Miracle-dz/UniFAR-FTUs huggingface dataset:
The voice from the periphery : towards an African business ethics beyond the western heritage : economics

This article argues that African business ethics should go beyond the western heritage by taking into account African indigenous values and knowledge systems. While western business practices are part and parcel of Africa’s heritage, African post-colonial scholarly efforts have worked at enriching this heritage by arguing for the incorporation of African indigenous knowledge systems and values in our way of thinking and doing business. There is a realisation that the western homo economicus who is solely self-interested, is irreconcilable with the African understanding of a person. The success of any business venture in Africa depends on incorporating African values in the way it operates.
An Evaluation of Deep Learning Miniature Concerning in Soft Computing

In recent years, Deep Learning at the latest developed field belonging to soft computing. The Deep learning has been a hot topic in the communities of artificial intelligence, artificial neural networks and machine learning. It tries to mimic the human brain, which is capable of processing the intricate input data, learning various knowledge's intellectually and intense as well as solving sundry kinds of sophisticated tasks well. The deep learning paradigm tackles problems in which shallow architectures (e.g. SVM) are impressed with the curse of dimensionality. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. The transformation these characteristics of the human brain to a learning model, we wish the model can deal with the high-dimensional data, support an intense and intellectual learning algorithm and perform well in the inextricable artificial intelligence, real tasks, such as pattern recognition speech recognition, image classification, computer vision and natural language processing. In this paper, we are discussing the history of deep learning, Deep Learning Architectures, abridge the components of Deep Boltzmann Machines (DBM), Deep Stacking Networks (DSN), Compound Hierarchical Deep Models(CHDM), Deep Convolutional Neural Network (DCNN) and Deep Belief Network (DBN) their learning algorithms.
DOUBLE LAYERED DNA BASED CRYPTOGRAPHY

DNA cryptography the new era of cryptography enhanced the cryptography in terms of time complexity as well as capacity. It uses the DNA strands to hide the information. The repeated sequence of the DNA makes highly difficult for unintended authority to get the message. The level of security can be increased by using the more than one cover medium. This paper discussed a technique that uses two cover medium to hide the message one is DNA and the other is image. The message is encrypted and converted to faked DNA then this faked DNA is hided to the image.
Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.
Adenosine Enhances Sweet Taste through A2B Receptors in the Taste Bud

Mammalian taste buds use ATP as a neurotransmitter. Taste Receptor (type II) cells secrete ATP via gap junction hemichannels into the narrow extracellular spaces within a taste bud. This ATP excites primary sensory afferent fibers and also stimulates neighboring taste bud cells. Here we show that extracellular ATP is enzymatically degraded to adenosine within mouse vallate taste buds and that this nucleoside acts as an autocrine neuromodulator to selectively enhance sweet taste. In Receptor cells in a lingual slice preparation, Ca2+ mobilization evoked by focally applied artificial sweeteners was significantly enhanced by adenosine (50 μm). Adenosine had no effect on bitter or umami taste responses, and the nucleoside did not affect Presynaptic (type III) taste cells. We also used biosensor cells to measure transmitter release from isolated taste buds. Adenosine (5 μm) enhanced ATP release evoked by sweet but not bitter taste stimuli. Using single-cell reverse transcriptase (RT)-PCR on isolated vallate taste cells, we show that many Receptor cells express the adenosine receptor, Adora2b, while Presynaptic (type III) and Glial-like (type I) cells seldom do. Furthermore, Adora2b receptors are significantly associated with expression of the sweet taste receptor subunit, Tas1r2. Adenosine is generated during taste stimulation mainly by the action of the ecto-5′-nucleotidase, NT5E, and to a lesser extent, prostatic acid phosphatase. Both these ecto-nucleotidases are expressed by Presynaptic cells, as shown by single-cell RT-PCR, enzyme histochemistry, and immunofluorescence. Our findings suggest that ATP released during taste reception is degraded to adenosine to exert positive modulation particularly on sweet taste.
On-Demand Dynamic Frequency Allocation to Serve Drop Calls in Cellular Mobile Networks

The most challenging task of managing Frequency Division Multiple Access (FDMA) based cellular networks is to allocate the frequencies to the cells efficiently. In practical scenario, the number of frequencies that are available for allocation to the cells is finite. As a result the system could not satisfy the requirements of the cells as per their demands. As a result, some of the new calls drop due to the lack availability of free frequencies. In this paper, an on-demand dynamic frequency allocation algorithm is proposed and investigated. This method is also used to determine amount of drop calls and its probability.
Rational Expectations and Monetary Policy: A New Perspective on the Chinese Housing Market

This paper revisits the effectiveness of Chinese monetary policy from augments concerning rational expectations. To estimate the dynamics of expectations, we incorporate market regime switching into the estimation of the rational expectations element using a recursive solution method. When Chinese market-oriented reforms improves the access of agents to market information, we show that (i) agents using available information behave rationally in forming price expectations and (ii) monetary policies in the presence of rational expectations are neutral with respect to real asset price dynamics, even if the market is heavily regulated by the monetary authority.
Enhancing fairness and congestion control in multipath TCP

With the advancement in technology, today most of the end-host devices are equipped with multiple wired/wireless interfaces and capable of using them in parallel. This has led to research in taking advantage of utilizing additional available network resources simultaneously such as multiple paths between the multi-homed end devices to achieve better performance. In this regard, new multipath transport protocols such as Multipath TCP and Concurrent Multipath Transfer SCTP are being designed and developed. On one hand these new protocols need to optimize the usage of the available multiple paths efficiently with a suitable scheduler while on the other hand they should be also fair to the existing transport protocols like TCP and SCTP, especially in a congested environment. This paper illustrates and compares the solutions that have been proposed to ascertain that Multipath TCP can yield an improved performance while being fair to standard TCP. In addition, this paper highlights improvements to two of the proposed congestion control solutions-Dynamic Window Coupling and Opportunistic Linked Increases Algorithm. A brief look into hybrid scheduling mechanisms is also provided with a special interest in minimizing the overall reordering delay and to capture the dependency on the receiver buffer size. It is shown that the proposed solutions give good performance in most of the different bottleneck scenarios while staying friendly to legacy transport protocols.
Patterns of co-production in public services

Abstract Research on the roles of the third sector in the delivery of public services has so far been scattered. However, there is much to learn from drawing the different manifestations of third-sector involvement together, as each represents an element of the third sector within the public services, expressed in different ways. An interesting question for research and practice is how different combinations of such elements are and should be embedded, given the variations in national structures of service provision. The studies presented in this collection have offered a stepping-stone in progressing towards an answer. Here we offer some suggestions for a future research agenda. These concern, respectively, the relationships between different roles of the third sector, links with the analysis of welfare state reform and the function of co-production.
Exploiting application-dependent ambient temperature for accurate architectural simulation

In the early stage of processor design, Dynamic Thermal Management (DTM) schemes should be evaluated to avoid excessively high temperature, while minimizing performance overhead as small as possible. In this paper, we show that conventional thermal simulations using fixed ambient temperature may lead to wrong conclusion in terms of performance and temperature; though ambient temperature converges to a steady state after hundreds of seconds, the steady state ambient temperature is significantly different depending on applications. To overcome the inaccuracy of conventional thermal simulations, we propose that architectural thermal simulation should exploit application-dependent ambient temperature. Our evaluation results show that the performance of the same DTM scheme is different, when application-dependent ambient temperature (compared to fixed temperature) is used. For accurate simulation, future architectural thermal researchers are expected to evaluate their proposed DTM schemes, reflecting application- dependent ambient temperature.
A Role-based feature model componentization framework and related algorithms

As a kind of requirement model, feature model represents functions of a family of products in a uniform form. To solve the chaos and entanglement problem in the process of feature model description and configuration, this paper designs a feature model componentization framework. With the help of the concept of Role and Reference Role, the framework proposes a process to analyze and decompose complex requirement specification to simple and coherent roles, and then implements Feature -Role-Component algorithms which map all features generated by requirement elicitation and analysis to different model components. In the framework and algorithms, role and reference role plays as an intermediary who decouple the feature and component, which makes convenient feature variants selection and composition and enhances the componentization level of the system. By decomposing the system functions in the early phase of software lifecycle, the framework improves the flexibility and adaptability of software artifact, which makes a stable foundation for higher quality product.
Contributions of short selling : A qualitative study of short selling on the Swedish stock market

Since the subprime crises numerous articles examining short selling have been published, most of them present positive contributions of short selling to financial markets. Short selling, however, is continually a subject for criticism and mistrust. The critique presented by legislators, media and bankers are hard to back up with sufficient evidence according to the researchers in the field. There are assumptions that short selling contribute to increase financial crisis, short selling is also a subject to ethical questioning. The research question of this thesis is “how does short selling affect the Swedish stock market? ” with the purpose to examine the positive and negative contributions of short selling, to generate an understanding to why it exist different perspectives regarding short selling.This is a bachelor thesis written by two students at Umea School of Business and Economics. The epistemological view of this thesis is interpretivism and the ontological standpoint is constructionism. By having this view the authors have drawn their conclusions based on existing studies. By identifying a set of factors that are needed to create an understanding about the negative and positive contributions of short selling, a theoretical framework was gathered and analyzed. After the analysis the authors conducted five in-depth interviews to get the views from respondents with a close connection to short selling. Analyzing the respondent’s answers with the theoretical framework the authors developed an understanding covering positive and negative contributions of short selling.The conclusions made in this paper are that short selling overall is positive for financial market by arguing reductio ad absurdum. The author’s conclusion is that short sales strengthen the Swedish financial market in the long run by increasing market efficiency, liquidity and stability. Hence the critique against short selling are in most cases unjustified and based on lack of knowledge. Furthermore the authors of this thesis, based on the conducted interviews, argue that the conclusion can be a foundation for authorities in Sweden for future legislations. The conclusion is that the legislations overall is useful since they aim to prevent market abuse and gives security to the financial market. However, the authors have found indications showing that the disclosure requirement today is misallocating resources. Therefore the authors recommend that the Swedish Financial Supervisory Authority should investigate how much the disclosure actually is contributing to the market efficiency in Sweden. Furthermore, the authorities should develop a solution solving the problems regarding market abuse without restricting short selling.
Representations Of And Strategies For Static Information, Noncooperative Games With Imperfect Inform

In this thesis, we will examine a card game called MYST, a variant of the Parker Brothers' classic board game Clue. In MYST, a set of cards is divided uniformly among a set of players, and the remaining cards form a hidden pile. The goal of each player is to be the rst to determine the contents of the hidden pile. On their turn, a player asks a question about the holdings of the other players, and, through a process of elimination, a player can determine the contents of the hidden pile. MYST is one of few static information games, wherein the position does not change during the course of the game. To do well, players need to reason about their opponents' holdings over the course of multiple turns, and therefore a sound representation of knowledge is required. MYST is an interesting game for AI because it ties elements of knowledge representation to game theory and game strategy. After informally introducing the essential elements of the game, we will o er a formal speci cation of the game in terms of rst-order logic and the situation calculus developed by Levesque et al. Strategies will be discussed including: existence of a winning strategy, randomized strategies, and blu ng. Implementation of some strategies will be discussed. iii Acknowledgments I would like to acknowledge the support of NSERC for money, Simon Fraser University for accepting me into the program, Jim Delgrande for money and for being helpfully skeptic, Oliver Schulte for insights on game theory, and Peter Gvozdjak and Petr Kubon for their LATEX help. Their support was instrumental to the existence of this thesis. iv
Convergence of Power Control Algorithms for Wireless Networks with and without Fading

This paper presents a geometric analysis of the convergence condition for the Foschini-Miljanic power control algorithm with and without fading. In the fading case, a condition on the Lyapunov exponent is provided as the convergence condition. The Möbius transform is exploited for the first time to analyze the convergence conditions for both non-fading and fading cases. For the two-transmitter case, it reveals the connection between the eigenvalue condition of the non-fading case and the Lyapunov exponent condition of the fading case. An analysis of the power levels in linear networks is provided and applied to cognitive radio networks. The peak power constraint of wireless networks is also analyzed theoretically, and applications to random networks are explored in detail. Numerical studies confirm the accuracy of our results.
Agricultural and Resource Policy: Principles and Practice

Introduction. Part 1 - Policy Analysis Framework. 1: Governing the Farm: economic efficiency foundations. 2: Farming the Government? : economic analyses of the policy process. 3: Cultivating Power: institutions of Australian agricultural and resource policy. Part II - Intrasectoral Issues: Input and Product Markets. 4: Farm inputs - water and externalities. 5: Research and Development. 6: Agricultural Marketing: general issues. 7: Agricultural marketing Policy - case studies: wheat, wool, sugar. 8: Marketing Issues- value adding and food safety. Part III - Intrasectoral Issues: Structural Change. 9: Structural Adjustment - European farming. 10: Structural Adjustment-Aborigines in the rural sector. 11: Rural Services. Part IV - Intersectoral Issues. 12: Agriculture in an Economy-Wide Context. 13: Differential Sectoral Rates of Protection. 14: Microeconomic Reform
Source and Destination Antenna Selection in MIMO Relay Systems

The antenna selection technique balances the performance and hardware cost in the multiple-input multiple-output (MIMO) systems, and the problems on the antenna selection in MIMO relay systems have not been fully solved. We consider antenna selection at the source and destination in the amplify-and-forward (AF) MIMO relay systems to maximize capacity. We proposed two fast antenna selection algorithms for the source and destination respectively. These algorithms are based on the properties of matrix determinants and inversions, and have lower complexity than the optimal algorithm. Simulation results show that the proposed algorithms achieve comparable performance to the optimal algorithm under various conditions.
Ipsilateral shoulder pain after thoracic surgery procedures under general and regional anesthesia – a retrospective observational study

Background Ipsilateral shoulder pain (ISP) is a common complication of mixed etiology after thoracic surgery (its prevalence is estimated in the literature at between 42% and 97%). It is severe and resistant to treatment (patients complain of pain despite effective epidural analgesia at the surgical site). Aim of the study The aim of this retrospective, observational study was to evaluate the prevalence of ISP in patients operated on in our facility and to determine the risk factors for ISP development. Material and methods 68 patients after thoracotomy or videothoracoscopy (video-assisted thoracic surgery – VATS) conducted under general and regional anesthesia were enrolled in the study and divided into two groups: group I without ISP and group II with postoperative ISP. We recorded age, sex, BMI, duration of surgery, type of surgery, type of regional anesthesia, and, in patients with epidural anesthesia, level of catheter placement. Results Statistically significant differences between the groups were obtained for BMI (24.67 and 27.68, respectively; p = 0.049), type of surgery (24% for thoracotomy and 0% for VATS, p = 0.026), and level of epidural catheter placement (4.35% for catheters placed at the level of Th5 or higher and 40.47% for catheters placed below Th5; p = 0.003). Conclusions The prevalence of ISP in our medical center amounts to 24% of thoracotomy patients. The fact that the difference in ISP prevalence was significantly related to the level of epidural catheter placement is consistent with the theory that ISP is related to phrenic nerve innervation. Moreover, epidural catheter placement is a modifiable factor, which can be used to reduce the prevalence of post-thoracotomy ISP.
Crime Risk Evaluation in Individual's Local Community

Our everyday lives involve navigating in the public space. If the public space is not safe it will reduce our freedom of movement and ability to participate in school, work and public life. Awareness on the level of security and danger in our public space can help us prepare and secure the area around us. But the lack of boundaries of public space makes it difficult to assess the level of safety and designing of security. The theory suggest (Creating Defensible Space by Oscar Newman, 1976) that the more personal and individualize the space we have, the more control and influence we have of defending it. Based on this theory, we are proposing a new sociological term called "Individual's Local Community (ILC)", which addresses on the unique environment of each individual navigating the public space. ILC is designed as the smallest measurable unit crossover local communities. ILC will personalize each individual's navigation to the public space. To measure the level of danger and safety in ILC we developed an android-based mobile application that estimate the risk of being victimize of crime in specified space and time-period. To extend the concept, one resident's risk to become victim or perpetrators of crime incidents is evaluated by estimated values based on "stable" ILC and historical crime records. The evaluation system is developed as a mobile app, named as "Are You Safe". The application contains local crime maps and a GPS tracking component. Mathematical formulas are developed to evaluate the potential risk. Furthermore, a re-routing function is provided for "safer" ILC. The prototype of "Are You Safe" app is implemented and tested in the city of northwestern Pennsylvania, United States. We believe the ILC concept will enrich the study of Personal Big Data and enable us to study social science in a different level. Also the app will help residents to have a better understanding on the safety and security of their environment.
Applying Media Richness Theory to Essay Writing Instruction - A Case of an Elementary School

Essay standards are generally determined by teachers' subjective opinions. The tacit knowledge requires choosing correct type of communication media and picking a suitable knowledge transfer mechanism. Therefore, the purpose of this study is to reduce the subjectively in feedback to student essays. The quasi-experimental method is used. The result shows that teaching strategies in writing can enhance student's learning outcomes. With the strategy of information feedback, writing effectiveness is more significant.