Among all mechanical joining processes, welding has been employed for its advantage in design flexibility, cost saving, reduced overall weight and enhanced structural performance. However, for structures made of relatively thin components, welding can introduce significant buckling distortion which causes loss of dimensional control, structural integrity and increased fabrication costs. Different parameters can affect buckling behavior of welded thin structures such as, heat input, welding sequence, dimension of structure. In this work, a 3-D thermo elastic-viscoplastic finite element analysis technique is applied to evaluate the effect of shell dimensions on buckling behavior and entropy generation of welded thin shells. Also, in the present work, the approximated longitudinal transient stresses which produced in each time step, is applied to the 3D-eigenvalue analysis to ratify predicted buckling time and corresponding eigenmode. Besides, the possibility of buckling prediction by entropy generation at each time is investigated and it is found that one can predict time of buckling with drawing entropy generation versus out of plane deformation. The results of finite element analysis show that the length, span and thickness of welded thin shells affect the number of local buckling, mode shape of global buckling and post-buckling behavior of welded thin shells.

Keywords: Buckling behavior, Elastic viscoplastic model, Entropy generation, Finite element method, Shell dimensions.

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Authors: Aya Salama

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Digital Twin has emerged as a compelling research area, capturing the attention of scholars over the past decade. It finds applications across diverse fields, including smart manufacturing and healthcare, offering significant time and cost savings. Notably, it often intersects with other cutting-edge technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, the concept of a Human Digital Twin (HDT) is still in its infancy and requires further demonstration of its practicality. HDT takes the notion of Digital Twin a step further by extending it to living entities, notably humans, who are vastly different from inanimate physical objects. The primary objective of this research was to create an HDT capable of automating real-time human responses by simulating human behavior. To achieve this, the study delved into various areas, including clustering, supervised classification, topic extraction, and sentiment analysis. The paper successfully demonstrated the feasibility of HDT for generating personalized responses in social messaging applications. Notably, the proposed approach achieved an overall accuracy of 63%, a highly promising result that could pave the way for further exploration of the HDT concept. The methodology employed Random Forest for clustering the question database and matching new questions, while K-nearest neighbor was utilized for sentiment analysis.

Keywords: Human Digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification and clustering.

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Authors: Laor Boongasame, Veera Boonjing, Ho-fung Leung

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Buyer coalition with a combination of items is a group of buyers joining together to purchase a combination of items with a larger discount. The primary aim of existing buyer coalition with a combination of items research is to generate a large total discount. However, the aim is hard to achieve because this research is based on the assumption that each buyer completely knows other buyers- information or at least one buyer knows other buyers- information in a coalition by exchange of information. These assumption contrast with the real world environment where buyers join a coalition with incomplete information, i.e., they concerned only with their expected discounts. Therefore, this paper proposes a new buyer community coalition formation with a combination of items scheme, called the Community Compromised Combinatorial Coalition scheme, under such an environment of incomplete information. In order to generate a larger total discount, after buyers who want to join a coalition propose their minimum required saving, a coalition structure that gives a maximum total retail prices is formed. Then, the total discount division of the coalition is divided among buyers in the coalition depending on their minimum required saving and is a Pareto optimal. In mathematical analysis, we compare concepts of this scheme with concepts of the existing buyer coalition scheme. Our mathematical analysis results show that the total discount of the coalition in this scheme is larger than that in the existing buyer coalition scheme.

Keywords: group decision and negotiations, group buying, gametheory, combinatorial coalition formation, Pareto optimality

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Authors: Sunil Gupta, Harsh Kumar Verma, AL Sangal

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Wireless sensor networks can be used to measure and monitor many challenging problems and typically involve in monitoring, tracking and controlling areas such as battlefield monitoring, object tracking, habitat monitoring and home sentry systems. However, wireless sensor networks pose unique security challenges including forgery of sensor data, eavesdropping, denial of service attacks, and the physical compromise of sensor nodes. Node in a sensor networks may be vanished due to power exhaustion or malicious attacks. To expand the life span of the sensor network, a new node deployment is needed. In military scenarios, intruder may directly organize malicious nodes or manipulate existing nodes to set up malicious new nodes through many kinds of attacks. To avoid malicious nodes from joining the sensor network, a security is required in the design of sensor network protocols. In this paper, we proposed a security framework to provide a complete security solution against the known attacks in wireless sensor networks. Our framework accomplishes node authentication for new nodes with recognition of a malicious node. When deployed as a framework, a high degree of security is reachable compared with the conventional sensor network security solutions. A proposed framework can protect against most of the notorious attacks in sensor networks, and attain better computation and communication performance. This is different from conventional authentication methods based on the node identity. It includes identity of nodes and the node security time stamp into the authentication procedure. Hence security protocols not only see the identity of each node but also distinguish between new nodes and old nodes.

Keywords: Authentication, Key management, Wireless Sensornetwork, Elliptic curve cryptography (ECC).

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Authors: Kanthida Kusonmano, Michael Netzer, Bernhard Pfeifer, Christian Baumgartner, Klaus R. Liedl, Armin Graber

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Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.

Keywords: Classification, High dimensional data, Machine learning

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Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami

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Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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Authors: S. D. El Wakil

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The research work reported here was aimed at investigating the feasibility of joining high-porosity stainless steel discs and wrought iron bars by friction welding. The sound friction-welded joints were then subjected to a metallurgical investigation and an analysis of failure resulting from tensile loading. Discs having 50 mm diameter and 10 mm thickness were produced by loose sintering of stainless steel powder at a temperature of 1350 ^oC in an argon atmosphere for one hour. Minor machining was then carried out to control the dimensions of the discs, and the density of each disc could then be determined. The level of porosity was calculated and was found to be about 40% in all of those discs. Solid wrought iron bars were also machined to facilitate tensile testing of the joints produced by friction welding. Using our previously gained experience, the porous stainless steel disc and the wrought iron tube were successfully friction welded. SEM was employed to examine the fracture surface after a tensile test of the joint in order to determine the type of failure. It revealed that the failure did not occur in the joint, but rather in the in the porous metal in the area adjacent to the joint. The load carrying capacity was actually determined by the strength of the porous metal and not by that of the welded joint. Macroscopic and microscopic metallographic examinations were also performed and showed that the welded joint involved a dense heat-affected zone where the porous metal underwent densification at elevated temperature, explaining and supporting the findings of the SEM study.

Keywords: Fracture of friction-welded joints, metallurgy of friction welding, solid-porous structures, strength of joint.

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Authors: C. W. Hsu, C. N. Liang, L. Y. Ke, F. Y. Huang

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Many accidents were happened because of fast driving, habitual working overtime or tired spirit. This paper presents a solution of remote warning for vehicles collision avoidance using vehicular communication. The development system integrates dedicated short range communication (DSRC) and global position system (GPS) with embedded system into a powerful remote warning system. To transmit the vehicular information and broadcast vehicle position; DSRC communication technology is adopt as the bridge. The proposed system is divided into two parts of the positioning andvehicular units in a vehicle. The positioning unit is used to provide the position and heading information from GPS module, and furthermore the vehicular unit is used to receive the break, throttle, and othersignals via controller area network (CAN) interface connected to each mechanism. The mobile hardware are built with an embedded system using X86 processor in Linux system. A vehicle is communicated with other vehicles via DSRC in non-addressed protocol with wireless access in vehicular environments (WAVE) short message protocol. From the position data and vehicular information, this paper provided a conflict detection algorithm to do time separation and remote warning with error bubble consideration. And the warning information is on-line displayed in the screen. This system is able to enhance driver assistance service and realize critical safety by using vehicular information from the neighbor vehicles.KeywordsDedicated short range communication, GPS, Control area network, Collision avoidance warning system.

Keywords: Dedicated short range communication, GPS, Control area network, Collision avoidance warning system.

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Authors: Bhed Bahadur Bista

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Network layer multicast, i.e. IP multicast, even after many years of research, development and standardization, is not deployed in large scale due to both technical (e.g. upgrading of routers) and political (e.g. policy making and negotiation) issues. Researchers looked for alternatives and proposed application/overlay multicast where multicast functions are handled by end hosts, not network layer routers. Member hosts wishing to receive multicast data form a multicast delivery tree. The intermediate hosts in the tree act as routers also, i.e. they forward data to the lower hosts in the tree. Unlike IP multicast, where a router cannot leave the tree until all members below it leave, in overlay multicast any member can leave the tree at any time thus disjoining the tree and disrupting the data dissemination. All the disrupted hosts have to rejoin the tree. This characteristic of the overlay multicast causes multicast tree unstable, data loss and rejoin overhead. In this paper, we propose that each node sets its leaving time from the tree and sends join request to a number of nodes in the tree. The nodes in the tree will reject the request if their leaving time is earlier than the requesting node otherwise they will accept the request. The node can join at one of the accepting nodes. This makes the tree more stable as the nodes will join the tree according to their leaving time, earliest leaving time node being at the leaf of the tree. Some intermediate nodes may not follow their leaving time and leave earlier than their leaving time thus disrupting the tree. For this, we propose a proactive recovery mechanism so that disrupted nodes can rejoin the tree at predetermined nodes immediately. We have shown by simulation that there is less overhead when joining the multicast tree and the recovery time of the disrupted nodes is much less than the previous works. Keywords

Keywords: Network layer multicast, Fault Resilience, IP multicast

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Authors: Mohammed A. Elhaj, Jamal S. Yassin

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Owing to the lack of synchronization between the solar energy availability and the heat demands in a specific application, the energy storing sub-system is necessary to maintain the continuity of thermal process. The present work is dealing with an active solar heating storing system in which an air solar collector is connected to storing unit where this energy is distributed and provided to the heated space in a controlled manner. The solar collector is a box type absorber where the air flows between a number of vanes attached between the collector absorber and the bottom plate. This design can improve the efficiency due to increasing the heat transfer area exposed to the flowing air, as well as the heat conduction through the metal vanes from the top absorbing surface. The storing unit is a packed bed type where the air is coming from the air collector and circulated through the bed in order to add/remove the energy through the charging / discharging processes, respectively. The major advantage of the packed bed storage is its high degree of thermal stratification. Numerical solution of the packed bed energy storage is considered through dividing the bed into a number of equal segments for the bed particles and solved the energy equation for each segment depending on the neighbor ones. The studied design and performance parameters in the developed simulation model including, particle size, void fraction, etc. The final results showed that the collector efficiency was fluctuated between 55%-61% in winter season (January) under the climatic conditions of Misurata in Libya. Maximum temperature of 52ºC is attained at the top of the bed while the lower one is 25ºC at the end of the charging process of hot air into the bed. This distribution can satisfy the required load for the most house heating in Libya.

Keywords: Solar energy, thermal process, performance, collector, packed bed, numerical analysis, simulation.

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Authors: Jindřiška Šedová

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The Czech Republic is a country whose economy has undergone a transformation since 1989. Since joining the EU it has been striving to reduce the differences in its economic standard and the quality of its institutional environment in comparison with developed countries. According to an assessment carried out by the World Bank, the Czech Republic was long classed as a country whose institutional development was seen as problematic. For many years one of the things it was rated most poorly on was its bankruptcy law. The new Insolvency Act, which is a modern law in terms of its treatment of bankruptcy, was first adopted in the Czech Republic in 2006. This law, together with other regulatory measures, offers debtridden Czech economic subjects legal instruments which are well established and in common practice in developed market economies. Since then, analyses performed by the World Bank and the London EBRD have shown that there have been significant steps forward in the quality of Czech bankruptcy law. The Czech Republic still lacks an analytical apparatus which can offer a structured characterisation of the general and specific conditions of Czech company and household debt which is subject to current changes in the global economy. This area has so far not been given the attention it deserves. The lack of research is particularly clear as regards analysis of household debt and householders- ability to settle their debts in a reasonable manner using legal and other state means of regulation. We assume that Czech households have recourse to a modern insolvency law, yet the effective application of this law is hampered by the inconsistencies in the formal and informal institutions involved in resolving debt. This in turn is based on the assumption that this lack of consistency is more marked in cases of personal bankruptcy. Our aim is to identify the symptoms which indicate that for some time the effective application of bankruptcy law in the Czech Republic will be hindered by factors originating in householders- relative inability to identify the risks of falling into debt.

Keywords: bankruptcy law, household debt, consumer bankruptcy, business bankruptcy

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Authors: Er, A. C., Rosli, M. H., Asmahani A., Mohamad Naim M. R., Harsuzilawati M.

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Dengue is a mosquito-borne infection that has peaked to an alarming rate in recent decades. It can be found in tropical and sub-tropical climate. In Malaysia, dengue has been declared as one of the national health threat to the public. This study aimed to map the spatial distributions of dengue cases in the district of Hulu Langat, Selangor via a combination of Geographic Information System (GIS) and spatial statistic tools. Data related to dengue was gathered from the various government health agencies. The location of dengue cases was geocoded using a handheld GPS Juno SB Trimble. A total of 197 dengue cases occurring in 2003 were used in this study. Those data then was aggregated into sub-district level and then converted into GIS format. The study also used population or demographic data as well as the boundary of Hulu Langat. To assess the spatial distribution of dengue cases three spatial statistics method (Moran-s I, average nearest neighborhood (ANN) and kernel density estimation) were applied together with spatial analysis in the GIS environment. Those three indices were used to analyze the spatial distribution and average distance of dengue incidence and to locate the hot spot of dengue cases. The results indicated that the dengue cases was clustered (p < 0.01) when analyze using Moran-s I with z scores 5.03. The results from ANN analysis showed that the average nearest neighbor ratio is less than 1 which is 0.518755 (p < 0.0001). From this result, we can expect the dengue cases pattern in Hulu Langat district is exhibiting a cluster pattern. The z-score for dengue incidence within the district is -13.0525 (p < 0.0001). It was also found that the significant spatial autocorrelation of dengue incidences occurs at an average distance of 380.81 meters (p < 0.0001). Several locations especially residential area also had been identified as the hot spots of dengue cases in the district.

Keywords: Dengue, geographic information system (GIS), spatial analysis, spatial statistics

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Authors: Bua Srikos, Phusit Phukamchanoad, Suwaree Yordchim

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The purpose is to study the model and characteristic of participation of the suitable community to lead to develop permanent water marketing in Bang Noi Floating Market, Bangkonti District, Samutsongkhram Province. A total of 342 survey questionnaire was administered to potential respondents. The researchers interviewed the leader of the community. Appreciation Influence Control (AIC) was used to talk with 20 villagers on arena. The findings revealed that overall, most people had the middle level of the participation in developing the durable Bang Noi Floating Market, Bangkonti, Samutsongkhram Province and in aspects of gaining benefits from developing it with atmosphere and a beautiful view for tourism. For example, the landscape is beautiful with public utilities. The participation in preserving and developing Bang Noi Floating Market remains in the former way of life. The basic factor of person affects to the participation of people such as age, level of education, career, and income per month. Most participants are the original hosts that have houses and shops located in the marketing and neighbor. These people involve with the benefits and have the power to make a water marketing strategy, the major role to set the information database. It also found that the leader and the villagers play the important role in setting a five-physical database. Data include level of information such as position of village, territory of village, road, river, and premises. Information of culture consists of a two-level of information, interesting point, and Itinerary. The information occurs from presenting and practicing by the leader and villagers in the community.All of phases are presented for listening and investigating database together in both the leader and villagers in the process of participation.

Keywords: Community Participation, Sustainable Development, Encouragement Tourism.

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Authors: Diya Sarkar, Prafulla C. Mishra

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In a parliamentary system, party discipline is the impulse; when it falls short, the government usually falls. Conceivably, the platform of Indian politics suffers with innumerous practical disorders. The politics of defection is one such specie entailing gross miscarriage of fair conduct turning politics into a game of thrones (powers). This practice of political nomaditude can trace its seed in the womb of British House of Commons. Therein, if a legislator was found to cross the floor, the party considered him disloyal. In other words, the legislator lost his allegiance to his former party by joining another party. This very phenomenon, in practice has a two way traffic i.e. ruling party to the opposition party or vice versa. The democracies like USA, Australia and Canada were also aware of this fashion of swapping loyalties. There have been several instances of great politicians changing party allegiance, for example Winston Churchill, Ramsay McDonald, William Gladstone etc. Nevertheless, it is interesting to cite that irrespective of such practice of changing party allegiance, none of the democracies in the west ever desired or felt the need to legislatively ban defections. But, exceptionally India can be traced to have passed anti-defection laws. The politics of defection had been a unique popular phenomenon on the floor of Indian Parliamentary system gradually gulping the democratic essence and synchronization of the Federation. This study is both analytical and doctrinal, which tries to examine whether representative democracy has lost its essence due to political nomadism. The present study also analyzes the classical as well as contemporary pulse of floor crossing amidst dynastic politics in a representative democracy. It will briefly discuss the panorama of defections under the Indian federal structure in the light of the anti-defection law and an attempt has been made to add valuable suggestions to streamline remedy for the still prevalent political defections.

Keywords: Constitutional law, defection, democracy, political anti-trust.

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Authors: F. Pottmeyer, M. Weispfenning, K. A. Weidenmann

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Continuous carbon fiber reinforced plastics (CFRP) exhibit a high application potential for lightweight structures due to their outstanding specific mechanical properties. Embedded metal elements, so-called inserts, can be used to join structural CFRP parts. Drilling of the components to be joined can be avoided using inserts. In consequence, no bearing stress is anticipated. This is a distinctive benefit of embedded inserts, since continuous CFRP have low shear and bearing strength. This paper aims at the investigation of the load bearing capacity after preinduced damages from impact tests and thermal-cycling. In addition, characterization of mechanical properties during dynamic high speed pull-out testing under different loading velocities was conducted. It has been shown that the load bearing capacity increases up to 100% for very high velocities (15 m/s) in comparison with quasi-static loading conditions (1.5 mm/min). Residual strength measurements identified the influence of thermal loading and preinduced mechanical damage. For both, the residual strength was evaluated afterwards by quasi-static pull-out tests. Taking into account the DIN EN 6038 a high decrease of force occurs at impact energy of 16 J with significant damage of the laminate. Lower impact energies of 6 J, 9 J, and 12 J do not decrease the measured residual strength, although the laminate is visibly damaged - distinguished by cracks on the rear side. To evaluate the influence of thermal loading, the specimens were placed in a climate chamber and were exposed to various numbers of temperature cycles. One cycle took 1.5 hours from -40 °C to +80 °C. It could be shown that already 10 temperature cycles decrease the load bearing capacity up to 20%. Further reduction of the residual strength with increasing number of thermal cycles was not observed. Thus, it implies that the maximum damage of the composite is already induced after 10 temperature cycles.

Keywords: Composite, joining, inserts, dynamic loading, thermal loading, residual strength, impact.

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Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: Early stage prediction, heart rate variability, linear and non linear analysis, sudden cardiac death.

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Authors: Khaled Igbaria

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While Ba‘albakī ceased writing or publishing since 1964, it is considerable and significant to investigate Ba‘albakī’s influence on others. This paper examines her influence on three Lebanese women writers: Emily Nasrallah, Muná Jabbūr, and Hanan al-Shaykh. However, the aim is not simply to examine the influence of the writer on these three authors, but rather to note similarities and differences in the challenges they faced and the agendas they followed in their fiction writing. For each of these writers, this article will describe elements of their literature, and then sketch out the influence which Ba‘albakī has had on them. This paper relies on material from Sidawi because it includes interviews with the female writers discussed that are relevant to the current discussion. Sidawi asked them about Ba‘albakī and her influence on them, the challenges they faced, and how they coped with them. This paper points out their comments using their own words. To be clear, examining these writers' notes and works is beyond the scope of this paper. To sum up, there are significant parallels between the life and work of Ba‘albakī, and other Lebanese women writers such as Nasrallah, Jabbūr and al-Shaykh. Like Ba‘albakī, Nasrallah and al-Shaykh also suffered in their struggle against their families. Nasrallah and al-Shaykh, like Ba‘albakī, suffered because their society did not trust in their abilities and creativity. Ba‘albakī opted for isolation because of her conflict with patriarchal society including the Lebanese women’s groups, while Nasrallah’s isolation was because she preferred individualism and autonomy, and Jabbūr, as could be speculated, was not able to cope with the suffering caused by her role as a woman writer within Lebanese society. Whereas Ba‘albakī isolated herself from the Lebanese women’s groups, focusing instead on her feminist writing and joining the Shi'r group, Al-Shaykh and the Lebanese women’s groups are able to cooperate in harmony. Furthermore, while Nasrallah and Al-Shaykh continued to publish fiction, Ba‘albakī stopped publishing fiction in 1964. All of the above confirms not only that it is worthy to investigate deeply and academically both the biography and the works of Ba‘albakī, but also that she deserves to include her throughout the top great Arab female writers, at the time, like Al-Shaykh and Nawal El Saadawi.

Keywords: Feminist writing, Hanan Al-Shaykh, Laylá Ba‘albakī, Lebanese women writers, Muná Jabbūr.

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Authors: Luca Indovina, Carmela Coppola, Carlo Altucci, Riccardo Barberi, Rocco Romano

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In this paper a real court case, held in Italy at the Court of Nola, in which a correct physical description, conducted with both a Monte Carlo and biophysical analysis, would have been sufficient to arrive at conclusions confirmed by documentary evidence, is considered. This will be an example of how forensic physics can be useful in confirming documentary evidence in order to reach hardly questionable conclusions. This was a libel trial in which the defendant, Mr. DS (Defendant for Slander), had falsely accused one of his neighbors, Mr. OP (Offended Person), of having caused him some damages. The damages would have been caused by an external plaster piece that would have detached from the neighbor’s property and would have hit Mr DS while he was in his garden, much more than a meter far away from the facade of the building from which the plaster piece would have detached. In the trial, Mr. DS claimed to have suffered a scratch on his forehead, but he never showed the plaster that had hit him, nor was able to tell from where the plaster would have arrived. Furthermore, Mr. DS presented a medical certificate with a diagnosis of contusion of the cerebral cortex. On the contrary, the images of Mr. OP’s security cameras do not show any movement in the garden of Mr. DS in a long interval of time (about 2 hours) around the time of the alleged accident, nor do they show any people entering or coming out from the house of Mr. DS in the same interval of time. Biophysical analysis shows that both the diagnosis of the medical certificate and the wound declared by the defendant, already in conflict with each other, are not compatible with the fall of external plaster pieces too small to be found. The wind was at a level 1 of the Beaufort scale, that is, unable to raise even dust (level 4 of the Beaufort scale). Therefore, the motion of the plaster pieces can be described as a projectile motion, whereas collisions with the building cornice can be treated using Newtons law of coefficients of restitution. Numerous numerical Monte Carlo simulations show that the pieces of plaster would not have been able to reach even the garden of Mr. DS, let alone a distance over 1.30 meters. Results agree with the documentary evidence (images of Mr. OP’s security cameras) that Mr. DS could not have been hit by plaster pieces coming from Mr. OP’s property.

Keywords: Biophysical analysis, Monte Carlo simulations, Newton’s law of restitution, projectile motion.

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Authors: Japhet N. Mwambusi

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High tropical forests deforestation for solid wood furniture industry is among of climate change contributing agents. This pressure indirectly is caused by furniture joints failure due to poor gluing technology based on improper use of different glues to different wood species which lead to low quality and weak wood-glue joints. This study was carried in order to run performance tests of wood glues on different wood species used in wood workshops: Morogoro Tanzania whereby three popular wood species of C. lusitanica, T. glandis and E. maidenii were tested against five glues of Woodfix, Bullbond, Ponal, Fevicol and Coral found in the market. The findings were necessary on developing a guideline for proper glue selection for a particular wood species joining. Random sampling was employed to interview carpenters while conducting a survey on the background of carpenters like their education level and to determine factors that influence their glues choice. Monsanto Tensiometer was used to determine bonding strength of identified wood glues to different wood species in use under British Standard of testing wood shear strength (BS EN 205) procedures. Data obtained from interviewing carpenters were analyzed through Statistical Package of Social Science software (SPSS) to allow the comparison of different data while laboratory data were compiled, related and compared by the use of MS Excel worksheet software as well as Analysis of Variance (ANOVA). Results revealed that among all five wood glues tested in the laboratory to three different wood species, Coral performed much better with the average shear strength 4.18 N/mm², 3.23 N/mm² and 5.42 N/mm² for Cypress, Teak and Eucalyptus respectively. This displays that for a strong joint to be formed to all tree wood species for soft wood and hard wood, Coral has a first priority in use. The developed table of guideline from this research can be useful to carpenters on proper glue selection to a particular wood species so as to meet glue-bond strength. This will secure furniture market as well as reduce pressure to the forests for furniture production because of the strong existing furniture due to their strong joints. Indeed, this can be a good strategy on reducing climate change speed in tropics which result from high deforestation of trees for furniture production.

Keywords: Climate change, deforestation, gluing technology, joint failure, wood-glue, wood species.

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Authors: K. Kalaikumar, E. Baburaj

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One of the problems to be addressed in wireless sensor networks is the issues related to cross layer communication. Cross layer architecture shares the information across the layer, ensuring Quality of Services (QoS). With this shared information, MAC protocol adapts effective functionality maintenance such as route selection on changeable sensor network environment. However, time slot assignment and neighbour route selection time duration for cross layer have not been carried out. The time varying physical layer communication over cross layer causes high traffic load in the sensor network. Though, the traffic load was reduced using cross layer optimization procedure, the computational cost is high. To improve communication efficacy in the sensor network, a self-determined time slot based Cross-Layered Neighbour Route Discovery (C-LNRD) method is presented in this paper. In the presented work, the initial process is to discover the route in the sensor network using Dynamic Source Routing based Medium Access Control (MAC) sub layers. This process considers MAC layer operation with dynamic route neighbour table discovery. Then, the discovered route path for packet communication employs Broad Route Distributed Time Slot Assignment method on Cross-Layered Sensor Network system. Broad Route means time slotting on varying length of the route paths. During packet communication in this sensor network, transmission of packets is adjusted over the different time with varying ranges for controlling the traffic rate. Finally, Rayleigh fading model is developed in C-LNRD to identify the performance of the sensor network communication structure. The main task of Rayleigh Fading is to measure the power level of each communication under MAC sub layer. The minimized power level helps to easily reduce the computational cost of packet communication in the sensor network. Experiments are conducted on factors such as power factor, on packet communication, neighbour route discovery time, and information (i.e., packet) propagation speed.

Keywords: Medium access control, neighbour route discovery, wireless sensor network, Rayleigh fading, distributed time slot assignment

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: Crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest.

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: Affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, Signal Detection Theory, student engagement.

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