Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Affecting Non-Teaching Staff Development in Kenyan Universities

The study was carried out to investigate the factors that affect non-teaching staff development in campuses of Kenyan universities. In light of theoretical literature reviewed and empirical studies related to employee development, the research focused on the five sub-variables considered in this study, namely work environment facilities available, technology development, staff training and development, policies and work systems (infrastructure) and number of non-teaching staff working in campuses. Literature review was conducted to identify what other researchers have done in the areas of staff development and open to further understanding of their precious contribution to this area of study. The research study was carried out in Mt. Kenya region. Out of sixteen campuses in Mt. Kenya region four were randomly selected. A cross-section survey random sampling was used to select the population through of different cadre of middle level non-academic staff in various sections in the four campuses. A sample of 30 participants were used which is 20% of population study. Data was collected through questionnaires administered through drop and pick by the researcher and personal interview were conducted where possible. The Questionnaires were screened for completeness. Inferential statistics method was used to analyze the data collected. Data analysis, interpretation and presentation by use of tables, pie-charts and bar-graphs was done. Correlation analysis and hypothesis testing was done to test the strength of association of variables.
Design of High-$Q$ Millimeter-Wave Oscillator by Differential Transmission Line Loaded With Metamaterial Resonator in 65-nm CMOS

<? Pub Dtl? >In this paper, low phase-noise, low-power, and compact oscillators are demonstrated at the millimeter-wave region based on differential transmission lines (DTLs) loaded with metamaterial resonators. There are two types of metamaterial resonators explored: split-ring resonators (SRRs) and complementary split-ring resonators (CSRRs). By creating a sharp stopband at the resonance frequency from a loaded SRR or CSRR, the backward electrical-magnetic (EM) wave is reflected to couple with the forward EM wave to form a standing EM wave in the DTL host, which results in a high-<formula formulatype="inline"><tex Notation="TeX">$Q$</tex> </formula> and low-loss millimeter-wave resonator with stable EM energy stored. The resulting DTL-SRR and DTL-CSRR resonators are deployed for designs of millimeter-wave oscillators in 65-nm CMOS. The measurement results show that one DTL-SRR-based oscillator works at 76 GHz with power consumption of 2.7 mW, phase noise of <formula formulatype="inline"><tex Notation="TeX">$-{\hbox{108.8 dBc/Hz}}$</tex></formula> at 10-MHz offset, and figure-of-merit (FOM) of <formula formulatype="inline"><tex Notation="TeX">$-{\hbox{182.1 dBc/Hz}}$</tex></formula> , which is 4 dB better than that of a 76-GHz standing-wave oscillator implemented on the same chip. Moreover, another DTL-CSRR-based oscillator works at 96 GHz with power consumption of 7.5 mW. Compared to the existing oscillators with an LC-tank-based resonator, the DTL-CSRR oscillator has much lower phase noise of <formula formulatype="inline"> <tex Notation="TeX">$- {\hbox{111.5 dBc/Hz}}$</tex></formula> at 10-MHz offset and a FOM of <formula formulatype="inline"><tex Notation="TeX">$- {\hbox{182.4 dBc/Hz}}$</tex></formula>.
Querying Visible and Invisible Information

We provide a wide-ranging study of the scenario where a subset of the relations in the schema are visible — that is, their complete contents are known — while the remaining relations are invisible. We also have integrity constraints (invariants given by logical sentences) which may relate the visible relations to the invisible ones. We want to determine which information about a query (a positive existential sentence) can be inferred from the visible instance and the constraints. We consider both positive and negative query information, that is, whether the query or its negation holds. We consider the instance-level version of the problem, where both the query and the visible instance are given, as well as the schema-level version, where we want to know whether truth or falsity of the query can be inferred in some instance of the schema.
Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation

In the machine learning field, the performance of a classifier is usually measured in terms of prediction error. In most real-world problems, the error cannot be exactly calculated and it must be estimated. Therefore, it is important to choose an appropriate estimator of the error. This paper analyzes the statistical properties, bias and variance, of the k-fold cross-validation classification error estimator (k-cv). Our main contribution is a novel theoretical decomposition of the variance of the k-cv considering its sources of variance: sensitivity to changes in the training set and sensitivity to changes in the folds. The paper also compares the bias and variance of the estimator for different values of k. The experimental study has been performed in artificial domains because they allow the exact computation of the implied quantities and we can rigorously specify the conditions of experimentation. The experimentation has been performed for two classifiers (naive Bayes and nearest neighbor), different numbers of folds, sample sizes, and training sets coming from assorted probability distributions. We conclude by including some practical recommendation on the use of k-fold cross validation.
Determination of the Free Neutron Lifetime

We present the status of current US experimental efforts to measure the lifetime of the free neutron by the "beam" and "bottle" methods. BBN nucleosynthesis models require accurate measurements with 1 second uncertainties, which are currently feasible. For tests of physics beyond the standard model, future efforts will need to achieve uncertainties well below 1 second. We outline paths achieve both.
Logicality of ASP in healthcare: the NHS case study

Obtaining value from information technology (IT) is important for organizations to survive and flourish in the highly competitive economy of the 21/sup st/ century. Especially when that organization is the UK's National Health Service (NHS), to whom an heavy investment - for IT improvement - of $7 bn is being injected to cope with pressures exerted within a more demanding population with constantly evolving healthcare needs. This paper explores the emergence of primary service provision (PSP) from perspectives that span the macrolevel of national health policies, the mezzo level of local strategies and the microlevel of IT procurement. These interrelations are studied at a greater depth within case study using the NHS. PSP is used in this paper as a subset of the application provision service (ASP) business model. In healthcare, the study of technology implications cannot be removed from an understanding of the processes of conceptualising, conceiving and using such technology. The authors argue the risk of falling into the trap of technological determinism or considering the impacts as a result of rationally planned actions guiding implementation of technologies. This research has shown there are thousands of hospitals, most doing different business processes in different ways thereby presenting an impossible task of successfully implementing a complex national project consisting of electronic patient records and booking systems. This study of PSP processes does not clearly show how and by whom the meanings of PSP are created, whose interests are voiced and taken into account, what are the overriding aims expressed by ASP vendors and what ethical concerns guide these developments being spearheaded by the NHS information authority.
Augmented Reality-Based Tele-Robotic System Architecture for On-Site Construction

The planning of construction process is crucial for successful project management and based on which all other sub-tasks and activities follow. Labourintensive construction process which relies on field workers’ own intuition and interpretation, has been too complicated to control, which can lead to mistakes, wasted time, and fatal accidents in worst but commonly happening cases. In this sense, applying innovative techniques to on-site construction process for construction planning, scheduling, operation, and monitoring has the potential to assist stakeholders in making better decisions. A head-mounted display (HMD) such as Oculus Rift can visualize construction processes information anytime whether during on-site work or beforehand by providing realistic augmented superimposed environment which is captured via the proposed 2-DOF stereo head. Moreover, by calculating the physical movement (translation, rotation) of building components, which can be accomplished by reading physical, material property data from Building Information Modeling (BIM), and combining it with computational kinematics model of on-site robotic equipment, the field workers can have the digital information for off-site component assembly in real-time manner. This research develops a new methodology for integration of tele-operation with 4D modelling in order to improve building component positioning and erection in terms of efficiency and quality by operating onsite robotic system intelligently. Based on the proposed methodology, an intelligent remotely operated, considering the control and video streaming processes, virtual tele-presence system is prototyped. The proposed system is designed for tele-operated construction robots and comprises a 2DOF stereo head, a pair of high spatial resolution cameras, and a head mounted display with integrated head tracking mechanism. To validate the proposed methodology, controlled laboratory experiments were designed and implemented.
Seasonal variation of long-term potentiation at a central synapse in the medicinal leech

SUMMARY Long-term potentiation (LTP) is a persistent increase in synaptic transmission that is thought to contribute to a variety of adaptive processes including learning and memory. Although learning is known to undergo circannual variations, it is not known whether LTP undergoes similar changes despite the importance of LTP in learning and memory. Here we report that synapses in the CNS of the medicinal leech demonstrate seasonal variation in the capacity to undergo LTP following paired presynaptic and postsynaptic stimulation. LTP was observed during the April–October period, but no LTP was observed during the November–March period. Application of forskolin, a technique often used to produce chemical LTP, failed to elicit potentiation during the November–March period. Implementing stimulation patterns that normally result in long term depression (LTD) also failed to elicit any change in synaptic strength during the November–March period. These experiments indicate that LTP and LTD can be influenced by circannual rhythms and also suggest a seasonal influence on learning and memory.
Overnight Borrowing, Interest Rates and Extreme Value Theory

We examine the dynamics of extreme values of overnight borrowing rates in an inter-bank money market before a financial crisis during which overnight borrowing rates rocketed up to (simple annual) 4000 percent. It is shown that the generalized Pareto distribution fits well to the extreme values of the interest rate distribution. We also provide predictions of extreme overnight borrowing rates before the crisis. The examination of tails (extreme values) provides answers to such issues as what are the extreme movements expected in financial markets; have we already seen the largest moves; is there a possibility for even larger movements and, are there theoretical processes that can model the type of fat tails in the observed data? The answers to such questions are essential for proper management of financial exposures and laying ground for regulations.
Grammar-based whitebox fuzzing

Whitebox fuzzing is a form of automatic dynamic test generation, based on symbolic execution and constraint solving, designed for security testing of large applications. Unfortunately, the current effectiveness of whitebox fuzzing is limited when testing applications with highly-structured inputs, such as compilers and interpreters. These applications process their inputs in stages, such as lexing, parsing and evaluation. Due to the enormous number of control paths in early processing stages, whitebox fuzzing rarely reaches parts of the application beyond those first stages. In this paper, we study how to enhance whitebox fuzzing of complex structured-input applications with a grammar-based specification of their valid inputs. We present a novel dynamic test generation algorithm where symbolic execution directly generates grammar-based constraints whose satisfiability is checked using a custom grammar-based constraint solver. We have implemented this algorithm and evaluated it on a large security-critical application, the JavaScript interpreter of Internet Explorer 7 (IE7). Results of our experiments show that grammar-based whitebox fuzzing explores deeper program paths and avoids dead-ends due to non-parsable inputs. Compared to regular whitebox fuzzing, grammar-based whitebox fuzzing increased coverage of the code generation module of the IE7 JavaScript interpreter from 53% to 81% while using three times fewer tests.
Accurate and fast Dynamic Time Warping approximation using upper bounds

The purpose of Dynamic Time Warping (DTW) is to determine the shortest warp path, corresponding to the optimal alignment between two sequences. It is one of the most used methods for time series distance measure. DTW was introduced to the community as a Data Mining utility for various tasks for time series problems such as classification and clustering. Many variants of DTW aim to accelerate the calculation of this distance and others order to overcome the weakness points of DTW as the singularity problem. We propose a new approach called Dynamic Warping Window (DWW) for speeding up DTW algorithm based on upper bound. It gives an accurate approximation of DTW in linear time. It accelerates the calculation of DTW distance. Results show that the new approach provides a good compromise between accuracy of DTW approximation and the non-degradation of KNN classification results.
A framework for optimal repairing of vector field-based motion plans

This paper presents a framework that integrates vector field based motion planning techniques with an optimal path planner. The main motivation for this integration is the solution of UAVs' motion planning problems that are easily and intuitively solved using vector fields, but are very difficult to be even posed as optimal motion planning problems, mainly due to the lack of clear cost functions. Examples of such problems include the ones where a goal configuration is not defined, such as circulation of curves, loitering and road following. While several vector field methodologies were proposed to solve these tasks, they are susceptible to failures in the presence of previously unmodeled obstacles, including no-fly zones specified during the flight. Our framework uses a vector field as a high level specification of a task and an optimal motion planner (in our case RRT*) as a local, on-line planner that generates paths that follow the vector field, but also consider the new obstacles encountered by the vehicle during the flight. A series of simulations illustrate and validate the proposed methodology. One of these simulations considers a rotorcraft UAV equipped with a spinning laser patrolling an urban area in the presence of unmodeled obstacles and no-fly zones.
How Much Do Sociologists Write About Economic Topics? Using Big Data to Test Some Conventional Views in Economic Sociology, 1890 to 2014

Sociological self-understanding is that the frequency of economic topics in sociology has peaked twice: first during the classical era between 1890 and 1920 and second after Mark Granovetter's most cited 1985 article. This paper tests this established view using all JSTOR sociology articles from 1890 to 2014 (142,040 articles, 157 journals). Combined topic and multilevel modeling found strong evidence for the first peak but the proportion of economics topics has also been decreasing over the past century. The rise of a New Economic Sociology as a subdiscipline of sociology came with the increasing focus on general economic issues but also with a topic mix of organization and social-theory research. The paper shows that this specific topic mix began to increase from 1929 peaking by 1989 and suggests that the New Economic Sociology, rather than marking the beginning of a second peak, is more a product of the other general currents of organization sociology and social theory. The paper also finds that this subdiscipline is internally diverse in topics and rather male dominated.
Differences between pregnant women with secure and fearful attachment patterns with respect to transition to motherhood

This study investigated the possibility of discerning differences between attachment patterns of pregnant women in some mental processes during the transition to motherhood. Participants were 335 primiparae, examined between 20 and 32 weeks of pregnancy. The revised version of Questionnaire for Attachment Assessment (UPIPAV-R) was used for the assessment of seven attachment dimensions. Cluster analysis, k means method, was employed for determining the general attachment pattern of the participants. Four clusters were identified: secure, fearful, preoccupied and dismissing. Maternal prenatal attachment, her anxieties about the prospective maternal role and her possibly dysfunctional expectations about the role of the child in her private and family life were assessed using scales developed for the purpose of the research. The hypothesis about differences of attachment patterns in examined mental processes of preparation for motherhood was confirmed by the results of discriminant analysis. All dimensions of maternal prenatal attachment are central for discriminating secure from fearful attachment pattern. All dimensions of possibly dysfunctional expectations are central for discriminating preoccupied from dismissing attachment patterns. Anxiety related to loss of freedom and no self-realization in the mother role has significant contribution to discriminating secure from fearful attachment pattern. The other two dimensions of anxiety, related to the 'difficult baby' and incompetence in mother role, are important for discriminating dismissing from preoccupied attachment patterns.
The Dichotomy in Degree Correlation of Biological Networks

Most complex networks from different areas such as biology, sociology or technology, show a correlation on node degree where the possibility of a link between two nodes depends on their connectivity. It is widely believed that complex networks are either disassortative (links between hubs are systematically suppressed) or assortative (links between hubs are enhanced). In this paper, we analyze a variety of biological networks and find that they generally show a dichotomous degree correlation. We find that many properties of biological networks can be explained by this dichotomy in degree correlation, including the neighborhood connectivity, the sickle-shaped clustering coefficient distribution and the modularity structure. This dichotomy distinguishes biological networks from real disassortative networks or assortative networks such as the Internet and social networks. We suggest that the modular structure of networks accounts for the dichotomy in degree correlation and vice versa, shedding light on the source of modularity in biological networks. We further show that a robust and well connected network necessitates the dichotomy of degree correlation, suggestive of an evolutionary motivation for its existence. Finally, we suggest that a dichotomous degree correlation favors a centrally connected modular network, by which the integrity of network and specificity of modules might be reconciled.
Cybernetic models based on lumped elementary modes accurately predict strain‐specific metabolic function

In a recent article, Song and Ramkrishna (Song and Ramkrishna [2010]. Biotechnol Bioeng 106(2):271–284) proposed a lumped hybrid cybernetic model (L‐HCM) towards extracting maximum information about metabolic function from a minimum of data. This approach views the total uptake flux as distributed among lumped elementary modes (L‐EMs) so as to maximize a prescribed metabolic objective such as growth or uptake rate. L‐EM is computed as a weighted average of EMs where the weights are related to the yields of vital products (i.e., biomass and ATP). In this article, we further enhance the predictive power of L‐HCMs through modifications in lumping weights with additional parameters that can be tuned with data viewed to be critical. The resulting model is able to make predictions of diverse metabolic behaviors varying greatly with strain types as evidenced from case studies of anaerobic growth of various Escherichia coli strains. Incorporation of the new lumping formula into L‐HCM remarkably improves model predictions with a few critical data, thus presenting L‐HCM as a dynamic tool as being not only qualitatively correct but also quantitatively accurate. Biotechnol. Bioeng. 2011; 108:127–140. © 2010 Wiley Periodicals, Inc.
Convergence analysis of a segmentation algorithm for the evolutionary training of neural networks

In contrast to standard genetic algorithms with generational reproduction, we adopt the viewpoint of the reactor algorithm (Dittrich and Banzhaf, 1998) which is similar to steady-state genetic algorithms, but without ranking. This permits an analysis similar to Eigen's (1971) molecular evolution model. From this viewpoint, we consider combining segments from different populations into one genotype at every time-step, which can be regarded as many-parent combinations with fined crossover points, and is comparable to cooperative evolution (Potter and De Jong, 2000). We present fixed-point analysis and phase portraits of the competitive dynamics, with the result that only the first-order (single parent) replicators exhibit global optimisation. A segmentation algorithm is developed that theoretically ensures convergence to the global optimum while keeping the cooperative or reactor aspect for a better exploration of the search space. The algorithm creates different population islands for such cases of competition that otherwise cannot be solved correctly by the population dynamics. The population blends have different segmentation boundaries which are generated by combining well converged components into new segments. This gives first-order replicators that have the appropriate dynamical properties to compete with new solutions.
HitME: Low power Hit MEmory buffer for embedded systems

In this paper, we present a novel HitME (Hit-MEmory) buffer to reduce the energy consumption of memory hierarchy in embedded processors. The HitME buffer is a small direct-mapped cache memory that is added as additional memory into existing cache memory hierarchies. The HitME buffer is loaded only when there is a hit on L1 cache. Otherwise, L1 cache is updated from the memory and the processor's memory request is served directly from the L1 cache. The strategy works due to the fact that 90% of memory accesses are only accessed once, and these often pollute the cache. Energy reduction is achieved by reducing the number of accesses to the L1 cache memory. Experimental results show that the use of HitME buffer will reduce the L1 cache accesses resulting in a reduction in the energy consumption of the memory hierarchy. This decrease in L1 cache accesses reduces the cache system energy consumption by an average of 60.9% when compared to traditional L1 cache memory architecture and an energy reduction of 6.4% when compared to filter cache architecture for 70nm cache technology.