Miracle-dz/UniFAR-FTUs huggingface dataset:
Practical Quantum Fingerprinting and Appointment Scheduling

Quantum protocols for many communication tasks have been found which significantly improve on their classical counterparts. However, many of these protocols are beyond the reach of current technology. In this work, we find more readily implementable protocols for the tasks of quantum fingerprinting and appointment scheduling. Our protocols maintain a quantum advantage even under realistic experimental imperfections. In the task of quantum fingerprinting, two parties wish to evaluate the equality function on two n-bit strings in the simultaneous message passing model. The original quantum fingerprinting protocol uses a tensor product of a small number of O(logn)-qubit highly entangled signals [14], whereas a recently-proposed optical protocol uses a tensor product of O(n) single-qubit signals, while maintaining theO(logn) information leakage of the original protocol [4]. The lowdimensionality of each signal in the recently proposed optical protocol makes it more amenable to experimental implementation [68, 32], but due to limited coherence times the large number of signals remains a significant barrier to observing a quantum advantage in information leakage. In contrast, the original protocol sends few signals, but the dimension of each signal is prohibitively high. We find a family of protocols which interpolate between the original and optical protocols while maintaining the O(logn) information leakage, thus demonstrating a trade-off between the number of signals sent and the dimension of each signal, and opening the door for experimental implementations to find a “sweet spot” for which the number of signals sent and the dimension of each signal are both amenable to current technology. In [68, 32] the recently proposed optical protocol is implemented using coherent states. We develop a coherent state protocol which reduces the number of signals by a factor 1/2 from the recently proposed optical protocol, while also reducing the information leakage. We consider several natural generalizations of this protocol to other coherent state protocols which further reduce the number of signals, but find numerical evidence that they have greater information leakage in the ideal setting and also under realistic experimental imperfections. Using a similar technique, we improve a recently proposed coherent state protocol for evaluating the Euclidean distance between two real unit vectors [41] by reducing the number of signals by a factor 1/2 while also reducing the information leakage. We also extend this protocol to handle complex unit vectors. Along the way, we find a simple beamsplitter measurement to perform optimal unambiguous state comparison between two coherent states. In the task of appointment scheduling, two parties each have n-bit strings, and they wish to find a common intersection in the interactive communication model. The known quantum appointment scheduling protocol of [15] performs this task with O( √ n logn) qubits of communication, a nearly quadratic improvement over the classical lower bound of Ω(n) bits [39]. However,
ERP Software Selection Model for Small and Medium-Sized in Retail Sector Using Analytic Network Process

Small and medium sized (SME) retailers strive to maintain the balance of demand and supply in their stores. By maintaining the availability of items, they able to provide positive shopping experience for customers. Therefore, they are able to survive in a competition with large retailers. The technological advances and the shopping behavior are among the factors that encourage SME retailers to adopt the technology information system for supports information between business functions to keep the balance of supply, demand and their distribution. One of the many ways to maintain balance of demand and supply is by implementing Enterprise Resource Planning (ERP) (). However, ERP is quite difficult for SME retailers to be implemented in their organization. Selecting the optimal ERP software is a critical process in the early phase of an ERP project. This study aimed to investigating the priority (preference) of the criteria and alternatives using the Analytic Network Process (ANP) approach for the small and medium-sized retailers focusing in Jakarta. This study conducted by observation and interviews with the experts who have experience with ERP and small and medium-sized retailers. In this study, the pairwise comparisons used to assess the proposed alternatives and criteria. Furthermore, this study also calculates the overall score of the criteria and alternatives for analyzing the relation and preference of the criteria and alternatives. The theory of ANP used to evaluate all criteria and alternatives with expressed numerically. The findings of this study provide an overview that small and medium-sized retail companies tend to require systems or ERP software. In this study, there are 5 criteria most preferred: ease of customization, technical aspects, functionality and compatibility with other systems, and software prices. These criteria are considered to ensure the good operational activities. The most preferred alternative is SAP Business One, as it scored highest on several criteria, Odoo and Acumatica. The limitation of this study is that this study only used three ERP software programs as alternatives and this study focuses only for the small and medium-sized retailers in Jakarta.
Taxonomy of the genus Scrophularia (Scrophulariaceae) in Korea

Inter-specific relationships among six species and two varieties, belonging to Scrophularia (Scrophulariaceae), in Korea were re-examined based on both morphological and molecular data. Scrophularia takesimensis, a Korean endemic species, should be separated from S. grayana as an independent species based upon unique morphological characters such as non-winged stems, thickened leaves and glabrous surfaces of leaves, even though they share a lot of other features. It was found that S. grayana is distributed in Sokcho in Korea and along the coast of the East Sea north to far eastern Russia. Although some morphologies of three taxa, S. cephalantha, S. koraiensis var. velutina and S. kakudensis var. microphylla appeared to differ from each other, their ITS DNA sequence data was similar to that of S. kakudensis, suggesting that they might better be designated with the later species. The taxonomic position of S. koraiensis, only found in Korea, has been ambiguous, but ITS DNA sequence data in this study revealed that this species is distinct from S. kakudensis. Consequently, we conclude that the genus Scrophularia in Korea includes five species.
Detecting Different Attack Instances of DDoS Vulnerabilities on Edge Network of Fog Computing using Gaussian Naive Bayesian Classifier

Fog computing generally uses the host's resources instead of acquiring resources from remote PC leading to less latency problems and moreover, improving the performance which makes it more competent. Distributed denials of service (DDOS) attack exhausts the existing resources which make the services inaccessible to genuine users. DDoS has deep impact on the computer networks. As a cyber-threat, it compromises the standard performance of the organization by Internet protocol (IP) spoofing, overflow of bandwidth, memory space consumption and leading to immense loss. DoS attacks are a great threat to computerized association. Primary objective of any defense system for DoS is knowledge that it exists, preferably as early prior to accumulation of attack traffic. In case of large traffic inflow to an attacked server, it is essential to categorize the legitimate acquisitions and intrusions. In this work, the authors present a model that draws out the key parameters from requests in traffic for DDoS attack recognition in fog network. It benefits from existing data, and presents competent algorithms to detect and predict most probable cases. Authors have used Bayesian Network to calculate the conditional probabilities to decide whether the new packet is normal or intruded. A log of the path of the attacker is maintained in a VHD so as to easily detect attacks that have previously occurred. Having both the systems in place, the false positives of DDoS attacks detection have decreased immensely which has been observed through the implementation of this experiment.
Imputing Various Incomplete Attributes via Distance Likelihood Maximization

Missing values may appear in various attributes. By "various", we mean (1) different types of values in a tuple, such as numerical or categorical, and (2) different attributes in a tuple, either the dependent or determinant attributes of regression models or dependency rules. Such varieties unfortunately prevent the imputation performing. In this paper, we propose to study the distance models that predict distances between tuples for missing data imputation. The immediate benefits are in two aspects, (1) uniformly processing and collaboratively utilizing the distances on all the attributes with various types of values, and (2) rather than enumerating the combinations of imputation candidates on various attributes, we can directly calculate the most likely distances of missing values to other complete ones and thus infer the corresponding imputations. Our major technical highlights include (1) introducing the imputation statistically explainable by the likelihood on distances, (2) proving NP-hardness of finding the maximum likelihood imputation, and (3) devising the approximation algorithm with performance guarantees. Experiments over datasets with real missing values demonstrate the superiority of the proposed method compared to 11 existing approaches in 5 categories. Our proposal improves not only the imputation accuracy but also the downstream applications such as classification, clustering and record matching.
Review of drug indications for proton pump inhibitors among hospitalized patients in King Fahd Hospital, Alkobar, Saudi Arabia

Proton pump inhibitors (PPIs) are among the most commonly prescribed medications worldwide. Irrational use of PPIs is a common practice among hospitalized patients. The major objective of this study was to determine the appropriateness of indications of PPIs among hospitalized patients in King Fahd Hospital, Al Khobar, Saudi Arabia. A cross-sectional study was conducted at King Fahd Hospital, during December 2018 to March 2019. All adult patients admitted to the Medical and Surgical Departments were eligible. Data was collected from each patient’s medical record using a structured - data collection form. Assessment of the appropriateness of PPIs indications was performed based on standardized criteria. Descriptive statistics were used to describe all variables. Regression models were performed to identify the determinants of inappropriateness of PPIs indication. A p-value less than 0.05 was considered as statistically significant. Overall, a total of 181 patients was included, of them 96 (53%) were males. Patients aged > 65 years were 47 (26%). Out of all patients PPIs was prescribed as prophylactic therapy for 163 (90.1%) and for 18 (9.9%) as treatment. For 128 (70.7%) patients PPIs was inappropriately indicated. Multiple logistic regression analysis showed that, age more than 65 years [AOR 8.36 (3.82 - 18.3), (P
Hennig's Parasitological Method: A Proposed Solution

Brooks, D. R. (Department of Zoology, University of British Columbia, 2075 Wesbrook Mall, Vancouver, B.C., Canada V6T 2A9) 1981. Hennig's parasitological method: a proposed solution. Syst. Zool. , 30:229-249. -A quantitative solution for Hennig's parasitological method is presented. Cladograms summarizing natural relationships among parasite taxa are converted into host-group characters by means of additive binary coding. Unrooted Wagner analysis followed by most parsimonious rooting produces a maximum information-content representation of natural host-parasite relationships. Because host-parasite relationships result either from random colonization or from co-speciation, host relationships well corroborated by a multi-parasite analysis correspond to host phylogeny. Poorly corroborated host relationships indicate an ambiguous parasite message alerting a worker to possible host transfers. Thus, such analyses point out co-speciation and random colonization components of host-parasite systems. Single or multiple parasite taxa may be used. A host phylogeny based on non-parasite characters is neither necessary nor sufficient for studying phylogenetic aspects of coevolution, although such may be helpful in testing ambiguous aspects. Once a host-group cladogram based on parasites has been established, phylogenetic interpretations for each observed host-parasite relationship may be made according to a listed set of necessary and sufficient criteria. Finally, evaluation of two models of coevolution, a "vicariance" model and the "resource-tracking" model, indicates that the latter cannot be extrapolated successfully to explain congruent phylogenetic differentiation of hosts and parasites and that the former model represents the general pattern of natural relationships among hosts and parasites. [Cladistics; coevolution; phylogeny; quantitative systematics. ]
Continuity and change: Transformations in the urban history of Phnom Penh, Cambodia

In simple terms, transformation is the process that occurs when something changes from one state to another. Irrespective of the definitional nuances in urban and rural research, there is consensus that such events are complex and ongoing. To disentangle the factors and drivers from the outcomes and features, this paper’s conceptual ap-proach differentiates between the transitional process, or the “flow”, and the “status”, which refers to the existing state of affairs at a specific time in the past. My historical analysis, however, in the guise of snapshots, presents several in-between stages in Phnom Penh’s urban development status with particular reference to its urban mor-phology. This angle prioritizes long-term historical and slowly evolving structures also they advancing traditional to societies”
Comprehensive Analysis of Energy Efficiency Schemes in the Internet of Things

Internet of things (IoT) is an innovative technology that has gained significant research attention in recent years and is still gaining momentum. This technology permits communication between humans and objects or objects with objects to collect and exchange data as well as provide essential services. However, despite the benefits and services it offers, it is faced with several challenges that are dominated by inefficient energy utilization due to nodes' continuous communication and other issues. This challenge affects all existing low power wide area network (LPWAN) technologies such as SigFox, LoRa, Narrow-band IoT (NB-IoT), and so on. Accordingly, several solutions have been offered to address the challenge but yet to achieve an optimum solution. Therefore, this paper conducted a review of existing approaches to minimize energy utilization and high latency during transmission in the NB-IoT and IoT in general. The essence is to comprehend the different techniques, challenges, and technologies used. The analysis revealed the existence of schemes/algorithms which are routing based, sleep/wake, and others. It also shows that NB-IoT is still faced with the challenge of an increase in latency and high energy consumption. Thus, there a need to address the challenge to boost the smooth operation of the technology.
Detecting abuses in archaeological areas using k-mean clustering analysis and UAVs/drones data

In recent years, new technologies in archaeology have emerged to get reliable data easily and at a lower cost. Unmanned aerial vehicles (UAVs) or drones have become advanced technological devices that archaeologists use and aim to add to their survey and gravure kits. Drones used for 3D documentation and analysis of landmarks and historical structures, aerial mapping, and forest archaeological analysis. Drones used now instead of the conventional field walking approach known as the pedestrian survey, which was historically used by archaeologists and archaeology students (Hill, Laugier & Casana, 2020). While satellite imagery offers wider coverage for any surveys (Bi, 2020), but at considerable expense and with little spatial precision compared to the cost and precision of drones’ spatial discrimination, which flies at a relatively low altitude, providing a precise view of the archaeological region being surveyed. Satellite images vary in their spatial resolution and by the satellite used, which means they can cover an area of one kilometer per pixel in the image, or hundreds of meters, or at best tens of meters per pixel. This little precision has limited applications to uncover archaeologist’s tiny archaeological features. Though these satellite images can be obtained free of charge, such as the satellite launched by the European Space Agency called Sentinel, which provides excellent spectral bands with a spatial accuracy of 10 m per pixel, it is not considered effective in the study of often small monuments and archaeological areas (Noor, Abdullah & Hashim, 2018). In addition to restrictions on the use of satellites such as the large height of the satellites and the distance between the satellites and the earth, this means that the emission signal entering the senScientific Review – Engineering and Environmental Sciences (2021), 30 (1), 182–194 Sci. Rev. Eng. Env. Sci. (2021), 30 (1) Przegląd Naukowy – Inżynieria i Kształtowanie Środowiska (2021), 30 (1), 182–194 Prz. Nauk. Inż. Kszt. Środ. (2021), 30 (1) http://iks.pn. sggw.pl DOI 10.22630/PNIKS.2021. 30.1. 16
Probing the metallic energy spectrum beyond the Thouless energy scale using singular value decomposition

Disordered quantum systems feature an energy scale know as the Thouless energy. For energy ranges below this scale, the properties of the energy spectrum can be described by random matrix theory. Above this scale a different behavior sets in. For a metallic system it has been long ago shown by Altshuler and Shklovskii that the number variance should increase as a power law with a power dependent only on the dimensionality of the system. Although tantalizing hints for this behavior have been seen in previous numerical studies, it is quite difficult to verify this prediction using the standard local unfolding methods. Here we use a different unfolding method, i.e., the singular value decomposition, and establish a connection between the power law behavior of the scree plot (the singular values ranked by their amplitude) and the power law behavior of the number variance. Thus we are able to numerically verify the Altshuler and Shklovskii’s prediction for disordered 3D, 4D, and 5D single-electron Anderson models on square lattices in the metallic regime. The same method could be applied to systems such as the Sachdev-Ye-Kitaev model and various interacting many body models for which the many body localization occurs. It has been recently reported that such systems exhibit a Thouless energy and analyzing the spectrum’s behavior on larger scales is of much current interest.
The Benefit of Apparent Diffusion Coefficient in Evaluating the Invasiveness of Hepatocellular Carcinoma

Background This study aimed to evaluate hepatocellular carcinoma (HCC) invasiveness using the apparent diffusion coefficient (ADC). Methods Eighty-one patients with HCC confirmed by pathology and examined by preoperative magnetic resonance imaging diffusion-weighted imaging from January 2015 to September 2020 were retrospectively analyzed. Clinical and pathological data were recorded. The minimum ADC (ADCmin), average ADC (ADCmean), and the ratio of ADCmean to normal-appearing hepatic parenchyma ADC (ADCnahp) were assessed. The associations between clinical information, ADC value, and HCC invasiveness (microvascular invasion [MVI], tumor differentiation, and Ki-67 expression) were evaluated statistically. Independent risk factors related to HCC invasiveness were screened using binary logistic regression, and the diagnostic efficiency was evaluated by the receiver operating characteristic curve and its area under the curve (AUC) value. Results Tumor size was related to HCC MVI and tumor differentiation (P < 0.05). HCC MVI was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P < 0.05) with AUC values of 0.860, 0.860, and 0.909, respectively. If these were combined with tumor size, the AUC value increased to 0.912. The degree of tumor differentiation was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P < 0.05) with AUC values of 0.719, 0.708, and 0.797, respectively. If these were combined with tumor size, the AUC value increased to 0.868. Ki-67 expression was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P < 0.05) with AUC values of 0.731, 0.747, and 0.746, respectively. Combined them, the AUC value increased to 0.763. Conclusions The findings indicated that the ADC value has significant potential for the non-invasive preoperative evaluation of HCC invasiveness.
Rank estimation for (approximately) low-rank matrices

In observational data analysis, e.g., causal inference, one often encounters data sets that are noisy and incomplete, but come from inherently "low rank" (or correlated) systems. Examples include user ratings of movies/products and term frequency matrices for documents amongst others. In such analysis, estimating the approximate rank of the data sets serves an important function of delineating the signal from the noise. In this paper, we propose a technique to estimate the rank of observational data matrices, compare it to previously proposed techniques, and make a specific methodological contribution of improving the algorithmic parameter estimation in the robust synthetic control method in [1].