Search results for: target firm

Authors: Yao Fu, Xingli Zhang, Jiannong Shi

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Visual working memory (VWM) capacity is the ability to maintain and manipulate short-term information which is not currently available. It is well known for its significance to form the basis of numerous cognitive abilities and its limitation in holding information. VWM span, the most popular measurable indicator, is found to reach the adult level (3-4 items) around 12-13 years’ old, while less is known about the precision development of the VWM capacity. By using simultaneously delayed responses paradigm, the present study investigates the development of VWM precision among 6-18-year-old children and young adults, besides its possible relationships with fluid intelligence and span. Results showed that precision and span both increased with age, and precision reached the maximum in 16-17 age-range. Moreover, when remembering 3 simultaneously presented items, the probability of remembering target item correlated with fluid intelligence and the probability of wrap errors (misbinding target and non-target items) correlated with age. When remembering more items, children had worse performance than adults due to their wrap errors. Compared to span, VWM precision was effective predictor of intelligence even after controlling for age. These results suggest that unlike VWM span, precision developed in a slow, yet longer fashion. Moreover, decreasing probability of wrap errors might be the main reason for the development of precision. Last, precision correlated more closely with intelligence than span in childhood and adolescence, which might be caused by the probability of remembering target item.

Keywords: fluid intelligence, precision, visual working memory, wrap errors

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Authors: Aisulu Tileukulova, Zhexebay Dauren

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Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

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Authors: Junichiro Kawaguchi

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Space debris problems have emerged and threatened the use of low earth orbit around the Earth owing to a large number of spacecraft. In debris removal, a number of research and patents have been proposed and published so far. They assume servicing spacecraft, robots to be built for accessing the target debris objects. The robots should be sophisticated enough automatically to access the debris articulating the attitude and the translation motion with respect to the debris. This paper presents the idea of using the torpedo-like third unsophisticated and disposable body, in addition to the first body of the servicing robot and the second body of the target debris. The third body is launched from the first body from a distance farer than the size of the second body. This paper presents the method and the system, so that the third body is launched from the first body. The third body carries both a net and an inflatable or extendible drag deceleration device and is built small and light. This method enables even a micro to nano satellite to perform contactless and multiple debris removal even via a single flight.

Keywords: ballute, debris removal, echo satellite, gossamer, gun-net, inflatable space structure, small satellite, un-cooperated target

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Authors: Heeyong Noh, Seongryong Kang, Sungjoo Lee

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As the world becomes increasingly interconnected, firms have tried to explore market opportunities not only in the domestic market but also abroad. In particular, transactions of intangible assets in the global market now take on great importance. Accordingly, technology transfer activities such as patent licensing, copyright transfer, or workforce trainings which are considered significant to leverage an organization’s internal capabilities, are occurring more frequently and briskly across the world than ever before. Though a number of studies have addressed the issues regarding technology transfer, most of them have focused on university-industry technology transfer. Of course, some have investigated international technology transfer phenomenon but used patent citations data as a proxy. In order to understand the phenomena more clearly, it would be necessary to collect and analyze data that can measure technology transfer activities between firms more directly. Therefore, this study aims to examine the patterns of international trade in technology by employing data about international technology in-licensing activities in Korean firms. We also investigate the effect of international technology in-licensing strategy on a firm’s innovation performance. The research findings are expected to help R&D managers understand how firms have absorbed technological knowledge from foreign firms in the form of licensing and further develop effective international collaboration strategies. In addition, significant implications can be offered for political decision-making regarding technology trade within increasing international interconnections.

Keywords: international technology trade, technology trade effect, technology transfer, R&D managers

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Authors: Nasir Yusoff, Ahmad Adamu Adamu, Tahamina Begum, Faruque Reza

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The P300 from Event related potential (ERP) explains the psycho-physiological phenomenon in human body. The present study aims to identify the differences of amplitude and latency of P300 component from auditory stimuli, between ambiversion and extraversion types of personality. Ambivert (N=20) and extravert (N=20) undergoing ERP recording at the Hospital Universiti Sains Malaysia (HUSM) laboratory. Electroencephalogram data was recorded with oddball paradigm, counting auditory standard and target tones, from nine electrode sites (Fz, Cz, Pz, T3, T4, T5, T6, P3 and P4) by using the 128 HydroCel Geodesic Sensor Net. The P300 latency of the target tones at all electrodes were insignificant. Similarly, the P300 latency of the standard tones were also insignificant except at Fz and T3 electrode. Likewise, the P300 amplitude of the target and standard tone in all electrode sites were insignificant. Extravert and ambivert indicate similar characteristic in cognition processing from auditory task.

Keywords: amplitude, event related potential, p300 component, latency

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Authors: Edson Vengesai

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Derivative products have become essential instruments in portfolio diversification, price discovery, and, most importantly, risk hedging. Derivatives are complex instruments; their valuation, volatility implications, and real impact on the underlying assets' behaviour are not well understood. Little is documented empirically, with conflicting conclusions on how these instruments affect firm risk exposures. Given the growing interest in using derivatives in risk management and portfolio engineering, this study examines the practical impact of derivative usage on the underlying stock price exposure and systematic risk. The paper uses data from South African listed firms. The study employs GARCH models to understand the effect of derivative uses on conditional stock volatility. The GMM models are used to estimate the effect of derivatives use on stocks' systematic risk as measured by Beta and on the total risk of stocks as measured by the standard deviation of returns. The results provide evidence on whether derivatives use is instrumental in reducing stock returns' systematic and total risk. The results are subjected to numerous controls for robustness, including financial leverage, firm size, growth opportunities, and macroeconomic effects.

Keywords: derivatives use, hedging, volatility, stock price exposure

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Authors: Anita Richter

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Innovation is one of the key foundations of competitive advantage, generating growth and welfare worldwide. Consequently, all firms should innovate to bring new ideas to the market. Innovation is a vital growth driver, particularly for transition countries to move towards knowledge-based, high-income economies. However, numerous barriers, such as financial, regulatory or infrastructural constraints prevent, in particular, new and small firms in transition countries from innovating. Thus SMEs’ innovation output may benefit substantially from government support. This research paper aims to assess the effect of government interventions on innovation activities in SMEs in emerging countries. Until now academic research related to the innovation policies focused either on single country and/or high-income countries assessments and less on cross-country and/or low and middle-income countries. Therefore the paper seeks to close the research gap by providing empirical evidence from 8,500 firms in 15 transition countries (Eastern Europe, South Caucasus, South East Europe, Middle East and North Africa). Using firm-level data from the Business Environment and Enterprise Performance Survey of the World Bank and EBRD and policy data from the SME Policy Index of the OECD, the paper investigates how government interventions affect SME’s likelihood of investing in any technological and non-technological innovation. Using the Standard Linear Regression, the impact of government interventions on SMEs’ innovation output and R&D activities is measured. The empirical analysis suggests that a firm’s decision to invest into innovative activities is sensitive to government interventions. A firm’s likelihood to invest into innovative activities increases by 3% to 8%, if the innovation eco-system noticeably improves (measured by an increase of 1 level in the SME Policy Index). At the same time, a better eco-system encourages SMEs to invest more in R&D. Government reforms in establishing a dedicated policy framework (IP legislation), institutional infrastructure (science and technology parks, incubators) and financial support (public R&D grants, innovation vouchers) are particularly relevant to stimulate innovation performance in SMEs. Particular segments of the SME population, namely micro and manufacturing firms, are more likely to benefit from an increased innovation framework conditions. The marginal effects are particularly strong on product innovation, process innovation, and marketing innovation, but less on management innovation. In conclusion, government interventions supporting innovation will likely lead to higher innovation performance of SMEs. They increase productivity at both firm and country level, which is a vital step in transitioning towards knowledge-based market economies.

Keywords: innovation, research and development, government interventions, economic development, small and medium-sized enterprises, transition countries

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Authors: C. L. Huang, J. J. Sia

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The interest-based social networks, also known as social bookmark sharing systems, are useful platforms for people to conveniently read and collect internet resources. These platforms also providing function of social networks, and users can share and explore internet resources from the social networks. Providing personalized internet resources to users is an important issue on these platforms. This study uses two types of relationship on the social networks—following and follower and proposes a collaborative recommender system, consisting of two main steps. First, this study calculates the relationship strength between the target user and the target user's followings and followers to find top-N similar neighbors. Second, from the top-N similar neighbors, the articles (internet resources) that may interest the target user are recommended to the target user. In this system, users can efficiently obtain recent, related and diverse internet resources (knowledge) from the interest-based social network. This study collected the experimental dataset from Diigo, which is a famous bookmark sharing system. The experimental results show that the proposed recommendation model is more accurate than two traditional baseline recommendation models but slightly lower than the cosine model in accuracy. However, in the metrics of the diversity and executing time, our proposed model outperforms the cosine model.

Keywords: recommender systems, social networks, tagging, bookmark sharing systems, collaborative recommender systems, knowledge management

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Authors: Eugene Y. C. Wong

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The increased market competition, customer expectation, and warehouse operating cost in third-party logistics have motivated the continuous exploration in improving operation efficiency in warehouse logistics. Cargo tracing in ordering picking process consumes excessive time for warehouse operators when handling enormous quantities of goods flowing through the warehouse each day. Internet of Things (IoT) with mobile cargo tracing apps and database management systems are developed this research to facilitate and reduce the cargo tracing time in order picking process of a third-party logistics firm. An operation review is carried out in the firm with opportunities for improvement being identified, including inaccurate inventory record in warehouse management system, excessive tracing time on stored products, and product misdelivery. The facility layout has been improved by modifying the designated locations of various types of products. The relationship among the pick and pack processing time, cargo tracing time, delivery accuracy, inventory turnover, and inventory count operation time in the warehouse are evaluated. The correlation of the factors affecting the overall cycle time is analysed. A mobile app is developed with the use of MIT App Inventor and the Access management database to facilitate cargo tracking anytime anywhere. The information flow framework from warehouse database system to cloud computing document-sharing, and further to the mobile app device is developed. The improved performance on cargo tracing in the order processing cycle time of warehouse operators have been collected and evaluated. The developed mobile voice picking and tracking systems brings significant benefit to the third-party logistics firm, including eliminating unnecessary cargo tracing time in order picking process and reducing warehouse operators overtime cost. The mobile tracking device is further planned to enhance the picking time and cycle count of warehouse operators with voice picking system in the developed mobile apps as future development.

Keywords: warehouse, order picking process, cargo tracing, mobile app, third-party logistics

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Authors: Alireza Dantism

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Presently, describing the function of a protein sequence is one of the most common problems in biology. Usually, this problem can be facilitated by studying the three-dimensional structure of proteins. In the absence of a protein structure, comparative modeling often provides a useful three-dimensional model of the protein that is dependent on at least one known protein structure. Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) mainly based on its alignment with one or more proteins of known structure (templates). Comparative modeling consists of four main steps 1. Similarity between the target sequence and at least one known template structure 2. Alignment of target sequence and template(s) 3. Build a model based on alignment with the selected template(s). 4. Prediction of model errors 5. Optimization of the built model There are many computer programs and web servers that automate the comparative modeling process. One of the most important advantages of these servers is that it makes comparative modeling available to both experts and non-experts, and they can easily do their own modeling without the need for programming knowledge, but some other experts prefer using programming knowledge and do their modeling manually because by doing this they can maximize the accuracy of their modeling. In this study, a web-based tool has been designed to predict the tertiary structure of proteins using PHP and Python programming languages. This tool is called EasyModel. EasyModel can receive, according to the user's inputs, the desired unknown sequence (which we know as the target) in this study, the protein sequence file (template), etc., which also has a percentage of similarity with the primary sequence, and its third structure Predict the unknown sequence and present the results in the form of graphs and constructed protein files.

Keywords: structural bioinformatics, protein tertiary structure prediction, modeling, comparative modeling, modeller

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Authors: Nadir Ali Mugheri, Shaukat Ali Lohar

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In a multilingual society like Pakistan, code switching is commonly observed in different contexts. Mostly people use L1 (Native Languages) and L2 for common communications and L3 (i.e. English, Urdu, Sindhi) in formal contexts and for academic writings. Such a frequent code switching does affect EFL learners' acquisition of grammar and lexis of the target language which in the long run result in different types of errors in their writings. The current study is to investigate and identify common elements of L1 and L2 (spoken by students of the Universities in Pakistan) which create hindrances for EFL learners. Case study method was used for this research. Formal writings of 400 EFL learners (as participants from various Universities of the country) were observed. Among 400 participants, 200 were female and 200 were male EFL learners having different academic backgrounds. Errors found were categorized into different types according to grammatical items, the difference in meanings, structure of sentences and identifiers of tenses of L1 or L2 in comparison with those of the target language. The findings showed that EFL learners in Pakistani varsities have serious problems in their writings and they committed serious errors related to the grammar and meanings of the target language. After analysis of the committed errors, the results were found in the affirmation of the hypothesis that L1 or L2 does affect EFL learners. The research suggests in the end to adopt natural ways in pedagogy like task-based learning or communicative methods using contextualized material so as to avoid impediments of L1 or L2 in acquisition the target language.

Keywords: multilingualism, L2 acquisition, code switching, language acquisition, communicative language teaching

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Authors: V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

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This paper presents different methodology for an acoustic source sensing and localization in an unknown environment. The developed methodology includes an acoustic based sensing and localization system, a converging target localization based on the recursive direction of arrival (DOA) error minimization, and a regressive obstacle avoidance function. Our method is able to augment the existing proven localization techniques and improve results incrementally by utilizing robot locomotion and is capable of converging to a position estimate with greater accuracy using fewer measurements. The results also evinced the DOA error minimization at each iteration, improvement in time for reaching the destination and the efficiency of this target localization method as gradually converging to the real target position. Initially, the system is tested using Kinect mounted on turntable with DOA markings which serve as a ground truth and then our approach is validated using a FireBird VI (FBVI) mobile robot on which Kinect is used to obtain bearing information.

Keywords: acoustic source localization, acoustic sensing, recursive direction of arrival, robot locomotion

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Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

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Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

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Authors: Farahnaz Sadat Golestan Hashemi, Mohd Razi Ismail, Mohd Y. Rafii

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Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas) system can facilitate targeted genome editing in organisms. Dual or single guide RNA (gRNA) can program the Cas9 nuclease to cut target DNA in particular areas; thus, introducing concise mutations either via error-prone non-homologous end-joining repairing or via incorporating foreign DNAs by homologous recombination between donor DNA and target area. In spite of high demand of such promising technology, developing a well-organized procedure in order for reliable mining of potential target sites for gRNAs in large genomic data is still challenging. Hence, we aimed to perform high-throughput detection of target sites by specific PAMs for not only common Streptococcus pyogenes (SpCas9) but also for Neisseria meningitides (NmCas9) CRISPR-Cas systems. Previous research confirmed the successful application of such RNA-guided Cas9 orthologs for effective gene targeting and subsequently genome manipulation. However, Cas9 orthologs need their particular PAM sequence for DNA cleavage activity. Activity levels are based on the sequence of the protospacer and specific combinations of favorable PAM bases. Therefore, based on the specific length and sequence of PAM followed by a constant length of the target site for the two orthogonals of Cas9 protein, we created a reliable procedure to explore possible gRNA sequences. To mine CRISPR target sites, four different searching modes of sgRNA binding to target DNA strand were applied. These searching modes are as follows i) coding strand searching, ii) anti-coding strand searching, iii) both strand searching, and iv) paired-gRNA searching. Finally, a complete list of all potential gRNAs along with their locations, strands, and PAMs sequence orientation can be provided for both SpCas9 as well as another potential Cas9 ortholog (NmCas9). The artificial design of potential gRNAs in a genome of interest can accelerate functional genomic studies. Consequently, the application of such novel genome editing tool (CRISPR/Cas technology) will enhance by presenting increased versatility and efficiency.

Keywords: CRISPR/Cas9 genome editing, gRNA mining, SpCas9, NmCas9

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Authors: Xi Yuan, Xuebin Zhu, Bojun Li

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This work describes the experiment to produce high-intensity pulsed neutron beams on XingGuangIII laser facility. The high-intensity laser is utilized to drive protons and deuterons, which hit a thick solid target to produce neutrons. The pulse duration of the laser used in the experiment is about 0.8 ps, and the laser energy is around 100 J. Protons and deuterons are accelerated from a 10-μm-thick deuterated polyethylene (CD₂) foil and diagnosed by a Thomson parabola ion-spectrometer. The energy spectrum of neutrons generated via ⁷Li(d,n) and ⁷Li(p,n) reaction when proton and deuteron beams hit a 5-mm-thick LiF target is measured by a scintillator-based time-of-flight spectrometer. Results from the neuron measurements show that the maximum neutron energy is about 12.5 MeV and the neutron yield is up to 2×10⁹/pulse. The high-intensity pulsed neutron beams demonstrated in this work can provide a valuable neutron source for material research, fast neutron induced fission research, and so on.

Keywords: picosecond laser driven, fast neutron, time-of-flight spectrometry, XinggungIII

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Authors: Sevde D. Karayel, Ediz Atmaca

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Supplier selection subject is vital because of development competitiveness and performance of firms which have right, rapid and with low cost procurement. Considering the fact that competition between firms is no longer on their supply chains, hence it is very clear that performance of the firms’ not only depend on their own success but also success of all departments in supply chain. For this purpose, firms want to work with suppliers which are cost effective, flexible in terms of demand and high quality level for customer satisfaction. However, diversification and redundancy of their expectations from suppliers, supplier selection problems need to be solved as a hard problem. In this study, supplier selection problem is discussed for critical piece, which is using almost all production of products in and has troubles with lead time from supplier, in a firm that produces medical devices. Analyzing policy in the current situation of the firm in the supplier selection indicates that supplier selection is made based on the purchasing department experience and other authorized persons’ general judgments. Because selection do not make based on the analytical methods, it is caused disruptions in production, lateness and extra cost. To solve the problem, AHP and TOPSIS which are multi-criteria decision making techniques, which are effective, easy to implement and can analyze many criteria simultaneously, are used to make a selection among alternative suppliers.

Keywords: AHP-TOPSIS methods, multi-criteria decision making, supplier selection problem, supply chain management

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Authors: I-Huan Chiu, Kazuhiko Ninomiya, Shin’ichiro Takeda, Meito Kajino, Miho Katsuragawa, Shunsaku Nagasawa, Atsushi Shinohara, Tadayuki Takahashi, Ryota Tomaru, Shin Watanabe, Goro Yabu

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In recent years, a nondestructive elemental analysis method based on muonic X-ray measurements has been developed and applied for various samples. Muonic X-rays are emitted after the formation of a muonic atom, which occurs when a negatively charged muon is captured in a muon atomic orbit around the nucleus. Because muonic X-rays have higher energy than electronic X-rays due to the muon mass, they can be measured without being absorbed by a material. Thus, estimating the two-dimensional (2D) elemental distribution of a sample became possible using an X-ray imaging detector. In this work, we report a non-destructive imaging experiment using muonic X-rays at Japan Proton Accelerator Research Complex. The irradiated target consisted of polypropylene material, and a double-sided silicon strip detector, which was developed as an imaging detector for astronomical observation, was employed. A peak corresponding to muonic X-rays from the carbon atoms in the target was clearly observed in the energy spectrum at an energy of 14 keV, and 2D visualizations were successfully reconstructed to reveal the projection image from the target. This result demonstrates the potential of the non-destructive elemental imaging method that is based on muonic X-ray measurement. To obtain a higher position resolution for imaging a smaller target, a new detector system will be developed to improve the statistical analysis in further research.

Keywords: DSSD, muon, muonic X-ray, imaging, non-destructive analysis

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Authors: Ahmet Karagoz, Irfan Karagoz

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Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

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Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

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Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

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Authors: Natasha Hazarika, Xiaoling Zhang

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Eco- innovations, unlike regular innovations, are not self-enforcing and are associated with the double externality problem. Therefore, it is emphasized that eco-innovations need government. intervention in the form of supportive policies on priority. Off late, factors like consumer demand, technological advancement as well as the competitiveness of the firms have been considered as equally important. However, the interaction among these driving forces has not been fully traced out. Also, the theory on eco-innovation is found to be at a nascent stage which does not resonate with its dynamics as it is traditionally studied under the neo- classical economics theory. Therefore, to begin with, insights for this research have been derived from the merits of ‘neo- classical economics’, ‘evolutionary approach’, and the ‘resource based view’ which revealed the issues pertaining to technological system lock- ins and firm- based capacities which usually remained undefined by the neo classical approach; it would be followed by determining how the policies (in the national level) and their instruments are designed in order to motivate firms to eco-innovate, by analyzing the innovation ‘friendliness’ of the policy style and the policy instruments as per the indicators provided in innovation literature by means of document review (content analysis) of the relevant policies introduced by the Chinese government. The significance of theoretical analysis lies in its ability to show why certain practices become dominant irrespective of gains or losses, and that of the policy analysis lies in its ability to demonstrate the credibility of govt.’s sticks, carrots and sermons for eco-innovation.

Keywords: firm competency, eco-innovation, policy, theory

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Authors: Henry Kiptum Yatich, Ronald Chepkilot, Aquilars Mutuku Kalio

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Studies on energy management have focused on environmental conservation, reduction in production and operation expenses. However, transferring gains of energy management practices to competitive advantage is importance to manufacturers in Kenya. Success in managing competitive advantage arises out of a firm’s ability in identifying and implementing actions that can give the company an edge over its rivals. Manufacturing firms in Kenya are the highest consumers of both electricity and petroleum products. In this regard, the study posits that transfer of the gains of energy management practices to competitive advantage is imperative. The study was carried in Nairobi and its environs, which hosts the largest number of manufacturers. The study objectives were; to determine the level of implementing energy management regulations on sustaining competitive advantage, to determine the level of implementing company energy management policy on competitive advantage, to examine the level of implementing energy efficient technology on sustaining competitive advantage, and to assess the percentage energy expenditure on sustaining competitive advantage among manufacturing firms. The study adopted a survey research design, with a study population of 145,987. A sample of 384 respondents was selected randomly from 21 proportionately selected firms. Structured questionnaires were used to collect data. Data analysis was done using descriptive statistics (mean and standard deviations) and inferential statistics (correlation, regression, and T-test). Data is presented using tables and diagrams. The study found that Energy Management Regulations, Company Energy Management Policies, and Energy Expenses are significant predictors of Competitive Advantage (CA). However, Energy Efficient Technology as a component of Energy Management Practices did not have a significant relationship with Competitive Advantage. The study revealed that the level of awareness in the sector stood at 49.3%. Energy Expenses in the sector stood at an average of 10.53% of the firm’s total revenue. The study showed that gains from energy efficiency practices can be transferred to competitive strategies so as to improve firm competitiveness. The study recommends that manufacturing firms should consider energy management practices as part of its strategic agenda in assessing and reviewing their energy management practices as possible strategies for sustaining competitiveness. The government agencies such as Energy Regulatory Commission, the Ministry of Energy and Petroleum, and Kenya Association of Manufacturers should enforce the energy management regulations 2012, and with enhanced stakeholder involvement and sensitization so as promote sustenance of firm competitiveness. Government support in providing incentives and rebates for acquisition of energy efficient technologies should be pursued. From the study limitation, future experimental and longitudinal studies need to be carried out. It should be noted that energy management practices yield enormous benefits to all stakeholders and that the practice should not be considered a competitive tool but rather as a universal practice.

Keywords: energy, efficiency, management, guidelines, policy, technology, competitive advantage

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Authors: Konstantinos Kottikas, Vlasis Stathakopoulos, Ioannis G. Theodorakis, Efthymia Kottika

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Theorists have argued that Market Orientation is comprised of two facets, namely the Market Driven and the Market Driving components. The present theoretical paper centers on the latter, which to date has been notably under-investigated. The term Market Driving (MD) pertains to influencing the structure of the market, or the behavior of market players in a direction that enhances the competitive edge of the firm. Presently, the main objectives of the paper are the specification of key antecedents and outcomes of Market Driving behavior. Market Driving firms behave proactively, by leading their customers and changing the rules of the game rather than by responding passively to them. Leading scholars were the first to conceptually conceive the notion, followed by some qualitative studies and a limited number of quantitative publications. However, recently, academicians noted that research on the topic remains limited, expressing a strong necessity for further insights. Concerning the key antecedents, top management’s Transformational Leadership (i.e. the form of leadership which influences organizational members by aligning their values, goals and aspirations to facilitate value-consistent behaviors) is one of the key drivers of MD behavior. Moreover, scholars have linked the MD concept with Entrepreneurship. Finally, the role that Employee’s Creativity plays in the development of MD behavior has been theoretically exemplified by a stream of literature. With respect to the key outcomes, it has been demonstrated that MD Behavior positively triggers firm Performance, while theorists argue that it empowers the Competitive Advantage of the firm. Likewise, researchers explicate that MD Behavior produces Radical Innovation. In order to test the robustness of the proposed theoretical framework, a combination of qualitative and quantitative methods is proposed. In particular, the conduction of in-depth interviews with distinguished executives and academicians, accompanied with a large scale quantitative survey will be employed, in order to triangulate the empirical findings. Given that it triggers overall firm’s success, the MD concept is of high importance to managers. Managers can become aware that passively reacting to market conditions is no longer sufficient. On the contrary, behaving proactively, leading the market, and shaping its status quo are new innovative approaches that lead to a paramount competitive posture and Innovation outcomes. This study also exemplifies that managers can foster MD Behavior through Transformational Leadership, Entrepreneurship and recruitment of Creative Employees. To date, the majority of the publications on Market Orientation is unilaterally directed towards the responsive (i.e. the Market Driven) component. The present paper further builds on scholars’ exhortations, and investigates the Market Driving facet, ultimately aspiring to conceptually integrate the somehow fragmented scientific findings, in a holistic framework.

Keywords: entrepreneurial orientation, market driving behavior, market orientation

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Authors: M. Kolotylo, H. Zheng, R. Parente, R. Dahiya

Abstract:

Large number of organizations, frequently motivated by budget and cost cuts, outsource their Information Technology (IT) positions every year. Although the objective of reduction in financial obligations is often not accomplished, many buyer companies still manage to benefit from outsourcing projects. Knowledge Transfer (KT), being one of the major processes that take place during IT outsourcing partnership, may exert a strong impact on the performance of the parties involved, particularly that of the buyer. Research, however, lacks strong conceptual basis for the possible benefits that KT from supplier may bring to the buyer; and for the mechanisms that may be adopted by the buyer to maximize such benefit. This paper aims to fill this gap by proposing a conceptual framework of organizational learning and development of dynamic capabilities enabled by KT from the supplier to the buyer. The study examines buyer-supplier relationships in the context of IT outsourcing transactions, and theorizes how KT from the supplier to the buyer helps the performance of the buyer. It warrants that more research is carried out in order to explicate and provide evidence regarding the role that KT plays in strategic improvements for the buyer. The paper proposes to take up a two-fold approach to the research: conceptual development that utilizes logical argumentation and interpretive historical research, as well as a qualitative case study which aims to capture and understand the complex processes involved. Thus, the study provides a comprehensive visualization of the dynamics of the conditions under which participation in IT outsourcing partnership might be of benefit to the buyer company. The framework demonstrates the mechanisms involved in buyer’s achievement of strategic alignment through organizational learning enabled by KT from the supplier. It highlights that organizational learning involves a balance between exploitation of assets and exploration of new possibilities, and further notes that the dynamic capabilities mediate the effect of organizational learning on firm performance. The paper explicates in what ways managers can leverage outsourcing projects to execute strategy, which would enable their organization achieve better performance. The study concludes that organizational learning enables the firm to develop IT capabilities of strategic planning, IT integration, and IT relationships in the outsourcing context, and that IT capabilities developed through the organizational learning would help the firm in achieving strategic alignment.

Keywords: dynamic capabilities, it outsourcing, knowledge transfer, organizational learning, strategic alignment

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Authors: Mary David, Denis Basila

Abstract:

This study assessed the Impact of Board Composition on the Performance of Listed Deposit Money Banks in Nigeria. A sample of ten (10) deposit money banks formed the sample of this study. Board size, gender diversity, and board independence were used as the independent variables, and firm size as a control variable, whiles the bank performance was proxy with Tobin’s Q (TQ) as the dependent variable. Secondary data was collected from secondary source through the annual report and account of the banks and was analyzed through the support of STATA 14 versions. Descriptive statistics, correlation matrix, and OLS multiple regression model were adopted for the study. Breusch and pagan lagrangian multiplier test for random effect was conducted. The findings of the study reveal that board size has positive and significant impact on Tobin’s Q, gender diversity has positive and significant impact on Tobin’s Q, while board independent had a negative and nonsignificant influence on the Tobin’s Q, Similarly, firm size was found to have a negative and nonsignificant impact on Tobin’s Q of the study banks. This study recommended that policy makers, stakeholders, and corporate managers of deposit money banks of Nigeria and related industries are encouraged to adopt board sizes and gender diversity that impact positively on bank performance.

Keywords: board composition, performance, deposit money banks, nigeria

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Authors: Steffen Happel

Abstract:

Non-standard isotopes such as Sc-44/47, Zr-89, and Sn-117mare finding interest is increasing in radiopharmaceutical applications. Methods for the separation of these elements from typical target materials were developed. The methods used in this paper are based on the use of extraction chromatographic resins such as UTEVA, TBP, and DGA resin. Information on the selectivity of the resins (Dw values of selected elements in HCl and HNO3 of varying concentration) will be presented as well as results of the method development such as elution studies, chemical recoveries, and decontamination factors. Developed methods are based on the use of vacuum supported separation allowing for fast and selective separation.

Keywords: elution, extraction chromatography, radiopharmacy, decontamination factors

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Authors: Lina Najafian, Hamidreza Vakilifard

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The present study focused on the relationship between the quality of accruals and non-systematic risk. The independent study variables included the ability of accruals, the information content of accruals, and amount of discretionary accruals considered as accruals quality measures. The dependent variable was non-systematic risk based on the Fama and French Three Factor model (FFTFM) and the capital asset pricing model (CAPM). The control variables were firm size, financial leverage, stock return, cash flow fluctuations, and book-to-market ratio. The data collection method was based on library research and document mining including financial statements. Multiple regression analysis was used to analyze the data. The study results showed that there is a significant direct relationship between financial leverage and discretionary accruals and non-systematic risk based on FFTFM and CAPM. There is also a significant direct relationship between the ability of accruals, information content of accruals, firm size, and stock return and non-systematic based on both models. It was also found that there is no relationship between book-to-market ratio and cash flow fluctuations and non-systematic risk.

Keywords: accruals quality, non-systematic risk, CAPM, FFTFM

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Authors: Ali Hojati Najafabadi, Mohamad Hosein Rahmati, Seyed Ali Madanizadeh

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Governments execute energy subsidy reforms by either increasing energy prices or reducing energy price dispersion. These policies make less use of energy per plant (intensive margin), vary the total number of firms (extensive margin), promote technological progress (technology channel), and make additional resources to redistribute (resource channel). We estimate a structural dynamic firm model with endogenous technology adaptation using data from the manufacturing firms in Iran and a country ranked the second-largest energy subsidy plan by the IMF. The findings show significant dynamics and distributional effects due to an energy reform plan. The price elasticity of energy consumption in the industrial sector is about -2.34, while it is -3.98 for large firms. The dispersion elasticity, defined as the amounts of changes in energy consumption by a one-percent reduction in the standard error of energy price distribution, is about 1.43, suggesting significant room for a distributional policy. We show that the intensive margin is the main driver of energy price elasticity, whereas the other channels mostly offset it. In contrast, the labor response is mainly through the extensive margin. Total factor productivity slightly improves in light of the reduction in energy consumption if, at the same time, the redistribution policy boosts the aggregate demands.

Keywords: energy reform, firm dynamics, structural estimation, subsidy policy

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Authors: Emad Alenany, M. Adel El-Baz

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In this paper, the flow of different classes of patients into a hospital is modelled and analyzed by using the queueing network analyzer (QNA) algorithm and discrete event simulation. Input data for QNA are the rate and variability parameters of the arrival and service times in addition to the number of servers in each facility. Patient flows mostly match real flow for a hospital in Egypt. Based on the analysis of the waiting times, two approaches are suggested for improving performance: Separating patients into service groups, and adopting different service policies for sequencing patients through hospital units. The separation of a specific group of patients, with higher performance target, to be served separately from the rest of patients requiring lower performance target, requires the same capacity while improves performance for the selected group of patients with higher target. Besides, it is shown that adopting the shortest processing time and shortest remaining processing time service policies among other tested policies would results in, respectively, 11.47% and 13.75% reduction in average waiting time relative to first come first served policy.

Keywords: queueing network, discrete-event simulation, health applications, SPT

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Authors: Myonghwa Park, Eun Jeong Choi

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Persons with dementia living at home have complex caregiving demands, which can be significant sources of stress for the family caregivers. Thus, the dementia family support program facilitators struggle to provide various health and social services, facing diverse challenges. The purpose of this study was to research the effects of training program for the dementia family support program facilitators on self-efficacy, competence, and target complaints concerning operating their program. We created a training program with systematic contents, which was composed of 10 sessions and we provided the program for the facilitators. The participants were 32 people at 28 community dementia support centers who manage dementia family support programs and they completed quantitative and qualitative self-report questionnaire before and after participating in the training program. For analyzing the data, descriptive statistics were used and with a paired t-test, pretest and posttest scores of self-efficacy, competence, and target complaints were analyzed. We used Statistical Package for the Social Sciences (SPSS) statistics (Version 21) to analyze the data. The average age of the participants was 39.6 years old and the 84.4% of participants were nurses. There were statistically meaningful increases in facilitators’ self-efficacy scores (t = -4.45, p < .001) and competence scores (t = -2.133, p = 0.041) after participating in training program and operating their own dementia family support program. Also, the facilitators’ difficulties in conducting their dementia family support program were decreased which was assessed with target complaints. Especially, the facilitators’ lack of dementia expertise and experience was decreased statistically significantly (t = 3.520, p = 0.002). Findings provided evidence of the benefits of the training program for facilitators to enhance managing dementia family support program by improving the facilitators’ self-efficacy and competence and decreasing their difficulties regarding operating their program.

Keywords: competence, dementia, facilitator, family, self-efficacy, training

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Authors: Cindy Sahera, Sarwono Sutikno

Abstract:

Rapid technological developments also have negative impacts, namely the increasing criminal cases based on technology or cybercrime. One technique that can be used to conduct cybercrime attacks are phishing email. The issue is whether the user is aware that email can be misused by others so that it can harm the user's own? This research was conducted to measure the susceptibility of selected targets against email abuse. The objectives of this research are measurement of targets’ susceptibility and find vulnerability in email recipient. There are three steps being taken in this research, (1) the information gathering phase, (2) the design phase, and (3) the execution phase. The first step includes the collection of the information necessary to carry out an attack on a target. The next step is to make the design of an attack against a target. The last step is to send phishing emails to the target. The levels of susceptibility are three: level 1, level 2 and level 3. Level 1 indicates a low level of targets’ susceptibility, level 2 indicates the intermediate level of targets’ susceptibility, and level 3 indicates a high level of targets’ susceptibility. The results showed that users who are on level 1 and level 2 more that level 3, which means the user is not too careless. However, it does not mean the user to be safe. There are still vulnerabilities that may occur, such as automatic location detection when opening emails and automatic downloaded malware as user clicks a link in the email.

Keywords: cybercrime, email phishing, susceptibility, vulnerability

Procedia PDF Downloads 289